Factors Associated With Overweight and Obesity in Preschool Children
Factors Associated With Overweight and Obesity in Preschool Children
Department of Social Medicine, School of Medicine, University of Sarajevo, 2Secondary Medical School; Sarajevo, Bosnia and Herzegovina
1
ABSTRACT
538
Kurspahić-Mujčić et al. Overweight /obesity in preschoolers
539
Medicinski Glasnik, Volume 17, Number 2, August 2020
pleted high school/university) and employment between normal weight and overweight/obese
status based on mothers’ stated employment du- group was performed by χ2 test.
ring an interview (employed or not employed). The individual effects of potential childhood
The mothers reported average minutes that the- overweight/obesity risk factors on the presence of
ir child spent in moderate to vigorous intensity child overweigh/obesity were obtained by logistic
physical activity (that makes him/her out of bre- regression analysis through the calculation of the
ath or warmer than usual) daily. According to the odds ratio (OR). The level of significance was set
World Health Organization (WHO) physical acti- at p<0.05, and the confidence level of 95%.
vity guidelines, preschool children who are physi-
cally active for at least 60 minutes of moderate-to RESULTS
vigorous intensity physical activity (MVPA) da- The study evaluated 300 children in two groups
ily were considered as compliant with the WHO of 150 each (i.e. normal weight and overweight/
physical activity recommendations (21). obese).
The mothers reported average minutes per day their More male children were in the overweight/obe-
child sat and watched television, and also the time se than in the normal weight group, 82 (55.0%)
the child used a computer/ tablet/ mobile phones. and 65 (43.3%). More female children were in
The specific questions asked were, ''Over the past the normal weight group than in the overweight/
30 days, for how many minutes on average per day obese, 85 (56.7%) and 67 (45.0%).
did the child sit and watch TV?“ and ''Over the past Most of the children in the normal weight and
30 days, for how many minutes on average per day overweight/obese group, 124 and 123 (82.7% and
did the child use a computer/tablet/mobile phone?" 82.0%, respectively) resided in 2-parent househol-
We summed up average minutes of television and ds, with both their biological mother and father.
computers/ tablet/ mobile phones to estimate "scre-
Maternal education level in the normal weight
en time." We defined high screen time as greater
and overweight/obese group was not significantly
than 120 minutes (2 hours) per day (22).
different (p=0.448). Maternal education level
Variables “snacks in front of TV” and “snacks in included mainly high school/ university educati-
front of computers/tablet/mobile phones ” were on, 86 (57.3%) in the normal weight group and
grouped in “snacks in front of screens”, with 92 (61.3%) in the overweight/ obese group.
three options of answers: never, sometimes, and
Maternal employment in the normal weight and
always eats snacks in front of screens.
overweight/obese group was not significantly
The mothers were asked to indicate their own height different (p=0.803). Slightly more children of
and weight. Maternal body mass index (BMI) was employed mothers were in the overweight/obese
calculated as underweight (BMI <18.5), normal- group than in the normal weight, 105 (70.0) and
weight (18.5< BMI <24.9), overweight (BMI ≥25- 102 (68.0), respectively.
29.9), and obese (BMI ≥30). Children were weighed
Among normal weight children, 16 (10.7%) li-
and measured, and BMI was calculated. Weight was
ved with an overweight mother, and five (3.3%)
measured with the child in light clothing, to the ne-
lived with a mother who was obese. Among
arest 0.1 kg. Standing height was recorded without
overweight/obese children, 43 (28.7%) lived
shoes to the nearest 0.1 cm. The BMI was calculated
with an overweight mother, and six (4.0%) lived
as weight (kg) divided by height in square meters
with a mother who was obese.
(m2). The BMI categories were defined according
to the WHO reference curves for different age and A total of 87 (58.0%) children in the normal weight
gender groups (23): normal weight (BMI between group and 65 (43.3%) in the overweight/obese gro-
5th-85thpercentiles), overweight (BMI between up spent at least 60 minutes each day in MVPA.
85th-95th percentiles), and obese (BMI ≥85th-95th A total of 14 (9.3%) children in the normal weight
percentiles). The mothers were also asked to report group and eight (5.3%) in the overweight/obese
their weight and height. group achieved screen time recommendations
(<2 hr per day).
Statistical analysis
Four times more children with regular snacking
Testing of the difference in the distribution of po- while watching television, using computer/tablet/
tential childhood overweight/obesity risk factors mobile phones was in the overweight/obese gro-
540
Kurspahić-Mujčić et al. Overweight /obesity in preschoolers
Table 1. Distribution and association of risk factors and overweight/obesity in preschool children
No (%) of children Logistic regression analysis
Potential risk factor
p
Normal weight Overweight / obese OR (95% CI) p
Child gender
Female 85 (56.7) 67 (45.0) 0.049 1
Male 65 (43.3) 82 (55.0) 1.6 (1.01-2.53) 0.043
Family status
Two-parent family (married) 124 (82.7) 123 (82.0) 0.582 1
Single parent family (divorced) 25 (16.7) 27 (18.0) 1.09 (0.59-1.98) 0.780
Single parent family (single) 1 (0.7) 0 (0.0) 0.34 (0.01-8.33) 0.505
Maternal education level
Completed high school /university 86 (57.3) 92 (61.3) 0.448 1
Completed secondary school 64 (42.7) 57 (38.0) 1.2 (0.46-1.91) 0.437
Incomplete/completed elementary school 0 (0.0) 1 (0.7) 0.36 (0.01-8.87) 0.529
Maternal employment
Yes 102 (68.0) 105 (70.0) 0.803 1
No 48 (32.0) 45 (30.0) 1.09 (0.68-1.79) 0.7081
Maternal body mass index status
Normal weight 123 (82.0) 99 (66.0) 0.001 1
Underweight 6 (4.0) 2 (1.3) 0.41 (0.08-2.09) 0.286
Overweight 16 (10.7) 43 (28.7) 3.34 (1.77-6.28) 0.000
Obese 5 (3.3) 6 (4.0) 1.49 (0.44-5.03) 0.519
Physical activity (minutes/day)
≥60 87 (58.0) 65 (43.3) 0.039 1
30-59 59 (39.3) 79 (52.7) 1.79 (1.12-2.86) 0.014
< 30 4 (2.7) 6 (4.0) 2.01 (0.54-7.41) 0.295
Sedentary behaviour
Screen time (minutes/day)
< 120 14 (9.3) 8 (5.3) 0.022 1
120-180 118 (78.7) 107 (71.3) 1.59 (0.64-3.93) 0.318
> 180 18 (12.0) 35 (23.3) 3.40 (1.20-9.61) 0.020
Snacks in front of screens
Never 49 (32.7) 14 (9.3) 0.000 1
Always 14 (9.3) 56 (37.3) 3.22 (1.65-6.27) 0.000
Sometimes 87 (58.0) 80 (53.3) 1.14 (0.49-2.63) 0.753
OR, odds ratio; CI, confidence interval
541
Medicinski Glasnik, Volume 17, Number 2, August 2020
obesity in Turkish children aged less than 7 years related to consumption of unhealthy food thro-
was without gender difference (29). ughout the day (40). Studies have revealed that
Research on relationship between maternal edu- children consume a large proportion of their daily
cation level and overweight /obesity in prescho- calories and meals while watching screen media
ol children has not provided a definite answer. (41). In this study, regular snacking in front of
Some studies, as well as this one, have not found screens is a practice that triples children’s risk for
a statistically significant relationship (30). Pre- becoming obese.
vious studies across 11 European countries have This study aimed to focus on the role of sociode-
indicated that low maternal education could yield mographic characteristics of child and mother,
a substantial risk of early childhood obesity (31). physical activity and sedentary behaviour of the
Interestingly, the association between maternal child, but many other factors of the family envi-
education and children’s weight status in China ronment might influence children’ obesity. The-
is different from that in western countries. In refore, future research is needed to explore other
China, the obesity rate among children with high potential factors associated with overweight/obe-
maternal education is higher than that of lower sity in preschool children that were not included
maternal education (32). in the present study.
A growing research literature has explored the In conclusion, this study demonstrated a signi-
relationship between maternal employment and ficant association between maternal overweight
children’s body mass index (BMI) (33,34). A syste- and children’s weight status. This suggests that
matic review using six studies from the United Sta- early interventions for childhood obesity sho-
tes of America, the United Kingdom, Germany and uld focus on children of overweight or obese
Japan, concludes that maternal employment is asso- mothers. In addition, factors including screen
ciated with an increased risk of overweight /obe- time viewing and physical activity are also asso-
sity for children (35). The employed mothers spent ciated with children’s weight status. Educating
less time on meal preparation and healthy weight parents, specially mothers on the screen-use re-
management than unemployed mothers as docu- commendations and the negative health risks of
mented by Savage et al. (36). In this study maternal excessive screen use, as well recommendations
employment was not significantly associated with for physical activity may improve parental awa-
overweight/obesity status of the preschool children. reness and monitoring of their children’s seden-
Regarding other risk factors for overweight / tary behaviour and physical activity.
obesity, our results fit into known patterns; as in
FUNDING
other studies, screen time viewing was positively
(37,38), whereas physical activity was inversely No funding was received for this study.
associated with childhood overweight or obesity
in preschool age children (39). TRANSPARENCY DECLARATION
542
Kurspahić-Mujčić et al. Overweight /obesity in preschoolers
11. van Ansem WJ, Schrijvers CT, Rodenburg G, van de 27. Kurspahić Mujčić A, Zećo E. Socioeconomic and
Mheen D. Maternal educational level and children’s demographic factors associated with abdominal obe-
healthy eating behaviour: role of the home food envi- sity in women of childbearing age. Med Glas (Zeni-
ronment (cross-sectional results from the INPACT ca) 2017; 14:218-23.
study). Int J Behav Nutr Phys Act 2014; 11:113. 28. Cattaneo A1, Monasta L, Stamatakis E, Lioret S, Ca-
12. Sijtsma A, Koller M, Sauer PJJ, Corpeleijn E. Te- stetbon K, Frenken F, Manios Y, Moschonis G, Savva
levision, sleep, outdoor play and BMI in young S, Zaborskis A, Rito AI, Nanu M, Vignerová J, Caroli
children: the GECKO Drenthe cohort. Eur J Pediatr M, Ludvigsson J, Koch FS, Serra-Majem L, Szponar
2015; 174:631-9. L, van Lenthe F, Brug J. Overweight and obesity in in-
13. Barbosa SC, Coledam DHC, Stabelini Neto A, Elias fants and pre-school children in the European Union:
RGM, Oliveira AR. School environment, sedentary a review of existing data. Obes Rev 2010;11:389–98.
behavior and physical activity in preschool children. 29. Kondolot M, Balci E, Ozturk A, Mazicioglu MM,
Rev Paul Ped 2016; 34:301–8. Hatipoglu N, Kurtoglu S, Ustunbas HB. Body mass
14. Uijtdewilligen L, Nauta J, Singh AS, van Mechelen index percentiles for Turkish children aged 0-84
W, Twisk JWR, van der Horst K, Chinapaw MJM. months. Ann Hum Biol 2011; 38:676-80.
Determinants of physical activity and sedentary 30. Savva1 SC, Tornaritis M, Chadjigeorgiou C, Kou-
behaviour in young people: a review and quality rides YA, Savva ME, Panagi A, Chrictodoulou E,
synthesis of prospective studies. Br J Sports Med Kafatos A. Prevalence and socio-demographic asso-
2011; 45:896–905. ciations of undernutrition and obesity among pres-
15. Jiang J, Rosenqvist U, Wang H, Greiner T, Ma Y, chool children in Cyprus. Eur J Clin Nutr 2005; 59:
Toschke AM. Risk factors for overweight in 2- to 1259–65.
6-year-old children in Beijing, China. Int J Pediatr 31. Ruiz M, Goldblatt P, Morrison J, Porta D, Forastie-
Obes 2006; 1:103–8. re F, Hryhorczuk D, Antipkin Y, Saurel Cubizolles
16. Mendoza JA, Zimmerman FJ, Christakis DA. Tele- MJ, Lioret S, Vrijheid M, Torrent M, Iñiguez C,
vision viewing, computer use, obesity, and adiposity Larrañaga I, Bakoula C, Veltsista A, van Eijsden
in US preschool children. Int J Behav Nutr Phys Act M, Vrijkotte TG, Andrýsková L, Dušek L, Barros
2007; 4:44. H, Correia S, Järvelin MR, Taanila A, Ludvigsson
17. Marsh S, Ni Mhurchu C, Maddison R. The non-ad- J, Faresjö T, Marmot M, Pikhart H. Impact of low
vertising effects of screen-based sedentary activities maternal education on early childhood overweight
on acute eating behaviours in children, adolescents, and obesity in Europe. Paediatr Perinat Epidemiol
and young adults. A systematic review. Appetite 2016; 30:274-84.
2013; 71:259. 32. Liu W. Lin R, Li B. Pallan M, Cheng KK, Adab
18. Hasanbegovic S, Mesihovic-Dinarevic S, Cuplov P. Socioeconomic determinants of childhood obe-
M, Hadzimuratovic A, Boskailo H, Ilic N, Njuhović sity among primary school children in Guangzhou,
A, Čengić N, Bajramović E, Brković Š. Epidemio- China. BMC Public Health 2016; 16:473.
logy and etiology of obesity in children and youth 33. Morrissey TW, Dunifon RE, Kalil A. Maternal em-
of Sarajevo Canton. Bosn J Basic Med Sci 2010; ployment, work schedules, and children’s body mass
10:140–6. index. Child Dev 2011; 82: 66–81.
19. Kail RV. Children and Their Development 6th ed. En- 34. Chia Y. Maternal labour supply and childhood obe-
glewood Cliffs, NJ: Prentice Hall, 2011. sity in Canada: evidence from the NLSCY. CJE
20. Hawkins SS, Law C. A review of risk factors for 2008; 41:217–44.
overweight in preschool children: a policy perspecti- 35. Mindlin M, Jenkins R, Law C. Maternal employment
ve. Int J Pediatr Obes 2006; 1:195–209. and indicators of child health: a systematic review in
21. WHO. Global recommendations on physical activity pre-school children in OECD countries. J Epidemiol
for health. Geneva, Switzerland: WHO, 2010. Community Health 2009; 63:340-50.
22. Briefel RR, Deming DM, Reidy KC. Parents’ per- 36. Savage JS, Fisher JO, Birch LL. Parental influence
ceptions and adherence to children’s diet and acti- on eating behaviour: conception to adolescence. J
vity recommendations: the 2008 feeding infants and Law Med Ethics 2007; 35:22–34.
toddlers study. Prev Chronic Dis 2015;12:150110. 37. Jiang J, Rosenqvist U, Wang H, Greiner T, Ma Y,
23. WHO Multicentre Growth Reference Study Group. Toschke AM. Risk factors for overweight in 2-to
WHO child growth standards: length/height-for-age, 6-year-old children in Beijing, China. Int J Pediatr
weight-for-age, weight-for-length, weight-for-height Obes 2006; 1:103–8.
and body mass index-for-age: methods and deve- 38. Ariza AJ, Chen EH, Binns HJ, Christoffel KK. Risk
lopment. Geneva: WHO, 2006. factors for overweight in five-to six-year-old Hispa-
24. Janjua NZ, Mahmood B, Islam MA, Goldenberg nic American children: a pilot study. J Urban Health
RL. Maternal and early childhood risk factors for 2004; 81;150–61.
overweight and obesity among low-income predo- 39. Brophy S, Cooksey R, Gravenor MB, Mistry R,
minantly black children at age five years: a prospec- Thomas N, Lyons RA, Williams R. Risk factors for
tive cohort study. J Obes 2012; 2012:1–9. childhood obesity at age 5: analysis of the millenni-
25. Olson CM, Demment MM, Carling SJ, Strawder- um cohort study. BMC Public Health 2009; 9:467.
man MS. Associations between mothers’ and their 40. Hare-Bruun H, Nielsen BM, Kristensen PL, Møller
children’s weights at 4 years of age. Child Obes NC, Togo P, Heitmann BL. Television viewing, food
2010; 6:201–7. preferences, and food habits among children: a pros-
26. Heslehurst N, Vieira R, Akhter Z, Bailey H, Slack pective epidemiological study. BMC Public Health
E, Ngongalah L, Pemu A, Rankin J. The association 2011; 11:311.
between maternal body mass index and child obe- 41. Matheson DM, Wang Y, Klesges LM, Beech BM,
sity: a systematic review and meta-analysis. PLoS Kraemer HC, Robinson TN. African-American girls’
Med 2019;16:e1002817. dietary intake while watching television. Obes Res
2004; 12:32–7.
543