Study of different lifestyle parameters and their impact on health parameters of rural and urban adolescent school children

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This cross-sectional study conducted on 979 students of both sexes in different schools during August-November-2023. A predesigned, structured questionnaire containing food habits (vegetarian/non vegetarian), frequency of non-vegetarian and junk food consumption, mode of transport to schools, screen watching time, time spent for physical activity, health issues and stress levels was answered by the study subjects. Anthropometric measurements were taken to measure body mass index (BMI). The study found that high percentage of girls in rural and urban schools are vegetarians than boys. Non-vegetarian food consumption is high among urban boys than other groups and urban school children show high frequency of fast-food consumption. Urban school children also showed higher levels of less physical activity, vehicle use, and screen watching. In underweight category, regardless of school type, a greater number of girls were recorded, while higher percentages of urban private school boys were found to be overweight and obese than other groups. A higher percentage of boys and girls in rural and urban schools reported partial mental health issues. The findings highlight that rural urban divide and changed life style factors profoundly influence underweight/overweight/obesity that consequently affects a child's psychological well-being. It accentuates the importance of bringing in awareness among students, teachers and parents about nurturing healthier lifestyles that fosters improved health and overall well-being of adolescent children. Adolescent school children Body mass index Food habits Fast foods Mental Health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Overweight or underweight is a complex, multifactorial condition that arises from an intricate interplay of genetic, demographic, and lifestyle factors [ 1 ]. Current evidence highlights that it is not solely a result of individual behaviour or willpower but also influenced by broader societal and environmental changes [ 2 – 3 ]. While the incidence of obesity is not new to the developed countries, the main drivers of the escalating trends of childhood obesity in India and other developing countries are changed life styles, increased accessibility to energy density foods and drinks, changed work habits, ambient temperatures, sedentary lifestyles, rapid nutritional transitions, increasing affluence, socioeconomic transitions, urbanization, mechanization, rural-to-urban migration and disturbed biological clocks [ 4 – 7 ]. In the present times, children consume three times more food from fast-food outlets/restaurants compared to 30 years ago [ 8 – 9 ]. This increase may be attributed to the affordability and accessibility of fast foods, extensive food advertising, and the fact that both parents often work, leaving less time to prepare home-cooked meals for the family [ 10 ]. Studies examining the relationship between physical activity and metabolic disorders have shown less consistent results, with findings varying based on the method used to assess physical activity. In studies that utilized accelerometer, physical activity consistently showed a negative association with metabolic syndrome; however, this association was weaker compared to the relationship observed with fitness levels [ 11 ]. In addition, overweight and obesity is favored by risky dietary behaviors such as consumption of fast foods and drinks, eating away from home, skipping/missing of meal, regular drinking of sugar rich beverages and low intake of fruit and vegetables. Overweight/Obesity plays a central role to develop hyper tension, dyslipidemia, diabetes, insulin resistance, CVDs and some types of cancers [ 12 ]. The results of the healthy lifestyle in Europe by nutrition in adolescence (HELENA) study, which included 3,528 children from European cities, suggested that children in the 9-year-old age group with a low physical fitness level were at elevated risk of developing cardiovascular risk factors such as obesity and overweight [ 13 ]. Adolescence may be the period of greatest risk for those with these disorders. Adults who have been obese since childhood are more likely to suffer from stress, depression and other psychological disorders [ 14 ]. Body mass index (BMI) is the most widely accepted tool in epidemiological studies and clinical practice to diagnose excess body weight in both children and adults. In children, there is no a clear consensus on the BMI-based obesity classification method that should be used to identify overweight and obesity [ 15 ]. Considering the mushrooming of private schools in India, where sedentary type of environment prevails, there is more scope for such students to develop risk factors that lead to obesity and associated disorders when compared to govt.schools. Thus, the present study aimed to examine demographic, behavioral, and lifestyle factors and their association with underweight, overweight, obesity, and other health issues. These findings will help national health authorities identify target populations and formulate appropriate policies to address health and social inequalities, thereby contributing to the development of a stronger and healthier nation. 2 Methods 2.1 Study design and study setting The study was conducted in randomly selected government and private schools in Tirupati in around rural and urban areas. Out of 20 schools invited to participate, 16 schools consented and permitted data collection, while 4 schools declined participation due to academic schedule constraints. The study was carried out from August 2023 to October 2023 among both male and female students from classes 8 to 10, aged 12–16 years. Various lifestyle-related parameters, including dietary habits, physical activity, and behavioural factors, were assessed to evaluate underweight, overweight, obesity, and other physiological and stress-related conditions. 2.2 Questionnaire A pre-designed, pre-tested, and semi-structured questionnaire was used to collect data on students’ food habits (Veg/Non-veg consumption), physical activity, screen time (Cell phone, TV watching etc.), health issues, and stress levels. The questionnaire was developed after reviewing relevant literature and was reviewed by subject experts to ensure content validity. It was pre-tested among a small group of students for clarity and suitability. The questions were explained in both teaching and local language (Telugu) for better understanding. Although no formal statistical validity or reliability testing was conducted, the tool was refined through expert review and pilot testing to ensure consistency and appropriateness for the study population. 2.3 Inclusion criteria Inclusive criteria were followed by considering apparently healthy children in the age group of 12 to 16 years without any chronic illness or any surgery in near past. 2.4 Exclusion criteria Exclusive criteria were followed by not selecting the students diagnosed with chronic disease and on medication from one year, and also those who are unwilling to participate. 2.5 Anthropometric measurements Anthropometric measurementslikeheight, weight were taken by using stadio meter and digital weighing machine for each student, and body mass index (BMI) was calculated by the following formula. 2.6 Human ethical committee approval Institute human ethical committee approval was obtained (SVU/IHEC/002/2023) and the approved procedures were followed to collect data. A total of 1,050 students were invited to participate in the study, of which 979 consented and completed the questionnaire, yielding a response rate of approximately 93.2%. Participation was voluntary, and students could withdraw at any point without providing a reason. 2.7 Data quality control For data quality control a pre-test on 5% of the samples was performed and regular supervision during data collection was also carried out. The completeness of the questionnaire was checked before data entry too. 2.8 Statistical Analysis Statistical analysis was performed using the computer software SPSS for Windows version 14.0 (SPSS Inc., Chicago, USA). Analysis of variance factorial analysis and post hoc multiple comparisons were used to evaluate the significance of the differences. Differences in proportions were analysed using the Chi-square test. 3 Results 3.1 Demographic characteristics and gender-based body mass index distribution among school adolescents A total of 979 students completed the questionnaire, achieving a 93.2% response rate. The government and private schools distributed in rural and urban areas and percent of boys and girls are presented in table-1. Among the total participants, 467 (47.7%) were girls, among them, 81 are from rural government schools and 73 are from rural private schools, 127 are from urban government schools and 186 are from urban private schools. The total number of boys in the present study is 512 (52.3%), among them, 95 are from rural government schools and 85 are from rural private schools, 157 are from urban government schools and 175 are from urban private schools. Based on their BMI, adolescent children from different school areas were classified into underweight, normal weight, overweight and obesity (Tables 1 and Table 2 ). Table 1 Classification of male students of different schools in to different weight groups based on BMI in Percentages. Male N(%) Rural Govt 95(%) Rural Pvt 85(%) Urban Govt 157(%) Urban Pvt 175(%) Under Weight 5(5.3) 8(9.4) 20(12.7) 29(16.6) Normal 62(65.3) 56(65.9) 90(57.3) 64(36.6) Over Weight 17(17.9) 13(15.3) 36(22.9) 48(27.4) Obese 11(11.6) 8(9.4) 11(7.0) 23(8.1) Table 2 Classification of female students of different schools in to different weight groups based on BMI in Percentages. Female N Rural Govt 81(%) Rural Pvt 73(%) Urban Govt 127(%) Urban Pvt 186(%) Under Weight 9(11.1) 19(26.0) 43(33.9) 68(36.6) Normal 56(69.1) 34(46.6) 43(33.9) 72(38.7) Over Weight 12(14.8) 9(12.3) 29(22.8) 32(17.2) Obese 4(4.9) 11(15.1) 12(9.4) 14(7.5) Based on the height and weight, BMI was calculated and students were divided as underweight, normal weight, overweight and obese. In rural government schools category, 11.1% girls are underweight when compared to boys (5.3%), 14.8% girls are overweight when compared to boys (17.9%) and 4.9% girls are obese when compared to boys 11.6%. In rural private schools, more girls (26%) are underweight compared to boys (9.4%), and slightly more girls (15.1%) are obese than boys (9.4%). In urban government schools, a higher percentage of girls (33.9%) are underweight compared to boys (12.7%), in overweight group, boys and girls showed almost same percentage (22.8%), and in obesity group girls showed 9.4% and boys showed 7%. In urban private schools, the contrast is sharper: 36.6% of girls are underweight compared to 16.6% of boys, while 27.4% of boys are obese versus only 7.5% of girls. Across all categories, boys are more often found in the overweight and obese groups, while girls especially in urban settings are more likely to be underweight or within the normal range. This highlights a noticeable gender difference in body weight trends that may reflect lifestyle, diet, and health behaviours. 3.2 Fast food consumption and dietary Preferences by gender and school type Figure 1 (a) and (b) explains that, in more than 3 times fast food consumption per week group, more number of rural private school students (50% boys, 54% girls) figured when compared to rural government school students (about35% of both sexes). In urban private schools, both boys and girls have high fast-food intake, with 58.9% of boys and 55.9% of girls consuming fast food more than 3 times a week. Overall, students in private schools, especially in urban areas, tend to eat fast foods more frequently, may be due to high availability of fast foods near urban schools. Figure 1 (c) and (d) shows the types of food preferences (vegetarian, non-vegetarian, mixed) among school students across rural and urban areas in both government and private schools. In rural government schools, 49.4% of girls are vegetarians, while boys are only 21.1%, and most boys (45.3%) prefer a mixed diet. In rural private schools, 52% of girls are vegetarian, compared to just 11.8% of boys, while most boys prefer non-vegetarian (48.2%) or mixed diets (40%). In urban government schools, food preferences are more evenly spread, with boys favouring non-vegetarian food (45.9%) and girls leaning toward mixed diets (35.4%) and non-vegetarian (38.6%). In urban private schools, the pattern shifts 44.9% of girls are vegetarian, while boys mostly prefer mixed diets (56%). Only 17.6% of urban private school girls eat mixed diets, compared to 56% of boys. Overall, girls are more likely to be vegetarians, especially in rural and private schools, while boys particularly in private schools show a stronger preference for mixed and non-vegetarian diets. This suggests gender and school-type influence food habits, possibly due to cultural norms, family practices, or personal choices. 3.3 Transport modes and outdoor physical activity patterns among schoolchildren Figure 2 (a) and (b) explains the mode of transport among schoolchildren, exhibited notable rural–urban and government–private school disparities. In rural areas, walking or cycling was found to be the predominant mode, with the highest prevalence observed among boys of government school (81.10%), followed by girls of private school (74.00%), boys of private school (71.80%), and government school girls (70.40%). Conversely, vehicle usage was comparatively lower in these groups, ranging from 18.90% to 29.60%. In contrast, urban areas demonstrated a shift towards increased dependence on vehicular transport, particularly among private school students. Boys of private schools reported vehicular transport (58.30%), followed by private school girls (49.50%), government school girls (41.00%), and government school boys (31.80%). These findings suggest that urbanization and school type influence transport choices, with urban and private school students showing greater reliance on motorized vehicles compared to their rural and government school counterparts, who primarily depend on walking and cycling. As shown in Fig. 2 (c) and (d) , in rural government schools, 64.2% of boys spend more than 2 hours a day on outdoor games, while only 30.9% of girls do so. In rural private schools, a similar pattern is observed, with 70.6% of boys spending more than 2 hours, compared to only 34.2% of girls. The difference is more noticeable in rural areas, where boys engage in outdoor games much more frequently than girls. In urban government schools, the time spent is more balanced, with 52.3% of boys and 52% of girls spending more than 2 hours a day on outdoor activities, indicating more equal participation in physical activities. In urban private schools, 69.1% of boys and 65.6% of girls spend less than 2 hours/day, with a smaller proportion of both genders spending more than 2 hours daily (2 days in a week) for outdoor games. Overall, rural private schools show a marked difference between boys and girls in outdoor game participation time with boys engaging more time for outdoor physical activities. 3.4 Screen time patterns: Television and mobile phone use The Fig. 3 (a) and (b) show the time spent (less than 2 hours or more than 2 hours a day) for watching TV by boys and girls across rural and urban areas in government and private schools. In rural government schools, both boys and girls (about 65%) spend less than 2 hours per day watching TV. The same trend is seen in rural private schools (47.1% of boys and 49.3% of girls) spending less than 2 hours per day watching TV. In urban government schools, 52.9% of boys and 45.7% of girls spend less than 2 hours per day watching TV, while the remaining percentage of students watch TV for more than 2 hours. In urban private schools, a larger percentage of boys (48%) and girls (43%) watch TV for more than 2 hours per day. Overall, across both rural and urban areas, boys and girls spend a relatively similar amount of time watching TV, with some slight variations depending on the area and type of school, but the differences are generally not statistically significant. The patterns suggest that TV watching habits are quite balanced across genders. Figure 3 (c) and (d) shows the time spent on mobile phones watching by boys and girls across rural and urban areas in government and private schools. In rural government schools, time spent on mobile phone usage was less by both boys and girls (67–71% spend less than 2 hours per day on mobile phones), while the remaining percentage spend more than 2 hours. In comparison, in rural private schools, the percentage of boys and girls who spend less than 2 hours per day on mobile phones was 54.1&45.9% % respectively, while the remaining spends more than 2 hours. In contrast, 78.1% of girls in rural private schools use mobile phones for less than 2 hours, while only 21.9% spend more than 2 hours. In urban government schools, 50.3% of boys and 52% of girls spend less than 2 hours per day on mobile phones, with a near-equal split in usage over 2 hours. In urban private schools, 52.5% of boys and 45.7% of girls spend less than 2 hours, while 44.3% of boys and 54.3% of girls use mobile phones for more than 2 hours. Overall, rural private school students, particularly girls, tend to use mobile phones less frequently, while urban private school students, especially girls, are more likely to spend more than 2 hours on their phones. Private school students in both rural and urban areas generally spend more time on mobile devices than their counterparts in government schools. 3.5 Prevalence of vision and dental problems among schoolchildren The Fig. 4 (a) and (b) highlight the presence of vision problems among schoolchildren in rural and urban areas, comparing government and private schools. In rural government schools, 18.9% of boys and 9.9% of girls have reported vision problems. In rural private schools, a higher percentage of boys (17.6%) and 42.5% of girls have reported vision problems. In urban government schools, 25.5% of boys and 17.3% of girls experienced vision problems, in urban private schools, 29.7% of boys and 9.7% of girls had vision problems, with the majority of both boys (38.9%) and girls (55.4%) reporting no issues. A significant portion of boys (31.4%) and girls (35%) had partial vision problems. Overall, private school students in both rural and urban areas reported more vision problems compared to their government school counterparts, with urban private school boys being most affected. The differences in vision issues across gender and school types indicate a need for targeted interventions for schoolchildren's eye health. Figure 4 (c) and (d) present data on dental problems among schoolchildren studying in government and private schools located in rural and urban areas. Dental problems were identified as partial dental, dental and no dental issues. In rural government schools, 13.7% of boys and 18.5% of girls have reported dental problems, and partial dental issues were found in 15.8% of boys and 13.6% of girls. In rural private schools, 24.7% of boys and 30.1% of girls had dental problems, while partial dental issues were reported by 17.6% of boys and 21.9% of girls. In urban government schools, 29.3% of boys and 17.3% of girls reported dental problems and a notable portion (24.8% of boys and 29.1% of girls) reported partial dental problems. In urban private schools, 16% of boys and 16.1% of girls reported dental problems, and 32.6% of boys and 32.3% of girls reported partial dental problems. Overall, a considerable percentage of students from urban private and government schools showed more partial dental issues when compared to rural students. 3.6 Stress, anxiety, and depression among schoolchildren Figure 5 (a) and (b) explains students who were reported feeling partial stress, stress or no stress. In rural government schools, 17–18% of boys and girls expressed partial stress and anxiety, 7.4% of boys and 14.8% of girls reported stress and anxiety and the remaining did not report any mental health issues. In rural private schools, 28.2% of boys and 24.7% of girls reported partial stress/anxiety issues, 14.1% of boys and 16.4% of girls experienced stress and anxiety and the remaining showed no mental health issues. In urban government schools, 34.4% of boys and 34.6% of girls reported partial stress/anxiety issues 22.9% of boys and 7.9% of girls experienced stress and anxiety. In urban private schools, 17.1% of boys and 12.4% of girls had mental health issues, and 29.1% of boys and 25.8% of girls reported partial stress and anxiety and the remaining students had no mental health issues. Overall, a considerably larger percentage of girl students in rural schools were found to be suffering with more stress and anxiety than boys, in contrast, in urban schools a greater number of boys were reported with stress and anxiety. A higher percentage of boys and girls in rural and urban schools suffer with partial mental health issues. Figure 5 (c) and (d) provides data on depression among schoolchildren studying in government and private schools of rural and urban areas. In rural government schools, 10.5% of boys and 13.6% of girls reported experiencing depression, only 9.5% of boys and 11.1% of girls reported partial depression and the remaining were with no depression. In rural private schools, 11.8% of boys and 16.4% of girls reported depression, a moderate portion (20% of boys and 21.9% of girls) experienced partial depression and the remaining were without any depression. In urban government schools, 10.8% of boys and 15.7% of girls reported depression, while partial depression was reported in 21.7% of boys and 26.8% of girls. In urban private schools, 17.1% of boys and 9.7% of girls reported depression, and partial depression was found in24%boys and 29.6% girls. Our results demonstrate that, a considerably larger percentage of girl students in rural schools were found to be with depression than boys, in contrast, in urban schools more boys are found to be with depression. Partial depression was reported by a larger percentage of both boys and girls in both rural and urban schools. 4 Discussion Sedentary life styles and modern food habits significantly influence the health status of adults and adolescent school children. The present study by taking weight and height, BMI distribution among school children in the Tirupati region was done and it reveals significant disparities based on school type and location. Rural government schools have a healthier BMI profile, with 65.3% of boys and 69.1% of girls in the normal range. However, rural private schools have a dual burden of underweight and obese girls, indicating nutritional imbalances. Urban government schools have a higher prevalence of overweight or obese girls, with 33.9% maintaining normal BMI and 32.2% being overweight or obese. Addressing these issues requires targeted interventions, including nutrition education, physical activity promotion, and mental health support, especially in urban and private school settings. With regard to food consumption pattern, in rural government schools, a significant portion of male students 45.3% consume a mixed diet, while 33.7% are non-vegetarians and 21% are vegetarians. In contrast, rural private school students exhibit a higher preference for non-vegetarian foods, with 41.9% of boys and 52.1% of girls consuming non-vegetarian meals, and 11.8% of boys and 52.1% of girls consuming vegetarian meals (Table 1 and Table 2 ). Urban government school students show a more balanced distribution, with 46.2% of boys and 26% of girls consuming non-vegetarian foods, and 21.6% of boys and 26.8% of girls consuming vegetarian meals. Urban private school students have the highest preference for mixed diets, with 56% of boys and 44.1% of girls consuming mixed diets, and 26.3% of boys and 41.9% of girls consuming non-vegetarian foods (Fig. 1 (a-d) ).​ These patterns suggest that urban and private school students have greater access to diverse food options, possibly due to better economic conditions and availability of various food types. In contrast, rural students, particularly in government schools, may have limited access to diverse food options, leading to a higher consumption of vegetarian and mixed diets. This disparity underscores the need for targeted interventions to promote balanced and nutritious diets among students, especially in rural and government school settings. Additionally, socioeconomic factors and infrastructure development play crucial roles in shaping students' food consumption patterns, highlighting the importance of addressing these underlying factors to improve dietary habits among school children [ 16 ].​ Similarly in fast food consumption in rural government schools, a majority of male students 66.3% consume fast food less than three times per week, while 33.7% consume it more frequently. In rural private schools, 49.4% of boys consume fast food less than three times per week, and 50.6% consume it more frequently. Urban government schools show a higher frequency of consumption, with 55.7% of boys eating fast food more than three times per week. Urban private schools have the highest frequency, with 59.1% of boys consuming fast food more than three times per week. These patterns suggest that students in urban and private schools have greater access to fast food options, potentially due to increased availability and marketing [ 17 ]. Studies indicate that fast-food consumption is linked to poorer academic performance and health outcomes, highlighting the need for interventions to promote healthier eating habits among students. With regard to non-vegetarian/vegetarian foodconsumption frequency,the current study reveals significant differences in food consumption patterns among school boys and girls. In rural government schools, 45.3% of male students consume a mixed diet, while 33.7% are non-vegetarians and 21% are vegetarians. Rural private school students have a higher preference for non-vegetarian foods, with 41.9% of boys and 52.1% of girls consuming non-vegetarian meals. Urban government school students show a more balanced distribution, with 46.2% of boys and 26% of girls consuming non-vegetarian foods, and 21.6% of boys and 26.8% of girls consuming vegetarian meals. This disparity highlights the need for targeted interventions to promote balanced and nutritious diets among students, especially in rural and government school settings [ 18 ]. The study also reveals significant differences in school students' modes of school transport in the Tirupati region (Fig. 2 (a-d) ). In rural government schools, walking is the most preferred mode of transport for both boys and girls followed by cycling. This indicates greater reliance on walking in rural areas, likely due to shorter distances or limited availability of private transport. In rural private schools and in urban government schools, walking remains the most common mode, with cycling being the second most common. In urban private schools, 58.3% of boys and 49.5% of girls rely on motorized transport, while walking is less common. This disparity highlights the family financial background and the need for targeted interventions to improve transportation infrastructure and promote safe and sustainable commuting options for students, especially in rural areas [ 19 ]. Coming to outdoor game time among Tirupati region, school students of rural government and private schools reveal significant differences based on gender, school type, and location. More than 60% of boys spend more than two hours for outdoor games daily while majority of the girls spend less than 2 hours for outdoor games. Urban government and private schools have a more balanced distribution, with high percentage of both boys and girls spending less than two hours for outdoor games. These patterns suggest that rural boys have more opportunities or inclination to engage in outdoor play, possibly due to lesser academic pressures or more accessible play areas. In contrast, girls, especially in rural areas, may face cultural or household responsibilities limiting their playtime [ 20 ]. Urban students, particularly in private schools, might have limited time for outdoor activities due to academic commitments or lack of open spaces. Studies indicate that outdoor play is crucial for children's physical and mental well-being, and a decline in such activities can impact their overall development [ 21 ]. Time for TV watching in rural/ urban and government/ private schools show that a significant number of students, both boys and girls, spend more than two hours daily watching TV. In rural government schools, 35.8% of boys and 33.3% of girls watch TV for more than two hours daily. Urban government schools have 47.1% of boys and 54.3% of girls watching TV for more than two hours daily (Fig. 3 (a-b) ). These patterns align with broader trends in India, where a significant proportion of children exceed recommended screen time limits [ 22 ]. Excessive screen time has been associated with health concerns, including inadequate sleep and behavioural issues. With regard to activities such as screen time, study hours, and time spent on outdoor games, significant variations in students' daily routines based on gender and geographic location was noticed. Urban girls prioritize academics, while rural girls face constraints due to household responsibilities. But, boys, regardless of location, spend more time on screen watching and outdoor games [ 23 ]. Boys across all categories (rural and urban, government and private schools) spend more than 2 hours daily on TV and cell phones compared to girls. In study time patronsin rural schools, boys are more likely to study for more than 2 hours at home compared to girls (Fig. 3 and Fig. 4 (a-d) ). This disparity is attributed to girls spending more time on household chores, limiting their study hours. More screen time also leads to the risk for neck/shoulder pain in school-aged children [ 24 ]. In urban schools, girls surpass boys in studying for more than 2 hours daily. Urban girls have greater focus on academics compared to rural girls, may be perhaps influenced by better educational awareness and fewer domestic responsibilities in urban settings [ 25 ]. Finally in health conditions among students based on location, school type, and gender, particularly in urban private schools, more students are prone to both mental and physical ill health due to lifestyle and academic demands while rural students exhibit lower prevalence rates but may face hidden challenges due to underreporting and lack of access to healthcare [ 26 ]. Finally, targeted interventions are needed to address mental health issues in urban schools and improve healthcare access and awareness in rural areas (Fig. 5 (a-d) ). Additionally, promoting healthy lifestyles across all schools can help mitigate physical health conditions [ 27 ]. With the increasing prevalence of private schools, which often foster a sedentary environment, students in these schools are more vulnerable to develop risk factors associated with obesity and related disorders. In contrast, students in government schools may lead less sedentary lifestyles and benefit from the Mid-Day Meal Programme, a flagship initiative aimed at providing children with nutritious food [ 28 ]. School authorities should take necessary steps to maintain proper hygiene while preparing and serving meals under the Mid-Day Meal Programme, as it directly impacts children's health and well-being[ 29 ]. Additionally, the study will help identify students with underlying health issues and provide insights to guide the implementation of appropriate preventive and therapeutic interventions. 5 Conclusion The findings of this study underscore the need for comprehensive health promotion and lifestyle awareness initiatives that are responsive to the diverse demographic and socio-environmental contexts of school-aged children. Strengthening interventions that encourage healthy behaviors, improve access to basic healthcare services, and address emerging mental health concerns should remain a key public health priority. The evidence generated provides a valuable platform for future research, community-based engagement, and the design of effective school-centred preventive programmes aimed at enhancing both physical and psychological well-being among students. In addition, policy development focusing on safe transportation practices, equitable and nutritious dietary access, and the reduction of lifestyle-related health risks is essential to support holistic health outcomes in both rural and urban settings. In conclusion, the study demonstrates that students from rural government schools exhibited comparatively healthier physiological profiles and overall better health status than their urban counterparts. A similar trend was observed among rural private school students, who showed more favourable health indicators than those in urban private schools. Overall, children attending government schools displayed better health indices than those in private schools, which may be partially attributed to the positive impact of the mid-day meal programme. Conversely, urban private school students appeared more vulnerable to obesity and related metabolic risks, likely influenced by sedentary lifestyles, unhealthy dietary patterns, and limited physical activity. These findings highlight the importance of early identification of at-risk children and the implementation of targeted preventive strategies to reduce the future burden of metabolic syndrome and related disorders. Increasing awareness among students, parents, teachers, and healthcare professionals regarding the physical, social, and psychological consequences of malnutrition and obesity is essential. Coordinated efforts promoting balanced nutrition, regular physical activity, and health education can foster sustainable healthy behaviours and contribute to improved long-term health outcomes. Declarations Acknowledgments Authors gratefully acknowledge the cooperation of the government and private schools of Tirupati region and the concerned school authorities for giving permission and also the students for participating in the study. We acknowledge the ICMR, (Sanction No. No Adhoc/210/2022/SBHSR), New Delhi, India for its funding. Author contributions PKN Conceptualization, Designed the questionnaire, Investigation, Data analysis, Writing original draft. SYKCK, VM, SAMD Data curation, Methodology, Analyzed the data. BM Conceptualization, Supervision, Writing- Review &editing. Funding This work did not receive funding towards article processing and publication charges. Availability of Data and Materials Data will be provided upon request through mail to the corresponding author. Email id: [ [email protected] ] Disclosure statement No potential conflict of interest was reported by the author(s). Human ethical committee approval All procedure in the study adhered to the guidelines laid out in the Declaration of Helsinki. All six IECs gave their approval to the study protocol for their selected district, and Ethics Committees at the universities where the authors worked also provided their approval. Clinical trial number Not applicable Ethics Approval Institute human ethical committee (IHEC) approval was obtained (SVU/IHEC/002/2023). Patient Consent Parents or legal guardians were informed of the purpose of the study and written informed parental consent was obtained. References Smith JD, Fu E, Kobayashi MA. Prevention and Management of Childhood Obesity and Its Psychological and Health Comorbidities. Ann Rev Clin Psychol. 2020;16:351–78. https://doi.org/10.1146/annurev-clinpsy-100219-060201 . Hunegnaw WA, Ferede AG, Tekalign T, Asres AW. Obesity and associated factors among high school adolescent students in Bahir Dar town, North West Ethiopia: A cross-sectional study. 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Revue d'epidemiologie et de sante publique. 2015; 63(3): 173–182. https://doi.org/10.1016/j.respe.2014.11.003 Patterson R, Risby A, Chan MY. Consumption of takeaway and fast food in a deprived inner London Borough: are they associated with childhood obesity? BMJ open. 2012;2(3):e000402. https://doi.org/10.1136/bmjopen-2011-000402 . Saunders TJ, Gray CE, Poitras VJ, Chaput JP, Janssen I, Katzmarzyk PT, Olds T, Connor Gorber S, Kho ME, Sampson M, Tremblay MS, Carson V. Combinations of physical activity, sedentary behaviour and sleep: relationships with health indicators in school-aged children and youth. Applied physiology, nutrition, and metabolism Physiologieappliquee. Nutr et Metab. 2016;41(6 Suppl 3):S283–93. https://doi.org/10.1139/apnm-2015-0626 . Hassapidou M, Tzotzas T, Makri E, Pagkalos I, Kaklamanos I, Kapantais E, Abrahamian A, Polymeris A, Tziomalos K. Prevalence and geographic variation of abdominal obesity in 7- and 9-year-old children in Greece; World Health Organization Childhood Obesity Surveillance Initiative 2010. BMC Public Health. 2017;17(1):126–38. https://doi.org/10.1186/s12889-017-4061-x . Moreno LA, Gottrand F, Huybrechts I, Ruiz JR, González-Gross M, DeHenauw S, HELENA Study Group. Nutrition and lifestyle in european adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. Advances in nutrition (Bethesda, Md.). 2014; 5(5): S615–23. https://doi.org/10.3945/an.113.005678 Gonzalez-Casanova I, Sarmiento OL, Gazmararian JA, Cunningham SA, Martorell R, Pratt M, Stein AD. Comparing three body mass index classification systems to assess overweight and obesity in children and adolescents. Revista Panam de salud publica Pan Am J public health. 2013;33(5):349–55. https://doi.org/10.1590/s1020-49892013000500006 . Ranjani H, Mehreen TS, Pradeepa R, Anjana RM, Garg R, Anand K, Mohan V. Epidemiology of childhood overweight & obesity in India: A systematic review. Indian J Med Res. 2016;143(2):160–74. https://doi.org/10.4103/0971-5916.180203 . Azemati B, Kelishadi R, Ahadi Z, Shafiee G, Taheri M, Ziaodini H, Qorbani M, Heshmat R. Association between junk food consumption and cardiometabolic risk factors in a national sample of Iranian children and adolescents population: the CASPIAN-V study. Eating and weight disorders: EWD. 2020; 25(2): 329–35. https://doi.org/10.1007/s40519-018-0591-1 Gupta DK, Shah P, Misra A, Bharadwaj S, Gulati S, Gupta N, Sharma R, Pandey RM, Goel K. Secular trends in prevalence of overweight and obesity from 2006 to 2009 in urban asian Indian adolescents aged 14–17 years. PLoS ONE. 2011;6(2):e17221. https://doi.org/10.1371/journal.pone.0017221 . Fonseca LB, Pereira LP, Rodrigues PRM, Andrade ACS, Muraro AP, Gorgulho BM, Pereira RA, Ferreira MG. Food consumption on campus is associated with meal eating patterns among college students. Br J Nutr. 2021;126(1):53–65. https://doi.org/10.1017/S0007114520003761 . Delclos-Alio X, Rodríguez DA, Medina C, Jaime Miranda J, Avila-Palencia I, Targaf F, Moran MR, Sarmiento OL, Alex Quistberg D. Walking for transportation in large Latin American cities: walking-only trips and total walking events and their sociodemographic correlates. Transp reviews. 2022;42(3):296–317. https://doi.org/10.1080/01441647.2021.1966552 . Lemberg GM, Kull M, Maestu J, Riso EM, Magi K, Maestu E. Outdoor recess is associated with more positive attitudes toward physical activity among pre-adolescent students and their parents. Front sports Act living. 2024;6:1433801. https://doi.org/10.3389/fspor.2024.1433801 . Kennedy-Behr A, Webb-Williams JL. Capturing children's play behaviours in outdoor environments: A comparative analysis of play in early adolescence at primary school versus high school. Aust Occup Ther J. 2024;71(1):76–87. https://doi.org/10.1111/1440-1630.12912 . Qi J, Yan Y, Yin H. Screen time among school-aged children of aged 6–14:a systematic review. Global health Res policy. 2023;8(1):12. https://doi.org/10.1186/s41256-023-00297-z . Parssinen O, Kauppinen M. Associations of near work time, watching TV, outdoors time, and parents' myopia with myopia among school children based on 38-year-old historical data. Acta Ophthalmol. 2022;100(2):e430–8. https://doi.org/10.1111/aos.14980 . Dianat I, Alipour A, Asgari Jafarabadi M. Risk factors for neck and shoulder pain among schoolchildren and adolescents. J Paediatr Child Health. 2018;54(1):20–7. https://doi.org/10.1111/jpc.13657 . Dubuc MM, Aubertin-Leheudre M, Karelis AD. Predictors of Academic Performance in High School Students: The Longitudinal ASAP Study. Int J Exerc Sci. 2022;15(4):616–31. https://doi.org/10.70252/ZAZQ9758 . Crump C, Rivera D, London R, Landau M, Erlendson B, Rodriguez E. Chronic health conditions and school performance among children and youth. Ann Epidemiol. 2013;23(4):179–84. https://doi.org/10.1016/j.annepidem.2013.01.001 . de Onis M, Blossner M, Borghi E. Prevalence and trends of stunting among pre-school children, 1990–2020. Public Health Nutr. 2012;15(1):142–8. https://doi.org/10.1017/S1368980011001315 . Laftman SB, Modin B, GranvikSaminathen M, Ostberg V, Lofstedt P, Rajaleid K. Psychosocial School Conditions and Mental Wellbeing Among Mid-adolescents: Findings From the 2017/18 Swedish HBSC Study. Int J public health. 2023;67:1605167. https://doi.org/10.3389/ijph.2022.1605167 . Ramachandran P. School Mid-day Meal Programme in India: Past, Present, and Future. Indian J Pediatr. 2019;86(6):542–7. https://doi.org/10.1007/s12098-018-02845-9 . Sembiah S, Burman J, Dasgupta A, Paul B. Safety of food served in Mid-Day Meal program: An in-depth study in upper primary schools of Kolkata. J family Med Prim care. 2019;8(3):938–43. https://doi.org/10.4103/jfmpc.jfmpc_59_19 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8671949","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595191031,"identity":"af3b2fd1-f845-463e-898a-14f8adc2505f","order_by":0,"name":"Pradeep Kumar Narasimhappagari","email":"","orcid":"","institution":"Sri Venkateswara University","correspondingAuthor":false,"prefix":"","firstName":"Pradeep","middleName":"Kumar","lastName":"Narasimhappagari","suffix":""},{"id":595191034,"identity":"6700ae4d-f15b-408f-8692-ec89cc196c1f","order_by":1,"name":"Sai Yashwanth Kumar CK","email":"","orcid":"","institution":"Sri Venkateswara 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Meriga","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACAwbmBgYJAxCTsYGBoQJIMwNF8GthRNZyBqSFkQgtcMDYBtOLB5izH2z8YFHAEM0vfbj5xc95tdH87UAtPyq24dRi2ZPYLAF0WO7MvsQ2y95tx3NnHGZsYOw5cxu3ww4kNoC1bDjD2GbAu+1YbgNQCzNjGx4t5x82/wBp2Q/UYvh3zrHc+QS13Ehsg9jCw9j8mLehJncDIS2WMx62WUgYSOTOANrCLHPsQO5GoJaD+Pxizp98+LbEH5vc/h72xx/f1NTlzjt/+OCDHxW4tYAAswSDBIhmA5KHwSIH8KoHAsYPUK1Auo6Q4lEwCkbBKBiBAACgOF2AGlMROAAAAABJRU5ErkJggg==","orcid":"","institution":"Sri Venkateswara University","correspondingAuthor":true,"prefix":"","firstName":"Balaji","middleName":"","lastName":"Meriga","suffix":""}],"badges":[],"createdAt":"2026-01-22 16:39:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8671949/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8671949/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103505311,"identity":"0ce8f00c-8c64-42d6-ba8b-ba7517539882","added_by":"auto","created_at":"2026-02-26 13:29:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":952427,"visible":true,"origin":"","legend":"\u003cp\u003eFast-Food and Food Consumption Patterns Among School Students in Rural and Urban Areas \u003cstrong\u003e(a) \u003c/strong\u003eFast-food consumption in Rural area students \u003cstrong\u003e(b) \u003c/strong\u003eFast-food consumption in Urban area students \u003cstrong\u003e(c) \u003c/strong\u003eType of food consumption in rural schools among boys and girls\u003cstrong\u003e (d) \u003c/strong\u003eType of food consumption in urban schools among boys and girls.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/405084cdc829007722261781.jpg"},{"id":103259294,"identity":"15d19733-87e7-469c-91d9-fe7bddb029a1","added_by":"auto","created_at":"2026-02-23 17:37:31","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1170169,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of School Transportation and Outdoor Game Time Among Rural and Urban Students \u003cstrong\u003e(a) \u003c/strong\u003eMode of transport to schools by rural area students \u003cstrong\u003e(b) \u003c/strong\u003eMode of transportby Urban area students \u003cstrong\u003e(c) \u003c/strong\u003eTime spent for outdoor games by rural area students \u003cstrong\u003e(d) \u003c/strong\u003eTime spent for outdoor games by urban area students.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/35dbb44c7befce8aeff2c74e.jpg"},{"id":103505635,"identity":"b2a31858-8e69-4a96-8a0f-ff6fd69c96de","added_by":"auto","created_at":"2026-02-26 13:32:17","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1319658,"visible":true,"origin":"","legend":"\u003cp\u003eScreen Time Patterns Among Rural and Urban School Students \u003cstrong\u003e(a) \u003c/strong\u003eTime spent for TV watching by rural area students \u003cstrong\u003e(b) \u003c/strong\u003eTime spent for TV watching by urban area students \u003cstrong\u003e(c) \u003c/strong\u003eTime spent for mobile phone watching by rural area students \u003cstrong\u003e(d) \u003c/strong\u003eTime spent for mobile phone watching by urban area students.\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/13940c74ae74457a902321dc.jpg"},{"id":103259290,"identity":"de12396d-b23f-4547-b17f-0caf5b5d05ea","added_by":"auto","created_at":"2026-02-23 17:37:31","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":849565,"visible":true,"origin":"","legend":"\u003cp\u003eHealth Issues Among Rural and Urban School Students \u003cstrong\u003e(a) \u003c/strong\u003eVision problems in Rural area students \u003cstrong\u003e(b) \u003c/strong\u003eVision problems in urban area students \u003cstrong\u003e(c) \u003c/strong\u003eDental problems in rural area students \u003cstrong\u003e(d) \u003c/strong\u003eDental problems in urban area students.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/146268805498b21745bbc3d0.jpg"},{"id":103505917,"identity":"2e2a8e9c-fe2c-48db-95f0-5f4c6a7d3e0a","added_by":"auto","created_at":"2026-02-26 13:33:29","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":897494,"visible":true,"origin":"","legend":"\u003cp\u003eMental Health Issues Among Rural and Urban School Students \u003cstrong\u003e(a) \u003c/strong\u003eStress and anxiety problems in rural area students \u003cstrong\u003e(b) \u003c/strong\u003eStress and anxiety problems in urban area students \u003cstrong\u003e(c) \u003c/strong\u003eDepression problems in rural area students \u003cstrong\u003e(d) \u003c/strong\u003eDepression problems in urban area students.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/c5c63ecd68f4fbb084e2bd6e.jpg"},{"id":104876895,"identity":"bc9cb809-f037-4e8a-9883-6815ff19a608","added_by":"auto","created_at":"2026-03-18 08:44:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6186852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8671949/v1/2435a952-bc75-4f7a-8a34-490df530c2f3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study of different lifestyle parameters and their impact on health parameters of rural and urban adolescent school children","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eOverweight or underweight is a complex, multifactorial condition that arises from an intricate interplay of genetic, demographic, and lifestyle factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Current evidence highlights that it is not solely a result of individual behaviour or willpower but also influenced by broader societal and environmental changes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While the incidence of obesity is not new to the developed countries, the main drivers of the escalating trends of childhood obesity in India and other developing countries are changed life styles, increased accessibility to energy density foods and drinks, changed work habits, ambient temperatures, sedentary lifestyles, rapid nutritional transitions, increasing affluence, socioeconomic transitions, urbanization, mechanization, rural-to-urban migration and disturbed biological clocks [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In the present times, children consume three times more food from fast-food outlets/restaurants compared to 30 years ago [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This increase may be attributed to the affordability and accessibility of fast foods, extensive food advertising, and the fact that both parents often work, leaving less time to prepare home-cooked meals for the family [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies examining the relationship between physical activity and metabolic disorders have shown less consistent results, with findings varying based on the method used to assess physical activity. In studies that utilized accelerometer, physical activity consistently showed a negative association with metabolic syndrome; however, this association was weaker compared to the relationship observed with fitness levels [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In addition, overweight and obesity is favored by risky dietary behaviors such as consumption of fast foods and drinks, eating away from home, skipping/missing of meal, regular drinking of sugar rich beverages and low intake of fruit and vegetables. Overweight/Obesity plays a central role to develop hyper tension, dyslipidemia, diabetes, insulin resistance, CVDs and some types of cancers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The results of the healthy lifestyle in Europe by nutrition in adolescence (HELENA) study, which included 3,528 children from European cities, suggested that children in the 9-year-old age group with a low physical fitness level were at elevated risk of developing cardiovascular risk factors such as obesity and overweight [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Adolescence may be the period of greatest risk for those with these disorders. Adults who have been obese since childhood are more likely to suffer from stress, depression and other psychological disorders [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Body mass index (BMI) is the most widely accepted tool in epidemiological studies and clinical practice to diagnose excess body weight in both children and adults. In children, there is no a clear consensus on the BMI-based obesity classification method that should be used to identify overweight and obesity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Considering the mushrooming of private schools in India, where sedentary type of environment prevails, there is more scope for such students to develop risk factors that lead to obesity and associated disorders when compared to govt.schools. Thus, the present study aimed to examine demographic, behavioral, and lifestyle factors and their association with underweight, overweight, obesity, and other health issues. These findings will help national health authorities identify target populations and formulate appropriate policies to address health and social inequalities, thereby contributing to the development of a stronger and healthier nation.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study design and study setting\u003c/h2\u003e\n \u003cp\u003eThe study was conducted in randomly selected government and private schools in Tirupati in around rural and urban areas. Out of 20 schools invited to participate, 16 schools consented and permitted data collection, while 4 schools declined participation due to academic schedule constraints. The study was carried out from August 2023 to October 2023 among both male and female students from classes 8 to 10, aged 12\u0026ndash;16 years. Various lifestyle-related parameters, including dietary habits, physical activity, and behavioural factors, were assessed to evaluate underweight, overweight, obesity, and other physiological and stress-related conditions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Questionnaire\u003c/h2\u003e\n \u003cp\u003eA pre-designed, pre-tested, and semi-structured questionnaire was used to collect data on students\u0026rsquo; food habits (Veg/Non-veg consumption), physical activity, screen time (Cell phone, TV watching etc.), health issues, and stress levels. The questionnaire was developed after reviewing relevant literature and was reviewed by subject experts to ensure content validity. It was pre-tested among a small group of students for clarity and suitability. The questions were explained in both teaching and local language (Telugu) for better understanding. Although no formal statistical validity or reliability testing was conducted, the tool was refined through expert review and pilot testing to ensure consistency and appropriateness for the study population.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Inclusion criteria\u003c/h2\u003e\n \u003cp\u003eInclusive criteria were followed by considering apparently healthy children in the age group of 12 to 16 years without any chronic illness or any surgery in near past.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Exclusion criteria\u003c/h2\u003e\n \u003cp\u003eExclusive criteria were followed by not selecting the students diagnosed with chronic disease and on medication from one year, and also those who are unwilling to participate.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Anthropometric measurements\u003c/h2\u003e\n \u003cp\u003eAnthropometric measurementslikeheight, weight were taken by using stadio meter and digital weighing machine for each student, and body mass index (BMI) was calculated by the following formula.\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Human ethical committee approval\u003c/h2\u003e\n \u003cp\u003eInstitute human ethical committee approval was obtained (SVU/IHEC/002/2023) and the approved procedures were followed to collect data. A total of 1,050 students were invited to participate in the study, of which 979 consented and completed the questionnaire, yielding a response rate of approximately 93.2%. Participation was voluntary, and students could withdraw at any point without providing a reason.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Data quality control\u003c/h2\u003e\n \u003cp\u003eFor data quality control a pre-test on 5% of the samples was performed and regular supervision during data collection was also carried out. The completeness of the questionnaire was checked before data entry too.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eStatistical analysis was performed using the computer software SPSS for Windows version 14.0 (SPSS Inc., Chicago, USA). Analysis of variance factorial analysis and post hoc multiple comparisons were used to evaluate the significance of the differences. Differences in proportions were analysed using the Chi-square test.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic characteristics and gender-based body mass index distribution among school adolescents\u003c/h2\u003e \u003cp\u003eA total of 979 students completed the questionnaire, achieving a 93.2% response rate. The government and private schools distributed in rural and urban areas and percent of boys and girls are presented in table-1. Among the total participants, 467 (47.7%) were girls, among them, 81 are from rural government schools and 73 are from rural private schools, 127 are from urban government schools and 186 are from urban private schools. The total number of boys in the present study is 512 (52.3%), among them, 95 are from rural government schools and 85 are from rural private schools, 157 are from urban government schools and 175 are from urban private schools. Based on their BMI, adolescent children from different school areas were classified into underweight, normal weight, overweight and obesity (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of male students of different schools in to different weight groups based on BMI in Percentages.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural Govt\u003c/p\u003e \u003cp\u003e95(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRural Pvt\u003c/p\u003e \u003cp\u003e85(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrban Govt\u003c/p\u003e \u003cp\u003e157(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrban Pvt\u003c/p\u003e \u003cp\u003e175(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnder Weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20(12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29(16.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62(65.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56(65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90(57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64(36.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOver Weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17(17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36(22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48(27.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObese\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11(7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23(8.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of female students of different schools in to different weight groups based on BMI in Percentages.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural Govt\u003c/p\u003e \u003cp\u003e81(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRural Pvt\u003c/p\u003e \u003cp\u003e73(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrban Govt\u003c/p\u003e \u003cp\u003e127(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrban Pvt\u003c/p\u003e \u003cp\u003e186(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnder Weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19(26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68(36.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56(69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34(46.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72(38.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOver Weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12(14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29(22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32(17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObese\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4(4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11(15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14(7.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the height and weight, BMI was calculated and students were divided as underweight, normal weight, overweight and obese. In rural government schools category, 11.1% girls are underweight when compared to boys (5.3%), 14.8% girls are overweight when compared to boys (17.9%) and 4.9% girls are obese when compared to boys 11.6%. In rural private schools, more girls (26%) are underweight compared to boys (9.4%), and slightly more girls (15.1%) are obese than boys (9.4%). In urban government schools, a higher percentage of girls (33.9%) are underweight compared to boys (12.7%), in overweight group, boys and girls showed almost same percentage (22.8%), and in obesity group girls showed 9.4% and boys showed 7%. In urban private schools, the contrast is sharper: 36.6% of girls are underweight compared to 16.6% of boys, while 27.4% of boys are obese versus only 7.5% of girls. Across all categories, boys are more often found in the overweight and obese groups, while girls especially in urban settings are more likely to be underweight or within the normal range. This highlights a noticeable gender difference in body weight trends that may reflect lifestyle, diet, and health behaviours.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Fast food consumption and dietary Preferences by gender and school type\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e and \u003cb\u003e(b)\u003c/b\u003e explains that, in more than 3 times fast food consumption per week group, more number of rural private school students (50% boys, 54% girls) figured when compared to rural government school students (about35% of both sexes). In urban private schools, both boys and girls have high fast-food intake, with 58.9% of boys and 55.9% of girls consuming fast food more than 3 times a week. Overall, students in private schools, especially in urban areas, tend to eat fast foods more frequently, may be due to high availability of fast foods near urban schools. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e(c)\u003c/b\u003e and \u003cb\u003e(d)\u003c/b\u003e shows the types of food preferences (vegetarian, non-vegetarian, mixed) among school students across rural and urban areas in both government and private schools. In rural government schools, 49.4% of girls are vegetarians, while boys are only 21.1%, and most boys (45.3%) prefer a mixed diet. In rural private schools, 52% of girls are vegetarian, compared to just 11.8% of boys, while most boys prefer non-vegetarian (48.2%) or mixed diets (40%). In urban government schools, food preferences are more evenly spread, with boys favouring non-vegetarian food (45.9%) and girls leaning toward mixed diets (35.4%) and non-vegetarian (38.6%). In urban private schools, the pattern shifts 44.9% of girls are vegetarian, while boys mostly prefer mixed diets (56%). Only 17.6% of urban private school girls eat mixed diets, compared to 56% of boys. Overall, girls are more likely to be vegetarians, especially in rural and private schools, while boys particularly in private schools show a stronger preference for mixed and non-vegetarian diets. This suggests gender and school-type influence food habits, possibly due to cultural norms, family practices, or personal choices.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Transport modes and outdoor physical activity patterns among schoolchildren\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e and \u003cb\u003e(b)\u003c/b\u003e explains the mode of transport among schoolchildren, exhibited notable rural\u0026ndash;urban and government\u0026ndash;private school disparities. In rural areas, walking or cycling was found to be the predominant mode, with the highest prevalence observed among boys of government school (81.10%), followed by girls of private school (74.00%), boys of private school (71.80%), and government school girls (70.40%). Conversely, vehicle usage was comparatively lower in these groups, ranging from 18.90% to 29.60%. In contrast, urban areas demonstrated a shift towards increased dependence on vehicular transport, particularly among private school students. Boys of private schools reported vehicular transport (58.30%), followed by private school girls (49.50%), government school girls (41.00%), and government school boys (31.80%). These findings suggest that urbanization and school type influence transport choices, with urban and private school students showing greater reliance on motorized vehicles compared to their rural and government school counterparts, who primarily depend on walking and cycling. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e and \u003cb\u003e(d)\u003c/b\u003e, in rural government schools, 64.2% of boys spend more than 2 hours a day on outdoor games, while only 30.9% of girls do so. In rural private schools, a similar pattern is observed, with 70.6% of boys spending more than 2 hours, compared to only 34.2% of girls. The difference is more noticeable in rural areas, where boys engage in outdoor games much more frequently than girls. In urban government schools, the time spent is more balanced, with 52.3% of boys and 52% of girls spending more than 2 hours a day on outdoor activities, indicating more equal participation in physical activities. In urban private schools, 69.1% of boys and 65.6% of girls spend less than 2 hours/day, with a smaller proportion of both genders spending more than 2 hours daily (2 days in a week) for outdoor games. Overall, rural private schools show a marked difference between boys and girls in outdoor game participation time with boys engaging more time for outdoor physical activities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Screen time patterns: Television and mobile phone use\u003c/h2\u003e \u003cp\u003eThe Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e and \u003cb\u003e(b)\u003c/b\u003e show the time spent (less than 2 hours or more than 2 hours a day) for watching TV by boys and girls across rural and urban areas in government and private schools. In rural government schools, both boys and girls (about 65%) spend less than 2 hours per day watching TV. The same trend is seen in rural private schools (47.1% of boys and 49.3% of girls) spending less than 2 hours per day watching TV. In urban government schools, 52.9% of boys and 45.7% of girls spend less than 2 hours per day watching TV, while the remaining percentage of students watch TV for more than 2 hours. In urban private schools, a larger percentage of boys (48%) and girls (43%) watch TV for more than 2 hours per day. Overall, across both rural and urban areas, boys and girls spend a relatively similar amount of time watching TV, with some slight variations depending on the area and type of school, but the differences are generally not statistically significant. The patterns suggest that TV watching habits are quite balanced across genders. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e and \u003cb\u003e(d)\u003c/b\u003e shows the time spent on mobile phones watching by boys and girls across rural and urban areas in government and private schools. In rural government schools, time spent on mobile phone usage was less by both boys and girls (67\u0026ndash;71% spend less than 2 hours per day on mobile phones), while the remaining percentage spend more than 2 hours. In comparison, in rural private schools, the percentage of boys and girls who spend less than 2 hours per day on mobile phones was 54.1\u0026amp;45.9% % respectively, while the remaining spends more than 2 hours. In contrast, 78.1% of girls in rural private schools use mobile phones for less than 2 hours, while only 21.9% spend more than 2 hours. In urban government schools, 50.3% of boys and 52% of girls spend less than 2 hours per day on mobile phones, with a near-equal split in usage over 2 hours. In urban private schools, 52.5% of boys and 45.7% of girls spend less than 2 hours, while 44.3% of boys and 54.3% of girls use mobile phones for more than 2 hours. Overall, rural private school students, particularly girls, tend to use mobile phones less frequently, while urban private school students, especially girls, are more likely to spend more than 2 hours on their phones. Private school students in both rural and urban areas generally spend more time on mobile devices than their counterparts in government schools.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Prevalence of vision and dental problems among schoolchildren\u003c/h2\u003e \u003cp\u003eThe Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e and \u003cb\u003e(b)\u003c/b\u003e highlight the presence of vision problems among schoolchildren in rural and urban areas, comparing government and private schools. In rural government schools, 18.9% of boys and 9.9% of girls have reported vision problems. In rural private schools, a higher percentage of boys (17.6%) and 42.5% of girls have reported vision problems. In urban government schools, 25.5% of boys and 17.3% of girls experienced vision problems, in urban private schools, 29.7% of boys and 9.7% of girls had vision problems, with the majority of both boys (38.9%) and girls (55.4%) reporting no issues. A significant portion of boys (31.4%) and girls (35%) had partial vision problems. Overall, private school students in both rural and urban areas reported more vision problems compared to their government school counterparts, with urban private school boys being most affected. The differences in vision issues across gender and school types indicate a need for targeted interventions for schoolchildren's eye health. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e(c)\u003c/b\u003e and \u003cb\u003e(d)\u003c/b\u003e present data on dental problems among schoolchildren studying in government and private schools located in rural and urban areas. Dental problems were identified as partial dental, dental and no dental issues. In rural government schools, 13.7% of boys and 18.5% of girls have reported dental problems, and partial dental issues were found in 15.8% of boys and 13.6% of girls. In rural private schools, 24.7% of boys and 30.1% of girls had dental problems, while partial dental issues were reported by 17.6% of boys and 21.9% of girls. In urban government schools, 29.3% of boys and 17.3% of girls reported dental problems and a notable portion (24.8% of boys and 29.1% of girls) reported partial dental problems. In urban private schools, 16% of boys and 16.1% of girls reported dental problems, and 32.6% of boys and 32.3% of girls reported partial dental problems. Overall, a considerable percentage of students from urban private and government schools showed more partial dental issues when compared to rural students.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Stress, anxiety, and depression among schoolchildren\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e and \u003cb\u003e(b)\u003c/b\u003e explains students who were reported feeling partial stress, stress or no stress. In rural government schools, 17\u0026ndash;18% of boys and girls expressed partial stress and anxiety, 7.4% of boys and 14.8% of girls reported stress and anxiety and the remaining did not report any mental health issues. In rural private schools, 28.2% of boys and 24.7% of girls reported partial stress/anxiety issues, 14.1% of boys and 16.4% of girls experienced stress and anxiety and the remaining showed no mental health issues. In urban government schools, 34.4% of boys and 34.6% of girls reported partial stress/anxiety issues 22.9% of boys and 7.9% of girls experienced stress and anxiety. In urban private schools, 17.1% of boys and 12.4% of girls had mental health issues, and 29.1% of boys and 25.8% of girls reported partial stress and anxiety and the remaining students had no mental health issues. Overall, a considerably larger percentage of girl students in rural schools were found to be suffering with more stress and anxiety than boys, in contrast, in urban schools a greater number of boys were reported with stress and anxiety. A higher percentage of boys and girls in rural and urban schools suffer with partial mental health issues. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e(c)\u003c/b\u003e and \u003cb\u003e(d)\u003c/b\u003e provides data on depression among schoolchildren studying in government and private schools of rural and urban areas. In rural government schools, 10.5% of boys and 13.6% of girls reported experiencing depression, only 9.5% of boys and 11.1% of girls reported partial depression and the remaining were with no depression. In rural private schools, 11.8% of boys and 16.4% of girls reported depression, a moderate portion (20% of boys and 21.9% of girls) experienced partial depression and the remaining were without any depression. In urban government schools, 10.8% of boys and 15.7% of girls reported depression, while partial depression was reported in 21.7% of boys and 26.8% of girls. In urban private schools, 17.1% of boys and 9.7% of girls reported depression, and partial depression was found in24%boys and 29.6% girls.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur results demonstrate that, a considerably larger percentage of girl students in rural schools were found to be with depression than boys, in contrast, in urban schools more boys are found to be with depression. Partial depression was reported by a larger percentage of both boys and girls in both rural and urban schools.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eSedentary life styles and modern food habits significantly influence the health status of adults and adolescent school children. The present study by taking weight and height, BMI distribution among school children in the Tirupati region was done and it reveals significant disparities based on school type and location. Rural government schools have a healthier BMI profile, with 65.3% of boys and 69.1% of girls in the normal range. However, rural private schools have a dual burden of underweight and obese girls, indicating nutritional imbalances. Urban government schools have a higher prevalence of overweight or obese girls, with 33.9% maintaining normal BMI and 32.2% being overweight or obese. Addressing these issues requires targeted interventions, including nutrition education, physical activity promotion, and mental health support, especially in urban and private school settings.\u003c/p\u003e \u003cp\u003eWith regard to food consumption pattern, in rural government schools, a significant portion of male students 45.3% consume a mixed diet, while 33.7% are non-vegetarians and 21% are vegetarians. In contrast, rural private school students exhibit a higher preference for non-vegetarian foods, with 41.9% of boys and 52.1% of girls consuming non-vegetarian meals, and 11.8% of boys and 52.1% of girls consuming vegetarian meals (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Urban government school students show a more balanced distribution, with 46.2% of boys and 26% of girls consuming non-vegetarian foods, and 21.6% of boys and 26.8% of girls consuming vegetarian meals. Urban private school students have the highest preference for mixed diets, with 56% of boys and 44.1% of girls consuming mixed diets, and 26.3% of boys and 41.9% of girls consuming non-vegetarian foods (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e(a-d)\u003c/b\u003e).​ These patterns suggest that urban and private school students have greater access to diverse food options, possibly due to better economic conditions and availability of various food types. In contrast, rural students, particularly in government schools, may have limited access to diverse food options, leading to a higher consumption of vegetarian and mixed diets. This disparity underscores the need for targeted interventions to promote balanced and nutritious diets among students, especially in rural and government school settings. Additionally, socioeconomic factors and infrastructure development play crucial roles in shaping students' food consumption patterns, highlighting the importance of addressing these underlying factors to improve dietary habits among school children [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].​ Similarly in fast food consumption in rural government schools, a majority of male students 66.3% consume fast food less than three times per week, while 33.7% consume it more frequently. In rural private schools, 49.4% of boys consume fast food less than three times per week, and 50.6% consume it more frequently. Urban government schools show a higher frequency of consumption, with 55.7% of boys eating fast food more than three times per week. Urban private schools have the highest frequency, with 59.1% of boys consuming fast food more than three times per week. These patterns suggest that students in urban and private schools have greater access to fast food options, potentially due to increased availability and marketing [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Studies indicate that fast-food consumption is linked to poorer academic performance and health outcomes, highlighting the need for interventions to promote healthier eating habits among students.\u003c/p\u003e \u003cp\u003eWith regard to non-vegetarian/vegetarian foodconsumption frequency,the current study reveals significant differences in food consumption patterns among school boys and girls. In rural government schools, 45.3% of male students consume a mixed diet, while 33.7% are non-vegetarians and 21% are vegetarians. Rural private school students have a higher preference for non-vegetarian foods, with 41.9% of boys and 52.1% of girls consuming non-vegetarian meals. Urban government school students show a more balanced distribution, with 46.2% of boys and 26% of girls consuming non-vegetarian foods, and 21.6% of boys and 26.8% of girls consuming vegetarian meals. This disparity highlights the need for targeted interventions to promote balanced and nutritious diets among students, especially in rural and government school settings [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study also reveals significant differences in school students' modes of school transport in the Tirupati region (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a-d)\u003c/b\u003e). In rural government schools, walking is the most preferred mode of transport for both boys and girls followed by cycling. This indicates greater reliance on walking in rural areas, likely due to shorter distances or limited availability of private transport. In rural private schools and in urban government schools, walking remains the most common mode, with cycling being the second most common. In urban private schools, 58.3% of boys and 49.5% of girls rely on motorized transport, while walking is less common. This disparity highlights the family financial background and the need for targeted interventions to improve transportation infrastructure and promote safe and sustainable commuting options for students, especially in rural areas [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComing to outdoor game time among Tirupati region, school students of rural government and private schools reveal significant differences based on gender, school type, and location. More than 60% of boys spend more than two hours for outdoor games daily while majority of the girls spend less than 2 hours for outdoor games. Urban government and private schools have a more balanced distribution, with high percentage of both boys and girls spending less than two hours for outdoor games. These patterns suggest that rural boys have more opportunities or inclination to engage in outdoor play, possibly due to lesser academic pressures or more accessible play areas. In contrast, girls, especially in rural areas, may face cultural or household responsibilities limiting their playtime [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Urban students, particularly in private schools, might have limited time for outdoor activities due to academic commitments or lack of open spaces. Studies indicate that outdoor play is crucial for children's physical and mental well-being, and a decline in such activities can impact their overall development [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTime for TV watching in rural/ urban and government/ private schools show that a significant number of students, both boys and girls, spend more than two hours daily watching TV. In rural government schools, 35.8% of boys and 33.3% of girls watch TV for more than two hours daily. Urban government schools have 47.1% of boys and 54.3% of girls watching TV for more than two hours daily (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(a-b)\u003c/b\u003e). These patterns align with broader trends in India, where a significant proportion of children exceed recommended screen time limits [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Excessive screen time has been associated with health concerns, including inadequate sleep and behavioural issues. With regard to activities such as screen time, study hours, and time spent on outdoor games, significant variations in students' daily routines based on gender and geographic location was noticed. Urban girls prioritize academics, while rural girls face constraints due to household responsibilities. But, boys, regardless of location, spend more time on screen watching and outdoor games [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Boys across all categories (rural and urban, government and private schools) spend more than 2 hours daily on TV and cell phones compared to girls. In study time patronsin rural schools, boys are more likely to study for more than 2 hours at home compared to girls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003e(a-d)\u003c/b\u003e). This disparity is attributed to girls spending more time on household chores, limiting their study hours. More screen time also leads to the risk for neck/shoulder pain in school-aged children [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In urban schools, girls surpass boys in studying for more than 2 hours daily. Urban girls have greater focus on academics compared to rural girls, may be perhaps influenced by better educational awareness and fewer domestic responsibilities in urban settings [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally in health conditions among students based on location, school type, and gender, particularly in urban private schools, more students are prone to both mental and physical ill health due to lifestyle and academic demands while rural students exhibit lower prevalence rates but may face hidden challenges due to underreporting and lack of access to healthcare [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Finally, targeted interventions are needed to address mental health issues in urban schools and improve healthcare access and awareness in rural areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e(a-d)\u003c/b\u003e). Additionally, promoting healthy lifestyles across all schools can help mitigate physical health conditions [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. With the increasing prevalence of private schools, which often foster a sedentary environment, students in these schools are more vulnerable to develop risk factors associated with obesity and related disorders. In contrast, students in government schools may lead less sedentary lifestyles and benefit from the Mid-Day Meal Programme, a flagship initiative aimed at providing children with nutritious food [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. School authorities should take necessary steps to maintain proper hygiene while preparing and serving meals under the Mid-Day Meal Programme, as it directly impacts children's health and well-being[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, the study will help identify students with underlying health issues and provide insights to guide the implementation of appropriate preventive and therapeutic interventions.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe findings of this study underscore the need for comprehensive health promotion and lifestyle awareness initiatives that are responsive to the diverse demographic and socio-environmental contexts of school-aged children. Strengthening interventions that encourage healthy behaviors, improve access to basic healthcare services, and address emerging mental health concerns should remain a key public health priority. The evidence generated provides a valuable platform for future research, community-based engagement, and the design of effective school-centred preventive programmes aimed at enhancing both physical and psychological well-being among students. In addition, policy development focusing on safe transportation practices, equitable and nutritious dietary access, and the reduction of lifestyle-related health risks is essential to support holistic health outcomes in both rural and urban settings. In conclusion, the study demonstrates that students from rural government schools exhibited comparatively healthier physiological profiles and overall better health status than their urban counterparts. A similar trend was observed among rural private school students, who showed more favourable health indicators than those in urban private schools. Overall, children attending government schools displayed better health indices than those in private schools, which may be partially attributed to the positive impact of the mid-day meal programme. Conversely, urban private school students appeared more vulnerable to obesity and related metabolic risks, likely influenced by sedentary lifestyles, unhealthy dietary patterns, and limited physical activity. These findings highlight the importance of early identification of at-risk children and the implementation of targeted preventive strategies to reduce the future burden of metabolic syndrome and related disorders. Increasing awareness among students, parents, teachers, and healthcare professionals regarding the physical, social, and psychological consequences of malnutrition and obesity is essential. Coordinated efforts promoting balanced nutrition, regular physical activity, and health education can foster sustainable healthy behaviours and contribute to improved long-term health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors gratefully acknowledge the cooperation of the government and private schools of Tirupati region\u0026nbsp;and the concerned school authorities for giving permission and also the students for participating in the study. We acknowledge the ICMR,\u0026nbsp;(Sanction No. No Adhoc/210/2022/SBHSR), New Delhi, India for its funding.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePKN\u0026nbsp;\u003c/strong\u003eConceptualization, Designed the questionnaire, Investigation, Data analysis, Writing original draft. \u003cstrong\u003eSYKCK, VM, SAMD\u0026nbsp;\u003c/strong\u003eData curation, Methodology, Analyzed the data. \u003cstrong\u003eBM\u003c/strong\u003e Conceptualization, Supervision, Writing- Review \u0026amp;editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work did not receive funding towards article processing and publication charges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be provided upon request through mail to the corresponding author. Email id: [[email protected]]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the author(s).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman ethical committee approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedure in the study adhered to the guidelines laid out in the Declaration of Helsinki. All six IECs gave their approval to the study protocol for their selected district, and Ethics Committees at the universities where the authors worked also provided their approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitute human ethical committee (IHEC)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eapproval was obtained (SVU/IHEC/002/2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent\u0026nbsp;\u003c/strong\u003eParents or legal guardians were informed of the purpose of the study and written informed parental consent was obtained.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSmith JD, Fu E, Kobayashi MA. Prevention and Management of Childhood Obesity and Its Psychological and Health Comorbidities. 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J family Med Prim care. 2019;8(3):938\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/jfmpc.jfmpc_59_19\u003c/span\u003e\u003cspan address=\"10.4103/jfmpc.jfmpc_59_19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adolescent school children, Body mass index, Food habits, Fast foods, Mental Health","lastPublishedDoi":"10.21203/rs.3.rs-8671949/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8671949/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe present study investigated the impact of lifestyle parameters on physical and psychological health aspects of adolescent school children in rural and urban areas of the Tirupati region, focusing on socio demographic characteristics and lifestyle parameters. This cross-sectional study conducted on 979 students of both sexes in different schools during August-November-2023. A predesigned, structured questionnaire containing food habits (vegetarian/non vegetarian), frequency of non-vegetarian and junk food consumption, mode of transport to schools, screen watching time, time spent for physical activity, health issues and stress levels was answered by the study subjects. Anthropometric measurements were taken to measure body mass index (BMI). The study found that high percentage of girls in rural and urban schools are vegetarians than boys. Non-vegetarian food consumption is high among urban boys than other groups and urban school children show high frequency of fast-food consumption. Urban school children also showed higher levels of less physical activity, vehicle use, and screen watching. In underweight category, regardless of school type, a greater number of girls were recorded, while higher percentages of urban private school boys were found to be overweight and obese than other groups. A higher percentage of boys and girls in rural and urban schools reported partial mental health issues. The findings highlight that rural urban divide and changed life style factors profoundly influence underweight/overweight/obesity that consequently affects a child's psychological well-being. It accentuates the importance of bringing in awareness among students, teachers and parents about nurturing healthier lifestyles that fosters improved health and overall well-being of adolescent children.\u003c/p\u003e","manuscriptTitle":"Study of different lifestyle parameters and their impact on health parameters of rural and urban adolescent school children","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 17:37:24","doi":"10.21203/rs.3.rs-8671949/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a3531ae-8c48-4052-a9ea-5aebc7733d9f","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T08:42:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 17:37:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8671949","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8671949","identity":"rs-8671949","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}