Prevalence and Predictors of Overweight and Obesity Among School-Aged Children in the Country of Georgia: A Cross-Sectional Study, 2022

Abstract

Background

Childhood overweight and obesity are significant global public health challenges that affect approximately 340 million children worldwide. In Georgia, the prevalence of childhood obesity is alarming, with approximately 28% of 7-year-old children classified as overweight or obese in 2019. This study aimed to investigate the key factors associated with overweight and obesity among school-age children in Georgia.

Methods

Data from the Childhood Obesity Surveillance Initiative Survey (COSI), which was conducted in 2022, was analyzed. The study involved 3,334 children from 245 schools across the region. Anthropometric measurements and a structured questionnaire were utilized to evaluate body weight, dietary behaviors, physical activity behaviors, parental education, household socioeconomic status, and body mass index (BMI).

Results

Among second-grade school children in Georgia, 17.2% were overweight and 11.0% were obese, with higher percentages of boys (30.0%) than girls (26.3%). The prevalence of overweight/obesity was greater in urban-dwelling children (30.3%) than in rural children (23.6%). Significant associations were found between BMI and living area (p < 0.001), playing outside (p = 0.01), passive modes of transportation (e.g., cars) for school travel (p < 0.05), parental education (p = 0.03) and parental body weight (p < 0.05). However, no significant differences were observed in the prevalence of various dietary behaviors or screen time between normal-weight and overweight/obese children.

Conclusions

This study revealed significant associations between body weight status and certain demographic and lifestyle factors, highlighting the critical role of promoting physical activity, encouraging active transportation (e.g., walking or cycling to school) and raising parental awareness to address childhood overweight and obesity. Future interventions should prioritize creating a supportive environment for healthy behaviors and implementing early screening measures to prevent potential complications and improve overall health outcomes in children.

Background

Childhood overweight and obesity represent significant global public health challenges, with an estimated 340 million children and adolescents affected worldwide [1]. Over the past 30 years, the prevalence of obesity has increased, partly due to a phenomenon known as the “nutrition transition,” which is closely linked to urbanization and trade liberalization [2]. The removal of barriers to international trade exposes countries to processed and high-calorie food products, leading to shifts in food systems and consumer behaviors. This transition results in increased consumption of processed and calorie-dense foods [3,4,5], creating an environment where unhealthy dietary behaviors are promoted and nutritious options such as fruits and vegetables are often discouraged, particularly among children and adolescents [6]. In addition to the nutrition transition, several other factors influence the obesity rate, including parental education and socioeconomic status [7,8,9]. Children from lower-income families are more vulnerable to body weight gain due to limited access to healthy food options and fewer opportunities for physical activity. Furthermore, the issue of obesity is compounded by excessive screen time, which reduces physical activity levels and promotes a more sedentary lifestyle among children and adolescents [10].

Obesity is linked to numerous diseases and conditions, contributing to higher mortality rates [11,12,13]. Although obesity may not significantly impact morbidity during adolescence, it remains a predictor of obesity and its associated complications in adulthood [14,15,16].

In Georgia, the prevalence of overweight and obesity has increased over the years. According to the Non-Communicable Disease Risk Factors Survey (STEPS) conducted in 2010, 56.5% of adults were overweight, and 25.1% were classified as obese [17]. By 2016, these rates had risen to 64.6% and 33.2%, respectively [18]. Childhood obesity rates in Georgia are also concerning, with approximately 28% of Georgian children aged 7 years being overweight or obese according to the World Health Organization (WHO) Childhood Obesity Surveillance Initiative (COSI) project conducted in 2019 [19].

Given the strength of this situation, understanding the risk factors associated with overweight and obesity in adolescents is crucial. Therefore, this study aimed to estimate the prevalence of overweight and obesity and investigate the key factors associated with these conditions among school-age children in Georgia. Specifically, our objectives were to estimate (1) the prevalence of overweight and obesity among 2nd-grade school children in Georgia; (2) the associations between children’s body weight status and their individual characteristics, including gender, as well as their dietary and physical activity behavior; and (3) the relationship between children’s body weight status and parental background characteristics, including parental education, parental body weight status and perceived family wealth. The findings of this study will provide valuable insights for developing future interventions and public health strategies to address this critical issue.

Methods

Study design and data source

Data from the Childhood Obesity Surveillance Initiative Survey (COSI), conducted in Georgia in 2022 was utilized. The survey aimed to provide a nationwide representation of 2nd-grade (aged 6–8) school children in Georgia and employed a 2-stage stratified cluster random sampling approach to obtain the sample. In the first stage of sampling, schools under the Ministry of Education were selected with a probability proportional to the school enrollment size across the country. In the second stage, classes were randomly selected from each selected school using simple random sampling. All children present on the day of the survey were enrolled from a total of 245 schools.

Informed consent and ethics

Before collecting the data, written consent was obtained from parents and verbal consent from the children after they explained the study’s objectives and procedures. The study was approved by the ethics committee of the National Center for Disease Control and Public Health (NCDC).

Clinical trial number

not applicable.

Data collection

Data were collected using a structured questionnaire developed based on modified WHO questionnaires employed by COSI study groups. The questionnaire included questions related to children’s dietary behaviors; physical activity, including screen time and family socioeconomic status; and parental body weight and height. After the parents completed the questionnaire at home, anthropometric measurements of the children’s height and body weight were conducted by trained interviewers at school. The standard measurement procedures recommended by the WHO for both height and body weight measurements were followed [20]. Body weight was measured using a digital weighing machine (Omron Model: HN286, accuracy 0.1 kg). Height measurements were taken with a stature meter (Seca body meter 206, accuracy 0.001 m).

Study variables

The outcome variable of the study was overweight/obesity, which was determined based on the body mass index (BMI) for the age-sex of the children. Overweight was defined as having a BMI-for-age above the WHO growth reference median by more than 1 standard deviation, and obesity was defined as having a BMI-for-age above the WHO growth reference median by more than 2 standard deviations [21]. Underweight individuals were grouped with the normal weight category for analysis due to their small representation in the dataset. Several exposures, including dietary behaviors, physical activity and sedentary behaviors, were examined in the children.

Dietary behaviors

Healthy dietary behavior was classified as regular consumption of breakfast, fresh fruits and vegetables (excluding potatoes) on a daily basis , as these foods provide important nutrients. Participants were divided into two groups: those who consumed breakfast, fresh fruits and vegetables seven days per week and those who did not meet the recommended frequency. The consumption of sugary beverages, savory snacks (such as potato chips, corn chips, popcorn, peanuts), sweet snacks (including cakes, biscuits, candy desserts) and fast-food items (such as pizza, hamburgers, shawarma, sausages, or meat and bean pies) has been linked to elevated levels of saturated fats, free sugars and salt and can have negative health implications. A cutoff of consuming these items no more than three days per week was used to classify dietary behavior as healthy or not.

Physical activity assessment

Physical activity was assessed based on the WHO’s guidelines [22]. For school children, meeting the recommended activity level includes spending at least one hour per day playing outside. Additionally, a minimum requirement of engaging in sports activities on at least two days per week was set. Based on these criteria, participants were divided into two groups: those who met the activity recommendations and those who did not. Additionally, we considered participants’ transportation preferences to and from school when assessing their physical activity level. This classification defined two groups: active transportation, in which children who actively chose walking or cycling for their school journeys were categorized ; and passive transportation, in which children who relied on motorized transportation, including cars, or a combination of motorized transport with occasional walking or cycling., were grouped. . When assessing physical activity, screen time was also taken into account. It was defined as the duration spent on media and participants were categorized into 2 groups: those with less than two hours of daily screen time and those with more daily screen time based on WHO guidelines.

Family Socioeconomic Status (SES)

Family SES was evaluated using two indicators: parental education level and self-reported perceived family wealth. While these indicators are not exhaustive in capturing the multifaceted nature of SES, they provide valuable information relevant to the study’s objectives. Parental education was categorized into three groups: low, where both parents had lower secondary education or less; medium, where one parent had lower secondary education and the other had higher education; and high, where both parents had a bachelor’s degree or higher. Family perceived wealth was assessed based on the participants’ reported ability to meet monthly expenses with their own earnings. Categories included low family perceived wealth, where participants barely managed to meet expenses; medium family perceived wealth, where participants passed the month without significant financial difficulty; and high family perceived wealth, where participants easily managed their finances without strain. In our analysis, we refer to parental education and perceived wealth separately to highlight their distinct impacts on childhood obesity.

Parental BMI

Data on parents’ body weight and height were collected via self-report questionnaires. Following WHO guidelines, we calculated parental body weight based on BMI [23]. During data cleaning, inconsistent responses, such as unusually low or high values were identified. Due to concerns about data reliability, these questionable responses were excluded from the dataset, resulting in the removal of 569 responses from the analysis. For a comprehensive analysis of its correlation with child body weight status, parental self-reported body weight was considered as continuous data.

In this study, participants were categorized based on their residential area as either urban or rural, using definitions aligned with official national classifications from the Georgian Statistical Office. Urban areas included both cities and semi-urban regions characterized by higher population density, significant infrastructure, and economic activity. These areas provide residents with access to a variety of services such as schools, healthcare, and recreational facilities. Rural areas, on the other hand, were defined as regions with lower population density, less infrastructure, and fewer economic opportunities, often consisting of villages or countryside locations with limited access to services.

Data analysis

The data analysis was conducted using SPSS V.24.0. Categorical variables are reported as frequencies and percentages, while continuous variables are presented as means and standard deviations (SDs). To identify variables associated with children’s overweight and obesity, several statistical tests were employed: chi-square tests were used to assess the associations between categorical independent variables and categorical dependent variables (normal weight vs. overweight/obesity), and independent samples t-tests were used to compare the means of continuous independent variables (such as maternal BMI and paternal BMI) between children of different body weight groups (normal weight vs. overweight/obese). Binary logistic regression was used to examine characteristics independently associated with overweight status. In the logistic regression analysis, continuous BMI values for both mothers and fathers were included as predictor variables to evaluate their associations with the likelihood of children being overweight or obese. Coefficients (Coefficient B) were used to represent the change in the log-odds of the outcome variable for each predictor variable and odds ratios (Exp (B)) to indicate how the odds of the outcome variable changed with a one-unit increase in the predictor variable. Statistical significance was defined as p < 0.05.

Results

A total of 3,334 2nd-grade children participated in the study, including 1,749 boys (52.5%) and 1,585 girls (47.5%). The mean age was 7 years, with a range of 6–8 years. Most of the children (71.7%) had a normal weight, 17.2% were overweight, and 11.0% were obese. The overweight and obesity rates were greater among boys, with 30.0% classified as overweight or obese (mean BMI = 16.8; ±SD = 2.9), than among girls (mean BMI = 16.4; ±SD = 2.7). The majority of participants (69.6%) lived in urban areas, where the prevalence of overweight/obesity was greater (30.3%) than in rural areas (23.6%) (mean BMI = 16.7 and 16.4 respectively). BMI was significantly positively associated with sex (p = 0.02) indicating that boys were more likely to be overweight/obese. Additionally, living area was significantly associated with overweight/obesity (p < 0.05) with a higher likelihood observed in urban areas (Table 1).

Table 1 Demographic characteristics and BMI z-score of 2nd-grade school children (Chi-square and t-tests)

Regarding dietary behaviors, the prevalence of healthy behaviors, such as regular consumption of breakfast, fresh fruits and vegetables, was generally low among the study participants. However, there were no statistically significant differences in the prevalence of these behaviors between normal-weight and overweight/obese children. Table 2 shows the prevalence of various dietary behaviors among the study participants, categorized by body weight status (normal weight vs. overweight/obese).

Table 2 Dietary behaviors by body weight status in 2nd-grade school children (n = 3334; Chi-square test)

Table 3 shows the prevalence of various physical activity behaviors, screen time, parental education and household socioeconomic status among normal-weight and overweight/obese children. Overweight/obese individuals tended to spend less time playing outside and were less likely to use active modes of transportation (p = 0.01 and p < 0.05, respectively). Additionally, parental education, as a component of family socioeconomic status, was identified as a significant factor associated with childhood overweight and obesity (p = 0.028), with higher parental education linked to a greater likelihood of childhood overweight/obesity.

Table 3 Factors influencing body weight status in 2nd-grade school children (n = 3334; Chi-square test)

The data provided in Table 4 reveal significant positive associations between parental BMI and children’s body weight status. Specifically, both maternal and paternal BMI were higher among overweight/obese children than among normal-weight children (p < 0.05).

Table 4 Association between parental BMI and child’s body weight status (independent samples t-tests)

Bivariate analysis revealed significant associations between body weight status and certain variables. There were no significant differences in dietary behaviors between individuals with a normal weight and those classified as overweight. Additionally, screen time and family perceived wealth did not show significant associations. According to our logistic regression analysis (Table 5), several factors were associated with increased odds of children being classified as overweight/obese. Living in urban areas was associated with a 1.3 times greater likelihood of overweight or obesity than living in rural areas; boys had 1.2 times greater odds of being overweight or obese than girls; and children who used passive transportation had a 25.2% greater chance of being overweight or obese than those using active transportation. Additionally, both parents’ BMIs played a significant role: for every one-unit increase in parental BMI, the likelihood of a child being overweight or obese increased by approximately 8.3% for mothers and 6.5% for fathers.

Table 5 Factors associated with overweight and obesity among 2nd-grade school children (logistic regression)

Discussion

Our study investigated the key factors associated with overweight and obesity among school-age children in Georgia. We found that approximately 28.2% of our target population was affected by these conditions, aligning with global trends showing a rise in childhood overweight and obesity rates. Certain demographic factors, such as sex and living area, were associated with children’s body weight status. The prevalence of overweight and obesity was greater in boys (30.0%) than in girls (26.3%), similar to the findings of earlier studies in other countries [24, 25], indicating the need for gender-specific approaches for addressing childhood obesity. Urban settings contribute to the prevalence of obesity not only due to limited opportunities for physical activity, increased sedentary behaviors and easier access to high-calorie foods but also due to increased levels of air pollution, road traffic and noise [26, 27]. In our study, children in urban areas showed a greater prevalence of overweight and obesity than did those in rural areas, aligning with studies emphasizing the link between urban living and an elevated risk of childhood obesity [28, 29]. However, other studies have reported lower obesity rates among urban children, possibly due to differences in socioeconomic status, cultural habits and access to recreational facilities [30, 31]. These findings show how local factors can impact childhood obesity.

Our study also highlighted the positive association between low physical activity and overweight (including obesity): children who spent less time playing outside and who relied on passive transportation, such as cars, were more likely to have elevated BMI. Although the association with outdoor playtime was not statistically significant, this finding suggested that less outdoor activity might increase the risk of overweight and obesity. This finding aligns with earlier studies conducted in other developing countries [32,33,34]. Physical inactivity is closely linked to obesity because children who are less active burn fewer calories, which are stored as fat. Additionally, sedentary behaviors, such as excessive screen time, also contribute to body weight gain by replacing active play by promoting unhealthy snacking habits [35, 36]. Research indicates that children who engage in screen-based activities for more than two hours per day are at a higher risk of obesity compared to those with less screen time [37, 38]. Furthermore, a cycle may develop where overweight children avoid physical activity due to body image concerns, exacerbating the issue over time [39, 40].

We found a significant association between parental BMI and childhood body weight status, consistent with international studies, suggesting that familial and genetic factors contribute to childhood obesity across diverse populations [41,42,43]. Additionally, parental education levels showed some association with childhood body weight status: children whose parents had a middle level of education were more likely to be overweight or obese compared to those whose parents had lower education level. However, there was no significant difference in the likelihood of overweight or obesity between children whose parents were highly educated and those whose parents were less educated. The association between parental education and childhood overweight/obesity varies across studies. Some studies indicate a higher risk with less educated parents [44,45,46,47], others, particularly in low-income countries, suggest a positive association with higher parental education [41]. This complexity underlines the importance of carefully considering socioeconomic factors when developing interventions to address childhood obesity.

However, our analysis did not reveal statistically significant associations between overweight and various dietary behaviors, screen time, or household socioeconomic status indicators. This could be due to limitations in self-reported data accuracy and reporting biases. Further research with more detailed dietary assessments could provide a better understanding of the relationship between diet and overweight in this population.

The strengths of this study include the use of the WHO growth reference to determine overweight and obesity, as well as the inclusion of a large number of schools across the country of Georgia, enhancing the representativeness of the sample. However, limitations such as the cross-sectional design and reliance on self-report questionnaires should be considered. Furthermore, our assessment of family SES was based only two indicators, parental education level and self-reported family perceived wealth. This approach may oversimplify the complex nature of socioeconomic status. This may limit our understanding of how these factors influence childhood obesity.

Additionally, the study’s focus on 2nd-grade school children aged approximately 7 years may limit the generalizability of the results to older or younger children. Longitudinal studies and objective measures of dietary and physical activity behaviors would be valuable in examining the temporal relationships between these variables and body weight status. Lastly, while BMI is a commonly used screening tool for overweight and obesity, it only provides an estimate of children’s nutritional status. BMI does not directly measure body fat and may not accurately reflect the health status of children with varying body compositions. Future studies should include more accurate measures of body composition, such as body fat percentage.

Conclusion

The prevalence of overweight and obesity among school children in the country of Georgia is high, highlighting the urgent need for interventions and public health strategies. This study is unique in its focus on the association between demographic factors, physical activity habits and parental body weight, specifically within the Georgian context. Sex, living area, physical activity habits and parental body weight were identified as significant contributors to childhood overweight and obesity. Importantly, the study underscores the unique socio-cultural dynamics present in urban and rural settings in Georgia, which impact children’s access to physical activity and healthy food choices. This aspect has not been thoroughly explored in previous research. Given that physical activity is the modifiable risk factor, interventions must focus on promoting regular physical activity among school-age children. This includes enhancing the physical education curriculum to encourage regular participation in physical activities and advocating for walking or cycling to school to increase daily physical activity level. To achieve effective results, public health programs should consider gender-specific strategies and address challenges related to urbanization.

Parents serve as role models for their children, influencing their perceptions of healthy body weight and lifestyle choices. Therefore, improving parental knowledge and skills regarding healthy lifestyle choices is crucial. Empowering parents to make healthier choices can significantly reduce the risk of childhood obesity.