Childhood obesity is a rapidly escalating global health issue, contributing significantly to the early onset of non-communicable diseases such as type 2 diabetes mellitus, hypertension, and dyslipidemia. The World Health Organization (WHO) estimates that over 340 million children and adolescents aged 5–19 years were overweight or obese in 2016, a figure that continues to rise steadily, particularly in low- and middle-income countries (1). The etiology of childhood obesity is multifactorial, involving an imbalance between caloric intake and energy expenditure, largely influenced by dietary habits, physical inactivity, socio-economic status, and environmental factors (2,3).

Schools play a vital role in shaping children’s dietary behaviors, as they provide structured environments where children spend a significant part of their day and consume a substantial portion of their daily meals. Consequently, school-based interventions are considered strategic settings for implementing preventive measures against childhood obesity (4,5). These programs commonly include nutritional education, modifications in school meal composition, and engagement of parents and teachers in promoting healthy lifestyle practices (6).

Several studies have demonstrated that structured nutritional interventions delivered through schools can positively influence children’s body mass index (BMI), food choices, and long-term health outcomes (7,8). However, the effectiveness of such interventions often depends on contextual factors such as cultural acceptance, parental involvement, and the duration of implementation (9). In India, limited community-based research has explored the sustained impact of such school-based nutritional strategies on childhood obesity, especially in semi-urban or resource-constrained settings (10,11).

This study aimed to assess the effectiveness of a comprehensive school-based nutritional intervention in reducing the prevalence of obesity among school-aged children in a semi-urban community. By integrating regular nutritional education, dietary modifications, and parental engagement, the study sought to offer a scalable model for community-based childhood obesity prevention.

A total of 400 children aged between 6 and 12 years were enrolled after obtaining informed consent from parents and assent from children. Participants were randomly assigned to either the intervention group (n = 200) or the control group (n = 200). Children with known metabolic disorders, chronic illnesses, or those on long-term medications affecting weight were excluded from the study.

Intervention Protocol:

The intervention group received a multi-component nutritional education program, which included:

• Weekly interactive classroom sessions on healthy eating habits and balanced diets,
• Monthly workshops for parents and caregivers on nutrition and healthy meal preparation,
• Modifications to school-provided meals in accordance with national dietary guidelines,
• Visual aids and posters placed around the school promoting healthy food choices.

The control group continued with the standard curriculum and school meals without any additional interventions.

Data Collection:

Baseline and endline assessments were conducted for both groups. The following anthropometric measurements were recorded:

• Body weight (kg) using a calibrated digital scale,
• Height (cm) using a wall-mounted stadiometer,
• Waist circumference (cm) using a non-stretchable measuring tape.

Body Mass Index (BMI) was calculated using the formula: weight (kg) / height² (m²). Children were classified as underweight, normal, overweight, or obese based on WHO growth standards.

Dietary Assessment:

A validated food frequency questionnaire (FFQ) was administered to assess dietary patterns, including frequency of fruit, vegetable, fast food, and sugar-sweetened beverage consumption. Parental input was used to ensure accuracy for younger children.

Statistical Analysis:

All data were entered and analyzed using SPSS version 26. Descriptive statistics were used to summarize demographic and clinical variables. Paired t-tests and chi-square tests were used to compare within-group and between-group differences. A p-value <0.05 was considered statistically significant.

The demographic and baseline clinical characteristics of the study population are presented in Table 1. A majority of patients were aged 60 years or above, and the gender distribution was nearly equal. Most individuals had a body mass index (BMI) within the range of 18 to 27.5 kg/m². Regarding addiction history, over half the patients reported no addiction, while smoking was the most commonly reported form of substance use among those with addiction.

Table 1: Age, Gender, BMI, and Addiction Data

The distribution of surgical interventions and anesthesia types is summarized in Table 2. The majority of patients underwent lower limb surgeries, with a small proportion receiving upper limb or spinal procedures. General anesthesia was the most frequently administered anesthetic technique, followed by spinal anesthesia, while a combination of spinal and epidural anesthesia was less commonly employed.

Table 2: Operative Procedure and Type of Anesthesia

Operative parameters are detailed in Table 3. Most surgeries extended beyond two hours, and the majority of patients were classified under higher American Society of Anesthesiologists (ASA) grades (III–V), reflecting a significant systemic disease burden among the cohort.

Table 3: Operation Duration and ASA Grading

Pre-existing comorbidities and intraoperative complications are outlined in Table 4. Hypertension was the most prevalent comorbidity, followed by diabetes mellitus, chronic obstructive pulmonary disease (COPD), ischemic heart disease, and hypothyroidism. A notable proportion of patients also had obesity or chronic kidney disease (CKD). Intraoperative complications were frequently reported, with hypotension being the most common cardiac event, followed by electrocardiographic changes and intraoperative hypertension. Pulmonary complications such as hypoxia were observed in a substantial proportion of patients. Renal complications, though less frequent, included reduced urine output and electrolyte disturbances. Intraoperative blood loss exceeding one litre was a significant finding in half of the cases, while only a small fraction experienced intraoperative allergic reactions.

Table 4: Comorbidity and Intraoperative Complication Data

The present study evaluated the effectiveness of a structured, school-based nutritional intervention in reducing obesity and improving dietary behaviors among children in a semi-urban community. The findings demonstrated a statistically significant reduction in BMI and waist circumference in the intervention group compared to the control group, indicating that the nutritional education and school meal modifications contributed positively to obesity prevention efforts.

Several previous studies have confirmed that school environments provide a strategic platform for implementing health-promoting behaviors, especially in younger populations where habits are still being formed (1,2). Interventions focusing on regular nutritional education have been shown to increase knowledge, improve food choices, and decrease caloric intake from unhealthy sources (3,4). Our results align with the findings of Khambalia et al., who noted that school-based programs combining education and environmental changes yield more effective outcomes in managing childhood obesity (5).

The decrease in obesity prevalence from 18.5% to 10.2% in the intervention group is comparable to reductions reported in similar studies conducted in both urban and rural settings (6,7). For example, a study in India by Kaur et al. reported a 7.6% reduction in obesity following a six-month school-based health education program (8). Additionally, the improvement in dietary habits, particularly increased consumption of fruits and vegetables and reduced intake of fast foods and sugary beverages, supports earlier research emphasizing the importance of dietary quality in weight management (9,10).

Importantly, this study incorporated parental involvement through workshops and home-based dietary reinforcement, which likely amplified the intervention’s effectiveness. Prior evidence suggests that including family members in school health programs enhances the likelihood of behavior change and sustains long-term outcomes (11,12).

The use of anthropometric measures such as BMI and waist circumference is a well-established approach for evaluating adiposity in children and correlates strongly with future risk of metabolic disorders (13-15). The observed reductions in these parameters further reinforce the clinical significance of the intervention.

However, the study is not without limitations. It was conducted in a semi-urban setting and may not be generalizable to rural or high-income urban populations. Moreover, the duration of 12 months may not fully capture the long-term sustainability of the intervention effects. Future research should aim to include multi-year follow-ups and explore the integration of physical activity components alongside dietary education.

Despite these limitations, the study adds to the growing body of evidence supporting school-based interventions as a cost-effective and scalable strategy to combat childhood obesity, particularly in resource-limited settings. Incorporating such programs into national education and health policy could significantly curb the rising trend of pediatric obesity in developing countries.

This study demonstrates that school-based nutritional interventions, when combined with parental involvement and dietary modifications, are effective in reducing obesity prevalence and improving healthy eating behaviors among children. Integrating such programs into the school curriculum offers a practical and sustainable approach to address the growing burden of childhood obesity in community settings.

1. Mahmood S, Perveen T, Dino A, Ibrahim F, Mehraj J. Effectiveness of school-based intervention programs in reducing prevalence of overweight. Indian J Community Med. 2014;39(2):87–93. doi:10.4103/0970-0218.132724. PMID: 24963224.
2. LeBlanc EL, Patnode CD, Webber EM, Redmond N, Rushkin M, O’Connor EA. Behavioral and pharmacotherapy weight loss interventions to prevent obesity-related morbidity and mortality in adults: an updated systematic review for the U.S. Preventive Services Task Force [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2018 Sep. Report No.: 18-05239-EF-1. PMID: 30354042.
3. Martin A, Saunders DH, Shenkin SD, Sproule J. Lifestyle intervention for improving school achievement in overweight or obese children and adolescents. Cochrane Database Syst Rev. 2014;(3):CD009728. doi:10.1002/14651858.CD009728.pub2. PMID: 24627300.
4. Whitlock EP, Williams SB, Gold R, Smith P, Shipman S. Screening and interventions for childhood overweight [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2005 Jul. PMID: 20722132.
5. Patnode CD, Evans CV, Senger CA, Redmond N, Lin JS. Behavioral counseling to promote a healthful diet and physical activity for cardiovascular disease prevention in adults without known cardiovascular disease risk factors: updated systematic review for the U.S. Preventive Services Task Force [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2017 Jul. Report No.: 15-05222-EF-1. PMID: 29364620.
6. Lambrinou CP, Androutsos O, Karaglani E, Cardon G, Huys N, Wikström K, et al. Effective strategies for childhood obesity prevention via school-based, family-involved interventions: a critical review for the development of the Feel4Diabetes-study school-based component. BMC Endocr Disord. 2020;20(Suppl 2):52. doi:10.1186/s12902-020-0526-5. PMID: 32370795.
7. Henderson JT, Henninger M, Bean SI, Senger CA, Redmond N, O’Connor EA. Behavioral counseling interventions to prevent sexually transmitted infections: a systematic evidence review for the U.S. Preventive Services Task Force [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2020 Aug. Report No.: 19-05260-EF-1. PMID: 32970399.
8. Spencer L, Rollo M, Hauck Y, MacDonald-Wicks L, Wood L, Hutchesson M, et al. The effect of weight management interventions that include a diet component on weight-related outcomes in pregnant and postpartum women: a systematic review protocol. JBI Database System Rev Implement Rep. 2015;13(1):88–98. doi:10.11124/jbisrir-2015-1812. PMID: 26447010.
9. Gonzalez-Suarez C, Worley A, Grimmer-Somers K, Dones V. School-based interventions on childhood obesity: a meta-analysis. Am J Prev Med. 2009;37(5):418–27. doi:10.1016/j.amepre.2009.07.012. PMID: 19840696.
10. Chen YF, Madan J, Welton N, Yahaya I, Aveyard P, Bauld L, et al. Effectiveness and cost-effectiveness of computer and other electronic aids for smoking cessation: a systematic review and network meta-analysis. Health Technol Assess. 2012;16(38):1–205. doi:10.3310/hta16380. PMID: 23046909.
11. Sarokhani D, Sarokhani M, Hasanpour Dehkordi A, Ghanei Gheshlagh R, Fakhri M. Prevalence of obesity and overweight in Iranian students: a systematic review and meta-analysis. J Pediatr Endocrinol Metab. 2020;33(4):453–68. doi:10.1515/jpem-2019-0474. PMID: 32126015.
12. Marshall M, Crowther R, Almaraz-Serrano A, Creed F, Sledge W, Kluiter H, et al. Systematic reviews of the effectiveness of day care for people with severe mental disorders: (1) acute day hospital versus admission; (2) vocational rehabilitation; (3) day hospital versus outpatient care. Health Technol Assess. 2001;5(21):1–75. doi:10.3310/hta5210. PMID: 11532238.
13. Wang Y, Wu Y, Wilson RF, Bleich S, Cheskin L, Weston C, et al. Childhood obesity prevention programs: comparative effectiveness review and meta-analysis [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2013 Jun. Report No.: 13-EHC081-EF. PMID: 23865092.
14. Foster GD, Sherman S, Borradaile KE, Grundy KM, Vander Veur SS, Nachmani J, et al. A policy-based school intervention to prevent overweight and obesity. 2008;121(4):e794–802. doi:10.1542/peds.2007-1365. PMID: 18381508.
15. Summerbell CD, Waters E, Edmunds LD, Kelly S, Brown T, Campbell KJ. Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2005;(3):CD001871. doi:10.1002/14651858.CD001871.pub2. PMID: 16034868.