**Background:** Body mass index (BMI) is the most frequently used method to determine nutritional status in adolescents. School-going populations in developing countries like India are susceptible to undernutrition due to socioeconomic, demographic, and nutritional factors. Poor dietary habits, sedentary lifestyles, and improper hygiene can deleteriously affect BMI. Adolescence is a critical period for forming lifelong health behaviours, yet limited research exists on the combined impact of physical health, diet, and personal hygiene on BMI in Indian adolescents.
**Methods:** An analytical cross-sectional study was conducted from September 2020 to February 2021 among 160 school-going adolescents (grades 9–12) from 10 high schools near Patna, Bihar. Stratified random sampling with proportional allocation was used, selecting 16 students per school. The sample size was calculated using Cochrane's formula based on a 46.8% prevalence of malnutrition from a prior study, with 95% confidence and 20% relative margin of error, yielding a minimum of 110; 160 were ultimately enrolled. Participants completed the validated Indian Adolescent Health Questionnaire (IAHQ), which included close-ended questions on physical activity, dietary behaviour, and hygienic practices. BMI was calculated from self-reported height and weight. Statistical analyses included Pearson's correlation, independent t-test, ANOVA, Chi-square test, and multiple linear regression (stepwise method), with significance set at P<0.05.
**Key Results:** Only 39.4% of adolescents had normal BMI; nearly half were underweight (BMI<18.5 kg/m²), 7.5% were overweight (BMI 23.0–24.9 kg/m²), and 3.7% were obese (BMI>25.0 kg/m²). Mean age was 14.99±1.03 years, mean BMI was 19.03±3.16 kg/m². Pearson's correlation between BMI and age showed a weak positive, non-significant association (r=0.124, P=0.118). BMI differed significantly across self-perception of weight categories (P<0.001): underweight (17.9±3.0 kg/m²), right weight (18.9±2.8 kg/m²), and overweight (22.2±3.0 kg/m²). Physical activity purpose also showed significant BMI differences (P<0.001): no activity (18.9±3.1 kg/m²), gaining weight (17.7±2.1 kg/m²), losing weight (21.8±3.5 kg/m²). Self-perception of weight was significantly associated with physical activity purpose (χ²=42.385, df=4, P<0.001): 40% of self-perceived overweight adolescents exercised to lose weight vs. 9.2% of inactive and 2.1% exercising to gain weight. Among self-perceived underweight adolescents, 60.4% exercised to gain weight. Self-perception of weight was also significantly associated with frequency of consuming vegetables cooked in oil (χ²=13.437, df=4, P=0.009): 75% of those who rarely consumed cooked vegetables perceived themselves as underweight. The final linear regression model (Model 1) included four predictors—self-perception of weight (B=1.807, 95% CI 1.108–2.506, P<0.001), physical activity done (B=-0.602, 95% CI -1.206–0.002, P=0.051), frequency of brushing teeth per week (B=0.814, 95% CI 0.099–1.529, P=0.026), and washing hands after using toilet/latrine (B=-1.889, 95% CI -3.366– -0.411, P=0.013)—which together significantly predicted BMI (F=10.895, df=4,155, P<0.001, R²=21.9%, adjusted R²=19.9%).
**Clinical Implications:** This study demonstrates that malnutrition is highly prevalent among school-going adolescents near Patna, with nearly half being underweight. Self-perception of weight, physical activity, handwashing after toilet use, and toothbrushing frequency are significant predictors of BMI. These findings underscore the need for integrated school-based interventions addressing not only nutrition and physical activity but also personal hygiene practices. The significant association between self-perceived weight and actual behaviour suggests that adolescent health programmes should incorporate body image awareness and self-efficacy components. Given that malnutrition in adolescence can lead to infection, impaired reproductive health, anaemia, and long-term morbidities into adulthood, objective nutritional assessment and targeted preventive strategies are urgently needed in this population. Limitations include the cross-sectional design (precluding causal inference), reliance on self-reported height/weight and subjective questionnaire responses, and lack of comprehensive anthropometric measures such as waist-hip ratio.