Association Between Bmi, Waist Circumference, and Level of Interest in Physical Activity: A Cross-sectional Study Among College Students

Association Between Bmi, Waist Circumference, and Level of Interest in Physical Activity: A Cross-sectional Study Among College Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Bmi, Waist Circumference, and Level of Interest in Physical Activity: A Cross-sectional Study Among College Students M Anbupriya, A Kamaleswari, Karthikeyan S, Nandhini S This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8714032/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract BACKGROUND Body mass index (BMI) and waist circumference (WC) are widely used anthropometric indicators for assessing obesity risk in young adults. However, their relationship with behavioural variables such as interest in physical activity, activity frequency, intensity, sleep habits, and dietary history remains unclear in Indian university populations. This study examined the association between BMI, WC, and selected lifestyle behaviours among college students, with emphasis on gender differences in central obesity. METHODS A cross-sectional study was conducted among 400 university students aged 18–23 years. Anthropometric measurements included BMI and WC, classified using standard cut-offs. Physical activity frequency was assessed using the Youth Physical Activity Questionnaire, and activity intensity using the International Physical Activity Questionnaire (short form). Demographic data, interest in physical activity, usual dietary sources, and sleep history were collected using a self-reported questionnaire. Associations were analysed using descriptive statistics and chi-square tests. RESULTS Of the participants, 56.5% had normal BMI, 20% were overweight, 5.3% were obese, and 18.3% were underweight. Based on WC, 65% met the criteria for central obesity. BMI showed no significant association with interest in physical activity, participation frequency, MET-based intensity, sleep patterns, or dietary sources (p > 0.05). In contrast, WC showed significant associations with interest in physical activity (p = 0.017), participation frequency (p = 0.011), MET intensity (p = 0.009), sleep patterns (p = 0.025), and dietary sources (p = 0.034). CONCLUSION Although most students had normal BMI, WC identified a substantially higher prevalence of central obesity, particularly among males. Higher WC was associated with lower physical activity engagement, irregular sleep, and calorie-dense dietary patterns. Targeted lifestyle interventions may help reduce early central adiposity in university students. BMI waist circumference physical activity sleep history dietary source college students Figures Figure 1 1. BACKGROUND Both common and professionals often use the terms exercise, physical activity, and physical fitness interchangeably. It is crucial to define these terms to provide an organized framework for interpreting and comparing studies. Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure, measured in kilocalories. 1 It includes household, occupational, sports, self-care, and other daily activities. The amount of energy expended varies across individuals depending on the intensity, duration, frequency, and type of activity. Exercise is a structured, organized, and repetitive form of physical activity undertaken with the goal of improving or maintaining physical fitness. Physical fitness refers to health-related and skill-related attributes, and has been described as “the ability to carry out daily tasks with Vigor and alertness, to enjoy leisure pursuits, and to meet unforeseen emergencies”. 2 Physical inactivity and obesity represent critical, interlinked public-health challenges worldwide. Globally, more than one quarter of adults fail to meet recommended physical activity levels, and this inactivity contributes significantly to the burden of non-communicable diseases (NCDs). 3 Young adulthood, particularly the university years, is a pivotal period when lifestyle habits consolidate into long-term patterns, making this stage an important target for prevention efforts. In India, the situation mirrors global concerns but with added urgency. Large-scale survey data show surprisingly high rates of physical inactivity, over 50% of adults in some cohorts do not engage in sufficient activity. 4 Among urban populations, nearly half report low recreational activity and many university-age students report high sedentary behaviour 5 Studies in Indian medical colleges, for example, find that despite being young and well-informed, medical undergraduates’ physical activity levels are variable, and many show body-composition parameters (like waist–hip ratio) associated with higher metabolic risk. 6 Simultaneously, the prevalence of obesity in India has reached alarming levels recent nationwide data estimate that over 40% of adults are obese using standard definitions, with particularly high waist-circumference measures in certain subgroups. 7 Anthropometric indices such as Body Mass Index (BMI) have long been used to quantify obesity, but they are limited by their inability to distinguish between overall weight and fat distribution. In contrast, waist circumference (WC) more directly captures central (visceral) adiposity, which is strongly linked with metabolic disturbances such as insulin resistance, dyslipidaemia, and cardiovascular disease even in individuals whose BMI would classify them as “normal.” 8,9 In young adult populations, combining BMI with WC may therefore offer superior risk stratification and early identification of individuals at risk for cardiometabolic disease. Despite this, there is a gap in the literature especially among Indian university students on how BMI and WC relate to both physical activity motivation (interest) and actual lifestyle behaviours such as sleep quality and dietary habits. Moreover, the transition to university life is accompanied by lifestyle changes (increased access to processed meals, erratic sleep, academic stress) that may influence central adiposity independently of BMI. Understanding how anthropometric risk (through BMI and WC) aligns with motivational (interest) and behavioural factors could inform tailored interventions for early prevention. Therefore, the primary objective of this study was to examine associations between BMI, waist circumference, and self-reported interest in physical activity among college students. Secondary objectives included evaluating whether BMI and WC differ in relation to physical activity frequency/intensity, sleep issues, and usual dietary source (home-cooked vs. outside food), while also exploring gender differences. Based on existing evidence linking anthropometry with behavioural outcomes, we hypothesized that central adiposity (waist circumference) might be more sensitive than BMI in reflecting variation in lifestyle behaviours, including interest in physical activity. 2. METHODS Participants Recruitment (Fig. 1) : This cross-sectional study was conducted among undergraduate students of SRM Institute of Science and Technology (SRMIST), Tamil Nadu, India, to examine associations between body mass index (BMI), waist circumference (WC), and interest in physical activity. A multistage sampling strategy was adopted to ensure representation across academic disciplines and gender. Nine undergraduate departments were formally approached through their Heads of Department with study objectives, ethical clearance, and procedural details. Six departments provided consent, while three declined due to academic constraints. Following departmental approval, faculty coordinators assisted in scheduling orientation sessions during which study objectives, confidentiality, and assessment procedures were explained. Participation was voluntary, and all eligible students from the consenting departments were invited. Sample size estimation using G*Power 3.1 for a two-tailed Pearson correlation (r = 0.20, α = 0.05, power = 0.80) indicated a minimum requirement of 194 participants; accounting for a 15% nonresponse rate, a target of 224 was planned. Higher-than-expected participation allowed recruitment to be extended to enhance statistical power and permit subgroup analyses. Data collection was conducted between July and November 2025. A total of 493 students were initially enrolled. Inclusion criteria were full-time undergraduate enrolment, age 18–23 years, absence of chronic medical or orthopaedic conditions, and provision of informed consent. Exclusion criteria included recent illness, acute injury, or participation in structured fitness or dietary programs. Ninety-three students were excluded due to ineligibility, non-attendance, withdrawal, or incomplete anthropometric data, particularly refusal of WC measurement. The final sample comprised 400 participants (216 males, 184 females). Assessments were conducted by same-gender investigators to ensure privacy. The study was approved by the Departmental Internal Scientific Committee and conducted in accordance with the Declaration of Helsinki. Anthropometric Measurements : Body Mass Index (BMI) Height and weight were measured using standardized protocols aligned with large-scale Indian epidemiological surveys. 10 Height was measured to the nearest 0.1 cm using a wall-mounted stadiometer, and weight to the nearest 0.1 kg using a calibrated digital scale, with participants barefoot and wearing light clothing. Two readings were obtained, with a third taken if discrepancies exceeded predefined limits; the mean of the closest two values was used. BMI was calculated as weight (kg)/height² (m²) and classified using WHO criteria 11 adapted for South Asian populations 12 : underweight (< 18.5 kg/m²), normal (18.5–23.9 kg/m²), overweight (24.0–27.9 kg/m²), and obese (≥ 28 kg/m²). Waist Circumference (WC) WC was measured following WHO STEPS protocols 13 using a non-elastic tape at the midpoint between the lower rib margin and iliac crest at the end of normal expiration. Two readings were recorded, with a third taken if differences exceeded 0.5 cm. 14 Asian Indian cut-offs were applied: normal (< 90 cm for males, < 80 cm for females) and high-risk (≥ 90 cm for males, ≥ 80 cm for females). 15 Male participants were assessed by male investigators and females by female investigators to maintain comfort and privacy. Questionnaire Based Measures : International Physical Activity Questionnaire – Short Form (IPAQ-SF) The IPAQ-SF assessed frequency and duration of walking, moderate, and vigorous activities over the previous seven days, including sitting time. 16 Only activities lasting ≥ 10 minutes were considered. Responses were converted to MET-minutes/week 17 using standardized scoring, and participants were categorized into low, moderate, or high activity levels. Youth Physical Activity Questionnaire (YPAQ) The YPAQ was used to assess habitual physical activity frequency and sedentary behaviour. 18 Participants reported how often routine physical activities were performed during a typical week using standardized categories (never, once, two to three times, and four or more times per week), which were converted to numerical values (0, 1, 2.5, and 4.5 sessions/week) for analysis. The YPAQ has shown moderate validity when compared with accelerometer-based measures and was employed as a frequency-based complement to the intensity estimates obtained from the IPAQ-SF. 19,20 Self-Reported Questionnaire Measures A brief self-reported questionnaire was used to collect contextual information on demographics, lifestyle behaviours, sleep patterns, and interest in physical activity. To reduce respondent burden and enhance response accuracy, only concise, single-domain items were included, as longer questionnaires are associated with reduced data quality in young adults. 21 , 22 , 23 , 24 Demographic data (age and gender) were collected to characterize the sample and enable subgroup analyses. 25 , 26 Dietary context was assessed using a single categorical item on usual meal location (canteen, hostel, home-cooked, restaurant, or mixed), serving as a practical proxy for dietary patterns in student populations. 27 , 28 , 29 Sleep behaviour was evaluated using a brief symptom checklist covering common sleep-related difficulties (sleep initiation, awakening, non-restorative sleep, nocturnal awakenings, or no problems), commonly used in epidemiological screening. 30 , 31 , 32 Interest in physical activity was assessed using a single-item categorical measure ranging from “not at all interested” to “very much interested,” including “not sure” and “others,” which is appropriate for simple motivational constructs in the absence of a validated student-specific tool. 33 , 34 , 35 3. DATA ANALYSIS Data were analysed using descriptive and inferential statistics. Continuous variables, such as age, BMI, and waist circumference (WC), were summarised as mean ± standard deviation (SD), while categorical variables, including gender, interest in physical activity, frequency and intensity of activity, sleep history, and dietary patterns, were presented as frequencies and percentages. BMI was categorised according to standard cut-offs and Waist circumference was classified using Asian gender-specific thresholds. IPAQ MET scores were grouped into Mild, Moderate, and Severe categories for analysis. Associations between BMI and categorical lifestyle variables along with waist circumference and categorical lifestyle variables were assessed using Chi-square tests. All statistical tests were two-tailed, and a p-value of <0.05 was considered statistically significant. No adjustment for confounding, subgroup/interaction, or sensitivity analyses were performed, the dataset contained no missing values, so a complete-case analysis was possible. Analyses were performed using IBM SPSS Statistics (Version 26). TABLE 1 DEMOGRAPHIC CHARACTERISTICS FACTORS MEAN FREQUENCY (n) PERCENTAGE (%) AGE 19.95 400 - GENDER - 216 46% MALE FEMALE - 184 54% BMI CATEGORY - 73 18.3% UNDER WEIGHT NORMAL WEIGHT - 226 56.5% OVER WEIGHT - 80 20% OBESITY - 21 5.3% WAIST CIRCUMFERENCE CATEGORY - 80 20% FEMALE < 80 cm FEMALE ≥ 80 cm - 120 30% MALE < 90 cm - 60 15% MALE ≥ 90 cm - 140 35% TABLE 2 ASSOCIATION OF PHYSICAL ACTIVITY, SLEEP AND DEITARY HABITS TO BMI FACTORS UNDER WEIGHT n (%) NORMAL n (%) OVER WEIGHT n (%) OBESITY n (%) P VALUE Interest in PA Not at all interested Not really interested Somewhat interested Very much interested Not sure Others 4(20.0) 11(20.4) 31(19.7) 20(18.2) 7(15.9) 0 13(65.0) 29(53.7) 89(56.7) 68(61.8) 20(45.5) 7(46.7) 3(15.0) 10(18.5) 29(18.5) 18(16.4) 13(29.5) 7(46.7) 0 4(7.4) 8(5.1) 4(3.6) 4(9.1) 1(6.7) 0.304 Frequency in PA Never Rarely Often 19(17.1) 26(17.6) 28(19.9) 59(53.2) 93(62.8) 74(52.5) 30(27.0) 23(15.5) 27(19.1) 3(2.7) 6(4.1) 12(8.5) 0.092 IPAQ METs Mild Moderate Severe 3(20.0) 35(16.4) 35(20.3) 8(53.3) 116(54.5) 102(59.3) 3(20.0) 46(21.6) 31(18.0) 1(6.7) 16(7.5) 4(2.3) 0.341 Sleep History Difficulty in sleeping Difficulty in waking up Feels unrested after waking up Waking in middle of the night and cannot fall back to sleep Walking in middle of the night None 6(12.0) 21(26.9) 4(8.9) 1(9.1) 4(15.4) 37(19.5) 35(70.0) 44(56.4) 24(53.3) 5(45.5) 18(69.2) 100(52.6) 7(14.0) 11(14.1) 15(33.3) 4(36.4) 3(11.5) 40(21.1) 2(4.0) 2(2.6) 2(4.4) 1(9.1) 1(3.8) 13(6.8) 0.114 USUAL DIETARY SOURCE College canteen Hostel Home cooked Restaurant Mixed 1(25.0) 6(17.1) 64(18.9) 2(40.0) 0 2(50.0) 18(51.4) 190(56.0) 1(20.0) 15(88.2) 0 68(20.1) 9(25.7) 1(20.0) 2(11.8) 1(25.0) 2(5.7) 17(5.0) 1(20.0) 0 0.152 BMI= Body mass index; n= Frequency; %= Percentage; PA= Physical activity; IPAQ METs= International Physical Activity Questionnaire Metabolic Equivalents Score; p-values derived from Chi-square test; p < 0.05 considered statistically significant. TABLE 3 ASSOCIATION OF PHYSICAL ACTIVITY, SLEEP AND DEITARY HABITS TO WC FACTORS 90(M) n (%) 80(F) n (%) P VALUE Interest in PA Not at all interested Not really interested Somewhat interested Very much interested Not sure Others 2(1.4) 25(18.0) 54(54.6) 47(38.2) 6(15.2) 5(5.3) 2(2.6) 9(11.7) 30(39.0) 27(35.1) 9(11.7%) 0 4(7.4) 7(13.0) 21(38.9) 9(16.7) 9(16.7) 4(7.4) 12(9.2) 13(10.0) 52(40.0) 27(20.8) 20(15.4) 6(4.6) 0.002* Frequency in PA Never Rarely Often 32(23.0) 40(28.8) 67(48.2) 15(19.5) 27(35.1) 35(45.5) 21(38.9) 19(35.2) 14(25.9) 43(33.1) 55(42.3) 32(24.6) 0.001* IPAQ Mets Mild Moderate Severe 6(4.3) 77(55.4) 56(40.3) 3(3.9) 34(44.2) 40(51.9) 3(5.6) 42(77.8) 9(16.7) 3(2.3) 60(46.2) 67(51.5) 0.001* Sleep History Difficulty in sleeping Difficulty in waking up Feels unrested after waking up Waking in middle of the night and cannot fall back to sleep Walking in middle of the night None 19(13.7) 30(21.6) 15(10.8) 5(3.6) 3(2.2) 67(48.2) 18(23.4) 6(7.8) 10(13.0) 0 4(5.2) 39(50.6) 3(5.6) 13(24.1) 4(7.4) 3(5.6) 7(13.0) 4(44.4) 10(7.7) 29(22.3) 16(12.3) 3(2.3) 12(9.2) 60(46.2) 0.004* USUAL DIETARY SOURCE College canteen Hostel Home cooked Restaurant Mixed 2(1.4) 9(6.4) 125(89.9) 0 3(2.1) 5(6.5) 4(5.2) 61(74.3) 2(2.6) 5(6.1) 0 12(22.3) 41(72.2) 0 5(6.5) 2(1.6) 11(8.4) 112(86.2) 3(2.3) 2(3.9) 0.009* WC= Waist Circumference; 90(M)= circumference greater than 90 male; 80(F)= circumference greater than 80 female; n= Frequency; %= Percentage; PA= Physical activity; IPAQ METs= International Physical Activity Questionnaire Metabolic Equivalents Score; p-values derived from Chi-square test; * = p < 0.05 considered statistically significant. 4. RESULTS In this cross-sectional study, 400 college students aged 18 to 23 years participated to examine the association between body mass index (BMI), waist circumference (WC), and the level of interest in physical activity. Complete data for the variables included in the analysis were collected from students who were recruited from various departments during scheduled academic hours after excluding individuals who were ineligible, withdrew, or had incomplete anthropometric data. Table 1 presents the demographic and anthropometric characteristics of the study population. Of the 400 student participants, 216 were male and 184 were female, with a mean age of 19.95 years. More than half of the students (56.5%) were within the normal BMI range, while 20% were classified as overweight and 5.3% as obese. Waist circumference findings further indicated that a notable proportion of students exhibited central adiposity, with 35% of male students exceeding the recommended cut-off of 90 cm and 30% of female students exceeding 80 cm. Across BMI categories, no lifestyle variable demonstrated a statistically significant association, as shown in Table 2 . Interest in physical activity (p = 0.304), frequency of participation (p = 0.092), IPAQ-based activity intensity (p = 0.341), sleep-related characteristics (p = 0.114), and usual dietary source (p = 0.152) all showed nonsignificant differences among underweight, normal weight, overweight, and obese students. Although minor numerical variations were present with normal-weight students generally forming the largest share and obese students contributing smaller proportions, none of these differences reached statistical significance, indicating that BMI was not meaningfully associated with any assessed lifestyle behaviour. Furthermore, waist-circumference categories represented significant associations for multiple lifestyle behaviours, as summarised in Table 3 . Interest in physical activity (p = 0.002), frequency of participation (p = 0.001), IPAQ-based activity intensity (p = 0.001), sleep-related characteristics (p = 0.004), and usual dietary source (p = 0.009) all differed meaningfully between students with normal and elevated waist circumference. Participants within the lower WC ranges (< 90 cm for males; <80 cm for females) showed higher levels of physical-activity interest, more frequent participation, and greater representation in moderate and severe IPAQ intensity levels, whereas those above the WC cut-offs consistently reported lower engagement and contributed the smallest proportions to higher activity categories. Students with elevated WC also demonstrated more sleep disturbances and greater variability in dietary-location patterns. Overall, waist circumference unlike BMI showed significant associations across all assessed lifestyle variables, with higher WC consistently linked to less favourable behavioural profiles. 5. DISCUSSION The findings of this study indicate that although 56.5% of students fell within the normal BMI range, waist circumference (WC) assessment identified a substantially higher proportion with central obesity. This discrepancy between BMI and WC has been consistently reported in studies among Indian university populations, where BMI often underestimates adiposity while WC reveals a greater burden of abdominal fat. 36 , 37 , 38 This pattern may be explained by the known tendency of South Asian young adults to accumulate visceral fat at lower BMI values, a characteristic widely documented in regional epidemiological literature. 39 Central obesity was more prevalent among male students despite both genders largely exhibiting normal BMI values. While similar patterns of greater abdominal fat accumulation among young males have been reported, findings across Indian populations remain variable. 40 These gender differences are likely influenced by behavioural, dietary, and lifestyle factors rather than BMI alone. Female students often demonstrate greater dietary restraint and body-shape awareness, which may help limit abdominal fat accumulation. 41 In contrast, male students commonly report longer screen time, irregular sleep patterns, and lower engagement in structured physical activity, behaviours independently associated with increased central fat deposition. 42 , 43 Additionally, higher consumption of calorie-dense foods, takeaway meals, and late-night snacking is more frequently reported among males, potentially contributing to higher WC-defined obesity. 44 , 45 Alcohol consumption and smoking, which are more prevalent among male university students, are also linked to visceral fat accumulation and adverse metabolic profiles, further explaining the higher prevalence of central obesity observed. 46 , 47 Regarding associations with lifestyle factors, BMI was not significantly related to interest in physical activity, frequency of participation, IPAQ MET categories, sleep patterns, or usual dietary sources. Across BMI categories, students reported similar levels of physical activity interest and engagement, indicating no clear trend between BMI and physical activity behaviour. This aligns with findings from international studies reporting weak or non-significant associations between BMI and self-reported physical activity among young adults. 48 , 49 These observations may reflect limitations of questionnaire-based physical activity measures, which often capture perceived rather than physiologically meaningful activity. 50 Moreover, factors such as diet quality, caloric intake, sedentary behaviour, sleep patterns, and genetic or metabolic variability may exert stronger influences on BMI, diluting its association with physical activity in cross-sectional designs. 51 A notable strength of this study is the inclusion of “interest in physical activity” as a motivational measure alongside behavioural indicators, which remains relatively uncommon. By evaluating interest, frequency, and intensity of activity in conjunction with anthropometry, this study provides a more comprehensive understanding of the behavioural and psychological dimensions of physical activity. The findings highlight that motivation alone does not guarantee sufficient activity to influence BMI or adiposity, emphasizing the need for interventions that translate interest into sustained and adequately intense physical activity. In contrast to BMI, waist circumference showed significant associations with interest in physical activity, participation frequency, IPAQ MET levels, sleep disturbances, and dietary sources. Students with higher WC demonstrated lower interest and participation in physical activity, along with greater representation in irregular or sporadic activity patterns despite similar MET totals, likely reflecting sporadic rather than sustained activity patterns. Poor sleep quality and unfavourable dietary habits were also more common among those with higher WC, suggesting clustering of lifestyle behaviours linked to central adiposity. These findings support evidence indicating WC as a superior behavioural and metabolic indicator compared to BMI. 52 , 53 , 54 Literature suggests that WC reflects not only visceral fat accumulation but also behavioural characteristics related to physical activity tolerance, motivation, and lifestyle regularity. Individuals with higher WC often experience greater perceived exertion, reduced exercise tolerance, and lower psychological readiness for activity, which may limit continuous or vigorous physical activity despite similar total reported activity levels. 55 , 56 Suboptimal dietary habits and inconsistent sleep further reinforce a reciprocal cycle in which lifestyle behaviours promote central fat accumulation, which in turn constrains lifestyle capacity. 57 By integrating anthropometric, behavioural, and lifestyle assessments, this study underscores WC as a more sensitive indicator of health risk in young adults than BMI. The strengths of this study include its multidimensional assessment of lifestyle factors using validated questionnaires and the application of gender-specific WC cut-offs, enhancing clinical relevance. However, the cross-sectional design limits causal inference, and self-reported measures may introduce recall or social-desirability bias. Dietary assessment lacked detailed nutrient quantification, and more advanced body composition measures were not included. 58 Future research should employ objective physical activity monitoring, structured sleep assessments, detailed nutritional profiling, and advanced body composition analyses to better elucidate the interplay between lifestyle behaviours and adiposity in young adults. 6. CONCLUSION The association between waist circumference (WC) and lifestyle behaviours among Indian college students showed that higher WC was consistently linked with lower interest in physical activity, reduced participation frequency, irregular sleep patterns, and less favourable dietary habits. In contrast, BMI did not show a clear association with these behaviours across categories. The impact of central adiposity on lifestyle behaviours was more pronounced in male students than in female students, highlighting the relevance of WC as a sensitive indicator for behavioural and metabolic risk in young adults. These results provide a reference for promoting healthier lifestyle behaviours among college students, with a focus on enhancing interest in physical activity. Interventions should prioritize educational and awareness programs that motivate students to engage in regular exercise, improve sleep routines, and adopt balanced dietary habits. Encouraging structured physical activity at least three times per week, integrating movement into daily life, and fostering supportive environments may help maintain healthy body composition and stimulate sustained engagement in physical activity. Future efforts should target both behavioural motivation and practical opportunities to translate interest into consistent, beneficial habits. Abbreviations BMI: Body Mass Index WC: Waist Circumference IPAQ- SF: International Physical Activity Questionnaire-Short Form MET: Metabolic Equivalents Score PA: Physical Activity YPAQ: Youth Physical Activity Questionnaire NCDs: Non-Communicable Diseases STATEMENTS AND DECLARATIONS Ethics approval and consent to participate: Each participant read and signed a written informed consent form prior to enrollment. The study protocol was approved by the Institutional Ethics Committee of SRM Institute of Science and Technology. Competing Interests: The authors declare that they have no competing interests. Funding: Self-funded. Authors' contributions: M Anbupriya :Provided overall conceptual guidance, supervised the study design and methodology, critically reviewed the analysis and interpretation of findings, and approved the final version of the manuscript. A Kamaleswari: Conceived the study design, conducted participant recruitment and data collection, performed statistical analysis, and contributed to interpretation of the results . Karthikeyan S and Nandhini S: Drafted the initial manuscript, organized the results and discussion sections, performed literature review, and revised the manuscript based on critical feedback. Acknowledgements : The authors would like to thank the students for their participation in the study. Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public health reports. 1985 Mar;100(2):126. Haverkamp BF, Oosterlaan J, Königs M, Hartman E. Physical fitness, cognitive functioning and academic achievement in healthy adolescents. Psychology of Sport and Exercise. 2021 Nov 1;57:102060. Anjana RM, Pradeepa R, Das AK, Deepa M, Bhansali A, Joshi SR, Joshi PP, Dhandhania VK, Rao PV, Sudha V, Subashini R. Physical activity and inactivity patterns in India–results from the ICMR-INDIAB study (Phase-1)[ICMR-INDIAB-5]. International Journal of Behavioral Nutrition and Physical Activity. 2014 Feb 26;11(1):26. Newtonraj A, Murugan N, Singh Z, Chauhan RC, Velavan A, Mani M. Factors associated with physical inactivity among adult urban population of Puducherry, India: a population based cross-sectional study. Journal of clinical and diagnostic research: JCDR. 2017 May 1;11(5):LC15. Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1· 9 million participants. The lancet global health. 2018 Oct 1;6(10):e1077-86. Keating XD, Guan J, Piñero JC, Bridges DM. A meta-analysis of college students' physical activity behaviors. Journal of American college health. 2005 Sep 1;54(2):116-26. Venkatrao M, Nagarathna R, Majumdar V, Patil SS, Rathi S, Nagendra H. Prevalence of obesity in India and its neurological implications: a multifactor analysis of a nationwide cross-sectional study. Annals of Neurosciences. 2020 Jul;27(3-4):153-61. Lim SH, Lee T, Oh J, Hwang KH, Choi EH, Cha SK. Waist Circumference as an Independent Marker of Insulin Resistance: Evidence from a Nationwide Korean Population Study. Journal of Clinical Medicine. 2025 Nov 10;14(22):7957. Wildman RP, Gu D, Reynolds K, Duan X, Wu X, He J. Are waist circumference and body mass index independently associated with cardiovascular disease risk in Chinese adults?. The American journal of clinical nutrition. 2005 Dec 1;82(6):1195-202. Iips IC. National family health survey (NFHS-5): 2019-21 India. Mumbai: International Institute for Population Sciences (IIPS). 2021. World Health Organization. Body mass index – BMI: BMI classifications [Internet]. Geneva: WHO; [cited 2025 Feb 24]. Available from: https://www.who.int/data/gho/data/themes/theme-details/GHO/body-mass-index-(bmi) Misra A, Vikram NK. Clinical and pathophysiological consequences of abdominal adiposity and abdominal adipose tissue depots. Nutrition. 2003 May 1;19(5):457-66. World Health Organization. WHO STEPS surveillance manual: the WHO STEPwise approach to chronic disease risk factor surveillance/Noncommunicable Diseases and Mental Health, World Health Organization. InWHO STEPS surveillance manual: the WHO STEPwise approach to chronic disease risk factor surveillance/Noncommunicable Diseases and Mental Health, World Health Organization 2005. Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, Joshi SR, Sadikot S, Gupta R, Gulati S, Munjal YP. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. Japi. 2009 Feb;57(2):163-70. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund UL, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Medicine & science in sports & exercise. 2003 Aug 1;35(8):1381-95. IPAQ Research Committee. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)-short and long forms. http://www. ipaq. ki. se/scoring. pdf. 2005. Brooke HL, Corder K, Griffin SJ, van Sluijs EM. Physical activity maintenance in the transition to adolescence: a longitudinal study of the roles of sport and lifestyle activities in British youth. PloS one. 2014 Feb 12;9(2):e89028. McCrorie PR, Perez A, Ellaway A. The validity of the Youth Physical Activity Questionnaire in 12–13-year-old Scottish adolescents. BMJ Open Sport & Exercise Medicine. 2017 Jan 6;2(1). Corder K, Van Sluijs EM, Wright A, Whincup P, Wareham NJ, Ekelund U. Is it possible to assess free-living physical activity and energy expenditure in young people by self-report?. The American journal of clinical nutrition. 2009 Mar 1;89(3):862-70. Rolstad S, Adler J, Rydén A. Response burden and questionnaire length: is shorter better? A review and meta-analysis. Value in Health. 2011 Dec 1;14(8):1101-8. Galesic M, Bosnjak M. Effects of questionnaire length on participation and indicators of response quality in a web survey. Public opinion quarterly. 2009 Jan 1;73(2):349-60. Fan W, Yan Z. Factors affecting response rates of the web survey: A systematic review. Computers in human behavior. 2010 Mar 1;26(2):132-9. Edwards PJ, Roberts I, Clarke MJ, DiGuiseppi C, Woolf B, Perkins C. Methods to increase response to postal and electronic questionnaires. Cochrane database of systematic reviews. 2023(11). Tourangeau R, Rips LJ, Rasinski K. The psychology of survey response. Bowling A. Mode of questionnaire administration can have serious effects on data quality. Journal of public health. 2005 Sep 1;27(3):281-91. Laska MN, Larson NI, Neumark-Sztainer D, Story M. Dietary patterns and home food availability during emerging adulthood: do they differ by living situation?. Public health nutrition. 2010 Feb;13(2):222-8. Slotnick MJ, Ansari S, Parnarouskis L, Gearhardt AN, Wolfson JA, Leung CW. Persistent and Changing Food Insecurity Among Students at a Midwestern University is Associated With Behavioral and Mental Health Outcomes. American Journal of Health Promotion. 2024 May;38(4):483-91. Betancourt-Núñez A, Díaz R, Nava-Amante PA, Bernal-Orozco MF, Díaz-López A, González Palacios A, Márquez-Sandoval F, Velarde-Camaqui D, Vizmanos B. Beyond the Classroom: The Influence of Food Insecurity, Mental Health, and Sleep Quality on University Students’ Academic Performance. Foods. 2024 Aug 11;13(16):2508. Buysse D. The Pittsburgh sleep quality index (PSQI). An instrument for psychiatric practice and research. Psychiatry Res.. 1988;28:193-213. Lund HG, Reider BD, Whiting AB, Prichard JR. Sleep patterns and predictors of disturbed sleep in a large population of college students. Journal of adolescent health. 2010 Feb 1;46(2):124-32. Hershner SD, Chervin RD. Causes and consequences of sleepiness among college students. Nature and science of sleep. 2014 Jun 23:73-84. Rhodes RE, Smith NE. Personality correlates of physical activity: a review and meta-analysis. British journal of sports medicine. 2006 Dec 1;40(12):958-65. Dishman RK, Sallis JF, Orenstein DR. The determinants of physical activity and exercise. Public health reports. 1985 Mar;100(2):158. Wilson PM, Rodgers WM, Fraser SN. Examining the psychometric properties of the behavioral regulation in exercise questionnaire. Measurement in physical education and exercise science. 2002 Mar 1;6(1):1-21. Pengpid S, Peltzer K. Prevalence of overweight/obesity and central obesity and its associated factors among a sample of university students in India. Obesity research & clinical practice. 2014 Nov 1;8(6):e558-70. Nawab T, Khan Z, Khan IM, Ansari MA. Central obesity is a burden even in normal weight adolescents of a non-metropolitan Indian City: A case for alarm and action for prevention and control. Journal of Family Medicine and Primary Care. 2025 Jan 1;14(1):283-9. Behera S, Mishra A, Esther Sr A, Sahoo A. Tailoring body mass index for prediction of obesity in young adults: A multi-centric study on MBBS students of Southeast India. Cureus. 2021 Jan 8;13(1). Misra A, Khurana L. Obesity and the metabolic syndrome in developing countries. The Journal of Clinical Endocrinology & Metabolism. 2008 Nov 1;93(11_supplement_1):s9-30. Krishnan B, Kharde A. Assessment of Obesity using Anthropometric Markers among University Students. Current Research in Nutrition and Food Science. 2021 Apr 1;9(1):211. Moitra M, Desai K, Chaudhari V. Perceived body image among young girls residing in urban slums and reality: A cross sectional study. Natl J Community Med. 2019;10:579-84. Moitra P, Madan J, Verma P. Independent and combined influences of physical activity, screen time, and sleep quality on adiposity indicators in Indian adolescents. BMC Public Health. 2021 Nov 15;21(1):2093. Yadav G, Bodat S, Siwach I, Sachdeva K, Chuahan N. Physical activity and its relation with body composition among undergraduate medical students in Delhi: a cross sectional study. International Journal of Community Medicine and Public Health. 2020 Nov;7(11):4530. Francis DK, Van den Broeck J, Younger N, McFarlane S, Rudder K, Gordon-Strachan G, Grant A, Johnson A, Tulloch-Reid M, Wilks R. Fast-food and sweetened beverage consumption: association with overweight and high waist circumference in adolescents. Public health nutrition. 2009 Aug;12(8):1106-14. Ganpule A, Dubey M, Pandey H, Venkateshmurthy NS, Green R, Brown KA, Maddury AP, Khatkar R, Jarhyan P, Prabhakaran D, Mohan S. Snacking behavior and association with metabolic risk factors in adults from north and south India. The Journal of nutrition. 2023 Feb 1;153(2):523-31. Park KY, Park HK, Hwang HS. Relationship between abdominal obesity and alcohol drinking pattern in normal-weight, middle-aged adults: the Korea National Health and Nutrition Examination Survey 2008–2013. Public Health Nutrition. 2017 Aug;20(12):2192-200. Sumi M, Hisamatsu T, Fujiyoshi A, Kadota A, Miyagawa N, Kondo K, Kadowaki S, Suzuki S, Torii S, Zaid M, Sato A. Association of alcohol consumption with fat deposition in a community-based sample of Japanese men: the Shiga Epidemiological Study of Subclinical Atherosclerosis (SESSA). Journal of epidemiology. 2019 Jun 5;29(6):205-12. Yousif MM, Kaddam LA, Humeda HS. Correlation between physical activity, eating behavior and obesity among Sudanese medical students Sudan. BMC nutrition. 2019 Feb 6;5(1):6. Liu L, Liu Y, Zhang T, Luo J. Study on the influence of levels of physical activity and socio-economic conditions on body mass index of adolescents. International Health. 2025 Jul;17(4):470-80. Lee YY, Kamarudin KS, Wan Muda WA. Associations between self-reported and objectively measured physical activity and overweight/obesity among adults in Kota Bharu and Penang, Malaysia. BMC Public Health. 2019 May 22;19(1):621. AYDOĞAN K, KOSTANOĞLU A, TÖRPÜ GC. Effect of Body Mass Index on Balance, Trunk Muscle Endurance, Functional Mobility and, Physical Activity in College Students. Bezmialem Science. 2024 Nov 4. Peterson NE, Sirard JR, Kulbok PA, DeBoer MD, Erickson JM. Sedentary behavior and physical activity of young adult university students. Research in nursing & health. 2018 Feb;41(1):30-8. Carneiro-Barrera A, Amaro-Gahete FJ, Acosta FM, Ruiz JR. Body composition impact on sleep in young adults: the mediating role of sedentariness, physical activity, and diet. Journal of Clinical medicine. 2020 May 21;9(5):1560. Jayawardana NW, Jayalath WA, Madhujith WM, Ralapanawa U, Jayasekera RS, Alagiyawanna SA, Bandara AM, Kalupahana NS. Lifestyle factors associated with obesity in a cohort of males in the central province of Sri Lanka: a cross-sectional descriptive study. BMC public health. 2017 Jan 5;17(1):27. Dagan SS, Segev S, Novikov I, Dankner R. Waist circumference vs body mass index in association with cardiorespiratory fitness in healthy men and women: a cross sectional analysis of 403 subjects. Nutrition journal. 2013 Jan 15;12(1):12. Ekelund U, Besson H, Luan JA, May AM, Sharp SJ, Brage S, Travier N, Agudo A, Slimani N, Rinaldi S, Jenab M. Physical activity and gain in abdominal adiposity and body weight: prospective cohort study in 288,498 men and women. The American journal of clinical nutrition. 2011 Apr 1;93(4):826-35. Jansen EC, Dunietz GL, Tsimpanouli ME, Guyer HM, Shannon C, Hershner SD, O’Brien LM, Baylin A. Sleep, diet, and cardiometabolic health investigations: a systematic review of analytic strategies. Current nutrition reports. 2018 Dec;7(4):235-58. Borga M, West J, Bell JD, Harvey NC, Romu T, Heymsfield SB, Dahlqvist Leinhard O. Advanced body composition assessment: from body mass index to body composition profiling. Journal of Investigative Medicine. 2018 Jun;66(5):1-9. Additional Declarations No competing interests reported. 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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-8714032","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595085495,"identity":"450f4ab9-c54d-40f0-bfbd-e2922e7b07a1","order_by":0,"name":"M Anbupriya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYFACHhAhwcAPohIYoGQCMVokG8CKDYjWwsBgcABCMRBSz8A/u/eYdOEei2jj82efbnjw5w8DP3uOAcPDHbi1SNw5lyY945lE7rYb6WY3EtsMGCR73hgwJJ7BY82NHDNpngMgLWxsNxIbDBgMbgBtSWzDrUMepmVz/zG2Gwl/DBjsCWkxgGnZwJAG1MIGtEWCgBbDG3nJ1jOAWmbcAGpJbDPmkTjzrOAAPi1yN3IP3i44UJfbD3TYzR9/5OT425M3PvyJRwsIMCNzwNF0AL8GNC2jYBSMglEwCjAAAA83UaB0QxnEAAAAAElFTkSuQmCC","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"M","middleName":"","lastName":"Anbupriya","suffix":""},{"id":595085496,"identity":"eb7c8eda-fc21-4684-9616-260ff4734765","order_by":1,"name":"A Kamaleswari","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"A","middleName":"","lastName":"Kamaleswari","suffix":""},{"id":595085497,"identity":"35c00e4a-f110-46c2-87e2-17c89a67d6b8","order_by":2,"name":"Karthikeyan S","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Karthikeyan","middleName":"","lastName":"S","suffix":""},{"id":595085498,"identity":"315baf2c-ec6c-4131-8228-3ff3b99720d3","order_by":3,"name":"Nandhini S","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Nandhini","middleName":"","lastName":"S","suffix":""}],"badges":[],"createdAt":"2026-01-27 20:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8714032/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8714032/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103349368,"identity":"81553a30-9d32-430c-a8a7-c228d0482d27","added_by":"auto","created_at":"2026-02-24 16:42:13","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95985,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8714032/v1/02809cf98015f423fefdcdd4.jpeg"},{"id":105903882,"identity":"238f1d3c-56c9-4e1f-9698-602045086d17","added_by":"auto","created_at":"2026-04-01 09:56:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1116371,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8714032/v1/56b868dc-aacd-423d-9f99-ea9b46bb81b0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssociation Between Bmi, Waist Circumference, and Level of Interest in Physical Activity: A Cross-sectional Study Among College Students\u003c/p\u003e","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eBoth common and professionals often use the terms exercise, physical activity, and physical fitness interchangeably. It is crucial to define these terms to provide an organized framework for interpreting and comparing studies. Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure, measured in kilocalories.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It includes household, occupational, sports, self-care, and other daily activities. The amount of energy expended varies across individuals depending on the intensity, duration, frequency, and type of activity. Exercise is a structured, organized, and repetitive form of physical activity undertaken with the goal of improving or maintaining physical fitness.\u003c/p\u003e \u003cp\u003ePhysical fitness refers to health-related and skill-related attributes, and has been described as \u0026ldquo;the ability to carry out daily tasks with Vigor and alertness, to enjoy leisure pursuits, and to meet unforeseen emergencies\u0026rdquo;. \u003csup\u003e2\u003c/sup\u003e Physical inactivity and obesity represent critical, interlinked public-health challenges worldwide. Globally, more than one quarter of adults fail to meet recommended physical activity levels, and this inactivity contributes significantly to the burden of non-communicable diseases (NCDs).\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Young adulthood, particularly the university years, is a pivotal period when lifestyle habits consolidate into long-term patterns, making this stage an important target for prevention efforts.\u003c/p\u003e \u003cp\u003eIn India, the situation mirrors global concerns but with added urgency. Large-scale survey data show surprisingly high rates of physical inactivity, over 50% of adults in some cohorts do not engage in sufficient activity.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Among urban populations, nearly half report low recreational activity and many university-age students report high sedentary behaviour \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Studies in Indian medical colleges, for example, find that despite being young and well-informed, medical undergraduates\u0026rsquo; physical activity levels are variable, and many show body-composition parameters (like waist\u0026ndash;hip ratio) associated with higher metabolic risk.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Simultaneously, the prevalence of obesity in India has reached alarming levels recent nationwide data estimate that over 40% of adults are obese using standard definitions, with particularly high waist-circumference measures in certain subgroups.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003eAnthropometric indices such as Body Mass Index (BMI) have long been used to quantify obesity, but they are limited by their inability to distinguish between overall weight and fat distribution.\u003c/p\u003e \u003cp\u003eIn contrast, waist circumference (WC) more directly captures central (visceral) adiposity, which is strongly linked with metabolic disturbances such as insulin resistance, dyslipidaemia, and cardiovascular disease even in individuals whose BMI would classify them as \u0026ldquo;normal.\u0026rdquo; \u003csup\u003e8,9\u003c/sup\u003e In young adult populations, combining BMI with WC may therefore offer superior risk stratification and early identification of individuals at risk for cardiometabolic disease. Despite this, there is a gap in the literature especially among Indian university students on how BMI and WC relate to both physical activity motivation (interest) and actual lifestyle behaviours such as sleep quality and dietary habits. Moreover, the transition to university life is accompanied by lifestyle changes (increased access to processed meals, erratic sleep, academic stress) that may influence central adiposity independently of BMI. Understanding how anthropometric risk (through BMI and WC) aligns with motivational (interest) and behavioural factors could inform tailored interventions for early prevention.\u003c/p\u003e \u003cp\u003eTherefore, the primary objective of this study was to examine associations between BMI, waist circumference, and self-reported interest in physical activity among college students. Secondary objectives included evaluating whether BMI and WC differ in relation to physical activity frequency/intensity, sleep issues, and usual dietary source (home-cooked vs. outside food), while also exploring gender differences. Based on existing evidence linking anthropometry with behavioural outcomes, we hypothesized that central adiposity (waist circumference) might be more sensitive than BMI in reflecting variation in lifestyle behaviours, including interest in physical activity.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cp\u003e \u003cb\u003eParticipants Recruitment (Fig.\u0026nbsp;1)\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eThis cross-sectional study was conducted among undergraduate students of SRM Institute of Science and Technology (SRMIST), Tamil Nadu, India, to examine associations between body mass index (BMI), waist circumference (WC), and interest in physical activity. A multistage sampling strategy was adopted to ensure representation across academic disciplines and gender. Nine undergraduate departments were formally approached through their Heads of Department with study objectives, ethical clearance, and procedural details. Six departments provided consent, while three declined due to academic constraints.\u003c/p\u003e \u003cp\u003eFollowing departmental approval, faculty coordinators assisted in scheduling orientation sessions during which study objectives, confidentiality, and assessment procedures were explained. Participation was voluntary, and all eligible students from the consenting departments were invited. Sample size estimation using G*Power 3.1 for a two-tailed Pearson correlation (r\u0026thinsp;=\u0026thinsp;0.20, α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;0.80) indicated a minimum requirement of 194 participants; accounting for a 15% nonresponse rate, a target of 224 was planned. Higher-than-expected participation allowed recruitment to be extended to enhance statistical power and permit subgroup analyses.\u003c/p\u003e \u003cp\u003eData collection was conducted between July and November 2025. A total of 493 students were initially enrolled. Inclusion criteria were full-time undergraduate enrolment, age 18\u0026ndash;23 years, absence of chronic medical or orthopaedic conditions, and provision of informed consent. Exclusion criteria included recent illness, acute injury, or participation in structured fitness or dietary programs. Ninety-three students were excluded due to ineligibility, non-attendance, withdrawal, or incomplete anthropometric data, particularly refusal of WC measurement. The final sample comprised 400 participants (216 males, 184 females). Assessments were conducted by same-gender investigators to ensure privacy. The study was approved by the Departmental Internal Scientific Committee and conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAnthropometric Measurements\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cb\u003eBody Mass Index (BMI)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eHeight and weight were measured using standardized protocols aligned with large-scale Indian epidemiological surveys.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Height was measured to the nearest 0.1 cm using a wall-mounted stadiometer, and weight to the nearest 0.1 kg using a calibrated digital scale, with participants barefoot and wearing light clothing. Two readings were obtained, with a third taken if discrepancies exceeded predefined limits; the mean of the closest two values was used. BMI was calculated as weight (kg)/height\u0026sup2; (m\u0026sup2;) and classified using WHO criteria\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e adapted for South Asian populations\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e: underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), normal (18.5\u0026ndash;23.9 kg/m\u0026sup2;), overweight (24.0\u0026ndash;27.9 kg/m\u0026sup2;), and obese (\u0026ge;\u0026thinsp;28 kg/m\u0026sup2;).\u003c/p\u003e \u003cp\u003e \u003cb\u003eWaist Circumference (WC)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWC was measured following WHO STEPS protocols\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e using a non-elastic tape at the midpoint between the lower rib margin and iliac crest at the end of normal expiration. Two readings were recorded, with a third taken if differences exceeded 0.5 cm.\u003csup\u003e14\u003c/sup\u003e Asian Indian cut-offs were applied: normal (\u0026lt;\u0026thinsp;90 cm for males, \u0026lt;\u0026thinsp;80 cm for females) and high-risk (\u0026ge;\u0026thinsp;90 cm for males, \u0026ge;\u0026thinsp;80 cm for females).\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Male participants were assessed by male investigators and females by female investigators to maintain comfort and privacy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuestionnaire Based Measures\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cb\u003eInternational Physical Activity Questionnaire \u0026ndash; Short Form (IPAQ-SF)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe IPAQ-SF assessed frequency and duration of walking, moderate, and vigorous activities over the previous seven days, including sitting time.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Only activities lasting\u0026thinsp;\u0026ge;\u0026thinsp;10 minutes were considered. Responses were converted to MET-minutes/week\u003csup\u003e17\u003c/sup\u003e using standardized scoring, and participants were categorized into low, moderate, or high activity levels.\u003c/p\u003e \u003cp\u003e \u003cb\u003eYouth Physical Activity Questionnaire (YPAQ)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe YPAQ was used to assess habitual physical activity frequency and sedentary behaviour.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Participants reported how often routine physical activities were performed during a typical week using standardized categories (never, once, two to three times, and four or more times per week), which were converted to numerical values (0, 1, 2.5, and 4.5 sessions/week) for analysis. The YPAQ has shown moderate validity when compared with accelerometer-based measures and was employed as a frequency-based complement to the intensity estimates obtained from the IPAQ-SF.\u003csup\u003e19,20\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSelf-Reported Questionnaire Measures\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA brief self-reported questionnaire was used to collect contextual information on demographics, lifestyle behaviours, sleep patterns, and interest in physical activity. To reduce respondent burden and enhance response accuracy, only concise, single-domain items were included, as longer questionnaires are associated with reduced data quality in young adults.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Demographic data (age and gender) were collected to characterize the sample and enable subgroup analyses.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDietary context was assessed using a single categorical item on usual meal location (canteen, hostel, home-cooked, restaurant, or mixed), serving as a practical proxy for dietary patterns in student populations.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Sleep behaviour was evaluated using a brief symptom checklist covering common sleep-related difficulties (sleep initiation, awakening, non-restorative sleep, nocturnal awakenings, or no problems), commonly used in epidemiological screening.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Interest in physical activity was assessed using a single-item categorical measure ranging from \u0026ldquo;not at all interested\u0026rdquo; to \u0026ldquo;very much interested,\u0026rdquo; including \u0026ldquo;not sure\u0026rdquo; and \u0026ldquo;others,\u0026rdquo; which is appropriate for simple motivational constructs in the absence of a validated student-specific tool.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"3. DATA ANALYSIS","content":"\u003cp\u003eData were analysed using descriptive and inferential statistics. Continuous variables, such as age, BMI, and waist circumference (WC), were summarised as mean \u0026plusmn; standard deviation (SD), while categorical variables, including gender, interest in physical activity, frequency and intensity of activity, sleep history, and dietary patterns, were presented as frequencies and percentages. BMI was categorised according to standard cut-offs and Waist circumference was classified using Asian gender-specific thresholds. IPAQ MET scores were grouped into Mild, Moderate, and Severe categories for analysis. Associations between BMI\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand categorical lifestyle variables along with waist circumference and categorical lifestyle variables were assessed using Chi-square tests. All statistical tests were two-tailed, and a p-value of \u0026lt;0.05 was considered statistically significant.\u0026nbsp;No adjustment for confounding, subgroup/interaction, or sensitivity analyses were performed, the dataset contained no missing values, so a complete-case analysis was possible. Analyses were performed using IBM SPSS Statistics (Version 26).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 1 \u0026nbsp; \u0026nbsp; \u0026nbsp; DEMOGRAPHIC CHARACTERISTICS\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFACTORS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEAN\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFREQUENCY \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePERCENTAGE (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAGE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e19.95\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGENDER\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMALE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFEMALE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e54%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBMI CATEGORY\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18.3%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eUNDER WEIGHT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNORMAL WEIGHT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOVER WEIGHT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOBESITY\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWAIST CIRCUMFERENCE CATEGORY\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFEMALE \u0026lt; 80 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFEMALE \u0026ge; 80 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMALE \u0026lt; 90 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMALE \u0026ge; 90 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eASSOCIATION OF PHYSICAL ACTIVITY, SLEEP AND DEITARY HABITS TO BMI\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"752\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFACTORS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNDER WEIGHT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNORMAL\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOVER WEIGHT n (%) \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOBESITY\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP VALUE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterest in PA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNot at all interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNot really interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSomewhat interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVery much interested\u003c/p\u003e\n \u003cp\u003eNot sure\u003c/p\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(20.0)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11(20.4)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31(19.7)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20(18.2)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7(15.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13(65.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;29(53.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;89(56.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;68(61.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;20(45.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;7(46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(15.0)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10(18.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29(18.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18(16.4)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13(29.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7(46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(7.4)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8(5.1)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(3.6)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(9.1)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.304\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Frequency in PA\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003eRarely\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOften\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19(17.1)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26(17.6)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e59(53.2)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e93(62.8)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e74(52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30(27.0)\u003c/p\u003e\n \u003cp\u003e23(15.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27(19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(2.7)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6(4.1)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.092\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIPAQ METs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003cp\u003eModerate\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(20.0)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35(16.4)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35(20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8(53.3)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e116(54.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e102(59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(20.0)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46(21.6)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31(18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(6.7)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16(7.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.341\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep History\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDifficulty in sleeping\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDifficulty in waking up\u003c/p\u003e\n \u003cp\u003eFeels unrested after waking up\u003c/p\u003e\n \u003cp\u003eWaking in middle of the night and cannot fall back to sleep\u003c/p\u003e\n \u003cp\u003eWalking in middle of the night\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6(12.0)\u003c/p\u003e\n \u003cp\u003e21(26.9)\u003c/p\u003e\n \u003cp\u003e4(8.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(9.1)\u003c/p\u003e\n \u003cp\u003e4(15.4)\u003c/p\u003e\n \u003cp\u003e37(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35(70.0)\u003c/p\u003e\n \u003cp\u003e44(56.4)\u003c/p\u003e\n \u003cp\u003e24(53.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5(45.5)\u003c/p\u003e\n \u003cp\u003e18(69.2)\u003c/p\u003e\n \u003cp\u003e100(52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7(14.0)\u003c/p\u003e\n \u003cp\u003e11(14.1)\u003c/p\u003e\n \u003cp\u003e15(33.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(36.4)\u003c/p\u003e\n \u003cp\u003e3(11.5)\u003c/p\u003e\n \u003cp\u003e40(21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(4.0)\u003c/p\u003e\n \u003cp\u003e2(2.6)\u003c/p\u003e\n \u003cp\u003e2(4.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(9.1)\u003c/p\u003e\n \u003cp\u003e1(3.8)\u003c/p\u003e\n \u003cp\u003e13(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.114\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUSUAL DIETARY SOURCE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCollege canteen\u003c/p\u003e\n \u003cp\u003eHostel\u003c/p\u003e\n \u003cp\u003eHome cooked\u003c/p\u003e\n \u003cp\u003eRestaurant\u003c/p\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(25.0)\u003c/p\u003e\n \u003cp\u003e6(17.1)\u003c/p\u003e\n \u003cp\u003e64(18.9)\u003c/p\u003e\n \u003cp\u003e2(40.0)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(50.0)\u003c/p\u003e\n \u003cp\u003e18(51.4)\u003c/p\u003e\n \u003cp\u003e190(56.0)\u003c/p\u003e\n \u003cp\u003e1(20.0)\u003c/p\u003e\n \u003cp\u003e15(88.2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e68(20.1)\u003c/p\u003e\n \u003cp\u003e9(25.7)\u003c/p\u003e\n \u003cp\u003e1(20.0)\u003c/p\u003e\n \u003cp\u003e2(11.8)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1(25.0)\u003c/p\u003e\n \u003cp\u003e2(5.7)\u003c/p\u003e\n \u003cp\u003e17(5.0)\u003c/p\u003e\n \u003cp\u003e1(20.0)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.152\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI= Body mass index; n= Frequency; %= Percentage; PA= Physical activity; IPAQ METs= International Physical Activity Questionnaire\u0026nbsp;Metabolic Equivalents Score; p-values derived from Chi-square test; p \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 3\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eASSOCIATION OF PHYSICAL ACTIVITY, SLEEP AND DEITARY HABITS TO WC\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"752\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFACTORS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;90(M)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;90(M)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;80(F)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;80(F)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP VALUE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterest in PA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNot at all interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNot really interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSomewhat interested\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVery much interested\u003c/p\u003e\n \u003cp\u003eNot sure\u003c/p\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(1.4)\u003c/p\u003e\n \u003cp\u003e25(18.0)\u003c/p\u003e\n \u003cp\u003e54(54.6)\u003c/p\u003e\n \u003cp\u003e47(38.2)\u003c/p\u003e\n \u003cp\u003e6(15.2)\u003c/p\u003e\n \u003cp\u003e5(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(2.6)\u003c/p\u003e\n \u003cp\u003e9(11.7)\u003c/p\u003e\n \u003cp\u003e30(39.0)\u003c/p\u003e\n \u003cp\u003e27(35.1)\u003c/p\u003e\n \u003cp\u003e9(11.7%)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(7.4)\u003c/p\u003e\n \u003cp\u003e7(13.0)\u003c/p\u003e\n \u003cp\u003e21(38.9)\u003c/p\u003e\n \u003cp\u003e9(16.7)\u003c/p\u003e\n \u003cp\u003e9(16.7)\u003c/p\u003e\n \u003cp\u003e4(7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12(9.2)\u003c/p\u003e\n \u003cp\u003e13(10.0)\u003c/p\u003e\n \u003cp\u003e52(40.0)\u003c/p\u003e\n \u003cp\u003e27(20.8)\u003c/p\u003e\n \u003cp\u003e20(15.4)\u003c/p\u003e\n \u003cp\u003e6(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.002*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Frequency in PA\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003eRarely\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOften\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32(23.0)\u003c/p\u003e\n \u003cp\u003e40(28.8)\u003c/p\u003e\n \u003cp\u003e67(48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15(19.5)\u003c/p\u003e\n \u003cp\u003e27(35.1)\u003c/p\u003e\n \u003cp\u003e35(45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21(38.9)\u003c/p\u003e\n \u003cp\u003e19(35.2)\u003c/p\u003e\n \u003cp\u003e14(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43(33.1)\u003c/p\u003e\n \u003cp\u003e55(42.3)\u003c/p\u003e\n \u003cp\u003e32(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIPAQ Mets\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003cp\u003eModerate\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6(4.3)\u003c/p\u003e\n \u003cp\u003e77(55.4)\u003c/p\u003e\n \u003cp\u003e56(40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(3.9)\u003c/p\u003e\n \u003cp\u003e34(44.2)\u003c/p\u003e\n \u003cp\u003e40(51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(5.6)\u003c/p\u003e\n \u003cp\u003e42(77.8)\u003c/p\u003e\n \u003cp\u003e9(16.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(2.3)\u003c/p\u003e\n \u003cp\u003e60(46.2)\u003c/p\u003e\n \u003cp\u003e67(51.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep History\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDifficulty in sleeping\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDifficulty in waking up\u003c/p\u003e\n \u003cp\u003eFeels unrested after waking up\u003c/p\u003e\n \u003cp\u003eWaking in middle of the night and cannot fall back to sleep\u003c/p\u003e\n \u003cp\u003eWalking in middle of the night\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19(13.7)\u003c/p\u003e\n \u003cp\u003e30(21.6)\u003c/p\u003e\n \u003cp\u003e15(10.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5(3.6)\u003c/p\u003e\n \u003cp\u003e3(2.2)\u003c/p\u003e\n \u003cp\u003e67(48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18(23.4)\u003c/p\u003e\n \u003cp\u003e6(7.8)\u003c/p\u003e\n \u003cp\u003e10(13.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e4(5.2)\u003c/p\u003e\n \u003cp\u003e39(50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(5.6)\u003c/p\u003e\n \u003cp\u003e13(24.1)\u003c/p\u003e\n \u003cp\u003e4(7.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(5.6)\u003c/p\u003e\n \u003cp\u003e7(13.0)\u003c/p\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10(7.7)\u003c/p\u003e\n \u003cp\u003e29(22.3)\u003c/p\u003e\n \u003cp\u003e16(12.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3(2.3)\u003c/p\u003e\n \u003cp\u003e12(9.2)\u003c/p\u003e\n \u003cp\u003e60(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.004*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUSUAL DIETARY SOURCE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCollege canteen\u003c/p\u003e\n \u003cp\u003eHostel\u003c/p\u003e\n \u003cp\u003eHome cooked\u003c/p\u003e\n \u003cp\u003eRestaurant\u003c/p\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(1.4)\u003c/p\u003e\n \u003cp\u003e9(6.4)\u003c/p\u003e\n \u003cp\u003e125(89.9)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e3(2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5(6.5)\u003c/p\u003e\n \u003cp\u003e4(5.2)\u003c/p\u003e\n \u003cp\u003e61(74.3)\u003c/p\u003e\n \u003cp\u003e2(2.6)\u003c/p\u003e\n \u003cp\u003e5(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e12(22.3)\u003c/p\u003e\n \u003cp\u003e41(72.2)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e5(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(1.6)\u003c/p\u003e\n \u003cp\u003e11(8.4)\u003c/p\u003e\n \u003cp\u003e112(86.2)\u003c/p\u003e\n \u003cp\u003e3(2.3)\u003c/p\u003e\n \u003cp\u003e2(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.009*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWC= Waist Circumference;\u003cstrong\u003e\u0026nbsp;\u0026lt;\u003c/strong\u003e90(M)= circumference less than 90 male; \u0026gt;90(M)= circumference greater than 90 male; \u0026lt;80(F)= circumference less than 80 female; \u0026gt;80(F)= circumference greater than 80 female; n= Frequency; %= Percentage; PA= Physical activity; IPAQ METs= International Physical Activity Questionnaire Metabolic Equivalents Score; p-values derived from Chi-square test;\u0026nbsp;\u003cstrong\u003e* =\u0026nbsp;\u003c/strong\u003ep \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e"},{"header":"4. RESULTS","content":"\u003cp\u003eIn this cross-sectional study, 400 college students aged 18 to 23 years participated to examine the association between body mass index (BMI), waist circumference (WC), and the level of interest in physical activity. Complete data for the variables included in the analysis were collected from students who were recruited from various departments during scheduled academic hours after excluding individuals who were ineligible, withdrew, or had incomplete anthropometric data. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic and anthropometric characteristics of the study population. Of the 400 student participants, 216 were male and 184 were female, with a mean age of 19.95 years. More than half of the students (56.5%) were within the normal BMI range, while 20% were classified as overweight and 5.3% as obese. Waist circumference findings further indicated that a notable proportion of students exhibited central adiposity, with 35% of male students exceeding the recommended cut-off of 90 cm and 30% of female students exceeding 80 cm.\u003c/p\u003e \u003cp\u003eAcross BMI categories, no lifestyle variable demonstrated a statistically significant association, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Interest in physical activity (p\u0026thinsp;=\u0026thinsp;0.304), frequency of participation (p\u0026thinsp;=\u0026thinsp;0.092), IPAQ-based activity intensity (p\u0026thinsp;=\u0026thinsp;0.341), sleep-related characteristics (p\u0026thinsp;=\u0026thinsp;0.114), and usual dietary source (p\u0026thinsp;=\u0026thinsp;0.152) all showed nonsignificant differences among underweight, normal weight, overweight, and obese students. Although minor numerical variations were present with normal-weight students generally forming the largest share and obese students contributing smaller proportions, none of these differences reached statistical significance, indicating that BMI was not meaningfully associated with any assessed lifestyle behaviour.\u003c/p\u003e \u003cp\u003eFurthermore, waist-circumference categories represented significant associations for multiple lifestyle behaviours, as summarised in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Interest in physical activity (p\u0026thinsp;=\u0026thinsp;0.002), frequency of participation (p\u0026thinsp;=\u0026thinsp;0.001), IPAQ-based activity intensity (p\u0026thinsp;=\u0026thinsp;0.001), sleep-related characteristics (p\u0026thinsp;=\u0026thinsp;0.004), and usual dietary source (p\u0026thinsp;=\u0026thinsp;0.009) all differed meaningfully between students with normal and elevated waist circumference. Participants within the lower WC ranges (\u0026lt;\u0026thinsp;90 cm for males; \u0026lt;80 cm for females) showed higher levels of physical-activity interest, more frequent participation, and greater representation in moderate and severe IPAQ intensity levels, whereas those above the WC cut-offs consistently reported lower engagement and contributed the smallest proportions to higher activity categories. Students with elevated WC also demonstrated more sleep disturbances and greater variability in dietary-location patterns. Overall, waist circumference unlike BMI showed significant associations across all assessed lifestyle variables, with higher WC consistently linked to less favourable behavioural profiles.\u003c/p\u003e"},{"header":"5. DISCUSSION","content":"\u003cp\u003eThe findings of this study indicate that although 56.5% of students fell within the normal BMI range, waist circumference (WC) assessment identified a substantially higher proportion with central obesity. This discrepancy between BMI and WC has been consistently reported in studies among Indian university populations, where BMI often underestimates adiposity while WC reveals a greater burden of abdominal fat.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e This pattern may be explained by the known tendency of South Asian young adults to accumulate visceral fat at lower BMI values, a characteristic widely documented in regional epidemiological literature.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCentral obesity was more prevalent among male students despite both genders largely exhibiting normal BMI values. While similar patterns of greater abdominal fat accumulation among young males have been reported, findings across Indian populations remain variable.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e These gender differences are likely influenced by behavioural, dietary, and lifestyle factors rather than BMI alone. Female students often demonstrate greater dietary restraint and body-shape awareness, which may help limit abdominal fat accumulation.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e In contrast, male students commonly report longer screen time, irregular sleep patterns, and lower engagement in structured physical activity, behaviours independently associated with increased central fat deposition.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAdditionally, higher consumption of calorie-dense foods, takeaway meals, and late-night snacking is more frequently reported among males, potentially contributing to higher WC-defined obesity.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Alcohol consumption and smoking, which are more prevalent among male university students, are also linked to visceral fat accumulation and adverse metabolic profiles, further explaining the higher prevalence of central obesity observed.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRegarding associations with lifestyle factors, BMI was not significantly related to interest in physical activity, frequency of participation, IPAQ MET categories, sleep patterns, or usual dietary sources. Across BMI categories, students reported similar levels of physical activity interest and engagement, indicating no clear trend between BMI and physical activity behaviour. This aligns with findings from international studies reporting weak or non-significant associations between BMI and self-reported physical activity among young adults.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e These observations may reflect limitations of questionnaire-based physical activity measures, which often capture perceived rather than physiologically meaningful activity.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Moreover, factors such as diet quality, caloric intake, sedentary behaviour, sleep patterns, and genetic or metabolic variability may exert stronger influences on BMI, diluting its association with physical activity in cross-sectional designs.\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eA notable strength of this study is the inclusion of \u0026ldquo;interest in physical activity\u0026rdquo; as a motivational measure alongside behavioural indicators, which remains relatively uncommon. By evaluating interest, frequency, and intensity of activity in conjunction with anthropometry, this study provides a more comprehensive understanding of the behavioural and psychological dimensions of physical activity. The findings highlight that motivation alone does not guarantee sufficient activity to influence BMI or adiposity, emphasizing the need for interventions that translate interest into sustained and adequately intense physical activity.\u003c/p\u003e \u003cp\u003eIn contrast to BMI, waist circumference showed significant associations with interest in physical activity, participation frequency, IPAQ MET levels, sleep disturbances, and dietary sources. Students with higher WC demonstrated lower interest and participation in physical activity, along with greater representation in irregular or sporadic activity patterns despite similar MET totals, likely reflecting sporadic rather than sustained activity patterns. Poor sleep quality and unfavourable dietary habits were also more common among those with higher WC, suggesting clustering of lifestyle behaviours linked to central adiposity. These findings support evidence indicating WC as a superior behavioural and metabolic indicator compared to BMI.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLiterature suggests that WC reflects not only visceral fat accumulation but also behavioural characteristics related to physical activity tolerance, motivation, and lifestyle regularity. Individuals with higher WC often experience greater perceived exertion, reduced exercise tolerance, and lower psychological readiness for activity, which may limit continuous or vigorous physical activity despite similar total reported activity levels.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e Suboptimal dietary habits and inconsistent sleep further reinforce a reciprocal cycle in which lifestyle behaviours promote central fat accumulation, which in turn constrains lifestyle capacity.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e By integrating anthropometric, behavioural, and lifestyle assessments, this study underscores WC as a more sensitive indicator of health risk in young adults than BMI.\u003c/p\u003e \u003cp\u003eThe strengths of this study include its multidimensional assessment of lifestyle factors using validated questionnaires and the application of gender-specific WC cut-offs, enhancing clinical relevance. However, the cross-sectional design limits causal inference, and self-reported measures may introduce recall or social-desirability bias. Dietary assessment lacked detailed nutrient quantification, and more advanced body composition measures were not included.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e Future research should employ objective physical activity monitoring, structured sleep assessments, detailed nutritional profiling, and advanced body composition analyses to better elucidate the interplay between lifestyle behaviours and adiposity in young adults.\u003c/p\u003e"},{"header":"6. CONCLUSION","content":"\u003cp\u003eThe association between waist circumference (WC) and lifestyle behaviours among Indian college students showed that higher WC was consistently linked with lower interest in physical activity, reduced participation frequency, irregular sleep patterns, and less favourable dietary habits. In contrast, BMI did not show a clear association with these behaviours across categories. The impact of central adiposity on lifestyle behaviours was more pronounced in male students than in female students, highlighting the relevance of WC as a sensitive indicator for behavioural and metabolic risk in young adults. These results provide a reference for promoting healthier lifestyle behaviours among college students, with a focus on enhancing interest in physical activity. Interventions should prioritize educational and awareness programs that motivate students to engage in regular exercise, improve sleep routines, and adopt balanced dietary habits. Encouraging structured physical activity at least three times per week, integrating movement into daily life, and fostering supportive environments may help maintain healthy body composition and stimulate sustained engagement in physical activity. Future efforts should target both behavioural motivation and practical opportunities to translate interest into consistent, beneficial habits.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI: Body Mass Index\u003c/p\u003e\n\u003cp\u003eWC: Waist Circumference\u003c/p\u003e\n\u003cp\u003eIPAQ- SF: International Physical Activity Questionnaire-Short Form\u003c/p\u003e\n\u003cp\u003eMET: Metabolic Equivalents Score\u003c/p\u003e\n\u003cp\u003ePA: Physical Activity\u003c/p\u003e\n\u003cp\u003eYPAQ: Youth Physical Activity Questionnaire\u003c/p\u003e\n\u003cp\u003eNCDs: Non-Communicable Diseases\u003c/p\u003e"},{"header":"STATEMENTS AND DECLARATIONS","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach participant read and signed a written informed consent form prior to enrollment. The study protocol was approved by the Institutional Ethics Committee of SRM Institute of Science and Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eSelf-funded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM Anbupriya :Provided overall conceptual guidance, supervised the study design and methodology, critically reviewed the analysis and interpretation of findings, and approved the final version of the manuscript. A Kamaleswari: Conceived the study design, conducted participant recruitment and data collection, performed statistical analysis, and contributed to interpretation of the results\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eKarthikeyan S and Nandhini S: Drafted the initial manuscript, organized the results and discussion sections, performed literature review, and revised the manuscript based on critical feedback.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: The authors would like to thank the students for their participation in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCaspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public health reports. 1985 Mar;100(2):126.\u003c/li\u003e\n \u003cli\u003eHaverkamp BF, Oosterlaan J, Königs M, Hartman E. Physical fitness, cognitive functioning and academic achievement in healthy adolescents. Psychology of Sport and Exercise. 2021 Nov 1;57:102060.\u003c/li\u003e\n \u003cli\u003eAnjana RM, Pradeepa R, Das AK, Deepa M, Bhansali A, Joshi SR, Joshi PP, Dhandhania VK, Rao PV, Sudha V, Subashini R. Physical activity and inactivity patterns in India–results from the ICMR-INDIAB study (Phase-1)[ICMR-INDIAB-5]. International Journal of Behavioral Nutrition and Physical Activity. 2014 Feb 26;11(1):26.\u003c/li\u003e\n \u003cli\u003eNewtonraj A, Murugan N, Singh Z, Chauhan RC, Velavan A, Mani M. Factors associated with physical inactivity among adult urban population of Puducherry, India: a population based cross-sectional study. Journal of clinical and diagnostic research: JCDR. 2017 May 1;11(5):LC15.\u003c/li\u003e\n \u003cli\u003eGuthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1· 9 million participants. The lancet global health. 2018 Oct 1;6(10):e1077-86.\u003c/li\u003e\n \u003cli\u003eKeating XD, Guan J, Piñero JC, Bridges DM. A meta-analysis of college students' physical activity behaviors. Journal of American college health. 2005 Sep 1;54(2):116-26.\u003c/li\u003e\n \u003cli\u003eVenkatrao M, Nagarathna R, Majumdar V, Patil SS, Rathi S, Nagendra H. Prevalence of obesity in India and its neurological implications: a multifactor analysis of a nationwide cross-sectional study. Annals of Neurosciences. 2020 Jul;27(3-4):153-61.\u003c/li\u003e\n \u003cli\u003eLim SH, Lee T, Oh J, Hwang KH, Choi EH, Cha SK. Waist Circumference as an Independent Marker of Insulin Resistance: Evidence from a Nationwide Korean Population Study. Journal of Clinical Medicine. 2025 Nov 10;14(22):7957.\u003c/li\u003e\n \u003cli\u003eWildman RP, Gu D, Reynolds K, Duan X, Wu X, He J. Are waist circumference and body mass index independently associated with cardiovascular disease risk in Chinese adults?. The American journal of clinical nutrition. 2005 Dec 1;82(6):1195-202.\u003c/li\u003e\n \u003cli\u003eIips IC. National family health survey (NFHS-5): 2019-21 India. Mumbai: International Institute for Population Sciences (IIPS). 2021.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. \u003cem\u003eBody mass index – BMI: BMI classifications\u003c/em\u003e [Internet]. Geneva: WHO; [cited 2025 Feb 24]. Available from: https://www.who.int/data/gho/data/themes/theme-details/GHO/body-mass-index-(bmi)\u003c/li\u003e\n \u003cli\u003eMisra A, Vikram NK. Clinical and pathophysiological consequences of abdominal adiposity and abdominal adipose tissue depots. Nutrition. 2003 May 1;19(5):457-66.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. WHO STEPS surveillance manual: the WHO STEPwise approach to chronic disease risk factor surveillance/Noncommunicable Diseases and Mental Health, World Health Organization. InWHO STEPS surveillance manual: the WHO STEPwise approach to chronic disease risk factor surveillance/Noncommunicable Diseases and Mental Health, World Health Organization 2005.\u003c/li\u003e\n \u003cli\u003eLohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual.\u003c/li\u003e\n \u003cli\u003eMisra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, Joshi SR, Sadikot S, Gupta R, Gulati S, Munjal YP. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. Japi. 2009 Feb;57(2):163-70.\u003c/li\u003e\n \u003cli\u003eCraig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund UL, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Medicine \u0026amp; science in sports \u0026amp; exercise. 2003 Aug 1;35(8):1381-95.\u003c/li\u003e\n \u003cli\u003eIPAQ Research Committee. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)-short and long forms. http://www. ipaq. ki. se/scoring. pdf. 2005.\u003c/li\u003e\n \u003cli\u003eBrooke HL, Corder K, Griffin SJ, van Sluijs EM. Physical activity maintenance in the transition to adolescence: a longitudinal study of the roles of sport and lifestyle activities in British youth. PloS one. 2014 Feb 12;9(2):e89028.\u003c/li\u003e\n \u003cli\u003eMcCrorie PR, Perez A, Ellaway A. The validity of the Youth Physical Activity Questionnaire in 12–13-year-old Scottish adolescents. BMJ Open Sport \u0026amp; Exercise Medicine. 2017 Jan 6;2(1).\u003c/li\u003e\n \u003cli\u003eCorder K, Van Sluijs EM, Wright A, Whincup P, Wareham NJ, Ekelund U. Is it possible to assess free-living physical activity and energy expenditure in young people by self-report?. The American journal of clinical nutrition. 2009 Mar 1;89(3):862-70.\u003c/li\u003e\n \u003cli\u003eRolstad S, Adler J, Rydén A. Response burden and questionnaire length: is shorter better? A review and meta-analysis. Value in Health. 2011 Dec 1;14(8):1101-8.\u003c/li\u003e\n \u003cli\u003eGalesic M, Bosnjak M. Effects of questionnaire length on participation and indicators of response quality in a web survey. Public opinion quarterly. 2009 Jan 1;73(2):349-60.\u003c/li\u003e\n \u003cli\u003eFan W, Yan Z. Factors affecting response rates of the web survey: A systematic review. Computers in human behavior. 2010 Mar 1;26(2):132-9.\u003c/li\u003e\n \u003cli\u003eEdwards PJ, Roberts I, Clarke MJ, DiGuiseppi C, Woolf B, Perkins C. Methods to increase response to postal and electronic questionnaires. Cochrane database of systematic reviews. 2023(11).\u003c/li\u003e\n \u003cli\u003eTourangeau R, Rips LJ, Rasinski K. The psychology of survey response.\u003c/li\u003e\n \u003cli\u003eBowling A. Mode of questionnaire administration can have serious effects on data quality. Journal of public health. 2005 Sep 1;27(3):281-91.\u003c/li\u003e\n \u003cli\u003eLaska MN, Larson NI, Neumark-Sztainer D, Story M. Dietary patterns and home food availability during emerging adulthood: do they differ by living situation?. Public health nutrition. 2010 Feb;13(2):222-8.\u003c/li\u003e\n \u003cli\u003eSlotnick MJ, Ansari S, Parnarouskis L, Gearhardt AN, Wolfson JA, Leung CW. Persistent and Changing Food Insecurity Among Students at a Midwestern University is Associated With Behavioral and Mental Health Outcomes. American Journal of Health Promotion. 2024 May;38(4):483-91.\u003c/li\u003e\n \u003cli\u003eBetancourt-Núñez A, Díaz R, Nava-Amante PA, Bernal-Orozco MF, Díaz-López A, González Palacios A, Márquez-Sandoval F, Velarde-Camaqui D, Vizmanos B. Beyond the Classroom: The Influence of Food Insecurity, Mental Health, and Sleep Quality on University Students’ Academic Performance. Foods. 2024 Aug 11;13(16):2508.\u003c/li\u003e\n \u003cli\u003eBuysse D. The Pittsburgh sleep quality index (PSQI). An instrument for psychiatric practice and research. Psychiatry Res.. 1988;28:193-213.\u003c/li\u003e\n \u003cli\u003eLund HG, Reider BD, Whiting AB, Prichard JR. Sleep patterns and predictors of disturbed sleep in a large population of college students. Journal of adolescent health. 2010 Feb 1;46(2):124-32.\u003c/li\u003e\n \u003cli\u003eHershner SD, Chervin RD. Causes and consequences of sleepiness among college students. Nature and science of sleep. 2014 Jun 23:73-84.\u003c/li\u003e\n \u003cli\u003eRhodes RE, Smith NE. Personality correlates of physical activity: a review and meta-analysis. British journal of sports medicine. 2006 Dec 1;40(12):958-65.\u003c/li\u003e\n \u003cli\u003eDishman RK, Sallis JF, Orenstein DR. The determinants of physical activity and exercise. Public health reports. 1985 Mar;100(2):158.\u003c/li\u003e\n \u003cli\u003eWilson PM, Rodgers WM, Fraser SN. Examining the psychometric properties of the behavioral regulation in exercise questionnaire. Measurement in physical education and exercise science. 2002 Mar 1;6(1):1-21.\u003c/li\u003e\n \u003cli\u003ePengpid S, Peltzer K. Prevalence of overweight/obesity and central obesity and its associated factors among a sample of university students in India. Obesity research \u0026amp; clinical practice. 2014 Nov 1;8(6):e558-70.\u003c/li\u003e\n \u003cli\u003eNawab T, Khan Z, Khan IM, Ansari MA. Central obesity is a burden even in normal weight adolescents of a non-metropolitan Indian City: A case for alarm and action for prevention and control. Journal of Family Medicine and Primary Care. 2025 Jan 1;14(1):283-9.\u003c/li\u003e\n \u003cli\u003eBehera S, Mishra A, Esther Sr A, Sahoo A. Tailoring body mass index for prediction of obesity in young adults: A multi-centric study on MBBS students of Southeast India. Cureus. 2021 Jan 8;13(1).\u003c/li\u003e\n \u003cli\u003eMisra A, Khurana L. Obesity and the metabolic syndrome in developing countries. The Journal of Clinical Endocrinology \u0026amp; Metabolism. 2008 Nov 1;93(11_supplement_1):s9-30.\u003c/li\u003e\n \u003cli\u003eKrishnan B, Kharde A. Assessment of Obesity using Anthropometric Markers among University Students. Current Research in Nutrition and Food Science. 2021 Apr 1;9(1):211.\u003c/li\u003e\n \u003cli\u003eMoitra M, Desai K, Chaudhari V. Perceived body image among young girls residing in urban slums and reality: A cross sectional study. Natl J Community Med. 2019;10:579-84.\u003c/li\u003e\n \u003cli\u003eMoitra P, Madan J, Verma P. Independent and combined influences of physical activity, screen time, and sleep quality on adiposity indicators in Indian adolescents. BMC Public Health. 2021 Nov 15;21(1):2093.\u003c/li\u003e\n \u003cli\u003eYadav G, Bodat S, Siwach I, Sachdeva K, Chuahan N. Physical activity and its relation with body composition among undergraduate medical students in Delhi: a cross sectional study. International Journal of Community Medicine and Public Health. 2020 Nov;7(11):4530.\u003c/li\u003e\n \u003cli\u003eFrancis DK, Van den Broeck J, Younger N, McFarlane S, Rudder K, Gordon-Strachan G, Grant A, Johnson A, Tulloch-Reid M, Wilks R. Fast-food and sweetened beverage consumption: association with overweight and high waist circumference in adolescents. Public health nutrition. 2009 Aug;12(8):1106-14.\u003c/li\u003e\n \u003cli\u003eGanpule A, Dubey M, Pandey H, Venkateshmurthy NS, Green R, Brown KA, Maddury AP, Khatkar R, Jarhyan P, Prabhakaran D, Mohan S. Snacking behavior and association with metabolic risk factors in adults from north and south India. The Journal of nutrition. 2023 Feb 1;153(2):523-31.\u003c/li\u003e\n \u003cli\u003ePark KY, Park HK, Hwang HS. Relationship between abdominal obesity and alcohol drinking pattern in normal-weight, middle-aged adults: the Korea National Health and Nutrition Examination Survey 2008–2013. Public Health Nutrition. 2017 Aug;20(12):2192-200.\u003c/li\u003e\n \u003cli\u003eSumi M, Hisamatsu T, Fujiyoshi A, Kadota A, Miyagawa N, Kondo K, Kadowaki S, Suzuki S, Torii S, Zaid M, Sato A. Association of alcohol consumption with fat deposition in a community-based sample of Japanese men: the Shiga Epidemiological Study of Subclinical Atherosclerosis (SESSA). Journal of epidemiology. 2019 Jun 5;29(6):205-12.\u003c/li\u003e\n \u003cli\u003eYousif MM, Kaddam LA, Humeda HS. Correlation between physical activity, eating behavior and obesity among Sudanese medical students Sudan. BMC nutrition. 2019 Feb 6;5(1):6.\u003c/li\u003e\n \u003cli\u003eLiu L, Liu Y, Zhang T, Luo J. Study on the influence of levels of physical activity and socio-economic conditions on body mass index of adolescents. International Health. 2025 Jul;17(4):470-80.\u003c/li\u003e\n \u003cli\u003eLee YY, Kamarudin KS, Wan Muda WA. Associations between self-reported and objectively measured physical activity and overweight/obesity among adults in Kota Bharu and Penang, Malaysia. BMC Public Health. 2019 May 22;19(1):621.\u003c/li\u003e\n \u003cli\u003eAYDOĞAN K, KOSTANOĞLU A, TÖRPÜ GC. Effect of Body Mass Index on Balance, Trunk Muscle Endurance, Functional Mobility and, Physical Activity in College Students. Bezmialem Science. 2024 Nov 4.\u003c/li\u003e\n \u003cli\u003ePeterson NE, Sirard JR, Kulbok PA, DeBoer MD, Erickson JM. Sedentary behavior and physical activity of young adult university students. Research in nursing \u0026amp; health. 2018 Feb;41(1):30-8.\u003c/li\u003e\n \u003cli\u003eCarneiro-Barrera A, Amaro-Gahete FJ, Acosta FM, Ruiz JR. Body composition impact on sleep in young adults: the mediating role of sedentariness, physical activity, and diet. Journal of Clinical medicine. 2020 May 21;9(5):1560.\u003c/li\u003e\n \u003cli\u003eJayawardana NW, Jayalath WA, Madhujith WM, Ralapanawa U, Jayasekera RS, Alagiyawanna SA, Bandara AM, Kalupahana NS. Lifestyle factors associated with obesity in a cohort of males in the central province of Sri Lanka: a cross-sectional descriptive study. BMC public health. 2017 Jan 5;17(1):27.\u003c/li\u003e\n \u003cli\u003eDagan SS, Segev S, Novikov I, Dankner R. Waist circumference vs body mass index in association with cardiorespiratory fitness in healthy men and women: a cross sectional analysis of 403 subjects. Nutrition journal. 2013 Jan 15;12(1):12.\u003c/li\u003e\n \u003cli\u003eEkelund U, Besson H, Luan JA, May AM, Sharp SJ, Brage S, Travier N, Agudo A, Slimani N, Rinaldi S, Jenab M. Physical activity and gain in abdominal adiposity and body weight: prospective cohort study in 288,498 men and women. The American journal of clinical nutrition. 2011 Apr 1;93(4):826-35.\u003c/li\u003e\n \u003cli\u003eJansen EC, Dunietz GL, Tsimpanouli ME, Guyer HM, Shannon C, Hershner SD, O’Brien LM, Baylin A. Sleep, diet, and cardiometabolic health investigations: a systematic review of analytic strategies. Current nutrition reports. 2018 Dec;7(4):235-58.\u003c/li\u003e\n \u003cli\u003eBorga M, West J, Bell JD, Harvey NC, Romu T, Heymsfield SB, Dahlqvist Leinhard O. Advanced body composition assessment: from body mass index to body composition profiling. Journal of Investigative Medicine. 2018 Jun;66(5):1-9.\u003c/li\u003e\n\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":"BMI, waist circumference, physical activity, sleep history, dietary source, college students","lastPublishedDoi":"10.21203/rs.3.rs-8714032/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8714032/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eBody mass index (BMI) and waist circumference (WC) are widely used anthropometric indicators for assessing obesity risk in young adults. However, their relationship with behavioural variables such as interest in physical activity, activity frequency, intensity, sleep habits, and dietary history remains unclear in Indian university populations. This study examined the association between BMI, WC, and selected lifestyle behaviours among college students, with emphasis on gender differences in central obesity.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted among 400 university students aged 18\u0026ndash;23 years. Anthropometric measurements included BMI and WC, classified using standard cut-offs. Physical activity frequency was assessed using the Youth Physical Activity Questionnaire, and activity intensity using the International Physical Activity Questionnaire (short form). Demographic data, interest in physical activity, usual dietary sources, and sleep history were collected using a self-reported questionnaire. Associations were analysed using descriptive statistics and chi-square tests.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eOf the participants, 56.5% had normal BMI, 20% were overweight, 5.3% were obese, and 18.3% were underweight. Based on WC, 65% met the criteria for central obesity. BMI showed no significant association with interest in physical activity, participation frequency, MET-based intensity, sleep patterns, or dietary sources (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In contrast, WC showed significant associations with interest in physical activity (p\u0026thinsp;=\u0026thinsp;0.017), participation frequency (p\u0026thinsp;=\u0026thinsp;0.011), MET intensity (p\u0026thinsp;=\u0026thinsp;0.009), sleep patterns (p\u0026thinsp;=\u0026thinsp;0.025), and dietary sources (p\u0026thinsp;=\u0026thinsp;0.034).\u003c/p\u003e\u003ch2\u003eCONCLUSION\u003c/h2\u003e \u003cp\u003eAlthough most students had normal BMI, WC identified a substantially higher prevalence of central obesity, particularly among males. Higher WC was associated with lower physical activity engagement, irregular sleep, and calorie-dense dietary patterns. Targeted lifestyle interventions may help reduce early central adiposity in university students.\u003c/p\u003e","manuscriptTitle":"Association Between Bmi, Waist Circumference, and Level of Interest in Physical Activity: A Cross-sectional Study Among College Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 16:42:08","doi":"10.21203/rs.3.rs-8714032/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":"0c836dbd-c858-41be-9b72-cadfa128a00c","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T03:24:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 16:42:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8714032","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8714032","identity":"rs-8714032","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}