Abstract
Introduction:
Young adulthood is a critical period for the establishment of lifelong health behaviours. However, increasing sedentary lifestyles, suboptimal dietary patterns, and weight-related body image concerns contribute to the growing burden of obesity in this age group. A comprehensive and culturally sensitive assessment tool is needed to capture these multidimensional factors. This study aimed to develop and psychometrically validate a questionnaire assessing lifestyle behaviours, weight-related body image concerns, and past weight management strategies among young adults (YAs).
Methods:
A mixed-method design was employed. Item generation was informed by literature review and focus group discussions, followed by expert review for content validity and pilot testing for face validity. Construct validity was assessed using exploratory factor analysis (EFA; n = 302) and confirmatory factor analysis (CFA; n = 151) within a structural equation modelling framework. Internal consistency was evaluated using Cronbach’s alpha, and test–retest reliability (n = 102) was assessed using intraclass correlation coefficients (ICC) with 95% confidence intervals.
Results:
The final questionnaire comprised 30 items across three domains: lifestyle and associated barriers (17 items), weight-related body image concerns (6 items), and past weight management (7 items). Factor analyses supported a three-domain structure with satisfactory model fit indices. Internal consistency ranged from 0.72 to 0.86 across domains. Test–retest reliability demonstrated high stability (ICC range: 0.951–0.970).
Conclusion:
The developed questionnaire demonstrates satisfactory psychometric properties and may serve as a practical tool for assessing obesity-related behavioural and psychosocial factors among young adults in clinical and research settings.
Keywords: Body image, lifestyle, obesity, scale, tool, young adult
INTRODUCTION
Young adulthood is a critical developmental stage during which long-term health behaviours are established. However, this period is increasingly marked by sedentary lifestyles, irregular dietary patterns, and heightened weight-related body image concerns.[1] The rising prevalence of overweight and obesity among young adults (YAs) presents significant public health challenges. Projections suggest a substantial increase in obesity burden globally, including in India, with implications for cardiometabolic health, psychological well-being, and healthcare systems.[2,3,4,5]
Obesity in this age group is influenced by a complex interplay of behavioural and psychosocial factors. Dietary practices, physical inactivity, and environmental exposures contribute to weight gain, while body image dissatisfaction and social pressures may shape eating behaviours and engagement in weight management efforts.[6,7,8,9,10] Despite this multidimensional nature, existing instruments often assess isolated constructs such as diet, physical activity, or body image independently. This fragmented approach increases respondent burden and may limit applicability in clinical and community settings, particularly in resource-constrained environments.[11,12]
Therefore, there is a need for an integrated and culturally sensitive assessment tool tailored to young adults. The objectives of the present study were: (i) to develop a comprehensive questionnaire integrating lifestyle behaviours, weight-related body image concerns, and past weight management strategies; and (ii) to examine its psychometric properties, including construct validity, internal consistency, and test–retest reliability. Such a tool may facilitate holistic assessment, and support targeted interventions in clinical and public health contexts.
MATERIALS AND METHODS
Study design
This study employed a mixed-method design for the development and psychometric validation of a comprehensive obesity assessment questionnaire. The development team comprised a multidisciplinary group of nutritionists, general physicians, psychiatrists, psychologists, and statisticians. The team was actively involved in all phases of questionnaire development, including construct conceptualization, item generation, validation procedures, and finalization of the instrument.
Sampling and participants
The sample size for exploratory factor analysis (EFA) was determined using the subject-to-item ratio approach, with a recommended ratio of 5–10 participants per item. Based on an initial pool of 58 items, the estimated sample size ranged from 190 to 380 participants.[13]
Participants aged 18–30 years with a body mass index (BMI) ≥23 kg/m² were eligible for inclusion. The BMI cut-off was based on the World Health Organization (WHO) recommendations for Asian populations, where BMI ≥ 23 kg/m² is classified as overweight and ≥25 kg/m² as obesity due to higher metabolic risk at lower BMI thresholds in Asian individuals.[14]
A total of 302 participants were included in the development phase for EFA. For confirmatory factor analysis (CFA) and assessment of dimensionality and discriminant validity, an independent sample of 151 participants was recruited. To evaluate test–retest reliability, a subset of 102 participants completed the questionnaire again after a 1-week interval. The one-week interval was selected to minimize recall bias, while ensuring stability of the measured constructs.
Participants were recruited using purposive sampling to ensure socio-demographic diversity. Residential classification (metropolitan, city, town, and village) was defined according to the Census of India 2011 rural–urban criteria. Metropolitan areas were defined as urban agglomerations with a population ≥1 million. Cities referred to statutory urban local bodies with populations below 1 million. Towns were defined as census towns meeting population (≥5,000), occupational, and density criteria. Villages were classified as rural administrative units not meeting statutory or census urban criteria.[15]
Item generation and construct development
Literature review
A comprehensive literature review was conducted to identify validated instruments assessing lifestyle behaviours, body image concerns, and past weight management practices. The following MeSH-based search strategy was used: (“Body Weight”[MeSH] OR “Obesity”[MeSH]) AND (“Health Behavior”[MeSH] OR “Lifestyle”[MeSH]) AND (“Body Image”[MeSH]) AND (“Young Adult”[MeSH]).
Searches were conducted in PubMed and other relevant databases. Constructs from identified scales informed the initial item pool.
Focus group discussions (FGDs)
Six focus group discussions were conducted with 30 young adults representing diverse socioeconomic and cultural backgrounds. Participants shared experiences, perceptions, and challenges related to weight management and lifestyle behaviours.[16] Thematic analysis was performed to identify recurring themes, which informed item refinement and contextual adaptation.
Expert review
A panel of 10 subject matter experts from nutrition, medicine, clinical psychology, and metabolic research reviewed the draft questionnaire. Items were evaluated for clarity, relevance, cultural appropriateness, and comprehensiveness. Iterative revisions were made based on consensus feedback.
Pretesting
The revised questionnaire was pilot tested among 30 participants. Cognitive interviews were conducted to assess comprehension, clarity, and interpretability. Minor modifications were implemented based on participant feedback.
Validation procedures
Face and content validity
Content validity was assessed using both qualitative and quantitative approaches. Experts evaluated each item for necessity, relevance, clarity, and simplicity.
The content validity ratio (CVR) was calculated using Lawshe’s method, with items retained based on established cut-off criteria. The content validity index (CVI) was computed using a four-point rating scale. Items with CVI < 0.70 were removed, while those between 0.70 and 0.79 were revised. Iterative expert review ensured conceptual clarity and cultural relevance.
Exploratory factor analysis (EFA)
EFA was conducted using data from 302 participants to identify underlying factor structure and refine item groupings. Sampling adequacy was assessed using the Kaiser–Meyer–Olkin (KMO) test, and Bartlett’s test of sphericity confirmed suitability for factor analysis. Principal axis factoring with varimax rotation was performed. Items with factor loadings <0.40 or significant cross-loadings were removed through iterative refinement.
Confirmatory factor analysis (CFA)
CFA was performed on an independent sample (n = 151) using structural equation modelling (SEM) to assess dimensionality and discriminant validity. Model fit was evaluated using the Chi-square statistic, comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). Model adequacy was interpreted using conventional cut-off values (CFI/TLI ≥ 0.90–0.95; RMSEA ≤ 0.08; SRMR ≤ 0.08).
Reliability assessment
Internal consistency was evaluated using Cronbach’s alpha, with values ≥0.70 considered acceptable. Test–retest reliability was assessed using intraclass correlation coefficients (ICC) with 95% confidence intervals.
Scoring
The scoring methodology was developed in collaboration with seven subject matter experts, including nutritionists, psychiatrists, and metabolic specialists. Using the development dataset, unadjusted odds ratios were calculated, treating participants’ responses as categorical variables and BMI as a continuous variable. The odds ratio range (0.9–1.1) informed the assignment of equal weightage (1) to each item, organized in ascending order.
Responses are rated on a five-point Likert scale:
Dietary Behaviour (Item C1-C5): Daily (0), 3–4 times/week (1), 1–2 times/week (2), Sometimes (3), Rarely/Never (4).
Physical Activity (Item C11-12): Duration and intensity are similarly rated.
Barriers to a Healthy Lifestyle (Item C6-C10, C13-C17): Strongly agree (0), Agree (1), Neutral (2), Disagree (3), Strongly disagree (4).
The total score ranges from 0 to 68, where a higher score reflects a healthier lifestyle. This scale comprehensively evaluates diet, physical activity, and barriers to adopting a healthy lifestyle.
Weight-related body image
The initial questionnaire employed a five-point Likert scale (‘Strongly disagree’ to ‘Strongly agree’), Item B1-B6. The final version uses a three-point scale:
Never (0)
Sometimes (1)
Often (2).
Scores range from 0 to 12, with categories indicating the severity of body image concerns:
1–4: Mild issues (minimal impact).
5–8: Moderate issues (noticeable distortion).
9–12: Severe issues (significant and distressing distortion).
Past weight management
Responses are rated as Always, Frequently, Occasionally, Seldom, and Never, reflecting the frequency of weight management behaviours. Item scoring was directionally aligned such that higher scores reflect healthier and evidence-based practices. Adaptive behaviors (Item no. A1-A4, A7) were scored positively, whereas maladaptive practices (Item no. A5, A6) were reverse-scored to ensure consistency in interpretation.
Scores are to be calculated for each domain, with higher scores indicating healthier behaviours or fewer concerns. Domain-specific and total scores facilitate targeted analysis and interventions.
Ethical approval
The study was ethically approved by the Institute Ethics Committee of the All-India Institute of Medical Sciences, New Delhi, with approval letter number IECPG-595/20.09.2023, OT-06/25.04.2024, dated 26th April 2024. Written informed consent was obtained from all participants prior to their inclusion in the study, including consent for the use of their data for research and educational purposes. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments.
RESULTS
Participant characteristics
The development sample included 302 participants (mean age 23.4 ± 3.5 years), with a balanced gender distribution (56% female, 44% male). Participants represented diverse socioeconomic backgrounds, with 44% from upper-income groups and 56% from middle- and lower-income groups. BMI distribution included 38.4% overweight, 33.1% obese I, and 28.5% obese II categories. The detailed participant characteristics across various phases of questionnaire development and validation are given in Table 1.
Table 1.
Demographic characteristics of the participants across various phases of the study
| Characteristics | Development Phase (n=302) | Validation Phase (n=151) | Test-Retest Phase (n=102) |
|---|---|---|---|
| Gender | |||
| Male | 133 (44) | 62 (41.06) | 39 (37.86) |
| Female | 169 (56) | 89 (58.94) | 64 (62.14) |
| Socio-economic status | |||
| Upper | 134 (44.3) | 27 (17.88) | 21 (20.38) |
| Middle | 112 (37.08) | 86 (56.95) | 56 (54.36) |
| Lower | 56 (18.5) | 38 (25.16) | 26 (25.24) |
| Education | |||
| Postgraduate | 77 (25.5) | 26 (17.22) | 28 (27.18) |
| Graduate | 137 (45.4) | 78 (51.66) | 48 (46.60) |
| Intermediate | 53 (17.6) | 22 (14.57) | 10 (9.71) |
| Matriculate | 27 (8.9) | 19 (12.58) | 13 (12.62) |
| Middle-school certificate | 08 (2.6) | 6 (3.97) | 4 (3.88) |
| Marital Status | |||
| Married | 34 (11.25) | 105 (69.54) | 88 (85.44) |
| Single | 268 (88.75) | 46 (30.46) | 15 (14.56) |
| Place of Residence | |||
| Metropolitan | 196 (64.9) | 109 (72.18) | 45 (43.69) |
| Town | 2 (0.6) | 13 (8.60) | 0 (0.00) |
| City | 104 (34.5) | 29 (19.20) | 58 (56.31) |
| Anthropometric Parameters | |||
| Body Mass Index (BMI) | |||
| Overweight (23.0 kg/m2–24.9 kg/m2) Obese I ((≥25.0 kg/m2–27.9 kg/m2) Obese II (≥28.0 kg/m2) |
116 (38.4) 100 (33.1) 86 (28.5) |
08 (5.29) 44 (29.13) 99 (65.56) |
31 (30.09) 31 (30.09) 41 (39.80) |
Values are presented as mean±standard deviation or number (frequency%)
Development of the questionnaire
The comprehensive search through relevant MeSH terms yielded in 39 relevant full-text articles, from which 42 items were generated. Additionally, the FGDs contributed to 26 additional items and the construct of the questionnaire comprised of 58 items. After the various phases of development and validation [Table 2], the final questionnaire includes 30 items across three domains:
Table 2.
Summary of various of questionnaire development and validation
| Phase Information | Content Validity (Phase 2) | Face Validity (Phase 3) | Construct Validity (Phase 4) | Test-Retest Reliability (Phase 5) | Test of Dimensionality and Discriminant Validity (Phase 6) |
|---|---|---|---|---|---|
| Study Activity | Subject Matter Experts (SME) review | Pilot Testing | Exploratory Factor Analysis (EFA) with varimax rotation | Reliability Testing | Confirmatory Factor Analysis |
| Participants | 10 | 30 | 302 | 102 | 151 |
| Summary | Two rounds of SME review, 12+8 items removed | 10 items were reworded or reformed based on the ratings | 19 items were removed following multiple rounds of EFA | Re-Administration of the questionnaire on the subset of the same participants, one week apart | 09 additional items were removed to converge the model across various domains |
| Locations/Sessions | Academic Block | Out-patient department | Out-patient department | Out-patient department | Out-patient department |
| Revised Questionnaire Version, items | V1 n=58 |
V2 n=58 |
V3 n=39 |
V3 n=39 |
V4 n=30 |
Lifestyle and Associated Barriers (17 items): Assesses meal patterns, food choices, mindful eating behaviours and exercise frequency, intensity, and sedentary behaviours Example items include frequency of meal skipping and consumption of high-fat, high-sugar foods, time spent in physical activity and barriers to regular exercise. Amongst barriers, it contains items like psychological, social, and environmental obstacles, such as stress, peer influence, and lack of resources.
Weight-related Body Image Concerns (06 items): Measures self-perception, social judgment, and emotional impact related to body weight. Example items address feelings of embarrassment, societal judgment, self-esteem, and loneliness.
Past Weight Management (07 items): Evaluates previous strategies adapted for weight loss, Example items include lifestyle changes, indulgences into fad diets and trends.
Validation of the questionnaire
Exploratory Factor Analysis: EFA revealed a three-domain structure, with factor loadings >0.4 for all retained items. Items with low or cross-loadings were removed during iterative refinement. The final items with their respective factor loading are given in Supplementary Table 1.
Internal Consistency: Cronbach’s alpha values were 0.72 for lifestyle and associated barriers, 0.86 for body image concerns, and 0.83 for past weight management, indicating good internal consistency of the items. The detailed scale statistics are summarised in Table 3.
Test-Retest Reliability: The ICCs as shown in Supplementary Table 2 ranged from 0.970 (95% Confidence Interval [CI]: 0.958–0.981) for lifestyle, 0.957 (95% CI: 0.945–0.968) for body image concerns, and 0.951 (95% CI: 0.939–0.963) for past weight management.
Confirmatory Factor Analysis: Consistent with the EFA results, all three-domains were refined based on the factor loadings of the indicator items. For the ‘Lifestyle and Associated Barriers’ domain, 17 items were found to have a statistically significant contribution. In the ‘Body Image’ domain, six items converged, while seven items in the ‘Past Weight Management’ domain effectively captured key aspects of their respective latent factors. Consequently, these factors were retained in the final model, as the model fit indices indicated a ‘good fit’. The detailed results of the model fit indices are given in Supplementary Table 3.
Supplementary Table 1.
Factor loading after exploratory factor analysis
| Question | I | II | III | IV | V | VI | VII |
|---|---|---|---|---|---|---|---|
| Q5 | 0.651 | ||||||
| Q7 | 0.464 | ||||||
| Q8 | 0.844 | ||||||
| Q9 | 0.40 | ||||||
| Q10 | 0.762 | ||||||
| Q11 | 0.571 | ||||||
| Q13 | 0.72 | ||||||
| Q14 | 0.701 | ||||||
| Q15 | 0.829 | ||||||
| Q16 | 0.726 | ||||||
| Q17 | 0.849 | ||||||
| Q18 | 0.702 | ||||||
| Q19 | 0.846 | ||||||
| Q21 | 0.708 | ||||||
| Q24 | 0.773 | ||||||
| Q25 | 0.682 | ||||||
| Q26 | 0.584 | ||||||
| Q27 | 0.748 | ||||||
| Q31 | 0.715 | ||||||
| Q32 | 0.504 | ||||||
| Q33 | 0.561 | ||||||
| Q34 | 0.611 | ||||||
| Q42 | 0.426 | ||||||
| Q43 | 0.854 | ||||||
| Q44 | 0.844 | ||||||
| Q47 | 0.505 | ||||||
| Q48 | 0.519 | ||||||
| Q49 | 0.731 | ||||||
| Q50 | 0.73 | ||||||
| Q51 | 0.711 |
Table 3.
Scale statistics
| Measure | Past Weight | Body Image | Lifestyle |
|---|---|---|---|
| Mean | 19.42 | 13.53 | 83.37 |
| Variance (%) | 40.80 | 34.668 | 216.199 |
| Standard Deviation | 10.47 | 5.888 | 14.704 |
| Cronbach’s Alpha | 0.83 | 0.867 | 0.72 |
| Kaiser-Meyer Olkin (KMO) | 0.83 | 0.879 | 0.723 |
| Bartlett’s Test of Sphericity | Chi-square: 1318.934 | Chi-square: 804.224 | Chi-square: 2855.989 |
| df: 78 | df: 15 | df: 741 | |
| P<0.001 | P<0.001 | P<0.001 |
Supplementary Table 2.
Intraclass correlation of the items after test-retest analysis
| Questions | Intraclass Correlationb | 95% Confidence Interval |
|
|---|---|---|---|
| Lower Bound | Upper Bound | ||
| Past Weight Management | |||
| Eating less than your usual amount of food | 0.989 | 0.975 | 0.994 |
| Consuming diet pills, fat burners/detoxes | 0.987 | 0.978 | 0.997 |
| Using Food Supplements (Powders/Drinks) | 0.955 | 0.945 | 0.965 |
| Trying specific diets (Keto, Atkins, Gluten free, Lactose Free, Intermittent Fasting, etc) | 0.986 | 0.976 | 0.999 |
| Eating more fruits and vegetables | 0.977 | 0.965 | 0.987 |
| Decreasing the intake of high fat, salt, and sugar foods | 0.956 | 0.946 | 0.966 |
| Increasing Physical Activity | 0.981 | 0.972 | 0.991 |
| Body Image | |||
| I am conscious about my body weight | 0.987 | 0.965 | 0.990 |
| I am less confident due to my body weight | 0.989 | 0.970 | 0.992 |
| I am judged by others due to my body weight | 0.97 | 0.965 | 0.987 |
| I am anxious about my body weight | 0.965 | 0.948 | 0.974 |
| I am isolated and lonely because of my body weight | 0.967 | 0.952 | 0.983 |
| I am embarrassed due to my body weight | 0.988 | 0.962 | 0.991 |
| Lifestyle | |||
| How often do you make a conscious effort for regular meals (three major and two minor) | 0.987 | 0.976 | 0.998 |
| How often do you consume the three servings of whole grains (whole wheat, millet, whole pulses etc) | 0.985 | 0.978 | 0.998 |
| How often do you consume 1–2 serving of protein-rich foods (Dairy, Legumes, nuts, and chicken) | 0.978 | 0.968 | 0.988 |
| How often do you consume 2–3 servings of dairy and dairy-based products? | 0.967 | 0.957 | 0.977 |
| How often do you include 4–5 servings (400–500 gm) of fruits and vegetables in your diet? | 0.956 | 0.945 | 0.966 |
| How often do you eat when you are not hungry (e.g., when stressed, bored, or emotional)? | 0.988 | 0.978 | 0.999 |
| How often do you eat until you feel uncomfortably full? | 0.945 | 0.934 | 0.955 |
| Do you eat while distracted in leisure activities (e.g., watching TV, or scrolling on your phone)? | 0.956 | 0.949 | 0.966 |
| I often get tempted to eat food items high in fat, salt, and sugar (HFSS) after watching the advertisements of food on social media and apps | 0.998 | 0.987 | 1.000 |
| My friends and family often offer me foods rich in fat, sugar, and salt at social events and family gatherings | 0.912 | 0.901 | 0.922 |
| How often in a week do you engage in moderate-vigorous physical activity (brisk walking, dancing, jogging, cycling, swimming, playing outdoor sports etc.) | 0.945 | 0.934 | 0.955 |
| How many minutes do you spend on moderate-vigorous physical activity per day | 0.977 | 0.967 | 0.989 |
| I do not have enough time to indulge in physical activity due to my personal and professional commitments | 0.978 | 0.968 | 0.988 |
| I find it challenging to engage in physical activities due to joint pain/body pain/excessive tiredness | 0.965 | 0.955 | 0.976 |
| My friends and family members show little interest in maintaining an active lifestyle | 0.943 | 0.934 | 0.955 |
| I do not have access to parks, fitness centres, and gyms | 0.934 | 0.944 | 0.954 |
| I find it challenging to engage in physical activity due to weather or outside temperature | 0.912 | 0.901 | 0.922 |
Supplementary Table 3.
Model fit indices of structure equation model through confirmatory factor analysis
| Model Fit Indices | Past Weight Management | Weight-related Body Image | Lifestyle and Associated Barriers |
|---|---|---|---|
| RMSEA | 0.039 | 0.046 | 0.049 |
| P-CLOSE | 0.565 | 0.165 | 0.524 |
| CFI | 0.986 | 0.965 | 0.90 |
| TLI | 0.979 | 0.942 | 0.920 |
| SRMR | 0.088 | 0.050 | 0.054 |
| χ2/df | 1.70 | 1.67 | 1.70 |
DISCUSSION
The present study developed and validated a comprehensive questionnaire assessing past weight management efforts, weight-related body image concerns, and lifestyle behaviours along with associated barriers among YAs [Table 4a-c]. Using a structured and rigorous methodological framework, the final instrument integrates three distinct yet interrelated domains that are central to understanding weight management in this population. The resulting tool demonstrates satisfactory psychometric properties, including strong internal consistency and reliability.
Table 4a.
Final items of the questionnaire across various domains after development and validation (Past Weight Management)
| Past Weight Management | |||||
|---|---|---|---|---|---|
| This section aims to assess the strategies you have used to lose weight at any point in your life | |||||
| Statement | Always | Frequently | Occasionally | Seldom | Never |
| A1. Eating less than your usual amount of food | |||||
| A2. Eating more Fruits and Vegetables | |||||
| A3. Decreasing the intake of high-fat, salt, and sugar foods | |||||
| A4. Increasing Physical Activity | |||||
| A5. Consuming diet pills, fat-burners/detoxes | |||||
| A6. Using Food Supplements | |||||
| A7. Trying specific diets (Keto, Atkins, gluten- free, lactose-free, intermittent fasting) | |||||
Table 4c.
Final Items of the questionnaire across various domains after development and validation (Lifestyle and associated barriers)
| Lifestyle and Associated Barriers | |||||
|---|---|---|---|---|---|
| This section aims to assess your general dietary habits that encompass your consistent food and drink consumption patterns | |||||
| Statement | Daily | 3–4 times/week | 1–2 times/week | Sometimes | Rarely/Never |
| C1. How often do you make a conscious effort for regular meals (three major meals+two snacks) | |||||
| C2. How often do you consume the three servings of whole grains (whole wheat, millet, whole pulses) | |||||
| C3. How often do you consume 1–2 servings of protein-rich foods (dairy, legumes, nuts, and chicken)? | |||||
| C4. How often do you consume 2–3 servings of dairy and dairy-based products? | |||||
| C5. How often do you include 4–5 servings (400–500 gm) of fruits and vegetables in your diet? | |||||
|
| |||||
|
This section aims to assess your barriers to healthy eating by examining the actions, attitudes, and environment related to your food and eating pattern
| |||||
| Statement | Strongly Agree | Agree | Neither Agree nor Disagree | Disagree | Strongly Disagree |
|
| |||||
| C6. I often eat when I am not hungry (e.g., when stressed, bored, or emotional)? | |||||
| C7. I often eat until I feel uncomfortably full | |||||
| C8. I often eat while distracted in leisure activities (e.g., watching TV, or scrolling on your phone) | |||||
| C9. I often get tempted to eat food items high in fat, salt, and sugar (HFSS) after watching the advertisements of food on social media and apps | |||||
| C10. My friends and family often offer me foods rich in fat, sugar, and salt at social events and family gatherings | |||||
|
| |||||
|
This section aims to assess your general physical activity behaviour that encompasses your habitual patterns of movement and exercise that you engage in as part of your daily life
| |||||
| C11. How often in a week do you engage in moderate-vigorous physical activity (brisk walking, dancing, jogging, cycling, swimming, playing outdoor sports etc.)? (i) Daily (ii) 5–6 times per week (ii) 3–4 times per week (iii) Once in a fortnight (iv) Never C12. How many minutes do you spend on moderate-vigorous physical activity per day? (i) <30 min (ii) 30–60 min (iii) 60–90 min (iv) >90 min (v) Not Applicable | |||||
|
| |||||
|
This section consists of statements that aim to assess the barriers to physical activity affecting your ability to engage in regular exercise or movement
| |||||
| Statement | Strongly Agree | Agree | Neither Agree nor Disagree | Disagree | Strongly Disagree |
|
| |||||
| C13. I do not have enough time to indulge in physical activity due to my personal and professional commitments | |||||
| C14. I find it challenging to engage in physical activities due to joint pain/body pain/excessive tiredness. | |||||
| C15. My friends and family members show little interest in maintaining an active lifestyle | |||||
| C16. I do not have access to parks, fitness centres, and gyms | |||||
| C17. I find it challenging to engage in physical activity due to weather or outside temperature | |||||
Table 4b.
Final items of the questionnaire across various domains after development and validation (Weight-related Body Image)
| Weight-related Body Image | |||
|---|---|---|---|
| This section aims to assess your feelings, emotions, and perceptions regarding your body weight | |||
| Statement | Never | Sometimes | Often |
| B1. I am conscious about my body weight | |||
| B2. I am less confident due to my body weight | |||
| B3. I am judged by others due to my body weight | |||
| B4. I am anxious about my body weight | |||
| B5. I am isolated and lonely because of my body weight | |||
| B6. I am embarrassed due to my body weight | |||
The first domain examines past weight management efforts, differentiating between structured lifestyle modifications and engagement in fad-based approaches. The construct validity of this section is consistent with existing literature, indicating that weight management often involves behavioural strategies such as portion control, increased physical activity, and dietary changes, alongside the use of unsupervised practices including diet pills and detox regimens.[17,18,19] An important observation was the exclusion of self-monitoring items due to low factor loadings. This may suggest that self-monitoring was not perceived as a dominant behavioural component within this sample of YAs. This finding differs from prior research that highlights self-monitoring as a significant contributor to long-term weight regulation,[17,20] and may reflect contextual or age-specific behavioural patterns rather than a diminished theoretical importance of self-efficacy.
The second domain assesses weight-related body image concerns, encompassing self-perception, perceived social judgment, emotional distress, and social withdrawal related to body weight. Compared to existing instruments such as the Iranian body image scale for youth (BISY) and the Dresden body image questionnaire (DBIQ), the present tool offers relative brevity and a focused emphasis on weight-related concerns among YAs, particularly within the Indian context.[21,22] The inclusion of this domain is supported by literature demonstrating the psychological and social implications of body image dissatisfaction, including its influence on eating behaviours and mental well-being.[23,24] Unlike broader body image measures, this questionnaire emphasizes inclusive and non-stigmatizing language, which may foster a more supportive assessment environment.[6,21]
The third domain evaluates lifestyle behaviours and related barriers influencing weight management, including dietary habits, physical activity patterns, and psychosocial determinants. Sleep-related items were excluded during factor analysis due to insufficient loadings. Although prior studies have reported associations between sleep patterns and weight outcomes,[25,26] the present findings suggest that sleep may not have emerged as a primary behavioural determinant within this cohort. This observation should be interpreted cautiously and warrants further investigation.
A high prevalence of sedentary behaviour was observed, with many participants reporting prolonged sedentary time exceeding eight hours daily. This aligns with previous research documenting extended screen exposure and reduced physical activity among young adults.[27,28] The dietary component incorporates meal patterns, dietary diversity, and HFSS (high fat, sugar, and salt) food consumption, while also acknowledging psychological mediators such as stress, media exposure, and social influence as contributors to lifestyle choices.[29,30]
Strengths and limitations
The study has several strengths, including its comprehensive multidimensional assessment and rigorous validation process using multiple datasets. The questionnaire’s structured yet user-friendly format supports self-administration, potentially reducing participant burden and facilitating use in clinical and community settings. However, certain limitations merit consideration. The use of purposive sampling may limit the generalizability of findings, highlighting the need for validation in more diverse and representative populations. The reliance on self-reported data introduces the possibility of recall bias and social desirability bias.
Furthermore, although the instrument specifically captures weight-related body image concerns, broader psycho-social constructs, such as clinical depression, anxiety, emotional eating, structured measures of social support, and weight stigma, were not comprehensively assessed. These factors may interact with lifestyle behaviours and weight management outcomes. Future research integrating these constructs may provide a more nuanced understanding of the psychosocial dimensions of obesity in YAs.
Implications
This comprehensive questionnaire offers a multidimensional framework for assessing weight-related behaviours in young adults. By integrating past weight management efforts, body image concerns, and lifestyle factors, the instrument facilitates a more holistic evaluation of behavioural and psychosocial influences on weight management.
In clinical settings, it may assist healthcare providers in identifying maladaptive practices and psychosocial vulnerabilities that could influence intervention outcomes. In research contexts, the tool may support epidemiological and longitudinal investigations examining behavioural trends and psychosocial determinants. At a public health level, the questionnaire may contribute to the development of targeted strategies addressing sedentary behaviour, unhealthy dietary patterns, and weight-related stigma among YAs. Broader implementation, however, should follow further validation across diverse populations.
Future research
Future studies should focus on cross-cultural validation and longitudinal assessment to evaluate the predictive utility and responsiveness of the questionnaire over time. Application within interventional studies may help determine its sensitivity to behavioural change. Additionally, integrating objective physiological measures and standardized psychological assessments could enhance understanding of the interplay between lifestyle behaviours, mental health, and weight outcomes in young adults.
CONCLUSION
The present study developed and psychometrically validated a comprehensive, multidimensional questionnaire integrating lifestyle behaviours, weight-related body image concerns, and past weight management practices among young adults. The instrument demonstrated satisfactory construct validity, internal consistency, and test–retest reliability, supporting its robustness and applicability. By capturing behavioural and psychosocial dimensions within a single tool, it offers a practical and user-friendly approach for holistic assessment. This questionnaire may facilitate improved clinical evaluation and support research exploring determinants of obesity in young adults. Further validation across diverse populations and longitudinal settings is warranted to strengthen its generalizability and predictive utility.
Author contributions (CRediT)
WA was responsible for data collection and preparation of the initial draft. PR contributed to conceptualization, funding acquisition, supervision, and methodology development. AM, AK, and GK were involved in methodology development, writing, and supervision. AK and GK additionally contributed to methodological development. ADU conducted the statistical analysis. NKV contributed to conceptualization and methodology development. All authors reviewed and approved the final manuscript.
Conflicts of interest
There are no conflicts of interest.
Use of artificial intelligence
Artificial Intelligence tools were used solely for language refinement and improving the readability of the manuscript. No AI tools were used for data analysis, interpretation, or content generation. All final content was reviewed and approved by the authors.
Data availability
The data that support the findings of this study are available from the corresponding author upon request.
Acknowledgment
None.
Funding Statement
This study was funded by the Indian Council of Medical Research under the ICMR Adhoc Project Program extramural research scheme (Sanction No: 5/4/8-1/Obs/PR/2022-NCD-II).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon request.