Original Article

Global Advances in Health and Medicine

Volume 10: 1–9
Overweight/Obesity and Associated ! The Author(s) 2021
Article reuse guidelines:
Factors Among Second Cycle sagepub.com/journals-permissions
DOI: 10.1177/21649561211017883
Primary School Children in Kirkos journals.sagepub.com/home/gam

Sub-City, Addis Ababa, Ethiopia

Kidus Fitsum, MPH1, Gudina Egata, PhD2, Melake Demena, MPH3,

and Berhe Gebremichael, MPH3

Abstract
Background: Although overweight/obesity is becoming a public health issue in low income countries, there is a paucity of
evidence concerning overweight/obesity in Ethiopia. The aim of the study was to assess the magnitude of overweight/obesity
and associated factors among second cycle primary school children in Kirkos Sub-City, Addis Ababa, Ethiopia.
Methods: A school based cross-sectional study was conducted among 482 children from May to June, 2019. Data were
collected using a questionnaire and checklist. Data were entered using EpiData version 3.1 and exported into SPSS version
22.0. Bivariable and multivariable logistic regression analyses were done to identify factors associated with overweight/
obesity. Level of statistical significance was declared at p
0.05.
Results: The overall magnitude of overweight/obesity was 21.2%. The magnitude of overweight was 13.7% while obesity
was 7.5%. Vehicle availability, being from private school, not having friend(s), preferring sweet foods, eating breakfast irreg-
ularly, watching movies/Television while eating and physical inactivity were the factors significantly associated with over-
weight/obesity among second cycle primary school children.
Conclusions: The magnitude of overweight/obesity was high in the study area. Therefore, health and education sectors
should promote healthy lifestyle to curb child overweight/obesity.

Keywords
Addis Ababa, children, Kirkos Sub-City, obesity, overweight, second cycle primary school
Received October 9, 2020; Revised April 14, 2021. Accepted for publication April 23, 2021

Background
problem in many countries worldwide, and is a major
Overweight and obesity are defined as abnormal or public health challenge of the 21st century.2,3
excessive fat accumulation caused by an energy imbal- The prevalence of overweight and obesity among
ance between calories consumed and calories expended. children and adolescents aged 5–19 years has risen dra-
For children aged between 5–19 years, overweight is matically worldwide from just 4.0% in 1975 to just over
defined as body mass index (BMI)-for-age greater than
one standard deviation above the World Health
Organization (WHO) growth reference median, and obe- 1
Nutrition Team, Maternal and Child Health Directorate, Addis Ababa City
sity is greater than two standard deviations above the Administration Health Bureau, Addis Ababa, Ethiopia
WHO growth reference median.1 2
School of Public Health, College of Health Sciences, Addis Ababa
Globally, there has been an increased intake of University, Addis Ababa, Ethiopia
3
School of Public Health, College of Health and Medical Sciences,
energy-dense foods that are high in fat and an increase
Haramaya University, Harar, Ethiopia
in physical inactivity due to the increasingly sedentary
Corresponding Author:
nature of many forms of work, changing modes of trans- Berhe Gebremichael, School of Public Health, College of Health and
portation, and increasing urbanization. The childhood Medical Sciences, Haramaya University, Harar, Ethiopia.
obesity epidemic has become a serious public health Email: berhegere09@gmail.com

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-
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us/nam/open-access-at-sage).
2 Global Advances in Health and Medicine

18.0% in 2016.1 The number of children who were over- Ethiopia. It has 11 districts, and the total estimated pop-
weight or obese has nearly doubled from 5.4 million in ulation was 125,372 according to the Ethiopian Central
1990 to 10.6 million in 2014 in Africa.4 In the Sub- Statistical Agency projection for 2018. 15 There are 21
Saharan Africa (SSA), about 10.6% of school age chil- governmental, 20 private, 1 non-governmental organiza-
dren were overweight/obese, of which 2.5% were obese.5 tion and 2 public elementary schools in the sub-city.
Ethiopia is one of the SSA countries where 11.3% of The total number of students attending in primary
children and adolescents were overweight or obese schools of the sub-city was 21,843 (10,852 males and
nationally in 2018.6 The highest magnitude was reported 10,991 females).16 The study population for this study
in a study conducted in Dire Dawa City in 2016, which was children who were attending second cycle primary
was 20.5%.7 education of Kirkos Sub-City in Addis Ababa and their
Different studies showed that being female,8 having no parents/guardians.
close friend(s),7 learning in private school8–10 and avail-
ability of vehicle5,9,11 were positively associated with over- Sample Size Estimation and Sampling Procedure
weight/obesity among children. Similarly, physical
inactivity,8,12 long duration of watching movies/TV,7,12 The required sample size to assess the magnitude of
having the habit of watching movies/TV while overweight/obesity was determined using a formula for
eating,11,12 not participating in different activities after single population proportion, n=(Za/2)2p(1p)deff/(d)2,
school,9 poor consumption of fruits and vegetables,5,6 with the following assumptions: the corresponding stan-
sweet food preference,6,7,9 and fast foods consumption5 dard value (Za/2) at 95% confidence level ¼ 1.96, margin
were also positively associated with overweight/obesity. of error (d) ¼ 5%, design effect (deff) ¼ 2 and proportion
As a result of rapid demographic, epidemiological and of overweight/obesity (p) among school age children
economic transitions attributed to increased urbanization from previous study in Bahir Dar City ¼ 12%.5 This
and globalization, many SSA countries are experiencing resulted in a sample size of 324. Adding 10% for non-
lifestyle and behavioral changes such as unhealthy diet, response rate, the sample size was 356.
physical inactivity, and increased substance use. Ethiopia, The desired sample size to identify factors associated
one of the SSA countries, is currently experiencing a with the occurrence of overweight/obesity was calculated
nutrition transition with increased intake of inorganic in Epi Info software version 7 with the following
foods and foods with high fat content, increased seden- assumptions: confidence level ¼ 95%, power ¼ 80%,
tary lifestyle, changing modes of transportation and unexposed to exposed ratio ¼ 1, design effect ¼ 2, pro-
increasing urbanization. Consequently, it is common to portion of overweight/obese (p1) among children who
see overweight/obese children in the urban part of the consumed sweet foods ¼ 29% and those who did not
country.13,14 However, there is limited information consume (p2) ¼ 13%,7 and 10% for non-response. This
regarding the magnitude of overweight/obesity and its provided a sample size of 497. Different predictor vari-
predictors among second cycle primary school children ables were assessed in the calculation of sample size for
nationwide especially in cities and towns where the prob- the factors associated with the overweight/obesity.
lem is increasing rapidly.7,9 However, the variable ‘consumption of sweet foods’ pro-
Since there is a growing demand to prevent non- vided the largest sample size.
communicable diseases starting at early ages, updated Finally, the sample size calculated for the factors
information on the prevalence of overweight/obesity associated with overweight/obese (497) was planned for
and associated factors, particularly of primary school chil- this study as it was greater than the calculated sample
dren, is paramount to design situation based and context- size for the magnitude of the overweight/obesity.
specific preventive strategies. Therefore, this study aimed Multistage stratified sampling technique was imple-
at assessing the magnitude of overweight/obesity and mented to select the study samples. First, the second
associated factors among second cycle primary school cycle primary schools located in Kirkos Sub-City were
children in Kirkos Sub-City, Addis Ababa, Ethiopia. stratified into private and governmental schools in which
we assumed overweight/obesity could vary across public
and private schools. Then, simple random sampling
Methods and Materials technique was used to select five schools from a total
of twenty-three governmental schools, and four schools
Study Setting and Population from a total of twenty-one private schools. The numbers
A school based cross-sectional study was conducted and lists of eligible children were obtained from the
from May to June, 2019 among second cycle primary directors’ offices of the selected schools, and sampling
school children aged 10-18 years in Kirkos Sub-City, frames were created for each selected school.
Addis Ababa, Ethiopia. Kirkos Sub-City is one of the The numbers of students to be included in this study
10 sub-cities found in Addis Ababa, the capital city of were determined for each selected school by probability
Fitsum et al. 3

proportion to size (PPS) sampling. Finally, simple measure the weight and height of the study participants.
random sampling technique was employed to select indi- During weight and height measurements, jackets, sweat-
vidual student (actual study participant) from each ers, shoes, bags and hair ornaments were avoided to min-
school (Figure 1). imize measurement errors. The measured height was
recorded to the nearest 0.1 centimeters while weight was
Data Collection Methods recorded to the nearest 0.1 kilograms. Three measure-
Structured interviewer administered questionnaire was ments were taken for a single child, and average of the
adapted from previous studies5,9 and modified to collect three measurements was used for analysis.17
the data. The questionnaire was initially prepared in To measure height, the study participants were
English language, and translated to the local language requested to stand erect with their shoulder level;
(i.e. Amharic) for data collection by language professio- hands were at the side and their head, scapula/shoulder
nals. The data collection tool (questionnaire) was pre- blade, buttock, calf and heel were in contact with the
tested on five percent of the sample size among children vertical measuring board. The height of study partici-
from second cycle primary schools which were not part pants was recorded to the nearest 0.1cm. Concerning
of the study. Data were collected on socio-demographic, weight measurement, the weight scale was readjusted to
lifestyle and diet related characteristics. Both the zero and calibrated, and placed on a leveled surface
students/children and their parents/guardians were with no object on it daily before measuring. The mea-
involved in the interview. Concerning the family/house- sured weight was recorded to the nearest 0.1 kg, and
hold characteristics, parents/guardians were interviewed. BMI-for-age Z-score (BAZ) was generated for each
For questions which were related (specific) to the stu- child using WHO AnthroPlus version 1.0.4 software.17
dents/children characteristics, both the children and Then, BAZ greater than or equal to 1 Standard
parents were interviewed; students’/children’s responses Deviation (SD) was considered as overweight, while
were used in the data for those aged 15 years and above BAZ greater than or equal to 2 SD was considered
while parents’/guardians’ responses were used for stu- as obesity.1
dents aged less than 15 years. After collection, the data All the data collection and measurements were con-
were translated back to English for analysis. ducted by four Diploma Nurses who had previous expo-
Checklists were used to collect data from anthropo- sure to data collection. The data collectors were
metric measurements. Digital weight scale, which has an supervised by two Public Health professionals who had
attached height scale with sliding head bar, was used to BSc degree.

Figure 1. Sampling Procedure Among Second Cycle Primary School Children in Kirkos Sub-City, Addis Ababa, Ethiopia, 2019.
4 Global Advances in Health and Medicine

Operational Definitions goodness-of-fit was checked by Hosmer-Lemeshow

test, and the final model was well fitted (p-value ¼ 0.36).
Moderate intensity exercise is defined as low impact aer-
The final model was performed to control for all possible
obic exercise like walking to school or playing on the
confounding variables and identify factors associated
playground (volleyball) whereas vigorous intensity exer-
with outcome variable by estimating AOR with 95%
cise is high-intensity aerobic exercise like competitive
CI. Level of statistical significance was declared at
full-field sports (soccer) or basketball, swimming, run-
p-value < 0.05.
ning, or gymnastic.9 According to the Ethiopian educa-
tion system, second cycle primary school/education
includes grades from 5 to 8.18 In this study, sweet Ethics Approval and Consent to Participate
foods mean foods with added sugar or sweetened foods. Ethical clearance was secured from Institutional Health
Research Ethics Review Committee of the College of
Data Quality Control Health and Medical Sciences at Haramaya University.
Informed, voluntary, written and signed consent was
Five percent of the questionnaire was pre-tested before
obtained prior to initiation of the study from each
the actual task of data collection in Kirkos Sub-City
child’s parent/guardian and school director. The inter-
Primary School. Data collectors were trained for four
views and measurements were carried out privately in
days on the data collection process to have a common
separate rooms. All possible identifiers were excluded
understanding. Standardization of anthropometric
from the questionnaires and checklists to ensure partic-
measurements was done by considering the investigators
ipants’ confidentiality.
as the criterion anthropometrist. Relative technical error
of measurement (%TEM) was done for each data col-
lector during the training to minimize anthropometric Results
measurement errors in the field. The data collectors
were closely supervised by the supervisors and investiga- Socio-Demographic Characteristics
tors. Completeness of each questionnaire was checked In this study, a total of 482 children aged 10-18 years
by the investigators daily. Data were double entered and their parents/guardians participated resulting in a
and validated to check for consistency. response rate of 96.9%. The mean (SD) age of the
children was 13.29 (1.63) years and 258 (53.5%) were
Data Processing and Analysis females. Majority of the children (91.9%) had close
The collected data were first checked for completeness friends and 342 (71%) had less than five siblings. Two
and coded. Then, the data were entered onto Epidata 3.1 hundred forty seven (51.2%) of the children were from
software and exported to SPSS version 20 software for governmental schools. One hundred fifty six (32.5%) of
data cleaning and analysis. BMI for Age Z-score (BAZ) the students’ mothers had an education up to college or
of the children was calculated using WHO Anthro plus above (Table 1).
version 1.0.4 software. The dependent variable was re-
coded to dichotomous outcomes as the following: chil- Diet Related Characteristics
dren with BAZ < 1 SD were coded as ‘0’ and those with- The study showed that 348 (72.2%) of the children usu-
> 1 SD were coded as ‘1’. Independent variables were ally eat their snack less than two times per day. Two
coded based on previous related studies and distribution hundred thirty seven (49.2%) and 309 (64.1%) of the
of responses in the data. Descriptive statistics was used
children consume fruits and vegetables three and more
for the overall description of the results. Categorical
days per week, respectively. On the other hand, 242
variables were described using frequency, percentage,
(50.2%) of the children listed sweet foods as their favor-
tables and figures. Continuous variables were assessed
ite foods. Most of the children (90%) reported that they
for normality and were described using appropriate sum-
buy and eat fast foods in addition to their usual meal
mary measures.
(Table 2).
Bivariable logistic regression analyses were used and
Crude Odds Ratio (COR) with 95% CI was computed to
assess the association between each independent and the
Lifestyle Related Characteristics
outcome variables. Variables with p-value < 0.25 during Out of the total children included in this study, 397
the bivariable analyses were included in the multivari- (82.4%) of them reported as they involve in any type
able logistic regression analysis. Multicollinearity of activity (i.e. helping ones parents/guardians in their
between independent variables was checked using daily activities) in addition to schooling. Regarding
Variance Inflation Factor (VIF), and no significant physical activity of the children, 371 (77%) of them
(VIF > 10) collinearity was detected. Model had the habit of playing in their compound. On the
Fitsum et al. 5

Table 1. Socio-Demographic Characteristics of Children Table 3. Lifestyle Characteristics of Children Attending Second
Attending Second Cycle Primary Schools in Kirkos Sub-City, Addis Cycle Primary Schools in Kirkos Sub-City, Addis Ababa, Ethiopia,
Ababa, Ethiopia, 2019 (n ¼ 482). 2019 (n ¼ 482).

Variables Categories Frequency Percent Variables Categories Frequency Percent

Sex Male 224 46.5 Additional activities (helping Yes 397 82.4
Female 258 53.5 parents/guardians) No 85 17.6
Number of sibling <5 342 71.0 after school
>5 140 29.0 Habit of playing in Yes 371 77.0
Maternal educational Unable to read 18 3.7 compound No 111 23.0
status and write Walking or bicycling <2 days 72 14.9
Able to read 55 11.4 (per week)a 3–4 days 45 9.4
and write 5–7 days 365 75.7
1–8 grade 113 23.4 Duration of watching <2 hours 271 56.2
9–12 grade 156 32.5 movies/TV (per day) >2 hours 211 43.8
College and above 140 29.0 Duration of siting (per day) <2 hours 286 59.4
Vehicle availability Yes 161 33.4 3–5 hours 118 24.5
of family No 321 66.6 6–8 hours 59 12.2
School type Governmental 247 51.2 >9 hours 19 3.9
Private 235 48.8 Habit of watching movies/ Yes 122 25.3
Having close friend(s) Yes 443 91.9 TV while eating No 349 72.4
No 39 8.1 Did not watch 11 2.3
movies/TV
Doing vigorous intensity <3 days 197 40.9
exercise (per week) >3 days 285 59.1
Table 2. Dietary Characteristics of Children Attending Second Doing moderate intensity <3 days 441 91.5
Cycle Primary Schools in Kirkos Sub-City, Addis Ababa, Ethiopia, exercise (per week) >3 days 41 8.5
2019 (n ¼ 482).
a
Frequency of continuous walking or bicycling at least for 10 minutes per
Variables Categories Frequency Percent week.

Frequency of snack <2 times 348 72.2

consumption (per day) >2 times 134 27.8 On the other hand, 28 (5.8%) of the children were under-
Frequency of fruit Do not eat fruit 59 12.2 weight (Figure 2).
consumption (per week) 1–2 days 186 38.6
>3 days 237 49.2 Factors Associated With Overweight/Obesity
Frequency of vegetable Do not eat 83 17.2
consumption (per week) vegetables Bivariable and multivariable analyses were done using
1–2 days 90 18.7 binary logistic regression to identify factors associated
>3 days 309 64.1 with overweight/obesity. In the bivariable analysis, vehi-
Preferring sweet foods Yes 242 50.2 cle availability, being from private school, not having
No 240 49.8 close friend(s), preferring sweet foods, eating breakfast
Fast food consumption Yes 434 90 irregularly, watching movies/TV while eating, and dura-
No 48 10 tion of watching movies/TV were significantly associated
factors with overweight/obesity among children
(P<0.05). In the multivariable analysis, vehicle availabil-
other hand, 211 (43.8%) of the children reported that
ity, being from private school, not having close friend(s),
they spend two hours and more per day on watching
preferring sweet foods, eating breakfast irregularly,
movies/TV and 286 (59.3%) spend less than 2 hours
watching movies/TV while eating, and physical inactiv-
per day sitting in their home. One hundred twenty two
ity were identified as significantly associated factors of
(25.3%) of the children had the habit of watching overweight/obesity among children (P<0.05) (Table 4).
movies/TV while eating (Table 3).

Discussion
Magnitude of Overweight/Obesity The magnitude of overweight/obesity was 21.2% in the
The anthropometric analysis revealed that 102 (21.2%) study area. The magnitude in this study was similar with
of the children included in this study were overweight/ study findings from Dire Dawa, Ethiopia (20.5%),7
obese [95% CI: 17.5%, 24.8%)]. The magnitude of over- Kenya (20.8%)10 and Ghana (17%).8 However, it was
weight was 66 (13.7%) whereas obesity was 36 (7.5%). higher than study findings from Ethiopia; Addis Ababa
6 Global Advances in Health and Medicine

Figure 2. Magnitude of Overweight/Obesity Among Second Cycle Primary School Children in Kirkos Sub-City, Addis Ababa, Ethiopia,
2019 (n ¼ 482).

Table 4. Multivariate Analysis on the Factors Associated With Overweight/Obesity Among Children Attending Second Cycle Primary
Schools in Kirkos Sub-City, Addis Ababa, Ethiopia, 2019 (n ¼ 454).

Overweight/Obesity

Yes No
Variables Categories N (%) N (%) COR (95% CI) AOR (95% CI)

Vehicle availability Yes 73 (46.8) 83 (53.2) 8.16 (4.97, 13.39)** 5.35 (2.72, 10.51)**
No 29 (9.7) 269 (90.3) 1 1
School type Government 15 (6.5) 215 (93.5) 1 1
Private 87 (38.8) 137 (61.2) 9.10 (5.06, 16.39)** 10.72 (4.53, 25.37)**
Having friend(s) Yes 83 (20) 333 (80) 1 1
No 19 (50) 19 (50) 4.01 (2.03, 7.92)** 4.80 (1.96, 11.75)**
Sweet food preference Yes 75 (32.1) 159 (67.9) 3.3/7 (2.07, 5.49)** 5.38 (2.73, 10.62)**
No 27 (12.3) 193 (87.7) 1 1
Eating breakfast regularly Yes 34 (11.6) 259 (88.4) 1 1
No 68 (42.2) 93 (57.8) 5.57 (3.46, 8.96)** 6.46 (3.41, 12.26)**
Watching movies/TV while eating Yes 36 (31.3) 79 (68.7) 1.88 (1.17, 3.04)* 3.05 (1.51, 6.16)*
No 66 (19.5) 273 (80.5) 1 1
Additional work after school Yes 80 (21.3) 295 (78.7) 1 1
No 22 (27.8) 52 (72.2) 1.42 (0.82, 2.47) 0.87 (0.39, 1.97)
Physical activity Yes 93 (21.7) 336 (78.3) 1 1
No 9 (36) 16 (64) 2.03 (0.87, 4.75) 4.86 (1.24, 19.02)*
Duration of watching movie/TV <2 hour 45 (17.6) 211 (82.4) 1 1
>2 hour 57 (28.8) 141 (71.2) 1.90 (1.21, 2.96)** 1.57 (0.84, 2.92)
*Significant at p-value < 0.05.
**Significant at p-value < 0.01.
Fitsum et al. 7

(12.7%),9 Bahir Dar (11.9%),5 Bole Sub-City in Addis cumulative effect of these could lead a child to gain more
Ababa (9.8%).11 The variation may be related to weight.
decreased level of physical activity due to increasing sed- Eating breakfast irregularly was another determinant
entary nature of many forms of recreation time, chang- factor of overweight/obesity in this study among second
ing mode of transportation that include going to and cycle primary school children. This was supported by a
from school and increasing urbanization.19–21 study done in Addis Ababa, Ethiopia.9 This could be
The present study affirmed that availability of vehicle expressed as children who skip their breakfast may
was significantly associated with overweight/obesity lead them to an up-regulation of appetite and may
among second cycle primary school children. This was result in intake of high energy foods and consumption
in line with study findings reported from Ethiopia.5,9,11 of unhealthy foods.27
This could be explained as the use of vehicle to and from The study revealed that, watching movies/TV while
school makes children be physically inactive and adapt eating food was found to have significant association
more sedentary lifestyle which in turn leads to excess fat with overweight/obesity. This was in line with a study
accumulation.20 done in Addis Ababa, Ethiopia.11 Watching movies/TV
The current study revealed that learning in private while eating food may expose them to overeating; while
school was strongly associated with overweight/obesity. the children attention is on screen, they are encouraged
This was in agreement with studies conducted in to eat more.28 It is also expected that, children may learn
Ethiopia,5,6 Ghana8 and Kenya.10 This could be unhealthy dietary behavior due to the reason that, most
explained as students who learn in private schools are advertisement are dominated by high calorie products
from families having better socio-economic status. which promote eating fast foods, processed, packed,
Students from families with higher socioeconomic back- sweets and sweet drinks. It is not only predisposing
ground have more access to vehicles and purchasing them to unhealthy dietary behavior but also make
power for calorie-dense and nutrient-poor fast foods.22 them adapt sedentary behavior thereby resulting in less
Significant association was observed in this study energy expenditure.29–31 The cumulative effect of eating
between having no close friend(s) and overweight/obesi- high calorie diet, overeating and physical inactivity are
ty. This finding was consistent with a study done in Dire responsible for child to be overweight/obese.
Dawa, Ethiopia.7 This is probably due to children who According to the present study, physically inactive
children were more likely to have overweight/obesity
have no close friend(s) are less likely to play and exercise
compared with their counterparts. This was supported
physical activities; rather they spend more of their time
by other study reports from Ethiopia5,6 and Ghana.8
sitting in their school compound, and at home watching
This could be defined as physical inactivity is one of
movie/TV and playing electronic games. This exposes
the factors predisposing to overweight/obesity by dis-
children to exercise sedentary behavior which leads to
turbing the energy balance of the body. In order to
positive energy balance and weight gain.19 According
maintain healthy body weight, energy intake (food cal-
to a longitudinal study conducted by Christakis and
ories taken to the body in the form of food and drink)
Fowler for duration of 32 years, obesity appears to
and energy expenditure (calories being used in the body
spread through social ties/networks. For instance,
for our daily energy requirements) must be balanced. If a
having a friend was identified as one of the network child is physically inactive, it results in less energy expen-
phenomena relevant to the biologic and behavioral diture there by increasing energy accumulation in the
traits of obesity.23 body which in turn leads to overweight/obesity.19,30
This study found that the odds of overweight/obesity
was higher among children who prefer to eat sweet foods
as their favorite food, which was consistent with the Limitations of the Study
studies conducted in Dire Dawa, Ethiopia.7 This may The study might not show the temporal relation between
be due to the reason that sweet foods are the top priority the independent and dependent variables since it used
choice of many children and are sold within school cross-sectional study design. There is also the possibility
buildings through vending machines, cafeterias and are that some of the responses might suffer from recall bias
available in most convenience stores and shopping cen- since the questions for diet and lifestyle characteristics
ters. These foods are typically highly processed foods were based on recall. To minimize this bias, data collec-
which mean they are stripped of their nutrients and tors were trained on how to probe the respondents by
have added fat, sugar and salt.24,25 It is an established starting with the most recent events. The respondents
fact that if the body does not use all the energy that is were also allowed sufficient time for adequate recall of
consumed, it ends getting stored in the body as fat. In long term memory. The other limitation of this study
addition, children who consume sweet foods have low might be anthropometric measurement error. To mini-
satiety index and tend to eat more food.26 Therefore, the mize this error, intensive training was provided to data
8 Global Advances in Health and Medicine

collectors and supervisors. In addition, standardization References

and calibration of the anthropometric instruments was 1. World Health Organization. Obesity and overweight.
done throughout the study. https://www.who.int/news-room/fact-sheets/detail/obesity-
and-overweight. Accessed May 02, 2019. Published 2018.
2. Monasta L, Lobstein T, Cole TJ, Vignerová J, Cattaneo A.
Conclusions Defining overweight and obesity in pre-school children:
More than one-fifth of the children included in this study IOTF reference or WHO standard? Obes Rev. 2011;12
were overweight/obese. Compared to the previous local (4):295–300.
study findings, the magnitude of overweight/obesity in 3. Lydian V, Ineke V, Carry MR, et al. Behavioral risk fac-
tors for overweight in early childhood; the ‘be active, eat
this study was found to be high in the study area. Vehicle
right’ study. Int J Behav Nutr Phys Act. 2012;9:74.
availability, being from private school, not having close
4. Biadgilign S, Mgutshini T, Haile D, Gebremichael B,
friend(s), preferring sweet foods, eating breakfast irreg- Moges Y, Tilahun K. Epidemiology of obesity and over-
ularly, watching movies/TV while eating, and physical weight in sub-Saharan Africa: a protocol for a systematic
inactivity were identified as positively associated factors review and meta-analysis. BMJ Open. 2017;7(11):1–4.
of overweight/obesity among the children. The findings 5. Mekonnen T, Tariku A, Abebe SM. Overweight/obesity
of this study can be used to inform policy makers and among school aged children in Bahir Dar City: cross sec-
other stakeholders about an emerging nutrition related tional study. Ital J Pediatr. 2018;44(1):17.
problems among adolescents. Accordingly, health and 6. Gebre A, Alebel A, Zegeye A, Tesfaye B, Ferede A.
education sectors of the study area should invest Prevalence and associated factors of overweight/obesity
their efforts to prevent child overweight/obesity through among children and adolescents in Ethiopia: a systematic
review and meta-analysis. BMC Obes. 2018;5: 19.
the promotion of healthy eating habit and proper phys-
7. Desalew A, Mandesh A, Semahegn A. Childhood over-
ical activities.
weight, obesity and associated factors among primary
school children in dire dawa, eastern Ethiopia; a cross-
Availability of data and materials sectional study. BMC Obes. 2017;4: 20.
The datasets used and/or analyzed during the current study are 8. Richmond A, Anna L, Grace MS, Helena N, Esi C,
available from the corresponding author upon reasonable Patricia B. Prevalence and predictors of overweight and
request obesity among school-aged children in urban Ghana.
BMC Obes. 2017;4: 38.
Acknowledgements 9. Gebremichael B, Chere A. Prevalence of childhood over-
The authors are grateful to the staff of Kirkos Sub-City weight and obesity and its determinant factors among ele-
Education and Health Offices, school directors, the data mentary school children in Addis Ababa, Ethiopia: a cross-
collectors, supervisors, study participants, and questionnaire sectional study. J Nutr Disorders Ther. 2015;S1:1–9.
translators for their cooperation. The authors are also 10. Stella M, Lucy-Joy WM, Vincent OO, Mark TSS. Correlates
grateful to all individuals who provide their inputs directly or of objectively measured overweight/obesity and physical
indirectly. activity in Kenyan school children: results from ISCOLE-
Kenya. BMC Public Health. 2014;14: 436.
11. Askal T, Yifokr T, Bekri M, Getachew T. Prevalence and
Authors’ contributions
associated factors of overweight and/or obesity among pri-
KF initiated the research, and all the authors contributed in mary school children in Bole Sub-City, Addis Ababa,
proposal writing, data entry and analysis, drafting and revising Ethiopia. J Nutr Food Sci. 2015;5(5):1–6.
the paper, manuscript writing and agreed to be accountable for 12. Daniel DB, Maria IVS, Maria MF, et al. Socio-demo-
all aspects of the work. graphic and behavioral risk factors associated with the
high prevalence of overweight and obesity in Portuguese
Declaration of Conflicting Interests children. Am J Hum Biol. 2013;25(6):733–742.
The author(s) declared no potential conflicts of interest 13. Wai SW, Dhami RS, Gelaye B, et al. Comparison of meas-
with respect to the research, authorship, and/or publication ures of adiposity in identifying cardiovascular disease risk
of this article. among Ethiopian adults. Obesity. 2012;20(9):1887–1895.
14. EPHA. Emerging public health problems in Ethiopia and
Funding chronic non-communicable diseases. https://www.etpha.
org/publications/other-publications.html#. Accessed April
The author(s) received no financial support for the research, 30, 2021. Published 2012.
authorship, and/or publication of this article. 15. Central Statistical Agency. Report on the population and
housing census of Ethiopia: Addis Ababa, Ethiopia. www.
ORCID iD csa.gov.et/census-report/complete-report/census-2007.
Berhe Gebremichael https://orcid.org/0000-0002-0669-8521 Accessed April 20, 2019. Published 2007.
Fitsum et al. 9

16. Kirkos Sub-City Education Office. The Annual Report of 25. O’Halloran S, Eksteen G, Gebremariam M, Alston L.
Kirskos Sub-City Education Office. Addis Ababa: Kirkos Measurement methods used to assess the school food envi-
Sub-City Education Office; 2019. ronment: a systematic review. Int J Environ Res Public
17. Cogill B. Food and Nutrition Technical Assistance. Health. 2020;17(5):1623.
Anthropometric Indicators Measurement Guide. Washington, 26. Njike VY, Smith TM, Shuval O, et al. Snack food, satiety,
DC. https://www.academia.edu/10125195/Anthropometric_ and weight. Adv Nutr. 2016;7(5):866–878.
Indicators_Measurement_Guide. Accessed May 09, 2021. 27. Mohiuddin AK. Skipping breakfast everyday keeps well-
Published 2003. being away. Journal of Food Science and Nutrition
18. FDRE-MOE. Curriculum frame work for Ethiopian Research. 2018;1(1):18–30.
Education (KG-Grade 12). https://childresearchinterna 28. Blass EM, Anderson DR, Kirkorian HL, Pempek TA,
tional.files.wordpress.com/2017/02/ethiopia-curriculum. Price I, Koleini MF. On the road to obesity: TV viewing
pdf. Accessed April 30, 2021. Published 2009. increases intake of high-density foods. Physiol Behav.
19. Maturo C, Cunningham S. Influence of friends on child- 2006;88(4–5):597–604.
ren’s physical activity: a review. Am J Public Health. 29. Crespo CJ, Smit E, Troiano RP, Bartlett SJ, Macera CA,
2013;103(7):e23–e38. Andersen RE. Television watching, energy intake, and
20. Swinburn BA, Caterson I, Seidell JC, James WPT. Diet, obesity in US children: results from the third National
nutrition and the prevention of excess weight gain and Health and Nutrition Examination Survey, 1988–1994.
obesity. Public Health Nutr. 2004;7(1A):123–146. Arch Pediatr Adolesc Med. 2001;155(3):360–365.
21. World Health Organization. Diet, physical activity and 30. Cox R, Skouteris H, Rutherford L, Fuller-Tyszkiewicz M,
health. https://www.who.int/dietphysicalactivity/childh Aquila DD, Hardy L. Television viewing, television con-
ood_why/en/. Accessed April 30, 2021. tent, food intake, physical activity and body mass index: a
22. Piryani S, Baral KP, Pradhan B, Poudyal AK, Piryani cross-sectional study of preschool children aged 2–6 years.
RM. Overweight and its associated risk factors among Health Promot J Austr. 2012;23(1):58–62.
urban school adolescents in Nepal: a cross-sectional 31. Lobstein T, Dibb S. Evidence of a possible link between
study. BMJ Open. 2016;6(5):e010335. obesogenic food advertising and child overweight. Obes
23. Christakis N, Fowler J. The spread of obesity in a large Rev. 2005;6(3):203–208.
social network over 32 years. N Engl J Med.
2007;357(4):370–379.
24. Mennella JA, Finkbeiner S, Reed DR. The proof is in the
pudding: children prefer lower fat but higher sugar than do
mothers. Int J Obes. 2012;36(10):1285–1291.