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Childhood obesity is a growing health concern that increases the risk of cardiometabolic disorders. This study investigated family and lifestyle factors that contribute to overweight in schoolchildren.
Methods
This case-control study of 1,016 children (6–12 years) in Palembang was conducted using questionnaires and anthropometry. Multivariable logistic regression analysis was used to assess the association between selected variables and overweight, reported using adjusted odds ratios (AORs) with 95% confidence intervals (CIs).
Results
Frequent consumption of carbohydrate-rich foods, such as noodles or pasta, was associated with a higher risk of overweight (AOR, 1.76; 95% CI, 1.11–2.78; P=0.014). Limited protein 1 time per a day (AOR, 3.30; 95% CI, 2.00–5.43; P<0.001), flavored cow’s milk (AOR, 1.76; 95% CI, 1.06–2.95; P=0.029), and snacking (≥5 times per week) (AOR, 1.57; 95% CI, 1.04–2.39; P=0.031) also increased the risk. Conversely, daily fruit consumption reduced the risk (AOR, 0.66; 95% CI, 0.45–0.95; P=0.027). Family-related factors such as formal maternal employment (AOR, 1.57; 95% CI, 1.06–2.33; P=0.023), eating together less than 5 times per a week (AOR, 1.78; 95% CI, 1.04–3.04; P=0.032), and not bringing lunch to school (AOR, 1.96; 95% CI, 1.15–3.31; P=0.012) significantly increased the risk.
Conclusion
Several factors are associated with overweight among schoolchildren, including high intake of noodles or pasta, limited protein consumption, flavored milk, frequent snacking, low fruit intake, maternal employment, infrequent family meals, and not bringing food to school.
Childhood obesity is a serious health condition that has major health consequences and contributes to the development of type 2 diabetes and cardiometabolic problems in children and adults [1]. Obesity is a condition that begins with excess weight and continues to develop over time. Overweight and obesity are the result of the interaction between a person’s genetic predisposition to weight gain and environmental influences that are likely to persist into adulthood [2]. The prevalence of overweight and obesity in children has been associated with unhealthy eating habits, high consumption of energy-dense and nutrient-poor foods, and low fruit and vegetable intake. Excessive consumption of energy-dense, nutrient-poor foods and beverages high in saturated fat, added sugars, and salt can lead to weight gain, increased energy intake, and overweight and obesity [3].
Over the past few decades, the prevalence of overweight and obesity has increased across all age groups. In Indonesia, according to Indonesian Basic Health Research (Riskesdas), the prevalence of overweight and obesity increased significantly in most age groups between 2013 and 2018 [4]. Starting from 9.2% to 20.0% among children aged 5 to 12 years, 1.9% to 14.8% among adolescents aged 13 to 18 years, and 21.7% to 35.4% among adults aged >18 years [5]. Adults and children now frequently consume high-fat, high-sodium foods. Between 2007 and 2014, the percentage of overweight children remained constant, and working in physically demanding jobs continued to protect against overweight. More than half of Indonesians now live in urban areas, and living in urban areas is associated with higher odds of being overweight [6].
Considering the increasingly high rates of childhood obesity, the relevance and urgency of understanding children’s eating habits have become increasingly important. Implications arise from the association between nutrients, foods, and dietary patterns, particularly regarding the prevention and development of chronic diseases such as diabetes, cancer, chronic respiratory conditions (e.g., asthma and chronic obstructive pulmonary disease), and cardiovascular diseases (e.g., heart attack and stroke). Good eating habits are expected to support good nutritional intake in children. Nutritional intake plays an important role in optimizing children’s growth and development and is reflected not only in what children eat but also in how they eat [7]. Parents have a significant responsibility for shaping their children’s eating habits and dietary environment [8]. Family and peers are part of a child’s ecological niche, and these groups are affected by their community, society, media, and food sources. The environments in which children develop are complex and varied. Children receive food settings and eating experiences from their parents. Children follow their parents’ eating habits, way of life, attitudes toward food, and levels of body image satisfaction or dissatisfaction. Early life experiences affect dietary choices, which continue throughout life. Eating habits established in childhood have lasting consequences, including fussiness, a lack of variety in nutrition, and a higher risk of obesity, owing to heightened susceptibility to food cues. Children who are overweight or obese cannot be treated with medication unless significant comorbidities persist despite lifestyle modifications. Failure to take appropriate action will expose children to further weight gain, impaired glucose tolerance, and other related health effects, leading to widespread and serious health consequences. This study aimed to determine the various lifestyle and family factors associated with overweight among school-aged children in an urban area of Indonesia.
Methods
Study design and population setting
This case-control study was conducted from July to December 2024 with 1,016 schoolchildren. A multistage cluster random sampling approach was used to select a representative sample of the population. Palembang is geographically divided into the Ilir and Ulu regions, with a total of 17 sub-districts, comprising 13 sub-districts in Ilir and 4 sub-districts in Ulu. Four subdistricts were randomly selected, two from Ilir and two from Ulu, to ensure broad representation of the city’s population. This method ensured that 25% of the primary schools in each region were included in the sample, thus capturing the diversity of both areas separated by the Musi River. This study targeted children in middle childhood (aged 6–12 years) who were currently enrolled in elementary schools. Children with specific health conditions, such as growth hormone disorders, metabolic abnormalities (e.g., hypothyroidism, hyperthyroidism, or diabetes), heart conditions, kidney failure, or bone disease, were excluded from the study to minimize confounding variables. The selection of regions and subdistricts was based on their demographic and geographic representativeness, ensuring that the sample reflected a diverse range of children from both the urban and suburban areas of Palembang. Although a multistage cluster sampling approach was used, hierarchical clustering at the school level was not applied in the analysis. Each participant was analyzed individually. This approach was designed to ensure the robustness and generalizability of the findings to the broader urban population of elementary school children in Palembang. The sample size was calculated using a formula for case-control studies with a test power of 90% and z-value with 95% confidence intervals (CIs) to ensure sufficient power to detect significant associations between lifestyle factors and overweight in children.
Data collection, procedure, and measurements
Before data collection, a notification was sent to the school to be forwarded to the parents. Approval was also received from the teachers and school administration to assist in the approval and authorization of measurement implementation. All feedback and suggestions regarding the research objectives, participant information sheets, and interview question designs were considered and implemented. Each child’s weight and height were measured by a general practitioner assistant using standardized procedures to ensure consistency across participants. A commercial non-elastic tape measure was used to measure children’s height. Children stood barefoot with their feet hanging loosely, head up, and shoulders facing back. The highest point on the skull was represented by a point on a sizable piece of white cardboard affixed to a wall. The distance from the floor to the location was assessed using a tape measure. Height was rounded to within 0.1 cm. An electronic scale was used after removing heavy shoes, coats, and accessories and dressing in lightweight clothing. Totals were rounded to the nearest 100 g. The mean outcomes were determined after two or three repetitions of the measurements. Lifestyle data were collected through structured interviews with mother–child dyads. Trained data collectors used standardized, pre-tested tools to collect information on lifestyle factors [5,9]. These factors included dietary habits, screen time, and physical activity, which were chosen based on their well-established links to childhood obesity. This study considered both physical measurements and lifestyle behaviors to provide a comprehensive understanding of the factors that contribute to overweight in children.
Variable definitions
The dependent variable was childhood overweight, defined by body mass index (BMI) categories (overweight cases and normal weight controls). The dependent variable was childhood overweight, defined using BMI-for-age z-scores based on the growth standards recommended by the World Health Organization (WHO). Children were classified as overweight (cases) if their BMI-for-age z-score was greater than +1 standard deviation (SD) and as normal weight (controls) if their z-score ranged from −SD to +1 SD. Trained personnel using standardized procedures and calibrated equipment collected anthropometric measurements, including weight and height. Inter-rater consistency was evaluated before data collection through a training session and pilot measurement exercise to ensure data reliability. The independent variables included lifestyle factors, such as eating patterns (frequency and type of carbohydrates, protein, vegetables, fruits, and milk consumed), snacking habits (<5 or ≥5 times per week), soft drink consumption, family eating routines (≥5 or <5 times per week), school lunch habits (yes or no), and gadget use (duration and frequency). Physical activity was assessed using after-school playtime frequency. Family factors encompassed parental employment status (not working, informal, or formal), education level (bachelor’s degree, junior/senior high school, or elementary school), and number of siblings (<3 or ≥3). These variables aimed to capture the interplay between lifestyle choices and family influences in contributing to the prevalence of childhood overweight in the studied population.
Data analysis
Categorical variables are presented as percentages. Chi-square tests were used in the bivariate analysis to determine the association between lifestyle factors and childhood obesity. Logistic regression models were used in a multivariate setting to investigate lifestyle and family risk factors for childhood overweight. Multi-collinearity among the independent variables was assessed using the variance inflation factor, and all values were within acceptable limits. Data were analyzed using Stata ver. 15.0 (Stata Corp.) and WHO Anthro Plus software ver. 1.02 (WHO). Statistical significance was set at P<0.05 for all tests.
Ethical approval
This study involved human participants and was approved by the appropriate ethics committee. All procedures performed in this study involved human participants and were conducted in accordance with the ethical standards of institutional research committees. All source documents, including the questionnaires, were anonymized to ensure anonymity. This study was approved by the Chief Ethics Committee of the Medical Faculty of Universitas Sriwijaya on July 15, 2024 (protocol number: 206--2024). This certificate confirms the ethical clearance of the application of the first author (I.A.L.). We declare that the protocol has been granted exempt status. This research was also approved by the National Unity and Politics Service, Department of Education Service, and Public Health Office of Palembang. All participants provided informed consent before taking part in the study.
Results
The total participant sample comprised 1,016 children, including 459 (45.18%) boys and 557 (54.82%) girls. Of the participants, 20.67% (n=210) were overweight and 79.33% (n=806) were normal weight. Table 1 shows that maternal employment status is a sociodemographic factor significantly associated with being overweight. The research findings indicate an association between a maternal working position and overweight (odds ratio [OR], 1.71; 95% CI, 1.21–2.43; P=0.002), suggesting that children whose mothers held formal jobs were more vulnerable to weight gain. Among the children, 18.38% of those whose mothers were not working were overweight, compared to 19.15% of those with mothers in informal employment and 27.90% of those with mothers in formal employment. In contrast, sex did not significantly affect overweight risk, with 23.09% of boys and 18.67% of girls being overweight (OR, 1.30; 95% CI, 0.95–1.79; P=0.084). Paternal educational level showed no significant effect on childhood overweight. Number of siblings also had no significant effect on overweight, with 20.0% of those with fewer than three siblings and 21.56% of those with three or more siblings being overweight (OR, 0.91; 95% CI, 0.66–1.25; P=0.544).
Bivariate analysis was used to identify several lifestyle factors significantly associated with childhood overweight (Table 2). High consumption of noodles or pasta and limited protein intake (once per day) were associated with an increased risk, whereas frequent consumption of bread and daily fruit intake appeared to be protective factors. Children who snacked more than 5 times per week and those who did not bring lunch from home had higher odds of being overweight. Eating with family at least 5 times per week was associated with a lower risk. Excessive gadget use, particularly durations exceeding 2 hours per day, showed a strong association with overweight (OR, 4.25; 95% CI, 2.84–6.36; P<0.001), whereas after-school physical activity showed no significant association. These findings indicate the selection of variables for the multivariable model.
Multivariable logistic regression analysis identified several factors that were significantly associated with overweight in elementary school children (Table 3). Children who consumed protein only once per day had a significantly higher risk of overweight (adjusted odds ratio [AOR], 3.30; 95% CI, 2.00–5.43; P<0.001). In contrast, daily fruit consumption was a protective factor (AOR, 0.66; 95% CI, 0.45–0.95; P=0.027). Unhealthy eating behaviors also contributed to the risk. Frequent snacking (≥5 times per week) increased the likelihood of being overweight (AOR, 1.57; 95% CI, 1.04–2.39; P=0.031). Children who did not bring lunch from home were more likely to be overweight (AOR, 1.96; 95% CI, 1.15–3.31; P=0.012). Additionally, eating with family fewer than 5 times per week was associated with a higher overweight risk (AOR, 1.78; 95% CI, 1.04–3.04; P=0.032). The strongest predictor was excessive gadget use, with children who used gadgets for more than 2 hours per day having markedly higher odds of being overweight (AOR, 5.19; 95% CI, 3.26–8.25; P<0.001). This indicated a robust association between screen time and childhood overweight, even after adjusting for confounding factors. Other variables, including maternal employment status and type of milk consumed, did not remain significant in the adjusted model.
Discussion
This study confirms that childhood overweight is influenced by a complex interplay of dietary habits, screen time, and family-related factors, supporting a holistic approach to obesity prevention [10]. Sociodemographic variables, such as maternal employment, play a critical role, consistent with findings from Huls et al. [11] showing links between parental education, screen time, and obesity risk. Children with mothers who were formally employed had a higher risk of overweight (27%), potentially because of limited time for meal preparation and supervision [12,13]. This aligns with Fertig et al. [14], who reported that working mothers often rely on convenience foods and sugar-sweetened beverages. Supporting work–life balance may help families adopt healthier lifestyles and reduce obesity prevalence [15].
This study also explored various factors that influence childhood obesity, highlighting how everyday family factors and dietary patterns can play significant roles. The findings suggest that carbohydrate consumption, particularly from noodles or pasta, protein intake frequency, flavored milk consumption, family meal practices, lunch packing, snacking habits, and screen time contribute to children’s weight outcomes. High carbohydrate consumption, especially from refined sources, such as noodles, can lead to increased calorie intake without providing essential nutrients. This finding is similar to those of several other studies showing that excessive consumption of refined carbohydrates is associated with a higher risk of obesity in children and adolescents [16,17]. However, one study in the United States showed that pasta consumption is associated with better diet quality [18]. Further studies are needed to reveal the link between pasta or noodle intake and childhood obesity.
Regular protein intake appeared to be linked to healthier weight, indicating that protein-rich meals can help children feel fuller and more satisfied. However, this study’s findings conflict with those of several previous studies indicating that high protein consumption can lead to a higher risk of childhood overweight [19]. Encouraging families to include more balanced meals with optimal protein levels could be a practical way to support healthier eating habits [20]. Flavored milk is another contributor to childhood overweight. Although it provides essential nutrients such as calcium and vitamin D, its added sugars significantly increase total calorie intake [21]. This is consistent with the findings of Kanellopoulou et al. [22], who reported that children who consumed chocolate milk had a 14.5% higher risk of being overweight, whereas those who consumed only white milk were 30.4% less likely to be obese. Educating families about the differences between flavored and plain milk and encouraging water or low-sugar alternatives has been shown to effectively reduce sugar-sweetened beverage consumption in children [23].
This study also found that shared family meals were associated with healthier weight outcomes in children. This supports the findings of Lopez-Gil et al. [24] and Moreno-Aznar et al. [25], who emphasized that frequent family meals reduce the risk of overweight and obesity. Shared mealtimes promote better dietary quality and foster healthy eating behaviors. Similarly, bringing lunch from home was linked to healthier food intake, likely because of greater parental control over meal quality. Frequent snacking, especially on energy-dense foods, was significantly associated with an increased risk of overweight, consistent with studies showing that lunchbox interventions and snacking regulation help manage children’s weight [26,27].
Gadget use was another strong risk factor. Prolonged screen time encourages sedentary lifestyles and often coincides with mindless eating. Paduano et al. [28] and Rocka et al. [29] found that extensive use of tablets, smartphones, or video games was among the strongest predictors of childhood obesity. Reducing screen time and encouraging active play should be key components of obesity prevention strategies. Interpreting the dietary pattern findings indicates that reverse causation may be at play. Specifically, overweight children may be more prone to changing food choices or portion sizes by themselves or having their parents change them, all of which will affect the observed associations. Furthermore, variability in portion size, especially for carbohydrate- and snack-rich foodstuffs, may considerably influence calorie imbalance despite similar frequencies of consumption across groups. This must be considered when designing interventions, because both the type and amount of food consumed can have significant implications for weight outcomes.
These findings strongly suggest that incorporating more fruit into children’s diets is associated with healthier weight outcomes. Fruit is not only low in calories but also packed with essential vitamins, minerals, and fiber. This study showed that children who ate more fruit tended to feel fuller, which could help prevent overeating. Furthermore, the natural sugars in fruit provide a healthier alternative to sugary snacks and drinks, making it an excellent option for satisfying sweet cravings without extra calories. These findings are in line with those of Folkvord et al. [13], who promoted the consumption of healthy foods, such as fruits and vegetables, to prevent obesity in children. Tambalis et al. [30] corroborated this finding by stating that fruit intake is correlated with a lower incidence of obesity in children. This emphasizes the importance of promoting fruit intake as part of a balanced diet for children.
The generalizability of this study’s findings should be approached with caution because of the specific urban sample and school-based setting. Although the participants came from various socioeconomic backgrounds, the results may not reflect rural or underprivileged populations, in which obesity rates and contributing factors may differ significantly owing to environmental, cultural, and dietary variations. Additionally, these findings are based on data from one region, limiting their applicability to other countries with different food norms, physical activity levels, and cultural practices around family and meals. The case-control design allows for the identification of associations, but not causation. Reliance on parental self-reports for dietary patterns, routines, and screen time also introduces potential recall bias and underreporting of unhealthy behaviors. Longitudinal research is required to establish causal pathways and inform effective prevention strategies. Notably, overweight was slightly more common in boys than in girls. Key risk factors included high protein intake frequency, unhealthy snacking, and excessive screen use (>2 hours daily), whereas protective factors included fruit consumption, bringing lunch from home, and regular family meals. Sociodemographic factors, particularly maternal employment status, also played a role. These findings suggest that improving children’s eating habits, limiting screen time, and promoting family mealtimes could help address childhood overweight. Incorporating behavioral interventions alongside sociodemographic considerations is essential for effective prevention, especially across diverse populations and contexts.
This study demonstrated the multifactorial determination of childhood overweight. Diet, lifestyle behaviors, and sociodemographic factors are important factors that correlate with excess weight among children. High intake of refined carbohydrates, frequent unhealthy snacking, flavored milk consumption, and length of exposure to screens were identified as risk factors, whereas fruit consumption, family meals, and home-packed lunches were protective factors. This emphasizes the importance of using integrated strategies in family medicine to assess behavioral and structural influences on health. Targeted interventions to promote healthy eating, reduce sedentary behaviors, and provide support for families, especially working parents, could be of great importance in preventing childhood overweight in urban settings.
Notes
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Acknowledgments
The authors would like to thank all those who contributed to this research.
Funding
The author thanks the Ministry of Research, Technology, and Higher Education Indonesia for supporting this research through the Fundamental Regular Research Grants from the Directorate of Research, Technology, and Community Service, Directorate General of Higher Education, Research, and Technology in accordance with the Implementation Contract for the State University Operational Assistance Program for the 2024 Fiscal Year Research Program (No. 090/E5/PG.02.00.PL/2024).
Data availability
Data of this research are available from the corresponding author upon reasonable request.
Author contribution
Conceptualization: IAL, LH, NAF. Data curation: IAL, SDP, MI, RA. Formal analysis: IAL, LH, SDP, P. Investigation: IAL, SDP, MI, P. Project administration: FHT, P, SDP. Visualization: IAL, LH, RA. Writing–original draft: IAL, LH, NAF, FHT, RA. Writing–review & editing: IAL, FHT, HH. Final approval of the manuscript: all authors.
Table 1
Associations between family sociodemographic characteristics and childhood overweight (n=1,016)
AOR, adjusted odds ratio; CI, confidence interval; Ref, reference.
*P<0.05 (Statistical significance).
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, Laily Hanifah3
