Supplementary appendix

This appendix formed part of the original submission and has been peer reviewed.
We post it as supplied by the authors.

Supplement to: Ding D, Nguyen B, Nau T, et al. Daily steps and health outcomes in
adults: a systematic review and dose-response meta-analysis. Lancet Public Health
2025; published online July 23. https://doi.org/10.1016/S2468-2667(25)00164-1.
Supplementary materials
Supplementary materials ......................................................................................... 1
Supplementary File 1a. PRISMA checklist ............................................................... 3
Supplementary File 1b. PRISMA abstract checklist .................................................. 6
Supplementary File 1c. MOOSE checklist for Meta-analyses of Observational Studies
........................................................................................................................... 7
Supplementary File 2. Search strategies ................................................................. 9
Supplementary Table 1. Characteristics of included studies by outcome ................ 17
Supplementary Table 2. Individual study results by outcome ................................. 41
Supplementary Table 3. Device characteristics ..................................................... 52
Supplementary Table 4. Covariates included in the most adjusted multivariable
analysis model of each included study ................................................................. 58
Supplementary Table 5. Funding sources of included studies ................................ 63
Supplementary Table 6. List of excluded studies and reasons for exclusion ............ 69
Supplementary Table 7. Risk of bias assessment .................................................. 73
Supplementary Table 8. A summary of the pooled hazard ratios (HR) and 95%
confidence interval (CI) for 1000-step increments in the meta-analyses (with 7,000
steps/day as the reference) ................................................................................. 82
Supplementary Table 9. Studies on cadence ........................................................ 83
Supplementary Table 10. Bayesian Information Criterion (BIC) statistics for each
model ................................................................................................................ 89
Supplementary Figure 1. PRISMA flow chart for all-cause mortality ........................ 90
Supplementary Figure 2. PRISMA flow chart for cardiovascular disease .................. 91
Supplementary Figure 3. PRISMA flow chart for cancer .......................................... 92
Supplementary Figure 4. PRISMA flow chart for type 2 diabetes incidence .............. 93
Supplementary Figure 5. PRISMA flow chart for cognition ...................................... 94
Supplementary Figure 6. PRISMA flow chart for mental health ............................... 95
Supplementary Figure 7. PRISMA flow chart for physical function .......................... 96
Supplementary Figure 8. PRISMA flow chart for falls and falls-related injuries ......... 97
Supplementary Figures 9-13. Subgroup analyses .................................................. 98
Supplementary Figures14-19. Sensitivity analyses 1-3 ......................................... 101

1
Supplementary Figures 20-26. Sensitivity analyses 4: Leave-one-out analysis ...... 107
Supplementary Figure 27. Funnel plot for all-cause mortality............................... 111
Supplementary Figures 28-29 cadence meta-analyses........................................ 112

2
Supplementary File 1a. PRISMA checklist
Location
Section and Item
Checklist item where item is
Topic #
reported
TITLE
Title 1 Identify the report as a systematic review. Page (P) 1
ABSTRACT
Abstract 2 See the PRISMA 2020 for Abstracts checklist. Supplementary
File 1b
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of existing knowledge. P6, 8
Objectives 4 Provide an explicit statement of the objective(s) or question(s) the review addresses. P6, 9
METHODS
Eligibility criteria 5 Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. P10, 11-13
Information 6 Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify P9-10,
sources the date when each source was last searched or consulted. Supplementary
File 2
Search strategy 7 Present the full search strategies for all databases, registers and websites, including any filters and limits used. Supplementary
File 2
Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each P10
record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.
Data collection 9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked P11
process independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in
the process.
Data items 10a List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each P11,
study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect. Supplementary
Tables 1, 2
10b List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any P11,
assumptions made about any missing or unclear information. Supplementary
Tables 1, 3-5
Study risk of bias 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed P11
assessment each study and whether they worked independently, and if applicable, details of automation tools used in the process.
Effect measures 12 Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results. P12-13
Synthesis 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics P11-12
methods and comparing against the planned groups for each synthesis (item #5)).
13b Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data P12
conversions.

3
 Location
Section and Item
Checklist item where item is
Topic #
reported
13c Describe any methods used to tabulate or visually display results of individual studies and syntheses. P11
13d Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the P11-13
model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.
13e Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression). P12-13
13f Describe any sensitivity analyses conducted to assess robustness of the synthesized results. P13
Reporting bias 14 Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). P14
assessment
Certainty 15 Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. P13
assessment
RESULTS
Study selection 16a Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included P14,
in the review, ideally using a flow diagram. Supplementary
Figures 1-8
16b Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded. Supplementary
Table 6
Study 17 Cite each included study and present its characteristics. P14, Table 1,
characteristics Supplementary
Table 1
Risk of bias in 18 Present assessments of risk of bias for each included study. Supplementary
studies Table 7
Results of 19 For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its Supplementary
individual studies precision (e.g. confidence/credible interval), ideally using structured tables or plots. Tables 2, 9
Results of 20a For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies. P15-18,
syntheses Supplementary
Tables 2, 7, 9
20b Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision P15-19, Fig 1,
(e.g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect. Table 2,
Supplementary
Table 8,
Supplementary
Figures 27-28
20c Present results of all investigations of possible causes of heterogeneity among study results. P15-19,
Supplementary
Figures 9-13
20d Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results. P15-19,
Supplementary
Figures 14-25

4
 Location
Section and Item
Checklist item where item is
Topic #
reported
Reporting biases 21 Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed. P19-20,
Supplementary
Figure 26
Certainty of 22 Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed. P20, Table 3
evidence
DISCUSSION
Discussion 23a Provide a general interpretation of the results in the context of other evidence. P20-22
23b Discuss any limitations of the evidence included in the review. P22-23
23c Discuss any limitations of the review processes used. P22
23d Discuss implications of the results for practice, policy, and future research. P23
OTHER INFORMATION
Registration and 24a Provide registration information for the review, including register name and registration number, or state that the review was not registered. P5, 9
protocol
24b Indicate where the review protocol can be accessed, or state that a protocol was not prepared. P5, 9
24c Describe and explain any amendments to information provided at registration or in the protocol. N/A
Support 25 Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review. P14, 24
Competing 26 Declare any competing interests of review authors. P24-25
interests
Availability of 27 Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included P25.
data, code and studies; data used for all analyses; analytic code; any other materials used in the review. Supplementary
other materials Tables 1-5, 9

From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71

5
Supplementary File 1b. PRISMA abstract checklist
Item Reported
Section and Topic Checklist item
# (Yes/No)
TITLE
Title 1 Identify the report as a systematic review. Yes
BACKGROUND
Objectives 2 Provide an explicit statement of the main objective(s) or question(s) the review addresses. Yes
METHODS
Eligibility criteria 3 Specify the inclusion and exclusion criteria for the review. Yes
Information sources 4 Specify the information sources (e.g. databases, registers) used to identify studies and the date when each Yes
was last searched.
Risk of bias 5 Specify the methods used to assess risk of bias in the included studies. Yes
Synthesis of results 6 Specify the methods used to present and synthesise results. Yes
RESULTS
Included studies 7 Give the total number of included studies and participants and summarise relevant characteristics of studies. Yes
Synthesis of results 8 Present results for main outcomes, preferably indicating the number of included studies and participants for Yes
each. If meta-analysis was done, report the summary estimate and confidence/credible interval. If comparing
groups, indicate the direction of the effect (i.e. which group is favoured).
DISCUSSION
Limitations of evidence 9 Provide a brief summary of the limitations of the evidence included in the review (e.g. study risk of bias, Yes
inconsistency and imprecision).
Interpretation 10 Provide a general interpretation of the results and important implications. Yes
OTHER
Funding 11 Specify the primary source of funding for the review. Yes
Registration 12 Provide the register name and registration number. Yes

From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.
BMJ 2021;372:n71. doi: 10.1136/bmj.n71

6
 Supplementary File 1c. MOOSE checklist for Meta-analyses of
Observational Studies
Reported on
Item No Recommendation
Page No
Reporting of background should include
1 Problem definition 8
2 Hypothesis statement N/A
3 Description of study outcome(s) 9
4 Type of exposure or intervention used 9
5 Type of study designs used 9-10
6 Study population 10

Reporting of search strategy should include

7 Qualifications of searchers (eg, librarians and investigators) 1, 24

9-10,
Search strategy, including time period included in the synthesis and key
8 Supplementary
words
File 2
10,
9 Effort to include all available studies, including contact with authors Supplementary
Figures 1-8
9-10,
10 Databases and registries searched Supplementary
File 2
9,
Search software used, name and version, including special features used
11 Supplementary
(eg, explosion)
File 2
12 Use of hand searching (eg, reference lists of obtained articles) 10
Supplementary
13 List of citations located and those excluded, including justification
Table 6
14 Method of addressing articles published in languages other than English 10
15 Method of handling abstracts and unpublished studies 10
16 Description of any contact with authors 11
Reporting of methods should include
Description of relevance or appropriateness of studies assembled for
17 10-11, 13
assessing the hypothesis to be tested
Rationale for the selection and coding of data (eg, sound clinical principles or
18 11
convenience)
Documentation of how data were classified and coded (eg, multiple raters,
19 11
blinding and interrater reliability)
Assessment of confounding (eg, comparability of cases and controls in
20 11
studies where appropriate)
Assessment of study quality, including blinding of quality assessors,
21 11
stratification or regression on possible predictors of study results
22 Assessment of heterogeneity 12-13
Description of statistical methods (eg, complete description of fixed or
random effects models, justification of whether the chosen models account
23 11-13
for predictors of study results, dose-response models, or cumulative meta-
analysis) in sufficient detail to be replicated

7
 Tables 1-3,
Figure 1,
Supplementary
24 Provision of appropriate tables and graphics
Tables 1-9,
Supplementary
Figures 1-28
Reporting of results should include
Figure 1,
25 Graphic summarizing individual study estimates and overall estimate Supplementary
Figures 27-28
Supplementary
26 Table giving descriptive information for each study included
Tables 1-3
27 Results of sensitivity testing (eg, subgroup analysis) 15-19
15-19, Figure
1,
28 Indication of statistical uncertainty of findings
Supplementary
Figures 27-28
Reporting of discussion should include
29 Quantitative assessment of bias (eg, publication bias) 13-14, 19-20
10-11,
30 Justification for exclusion (eg, exclusion of non-English language citations) Supplementary
Table 6
31 Assessment of quality of included studies 15, 23
Reporting of conclusions should include
32 Consideration of alternative explanations for observed results 21-22
Generalization of the conclusions (ie, appropriate for the data presented and
33 20-23
within the domain of the literature review)
34 Guidelines for future research 7, 23
35 Disclosure of funding source 5, 14, 24

From: Stroup DF, Berlin JA, Morton SC, et al, for the Meta-analysis Of Observational Studies in Epidemiology
(MOOSE) Group. Meta-analysis of Observational Studies in Epidemiology. A Proposal for Reporting. JAMA.
2000;283(15):2008-2012. doi: 10.1001/jama.283.15.2008.

8
Supplementary File 2. Search strategies
Step counts and all-cause mortality
Searches conducted on 22/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Mortality AND (“death”[mh] OR “death”[tiab] OR “dying”[tiab] OR
fatal*[tiab] OR mortalit*[tiab] OR “mortality”[mh] OR
“postmortem”[tiab])
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

CINAHL: Terms searched in title or abstract

Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Mortality AND (“death” OR “dying” OR fatal* OR mortali* OR “mortality”
OR “postmortem”)
Limit 2014-present
Human
All-adult

Step counts and cardiovascular disease

Searches conducted on 22/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Cardiovascular disease AND (("Arteriosclerosis"[mh] OR “Death, sudden, cardiac”[mh]
OR "Heart failure"[mh] OR "Myocardial ischemia"[mh] OR
"myocardial infarction"[mh] OR "Stroke"[mh] OR "Subarachnoid
hemorrhage"[mh] OR "Intracranial hemorrhages"[mh]) OR
((Arteriosclero*[tiab] OR Atherosclero*[tiab] OR "Cerebral
infarction"[tiab] OR "Cerebrovascular diseases"[tiab] OR
"Cerebrovascular disease"[tiab] OR "Coronary"[tiab] OR
“Angina”[tiab] OR "Heart failure"[tiab] OR "Intracerebral
Hemorrhage"[tiab] OR "Intracerebral Hemorrhages"[tiab] OR
"Intracranial hemorrhage"[tiab] OR "Intracranial

9
 hemorrhages"[tiab] OR “Ischemic”[tiab] OR “Ischemia” OR
"myocardial infarction"[tiab] OR "Stroke"[tiab] OR
"Subarachnoid hemorrhages"[tiab] OR "Subarachnoid
hemorrhage"[tiab] OR “Heart diseases"[tiab] OR "Heart
disease"[tiab] OR “Cardiovascular”[tiab] OR “Heart
surgery”[tiab])))
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

CINAHL: Terms searched in title or abstract

Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Cardiovascular disease AND (Arteriosclero* OR "Arteriosclerosis" OR Atherosclero* OR
"Cerebral infarction" OR "Cerebrovascular diseases" OR
"Cerebrovascular disease" OR "Coronary" OR “Angina” OR
"Heart failure" OR "Intracerebral Hemorrhage" OR "Intracerebral
Hemorrhages" OR "Intracranial hemorrhage" OR "Intracranial
hemorrhages" OR "Myocardial ischemia" OR "myocardial
infarction" OR "Stroke" OR "Subarachnoid hemorrhage" OR
"Subarachnoid hemorrhages" OR "Ischemic" OR ”Ischemia” OR
“Heart diseases” OR “Heart disease” OR “Cardiovascular” or
“Heart surgery”)
Limit 2014-present
Human
All-adult

Step counts and type 2 diabetes

Searches conducted on 25/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Type 2 diabetes AND ((“insulin resistance”[mh] OR “blood glucose”[mh] OR
mellitus hyperglycemia[mh] OR “diabetes mellitus, Type 2”[mh] ) OR
((insulin resistance”[tiab] OR “diabetes”[tiab] OR
“hyperglycaemia”[tiab] OR “glycaemic index”[tiab] OR “blood
glucose”[tiab])))
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

10
CINAHL: Terms searched in title or abstract
Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Type 2 diabetes AND (“insulin resistance” OR “blood glucose” OR
mellitus “hyperglycemia” OR “diabetes mellitus, Type 2” OR “diabetes”
OR “glycaemic index”)
Limit 2014-present
Human
All-adult

Step counts and cancer

Searches conducted on 22/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Cancer AND (“Cancer”[tiab] OR "Neoplasm"[tiab] OR "Tumor"[tiab] OR
"Carcinogenesis"[tiab] OR “Metastasis”[tiab] OR “Oncol*”[tiab]
OR "Leukemia"[tiab] OR "Lymphoma"[tiab] OR "Malignan*"[tiab]
OR "Blastoma"[tiab] OR "Tumour"[tiab] OR "Melanoma"[tiab]
OR "Myeloma"[tiab] OR "Carcinoma"[tiab] OR "Neoplasia"[tiab]
OR "Sarcoma"[tiab] OR "Tumors"[tiab] OR "Tumours"[tiab] OR
"Neoplasms"[tiab] OR "Adenosarcoma"[tiab] OR
"Angiosarcoma"[tiab] OR "Astrocytoma"[tiab] OR
"Cholangiocarcinoma"[tiab] OR "Chondrosarcoma"[tiab] OR
"Craniopharyngioma"[tiab] OR "Ependymoma"[tiab] OR
"Fibrosarcoma"[tiab] OR "Glioma"[tiab] OR "Langerhans Cell
Histiocytosis"[tiab] OR "Hodgkin's Disease"[tiab] OR
"Leiomyosarcoma"[tiab] OR "Medulloblastoma"[tiab] OR
"Mesothelioma"[tiab] OR "Neuroblastoma"[tiab] OR
"Rhabdomyosarcoma"[tiab] OR "Osteosarcoma"[tiab])
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

11
CINAHL: Terms searched in title or abstract
Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Cancer AND ("Cancer" OR "Neoplasm" OR "Tumor" OR
"Carcinogenesis" OR “Metastasis” OR “Oncol*” OR "Leukemia"
OR "Lymphoma" OR "Malignan*" OR "Blastoma" OR "Tumour"
OR "Melanoma" OR "Myeloma" OR "Carcinoma" OR
"Neoplasia" OR "Sarcoma" OR "Tumors" OR "Tumours" OR
"Neoplasms" OR "Adenosarcoma" OR "Angiosarcoma" OR
"Astrocytoma" OR "Cholangiocarcinoma" OR
"Chondrosarcoma" OR "Craniopharyngioma" OR
"Ependymoma" OR "Fibrosarcoma" OR "Glioma" OR
"Langerhans Cell Histiocytosis" OR "Hodgkin's Disease" OR
"Leiomyosarcoma" OR "Medulloblastoma" OR "Mesothelioma"
OR "Neuroblastoma" OR "Rhabdomyosarcoma" OR
"Osteosarcoma")
Limit 2014-present
Human
All-adult

Step counts and physical function

PubMed search conducted on 25/03/24; CINAHL search conducted on 22/03/24;
searches updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR (step count*)[tw] OR (step* count*)[tw]
OR (step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Physical function AND ("Physical function"[tiab] OR "Physical functioning"[tiab]
OR "Physical ability"[tiab] OR "Physical disability"[tiab] OR “Gait
speed"[tiab] OR "Walking speed"[tiab] OR "Mobility"[tiab] OR
"Chair stands"[tiab] OR "Activities of daily living"[tiab] OR
"Activity of daily living"[tiab] OR "Tandem walk"[tiab] OR "Health
status"[ti] OR "Health related quality of life"[ti] OR "HRQOL"[ti]
OR "Physical performance"[tiab] OR “functional capacity” [tiab]
OR “functional impairment” [tiab] OR “functional limitations”
[tiab] OR “motor function” [tiab] OR ("Functional"[tiab] AND
"Physical"[tiab]))
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment” [Publication Type] OR “editorial” [Publication
Exclude Type] OR “Address” [Publication Type] OR “Autobiography”
[Publication Type] OR “Bibliography” [Publication Type] OR
“Biography” [Publication Type] OR “Books and Documents”
[Publication Type] OR “Case Reports” [Publication Type] OR
“Clinical Conference” [Publication Type] OR “Clinical Study”
[Publication Type] OR “Clinical Trial” [Publication Type] OR
“Clinical Trial Protocol” [Publication Type] OR “Clinical Trial,
Phase I” [Publication Type] OR “Clinical Trial, Phase II”
[Publication Type] OR “Clinical Trial, Phase III” [Publication
12
 Type] OR “Clinical Trial, Phase IV” [Publication Type] OR
“Dictionary” [Publication Type] OR “Clinical Trial, Veterinary”
[Publication Type] OR “Congress” [Publication Type] OR
“Consensus Development Conference” [Publication Type] OR
“Consensus Development Conference” [Publication Type] OR
“NIH, Controlled Clinical Trial” [Publication Type] OR “Corrected
and Republished Article” [Publication Type] OR “Dataset”
[Publication Type] OR “Meta-Analysis” [Publication Type] OR
“Observational Study” [Publication Type] OR “Veterinary,
Pragmatic Clinical Trial” [Publication Type] OR “Randomized
Controlled Trial” [Publication Type] OR “Retracted Publication”
[Publication Type] OR “Retraction of Publication” [Publication
Type] OR “Review” [Publication Type] OR “Systematic Review”
[Publication Type] OR “Webcast” [Publication Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

CINAHL: Terms searched in title or abstract

Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Physical function AND ("Physical function" OR "Physical functioning" OR
"Physical ability" OR "Physical disability" OR "Gait speed" OR
"Walking speed" OR "Mobility" OR "Chair stands" OR "Activities
of daily living" OR "Activity of daily living" OR "Tandem walk"
OR "Health status" OR "Health related quality of life" OR
"HRQOL" OR "Physical performance" OR “functional capacity”
OR “functional impairment” OR “functional limitations” OR
“motor function” OR (Functional AND Physical))
Limit 2014-present
Human
All-adult

Step counts and falls and falls-related injuries

Searches conducted on 22/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Fall AND ("Accidental falls"[mh] OR "Fall"[tiab] OR "Falls"[tiab] OR
"Slip"[tiab] OR "Slips"[tiab] OR "Trip"[tiab] OR "Trips"[tiab] OR
"Fell"[tiab] OR "Slipped"[tiab] OR "Tripped"[tiab])
Injury AND ("Brain concussion"[mh] OR "Hemorrhage"[mh] OR
"Wounds and injuries"[mh] OR (Limit*[tiab] AND activities[tiab])
OR (Limit*[tiab] AND activity[tiab]) OR (Reduc*[tiab] AND
activities[tiab]) OR (Reduc*[tiab] AND activity[tiab]) OR
(Broken[tiab] AND bone*[tiab]) OR "Bruise"[tiab] OR

13
 "Bruises"[tiab] OR "Bruised"[tiab] OR "Concussion"[tiab] OR
"Concussions"[tiab] OR "Contusion"[tiab] OR "Contusions"[tiab]
OR "Fracture"[tiab] OR "Fractured"[tiab] OR "Fractures"[tiab]
OR "Hemorrhage"[tiab] OR "Hemorrhages"[tiab] OR
"Hemorrhaging"[tiab] OR "Injuries"[tiab] OR "Injury"[tiab] OR
"Injured"[tiab] OR "Internal bleeding"[tiab] OR "Sprain"[tiab] OR
"Sprained"[tiab] OR "Sprains"[tiab])
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

CINAHL: Terms searched in title or abstract

Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Fall AND ("Fall" OR "Falls" OR "Slip" OR "Slips" OR "Trip" OR
"Trips" OR "Fell" OR "Slipped" OR "Tripped")
Injury AND ((Broken AND bone*) OR "Bruise" OR "Bruises" OR
"Bruised" OR "Concussion" OR "Concussions" OR "Contusion"
OR "Contusions" OR "Fracture" OR "Fractured" OR "Fractures"
OR "Hemorrhage" OR "Hemorrhages" OR "Hemorrhaging" OR
"Injuries" OR "Injury" OR "Injured" OR "Internal bleeding" OR
"Sprain" OR "Sprained" OR "Sprains" OR (Limit* AND activities)
OR (Limit* AND activity) OR (Reduc* AND activities) OR
(Reduc* AND activity))
Limit 2014-present
Human
All-adult

Step counts and mental health

Searches conducted on 22/03/24 and updated on 14/02/25
PubMed:

Set Search Terms

Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Mental health (anxiety AND ("Affect"[mh] OR "Affect"[tiab] OR "Anxiety"[mh] OR
depression) "Anxiety"[tiab] OR "Mood"[tiab] OR "Mood disorders"[mh] OR
"Mood disorders"[tiab] OR "Anxiety disorders"[mh] OR
"Panic"[tiab] OR "Affect disorder"[tiab] OR "Affect disorders"[tiab]
OR "Depression"[mh] OR "Antidepressant"[tiab] OR
"Affective"[tiab] OR "Adjustment disorder"[tiab] OR "Adjustment
disorders"[tiab] OR "Depression"[tiab] OR "Depressive"[tiab] OR
"Depressed"[tiab] OR "Anxiolytic"[tiab] OR "Dysthymic
Disorder"[tiab] OR "Dysthymia"[tiab])

14
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh]) NOT
(("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh]) AND
"adult"[Mesh]))

CINAHL: Terms searched in title or abstract

Set Search Terms

Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Mental health (anxiety AND ("affect" OR "anxiety" OR "Mood" OR "Panic” OR
depression) "depression" OR "antidepressant" OR "affective" OR "adjustment
disorder" OR "adjustment disorders” OR "depression" OR
"depressive" OR "depressed" OR "Anxiolytic" OR "dysthymic
disorder" OR "dysthymia")
Limit 2014-present
Human
All-adult

Step counts and cognition

Searches conducted on 22/03/24 and updated on 14/02/25

PubMed:
Set Search Terms
Steps ((“daily steps”[tiab] OR step count*[tw] OR (step* count*)[tw] OR
(step-count)[tw] OR (step count)[tw] OR (step* day*)[tw] OR
“step/day”[tw] OR (step volume)[tw] OR (aerobic step)[tw]))
Cognition AND (("Academic achievement"[tiab] OR "Academic
performance"[tiab] OR "Attentional control"[tiab] OR "Brain
health"[tiab] OR "Brain function"[tiab] OR “Cognition”[tiab] OR
"Cognitive ability"[tiab] OR "Cognitive control"[tiab] OR
“Cognitive decline”[tiab] OR "Cognitive function"[tiab] OR
"Cognitive functioning"[tiab] OR "Cognitive health"[tiab] OR
"Cognitive performance"[tiab] OR "Cognitive processing"[tiab]
OR "Executive control"[tiab] OR "Executive function"[mh] OR
"Executive functioning"[tiab] OR "Executive functions"[tiab] OR
"Information processing"[tiab] OR "Inhibitory control"[tiab] OR
"Memory"[mh] OR "Mental flexibility"[tiab] OR "Mental
recall"[tiab] OR "Neuro cognitive"[tiab] OR "Neurocognitive"[tiab]
OR "Perceptual processing"[tiab] OR "Problem solving"[mh] OR
"Problem solving"[tiab] OR "Scholastic achievement"[tiab] OR
"Scholastic performance"[tiab]) OR ("Executive function"[tiab]
OR "Memory"[tiab]) OR “Alzheimer”[tiab] OR “Dementia”[tiab]))
Limit: Publication Date AND ("2014/01/01"[PDAT] : "3000/12/31"[PDAT])
Limit: Publication Type NOT (“comment”[Publication Type] OR “editorial”[Publication
Exclude Type])
Limit: Exclude child NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
only NOT (("infant"[Mesh] OR "child"[mesh] OR "adolescent"[mh])
AND "adult"[Mesh]))

15
CINAHL: Terms searched in title or abstract
Set Search Terms
Steps (“daily steps” OR “step-count” OR step* n3 count* OR step* n3
day* OR “step/day” OR “step volume” OR “aerobic step”)
Cognition AND ("Academic achievement" OR "Academic performance"
OR "Attentional control" OR "Brain health" OR "Brain function"
OR “Cognition” OR "Cognitive ability" OR "Cognitive control"
OR “Cognitive decline” OR "Cognitive function" OR "Cognitive
functioning" OR "Cognitive health" OR "Cognitive performance"
OR "Cognitive processing" OR "Executive control" OR
"Executive function" OR "Executive functioning" OR "Executive
functions" OR "Information processing" OR "Inhibitory control"
OR "Memory" OR "Mental flexibility" OR "Mental recall" OR
"Neuro cognitive" OR "Neurocognitive" OR "Perceptual
processing" OR "Problem solving" OR "Scholastic achievement"
OR "Scholastic performance" OR “Alzheimer” OR “Dementia”)
Limit 2014-present
Human
All-adult

16
Supplementary Table 1. Characteristics of included studies by outcome
Study Cohort/ Study Participant characteristics Step monitoring Follow-up
Country entry period, no. of
events (%)

Study sample Excluded Age No. of participants Step- Baseline

participants (range, (female %); no. of monitoring step counts
mean (SD) participants based device and (mean (SD)
or median on reported race wear or median
(IQR)) and/or ethnicity (%) location (IQR))

ALL-CAUSE MORTALITY (ACM)

ACM studies included in meta-analysis

De Paula Estudo 2017-19 Middle-aged Deceased, non- 59.1 (8.61) 8,832 (55.8%); ACC: 6,185 5.43 years
(2025) Longitudinal de and older civil attendees from first ActiGraph (4,674– (median); 216
White/Asian descent:
Saúde do Adulto servants wave, missing GT3X+ 7,924) (2.4%)
107 (49.5%)
(ELSA-Brasil) enrolled from accelerometer use, (waist)
public invalid Black/Brown/
Brazil
research, accelerometer data, Brazilian indigenous:
education and incomplete 109 (50.5%)
healthcare information on
organisations covariates, or
missing sleep data

Del Pozo Cruz UK Biobank 2013-15 General adults Those with poor 61.1 (7.9) 78,500 (55.3%); ACC: Axivity 7198.2 7 years
(2022c) aged between self-rated health, AX3 (4609.2) (median) for
UK Non-White: 2,626
40 and 69 prevalent cancer or (dominant ACM, 2179
(3.3%)
years CVD, and/or wrist) (2.8%)
missing data for any
of the covariates

Dwyer (2015) The Tasped 2000-05 Adults living in 58.8 (13.2) 2,576 (52%); PED: Omron Males: 8,781 11.1 years
Prospective Tasmania, HJ-003; (4,538) (mean), 219
race/ethnicity not
Cohort Study Australia Omron HJ- (8.5%)
reported Females:
102, Yamax
Australia 8, 925
Digi-walker
(4,485)
SW-200
(waist)

17
Fox (2015) Project OPAL 2007-08 Adults aged 70 Not reported 70–74.9 201 (48.8%); ACC Not reported 29 months
(Older People and older, (36.6%) (Actigraph (mean), 33
race/ethnicity not
and Active living in GT1Ms) (16.4%)
75–79.9 reported
Living) & OPAL- suburban and (waist)
(26.8%)
PLUS urban sectors
of a large city 80–84.9
UK
in south west (24.9%)
England
85+
(11.7%)

Fretts (2023) Strong Heart 2001-03 American Participants not 41.0 (16.8) 2,204 (59.9%); PED: AE120 5,841.1 17.0 years
Family Study Indians aged meeting minimal (hip) (3,901.7) (mean), 449
race/ethnicity not
(SHFS) 14 to 65 years wear time ACM deaths
reported
from 12 rural (20.3%)
USA
American
Indian
communities in
Arizona,
Oklahoma,
North Dakota,
and South
Dakota

Hamaya Women’s Health 2011-15 Participants People with a 71.8 (5.6) 14,399 (100%); ACC: 5,183 9 years
(2024) Study (WHS) aged 62 years history of CVD or Actigraph (3,691- (median); 1,330
primarily of White
and over, cancer and not GT3X+ (hip) 7,001) deaths (9.2%)
USA race, otherwise
without CVD meeting minimal
race/ethnicity not
or cancer wear time
reported

Hansen (2020) Unnamed 2008-09 Adults aged 40 57 (10.9) 2183 (43.2%); ACC: 8,002 (3,113) 9.1 years
years or older ActiGraph (median), 119
Norway race/ethnicity not
with valid data GT1M (5.5%)
reported
across (waist)
exposure
variables and
covariates

18
Jefferis British Regional 2010-12 Men aged 71- Men with pre- 78.4 (4.6) 1,274 (0%); ACC: 4,938 5 years
(2019a) Heart Study 92 years existing CHD, Actigraph (2,794) (median), 194
Predominantly White
(BRHS) recruited from stroke or heart GT3x (hip) (15.2%)
British, otherwise
a single failure
UK race/ethnicity not
general
reported
practice in
each of 24
British towns

Mañas (2022) Toledo Study for 2012-14 Spanish adults Participants not 78.8 (4.9) 768 (53.9%); ACC: 5,835 5.74 years
Healthy Aging and aged 65 years meeting minimal ActiTrainer (3,445) (mean), 89
race/ethnicity not
2015-17 or older wear time ActiGraph (11.6%)
Spain reported
wGT3X-BT
(hip)

Oftedal (2020) Hunter 2005-08 Community- Participants with 64.4 (7.1) 1,697 (49.3%); PED: 6,678 9.6 years
Community dwelling adults implausible Yamasa Digi (4,689– (median), 204
race/ethnicity not
Study aged 55-85 pedometer data Walker SW 8,850) (12%)
reported
years 200
Australia

Paluch (2021) Coronary Artery 2005-06 Adults aged Participants not 45.2 (3.6) 2,110 (57.1%); ACC: 9,146 10.8 years
Risk 38-50 years meeting minimal ActiGraph (mean) (mean), 72
White: 1,222 (57.9%)
Development in wear time 7164 (hip) (3.4%)
Young Adults Black: 888 (42.1%)
(CARDIA)
USA

Saint-Maurice NHANES 2003-06 Representativ Those with missing 56.8 (56.2, 4,840 (53.5%); ACC: 9,124 (SD 10.1 years
(2020) e sample of data 57.4) ActiGraph not reported) (mean); 1,165
USA Non-Hispanic White:
US adults 7164 (hip) deaths (24.1%)
2,681 (77.4%)
aged 40 years
and older in Non-Hispanic Black:
NHANES 993 (10.2%)

Mexican American:
887 (5.3%)

Other: 279 (7.1%)

19
Watanabe Kyoto-Kameoka 2013 Community- Participants with an 72.3 (5.4) 4,165 (48.7%); ACC: EW- 4,192
(2023b) Study dwelling unknown date of NK52 (waist) (2,395)
race/ethnicity not
Japanese moving away from
Japan reported
adults aged 65 the community and
years and those not meeting
older minimal wear time

Yamamoto Unnamed 1998-99 Physically Those lost to follow- 71 (0) 419 (45.6%); PED: Yamax 6,470 9.8 years
(2018) independent, up due to moving EC 100S (2,732) (median), 76
Japan race/ethnicity not
community- from the target area pedometer, (18.1%)
reported
dwelling or other reasons, YAMASA,
Japanese and those with Tokyo (waist)
people aged insufficient wear
71 years time

ACM studies included in sensitivity analyses

Ahmadi (2024) UK Biobank 2013-15 Middle-aged Participants with 61.1 (7.8) 72,174 (57.9%); ACC: Axivity 6,222.5 6.9 years
and older diagnosed CVD or AX3 (4,102– (mean), 1633
UK Asian: 814 (1.1%)
adults with cancer prior to (dominant 9,225) ACM deaths
valid accelerometry Black: 622 (0.9%) wrist) (2%)
accelerometer measurement,
Mixed: 413 (0.6%)
data missing covariate
data or an event Other: 590 (0.8%)
within the first 12
White: 69,735
months from the
(96.6%)
accelerometry
measurement

Inoue (2023) NHANES 2005-06 Participants People who lacked 50.5 (18.3) 3,101 (51%); ACC: 8,793 10 years
aged 20 years data on insurance ActiGraph (6,238- (mean), 439
USA White: 1,579 (50.9%)
and older with status, BMI or 7164 (hip) 11,439) deaths (14.2%)
valid follow-up mortality Black: 666 (21.5%)
accelerometer data at 10 years
Hispanic: 734
data for 4 or
(23.7%)
more days
Other: 122 (3.9%)

20
Lee (2019) WHS 2011-15 Women aged Women not meeting 72 (5.7) 16,741 (100%); ACC: 5,499 (SD 4.3 years
between 62 minimal wear time ActiGraph not reported) (mean), 504
USA primarily White,
and 101 years GT3X+ (hip) (3%)
otherwise
at baseline
race/ethnicity not
reported

Small (2024) UK Biobank 2013-15 Participants Participants with 40-69 75,263 (58%); ACC: Axivity 9,156 6.9 years
without prior prevalent CVD or AX3 (6,936– (median), 1844
UK Non-White: 2,370
history of CVD cancer as a primary (dominant 11,762) deaths (2.4%)
(3.1%)
or cancer diagnosis. Those wrist)
not meeting minimal White: 72,893
wear time, with poor (96.9%)
device calibration or
unrealistic average
acceleration (>100
mg).

ACM studies not included in meta-analysis

Cavalheri Unnamed 2018-20 People People with brain 70 (10) 89 (38%); ACC: 7,848 12 months, 27
(2023) diagnosed with metastasis, acute Actigraph (3,737) (30%)
Australia race/ethnicity not
inoperable illness, unable to GT9X-Link
reported
lung cancer at ambulate and/or (waist)
three hospitals unable to
in Western understand spoken
Australia and written English

Del Pozo Cruz NHANES 2005-06 Adults aged 18 Participants with Pre- 1,194 (44.2% with ACC: 8,500 Pre-diabetes:
(2022a) years and less than 1 year of diabetes: prediabetes; 49.3% ActiGraph (median; 9.83 years
USA
older with follow-up were 54.7 (17.9) with diabetes); AM-7164 IQR not (median),
prediabetes removed from the (hip) reported) for (200/1194=16.8
Diabetes: race/ethnicity not
and diabetes analysis prediabetes %)
61.6 (13.8) reported
6,300 Diabetes: 8.75
(median; years (median),
IQR not (138/493=28.0%
reported) for )
diabetes

21
Guo (2025) NHANES 2005-06 Adults aged 18 Pregnant women, 57 (44–69) 1,629 (44.8%); ACC: 7,319 12.57 years
years and participants that ActiGraph (median; (mean); 370
USA Non-Hispanic White:
older with were ineligible or AM-7164 4,346- deaths (22.7%)
876 (53.8%)
hypertension had incomplete data (hip) 10,148)
on follow-up, daily Non-Hispanic Black:
step count, or other 408 (25.1%)
data
Mexican American:
263 (16.1%)
Other: 82 (5%)

Schneider UK Biobank 2013-15 Participants Participants not 37-73 714 (51.4%); ACC: Axivity Not reported 5.5 years
(2021) with previously meeting minimal AX3 (mean), 50 (7%)
UK Mean age White: 688 (96.4%)
known liver wear time and (dominant
reported
disease failure of data wrist)
according
calibration
to
accelero-
meter
average
quartiles:

Q1: 64.7
(6.8)
Q2: 63.3
(7.5)

Q3: 62.1
(7.7)

Q4: 61.3
(7.4)

22
Shimoda National Center Not Residents in Certification of 74 (71-78) 8,664 (54%); ACC: triaxial 5,514 60 months; 529
(2025) for Geriatrics reported the Midori support and care acceleromet (3,878- (6.1%)
race/ethnicity not
and Gerontology Ward of under the Japanese er GT40-020 7,616)
reported
Study of Nagoya or public long-term and HW-100
Geriatric Takahama at care insurance (waist)
Syndromes least 70 or 60 system owing to
(NCGG-SGS) years of age disability; presence
respectively of a disability
Japan affecting basic
activities of daily
living; health issues
including dementia,
stroke or Parkinson
disease; missing
health checkup data

Watanabe Kyoto-Kameoka 2013 Community- Residents of areas 72.3 (5.4) 4,159 (48.7%); ACC: EW- 4,194 3.38 years
(2023a) Study dwelling assigned to a NK52 (waist) (2,395) (median), 111
race/ethnicity not
Japanese comprehensive (2.7%)
Japan reported
adults aged 65 geriatric intervention
years and program by a
older cluster RCT,
persons whose
identify could not be
ascertained,
residents who were
dead or who had
moved out of the
city, certification of
long term care.
Those not meeting
minimal wear time.

23
Zhou (2023) NHANES 2005-06 Participants Patients without a 46.5 (1.76) 363 (46.3%); ACC: 6,601 (331) 10 years
with history of ActiGraph (mean), deaths:
USA Non-Hispanic White:
congestive congestive heart 7164 (hip) 52.89%
269 (73.98%)
heart failure failure and not
meeting minimal Non-Hispanic Black:
wear time 52 (14.35%)

Mexican American:
24 (6.74%)
Other Hispanic: 6
(1.72%)

Other: 12 (3.21%)

CVD

Studies included in meta-analysis of CVD incidence

Del Pozo Cruz UK Biobank 2013-15 General adults Those with poor 61.1 (7.9) 78,500 (55.3%); ACC: Axivity 7198.2 6.8 years
(2022c) aged between self-rated health, AX3 (4609.2) (median) for
UK Non-White: 2,626
40 and 69 prevalent cancer or (dominant CVD incidence,
(3.3%)
years CVD, and/or wrist) 10245 (13.1%)
missing data for any
of the covariates

Hamaya Women’s Health 2011-15 Participants People with a 71.8 (5.6) 14,399 (100%); ACC: 5,183 9 years
(2024) Study aged 62 years history of CVD or Actigraph (3,691- (median); 588
primarily of White
and over, cancer and not GT3X+ (hip) 7,001) developed CVD
USA race, otherwise
without CVD meeting minimal (4.1%)
race/ethnicity not
or cancer wear time
reported

Jefferis British Regional 2010-12 Men aged 71- Participants with 78.4 (4.6) 1,181 (0%); ACC: 4,938 4.9 years
(2019b) Heart Study 92 years pre-existing CVD ActiGraph (2,794) (median), 122
Predominantly White
(BRHS) recruited from and not meeting GT3X (hip) (10.3%)
British, otherwise
a single minimal wear time
UK race/ethnicity not
general
reported
practice in
each of 24
British towns

24
LaMonte Objective 2012-13 Women aged An alternative 78.6 (6.8) 5,951 (100%); ACC: 3133 (2303- 7.5 (2.6) years
(2024) Physical Activity 63 to 99 years diagnosis that could ActiGraph 4547) (mean), 407
Non-Hispanic White:
and better explain the GT3X+ (6.9%)
2,925 (49.2%)
Cardiovascular patient symptoms triaxial
Health (OPACH) such as iatrogenic Non-Hispanic Black: acceleromet
fluid overload, 2,004 (33.7%) er (hip)
USA
chronic obstructive
Hispanic: 1,022
pulmonary disease
(17.2%)
(COPD)
exacerbation, or
cardiac ischemia

Moniruzzaman Shiga 2006-08 Japanese men Participants that 63.6 (9.2) 680 (0%); PED: 8,524.6 5 years (mean),
(2020) Epidemiological aged 40-79 have had a stroke Yamasa Digi (3,537.1) 145 (21.3%)
race/ethnicity not
Study of years and not meeting Walker DW
reported
Subclinical minimal wear time 200 (waist)
Atherosclerosis
(SESSA)

Japan

Pan (2023) Strong Heart 2001-03 American Participants with a 40 (14.69) 2,492 (62.4%); PED: AE120 5,609 up to 20 years of
Family Study Indians aged history of CHD, or (hip) (3,799) follow-up, 301
race/ethnicity not
(SHFS) 14 to 65 years other ASCVD, such (12.1%)
reported
from 12 rural as ischemic stroke
USA
American and transient
Indian ischemic attack
communities in (TIA), who were
Arizona, pregnant, without a
Oklahoma, family ID, or did not
North Dakota, meet minimal wear
and South time
Dakota

Studies included in sensitivity analysis of CVD incidence

25
Ahmadi (2024) UK Biobank 2013-15 Middle-aged Participants with 61.1 (7.8) 72,174 (57.9%); ACC: Axivity 6,222.5 6.9 years
and older diagnosed CVD or AX3 (4,102– (mean), 6190
UK Asian: 814 (1.1%)
adults with cancer prior to (dominant 9,225) incident CVD
valid accelerometry Black: 622 (0.9%) wrist) (8.7%)
accelerometer measurement,
Mixed: 413 (0.6%)
data missing covariate
data or an event Other: 590 (0.8%)
within the first 12
White: 69,735
months from the
(96.6%)
accelerometry
measurement

Studies included in meta-analysis of CVD mortality

Del Pozo Cruz UK Biobank 2013-15 General adults Those with poor 61.1 (7.9) 78,500 (55.3%); ACC: Axivity 7198.2 6.8 years
(2022c) aged between self-rated health, AX3 (4609.2) (median), 664
UK Non-White: 2,626
40 and 69 prevalent cancer or (dominant CVD deaths
(3.3%)
years CVD, and/or wrist) (0.8%)
missing data for any
of the covariates

Fretts (2023) SHFS 2001-03 American Participants not 41.0 (16.8) 2,204 (59.9%); PED: AE120 5,841.1 17.0 years
Indians aged meeting minimal (hip) (3,901.7) (mean), 123
USA race/ethnicity not
14 to 65 years wear time CVD deaths
reported
from 12 rural (5.6%)
American
Indian
communities in
Arizona,
Oklahoma,
North Dakota,
and South
Dakota

26
Saint-Maurice NHANES 2003-06 Representativ Those with missing 56.8 (56.2, 4,840 (53.5%); ACC: 9,124 (SD 10.1 years
(2020) e sample of data 57.4) ActiGraph not reported) (mean); 406
USA Non-Hispanic White:
US adults 7164 (hip) CVD deaths
2,681 (77.4%)
aged 40 years (8.3%)
and older in Non-Hispanic Black:
NHANES 993 (10.2%)

Mexican American:
887 (5.3%)
Other: 279 (7.1%)

Studies included in sensitivity analysis of CVD mortality

Inoue (2023) NHANES 2005-06 Participants People who lacked 50.5 (18.3) 3,101 (51%); ACC: 8,793 10 years
aged 20 years data on insurance ActiGraph (6,238- (mean), 148
USA White: 1,579 (50.9%)
and older with status, BMI or 7164 (hip) 11,439) CVD deaths
valid follow-up mortality Black: 666 (21.5%) (5.3%)
accelerometer data at 10 years
Hispanic: 734
data for 4 or
(23.7%)
more days
Other: 122 (3.9%)

Small (2024) UK Biobank 2013-15 Participants Participants with 40-69 75,263 (58%); ACC: Axivity 9,156 6.9 years
without prior prevalent CVD or AX3 (6936– (median), 572
UK Non-White: 2,370
history of CVD cancer as a primary (dominant 11,762) CVD deaths
(3.1%)
or cancer diagnosis. Those wrist) (0.8%)
not meeting minimal White: 72,893
wear time, with poor (96.9%)
device calibration or
unrealistic average
acceleration (>100
mg).

CVD studies not included in meta-analysis of CVD incidence or mortality

Cochrane Lifestyle 2010-13 Participants Participants not 78.9 (5.2) 1,590 (67.2%); ACC: 2,681 2.7 years
(2017) Interventions aged 70-89 meeting minimal Actigraph (1,475) (mean), 234
Non-White: 375
and years, at high wear time GT3X (hip) (14.7%)
(23.6%)
Independence risk for mobility
for Elders (LIFE) disability
USA

27
Guo (2025) NHANES 2005-06 Adults aged 18 Pregnant women, 57 (44–69) 1,629 (44.8%); ACC: 7,319 12.57 years
years and participants that ActiGraph (median; (mean); 177
USA Non-Hispanic White:
older with were ineligible or AM-7164 4,346- CVD-related
876 (53.8%)
hypertension had incomplete data (hip) 10,148) deaths (10.9%)
on follow-up, daily Non-Hispanic Black:
step count, or other 408 (25.1%)
data
Mexican American:
263 (16.1%)
Other: 82 (5%)

Yates (2014) Nateglinide and 2002-04 Participants Those not meeting 63 (58-68) 4,345 (51%); PED (waist) 6,245 6 years (mean),
Valsartan in from 40 the protocol-defined (4,065, 531(5.9%)
White: 3,512 (80.8%)
Impaired countries with criteria for impaired 9,157)
Glucose impaired glucose tolerance Black: 64 (1.5%)
Tolerance glucose
Oriental: 384 (8.8%)
Outcomes tolerance who
Research trial either had Other: 385 (8.9%)
(NAVIGATOR) existing CVD
(if 50 years or
Various
older) or with
at least one
additional CVD
risk factor (if
55 years or
older)

CANCER

Cancer studies included in meta-analysis of cancer incidence and/or cancer mortality

Cuthbertson Women’s Health 2011-15 Women Women without 73.4 (6.7) 22,236 (100%); ACC: 4,993 7.9 years
(2024) Accelerometry enrolled in the cancer data, steps Actigraph (2,667) (mean), 1,462
Non-Hispanic White:
Collaboration Women’s data, not adherent GT3X+ (hip) cases of cancer
18,574 (83.2%)
Cohort (WHAC) Health Study with the (6.57%) and 487
(WHS) and accelerometry Non-Hispanic Black: cancer deaths
USA
Women’s protocol, missing 2,220 (9.9%) (2.19%)
Health covariate data and
Hispanic: 1,153
Initiative additional exclusion
(5.2%)
(WHI)/OPACH criteria based on
the cancer site Other: 379 (1.7%)
considered

28
Del Pozo Cruz UK Biobank 2013-15 General adults Those with poor 61.1 (7.9) 78,500 (55.3%); ACC: Axivity 7,198.2 6.9 years
(2022c) aged between self-rated health, AX3 (4,609.2) (median) for
UK Non-White: 2,626
40 and 69 prevalent cancer or (dominant cancer
(3.3%)
years CVD, and/or wrist) incidence, 2,813
missing data for any (3.6%)
of the covariates

Saint-Maurice NHANES 2003-06 Representativ Those with missing 56.8 (56.2, 4,840 (53.5%); ACC: 9,124 (SD 10.1 years
(2020) e sample of data 57.4) ActiGraph not reported) (mean); 283
USA Non-Hispanic White:
US adults 7164 (hip) cancer deaths
2,681 (77.4%)
aged 40 years (5.8%)
and older in Non-Hispanic Black:
NHANES 993 (10.2%)

Mexican American:
887 (5.3%)

Other: 279 (7.1%)

Cancer studies not included in meta-analysis of cancer incidence or mortality

Shreves 2023 UK Biobank 2013-15 Adults Participants with 62.0 (7.9) 86,556 (56%); ACC: Axivity 9,073 5.8 years
cancer, missing AX3 (6,834-11, (mean); 2,669
UK Non-White: 2,726
healthcare linkages (dominant 686) (3%)
(3%)
or covariate data, wrist)
not meeting minimal White: 83,830 (97%)
wear time

TYPE 2 DIABETES INCIDENCE

Type 2 diabetes studies included in meta-analysis

Ballin (2020) Healthy Ageing 2012-17 Community Participants who 70.5 (0.1) 3,055 (52%); ACC: 7,139 (SD 2.6 years
Initiative Study dwelling 70 had diabetes at Actigraph not reported) (mean), 81
race/ethnicity not
(HAI) year olds baseline and not GT3X+ (hip) (2.7%)
reported
meeting minimal
Sweden
wear time

29
Cuthbertson Hispanic 2008-11 Self-identified Participants who 39 (37.8, 6,634 (52%); ACC: Actical 8,164 6 years (mean),
(2022) Community Hispanic/ had diabetes at 39.1) (version B-1, (standard 115 (1.73%)
Hispanic/ Latino:
Health Study / Latino adults baseline and not model 198– error=92)
6,634 (100%)
Study of Latinos aged 18-74 meeting minimal 0200-03)
(HCHS/SOL) years wear time (hip)

USA

Garduno Objective 2012-14 Women aged Participants with 78.9 (6.7) 4,838 (100%); ACC: 3,729 (2,114) 5.7 years
(2022) Physical Activity 63 to 99 years prevalent diabetes, Actigraph (median), 395
White: 2,568 (53.1%)
and a history of diabetes GT3X+ (hip) (8.2%)
Cardiovascular treated with Black: 1,469 (30.4%)
Health (OPACH) medication prior to
Hispanic: 801
OPACH enrollment,
USA (16.6%)
and not meeting
minimal wear time

30
Master (2022) All of Us Not Participants Not having EHR 56.7 (41.5, 6,042 (72.5%); Other: Fitbit 7,731 4 years
Research reported who and Fitbit data or 67.6) (wrist) (5,866.8– (median); 156
White: 5,072 (83.9%)
Program consented to valid Fitbit data for 9,826.8)) T2D (3.1%)
(AoURP) share at least 6 months Black: 336 (5.6%)
electronic
USA Other: 309 (5.1%)
health record
(EHR) data, Hispanic/ Latino: 376
linked their (6.2%)
own Fitbit
Not Hispanic/ Latino:
device, and
5,590 (92.5%)
had valid Fitbit
data over 6 or
more months’
total
monitoring and
who were 18
years or older
at any time
during the
monitoring
period

Type 2 diabetes studies included in sensitivity analysis

Perry (2023) All of Us 2010 Adults who Participants with 50.9 (36, 5,677 (74%); Other: Fitbit 7,924 3.8 years
Research voluntarily prevalent diabetes 61.9) (wrist) (5,997-10, (mean), 97 (2%)
White: 4,705 (89%)
Program provided and not meeting 019)
(AoURP) accelerometry minimal wear time Black: 269 (5%)
data from their
USA Other: 292 (6%)
personal Fitbit
device

Type 2 diabetes studies not included in meta-analysis

31
Kraus (2018) Nateglinide and Not Participants Not reported Q1: 65 (59- 9,306 (66%); PED: Q1: 2,006 5.0 years
Valsartan in reported from 40 71) Accusplit (859, 2,859) (median), 3,254
White: 7,734 (83.1%)
Impaired countries with AE120 (35%)
Q2: 64 (59- Q2: 4,659
Glucose impaired Black: 236 (2.5%) (waist)
69) (4,085,
Tolerance glucose
Asian: 613 (6.6%) 5,216)
Outcomes tolerance who Q3: 63 (58-
Research trial either had 68) Other: 723 (7.8%) Q3: 7,093
(NAVIGATOR) CVD or risk (6,382,
Q4: (57-
factors for 7,754)
Various 66)
CVD
Q4: 10,699
(9,447,
12,299)

COGNITIVE OUTCOMES

Cognition studies included in meta-analysis

UK Biobank 2013-15 Middle-aged Those with 61.1 (7.9) 78,430 (55.3%); ACC: Axivity 8,040.59 6.9 (6.4-7.5);
and older prevalent CVD, AX3 (4,932.97) 866 developed
UK Asian: 881 (1.1%)
adults with cancer, dementia or (dominant dementia (1.1%)
valid other major health Black: 641 (0.8%) wrist)
Del Pozo Cruz accelerometer problems; invalid or
Mixed race: 427
(2022b) data insufficient
(0.5%)
accelerometer data
White: 75,852
(96.7%)

Other: 629 (0.8%)

Women’s Health 1993-98 Post- Women with mild 81.8 (6.2) 1,277 (100%); ACC: 3,216 (SD 4.2 years
Initiative menopausal cognitive ActiGraph not reported) (median); 267
White: 1,133 (88.7%)
Memory Study women impairment and/or GT3X+ (hip) (20.9%)
(WHIMS) and enrolled in dementia, not Black: 100 (7.8%)
Nguyen (2023)
OPACH both WHI meeting minimal
Hispanic/Latina: 44
Memory Study wear time
USA (33.4%)
(WHIMS) and
OPACH

Cognition studies not included in meta-analysis

32
 Unnamed 2012 Community- Individuals who 65-80+ 274 (54%); ACC: GT3X, 4,733.91 22.12 months
dwelling older cannot walk by Actigraph (3,073.56) (mean)
Taiwan race/ethnicity not
adults aged 65 themselves due to (waist)
Chen (2020) reported
years or above physical limitations
or severe chronic
diseases

Shibukawa Shiga 2006-08 Community- Individuals with 63.8 (9.1) 676 (0%); PED: DIGI- Mean step 4.8 years
(2024) Epidemiological dwelling clinical Walker, DW- counts for (mean)
race/ethnicity not
Study of healthy cardiovascular 200 (waist) each
reported
Subclinical Japanese men disease, or other quartile:
Atherosclerosis aged 40-79 severe physical or
Q1: 4,134
(SESSA) years from mental diseases,
(1,032)
Shiga, Japan, potentially hindering
Japan
with valid step PA participation, or Q2: 6,685
count data and with history of (576)
who remained stroke. Those with
Q3: 8,635
free of stroke unavailable or
(581)
at follow-up unreliable step
count data, did not Q4: 11,812
have the Cognitive (1,540)
Abilities Screening
Instrument (CASI)
administered, or
were missing other
pertinent variables.

MENTAL HEALTH

Mental health studies included in meta-analysis

33
Chan (2022) StandingTall 2015-17 Community- Not independent in 75.5 (72.3, 322 (62.1%); ACC: 7,485 2 years, 136
randomized living older activities of daily 80.1) MoveMonitor (3,308) (42.2%)
race/ethnicity not
controlled trial people aged living, , McRoberts
reported
70 years or (waist)
Australia not able to walk
older
household
distances without a
walking aid,
with unstable or
acute medical
condition that
preclude exercise
participation,

cognitively impaired
as defined by a
Pfeiffer Short
Portable Mental
Status
Questionnaire or
with a progressive
neurologic condition
(e.g. Parkinson’s
disease and
multiple sclerosis),

already participating
in a fall prevention
program.

Chan (2023b) UK Biobank 2013-15 Middle-aged Participants with a 62.0 (7.85) 72,359 (53.3%); ACC: Axivity 8,071.9 7.4 years
and older reported depressive AX3 (3,308.55) (mean), 1,332
UK race/ethnicity not
adults episode in their (dominant (1.8%)
reported
lifetime before the wrist)
collection of
accelerometry data

34
Master (2022) All of Us Not Participants Not having EHR 56.7 (41.5, 6,042 (72.5%); Other: Fitbit 7,731 4 years
Research reported who and Fitbit data or 67.6) (wrist) (5,866.8– (median); 467
White: 5,072 (83.9%)
Program consented to valid Fitbit data for 9,826.8)) MDD (9.6%)
(AoURP) share at least 6 months Black: 336 (5.6%)
electronic
USA Other: 309 (5.1%)
health record
(EHR) data, Hispanic/ Latino: 376
linked their (6.2%)
own Fitbit
Not Hispanic/ Latino:
device, and
5,590 (92.5%)
had valid Fitbit
data over 6 or
more months’
total
monitoring and
who were 18
years or older
at any time
during the
monitoring
period

Mental health studies not included in meta-analysis

Hsueh (2021b) Unnamed 2012 Older adults People with 74.5 (6.1) 148 (54%); ACC: 4,733.91 22.1 months
aged 65 years assistive walking Actigraph (3,073.56) (mean); N/A
Taiwan race/ethnicity not
or older devices or living in (waist)
reported
an institution, not
meeting minimal
wear time

35
Ramsey Precision 2019-20 US veterans Patients receiving 18-70 66 (28.8%); ACC: 3,545 24 weeks; N/A
(2022) Medicine in with MDD dosage increases of ActiGraph (1,819)
White: 49 (74.2%)
Mental Health enrolled in the a currently GT9X Link
Care study PRIME Care prescribed AD. Black: 17 (25.8%) (wear
(PRIME Care) study, who location not
Patients with a
were enrolled reported)
USA current diagnosis of
in the
a serious mental
actigraphy
illness
monitoring
(schizophrenia,
component of
bipolar disorder, or
the trial.
psychotic major
Participants
depression), an
were either
eating disorder,
starting or
antisocial or
switching to a
borderline
new course of
personality disorder,
antidepressant
or an active alcohol
(AD)
or drug use disorder
monotherapy
in the past six
at time of
months.
enrolment.
Patients on
continuing
prescriptions of
antipsychotic, mood
stabilizer, or
addiction treatment
medications, or
more than one AD
medication at the
time of enrolment.

Also excluded for

use of assistive
devices, or
insufficient wear
time.

36
Raudsepp Unnamed 2011 Convenience Participants with 72.1 (2.1) 195 (74.4%); PED: 6,394.5 2 years; N/A
(2017) sample of high level of Yamax- (841.4)
Estonia race/ethnicity not
generally depressive Digiwalker
reported
healthy, symptoms (Geriatric pedometer
community- Depression Scale > (SW-200-
dwelling 6), diabetes, 024;
individuals musculoskeletal Warminster,
aged 67-74 yo disease, PA)
from three cardiovascular (waistband
communities disease, or any of their
of Estonia known clothing or
(Tartu, Tallinn predisposition to belt at
and Rakvere) deep venous
the front of
thrombosis, and
the hip)
contraindication to
being physically
active.
Participants taking
regularly
antidepressants

Death, refusal,
moving out of
region, loss of
follow-up.

Removed data for

any single day
indicating <1000
steps, and values
>30,000 were
replaced with
30,000 steps.

PHYSICAL FUNCTION

Physical function studies included in meta-analysis

N/A

Physical function studies not included in meta-analysis

37
Hsueh (2021a) Unnamed 2018 Adults aged 60 People with 69.5 (SD 89 (70.8%); ACC: Baseline 1 year (mean);
years or older assistive walking not Actigraph step counts 52.8%
Taiwan race/ethnicity not
devices or living in reported) (waist) not reported maintained or
reported
an institution, not improved lower
44.9% had
meeting minimal extremity
<7,000
wear time performance
steps/day
between
55.1% had baseline and
7,000 or follow up
more
steps/day

Makino (2019) National Center 2013 Older adults in Participants not 76.0 (4.1) 693 (57.9%); ACC: GT40- 4,610.2 26 months
for Geriatrics the Japanese meeting pain criteria 020 (wear (2,435.5) (median), 69
race/ethnicity not
and Gerontology community or missing pain location not (10%)
reported
Study of aged 70 years assessment. Those reported)
Geriatric and older with with a certified
Syndromes chronic lower disability, a history
(NCGG-SGS) back or knee of Parkinson's,
pain stroke, depression
Japan
or dementia, or a
mini mental state
score <20. Those
with movement
limitations by
doctor's order or
with inadequate
accelerometer data

Tateuchi Unnamed 2013-15 Female Patients with a 49.5 (9.7) 30 (100%); PED: EX- 6,578 1 year; events
(2019) patients with history of previous 500 (wear (2,622.9) not reported
Japan race/ethnicity not
mild-to- hip injuries, location not
reported
moderate neurologic, reported)
secondary hip vascular, or other
osteoarthritis conditions that
affect gait
movements or
activities of daily
living

38
Taylor (2021) Unnamed 2016-17 Older adults Participants 80.4 (8.4) 57 (68%); ACC: 4,439 12 weeks
living discharged to live in activPAL (3,137)
Australia race/ethnicity not
independently residential care (thigh)
reported
in the
community
after hip
fracture

White (2014) Multicenter 2009-11 Participants Participants not 67.2 (7.7) 1,788 (59.8%); ACC: 7,073 2 years (mean);
Osteoarthritis who have or meeting minimal StepWatch (2,912) 23.9% <5,000
Non White: 173
(MOST) Study are at high risk wear time Activity steps/day, 8.6%
(9.7%)
of knee Monitor 5,000-7,499
USA
osteoarthritis (ankle) steps/day, 4.1%
aged 50-79 >= 7,500
steps/day

FALLS

Falls studies included in meta-analysis

Aranyavalai Unnamed 2018-19 Older people Serious medical 68.7 (6.7) 255 (71.8%); ACC (Actical 6694.6 6 months, 33
(2020) aged 60 years conditions including acceleromet (3386.9) (12.9%)
Thailand race/ethnicity not
and over who orthopaedic, er) (wrist)
reported
lived in five neurologic and
urban cardiovascular
communities conditions that
at Bangkok, restricted functional
Thailand mobility including
walking and activity
in daily living

Chan (2023a) UK Biobank 2013-15 People aged People aged less 69.1 (3) 32,619 (49.5%); ACC: Axivity 7,558 7 years (mean);
65 and older than 65 years old or AX3 (3,247) 1,627 (5%)
UK race/ethnicity not
who did not provide (dominant
reported
valid data for digital wrist)
gait biomarker
extraction

39
 Jefferis (2015) British Regional 2010-12 Community- Residents of care 78.0 (4.5) 700 (0%); ACC 4,992 1 year, 61
Heart Study dwelling men homes, who did not (ActiGraph (2,727) reported one fall
race/ethnicity not
(BRHS) report being GT3x): hip (9%) and 67
reported
confined to a chair reported
UK and had >=600 min recurrent falls
of accelerometer (10%)
wear time for 3-7 d;
people who did not
provide follow-up
data or were
missing covariate
data

OPACH 2012-14 Women aged Women who did not 78.8 (6.7) 5,545 (100%); ACC 3,216 11.1 months
63-99 years receive falls (GT3X+ (2,184- (mean), 5,473
USA Non-Hispanic White:
calendars during triaxial 4,597)
2,797 (50.4%)
their LLS visit or acceleromet
had missing falls Non-Hispanic Black: er) (hip)
Schumacher calendar data, were 1,820 (32.8%)
(2022) missing daily step
Hispanic: 928
counts or did not
(16.7%)
meet minimal wear
times, or had
extreme values for
falls or steps

Falls studies not included in meta-analysis

N/A

Abbreviations: ACC, accelerometer; ACM, all-cause mortality; AD: antidepressant; CVD: cardiovascular disease; EHR: electronic health records; MDD: major depressive disorder; N/A: not
applicable; PED: pedometer; Q: quartile; SD: standard deviation; T2D: type 2 diabetes; UK: United Kingdom; USA: United States of America.

40
Supplementary Table 2. Individual study results by outcome
ALL-CAUSE MORTALITY (ACM)
Studies included in meta-analysis of ACM
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps by
category
De Paula (2025) Estudo Available documentation – Quartiles: 1.00
Longitudinal de hospital health records, Q1: 3,881 0.44 (0.3, 0.64)
Saúde do Adulto certificate of death, autopsy Q2: 5,564 0.46 (0.31, 0.68)
(ELSA-Brasil) documentation, the Q3: 7,037 0.48 (0.33, 0.70)
Brazilian Mortality Q4: 9,394
Information System
(Sistema de Informaç˜ ao
sobre Mortalidade), and
eventually, interviewing
relatives and the medical
professionals responsible
for the death notification
Del Pozo Cruz UK Biobank Linkage with the National Quartiles: 1.00
(2022c) # Health Service Digital of Q1: 2,982 0.73 (0.65, 0.81)
England and Wales or the Q2: 5,058 0.69 (0.61, 0.77)
NHS Central Register and Q3: 7,385 0.63 (0.56, 0.72)
National Records of Q4: 11,962
Scotland

Dwyer (2015) The Tasped National Death Index Quartiles: 1.00

Prospective Q1: 2,775 0.66 (0.49, 0.93)
Cohort Study Q2: 6,776 0.57 (0.39, 0.91)
Q3: 9,001 0.48 (0.29, 0.89)*
Q4: 11,751
Fox (2015) Project OPAL Medical records Tertiles: 1.00
(Older People Q1: 1,598 0.26 (0.05, 1.3)
and Active Q2: 4,183 0.18 (0.03, 1.1)
Living) & OPAL- Q3: 6,157
PLUS
Fretts (2023) Strong Heart The Strong Heart Study Quartiles: 1.00
Family Study Morbidity and Mortality Q1: 1,563 0.72 (0.54, 0.95)
(SHFS) Committee based on Q2: 4,106 0.66 (0.47, 0.93)
information from medical Q3: 6,329 0.65 (0.44, 0.95)
records, death certificates Q4: 8,816
from state health
departments, review of the
National Death Index,
autopsy and coroner
reports, local review of
obituaries, and/or interviews
with next of kin
Hamaya (2024) Women’s Health Deaths were reported by Quartiles: 1.00
Study (WHS) family members or postal Q1: 2,808 0.7 (0.6, 0.81)
authorities, and confirmed Q2: 4,442 0.58 (0.49, 0.69)
by medical records and Q3: 5,995 0.55 (0.45, 0.68)
death certificates or Q4: 8,551
ascertained through the
National Death Index

Hansen (2020) Unnamed Norwegian Cause of Death Quartiles: 1.00

Registry Q1: 4,651 0.52 (0.29, 0.93)
Q2: 6,862 0.50 (0.27, 0.94)
Q3: 8,670 0.43 (0.21, 0.88)
Q4: 11,467
Jefferis (2019) British Regional National Health Service Quartiles: 1.00
Heart Study central registers Q1:1,524 0.63 (0.43, 0.93)
(BRHS) Q2: 3,730 0.59 (0.39, 0.90)
Q3: 5,473 0.31 (0.17, 0.57)
Q4: 12,097

41
Mañas (2022) # Toledo Study for Spanish National Death Quartiles: 1.00
Healthy Aging Index Q1: 2,083 0.37 (0.19, 0.7)
Q2: 4,390 0.56 (0.32, 1)
Q3: 6,504 0.4 (0.21, 0.78)
Q4: 10,042

Oftedal (2020) Hunter NSW Centre for Health Quartiles: 1.00

Community Record Linkage (CHeReL) Q1: 2,345 0.71 (0.55, 0.91)
Study Q2: 4,689 0.62 (0.43, 0.87)
Q3: 6,678 0.53 (0.32, 0.84)*
Q4: 8,850
Paluch (2021) Coronary Artery Participants or designated Tertiles: 1.00
Risk proxies were contacted T1: 5,837 0.28 (0.15, 0.54)
Development in twice yearly to ascertain T2: 8,502 0.45 (0.25, 0.81)
Young Adults vital status; searches of the T3: 11,815
(CARDIA) National Death Index were
conducted every 5years
Saint-Maurice NHANES National Death Index Categories 1.00
(2020) by cut-off 0.49 (0.44, 0.55)
points (not 0.35 (0.28, 0.45)
distribution):
1: 4,000
2: 8,000
3: 12,000

Watanabe (2023b) Kyoto-Kameoka Information from the Basic Quartiles 1.00

Study Resident Register managed (mean 0.84 (0.53, 1.32)
by the Kameoka City Hall values 0.57 (0.31, 1.03)
below): 0.39 (0.18, 0.85)
Q1: 1,786
Q2: 3,030
Q3: 4,452
Q4: 7,502
Yamamoto (2018) Unnamed Participants who did not Quartiles: 1.00
participate in the yearly Q1: 3,394 0.81 (0.43, 1.54)
health survey were visited Q2: 5,310 1.26 (0.7, 2.26)
at their homes, or they (or a Q3: 6,924 0.46 (0.22, 0.96)
family member) were Q4: 10,241
contacted by phone to verify
their survival status

Studies included in sensitivity analysis for ACM

Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps by
category
Ahmadi (2024) # UK Biobank Linkage with the NHS Quartiles: 1.00.
Digital of England and Q1: 3,043 0.74 (0.65, 0.84)
Wales or Q2: 5,127 0.65 (0.56, 0.74)
the NHS Central Register Q3: 7,478 0.69 (0.60, 0.79)
and National Records of Q4: 12,111
Scotland
Inoue (2023) # NHANES National Death Index Quartiles: 1.00
Q1: 4,394 0.53 (0.42, 0.65)
Q2: 7,571 0.41 (0.31, 0.55)
Q3: 10 082 0.53 (0.39, 0.72)
Q4: 14,449

Lee (2019) WHS Deaths were reported by Quartiles: 1.00

family members or postal Q1: 2,718 0.54 (0.43, 0.69)
authorities, and confirmed Q2:4,363 0.47 (0.35, 0.62)
with medical records and Q3:5,905 0.34 (0.24, 0.48)
death certificates, or Q4:8,442
ascertained through the
National Death Index

42
Small (2024) # UK Biobank UK Biobank linked death Quintiles: 1.00
registry Q1: 5,188 0.72 (0.92, 1.09)
Q2: 7,400 0.64 (0.65, 0.8)
Q3: 9,155 0.62 (0.57, 0.71)
Q4: 11,147 0.53 (0.47, 0.6)
Q5: 14,516
Studies not included in meta-analysis of ACM
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps by
category
Cavalheri (2023) Unnamed Electronic medical records 7,848 Among people with inoperable
(3,737) lung cancer, there was an inverse
association between steps/day
and all-cause mortality that was
no longer significant after
adjusting for all confounders (500
step increments; HR=0.93, 95%
CI: 0.85-1.01).
Del Pozo Cruz NHANES Linkage to death records 8,500 (IQR In participants with prediabetes,
(2022a) from the National Death not reported) compared
Index for with taking 3,779 steps per day
prediabetes (i.e., reference, 10th percentile),
taking 10,678 steps per day (i.e.,
6,300 (IQR nadir) was associated
not reported) with significantly lower all-cause
for diabetes mortality (HR 0.25 [95% CI 0.16–
0.36]).

In participants with diabetes,

compared
with taking 2,532 steps per day
(i.e., reference,
10th percentile), taking 10,177
steps per day (i.e., nadir) was
associated
with a lower risk of all-cause
mortality
HR 0.25 [95% CI, 0.14–0.47].
Guo (2025) NHANES National Death Index 7,319 When treated as a categorical
(4,346- variable, the HRs for all-cause
10,148) mortality for quartiles 2, 3, and 4
were 0.64 (95% CI: 0.50, 0.83),
Q1: 0, 4,346 0.43 (95% CI: 0.31, 0.60), and
Q2: 4,346, 0.46 (95% CI: 0.31, 0.67),
7,319 respectively, demonstrating a
Q3: 7,319, significant trend (P for trend <
10,148 0.01).
Q: 10,148,
28,249
Schneider (2021) UK Biobank Linkage to national death Not reported Quartile 4 vs 1: HR 0.15 [0.05–
registries 0.44]
Quartile 3 vs 1: HR 0.29 [0.13–
0.64]
Quartile 2 vs 1: HR 0.36 [0.18–
0.75]

Shimoda (2025) National Center Residential records and 5,514 Non-linear association between
for Geriatrics and local government data, vital (3,878- daily steps and mortality, with a
Gerontology data from the municipal 7,616) decreased risk of all-cause
Study of Geriatric government mortality between 2,818
Syndromes (HR=0.78, 95% CI: 0.62-0.98) and
(NCGG-SGS) 14,142 (HR=0.62, 95% CI: 0.39-
0.99) steps.
Watanabe (2023a) Kyoto-Kameoka Information from the Basic 4,194 Older adults who took ≥5000
Study Resident Registration (2,395) steps/day had less than half the
System managed by the hazard of all-cause mortality
Kameoka City Office (HR=0.45, 95% CI: 0.23, 0.88)
compared with those who took
<5,000 steps/day.
Zhou (2023) NHANES National Death Index 6,601 (331) In patients with congestive heart
failure, there was an inverse
43
 association between daily steps
and all-cause mortality. An
increase of
1,000 steps/day was associated
with reduced all-cause mortality
(HR=
0.85, 95% CI: 0.78–0.93).
Patients with ≥5,581 steps/day
group (HR=0.31, 95% CI: 0.16–
0.58) had a significantly reduced
risk of all-cause mortality
compared with patients with <
5,581 steps/day.
CARDIOVASCULAR DISEASE (CVD)
Studies included in meta-analysis of CVD incidence
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps by
category
Del Pozo Cruz UK Biobank Inpatient hospitalisation Q1: 2,982 1.00
(2022c) # data provided by either the Q2: 5,058 0.87 (0.83, 0.91)
Hospital Episode Statistics Q3: 7,385 0.81 (0.77, 0.85)
for England, the Patient Q4: 11,962 0.76 (0.71, 0.80)
Episode Database for
Wales or the Scottish
Morbidity Record for
Scotland. Included in the
definition of CVD were fatal
and nonfatal coronary heart
disease, stroke, and heart
failure
Hamaya (2024) Women’s Health CVD was defined as a Q1: 2,808 1.00
Study composite of fatal and Q2: 4,442 0.92 (0.74, 1.14)
nonfatal myocardial Q3: 5,995 0.83 (0.65, 1.06)
infarction (MI), fatal and Q4: 8,551 0.76 (0.57, 1.00)
nonfatal stroke, or other
CVD mortality. Medical
records were obtained to
adjudicate the self-reported
CVD events. Established
criteria was used to confirm
occurrence of MI and stroke
with only confirmed cases
included in the analysis
Jefferis (2019b) British Regional Nonfatal CVD events Q1: 1,532 1.00
Heart Study (defined as myocardial Q2: 3,742 0.75 (0.47, 1.20)
(BRHS) infarction (MI), stroke or Q3: 5,474 0.44 (0.25, 0.77)
heart failure event) were Q4: 12,094 0.34 (0.17, 0.67)
recorded from yearly
reviews of primary care
notes (which included notes
from secondary care). MI
was diagnosed in
accordance with WHO
criteria; stroke events were
those that produced a
neurological deficit present
for >24h. Physician
diagnosis of heart failure
was verified using available
clinical information, with
cases with strong likelihood
of alternative diagnoses
excluded. All cases were
adjudicated by study
director.
LaMonte (2024) Objective Incident acute Q1: 1,082 1.00
Physical Activity decompensated heart Q2: 2,687 0.72 (0.56, 0.93)
and failure (HF) was identified Q3: 3,876 0.60 (0.44, 0.81)
Cardiovascular annually by self-reported Q4: 5,206 0.54 (0.36, 0.79)
Health (OPACH) hospitalizations and
subsequently adjudicated
44
 by trained physicians using
medical record review. HF
cases required diagnosis of
HF, symptoms of HF,
initiation of HF treatment,
and appropriate response to
therapy
Moniruzzaman Shiga Cerebral small vessel Q1: 3,030 1.00
(2020) Epidemiological disease (CSVD) assessed Q2: 7,118 0.91 (0.7, 1.16)
Study of by brain MRI conducted Q3: 9,395 0.73 (0.55, 0.95)
Subclinical independently by two Q4: 11,835 0.84 (0.64, 1.1)
Atherosclerosis neurosurgeons, in duplicate
(SESSA) and blinded to participants’
clinical information
Pan (2023) Strong Heart Incident coronary heart Q1: 1,505 1.00
Family Study disease (CHD) cases Q2: 3,967 0.97 (0.72, 1.32)
(SHFS) determined by the morbidity Q3: 6,104 1.00 (0.73, 1.38)
and mortality surveillance Q4: 8,461 0.77 (0.54, 1.10)
review committee. CHD
included diagnoses of non-
fatal MI (definite, probably,
or possible), non-fatal CHD
(definite or possible), fatal
MI (definite or probable),
and fatal CHD (definite or
possible)
Studies included in sensitivity analyses of CVD incidence
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Ahmadi (2024) # UK Biobank Inpatient hospitalisation Q1: 3,043 1.00
data provided by either the Q2: 5,127 0.74 (0.65, 0.84)
Hospital Episode Statistics Q3: 7,478 0.65 (0.56, 0.74)
for England, the Patient Q4: 12,111 0.69 (0.60, 0.79)
Episode Database for
Wales or the Scottish
Morbidity Record for
Scotland. CVD was defined
as diseases of the
circulatory system,
excluding hypertension,
diseases of arteries and
lymphatic system
Studies included in meta-analysis of CVD mortality
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Del Pozo Cruz UK Biobank Linkage with the National Q1: 2,982 1.00
(2022c) # Health Service (NHS) Q2: 5,058 0.59 (0.49, 0.72)
Digital of England and Q3: 7,385 0.57 (0.46, 0.71)
Wales or the NHS Central Q4: 11,962 0.61 (0.48, 0.76)
Register and National
Records of Scotland
Fretts (2023) SHFS Adjudicated by the Strong Q1: 1,563 1.00
Heart Study Morbidity and Q2: 4,106 1.12 (0.7, 1.78)
Mortality Committee based Q3: 6,329 0.68 (0.42, 1.46)
on information from medical Q4: 8,816 0.78 (0.42, 1.46)
records, death certificates
from state health
departments, review of the
National Death Index,
autopsy and coroner
reports, local review of
obituaries, and/or interviews
with next of kin
Saint-Maurice NHANES National Death Index based Q1: 4,000 1.00
(2020) on CVD codes from Q2: 8,000 0.49 (0.4, 0.6)
International Classification Q3: 12,000 0.35 (0.24, 0.52)
of Diseases, 10th Revision
(ICD-10): ICD-10 code 053-
075
45
Studies included in sensitivity analyses of CVD mortality
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Inoue (2023) # NHANES National Death Index based Q1: 4,394 1.00
on relevant codes from Q2: 7,571 0.69 (0.48, 1.00)
International Classification Q3: 10,082 0.55 (0.33, 0.91)
of Diseases, 10th Revision Q4: 14,449 0.85 (0.51, 1.43)
(ICD-10): codes I00 to I09,
I11, I13, I20 to I51, and I60
to I69
Small (2024) # UK Biobank UK Biobank linked death Q1: 5,188 1.00
registry Q2: 7,400 0.63 (0.52, 0.75)
Q3: 9,155 0.52 (0.42, 0.63)
Q4: 11,147 0.50 (0.40, 0.62)
Q5: 14,516 0.38 (0.30, 0.49)
Studies not included in meta-analysis of CVD mortality or incidence
Study Cohort Outcome ascertainment Baseline Main findings
steps (mean
[SD] or
median
[IQR])
Cochrane (2017) Lifestyle CVD incidence assessed 2,681 Every 500 steps taken were
Interventions and using self-reported (1,475) associated with a 10% decrease
Independence for hospitalisations at each 6- in CVD event risk (HR:0.89 [0.84-
Elders (LIFE) month contact followed by 0.96]).
obtaining hospital records
where relevant and
assessment of records and
abstraction forms by 2
physician investigators with
adjudication as definite,
probable or not confirmed.
Only definite events were
included.
Guo (2025) NHANES CVD mortality assessed 7,319 An increase of 1,000 steps per
using the National Death (median; day was associated with a HR of
Index according to relevant 4,346- 0.92 [0.87-0.97].
codes in the 10th revision of 10,148)
the International When treated as a categorical
Classification of Diseases Quartile 1: 0- variable, the respective HRs were
(ICD-10): I00-I09, I11, I13, 4,346 as follows: Quartile 2: 0.55 [0.38-
I20-I51, and I60-I69 Quartile 2: 0.81]
4,346-7319 Quartile 3: 0.46 [0.29-0.74]
Quartile 3: Quartile 4: 0.46 [0.26-0.81]
7,319-
10,148
Quartile 4:
10,148-
28,249
Yates (2014) Nateglinide and A single CVD composite of 6,245 Each 2000 steps per day was
Valsartan in time to death from CVD (4,065, associated with a 10% lower CVD
Impaired causes or non-fatal 9,157) event rate. Each 2000 steps per
Glucose myocardial infarction or day change from baseline to 12
Tolerance non-fatal stroke was used. months was associated with an
Outcomes An independent committee, additional 8% difference in the
Research trial who were blinded to study CVD event rate.
(NAVIGATOR) allocation and ambulatory
activity level, adjudicated all
putative CVD events
CANCER
Studies included in cancer incidence meta-analysis
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Cuthbertson (2024) Women’s Health Self-reported cancer Q1: 1,250 1.00
Accelerometry diagnoses. Medical records Q2: 3,750 0.94 (0.8, 1.1)
Collaboration were obtained for all self- Q3: 6,250 0.97 (0.8, 1.18)
Cohort (WHAC) reported cancer diagnoses Q4: 8,750 1.01 (0.81, 1.27)
(except for non-melanoma

46
 skin cancers) if participants
consented and were
confirmed by physician
adjudicators.
Del Pozo Cruz UK Biobank Q1: 2,982 1.00
(2022c) # Q2: 5,058 0.86 (0.78, 0.95)
Q3: 7,385 0.82 (0.74, 0.9)
Q4: 11,962 0.78 (0.7, 0.87)
Studies included in cancer mortality meta-analysis
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Cuthbertson (2024) Women’s Health Self-reported and confirmed Q1: 1,250 1.00
Accelerometry by medical records and Q2: 3,750 0.76 (0.6, 0.97)
Collaboration physician adjudicators Q3: 6,250 0.77 (0.55, 1.09)
Cohort (WHAC) Q4: 8,750 0.96 (0.61, 1.51)
Del Pozo Cruz UK Biobank Linkage with the National Q1: 2,982 1.00
(2022c) # Health Service (NHS) Q2: 5,058 0.84 (0.69, 1.02)
Digital of England and Q3: 7,385 0.58 (0.46, 0.73)
Wales or the NHS Central Q4: 11,962 0.64 (0.51, 0.81)
Register and National
Records of Scotland
Saint-Maurice NHANES National Death Index using Q1: 4,000 1.00
(2020) the International Q2: 8,000 0.67 (0.54, 0.82)
Classification of Diseases Q3: 10,000 0.55 (0.42, 0.72)
(10th Revision) for cause of Q4: 12,000 0.45 (0.31, 0.66)
death (ICD-10) code for
cancer (ICD-10 code 019-
043)
Studies not included in meta-analysis of cancer incidence and mortality
Cohort Outcome ascertainment Baseline Main findings
steps (mean
[SD] or
median
[IQR])
Shreves 2023 UK Biobank Composite cancer outcome 9,073 Compared to individuals who took
of 13 sites associated with (6,834- 5,000 daily steps (10th percentile,
low physical activity, 11,686) reference), individuals who took
assessed via linkage with 9,000 daily steps had an 18%
National Health Service lower risk (HR=0.82, [0.74-0.90]),
(NHS) Digital for while those who took 13 000 steps
participants from England had a 23% lower risk (HR=0.77,
and Wales and the NHS [0.69-0.86]). Individuals taking
Central Register for fewer than 5,000 steps had a
participants from Scotland higher risk.
TYPE 2 DIABETES
Studies included in meta-analysis of type 2 diabetes
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Ballin (2020) # Healthy Ageing Type 2 diabetes incidence Q1: 4,138 1.00
Initiative Study determined from the Q2: 6,299 0.45 (0.18, 1.13)
(HAI) Swedish National Patient Q3: 8,121 0.86 (0.40, 1.84)
Register Q4: 10,910 0.88 (0.38, 2.03)

Cuthbertson (2022) Hispanic First definition based on Q1: 2,500 1.00

Community three criteria: 1) self- Q2: 6,250 0.81 (0.60, 1.1)
Health Study / reported diagnosis of Q3: 8,750 1.01 (0.72, 1.41)
Study of Latinos diabetes, 2) self-reported Q4: 11,250 0.60 (0.41, 0.87)
(HCHS/SOL) use of Q5: 13,750 0.69 (0.46, 1.02)
diabetic medication, or 3)
laboratory-tested fasting
plasma glucose >126mg/dl,
non-fasting plasma glucose
of >200mg/dl, 2-h postload
oral glucose tolerance test
(OGTT) >200mg/dl, or
glycosylated hemoglobin
(HbA1c) >6.5%.

47
 Second definition: self-
reported diabetic medication
and laboratory values.
Garduno (2022) Objective Self-report of newly Q1: 1,169 1.00
Physical Activity physician-diagnosed Q2: 2,867 0.86 (0.73, 1.03)
and diabetes requiring insulin or Q3: 4,155 0.80 (0.63, 1.04)
Cardiovascular oral hypoglycemic Q4: 5,673 0.74 (0.53, 1.06)*
Health (OPACH) medication, queried on
annual health
updates administered in the
national WHI

Master (2022) # All of Us Any incident billing code in Q1: 4,750 1.00
Research electronic health records Q2: 7,120 0.65 (0.43, 0.96)
Program (new diagnoses coded Q3: 9,300 0.46 (0.29, 0.74)
(AoURP) during the first 6 months of Q4: 1,250 0.43 (0.26, 0.71)
monitoring were excluded)

Studies included in sensitivity analysis for type 2 diabetes

Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Perry (2023) # All of Us Type 2 diabetes incidence Q1: 4,642 1.00
Research defined according to a Q2: 6,902 0.49 (0.28, 0.87)
Program Northwestern Q3: 8,845 0.57 (0.33, 0.99)
(AoURP) University algorithm for Q4: 11,711 0.35 (0.18, 0.71)
extracting status from
electronic health records
using diagnosis codes,
medication prescriptions,
serum glucose, and
hemoglobin A1c values

Studies not included in meta-analysis of type 2 diabetes

Study Cohort Outcome ascertainment Baseline Main findings
steps (mean
[SD] or
median
[IQR])
Kraus (2018) Nateglinide and Development of a fasting Q1: 2,006 On average, each 2,000-daily step
Valsartan in plasma (859, 2,859) increment, up to 10,000, was
Impaired glucose ≥7.0 mmol/L and/or associated with a 4% lower risk of
Glucose 2-hour glucose ≥200 mg/dL Q2: 4,659 progression to diabetes in the fully
Tolerance (≥11.1 (4,085, adjusted model (HR=0.96, 95%
Outcomes mmol/L), confirmed on oral 5,216) CI: 0.94 to 0.99).
Research trial glucose tolerance test Q3: 7,093
(NAVIGATOR) conducted within 12 weeks. (6,382,
Diagnoses of diabetes 7,754)
made outside of the study
were adjudicated by an Q4: 10,699
independent (9,447,
committee blinded to 12,299)
treatment allocation.
COGNITIVE OUTCOMES
Studies included in meta-analysis of cognitive outcomes
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Del Pozo Cruz NHANES Incidence of all-cause Q1: 3,487 1.00
(2022b) # dementia obtained through Q2: 5,757 0.73 (0.62, 0.88)
linkage with inpatient Q3: 8,294 0.57 (0.47, 0.70)
hospitalization or primary Q4: 13,152 0.65 (0.53, 0.79)
care records or recorded as
the underlying or
contributory cause of death
in death registers

48
Nguyen (2023) Women’s Health Incident probable dementia Q1: 934 1.00
Initiative Memory ascertained using annual Q2: 2,338 0.83 (0.53, 1.29)
Study (WHIMS) multi-stage clinical Q3: 3,430 0.65 (0.39, 1.08)
and OPACH evaluation of cognitive Q4: 4,671 0.48 (0.26, 0.87)
functioning followed by
independent review and
adjudication by panel of
experienced clinicians
Studies not included in meta-analysis of cognitive outcomes
Study Cohort Outcome ascertainment Baseline Main findings
steps (mean
[SD] or
median
[IQR])
Chen (2020) Unnamed Subjective cognitive decline 4,733.91 Inverse dose-response
assessed using the Chinese (3,073.56) association of daily steps with
version of the Ascertain subjective cognitive decline rate
Dementia 8-item
Questionnaire (AD8)
Shibukawa (2024) Shiga Cognitive function assessed Q1: 4,134 Positive linear association
Epidemiological using the Cognitive Abilities (1,032) between daily steps and the
Study of Screening Instrument Cognitive Abilities Screening
Subclinical (CASI) score Q2: 6,685 Instrument score
Atherosclerosis (576)
(SESSA) Q3: 8,635
(581)
Q4: 11,812
(1,540)
MENTAL HEALTH
Studies included in meta-analysis of mental health outcomes
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
Chan (2022) # StandingTall Incident depressive Q1: 4,038 1.00
randomized symptoms assessed using Q2: 5,952 1.09 (0.58, 2.07)
controlled trial the Patient Health Q3: 7,925 1.15 (0.6, 2.17)
Questionnairee-9 (PHQ-9) Q4: 11,651 0.51 (0.26, 1.02)

Chan (2023b) # UK Biobank Depressive symptom onset Q1: 4,577 1.00

derived from first reported Q2: 6,770 0.83 (0.72, 0.95)
occurrence of a depressive Q3: 8,710 0.63 (0.53, 0.73)
episode (Code F32) Q4: 11,774 0.67 (0.57, 0.78)
according to the
International Classification
of Diseases, 10th revision
(ICD-10)
Master (2022) # All of Us Major depressive disorder Q1: 4,845 1.00
Research determined from electronic Q2: 6,994 0.67 (0.51, 0.86)
Program health records Q3: 8,937 0.72 (0.55, 0.95)
(AoURP) Q4: 11,703 0.54 (0.4, 0.74)

Studies not included in meta-analysis of mental health outcomes

Study Cohort Outcome ascertainment Baseline Adjusted Hazard Ratio
steps (mean
[SD] or
median
[IQR])
Hsueh (2021b) Unnamed Depressive symptoms 4,733.91 A 1,000-daily step increase was
assessed using the 15-item (3,073.56) linearly associated with a reduced
Geriatric Depression Scale rate of subsequent depressive
(GDS) symptoms (rate ratio [RR] = 0.95,
95% confidence interval [CI] =
0.92–0.98).

Raudsepp (2017) Unnamed Depressive symptoms 6,394.5 Bidirectional relationship between

assessed using the 15-item (841.4) step counts and depressive
GDS symptoms
Ramsey (2022) Precision Depressive symptom 3,545 Non-significant association
Medicine in severity assessed using the (1,819) between daily steps and
49
 Mental Health Patient Health depressive symptoms in final
Care study Questionnaire (PHQ-9) adjusted model
(PRIME Care)
PHYSICAL FUNCTION
Studies included in meta-analysis of physical function outcomes
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile
N/A
Studies not included in meta-analysis of physical function outcomes
Study Cohort Outcome ascertainment Baseline Adjusted Hazard Ratio
steps (mean
[SD] or
median
[IQR])
Hsueh (2021a) Unnamed Lower extremity Not reported Those who took at least 7,000
performance assessed steps per day had higher odds of
using five-times-sit-to-stand maintained or improved follow-up
test lower-extremity performance
(OR=3.53 [1.05–11.84]).
Makino (2019) National Center Functional disability 4,610.2 Taking fewer than 4,149.5
for Geriatrics and incidence determined from (2,435.5) steps/day was associated with
Gerontology monthly certification data of higher risk of functional disability
Study of Geriatric care needs according to the (HR: 1.79 [1.02-3.14].
Syndromes National Long Term Care
(NCGG-SGS) Insurance (LTCI) system
Taylor (2021) Unnamed Physical function was 4,439 Daily steps were not predictive of
assessed with (1) functional (3,137) changes in physical functioning as
independence measure measured with the FIM mobility
(FIM) administered by a score
credentialed assessor; (2)
de Morton mobility index
(clinician-observed
unidimensional measure of
mobility); (3) Frenchay
Activities index which
measures frequency of
domestic, outdoor and
leisure/work activities; and
(4) self-reported
participation in outdoor
walking
White (2014) Multicenter Incident functional limitation 7,073 Those who walked 5,000–7,499
Osteoarthritis defined using performance- (2,912) steps/day had 0.50 and 0.51 times
(MOST) Study based and self-reported the adjusted risk of incident
measures. Performance- functional limitation by the
based measure was performance-based and self-
defined as walking with a report measures, respectively,
gait speed <1 meter/sec. compared with those walking
Self-reported measure was <5,000 steps/day.
defined as scores of >28 of
68 on the Western Ontario Those who walked 7,500
and McMaster Universities steps/day had 0.31 and 0.41 times
Osteoarthritis Index the risk by performance-based
(WOMAC) physical function and self-report measures,
subscale. respectively, compared with those
walking <5,000 steps/day.

Each additional 1,000 steps/day

was associated with a 16% and
18% reduction in incident
functional limitation by the
performance-based and self-
report measures, respectively.
FALLS AND FALL-RELATED INJURIES
Studies included in meta-analysis of falls and fall-related injuries
Study Cohort Outcome ascertainment Median Adjusted Hazard Ratio
steps in
quartile

50
 Aranyavalai (2020) Unnamed Self-reported first fall Q1: 3,442 1.00
# episode; ‘fall’ defined as Q2: 5,219 0.32 (0.11, 0.87)
“inadvertently coming to rest Q3: 7,221 0.35 (0.13, 0.9)
on the ground, floor, or Q4: 10,546 0.32 (0.11, 0.98)
other lower level, excluding
intentional change in
position to rest in furniture,
wall or other objects”
Chan (2023a) # UK Biobank Injurious falls data from Q1: 4,106 1.00
NHS electronic inpatient Q2: 6,260 0.76 (0.66, 0.87)
records; ‘injurious falls’ Q3: 8,185 0.67 (0.58, 0.77)
defined as falls requiring Q4: 11,213 0.74 (0.65, 0.85)
inpatient medical care—
codes W01 to W19 in the
International Classification
of Disease 10th revision
(ICD10; UKB#41270)
Jefferis (2015) # British Regional Self-reported according to Q1: 2,923 1.00
Heart Study answers to the question: Q2: 4,535 0.87 (0.28, 2.73)
(BRHS) ‘‘Have you had a fall in the Q3: 6,132 2.42 (0.85, 6.87)
past 12 months?’’ [yes/no] Q4: 8,817 3.08 (1.03, 9.23)
and ‘‘If yes, how many falls
have you had in the past 12
months?’’
Schumacher (2022) OPACH Self-reported according to Q1: 1,092 1.00
daily completion of a 13- Q2: 2,700 0.85 (0.67, 1.07)
month falls calendar; ‘fall’ Q3: 3,907 0.84 (0.64, 1.09)
defined as “lost balance and Q4: 5,288 0.86 (0.64, 1.16)
fell to the ground or a lower
level or if they had to use a
wall, rail, or other object to
prevent themselves from
falling to the ground”
Studies not included in meta-analysis of falls and falls-related injuries
Study Cohort Outcome ascertainment Baseline Main findings
steps (mean
[SD] or
median
[IQR])
N/A
Note. * Reported a linear relationship as it was the best model fit. # Authors of the primary studies conducted further
analysis upon request to facilitate meta-analysis.

Abbreviations: ACM: all-cause mortality; CHD, coronary heart disease; CI: confidence interval; CVD, cardiovascular
disease; GDS: Geriatric Depression Scale; HF: heart failure; HR: hazard ratio; ICD: International Classification of
Diseases; IQR: interquartile range; MI: myocardial infarction; N/A: not applicable; NHS: National Health Service; Q,
quartile; SD, standard deviation; UK: United Kingdom.

51
Supplementary Table 3. Device characteristics
Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

All of Us Master 2022 OTH: Fitbit (wrist) More than 100 steps N/A
Research or at least 6 months
Program (AoURP) of monitoring

USA

AoURP Perry 2023 TRK: Fitbit (wrist) At least 10 hours per N/A
day
USA

British Regional Jefferis 2015 ACC (ActiGraph 3 or more valid days Step counts per minute
Heart Study GT3x): hip of at least 600 min
(BRHS)
UK

BRHS Jefferis 2019a ACC: Actigraph 3 or more valid days N/A

GT3x (hip) of at least 600 min
UK

BRHS Jefferis 2019b ACC: ActiGraph 3 or more days of at N/A

GT3X (hip) least 10 hours
UK

Coronary Artery Paluch 2021 ACC: ActiGraph 3 or more days of at Peak 30-minute, time at ≥100 steps/min
Risk Development 7164 (hip) least 10 hours
in Young Adults
(CARDIA)

USA

Estudo de Paula 2025 ACC: ActiGraph 4 or more days of at N/A

Longitudinal de GT3X+ (waist) least 16 hours
Saúde do Adulto including one
(ELSA-Brasil) weekend day
Brazil

Healthy Ageing Ballin 2020 ACC: Actigraph 4 or more days of at N/A

Initiative Study GT3X+ (hip) least 10 hours
(HAI)

Sweden

Hispanic Cuthbertson ACC: Actical 3 or more days of at Peak 30-minute, cadence of > 40, > 70,
Community 2022 (version B-1, least 10 hours and > 100 steps/min
Health Study / model 198–0200-
Study of Latinos 03) (hip)
(HCHS/SOL)

USA

Hunter Oftedal 2020 PED: Yamasa Digi 3 or more days of at N/A

Community Study Walker SW 200 least 9 hours

Australia

Kyoto-Kameoka Watanabe ACC: EW-NK52 4 days N/A

Study 2023a (waist)
Japan

52
Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

Kyoto-Kameoka Watanabe ACC: EW-NK52 4 days N/A

Study 2023b (waist)

Japan

Lifestyle Cochrane 2017 ACC: Actigraph 3 or more days of at Peak 30-minute

Interventions and GT3X (hip) least 10 hours
Independence for
Elders (LIFE)

USA

Multicenter White 2014 ACC: StepWatch At least 3 days N/A

Osteoarthritis Activity Monitor
(MOST) Study (ankle)

USA

Nateglinide and Kraus 2018 PED: Accusplit Not reported N/A

Valsartan in AE120 (wear
Impaired Glucose location not
Tolerance reported)
Outcomes
Research trial
(NAVIGATOR)

Various

NAVIGATOR Yates 2014 PED (waist) Not reported N/A

Various

National Center Makino 2019 ACC: GT40-020 7 or more days of at N/A

for Geriatrics and (wear location not least 10 hours
Gerontology reported)
Study of Geriatric
Syndromes
(NCGG-SGS)

Japan

NCGG-SGS Shimoda 2025 ACC: GT40-020 7 or more days of N/A

and HW-100 more than 10 hours
Japan
(waist)

National Health Del Pozo Cruz ACC: ActiGraph 1 day or more than 10 N/A
and Nutrition 2022a AM-7164 (hip) hours
Examination
Survey
(NHANES)

USA

NHANES Guo 2025 ACC: ActiGraph 1 day or more of at N/A

7164 (hip) least 10 hours
USA

NHANES Inoue 2023 ACC: ActiGraph 4 days of at least 10 N/A

7164 (waist) hours
USA

NHANES Saint-Maurice ACC: ActiGraph 1 day or more of at Extended bout cadence, peak 30-min
2020 7164 (hip) least 10 hours cadence, peak 1-min cadence
USA
(steps/min)

53
Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

NHANES Zhou 2023 ACC: ActiGraph 3 days of at least 10 N/A

7164 (hip) hours
USA

Objective Physical Garduno 2022 ACC: Actigraph 4 or more days of at Peak 30 min, time at ≥40 steps/min,
Activity and GT3X+ (hip) least 10 hours steps/day accumulated in bouts of ≥5 min
Cardiovascular
Health (OPACH)

USA

OPACH LaMonte 2024 ACC: ActiGraph 4 or more days of at N/A

GT3X+ triaxial least 10 hours
USA
accelerometer
(hip)

OPACH Schumacher ACC (GT3X+ 4 or more days of at N/A

2022 triaxial least 10 hours
USA
accelerometer)
(hip)

Precision Ramsey 2022 ACC: ActiGraph At least 95% of the N/A

Medicine in GT9X Link (wear day for 3 or more
Mental Health location not days in weeks 1-4
Care study reported)
(PRIME Care)

USA

Project OPAL Fox 2015 ACC (Actigraph 5 or more days of at N/A

(Older People and GT1Ms) (waist) least 10 hours
Active Living) &
OPAL-PLUS
UK

Shiga Moniruzzaman PED: Yamasa Digi Not reported N/A

Epidemiological 2020 Walker DW 200
Study of (waist)
Subclinical
Atherosclerosis
(SESSA)

Japan

SESSA Shibukawa 2024 PED: DIGI- Complete step count N/A

Walker, DW-200 data for 7 consecutive
Japan
(waist) days without any
outliers (i.e. less than
500 or more than
20,000 steps/day)

StandingTall Chan 2022 ACC: Not reported Gait quality parameters comprised
randomized MoveMonitor, walking speed and stride frequency.
controlled trial McRoberts (waist) However, these were not reported
separately in the study.
Australia

Strong Heart Fretts 2023 PED: AE120 (hip) 3 days N/A

Family Study
(SHFS)

USA

SHFS Pan 2023 PED (hip) 4 or more days N/A

USA

54
Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

The Tasped Dwyer 2015 PED (waist) Not reported N/A

Prospective
Cohort Study

Australia

Toledo Study for Mañas 2022 ACC: ActiGraph 4 or more days of at Steps/min
Healthy Aging wGT3X-BT (hip) least 8 hours

Spain

UK Biobank Ahmadi 2024 ACC: Axivity AX3 3 or more days of N/A

(dominant wrist) wear time greater
UK
than 16 hours, with at
least one weekend
day and monitor worn
during sleep periods

UK Biobank Chan 2023a ACC: AX3 by Not reported Gait Speed and Intensity: assessed by
Axivity Ltd (wrist) usual and maximal walking speed
UK
defined as median and the 95th
percentile of daily walking speed; median
and the interquartile range of cadence.

UK Biobank Chan 2023b ACC: AX3 by Not reported Gait speed and intensity (Usual walking
Axivity Ltd (wrist) speed, Maximal walking speed, Cadence
UK
median)

UK Biobank Del Pozo Cruz ACC: Axivity AX3 3 or more days of Incidental steps (defined as <40steps per
2022b (dominant wrist) wear time, greater minute (eg, indoor walking from one room
UK
than 16 hours to another));

Purposeful steps (defined as 40 or more

steps per minute (eg, steps while
exercising);

Peak 30-minute cadence (ie, average

steps per minute recorded for the 30
highest, not necessarily consecutive,
minutes in a day).

UK Biobank Del Pozo Cruz ACC: Axivity AX3 3 or more valid Cadence-based stepping metrics
2022c (dominant wrist) monitoring days, reflective of the free-living stepping
UK
including at least one context (incidental steps, <40 steps/min;
weekend day and purposeful steps, ≥40 steps/min); and
monitor worn during stepping intensity (peak-30 cadence
sleep periods defined as average steps/min for the 30
highest, but not necessarily consecutive,
min/d).

UK Biobank Schneider 2021 ACC: Axivity AX3 7 days N/A

(wrist)
UK

UK Biobank Shreves 2023b ACC: Axivity AX3 3 days Peak 30 min

(wrist)
UK

UK Biobank Small 2024 ACC: Axivity AX3 3 days One minute peak cadence
(wrist)
UK

Women’s Health Cuthbertson ACC: Actigraph 4 days of at least 10 Peak 10-minute, peak 30-minute,
Accelerometry 2024 GT3X+ (hip) hours cadence of ≥40, ≥70, and ≥100 steps/min
Collaboration
Cohort (WHAC)

55
Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

USA

Women’s Health Hamaya 2024 ACC: Actigraph 4 days of at least 10 N/A

study GT3X+ (hip) hours

USA

Women’s Health Lee 2019 ACC: ActiGraph 4 or more days of at Peak 1-minute cadence is the highest
study GT3X+ (hip) least 10 hours number of steps recorded in any single
minute of the day; peak 30-minute
USA
cadence is the mean steps per minute of
the 30 highest 1-minute epochs that need
not be consecutive. Maximum 5-minute
cadence is the mean steps per minute
across any consecutive 5-minute span of
the day with the highest number of steps.

Women’s Health Nguyen 2023 ACC: ActiGraph One or more day of at N/A
Initiative GT3X+ (hip) least 10 hours

USA

Unnamed Aranyavalai ACC (Actical At least 12 hours per N/A

2020 accelerometer) day from 6am to 6pm
Thailand
(wrist)

Unnamed Cavalheri 2023 ACC: Actigraph 2 or more days of at N/A

GT9X-Link (waist) least 10 hours
Australia

Unnamed Chen 2020 ACC: GT3X, 5 days of at least 10 N/A

Actigraph (waist) hours
Taiwan

Unnamed Hansen 2020 ACC: ActiGraph 4 or more days of at N/A

GT1M (waist) least 10 hours
Norway

Unnamed Hsueh 2021a ACC: Actigraph At least 4 weekdays N/A

(waist) and one weekend,
Taiwan
with 10 or more hours
per day

Unnamed Hsueh 2021b ACC: Actigraph At least 4 weekdays N/A

(waist) and one weekend,
Taiwan
with 10 or more hours
per day

Unnamed Raudsepp 2017 PED: Yamax- Pedometer was N/A

Digiwalker instructed to be worn
Estonia
pedometer (SW- for 7 days (no
200-024; minimum wear time
Warminster, PA) per day). Data was
(waistband of removed for any
clothing or belt at single day indicating
front of hip) less than 1000 steps.

Unnamed Tateuchi 2019 PED: EX-500 7 consecutive days N/A

(wear location not
Japan
reported)

Unnamed Taylor 2021 ACC: activPAL 6 full days N/A

(thigh)
Australia

56
 Cohort/ country Author/Year Device type Minimum wear time Stepping rate measures
(wear location) to be included

Unnamed Yamamoto 2018 PED: Yamax EC 4 or more days (no N/A

100S pedometer, minimum hours per
Japan
YAMASA, Tokyo day)
(waist)

Abbreviations: ACC, accelerometer; N/A: not applicable; OTH: other; PED: pedometer; TRK: tracker.

57
Supplementary Table 4. Covariates included in the most adjusted multivariable
analysis model of each included study

Cohort/ country Author/Year Covariates

All of Us Master 2022 steps (time-varying), age, sex, race, systolic blood pressure, CAD, cancer, smoking,
Research education, alcohol, BMI, baseline step counts (averaged over first 6 mo)
Program (AoURP)

USA

AoURP Perry 2023 age, sex, race, BMI, smoking status

USA

British Regional Jefferis 2015 age, region of residence, accelerometer wear time, season of accelerometer wear, falls
Heart Study history, number of chronic diseases, number of medications, depression score, vision
(BRHS) problems, living alone, sit-to-stand test

UK

BRHS Jefferis 2019a age, geographic region, season of wear, social class, alcohol intake, smoking, sleep time,
living status, BMI, mobility disability, MVPA, LIPA
UK

BRHS Jefferis 2019b age, region of residence, season of accelerometer wear, average accelerometer wear
time, social class, alcohol intake, smoking status, sleep time, living status, BMI, presence
UK
of mobility disability

Coronary Artery Paluch 2021 age, accelerometer wear time, race, sex, education level, study center, BMI, smoking
Risk Development status, alcohol intake, SBP, hypertension, diabetes, hyperlipidemia, history of CVD, self-
in Young Adults rated health
(CARDIA)

USA

Estudo de Paula 2025 study center, age, sex, race/color, degree of schooling, household income, smoking
Longitudinal de status, alcohol consumption, total energy intake, prevalent cardiovascular disease,
Saúde do Adulto hypertension, diabetes, chronic kidney disease, and self-perceived health status.
(ELSA-Brasil)

Brazil

Healthy Ageing Ballin 2020 sex, accelerometer wear time, visceral adipose tissue, sedentary time, education level,
Initiative Study number of other cardiometabolic risk factors and diseases (anticoagulants, elevated
(HAI) triglycerides, elevated blood pressure, previous stroke/myocardial infarction/angina
pectoris)
Sweden

Hispanic Cuthbertson age, sex, Hispanic/Latino heritage, HCHS/SOL field center, education, marital status,
Community 2022 employment, years lived in the US, self-rated general health, mobility limitations, cigarette
Health Study / packyears, alcoholic drinks per week, energy intake, the 2010 Alternative Healthy Eating
Study of Latinos Index (AHEI-2010), BMI, insulin resistance, prediabetes, report of occupational physical
(HCHS/SOL) activity

USA

Hunter Oftedal 2020 mean age, diet quality score, income, smoking status
Community Study
Australia

Kyoto-Kameoka Watanabe age, sex, population density, season of wear, body mass index, smoking status, alcohol
Study 2023a consumption status, family structure, educational attainment, economic status, denture
use, medication use, number of chronic diseases, frailty status

58
Cohort/ country Author/Year Covariates

Japan

Kyoto-Kameoka Watanabe age, sex, population, density, step count assessment season, body mass index, smoking
Study 2023b status, alcohol drinking, living alone, educational attainment, socioeconomic status,
denture use, medication use, number of chronic diseases, frailty
Japan

Lifestyle Cochrane 2017 randomization, accelerometer wear time, sex, race, age, education, living alone, marital
Interventions and status, history of diabetes mellitus, CVD, use of antihypertensive drugs, use of lipid
Independence for lowering drugs, ankle‐brachial index, systolic blood pressure, diastolic blood pressure,
Elders (LIFE) Pittsburgh Sleep Quality Index score
USA

Multicenter White 2014 age, sex, race, education, BMI, comorbidity, depressive symptoms, widespread pain,
Osteoarthritis knee pain severity, radiographic knee osteoarthritis, and study site
(MOST) Study

USA

Nateglinide and Kraus 2018 age, sex, region, race, BMI, systolic blood pressure, family history of diabetes, composite
Valsartan in of history of myocardial infarction, unstable angina or coronary revascularization, fasting
Impaired Glucose glucose, 2-hour glucose on oral glucose tolerance test, hemoglobin A1C, low-density
Tolerance lipoprotein cholesterol, high-density lipoprotein cholesterol, platelet count, hemoglobin
Outcomes concentration
Research trial
(NAVIGATOR)

Various

NAVIGATOR Yates 2014 adjusted for randomised treatment group and the following variables at baseline: body-
mass index, age, region (North America, Europe, Asia, Latin America, other), sex, current
Various
smoker status, coronary heart disease composite (previous myocardial infarction, angina,
positive stress test, or coronary revascularisation), cerebrovascular composite (stroke,
transient ischaemic attack), significant abnormal electrocardiogram, insignificant
abnormal ECG, albumin/creatinine ratio, pulmonary composite (pulmonary embolism or
deep venous thrombosis), peripheral artery disease composite (limb or foot amputation,
intermittent claudication, limb arterial bypass procedure), congestive heart failure, chronic
obstructive pulmonary disease, pulse pressure, temporary atrial fibrillation or flutter,
sodium, estimated glomerular filtration rate (eGFR), haemoglobin, LDL-cholesterol, and
antihypertensive medication use; change in body-mass index from baseline to 12-months;
change in body-mass index, the occurrence of unstable angina between baseline and 12
months and change in eGFR between baseline and 12 months.

National Center Makino 2019 basic characteristics (not specified), pain severity and site, gait speed, step counts, MVPA
for Geriatrics and
Gerontology
Study of Geriatric
Syndromes
(NCGG-SGS)

Japan

NCGG-SGS Shimoda 2025 age, sex, BMI, cancer, osteoarthritis, current drinking, education, physical frailty, Geriatric
Depression Scale (GDS), Mini-Mental State Examination (MMSE), CVD risk, self-rated
Japan
health

National Health Del Pozo Cruz age, sex, ethnicity, education, smoking, alcohol, diet, diabetes medication, and valid daily
and Nutrition 2022a wear time
Examination
Survey
(NHANES)
USA

59
Cohort/ country Author/Year Covariates

NHANES Guo 2025 age, sex, race, marital status, educational level, smoking status, drinking status, history of
diabetes mellitus, coronary heart disease, congestive heart failure, stroke
USA

NHANES Inoue 2023 age, sex, self-reported race and ethnicity, insurance status, marital status, smoking, BMI,
estimated glomerular filtration rate, statin use, history of diabetes, hypertension, CVD,
USA
cancer, emphysema, average daily step counts

NHANES Saint-Maurice age; sex; race/ethnicity; education; diet quality; alcohol consumption; smoking status;
2020 body mass index; self-reported health; mobility limitations; and diagnoses of diabetes,
USA
stroke, heart disease, heart failure, cancer, chronic bronchitis, and emphysema

NHANES Zhou 2023 age, race/ethnicity, poverty index ratio (PIR), education, marital status, BMI, alcoholic
drinks, smoking, diabetes, PA, general health
USA

Objective Physical Garduno 2022 age, race-ethnicity, education, self-rated health, family history of diabetes, number of
Activity and chronic conditions, physical functioning, alcohol consumption, current smoking status,
Cardiovascular BMI
Health (OPACH)

USA

OPACH LaMonte 2024 age, race, ethnicity, education, alcohol intake, smoking, self-rated general health, walking
device use, physical function score, history of hypertension, history of atrial fibrillation,
USA
multimorbidity score, body mass index, systolic and diastolic blood pressure, total:high-
density lipoprotein cholesterol ratio, log (triglycerides), log (C-reactive protein), and
glucose

OPACH Schumacher age, race/ethnicity, education, vision, body pain, alcohol use, sleep aid use, body mass
2022 index, number of chronic conditions, and Short Physical Performance Battery (SPPB)
USA

Precision Ramsey 2022 age, gender, race, BMI, baseline depressive symptoms, smoking, alcohol consumption,
Medicine in diabetes, physical functioning composite score
Mental Health
Care study
(PRIME Care)
USA

Project OPAL Fox 2015 age, gender, educational attainment, Index of Multiple Deprivation (IMD), weight status,
(Older People and GP Management System and number of self-reported chronic illnesses at baseline
Active Living) &
OPAL-PLUS

UK

Shiga Moniruzzaman age, smoking, drinking status, diabetes, dyslipidemia, hypertension

Epidemiological 2020
Study of
Subclinical
Atherosclerosis
(SESSA)

Japan

SESSA Shibukawa 2024 age (years), education (years), smoking (current/past/never), drinking
(current/past/never), hypertension (yes/no), diabetes mellitus (yes/no), lipid medication
Japan
(yes/no), and body mass index (kg/m2)

StandingTall Chan 2022 sex, whether the participant lives alone, diagnoses of dementia, depression, central
randomized nervous system lesion, dizziness, Parkinson’s disease, osteoarthritis, hand grip strength,
controlled trial choice reaction time, presence of abnormal sleeping duration, alternated sleep phase

60
Cohort/ country Author/Year Covariates

Australia

Strong Heart Fretts 2023 baseline age, sex, study site, education, smoking status, alcohol use, diet quality, BMI,
Family Study systolic blood pressure, prevalent diabetes, prevalent CVD, biomarker levels (fibrinogen,
(SHFS) LDL cholesterol, triglycerides), medication use (hypertensive or lipid-lowering agents),
and self-reported health status
USA

SHFS Pan 2023 age, sex, study center, education level, AHEI score, smoking, alcohol status, diabetes
status, hypertension status, LDL level, and BMI
USA

The Tasped Dwyer 2015 age, sex, BMI at baseline, total energy intake from all sources (kJ) at baseline, current
Prospective smoking status at baseline, alcohol consumption (g/day) at baseline, education at
Cohort Study baseline and study cohort
Australia

Toledo Study for Mañas 2022 accelerometer wear time, age, sex, BMI, education level, income, marital status,
Healthy Aging comorbidities

Spain

UK Biobank Ahmadi 2024 age, sex, ethnicity, education, smoking status, alcohol consumption, fruit and vegetable
consumption (servings per day), parental history of CVD and cancer, medication use
UK
(cholesterol, insulin and hypertension) and accelerometer-measured sleep time
(hours/day)

UK Biobank Chan 2023a sex, whether the participant lives alone, diagnoses of dementia, depression, central
nervous system lesion, dizziness, Parkinson’s disease, osteoarthritis, hand grip strength,
UK
choice reaction time, presence of abnormal sleeping duration, alternated sleep phase

UK Biobank Chan 2023b age range, body mass index, sex, marital status, average total household income,
education level, main mode of transportation, smoking status, drinking status, presence of
UK
abnormal sleeping duration, alternated sleep phase, and diagnoses of other severe
medical conditions

UK Biobank Del Pozo Cruz age, sex, race, education, Townsend deprivation index, smoking, alcohol use, fruit and
2022b vegetable consumption, family history of cardiovascular disease and cancer, medication
UK
use (cholesterol, insulin, and hypertension), accelerometer-measured sleep, and days
wearing accelerometer

UK Biobank Del Pozo Cruz age (years), sex (male/female), race (White; yes/no), education (university degree;
2022c yes/no), socioeconomic status (Townsend Deprivation Index), smoking
UK
(never/previous/current smoker), alcohol use (never/previous/occasional/within
guidelines/double guidelines/>double guidelines), fruit and vegetable consumption
(servings/d), family history of cancer and/or CVD(yes/no), medication use (cholesterol,
insulin, hypertension; yes/no), accelerometer measured sleep time (min), and number of
days accelerometer was worn.

For peak-30 cadence, models were adjusted for daily steps.

UK Biobank Schneider 2021 age, sex, body mass index, daily alcohol consumption

UK

UK Biobank Shreves 2023b age, sex, ethnicity, smoking status, alcohol consumption, education, Townsend
Deprivation Index, reproductive factors (use of oral contraception, use of hormone
UK
replacement therapy, menopausal status, parity)

UK Biobank Small 2024 sex, ethnicity, education, alcohol intake, smoking status, Townsend deprivation index,
processed meat intake, fresh fruit intake, oily fish intake, and added salt intake
UK

Women’s Health Cuthbertson age (continuous), race (non-Hispanic white, non-Hispanic Black/Hispanic/other), self-
Accelerometry 2024 rated health, education, smoking, alcohol intake, history of CVD, history of diabetes, use

61
Cohort/ country Author/Year Covariates

Collaboration of postmenopausal hormone therapy, history of cancer diagnosis, accelerometer wear

Cohort (WHAC) time, BMI/physical function

Women’s Health Hamaya 2024 age, accelerometer wear time, smoking status, alcohol drinking status, intakes of
study saturated fat, fiber, fruit and vegetables, postmenopausal hormone therapy, self-rated
health, cancer screening, parental history of MI before 60 years of age, family history of
USA
cancer

Women’s Health Lee 2019 age, wear time, smoking status, alcohol intake, diet, hormone therapy, family history of MI
study and cancer, history of CVD, cancer, and hypertension, general health, cancer screening,
BMI, cholesterol, diabetes
USA

Women’s Health Nguyen 2023 age, race, ethnicity, education, smoking status, alcohol use, diabetes, hypertension
Initiative RAND-36 physical functioning score, APOE ε4, BMI
USA

Unnamed Aranyavalai age, polypharmacy/psychotics drugs, medical condition and urinary incontinence
2020
Thailand

Unnamed Cavalheri 2023 lung cancer stage, neutrophil-to-lymphocyte ratio, usual sedentary bout duration

Australia

Unnamed Chen 2020 mean daily accelerometer time, excluding participants with ADL difficulty at baseline and
participants with depressive symptoms, and cognitive impairment at baseline
Taiwan

Unnamed Hansen 2020 sex, wear time, VPA, education level, BMI, smoking status, alcohol intake, number of
medical conditions
Norway

Unnamed Hsueh 2021a age, gender, education level, number of chronic diseases, ADL, accelerometer wear time,
baseline depressive symptoms, with the following additional exclusions:
Taiwan
Model 3: excluded participants with ADL difficulty at baseline

Model 4: excluded participants with GDS (Geriatric Depression Scale) scores at baseline
greater than 5

Model 5: excluded individuals with baseline cognitive impairment

Unnamed Hsueh 2021b age, gender, education level, number of chronic diseases, ADL, accelerometer wear time,
baseline depressive symptoms
Taiwan

Unnamed Raudsepp 2017 All 4 models were estimated with covariates regressed on the baseline measures.
Walking and depressive symptoms were adjusted for age, sex, and health status at T1.
Estonia

Unnamed Tateuchi 2019 age, minimum joint space width, comorbidity count, physical function at baseline

Japan

Unnamed Taylor 2021 baseline physical function, walking self‐confidence, health‐related quality of life, age, sex
and time since fracture
Australia

Unnamed Yamamoto 2018 sex, body mass index (continuous variable), cigarette smoking (never smokers, past
smokers, current smokers), alcohol intake (non, 1-2 times/week, 3-5 times/week, 6-7
Japan
times/week), and medication use (yes, no)

62
Supplementary Table 5. Funding sources of included studies
First author / year Funding source
Ahmadi 2024 Australian National Health and Medical Research Council (NHMRC) Investigator
Grant Leadership level 2 (APP 1194510) and a National Heart Foundation
Fellowship (APP 107158)

Aranyavalai 2020 Faculty of Medicine Vajira Hospital, Navamindradhiraj University.

Ballin 2020 Swedish Research Council (grant nr 201602589). Open Access funding
provided by University of Umea.
Cavalheri 2023 Cancer Council Western Australia Postdoctoral Research Fellowship. São Paulo
Research Foundation—FAPESP (grant #2019/16004-1 and #2022/04801-7).
Chan 2022 Australian National Health and Medical Research Council grant (APP1084739)
and an Australian Government Research Training Program (RTP) Scholarship.
Chan 2023a Australian Government Research Training Program (RTP) Scholarship.

Chan 2023b Australian Government Research Training Program (RTP) Scholarship.

Chen 2020 Ministry of Science and Technology of Taiwan (MOST 104-2410-H-018-028 and
MOST 1082811-H-018-500).
Cochrane 2017 National Institutes of Health/ National Institute on Aging Cooperative Agreement
#U01 AG22376 and a supplement from the National Heart, Lung, and Blood
Institute 3U01AG022376-05A2S, sponsored in part by the Intramural Research
Program, National Institute on Aging, NIH. Partially supported by the Claude D.
Pepper Older Americans Independence Centers at the University of Florida (1
P30 AG028740), Tufts University (1P30AG031679), University of Pittsburgh
(P30 AG024827), Wake Forest University (P30AG021332), and Yale University
(P30AG021342) and the NIH/NCRR CTSA at Stanford University (UL1
RR025744). Tufts University is supported by the Boston Rehabilitation
Outcomes Center (1R24HD065688-01A1). LIFE investigators are also partially
supported by the following: Academic Leadership Award (K07AG3587) from the
National Institute on Aging, Career Development Award from the Department of
Veterans Affairs, US Department of Agriculture, under agreement No. 58-1950-
0-014.

Cuthbertson 2022 Grant #R01HL136266 from the National Heart, Lung, and Blood Institute
(NHLBI). National Heart, Lung, and Blood Institute National Research Service
Award (T32-HL007055). The Hispanic Community Health Study / Study of
Latinos (HCHS/SOL) was carried out as a collaborative study supported by
contracts from the National Institutes of Health (NIH), National Heart, Lung, and
Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233),
University of Miami (N01-HC65234), Albert Einstein College of Medicine
(N01-HC65235), Northwestern University (N01-HC65236), and San Diego State
University (N01-HC65237)
Cuthbertson 2024 National Institutes of Health (NIH) 5R01CA227122: National Cancer Institute,
Office of the Director, Office of Disease Prevention, and Office of Behavioral and
Social Sciences Research. The Women’s Health Study is funded by NIH grants
CA154647, CA047988, CA182913, HL043851, HL080467 and HL099355. The
Women’s Health Initiative Objective Physical Activity and Cardiovascular Health
Study (WHI/OPACH) program is funded by NIH, National Heart, Lung and Blood
Institute (NHLBI) #75N92021D00001, 75N92021D00002, 75N92021D00003,
75N92021D00004, 75N92021D00005 and grant R01HL105065.
de Paula 2025 Department of Science and Technology, Brazilian Ministry of Health (Minist´erio
da Saúde), and the Brazilian Ministry of Science, Technology and Innovation
(Financiadora de Estudos e Projetos and Conselho Nacional de
Desenvolvimento Cientıfico e Tecnologico [CNPq]) through grants 405545/
2015-0 RS, 405551/2015- 0 BA, 405543/2015-8 ES, 405552/2015-7 MG,
405547/2015- 3 SP, and 405544/2015-4 RJ.

63
First author / year Funding source
Del Pozo Cruz 2022a Not reported

Del Pozo Cruz 2022b University of Southern Denmark; National Health and Medical Research Council
Australia investigator grant APP1194510.
Del Pozo Cruz 2022c University of Southern Denmark; National Health and Medical Research Council
(investigator grant No. APP1194510).

Dwyer 2015 National Health and Medical Research Council of Australia, the Commonwealth
Department of Health and Aged Care, Abbott Australasia, Alphapharm, Aventis
Pharmaceutical, AstraZeneca, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly
(Australia), GlaxoSmithKline, Janssen-Cilag (Australia), Merck Lipha, Merck
Sharp and Dohme (Australia), Novartis Pharmaceutical (Australia), Novo Nordisk
Pharmaceutical, Pharmacia and Upjohn, Pfizer, Roche Diagnostics, Sanofi
Synthelabo (Australia), Servier Laboratories (Australia), BioRad Laboratories,
Hitech Pathology, the Australian Kidney Foundation, Diabetes Australia,
Tasmanian Department of Health and Human Services, the Physiotherapy
Research Foundation, Perpetual Trustees, Brain Foundation, Royal Hobart
Hospital Research Foundation, ANZ Charitable Trust, Tasmanian Community
Fund; Arthritis Foundation of Australia and Masonic Centenary Medical
Research Foundation.
Fox 2015 Dunhill Medical Trust (R200/0511), Avon Primary Care Research Collaborative,
South West General Practice Trust, National Prevention Research Initiative
(G0501312) supported by the British Heart Foundation, Cancer Research UK,
Department of Health, Diabetes UK, Economic and Social Research Council,
Medical Research Council, Research and Development Office for the Northern
Ireland Health and Social Services, Chief Scientist Office, Scottish Executive
Health Department, Welsh Assembly Government and World Cancer Research
Fund.
Fretts 2023 Federal funds under contract numbers 75N92019D00027, 75N92019D00028,
75N92019D00029, and 75N92019D00030 from the National Heart, Lung, and
Blood Institute (NHLBI) and the NIH. Research grants R01HL109315,
R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and
cooperative agreements U01HL41642, U01HL41652, U01HL41654,
U01HL65520, and U01HL65521 from the NHLB.

Garduno 2022 R01HL105065 (to A.Z.L.) and 5R01CA227122 (to K.R.E.). National Institute on
Aging grant P01 AG052352, the National Institute of Diabetes and Digestive and
Kidney Diseases (R01 DK114945), and the Tobacco-Related Disease Research
Program (T31KT1501). NIH-funded predoctoral fellowship (T32MH122376). The
WHI program is funded by the National Heart, Lung, and Blood Institute, NIH,
U.S. Department of Health and Human Services (HHSN268201100046C,
HHSN268201100001C, HHSN268201100002C, HHSN268201100003C,
HHSN268201100004C, and HHSN271201100004C).
Guo 2025 Key Project of Hunan Provincial Science and Technology Innovation (No.
2020SK1014-2), and Key Research and Development Program of Hunan
Province (No. 2019SK2022).

Hamaya 2024 Grants CA154647, CA047988, CA182913, HL043851, HL080467, and HL09935
from the National Institutes of Health (for Women’s Health Study); grant
NIH5R01CA227122 from National Cancer Institute, Office of the Director, Office
of Disease Prevention, and Office of Behavioral and Social Sciences Research
(Dr Evenson); and the extramural research program at the National Heart, Lung,
and Blood Institute.

Hansen 2020 Norwegian Directorate of Health, the Norwegian School of Sport Sciences and
the Research Council of Norway (249932/ F20).

64
First author / year Funding source
Hsueh 2021a Ministry of Science and Technology of Taiwan (MOST 106-2410-H-003-144-
MY2; MOST 1092410-H-845-037-MY2; MOST 107-2410-H-003-117-MY2).
Hsueh 2021b None declared.

Inoue 2023 Grants from the Japan Agency for Medical Research and Development (AMED;
JP22rea522107), grants 21K20900 and 22K17392 from the Japan Society for
the Promotion of Science; Japan Endocrine Society; Meiji Yasuda Life
Foundation of Health and Welfare; and Program for the Development of Next-
Generation Leading Scientists With Global Insight sponsored by the Ministry of
Education, Culture, Sports, Science and Technology, Japan.

Jefferis 2015 National Institute for Health Research Postdoctoral Fellowship (PDF-2010-03-
23). British Heart Foundation program grant (RG/08/013/25942). National
Institute for Health Research National School of Primary Care project number
80. National Health and Medical Research Council (Australia) Postdoctoral
Fellowship (571150).
Jefferis 2019 British Heart Foundation (PG/13/86/30546 and RG/13/16/30528) and the
National Institute of Health Research (Post-Doctoral Fellowship 2010-03-023).
Kraus 2018 Novartis, Inc. NIHR Diet, Lifestyle and Physical Activity Biomedical Research
Unit, Leicester, UK. NIDDK/NIA grant DK081559.
LaMonte 2024 National Heart, Lung, and Blood Institute, National Institutes of Health, and US
Department of Health and Human Services through contracts
75N92021D00001,75N92021D00002, 75N92021D00003,75N92021D0004,
75N92021D00005. HL105065 and HL153462, with additional funding HL151885,
HL130591, and HL150170 from the National Heart, Lung, and Blood Institute.
Lee 2019 Grants from the National Institutes of Health (CA154647,
CA047988,CA182913,HL043851, HL080467,and HL099355).
Makino 2019 Strategic Basic Research Programs (RISTEX Redesigning Communities for
Aged Society), Japan Science and Technology Agency; and Health and Labor
Sciences Research Grants.
Mañas 2022 Biomedical Research Networking Center on Frailty and Healthy Aging
(CIBERFES) and by European Regional Development Fund (FEDER) funds
from the European Union (CB16/10/00477, CB16/10/00456, and
CB16/10/00464). Further funded by grants from the government of Castilla-La
Mancha (PI2010/020; Institute of Health Sciences, 03031-00), by the Spanish
government (Spanish Ministry of Economy and Competitiveness (Ministerio de
Economıa y Competitividad), Institute of Health Carlos III (Instituto de Salud
Carlos III), PI10/01532, PI031558, PI11/01068) and by European grants
(Seventh Framework Programme: FRAILOMIC FP7-305483-2).
Master 2022 National Institutes of Health, Office of the Director: Regional Medical Centers (1
OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2
OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2
OD026551; 1 OT2 OD026555; IAA: AOD21037, AOD22003, AOD16037,
AOD21041), Federally Qualified Health Centers (HHSN 263201600085U), Data
and Research Center (5 U2C OD023196), Biobank (1 U24 OD023121), The
Participant Center (U24 OD023176), Participant Technology Systems Center (1
U24 OD023163), Communications and Engagement (3 OT2 OD023205; 3 OT2
OD023206) and Community Partners (1 OT2 OD025277; 3 OT2 OD025315; 1
OT2 OD025337; 1 OT2 OD025276). R01 HL146588 and 1 R61 HL158941-
01A1.

65
First author / year Funding source
Moniruzzaman 2020 Japan Society for the Promotion of Science KAKENHI Grant Number (A)
13307016, (A) 17209023, (A) 21249043, (A) 23249036, (A) 25253046, (A)
15H02528, (A) 18H04074, (B) 26293140, (B) 24790616, (B) 21790579, (B)
18H03048, and (B) 15K19225, (C) 23590790 from the Ministry of Education,
Culture, Sports, Science, and Technology Japan, and by the grant
R01HL068200, from Glaxo-Smith Kline GB.

Nguyen 2023 National Institute on Aging, Grant/Award Numbers:P01AG052352,

5T32AG058529-04; National Heart, Lung, and Blood Institute,
Grant/AwardNumbers: R01 HL105065,75N92021D00001,
75N92021D00002,75N92021D00003, 75N92021D00004,75N92021D00005
Oftedal 2020 CVRN Collaborative Project Grant (101584).
Paluch 2021 National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the
University of Alabamaat Birmingham (grant Nos. HHSN268201800005I and
HHSN268201800007I), Northwestern University (grant No.
HHSN268201800003I),University of Minnesota (grant No.
HHSN268201800006I),and Kaiser Foundation Research Institute (grant No.
HHSN268201800004I). Intramural Research Program of the National Institute on
Aging (NIA) and intra-agency agreement between NIA and NHLBI (grant No.
AG0005). National Institutes of Health (grant No. R01HL078972).
Pan 2023 Federal funds from the National Heart, Lung, and Blood Institute, National
Institute of Health, Department of Health and Human Services, under contract
numbers 75N92019D00027, 75N92019D00028, 75N92019D00029, &
75N92019D00030 and research grants: R01HL109315, R01HL109301,
R01HL109284, R01HL109282, and R01HL109319 and cooperative agreements:
U01HL41642, U01HL41652, U01HL41654, U01HL65520, and U01HL65521.
Oklahoma Shared Clinical and Translational Resources (U54GM104938) with an
Institutional Development Award (IDeA) from NIGMS.
Perry 2023 NHLBI R61 HL158941 NHLBI R01 HL146588 NIDDK R01 DK124845 The All of
Us Research Program is supported by the National Institutes of Health, Office of
the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1
OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD026552; 1 OT2
OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #:
AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data
and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The
Participant Center: U24 OD023176; Participant Technology Systems Center: 1
U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2
OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1
OT2 OD025337; 1 OT2 OD025276.
Ramsey 2022 Merit Review Award # 1P1 HX002375–01/ SDR 16–348 from the United States
(U.S.) Department of Veterans Affairs, Health Services Research and
Development Service. Mental Illness Research, Education, and Clinical Center
at the Corporal Michael J. Crescenz VA Medical Center (CMCVAMC). Janssen
Research & Development, LLC.
Raudsepp 2017 Estonian Research Council 10.13039/ 501100002301 (Grant. No. ETF 9224).

Saint-Maurice 2020 National Institutes of Health’s Intramural Research Program. Extramural Division
of Cancer Control and Population Sciences of the National Cancer Institute.
Individual fellowship grant awarded by the Fundacaoparaa Cienciae Tecnologia
(SFRH/BI/114330/2016) under the Programa Operacional Potencial
Humano/Fundo Social Europeu.

Schneider 2021 Walter-Benjamin Fellowship from the German Research Foundation (SCHN
1640/1-1). German Research Foundation (DFG) consortium (SCHN 1626/1-1).
National Institutes of Health T32 Training Grant (5T32DK007066-45).

66
First author / year Funding source
Schumacher 2022 The National Heart, Lung, and Blood Institute (grant number R01 HL105065 to
A.Z.L.). National Institute on Aging (P01 AG052352 to A.Z.L.). National Heart,
Lung, and Blood Institute, National Institutes of Health, U.S. Department of
Health and Human Services (contract numbers: HHSN268201600018C,
HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and
HHSN268201600004C).
Shibukawa 2024 JSPS KAKENHI Grant Number JP21249043, JP23249036, JP25253046,
JP23590790 from the Ministry of Education, Culture, Sports, Science and
Technology Japan, from Glaxo-Smith Kline GB (number N/A).
Shimoda 2025 Grant-in-Aid for Research Activity Start-up, Japan (JP23K19916); Grant-in-Aid
for Scientific Research (B), Japan (grant number: 23300205); Health Labour
Sciences Research Grant from the Japanese Ministry of Health, Labour and
Welfare (H24-tyoujyu-ippan-004); Strategic Basic
Research Programs (RISTEX Redesigning Communities for Aged Society),
Japan Science and Technology Agency; Research Project on Health and
Welfare Promotion for the Elderly; Research Funding for Longevity Sciences
from the National Center for Geriatrics and Gerontology, Japan (24-18, 25-26);
Japan Agency for Medical
Research and Development (grant numbers: JP15dk0107003 and
JP15dk0207004); and the Kao Corporation, Japan.

Shreves 2023 National Institutes of Health’s Intramural Research Program; National Institutes
of Health’s Oxford Cambridge Scholars Program; HDR UK, an initiative funded
by UK Research and Innovation, Department of Health and Social Care
(England) and the devolved administrations; Cancer Research UK (grant
number C16077/A29186); Novo Nordisk; Wellcome Trust (223100/Z/21/Z); 354
355 356 357 358 British Heart Foundation Centre of Research Excellence (grant
number RE/18/3/34214); Cancer Research UK (grant number C8221/A29017).
Small 2024 No direct project funding. Indirect funding support from Wellcome Trust
(223100/Z/21/Z; 203141/Z/16/Z), Swiss Re, Health Data Research (HDR) UK,
NovoNordisk, BHF Centre of Research Excellence, University of Oxford
Clarendon Fund, MRC Population Health Research Unit, GlaxoSmithKline,
Amgen and UCB BioPharma, NIHR Oxford Biomedical Research Centre
Tateuchi 2019 JSPS KAKENHI Grant-in-Aid for Scientific Research (C) (grant no. 24500578).
Taylor 2021 Collaborative grant from La Trobe University's Research Focus Area on Sport,
Exercise and Rehabilitation, and Eastern Health Foundation.
Watanabe 2023a Research grants provided to Misaka Kimura (24240091), Yosuke Yamada
(15H05363), Daiki Watanabe (21K17699), and Tsukasa Yoshida (22H03525); a
grant and administrative support by the Kyoto Prefecture Community-based
Integrated Elderly Care Systems Promotion Organization since 2011; and
Kameoka City under the program of the Long-term Care Insurance and Planning
Division of the Health and Welfare Bureau for the Elderly, the Ministry of Health,
Labour and Welfare, and the WHO Collaborating Centre on Community Safety
Promotion.

Watanabe 2023b Research grant provided to Misaka Kimura (24240091), Yosuke Yamada
(15H05363), and Daiki Watanabe (21K17699);a grant and administrative support
by the Kyoto Prefecture Community-based Integrated older adults Care Systems
Promotion Organization since 2011; Kameoka City under the program of the
Long-term Care Insurance and Planning Division of the Health and Welfare
Bureau for the older adults, Ministry of Health, Labour, and Welfare; and the
World Health Organization (WHO) Collaborating Centre on Community Safety
Promotion.

67
First author / year Funding source
White 2014 NIH (grants AG-18820, AG-18832, AG18947, AG-19069, AR-007598, and AR-
47785), the National Institute of Arthritis and Musculoskeletal and Skin Diseases
(grant R01AR062506), the Rheumatology Research Foundation Investigator
Award, the Boston Rehabilitation Outcomes Center (grant R24HD0065688), the
Boston Claude D. Pepper Older Americans Independence Center (grant
1P30AG031679), and the Foundation for Physical Therapy Geriatric Research
Grant. Based on work supported by the US Department of Agriculture (under
agreement 58-1950-0-014).
Yamamoto 2018 Research grant (16 K01825) and a Grant-in-Aid for Scientific Research from the
National Institute of Fitness and Sports in Kanoya (President’s Discretionary
Budget).
Yates 2014 Novartis Pharmaceuticals.
Zhou 2023 Key Research and Development Program of Hunan Province (2020SK1014-2),
Natural Science Foundation of Hunan Province (2021JJ30924), Beijing Medical
and Health Public Welfare Fund (YWJKJJHKYJJ-B20370BS), Degree &
Postgraduate Education Reform Project of Central South University
(2022JGB008), and the National Natural Science Foundation of China
(81100221).

68
Supplementary Table 6. List of excluded studies and reasons for exclusion
First author and Title Exclusion reason
publication date
Al Najem 2022 Correlation of walking activity and cardiac Wrong outcome
hospitalizations in coronary patients for 1 year
post cardiac rehabilitation: the more steps, the
better!
Bai 2022 Ecological momentary assessment of physical Wrong outcome
activity and wellness behaviors in college
students throughout a school year: longitudinal
naturalistic study.
Blond 2023 Step your way to a longer life: examining the Wrong study design
relation between step counts, morbidity and
mortality.
Calamia 2018 Pedometer-assessed steps per day as a Wrong study design
predictor of cognitive performance in older
adults.
Cavalheri 2023a Association between physical activity and Wrong setting
reduced mortality in inoperable lung cancer.
Cioe 2019 The effect of increased physical activity on Wrong outcome
symptom burden in older persons living with
HIV.
Del Pozo-Cruz 2022b Optimal number of steps per day to prevent all- Wrong outcome
cause mortality in people with prediabetes and
diabetes.
Dondzila 2015 Dose-response walking activity and physical Wrong study design
function in older adults.
Duncan 2016 Dose-response between pedometer assessed Wrong study design
physical activity, functional fitness, and fatness
in healthy adults aged 50-80 years.
Dwyer 2015 Correction: Objectively measured daily steps Wrong study design
and subsequent long term all-cause mortality:
the Tasped prospective cohort study.
Fini 2021 Adherence to physical activity and Wrong outcome
cardiovascular recommendations during the
2years after stroke rehabilitation discharge.
Fleig 2016 Sedentary behavior and physical activity Wrong study design
patterns in older adults after hip fracture: a call
to action.
Fretts 2023c Ambulatory activity and risk of premature Wrong outcome
mortality among young and middle-aged
American Indian individuals.
Fulcher 2014 Greater physical activity is associated with Wrong study design
better cognitive function in heart failure.
Grunberg 2022 Fitbit activity, quota-based pacing, and Wrong exposure
physical and emotional functioning among
adults with chronic pain.
Hult 2019 Objectively measured physical activity in older Wrong study design
adults with and without diabetes.
Hussenoeder 2023 Physical activity and mental health: the Wrong study design
connection between step count and
depression, anxiety and quality of sleep.
Inada 2021 Trajectories of objectively measured physical Wrong exposure
activity and mood states in older Japanese
adults: longitudinal data from the Nakanojo
Study.
Jayakody 2023 The role of daily step count in determining risk Wrong exposure
factors for falls.

69
First author and Title Exclusion reason
publication date
Kringle 2023 Associations between daily step count Wrong exposure
trajectories and clinical outcomes among
adults with comorbid obesity and depression.
Lin 2022 Low daily step count is associated with a high Wrong setting
risk of hospital admission and death in
community-dwelling patients with cirrhosis.
Lunney 2021 Wearable fitness trackers to predict clinical Wrong outcome
deterioration in maintenance hemodialysis: a
prospective cohort feasibility study.
Minetama 2022 Associations between psychological factors Wrong outcome
and daily step count in patients with lumbar
spinal stenosis.
Mishra 2021 Decrease in mobility during the COVID-19 Wrong exposure
pandemic and its association with increase in
depression among older adults: a longitudinal
remote mobility monitoring using a wearable
sensor.
Moshe 2021 Predicting symptoms of depression and Wrong study design
anxiety using smartphone and wearable data.
Nagata 2021 Relationships among changes in walking and Wrong outcome
sedentary behaviors, individual attributes,
changes in work situation, and anxiety during
the COVID-19 pandemic in Japan.
Nickerson 2021 Effect of increasing physical activity on Wrong study design
cognitive function in individuals with mild
cognitive impairment: a knowledge translation
to practice pilot project.
Nishi 2023 Trends in mortality from major causes and Wrong exposure
lifestyle factors by per capita prefectural
income: Ecological panel data analysis from
1995 to 2016 in Japan.
Nishi 2024 Mortality from major causes and lifestyles by Wrong exposure
proportions of public assistance recipients
among 47 prefectures in Japan: Ecological
panel data analysis from 1999 to 2016.
Nyrop 2023 Association of self-directed walking with Wrong setting
toxicity moderation during chemotherapy for
the treatment of early breast cancer.
Paolillo 2023 Data-driven physical actigraphy patterns relate Wrong study design
to cognitive and vascular health in older adults.
Peven 2022 Physical activity, memory function, and Wrong study design
hippocampal volume in adults with Down
syndrome.
Prasad 2021 Physical activity decline is disproportionate to Wrong outcome
decline in pulmonary physiology in IPF.
Printz 2020 Increased daily step count associated with Wrong study design
lower mortality rates.
Rosenberg 2020 More daily steps are associated with lower Wrong study design
mortality.
Savica 2017 Comparison of Gait Parameters for Predicting Wrong exposure
Cognitive Decline: The Mayo Clinic Study of
Aging
Saint-Maurice 2020d Association of daily step count and step Wrong outcome
intensity with mortality among US adults.
Schumacher 2022e Accelerometer-measured daily steps, physical Wrong outcome
function, and subsequent fall risk in older
women: the Objective Physical Activity and

70
 First author and Title Exclusion reason
publication date
Cardiovascular Disease in Older Women
Study.
Shingai 2021 Cutoff points for step count to predict 1-year Wrong setting
all-cause mortality in patients with idiopathic
pulmonary fibrosis.
Shreves 2023 Dose-response of accelerometer-measured Full text not available
physical activity, step count, and cancer risk in
the UK Biobank: a prospective cohort analysis.
Spartano 2019 Association of accelerometer-measured light- Wrong study design
intensity physical activity with brain volume:
the Framingham Heart Study.
Trayers 2014 Associations of objectively measured physical Wrong study design
activity with lower limb function in older men
and women: findings from the Older People
and Active Living (OPAL) study.
Tsai 2016 Objectively measured physical activity and Wrong outcome
changes in life-space mobility among older
people.
Van Oeijen 2020 Performance and self-reported functioning of Wrong outcome
people with chronic idiopathic axonal
polyneuropathy: a 4-year follow-up study.
Walker 2021 Associations between physical function and Wrong study design
device-based measures of physical activity
and sedentary behavior patterns in older
adults: moving beyond moderate-to-vigorous
intensity physical activity.
Wang 2020 Can smartphone-derived step data predict Wrong outcome
laboratory-induced real-life like fall-risk in
community-dwelling older adults?
Winberg 2015 Physical activity and the association with self- Wrong study design
reported impairments, walking limitations, fear
of falling, and incidence of falls in persons with
late effects of polio.
Yates 2014f Association between change in daily Wrong outcome
ambulatory activity and cardiovascular events
in people with impaired glucose tolerance
(NAVIGATOR trial): a cohort analysis.
Yu 2023 Impact of daily step count on diabetes Wrong study design
management and complications among elderly
individuals - Jiangsu province, China, 2020-
2022.
Zabetian-Targhi 2021 The association between physical activity Wrong study design
intensity, cognition, and brain structure in
people with type 2 diabetes.
Zheng 2024 Free-living ambulatory physical activity and Wrong study design
cognitive function in multiple sclerosis: the
significance of step rate vs. step volume.
a
This study which was included in the systematic review related to all-cause mortality, was excluded
from the systematic review related to cancer.
b
This study which was included in the systematic review related to all-cause mortality, was excluded
from the systematic review related to type 2 diabetes.
c
This study which was included in the systematic reviews related to all-cause mortality and
cardiovascular disease, was excluded from the systematic review related to type 2 diabetes.

71
d
This study which was included in the systematic reviews related to all-cause mortality, cardiovascular
disease and cancer, was excluded from the systematic review related to type 2 diabetes.
e
This study which was included in the systematic review related to falls and falls-related injuries, was
excluded from the systematic review related to physical function.
f
This study which was included in the systematic review related to cardiovascular disease, was
excluded from the systematic review related to type 2 diabetes.

72
Supplementary Table 7. Risk of bias assessment
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

All of Us
Research
Master
2022         9 High

Program
(AoURP)

AoURP Perry 2023

        9 High

British
Regional Heart
Jefferis
2015      6 Medium

Study (BRHS)

BRHS Jefferis
2019a         9 High

BRHS Jefferis
2019b         9 High

Coronary Paluch
2021        8 High

Artery Risk
Development
in Young
Adults
(CARDIA)

Estudo
Longitudinal de
De paula
       8 High

Saúde do 2025

73
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

Adulto (ELSA-
Brasil)

Healthy Ageing
Initiative Study
Ballin 2020
        9 High

(HAI)

Hispanic Cuthbertso
n 2022         9 High

Community
Health Study /
Study of
Latinos

(HCHS/SOL)

Hunter
Community
Oftedal
2020         9 High

Study

Kyoto-
Kameoka
Watanabe
2023a         9 High

Study

Kyoto-
Kameoka
Watanabe
2023b         9 High

Study

Lifestyle
Interventions
Cochrane
2017      6 Medium

and
Independence

74
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

for Elders
(LIFE)

Multicenter
Osteoarthritis
White 2014
   NA     8 out of 8 High

(MOST)

Study

Nateglinide
and Valsartan
Yates 2014
     6 Medium

in Impaired
Glucose
Tolerance

Outcomes
Research
(NAVIGATOR)

NAVIGATOR Kraus 2018

        9 High

National
Center for
Makino
2019   NA     7 out of 8 High

Geriatrics and
Gerontology
Study of
Geriatric
Syndromes
(NCGG-SGS)

NCGG-SGS Shimoda
2025         9 High

75
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

National Health
and Nutrition
Del Pozo
Cruz 2022a        8 High

Examination
Survey
(NHANES)

NHANES Guo 2025

      7 High

NHANES Inoue 2023

       8 High

NHANES Saint-
Maurice        8 High

2020

NHANES Zhou 2023

      7 High

Objective
Physical
Garduno
2022         9 High

Activity and
Cardiovascular
Disease in
Older Women
(OPACH)

OPACH LaMonte
2024         9 High

OPACH Schumache
r 2022       7 High

76
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

Precision
Medicine in
Ramsey
2022       7 High

Mental Health
Care study
(PRIME Care)

Project OPAL
(Older People
Fox 2015
        9 High

and Active
Living) &
OPAL-PLUS

Shiga
Epidemiologica
Moniruzza
man 2020       7 High

l Study of
Subclinical
Atherosclerosis
(SESSA)

SESSA Shibukawa
2024   NA    6 out of 8

StandingTall
randomized
Chan 2022
     6 Medium

controlled trial

Strong Heart
Family Study
Fretts 2023
       8 High

(SHFS)

77
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

SHFS Pan 2023

       8 High

The Tasped
Prospective
Dwyer 2015
       9 High

Cohort Study

Toledo Study
for Healthy
Mañas
2022        8 High

Aging

UK Biobank Ahmadi
2024         9 High

UK Biobank Chan
2023a        7 High

UK Biobank Chan
2023b         9 High

UK Biobank del Pozo

Cruz 2022b         9 High

UK Biobank del Pozo

Cruz 2022c         9 High

UK Biobank Schneider
2021       6 Medium

UK Biobank Shreves
2023b         8 High

UK Biobank Small 2024

        9 High

78
Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

Women’s
Health
Cuthbertso
n 2024         9 High

Accelerometry
Collaboration
Cohort

Women’s
Health Study
Hamaya
2024         9 High

Women’s
Health Study
Lee 2019
        9 High

Women’s
Health Initiative
Nguyen
2023         9 High

Unnamed Aranyavalai
2020     5 Medium

Unnamed Cavalheri
2023      5 Medium

Unnamed Chen 2020

   NA   6 out of 8 Medium

Unnamed Hansen
2020         8 High

Unnamed Hsueh
2021a      6 Medium

Unnamed Hsueh
2021b      6 Medium

79
 Study Selection Comparability Outcome
e

Study Publicatio Representativenes Selection Exposure Outcome Assessmentf Follow Adequacyh Overall Quality
n sa b ascertainmentc d -upg score rating

Unnamed Raudsepp
2017       7 High

Unnamed Tateuchi
2019  NA   4 out of 8 Medium

Unnamed Taylor 2021

   NA    7 out of 8 High

Unnamed Yamamoto
2018       7 High

* Study quality assessment criteria were from the Newcastle-Ottawa Quality Assessment Scale for cohort studies.23 According to this scale, a study can be awarded a
maximum of one star for each item within the Selection and Outcome categories, and a maximum of two stars for Comparability. The overall score is determined by the total
number of stars. The overall score was then categorised into three levels: Low (0-3), Medium (4-6), and High (7-9).

a Representativeness: a star was given if the cohort was truly or somewhat representative of exposed individuals in the community.
b Selection: all studies were awarded a star due to the nature of the study design.
c Ascertainment exposure: a star was given if the step count was ascertained by secure record (e.g. accelerometer).
dOutcome: a star was given in the case of all-cause mortality, if the study excluded individuals with major chronic disease. In relation to the other health outcomes, a star was
given if the study excluded those with the same outcome of interest (e.g. for the cardiovascular disease outcome, they excluded those with existing cardiovascular disease).
For outcomes measured using continuous variables (typically physical function and cognitive decline), the item was rated NA.
eComparability: up to two stars could be given – one if the study adjusted for age and health, whether by way of statistical adjustment for confounders or exclusion of
participants; another star if they adjusted for other factors (even if they did not adjust for age and health).
fAssessment of outcome: a star was given if the health outcome was assessed by independent or blind assessment or confirmation of the outcome by reference to secure
records, or by record linkage.
g Follow-up: a star was given if there was at least 2 years’ follow-up.

80
h Adequacy of follow-up: a star was given if there was no loss to follow-up or any loss was unlikely to introduce bias.

81
 Supplementary Table 8. A summary of the pooled hazard ratios (HR) and 95% confidence interval (CI) for
1000-step increments in the meta-analyses (with 7,000 steps/day as the reference)
All-cause CVD CVD Cancer Cancer Type 2 Dementiaa Depressive Fallsa
mortalitya incidencea mortalitya incidenceb mortalitya diabetes symptomsb
Steps/day incidenceb
(k=14) (k=6) (k=3) (k=2) (k=3) (k=4) (k=2) (k=3) (k=4)
(n=161,176) (n=111,349) (n=120,758) (n=100,505) (n=105,660) (n=61,594) (n=79,699) (n=77,565) (n=94,901)
HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs) HR (95% CIs)
7,000 Reference Reference Reference Reference Reference Reference Reference Reference Reference
8,000 0.97 (0.95, 0.98) 0.98 (0.97, 0.98) 1.22 (1.01, 1.49) 0.99 (0.98, 1.00) 0.96 (0.94, 0.99) 0.99 (0.95, 1.02) 0.93 (0.88, 0.98) 0.95 (0.93, 0.98) 1.00 (0.97, 1.03)
9,000 0.93 (0.90, 0.96) 0.95 (0.94, 0.97) 1.51 (1.02, 2.24) 0.98 (0.95, 1.01) 0.93 (0.88, 0.98) 0.97 (0.9, 1.05) 0.89 (0.82, 0.97) 0.9 (0.86, 0.96) 1.00 (0.95, 1.06)
10,000 0.90 (0.86, 0.94) 0.93 (0.91, 0.95) 1.68 (1.02, 2.78) 0.97 (0.93, 1.01) 0.90 (0.82, 0.98) 0.96 (0.86, 1.07) 0.88 (0.79, 0.98) 0.86 (0.79, 0.93) 1.01 (0.93, 1.09)
11,000 0.87 (0.82, 0.92) 0.91 (0.88, 0.94) 1.50 (0.97, 2.33) 0.96 (0.91, 1.02) 0.86 (0.77, 0.97) 0.95 (0.82, 1.09) 0.89 (0.80, 1.00) 0.82 (0.73, 0.91) 1.01 (0.90, 1.12)
12,000 0.84 (0.78, 0.90) 0.89 (0.85, 0.92) 0.97 (0.79, 1.19) 0.95 (0.88, 1.02) 0.83 (0.72, 0.96) 0.93 (0.78, 1.12) 0.93 (0.82, 1.07) 0.78 (0.68, 0.89) 1.01 (0.88, 1.16)
Note: Post-hoc additional analyses are based on the same models as the primary analyses but using 7,000 steps/day, instead of 2,000
steps/day as the reference

82
Supplementary Table 9. Studies on cadence
Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

All-cause mortality (ACM)

Coronary Artery Paluch 2021 2005-06 USA 38-50 years; 2,110 ActiGraph 7164 1) Peak 30-min No significant association between
Risk Development (57.1%) (hip) cadence cadence and ACM adjusted for steps
in Young Adults volume.
2) Time spent at
(CARDIA) ≥100 steps/min HR (95% CI) for Tertile 3 vs Tertile 1:
1) 0.98 (0.54-1.77)

2) 1.38 (0.73-2.61)

National Health Saint- 2003-06 USA 40+ years; 4,840 ActiGraph 7164 1) Bout cadence No significant association between
and Nutrition Maurice (53.5%) (hip) cadence and ACM adjusted for steps
2) Peak 30-min
Examination 2020 volume.
cadence
Survey
e.g., Quartile 4 vs Quartile 1 based on
3) Peak 1-min
(NHANES) peak-30 min cadence:
cadence
HR (95% CI) = 0.90 (0.65-1.27)

Toledo Study for Mañas 2022 2012-14 Spain 65+ years; 768 ActiGraph Steps/min Steps/min significantly associated with
Healthy Aging and wGT3X-BT (hip) ACM (HR=0.89, 95% CI: 0.84-0.95),
(53.9%)
2015-17 without adjusting for total steps volume.

UK Biobank Del Pozo 2013-15 UK 40-69 years; 78,500 Axivity AX3 Peak 30-min Peak 30-min cadences was significantly
Cruz 2022c (55.3%) (dominant wrist) cadence associated with ACM (mean rate of change
per 10% peak 30-min cadence, −0.08; 95%
CI, −0.10 to −0.05)

Women’s Health Lee 2019 2011-15 USA 62-101 16,741 ActiGraph GT3X+ Peak 1-min No significant association between
study years; (100%) (hip) cadence; cadence and ACM after adjusting for total
step counts.
(100%) peak 30-min
cadence; HR (highest vs lowest quartile) and 95%
CI:

83
Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

maximum 5-min Peak 1-min cadence: 0.87 (0.68-1.11);

cadence;
peak 30-min cadence: 0.86 (0.65-1.13);
Time spent at a
maximum 5-min cadence, 0.80 (0.62-1.05);
stepping rate of
40+ steps/min Time spent at a stepping rate of 40+
steps/min, 1.27 (0.96-1.68)

Cardiovascular disease (CVD)

NHANES Saint- 2003-06 USA 40+ years; 4,840 ActiGraph 7164 1) Bout cadence No significant association between
Maurice (53.5%) (hip) cadence and CVD mortality once adjusted
2) Peak 30-min
2020 for steps volume.
cadence

3) Peak 1-min
cadence

Lifestyle Cochrane 2010-13 USA 70-89 years; 1,590 Actigraph GT3X Peak 30-min No significant association between
Interventions and 2017 (67.2%) (hip) cadence cadence and CVD events without adjusting
Independence for for steps volume.
Elders (LIFE)
HR (95% CI) = 0.99 (0.97–1.00)

UK Biobank Del Pozo 2013-15 UK 40-69 years; 78,500 Axivity AX3 Peak 30-min Peak 30-min cadence was significantly
Cruz 2022c (55.3%) (dominant wrist) cadence associated with CVD mortality (mean rate
of change per 10% peak 30-min cadence:
−0.14; 95% CI, −0.18 to −0.10) and CVD
incidence (−0.07; 95% CI, −0.08 to −0.06).

Cancer

NHANES Saint- 2003-06 USA 40+ years; 4,840 ActiGraph 7164 1) Bout cadence No significant association between
Maurice (53.5%) (hip) cadence and cancer mortality once
2) Peak 30-min
2020 adjusted for steps volume.
cadence

84
Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

3) Peak 1-min
cadence

UK Biobank Del Pozo 2013-15 UK 40-69 years; 78,500 Axivity AX3 Peak 30-min Peak 30-min cadence was significantly
Cruz 2022c (55.3%) (dominant wrist) cadence associated with cancer mortality (mean
rate of change per 10% peak 30-min
cadence: −0.09; 95% CI, −0.13 to−0.05)
and cancer incidence (-0.04; 95% CI, -0.10
to -0.02)

UK Biobank Shreves 2013-15 UK 40-69 years; 86,556 Axivity AX3 Peak 30-minute No significant association between peak
2023 (56%) (dominant wrist) cadence 30-minute cadence and physical activity-
related cancer incidence after adjusting for
total step counts:

e.g., 120 vs 70 steps/min

HR (95% CI) = 0.88 (0.69-1.14)

Women’s Health Cuthbertson 2011-15 USA 62-97 years; 22,236 Actigraph GT3X+ 1) Peak 10-min More minutes at ≥40 steps/min and a faster
Accelerometry 2024 (100%) cadence peak 10- and 30-min step cadence were
Collaboration associated with a lower risk of endometrial
2) Peak 30-min
Cohort (WHAC) cancer; findings were attenuated after
cadence
adjustment for body mass index and
3) Minutes spent steps/day.
at ≥40, ≥70, and
1) Per a 10 step/min increase in peak 10-
≥100 steps per
min cadence, there was a 13% (HR = 0.87
min
[95% CI:0.79, 0.95]) lower risk of
endometrial cancer.

2) Per a 10 step/min increase in peak 30-

min cadence, there was a 12% (HR = 0.88
[95% CI: 0.79, 0.97]) lower risk of
endometrial cancer.

85
Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

3) Per 10-min increase for time spent at

≥40 steps/min, there was a 12% lower risk
of endometrial cancer (HR = 0.88 [95% CI:
0.79, 0.99]).

The HRs for step intensity and the risk of

colon, PA-related, and fatal cancers were
inverse but small and nonsignificant (HRs
ranged from 0.84 to 0.97). The HRs for
step intensity models with the risks of
breast, lung, ovarian, and total cancers
were close to 1.00.

Type 2 diabetes

Hispanic Cuthbertson 2008-11 USA 18-74 years; 6,634 Actical (version B- 1) Peak 30-min 1) HR (95% CI) for 100+ (highest)
Community 2022 (52%) 1, model 198– cadence steps/min vs <60 (lowest) steps/min:
Health Study / 0200-03) (hip)
2) Minutes spent 0.58 (0.41-0.82) based on 3 criteria
Study of Latinos
at ≥40, ≥70, and definition
(HCHS/SOL)
≥100 steps/min;
0.56 (0.35-0.89) based on 2 criteria
3) % of steps at definition
≥100 steps/min
2) HR (95% CI) for highest vs lowest
categories:

≥40 steps/min 0.78 (0.57, 1.07) based on 3

criteria definition

0.61 (0.43, 0.86) based on 2 criteria

definition;

≥70 steps/min

0.68 (0.51, 0.91) based on 3 criteria

definition

86
Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

0.65 (0.45, 0.94) based on 2 criteria

definition

≥100 steps/min

0.69 (0.53, 0.89) based on 3 criteria

definition

0.64 (0.47, 0.89) based on 2 criteria

definition

3) % of steps at ≥100 steps/min not

associated with incident diabetes

Total step counts not adjusted.

Objective Physical Garduno 2012-14 USA 63-99 years; 4,838 Actigraph GT3X+ 1) Peak 30-min None of the step cadence measures was
Activity and 2022 (hip) cadence; significantly associated with incident
(100%)
Cardiovascular diabetes.
Health (OPACH)
e.g., Per 20 steps/min increase in Peak 30-
2) % wear time min cadence:
with ≥40
steps/min HR (95% CI): 0.91 (0.81-1.02)

3) Average
steps/day
accumulated in
at lesast 5-min
bouts

Cognitive outcomes

UK Biobank Del Pozo 2013-15 UK 40-79 years; 78,430 Axivity AX3 Peak 30 min- There was an inverse dose-response
Cruz 2022b (55.3%) (dominant wrist) cadence relationship between peak 30 min-cadence

87
 Data source Study Study Country Sample Age Sample Accelerometer Cadence Main findings
entry range size model (wear measures
(female %) location)

and all-cause dementia after adjusting for

total step counts

The optimal dose was 112 steps per minute

(HR=0.38; 95% CI, 0.24-0.60).

Mental health outcomes

StandingTall Chan 2022 2015-17 Australi 70+ years; 322 MoveMonitor, Gait intensity in Gait intensity was not significantly
randomized a (62.1%) (62.1%) McRoberts (waist) the mediolateral associated with onset of depression in the
controlled trial (ML) axis and in adjusted models.
the
anteroposterior
(AP) axis

Falls and fall-related injuries

UK Biobank Chan 2023a 2013-15 UK 65+ years; 32,619 Axivity AX3 1) Usual and Only usual walking speed was significantly
(49.5%) (49.5%) (dominant wrist) maximal walking associated with time to first injuries fall HR
speed; (95% CI) = 0.98 (0.96–1.00).
2) Steps/min

Abbreviations: ACM, all-cause mortality; CI, confidence interval; CVD: cardiovascular disease; HR: hazard ratio; UK, United Kingdom; USA, United States of America.

88
Supplementary Table 10. Bayesian Information Criterion (BIC) statistics for each model

Outcome Linear Splines Quadratic Cubic Quadratic + cubic

All cause-mortality 22.03514 14.36944 9.640109 14.37858 5.752809
Cardiovascular incidence -9.22115 -11.9979 -12.6599 -11.8469 -10.6023
Cardiovascular mortality 11.97777 13.4808 12.47241 13.32763 11.29905
Cancer incidence -9.93714 -8.19452 -8.16782 -8.23318 -8.15198
Cancer mortality 6.264457 7.716925 6.571699 7.469407 4.698545
Type 2 diabetes 8.630524 10.99605 10.97428 10.99169 13.5345
Dementia 5.202639 -1.92979 -2.87126 -3.26499 -1.56053
Depressive symptoms -1.62881 -0.15712 0.294139 0.138643 0.020893
Falls 12.14924 11.36413 10.78277 10.71368 13.19529

89
Supplementary Figure 1. PRISMA flow chart for all-cause mortality

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Searching reference lists of

Records removed before
- PubMed (n=864) relevant papers (n=3)
screening:
- CINAHL (n=66) Searching Google Scholar
Duplicate records removed
(n=0)
(n=34)
Total (n=930)

Records excluded based on the

Records screened (n=896) title/abstract
(n=865)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=31) (n=0) (n=3)
Reports not retrieved
(n =0)

Reports excluded: (n=9)

Reports assessed for eligibility Wrong study design (n=4) Reports assessed for eligibility
Wrong exposure (n=2) Reports excluded: (n=0)
(n=31) (n=3)
Wrong setting (n=2)
Wrong outcome (n=1)

Studies included in the

Included

systematic review
(n=25)

Studies included for meta-

analysis (n=14)

90
Supplementary Figure 2. PRISMA flow chart for cardiovascular disease

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=996) screening: relevant papers (n=3)
- CINAHL (n=131) Duplicate records removed Searching Google Scholar
(n=80) (n=0)
Total (n=1,127)

Records excluded based on the

Records screened (n=1,047) title/abstract
(n=1,031)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=16) (n=0) (n=3)
Reports not retrieved
(n =0)

Reports excluded: (n=5)

Reports assessed for eligibility Wrong outcome (n=2) Reports assessed for eligibility
Reports excluded: (n=0)
(n=16) Wrong study design (n=2) (n=3)
Wrong exposure (n=1)
Included

Studies included in the

systematic review
(n=14)

Studies included in the CVD

incidence meta-analysis (n=6)
91
Studies included in the CVD
mortality meta-analysis (n=3)
Supplementary Figure 3. PRISMA flow chart for cancer

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=960) screening: relevant papers (n=0)
- CINAHL (n=82) Duplicate records removed Searching Google Scholar
(n=49) (n=0)
Total (n=1,042)

Records excluded based on the

Records screened (n=993) title/abstract
(n=987)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=6) (n=0) (n=0)
Reports not retrieved
(n =0)

Reports excluded: (n=2)

Reports assessed for eligibility Reports assessed for eligibility
Wrong setting (n=1) Reports excluded: (n=0)
(n=6) (n=0)
Full text not available (n=1)
Included

Studies included in the

systematic review (n=4)

Studies included in the cancer

incidence meta-analysis (n=2)

Studies included in the cancer 92

mortality meta-analysis (n=3)
Supplementary Figure 4. PRISMA flow chart for type 2 diabetes incidence

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=744) screening: relevant papers (n=3)
- CINAHL (n=89) Duplicate records removed Searching Google Scholar
(n=35) (n=0)
Total (n=833)

Records excluded based on the

Records screened (n=798) title/abstract
(n=790)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=8) (n=0) (n=3)
Reports not retrieved
(n =0)

Reports excluded: (n=5)

Reports assessed for eligibility Reports assessed for eligibility
Wrong outcome (n=4) Reports excluded: (n=0)
(n=8) (n=3)
Wrong study design (n=1)
Included

Studies included in the

systematic review
(n=6)

Studies included in the meta-

analysis (n=5)
93
Supplementary Figure 5. PRISMA flow chart for cognition
Identification of studies via databases and registers Identification of studies via other methods

Records identified from:

Identification

Databases (n=2) Records identified from:

Records removed before
- PubMed (n=451) Searching reference lists of
screening:
- CINAHL (n=60) relevant papers (n=1)
Duplicate records removed
Searching Google Scholar
(n=36)
Total (n=511) (n=0)

Records excluded based on the

Records screened (n=475) title/abstract
(n=461)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=14) (n=0) (n=1)
Reports not retrieved
(n =0)

Reports excluded: (n=11)

Reports assessed for eligibility Wrong study design (n=9) Reports assessed for eligibility
Reports excluded: (n=0)
(n=14) Wrong exposure (n=1) (n=1)
Wrong outcome (n=1)
Included

Studies included in the

systematic review (n=4)

Studies included in the meta-

analysis (n=2)

94
Supplementary Figure 6. PRISMA flow chart for mental health
Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=825) screening: relevant papers (n=1)
- CINAHL (n=149) Duplicate records removed Searching Google Scholar
(n=90) (n=0)
Total (n=974)

Records excluded based on the

Records screened (n=884) title/abstract
(n=865)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=19) (n=0) (n=1)
Reports not retrieved
(n =0)

Reports excluded: (n=14)

Reports assessed for eligibility Wrong outcome (n=7) Reports assessed for eligibility
Wrong exposure (n=4) Reports excluded: (n=0)
(n=19) (n=1)
Wrong study design (n=2)
Wrong setting (n=1)
Included

Studies included in the

systematic review (n=6)

Studies included in meta-

analysis (n=3)
95
Supplementary Figure 7. PRISMA flow chart for physical function

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=2,501) screening: relevant papers (n=1)
- CINAHL (n=368) Duplicate records removed Searching Google Scholar
(n=158) (n=0)
Total (n=2,869)

Records excluded based on the

Records screened (n=2,711) title/abstract
(n=2,697)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=1)
(n=14) (n=0) (n=1)
Reports not retrieved
(n=0)

Reports excluded: (n=9)

Reports assessed for eligibility Reports assessed for eligibility
Wrong outcome (n=4) Reports excluded: (n=0)
(n=14) (n=0)
Wrong study design (n=4)
Wrong exposure (n=1)
Included

Studies included in the

systematic review
(n=5)

Studies included in the meta-

analysis (n=0)
96
Supplementary Figure 8. PRISMA flow chart for falls and falls-related injuries

Identification of studies via databases and registers Identification of studies via other methods

Records identified from: Records identified from:

Identification

Databases (n=2) Records removed before Searching reference lists of

- PubMed (n=94) screening: relevant papers (n=0)
- CINAHL (n=32) Duplicate records removed Searching Google Scholar
(n=17) (n=0)
Total (n=126)

Records excluded based on the

Records screened (n=109) title/abstract
(n=102)
Screening

Duplicates records removed

Reports sought for retrieval Reports not retrieved Reports sought for retrieval (n=0)
(n=7) (n=0) (n=0)
Reports not retrieved
(n =0)

Reports excluded: (n=3)

Reports assessed for eligibility Wrong study design (n=1) Reports assessed for eligibility
Reports excluded: (n=0)
(n=7) Wrong outcome (n=1) (n=0)
Wrong exposure (n=1)

Studies included in the

Included

systematic review (n=4)

Studies included in the meta-

analysis (n=4)

97
Supplementary Figures 9-13. Subgroup analyses
Subgroup analyses
All-cause mortality

Supplementary Figure 9. The association between steps/day and health outcomes by

age group

Supplementary Figure 10. The association between steps/day and health outcomes by
device type

98
CVD incidence

Supplementary Figure 11. The association between steps/day and CVD incidence by
age group

Supplementary Figure 12. The association between steps/day and CVD incidence by
device type

99
Type 2 diabetes

Supplementary Figure 13. The association between steps/day and type 2 diabetes by
age group

100
Supplementary Figures14-19. Sensitivity analyses 1-3
All-cause mortality

Supplementary Figure 14. The association between steps/day and all-cause mortality
excluding studies that did not receive two stars for comparability under the Newcastle-
Ottawa Scale (i.e., did not adjust for age, health, and other factors; Sensitivity analysis
1)

101
Supplementary Figure 15. The association between steps/day and all-cause mortality
including all studies and adjusting for the clustering of studies within datasets
(Sensitivity analysis 2)

102
CVD incidence

Supplementary Figure 16. The association between steps/day and CVD incidence
including all studies and adjusting for the clustering of studies within datasets
(Sensitivity analysis 2)

103
Supplementary Figure 17. The association between steps/day and CVD incidence
excluding the study that reported odds ratios (Sensitivity analysis 3)

104
CVD mortality

Supplementary Figure 18. The association between steps/day and CVD mortality
including all studies and adjusting for the clustering of studies within datasets
(Sensitivity analysis 2)

105
Type 2 diabetes

Supplementary Figure 19. The association between steps/day and type 2 diabetes
including all studies and adjusting for the clustering of studies within datasets
(Sensitivity analysis 2)

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Supplementary Figures 20-26. Sensitivity analyses 4: Leave-one-out
analysis

Supplementary Figure 20. The association between steps/day and all-cause mortality
leaving out one study at a time.
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Del Pozo Cruz B, Ahmadi MN, Lee IM, Stamatakis E. Prospective
Associations of Daily Step Counts and Intensity With Cancer and Cardiovascular Disease
Incidence and Mortality and All-Cause Mortality. JAMA Intern Med 2022; 182(11): 1139-48.

Supplementary Figure 21. The association between steps/day and CVD incidence
leaving out one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Del Pozo Cruz B, Ahmadi MN, Lee IM, Stamatakis E. Prospective
Associations of Daily Step Counts and Intensity With Cancer and Cardiovascular Disease
Incidence and Mortality and All-Cause Mortality. JAMA Intern Med 2022; 182(11): 1139-48.

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Supplementary Figure 22. The association between steps/day and CVD mortality
leaving out one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Del Pozo Cruz B, Ahmadi MN, Lee IM, Stamatakis E. Prospective
Associations of Daily Step Counts and Intensity With Cancer and Cardiovascular Disease
Incidence and Mortality and All-Cause Mortality. JAMA Intern Med 2022; 182(11): 1139-48.

Supplementary Figure 23. The association between steps/day and cancer mortality
leaving out one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Saint-Maurice PF, Troiano RP, Bassett DR, Jr., et al. Association of
Daily Step Count and Step Intensity With Mortality Among US Adults. JAMA 2020; 323(12): 1151-
60.

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Supplementary Figure 24. The association between steps/day and type 2 diabetes
incidence leaving out one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Cuthbertson CC, Moore CC, Sotres-Alvarez D, et al. Associations
of steps per day and step intensity with the risk of diabetes: the Hispanic Community Health
Study / Study of Latinos (HCHS/SOL). Int J Behav Nutr Phys Act 2022; 19(1): 46.

Supplementary Figure 25. The association between steps/day and depressive

symptoms leaving out one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Chan LLY, Brodie MA, Lord SR. Prediction of Incident Depression
in Middle-Aged and Older Adults using Digital Gait Biomarkers Extracted from Large-Scale Wrist
Sensor Data. Journal of the American Medical Directors Association 2023; 24(8): 1106-13.e11.

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Supplementary Figure 26. The association between steps/day and falls leaving out
one study at a time
Note. Each line corresponds to a meta-analysis performed after removing one specific study.
The most influential study was Chan LLY, Arbona CH, Brodie MA, Lord SR. Prediction of injurious
falls in older adults using digital gait biomarkers extracted from large-scale wrist sensor data.
Age Ageing 2023; 52(9).

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Supplementary Figure 27. Funnel plot for all-cause mortality

Supplementary Figure 27. Funnel plot for all-cause mortality

Abbreviation: HR, hazard ratio.

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Supplementary Figures 28-29 cadence meta-analyses

Supplementary Figure 28. The association between peak 30-minute step cadence and
all-cause mortality, adjusting for total daily steps

Supplementary Figure 29. The association between peak 30-minute step cadence and
cancer mortality, adjusting for total daily steps

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