Childhood obesity has become, a global public health problem, and epidemiological studies are important to identify its determinants in different populations. This study aimed to investigate factors associated with obesity in a representative sample of children in Neishabour, Iran. This study was conducted among 1500 randomly selected 6–12-year-old students from urban areas of Neishabour, northeast of Iran. Then, through a case-control study, 114 obese (
Obesity levels are increasing rapidly in children and youngsters of developed and developing countries [
Obesity is a multifactorial consequence. In addition to genetic, metabolic, socioeconomic, and cultural factors, life style habits as unhealthy diet, low physical activity levels, weight and order of birth and other factors like history of breast feeding, as well as the age and type of complementary food are among factors affecting obesity [
In this study, 1500 6–12-year-old students were selected via two-stage sampling method from urban areas of Neishabour. Neishabour is a city in the Razavi Khorasan province in northeastern Iran and had a population of 205972 people. On the first stage, 60 primary schools, both public and private, were chosen, and, on the second stage, in each cluster, school children were selected randomly from the class attendance register. It was approved by the ethics committee of Tehran University of Medical Sciences (TUMS). Written informed consent was obtained from parents and oral assent from students.
Then, through a case-control study, 14 obese (body mass index (BMI) ≥ 95th percentile of Iranian reference) children were selected as the case group, and the first nonobese student (15th ≤ BMI < 85th percentile) examined exactly after each obese student, and who was matched by age and sex, was selected as the control. Overall, 102 students were included in the control group.
We used the Iranian reference for BMI percentiles [
Data were collected by questionnaire via interview with mothers. Interviews were performed by trained health professionals. The questionnaire included mother-reported information about her child regarding the age, sex, birth weight, birth order, number of family household members, duration of breast feeding, age onset of complementary food, TV watching, playing electronic devices, sleep duration, father age, mother age, mother weight, economic status, and parental obesity history. The economic status of family was assessed by having some equipment such as color TV, refrigerators, washing machine, video, computer, video CD, and accessibility to car and private home. In data analysis, economic status was defined as low, moderate, and good based on an average score 3, 4–6, and more than 7, respectively. Physical activity score was evaluated using the modified Beacke et al. questionnaire that was asked from the pupils [
Data were analyzed using the SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). Quantitative variables are expressed as mean ± standard deviation (SD) and categorical data as percentage. We computed the crude odds ratio (OR) by using logistic regression test to establish the degree of association between various risk factors and childhood obesity. Multiple logistic regression (MLR) model was fitted to data to adjust for the presence of confounding factors. All variables with
Overall, 216 children consisting of 114 obese and 102 nonobese students were assessed. The mean (SD) of age, weight, height, and BMI of the students were
The crude ORS (univariate analysis) for birth weight, birth order, family extension, duration of breast feeding, age onset of complementary food, TV watching, playing electronic devices, sleep duration, physical activity score, father age, mother age, mother BMI as quantitative variables are shown in Table
Association between quantitative variables and obesity in univariate logistic regression model.
Variables | Cases ( |
Control ( |
Crude OR | 95% CI |
---|---|---|---|---|
(mean ± SD) | (mean ± SD) | |||
Birth weight (gr) | 3900. 90 ± 846.20 | 2837.10 ± 671.30 | 1.00 | 1.00–1.00 |
Birth order (n) | 1.90 ± 1.20 | 5.09 ± 13.05 | 0.62 | 0.50–0.76 |
Family extension (n) | 4.40 ± 0.97 | 5.10 ± 1.60 | 0.63 | 0.49–0.80 |
Duration of breast feeding (month) | 22.02 ± 9.80 | 23.76 ± 14.33 | 0.99 | 0.97–1.11 |
Age-onset of complementary food (month) | 8.77 ± 17.56 | 9.63 ± 15.63 | 1.00 | 0.98–1.01 |
TV watching, playing electronic devices (hour) | 5.42 ± 1.99 | 2.77 ± 1.26 | 2.33 | 1.87–2.90 |
Sleep duration (hour) | 10.40 ± 0.91 | 9.76 ± 0.89 | 2.24 | 1.60–3.15 |
Physical activity (score) | 2.30 ± 0.37 | 3.02 ± 0.39 | 0.01 | 0.01–0.04 |
Father age (year) | 39.57 ± 5.37 | 41.71 ± 6.27 | 0.94 | 0.90–0.99 |
Mother age (year) | 35.51 ± 5.84 | 37.50 ± 6.88 | 0.95 | 0.91–0.99 |
Mother BMI (kg/m2) | 26.98 ± 3.99 | 22.77 ± 3.81 | 1.40 | 1.25–1.55 |
Associations between qualitative variables and obesity determined by univariate logistic regression model are shown in Table
Association between qualitative variables and obesity in univariate logistic regression model.
Variables | Cases ( |
Control ( |
Crude OR | 95% CI |
---|---|---|---|---|
|
| |||
Father job | ||||
Jobless | 1 (0.90) | 4 (4.40) | Ref | |
Worker | 17 (15.00) | 31 (31.60) | 2.19 | 0.23–21.23 |
Employee | 34 (30.10) | 40 (40.80) | 3.40 | 0.36–31.89 |
Other | 61 (54.00) | 23 (23.50) | 10.60 | 1.13–99.96 |
Father education | ||||
Illiterate and primary school | 23 (20.40) | 36 (36.70) | Ref | |
Guidance school | 16 (14.20) | 29 (29.60) | 0.86 | 0.39–1.92 |
Diploma | 24 (21.20) | 21 (21.40) | 1.78 | 0.816–3.92 |
University degrees | 50 (44.20) | 12 (12.20) | 6.52 | 2.87–14.79 |
Mother job | ||||
Housewife | 55 (48.20) | 80 (78.40) | Ref | |
Employee | 59 (51.80) | 22 (21.60) | 3.90 | 2.14–7.09 |
Mother education | ||||
Illiterate and primary school | 35 (30.70) | 49 (48.00) | Ref | |
Guidance school | 12 (10.50) | 33 (32.40) | 0.51 | 0.23–1.12 |
Diploma | 12 (10.50) | 14 (13.70) | 1.20 | 0.50–2.90 |
University degrees | 55 (48.20) | 6 (5.90) | 12.80 | 4.97–33.10 |
Economic status | ||||
Weak | 18 (15.80) | 72 (63.20) | Ref | |
Moderate | 72 (63.20) | 57 (55.90) | 3.01 | 1.57–5.78 |
Good | 24 (21.10) | 2 (2.00) | 28.66 | 6.12–134.20 |
Family history of obesity | ||||
Without obesity history | 7 (6.10) | 76 (74.50) | Ref | |
Father side obesity history | 24 (21.10) | 11 (10.80) | 23.68 | 8.26–67.89 |
Mother side obesity history | 5 (4.40) | 13 (12.70) | 4.17 | 1.15–15.16 |
Both of them | 78 (68.40) | 2 (2.00) | 423.42 | 85.24–2010.00 |
Association between independent variables and obesity in multiple logistic regression model (last step).
Variables | Adjusted OR | *95% CI |
| ||
Physical activity (score) | 0.23 | 0.12-0.43 |
Family history of obesity | ||
Without obesity history | Ref | |
Father side obesity history | 47.41 | 9.87-227.60 |
Mother side obesity history | 2.36 | 0.39-14.32 |
Both of them | 547.58 | 45.26-6062.00 |
This study has demonstrated that parental obesity history and physical activity were the strongest determinants of childhood obesity. These findings are in agreement with some investigations, showing that low physical activity and parental obesity to be the predictors of youngsters obesity [
The result of Veugelers and Fitzgerald’s study showed that, as in other studies, normal-weight children were more physically active and engaged less in sedentary activities [
In our study, there was no significant association between mothers’ BMI and children obesity, but Sekine and his collogues found that mother’s obesity was associated with children’s BMI. In addition to genetic susceptibility, this may reflect environmental factors influencing children’s body composition because children’s food habits and preferences are usually shaped more by mothers than fathers [
The controversy between our result and other studies may be because of some factors related to family composition that we did not ask in our study and it may confound our conclusion. Our findings are also consistent with a previous study, which showed that a positive family history of being overweight is one of the most important indicators of the genetic risk for obesity and being overweight [
We did not document any relationship between SES and obesity, but, in some other studies, investigators observed a gradient whereby children by low SES were more likely to be overweight or obese [
In present study, we did not find any association between the sleep duration and obesity. Some studies demonstrated an inverse linear relationship between sleep duration and both mean BMI and obesity [
But, in our study, no significant association was observed between sleep duration at night and obesity. Maybe in current study, individuals of the case group went to bed later than the controls, and, in order to compensate for the lack of sleep, they slept more during the day instead of being more physically active or exercising.
Our study revealed no significant association between obesity and birth order. It may be related to increasing the knowledge of parents and paying more attention to the nutrition and health care of their children in both case and control groups.
In a meta-analysis carried out by Harder, the duration of breastfeeding was inversely and linearly associated with the risk of overweight. The risk of overweight was reduced by 4 percent for each month of breastfeeding [
This study had some limitations, which may have influenced the findings. First, the SES was measured indirectly by asking some relevant questions. Second, family composition was not assessed in this study, and it may be a confounder for some parts of our results. Despite these limitations, this study provides some data on childhood obesity risk factors.
Finally, we suggested that a high priority has been given to research strategies to prevent the development of childhood obesity. Also, based on our findings, more physical education classes and providing healthy places for more extracurricular physical activity are strongly recommended, and family education for preventive public health actions should be targeted.
The collaboration of the authorities of the Office for Education managers, manager's assistants, teachers and schoolchildren of the primary schools in Neishabour is sincerely appreciated. The study was conducted with the financial support of the School of Public Health, Tehran University of Medical Sciences.