A mixed method study to determine the prevalence of childhood obesity and determinants of physical activity and gadgets use amongst school-going children (standard 1^st to 10^th) from an urban area located in central India

Introduction

Childhood obesity is a significant public health concern. Obesity is a global problem that affects low- and middle-income countries.¹ Globally, more than 200 million school-aged children are overweight or obesity.² Approximately 18.3% of adolescent girls aged between 12 and 17 years in India are overweight or obese.³ Approximately 39 million children below the age of five were identified as overweight or obese by 2020.⁴ Overweight and obesity develop from unhealthy diets such as drinking cold drinks and eating fast food, missing meals, and eating too few vegetables and fruits.^5,6 Physical inactivity, sedentary lifestyle (bad sleeping habits, increased screen time), and improper nutrition are all behaviors that have a direct impact on children’s body weight.^2,5 Sedentary behaviors include activities such as using smartphones or tablets, watching television, playing video games, using a computer while in a vehicle, and reading or studying while at rest.⁷ The prevalence of childhood obesity is increasing daily in many developing countries, and it is a serious concern in developed countries.⁸ The prevalence of childhood and teenage obesity and overweight has significantly increased in India. Non-communicable diseases (NCDs) are associated with a number of risk factors such as smoking, high blood pressure, low fruit and vegetable diet, obesity, low physical activity, and increased cholesterol (WHO).⁹ Engaging in physical activity is crucial for regular growth and development, serving as a key factor in averting childhood and adolescent overweight or obesity, while reducing health risks linked to excessive weight.¹⁰ Physical activity is vital for reducing the likelihood of cardiovascular disease, type 2 diabetes, stroke, obesity, depression, dementia, and benign prostatic.

India is undergoing economic and nutritional transformation, which is related to changes in food habits, decreased physical activity, and an increase in the number of cases of obesity and overweight.^11,12 The rise in fast-food establishments and sedentary behaviors, such as prolonged television viewing and increased computer gaming, has contributed to reduced physical activity levels.^13,14 Recently, there has been a significant rise in television watching among young children and teenagers.^1,15 There has been an increase in sedentary activity accompanied by a decline in physical exercise participation. Research indicates a correlation between the duration of children’s television viewing and their consumption of highly advertised products, such as sugary cereals, sweetened beverages, and salty snacks. Physical activity is directly associated with children’s healthy weight status, as it increases energy expenditure.⁸

Rationale

With the Socioeconomic Transition occurring in India, nutrition transition follows, which is connected with a shift in eating preferences, decreased physical activity due to the increasing influence of westernized lifestyle, and an increase in obesity prevalence. Evidence suggests that childhood obesity is a risk factor for Hypertension & Diabetes, obesity, and other non-communicable diseases, including various cancers, in adulthood. In addition, with changes in lifestyle and the advent of gadgets and technology, outdoor sports and physical activity are on decline as compared to outdoor sports and physical activity required appropriate for the age group.

The goal of this study was to determine the prevalence of juvenile obesity, physical activity habits, and device usage (display time) among children in grades 1 through 10, as well as the viewpoints of their parents.

The study findings will help us understand the current situation of childhood obesity and physical activity in study participants, as well as to sensitize and motivate parents for needful corrective measures and, finally, for healthcare professionals to make further interventions and strategies for prevention.

Aim and objectives

Methods

Variables

Variables such as sociodemographic information, pattern of physical activity, obesity index, screen time, and intake of junk food.

Data collection procedure

The study will be conducted using an interview technique with a semi-structured validated questionnaire using the kobo collection online tool.

Data analysis plan

Data collected will be entered and transferred to Microsoft Excel Spreadsheet from the Kobo toolbox to analyze the data, and the statistical product and service solution R-statistical software (R: The R Project for Statistical Computing (r-project.org)) will be utilized. The full analysis dataset will include all study participants with no missing values for all the parameters in the dataset. The study subjects will be participants who fulfill the inclusion and exclusion criteria.

Primary variables: Physical activity.

Secondary variables: Gadgets application and duration.

All data will be summarized with baseline characteristics for demographic variables described by frequency and percentage for categorical data and with mean and standard deviation for continuous data.

Outcome variables will be analyzed over continuous variables and summarized with the minimum, maximum, mean, standard deviation, standard error, and 95% CI for parametric data. Data for the continuous outcome variables were first tested using the Kolmogorov – Smirnov test at a 5% level of significance (P ≤ 0.05). If the data are rejected, they will be regarded as normal; otherwise, a nonparametric test will be employed to determine significance. ANOVA will be performed to determine the difference in significance at the 5% level (P = 0.05) for the comparison groups comprising various BMI categories.

Non-normal data will be described by the mean, median, lower, and upper quartiles for nonparametric tests. It will be used to test significance using the Kruskal–Wallis test.

Categorical variables will be summarized as frequency (N) and percentage values (%). Efficacy over the categorical variable will be analyzed using chi-square analysis to determine efficacy. All confounding variables were analyzed using a multivariate analysis.

Discussion

According to the World Health Organization (WHO), a lack of physical activity results in 1.9 million deaths globally, while being overweight or obese causes at least 2.6 million deaths.¹⁶

Bhattad et al. (2023) conducted a school-based cross-sectional study on the prevalence of overweight and obesity in school-going children in Govt & Private schools in Latur District, Maharashtra. This study found that the prevalence rates of obesity and overweight were 5.0% and 9.8%, respectively. They concluded that boys were more obese and overweight than girls were.¹⁷

Grace et al. (2021) conducted a case-control study in Chengelpet district, Tamil Nadu, of urban areas on obesity and physical activity among children in urban areas. This study involved school-going children aged 10–17 years and observed inadequate physical activity in 30.9% of controls and 73.6% of cases. There was also a regular habit of watching television while eating food in about 68.2% of controls and 83.6% of cases. Inadequate physical activity, sedentary behavior, and watching television while eating food were found to be associated with obesity.¹⁸

Dabade et al. (2019) conducted a community-based cross-sectional study on the prevalence of overweight and obesity among school-going children in Satara District, Maharashtra. The research found that out of the 360 participants (185 boys and 175 girls), 12.97% of the male population and 9.14% of the female population were overweight or obese. A direct relationship was also observed between a history of obesity in the family, less sleeping time, and the working status of mothers with childhood obesity.¹⁹

Kumari Veena Sinha (2019) conducted the study which was a cross-sectional community study in the Urban Health Training Centre’s Field Practice Area on the occurrence of obesity in Indian adolescent school-going children in urban areas. According to this study, among adolescents aged 10–19 years, 18.5% were overweight and 5.8% were obese. In addition, overweight and obesity were prevalent in 24.3% of the study population.¹²

The incidence of overweight and obesity in school-age children in the Multan area was also the subject of a descriptive cross-sectional study by Khan S, Abbas A, et al. (2019). According to this study, approximately 10% and 5% of school-going children aged group (3 – 18 yrs) suffer from overweight and obese, respectively. This study found that fast food was directly associated with overweight and obesity, which was 36.5%, and also observed that children who were more physically active were not associated with overweight and obesity. Approximately 61.2% of children use television, mobile phones, and computers.⁵

Saikia et al. (2016) conducted a school-based cross-sectional study on the prevalence of overweight and obesity and their relationship with physical activity in Dibrugarh town. The study observed that 20.4% and 10.3% of boys and 24.9% and 9.7% of girls were overweight and obese, respectively. The study also used the Global Physical Activity Questionnaire for physical activity where it has been seen that boys are more involved in activity than girls (68.7% and 58.1%). In sedentary activity, girls spend more hours than boys (18.2%) and (11.3%, respectively).²

Rexlin et al. (2016) conducted a cross-sectional observational study on school-going children in Madurai. The children were recruited from two rural and two urban schools. The study observed that the prevalence rates of overweight and obesity were 16.8% and 9.3%, respectively.

Mahajan et al. (2011) conducted a school-based cross-sectional study of all four regions of Puducherry. Children aged 6–12 years were involved. The study observed that the prevalence rates of obesity and overweight among children were 2.12% and 4.41%, respectively. Obesity and overweight were prevalent in 4.69% and 8.66% of the four regions, respectively.²⁰