|
ORIGINAL RESEARCH |
https://doi.org/10.5005/bjotgh-11016-0004 |
Association of Body Mass Index between Adolescents and their Parents in Mumbai and Kolkata: A Population-based Study
1–4Department of Research, Healis Sekhsaria Institute for Public Health, Navi Mumbai, Maharashtra, India
5Centre for Cancer Prevention and Control Research, Fielding School of Public Health, University of California, Los Angeles, California, United States of America
6Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, Michigan, United States of America
Corresponding Author: Namrata Puntambekar, Department of Research, Healis Sekhsaria Institute for Public Health, Navi Mumbai, Maharashtra, India, Phone: +91 7977028413, e-mail: puntambekarn@healis.org
How to cite this article: Puntambekar N, Pednekar MS, Gupta PC, et al. Association of Body Mass Index between Adolescents and Their Parents in Mumbai and Kolkata: A Population-based Study. Br J Transl Glob Health 2024;1(1):3–8.
Source of support: National Cancer Institute/National Institutes of Health: R01CA201415 (Multiple PIs: Ritesh Mistry, Mangesh S Pednekar). The funder has no role in the design, implementation and interpretation of study results.
Conflict of interest: Dr Prakash C Gupta is associated as the Editorial Board member of this journal and this manuscript was subjected to this journal�s standard review procedures, with this peer review handled independently of this editorial board member and his research group.
Received on: 15 February 2024; Accepted on: 07 March 2024; Published on: 30 April 2024
ABSTRACT
Introduction: Adolescent overweight and obesity as measured by body mass index (BMI) seem to be increasing at an alarming rate in urban populations. Parental BMI plays an important role in their adolescent’s BMI. Overweight and obesity co-existing with undernutrition in adolescents is an important public health challenge in low- and middle-income countries (LMICs). We present results from a population-based study on adolescents’ prevalence of BMI and its association with their parents’ BMI in Mumbai and Kolkata, India.
Methods and materials: Multistage random sampling of households was used to select adolescents aged 12–14 years and one of their parents in 2019–2020. In Mumbai, 843 adolescents, and in Kolkata, 913 adolescents and one of their parents were interviewed independently by trained field investigators. Height and weight were measured using standardised procedures. Adolescents’ BMI categories were defined using Centres for Disease Control and Prevention (CDC) recommendations. For parents, the BMI was categorised using Asian cut-off categories into underweight (BMI < 18.5), normal weight (BMI: 18.5–22.9), overweight (BMI: 23.0–27.0), and obese (BMI > 27.0). Multivariate logistic regression was used to determine the relationship between parental BMI and adolescents’ BMI.
Results: In Mumbai, 15.7% and in Kolkata, 21.1% of adolescents were overweight or obese. Nearly 80% of mothers and 70% of other parents were either overweight or obese. The mothers of adolescents who were overweight or obese showed a high risk of their adolescent being overweight [odds ratio (OR): 4.16 (1.36–12.73)] or obese [OR: 18.53 (2.02–170.44)] in Mumbai and [OR: 4.45 (1.25–15.80)] and [OR: 8.81 (1.40–55.33)] in Kolkata respectively after adjusting for adolescent’s gender and head of the household’s highest level of educational attainment.
Conclusion: Adolescents’ overweight/obesity status is strongly associated with their mothers’ BMI in urban India. This association may reflect both genetic and environmental effects. The present study highlights the high prevalence of adolescent overweight and obesity in these urban populations and underscores how important it is to identify effective public health strategies for the primary prevention of childhood obesity.
Keywords: Adolescents, Body mass index, Loneliness, Obesity.
Highlights
What is known?
Globally, the association of children and their mother’s body mass index (BMI) is well established.
What is new?
To our knowledge, this is the first paper that describes the association of adolescents (who are aged 12–14 years) and their mother’s BMI from a population of two metropolitan cities in India.
INTRODUCTION
In many low- and middle-income countries (LMICs), the prevalence of overweight and obesity is increasing and emerging as a public health risk.1,2 The increasing prevalence of overweight and obesity co-existing with undernutrition is an increasingly significant public health challenge in LMICs, especially in women with lower levels of attained education.3,4 On one hand, improved economic conditions, urbanisation, the prevalence of sedentary routines, and dietary changes such as reduced dietary diversity have caused a steady increase in overweight and obesity. On the other hand, many LMICs are continuing to face concurrent challenges posed by undernutrition and its consequences.5−8 The overweight and obesity prevalence has doubled and tripled in pre-school and primary school-aged children, respectively, in India.9
Numerous earlier studies have shown that overweight and obesity in adolescent are the intricate interaction between genetic and environmental factors.10–12 Parental weight status has been shown to be an important predictor of their children’s obesity risk.13 Adolescents whose parents had a normal body mass index (BMI) exhibited healthier behaviours such as regular physical activity and healthy eating patterns compared with adolescents whose parents were overweight or obese.14
Preventing childhood obesity is a public health priority, because childhood obesity increases risk of obesity in adulthood and is associated with long-term adverse health consequences, both physical and emotional, such as loneliness.15–18 The onset of childhood obesity and its persistence into adulthood cannot be entirely attributed to inherited traits, but also to parental health practices.11,19 Many studies have examined the relationship between the severity of obesity in parents and their children in various age groups.20–24
In this paper, we report the results of these associations using data from a population-based study of adolescents and their parents in Mumbai and Kolkata, India.25 The purpose of this paper is to examine how the BMI status of 12–14-year-old adolescents relates to the BMI status of their parents, taking into account other confounding factors.
METHODS AND Materials
Sampling Design
We selected two cities Mumbai, Maharashtra and Kolkata, West Bengal as two large, populous, geographically distant and culturally diverse urban areas. To obtain a representative sample of communities and adolescents in both cities, we used a multistage sampling design. We used a sampling frame obtained for urban areas from the National Sample Survey Office (NSSO) of the Ministry of Statistics and Program Implementation known as the Urban Frame Survey.26 The geographic areas in the sampling frame were hierarchically nested as states, cities, investigator units (IV units) and blocks. Most blocks were designated by the NSSO as affluent residential areas, residential areas, and slum areas.
Sampling Plan
We sampled 26 IV units in each city from 916 IVs in Mumbai and 333 in Kolkata followed by 5 blocks on an average per IV unit for a total of 272 blocks out of total 27,059 from both cities. All the households within the selected blocks were enumerated and eligible households were recruited in the study. Households having at least one adolescent aged 12–14 years living with his/her parent were eligible for the study. During 2019–2020, a total of 843 adolescents in Mumbai and 913 in Kolkata eligible adolescents 12–14 years of age and their parent were surveyed. The measures of height and weight were obtained using scientific and uniform procedures as discussed in the following subsections:
Weight Measurement
A bathroom scale accurate to 0.1 kg (CAS Weighing Scale – HE23) was used to measure the weight of the study participants. The scale was placed on a flat, hard surface (not on a carpet). Participants were requested to step on the weighing scale with bare feet with hands by their sides, immobile without leaning on furniture or holding on to anything. Respondents’ weight measurements were recorded after ensuring removal of heavy clothing such as coats, jackets and vests, purses, cell phones, keys and heavy accessories such as belts with heavy buckles. A zero reading on the weighing scale was obtained prior to each use of the scale. Respondents were asked to stand motionless in the centre of the scale platform with feet slightly apart and body weight distributed equally on both feet. Respondents were then asked to step down from the scale and the displayed weight was recorded to the nearest 0.1 kg. Two measures per respondent were recorded for reliability; if the discrepancy between these first two measures was greater than 0.1 kg, then a third measure was taken and the average across all three measures was used as final measurement.
Height Measurement
The height of the respondents was measured using a portable stadiometer. Respondents were asked to remove their shoes, hats and any other hair accessories. Participants were asked to stand erect, back touching to the wall, with feet together, arms at sides, legs straight, and shoulders relaxed. Each respondent’s heels, buttocks, and shoulder blades and head were maintained in contact with the wall. A ruler was touched to the crown of the head, compressing the hair, if necessary. Respondents were asked to step out so that the interviewer could get closer to the ruler scale and take the reading. The ruler scale wasn’t moved until the height measurement was recorded. Height was recorded to the nearest centimetre. Two measures were recorded for accuracy; if discrepancy between those measures was greater than 1 cm, then a third measure was taken and the average across all three measures was used as a final measurement.
The structured questionnaire for data collection was made retrievable online using REDCap software.27,28 All data collected during face-to-face interviews were entered directly in computer tablets in the field and daily transferred to a secured server. The BMI values for each adolescent and their parent were calculated by using the formula “Weight (kg)/[height (m)]2.” Asian cut-off values for adults were used to categorise them into underweight (BMI: <18.5); normal weight (BMI: 18.5–22.9); overweight (BMI: 23.0–27.0); and obese (BMI > 27.0).29 The BMI categories for adolescents were defined using the following Centres for Disease Control and Prevention (CDC) recommendations: Underweight: Less than the 5th percentile; Normal weight: From 5th percentile to less than the 85th percentile; Overweight: From 85th percentile to less than the 95th percentile; Obese: From 95th percentile or greater.30 To assess loneliness among adolescents, the following question was used: “During the past 30 days, how often have you felt lonely?” Response options were as follows: “Never,” “Sometimes,” “Most of the times,” and “Always.” For analysis purposes “Sometimes,” “Most of the times,” and “Always” were coded as “Yes” and “never” as “No.”
Analysis
Descriptive statistics were calculated for both cities separately. All statistical analyses were performed using Statistical Package for the Social Sciences (SPSS), version 20.0, software using the complex sample survey analysis programs and project sampling weights. Multivariate logistic regression was used to evaluate the relationship between parental BMI and each adolescent’s BMI. Adolescent’s gender and head of the household’s highest level of education were included as covariates. The outcome variable BMI of the adolescents in relation to parental underweight, overweight or obese status, with parental normal weight status serving as the reference. Odds ratios (ORs) along with [95% conference intervals (CIs)] were calculated.
RESULTS
Table 1 describes the sample characteristics of Mumbai and Kolkata, respectively. Around 80% of mothers and 70% of other parents in Mumbai and Kolkata were overweight or obese. About 5% in Mumbai and 4% in Kolkata mothers were found to be underweight and other parents. Among adolescents, about 11.2% in Mumbai and 7.5% in Kolkata were overweight or obese. In both cities, around 5% adolescents were underweighted. Nearly 15.0% of adolescents in both cities reported that they often felt lonely in the past 30 days.
| Characteristics | Mumbai (adolescent)n = 843* | Kolkata (adolescent)n = 913* | ||
|---|---|---|---|---|
| n | Weighted % | n | Weighted % | |
| Mother’s BMI (kg/m2) | ||||
| Underweight% | 38% | 4.8%% | 34% | 3.6% |
| Normal weight% | 116% | 15.9%% | 162% | 16.3% |
| Overweight% | 213% | 32.2%% | 263% | 36.4% |
| Obese% | 290% | 47.1%% | 308% | 43.6% |
| Other than mother mostly father – BMI kg/m2 | ||||
| Underweight% | 11% | 2.1%% | 9% | 6.7% |
| Normal weight% | 37% | 24.7%% | 43% | 23.4% |
| Overweight% | 63% | 34.9%% | 44% | 33.5% |
| Obese% | 75% | 38.2%% | 50% | 36.5% |
| Adolescents | ||||
| Male% | 432% | 50.8%% | 448% | 48.2% |
| Female% | 411% | 49.2%% | 465% | 51.8% |
| Underweight (less than the fifth percentile)% | 41% | 5.1%% | 40% | 4.4% |
| Normal weight% | 663% | 76.1%% | 732% | 74.5% |
| Overweight (from 85th to less than the 95th percentile)% | 89% | 11.2%% | 90% | 14.2% |
| Obese (95th percentile or greater)% | 61% | 7.5%% | 40% | 6.9% |
| During the past 30 days, how often have you felt lonely? | ||||
| Yes% | 128% | 14.6%% | 129% | 15.0% |
| No% | 714% | 85.4%% | 782% | 85.0% |
Table 2 describes the adjusted odds ratios for the association of adolescents’ BMI with their parents’ BMI, adjusted for gender and head of the household’s highest level of education for Mumbai and Kolkata, respectively. Mother’s underweight was associated with adolescent’s overweight in Mumbai (Mumbai: 3.65, CI: 1.53–8.73) but no association was found in Kolkata. Mother’s overweight and obesity status was positively associated with adolescent’s overweight and obesity status in both cities (overweight: Mumbai: 4.16, CI: 1.36–12.73, Kolkata: 4.45, CI: 1.25–15.08; obesity: Mumbai: 18.53, CI: 2.02–170.44, Kolkata: 8.81, CI: 1.40–55.33). As compared to adolescent females, adolescent males were more likely to be obese (Mumbai: 2.79, CI: 1.02–7.58). Furthermore, those adolescents who often felt lonely in the past 30 days were more likely to be obese (Mumbai: 2.91, CI: 1.28–6.63, Kolkata: 2.90, CI: 1.61–5.21).
| Characteristics | Mumbai (adolescent)* | Kolkata (adolescent)* | ||||
|---|---|---|---|---|---|---|
| Underweight | Overweight | Obese | Underweight | Overweight | Obese | |
| Odds (95% CI) | Odds (95% CI) | Odds (95% CI) | Odds (95% CI) | Odds (95% CI) | Odds (95% CI) | |
| Mother’s BMI (kg/m2)** | ||||||
| Underweight % | 1.08 (0.27–4.34)% | 1.26 (0.34–4.62)% | 3.75 (0.22–63.41)% | 1.83 (0.27–12.6)% | 2.01 (0.32–12.67)% | 6.52 (0.47–89.94) |
| Overweight + obese % | 3.65 (1.53–8.73)% | 4.16† (1.36–12.73)% | 18.53† (2.02–170.44)% | 0.36 (0.07–1.7)% | 4.45† (1.25–15.8)% | 8.81† (1.40–55.33) |
| Other than mother mostly father – BMI (kg/m2)*** | ||||||
| Underweight% | 4.55 (0.21–100.64) | –% | 0.8 (0.06–10.32)% | 6.44 (0.12–355.93)% | 1.56 (0.07–32.68)% | 0.62 (0.07–5.35) |
| Overweight + obese% | 0.53 (0.07–4.05)% | 1.59 (0.27–9.4) | –% | 16.21† (2.03–129.55)% | 2.59 (0.3–22.32) | – |
| Adolescents | ||||||
| Male% | 1.05 (0.43–2.6)% | 1.22 (0.59−2.51)% | 2.79† (1.02–7.58)% | 1.47 (0.59–3.68)% | 0.75 (0.45–1.26)% | 0.59 (0.29–1.22) |
| Female | R | R | R | R | R | R |
| During the past 30 days, how often have you felt lonely? | ||||||
| Yes% | 0.44 (0.06–3.09)% | 1.84 (0.81–4.15)% | 2.91† (1.28–6.63)% | 0.76 (0.23–2.51)% | 2.90† (1.61–5.21)% | 1.57 (0.56–4.44) |
| No | R | R | R | R | R | R |
DISCUSSION
The current study explored the associations of BMI status from Mumbai and Kolkata adolescents and their parents at the city level. Households of overweight parents are more likely to feature unhealthy dietary habits, leading to further issues and a sedentary lifestyle.11,31 Therefore, it is important for parents with overweight to address their own weight issues and be mindful of the potential impacts that it could have on their children.32 Furthermore, the parents’ obesity can also create a home atmosphere that is not conducive to healthy eating habits or physical activity, leading to their child’s unhealthy weight status.24 Many parents and their adolescents can benefit from health interventions that focus on promoting healthier eating habits and physical activity.33 Additionally, parents should be aware of the connection between weight status and health outcomes so they can be proactive in promoting healthy habits in their adolescents.30
Parents with overweight have been linked to having adolescents who are overweight. Many studies suggest that there is a strong association between parental and adolescent obesity.24,34 In our study we found that adolescents from households with parents (mostly mothers) who were overweight or obese were at a significantly higher risk of overweight and obesity compared to adolescents of parents with normal weight. This is believed may be due to a combination of genetic, environmental and behavioural factors that influence both parents and adolescents and decreased physical activity and unhealthy eating patterns being passed down from one generation to the next.13,35,36
It is clear that the lifestyle of a mother with overweight can have significant consequences for her children’s health and well-being. Several environmental factors, that is, parental obesity, shared family lifestyle, food habits or socioeconomic status could explain the association between parent and child obesity risk.37–40 More specifically, unhealthy parental eating habits, such as consuming more fried, fast food, and sweets, as well as a sedentary lifestyle, such as doing little exercise and spending too much time in front of the TV or using a computer, mobile phones may raise the risk of overweight and obesity in both parents and their children.35,40
The relationship between adolescent loneliness and obesity status is probably bidirectional.41,42 While loneliness and social isolation can have numerous negative effects on mental health, they can also lead to adolescent overweight.43,44 When adolescents feel lonely or socially isolated, they may turn to food as a means of comfort, leading to overeating and unhealthy weight gain.45 Additionally, obesity-related stigma may make them less likely to engage in social or physical activities with others, further contributing to weight gain. Also, in our present study, it has been reported that adolescents who felt lonely were found to be overweight or obese (obese – Mumbai, 2.91, CI: 1.28–6.63; overweight – Kolkata, 2.90, CI: 1.61–5.21). It is important for adolescents to have supportive social networks and to engage in healthy behaviours to maintain a healthy weight and optimise their overall well-being.46 Encouraging adolescents to participate in group activities, to seek social support from family and friends, and eat a balanced and nutritious diet can all be helpful strategies for combating loneliness and preventing unhealthy weight gain.
Strengths and Limitations
The strengths of this study include the fact that we obtained a representative multi-stage sample of communities and adolescents in both major Indian cities, which will enhance generalisability. Given the nature of the study design being cross-sectional, causal association could not be ascertained. Thus, the association between parent BMI and the adolescents’ weight remains to be confirmed in prospective studies. The head of the household’s highest level of education was used as a proxy measure to control for household variation in socio-economic status.
CONCLUSION
The prevalence of overweight/obesity is increasing in urban India among adults and adolescents. For optimal impact, lifestyle change efforts to reduce population obesity risk should be family-centred. More specifically, interventions for the prevention and control of childhood obesity should focus on changing the health behaviours of both parents and children.47 Additionally, a more comprehensive intervention should include family environment as a multi-factorial contributing factor to childhood obesity epidemic. For these reasons, more studies need to be conducted using the most current data to confirm and extend the results reported here.
ACKNOWLEDGEMENT
The authors are thankful to the study team (Mr. Sameer Narake, Dr Manisha Pathak) and the collaborating Institute in Kolkata ‘Cancer Foundation of India (CFI)’ for their contribution to the project. We also thank the study respondents who participated in the survey.
Ethical Approval
The study is approved by the Institutional Review Boards of the Healis Sekhsaria Institute for Public Health (2015/18/03) and the University of Michigan University (HUM00129316) and parental/guardian permission was obtained for minor participants (under 18 years of age), who were asked to provide assent prior to enrolment in the study. Any protocol changes will be reported immediately to each Institutional Review Board.
ORCID
Namrata Puntambekar https://orcid.org/0000-0002-4797-7463
Mangesh S Pednekar https://orcid.org/0000-0001-6266-5356
Maruti B Desai https://orcid.org/0000-0002-9030-7078
REFERENCES
1. Pradeepa R, Anjana RM, Joshi SR, et al. Prevalence of generalized & abdominal obesity in urban & rural India: The ICMR–INDIAB study (Phase-I) [ICMR-INDIAB-3]. Indian J Med Res 2015;142(2):139–150. PMCID: PMC4613435.
2. Luhar S, Timæus IM, Jones R, et al. Forecasting the prevalence of overweight and obesity in India to 2040. PLoS One 2020;15(2):1–17. DOI: 10.1371/journal.pone.0229438.
3. Sebsbie A, Minda A, Ahmed S. Co-existence of overweight/obesity and stunting: It’s prevalence and associated factors among under - five children in Addis Ababa, Ethiopia. BMC Pediatr 2022;22(1):1–10. DOI: 10.1186/s12887-022-03445-5.
4. Dwivedi LK, Puri P, Pant A, et al. Concurrent undernutrition and overnutrition within Indian families between 2006 and 2021. Curr Dev Nutr 2023;7(9):101987. DOI: 10.1016/j.cdnut.2023.101987.
5. Gezaw A, Melese W, Getachew B, et al. Double burden of malnutrition and associated factors among adolescent in Ethiopia: A systematic review and meta-analysis. PLoS One 2023;18:(4):e0282240. DOI: 10.1371/journal.pone.0282240.
6. Agrawal P, Gupta K, Mishra V, et al. Effects of sedentary lifestyle and dietary habits on body mass index change among adult women in India: Findings from a follow-up study. Ecol Food Nutr 2013;52(5):387–406. DOI: 10.1080/03670244.2012.719346.
7. Afshin A, Forouzanfar MH, Reitsma MB, et al. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med 2017;377(1):13–27. DOI: 10.1056/NEJMoa1614362.
8. NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet 2016;387(10026):1377–1396. DOI: 10.1016/S0140-6736(16)30054-X.
9. Kumar HNH, Mohanan P, Kotian S, et al. Prevalence of overweight and obesity among pre-school children in semi urban South India. Indian Pediatr 2008;45(6):449–497. PMID: 18599938.
10. Xi B, Mi J, Duan J-li, et al. Familial clustering of obesity and the role of lifestyle factors among children in Beijing. Zhonghua Yu Fang Yi Xue Za Zhi 2009;43(2):122–127. PMID: 19534904.
11. Farajian P, Panagiotakos DB, Risvas G, et al. Hierarchical analysis of dietary, lifestyle and family environment risk factors for childhood obesity: The GRECO study. Eur J Clin Nutr 2014;68(10):1107–1112. DOI: 10.1038/ejcn.2014.89.
12. Liu Y, Chen HJ, Liang L, et al. Parent–child resemblance in weight status and its correlates in the United States. PLoS One 2013;8(6):e65361. DOI: 10.1371/journal.pone.0065361.
13. Stettler N, Tershakovec AM, Zemel BS, et al. Early risk factors for increased adiposity: A cohort study of African American subjects followed from birth to young adulthood. Am J Clin Nutr 2000;72(2):378–383. DOI: 10.1093/ajcn/72.2.378.
14. Kosti RI, Panagiotakos DB, Tountas Y, et al. Parental body mass index in association with the prevalence of overweight/obesity among adolescents in Greece; dietary and lifestyle habits in the context of the family environment: The Vyronas study. Appetite 2008;51(1):218–222. DOI: 10.1016/j.appet.2008.02.001.
15. Singh AS, Mulder C, Twisk JWR, et al. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes Rev 2008;9(5):474–488. DOI: 10.1111/j.1467-789X.2008.00475.x.
16. Biro FM, Wien M. Childhood obesity and adult morbidities. Am J Clin Nutr 2010;91(5):1499S–1505S. DOI: 10.3945/ajcn.2010.28701B.
17. Lindberg L, Hagman E, Danielsson P, et al. Anxiety and depression in children and adolescents with obesity: A nationwide study in Sweden. BMC Med 2020;18(1):1–9. DOI: 10.1186/s12916-020-1498-z.
18. Mason TB. Loneliness, eating, and body mass index in parent–adolescent dyads from the family life, activity, sun, health, and eating study. Pers Relatsh 2020;27(2):420–432. DOI: 10.1111/pere.12321.
19. Nelson MC, Gordon–Larsen P, North KE, et al. Body mass index gain, fast food, and physical activity: Effects of shared environments over time. Obesity (Silver Spring) 2006;14(4):701–709. DOI: 10.1038/oby.2006.80.
20. Bralić I, Vrdoljak J, Kovacić V. Associations between parental and child overweight and obesity. Coll Antropol 2005;29(2):481–486. PMID: 16417148.
21. Burke V, Beilin LJ, Dunbar D. Family lifestyle and parental body mass index as predictors of body mass index in Australian children: A longitudinal study. Int J Obes Relat Metab Disord J Int Assoc Study Obes 2001;25(2):147–157. DOI: 10.1038/sj.ijo.0801538.
22. Danielzik S, Langnäse K, Mast M, et al. Impact of parental BMI on the manifestation of overweight 5–7 year old children. Eur J Nutr 2002;41(3):132–138. DOI: 10.1007/s00394-002-0367-1.
23. Kivimäki M, Lawlor DA, Smith GD, et al. Substantial intergenerational increases in body mass index are not explained by the fetal overnutrition hypothesis: The cardiovascular risk in Young Finns study. Am J Clin Nutr 2007;86(5):1509–1514. DOI: 10.1093/ajcn/86.5.1509.
24. Zhang J, Clayton GL, Overvad K, et al. Body mass index in parents and their adult offspring: A systematic review and meta-analysis. Obes Rev 2024 25(1):e13644. DOI: 10.1111/obr.13644.
25. Mistry R, Pednekar MS, Gupta PC, et al. Longitudinal study of adolescent tobacco use and tobacco control policies in India. BMC Public Health 2018;18(1):815. DOI: 10.1186/s12889-018-5727-8.
26. Ministry of Statistics and Programme Implementation, Government of India. Urban Frame Survey (UFS). 2023. Available at: http://mospi.gov.in/urban-frame-surveyufs. Accessed on: 10 May 2023.
27. Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform 2019;95:103208. DOI: 10.1016/j.jbi.2019.103208.
28. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap): A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381. DOI: 10.1016/j.jbi.2008.08.010.
29. Joslin Diabetes Centre. BMI for Asian and Asian American Adults. 2016. Available at: https://tieuduongcardiff.com/fileman/Uploads/Documents/13.bmiforasianandasianamericanadults-horizontal-en-2015.pdf. Accessed on: 09 February 2023.
30. Hampl SE, Hassink SG, Skinner AC, et al. Clinical practice guideline for the evaluation and treatment of children and adolescents with obesity. Pediatrics 2023;151(2):e2022060640. DOI: 10.1542/peds.2022-060640.
31. Afrin S, Mullens AB, Chakrabarty S, et al. Dietary habits, physical activity, and sedentary behaviour of children of employed mothers: A systematic review. Prev Med reports 2021;24:101607. DOI: 10.1016/j.pmedr.2021.101607.
32. Weghuber D, Khandpur N, Boyland E, et al. Championing the use of people-first language in childhood overweight and obesity to address weight bias and stigma: A joint statement from the European-Childhood-Obesity-Group (ECOG), the European-Coalition-for-People-Living-with-Obesity (ECPO), the Inter. Pediatr Obes 2023;18(6):e13024. DOI: 10.1111/ijpo.13024.
33. Pastor R, Tur JA. Effectiveness of interventions to promote healthy eating habits in children and adolescents at risk of poverty: Systematic review and meta-analysis. Nutrients 2020;12(6):1891. DOI: 10.3390/nu12061891.
34. Bahreynian M, Qorbani M, Khaniabadi BM, et al. Association between obesity and parental weight status in children and adolescents. J Clin Res Pediatr Endocrinol 2017;9(2):111–117. DOI: 10.4274/jcrpe.3790.
35. Jiang MH, Yang Y, Guo XF, et al. Association between child and adolescent obesity and parental weight status: A cross-sectional study from rural North China. J Int Med Res 2013;41(4):1326–1332. DOI: 10.1177/0300060513480081.
36. Lister NB, Baur LA, Felix JF, et al. Child and adolescent obesity. Nat Rev Dis Prim 2023;9(1):24. DOI: 10.1038/s41572-023-00435-4.
37. Davison KK, Birch LL. Obesigenic families: Parents’ physical activity and dietary intake patterns predict girls’ risk of overweight. Int J Obes Relat Metab Disord J Int Assoc Study Obes 2002;26(9):1186–1193. DOI: 10.1038/sj.ijo.0802071.
38. Semmler C, Ashcroft J, van Jaarsveld CHM, et al. Development of overweight in children in relation to parental weight and socioeconomic status. Obesity (Silver Spring) 2009;17(4):814–820. DOI: 10.1038/oby.2008.621.
39. Bahreynian M, Motlagh ME, Qorbani M, et al. Prevalence of growth disorders in a nationally representative sample of Iranian adolescents according to socioeconomic status: The CASPIAN-III study. Pediatr Neonatol 2015;56(4):242–247. DOI: 10.1016/j.pedneo.2014.12.001.
40. Smith JD, Fu E, Kobayashi MA. Prevention and management of childhood obesity and its psychological and health comorbidities. Annu Rev Clin Psychol 2020;16:351–378. DOI: 10.1146/annurev-clinpsy-100219-060201.
41. Qualter P, Hurley R, Eccles A, et al. Reciprocal prospective relationships between loneliness and weight status in late childhood and early adolescence. J Youth Adolesc 2018;47(7):1385–1397. DOI: 10.1007/s10964-018-0867-9.
42. Khan A, Khan S, Burton N. Insufficient physical activity and high sedentary behaviour are associated with loneliness in adolescents with overweight/obesity: Evidence from 23 low- and middle-income countries. Pediatr Obes 2022;17(2):e12836. DOI: 10.1111/ijpo.12836.
43. Stickley A, Koyanagi A, Koposov R, et al. Loneliness and health risk behaviours among Russian and U.S. adolescents: A cross-sectional study. BMC Public Health 2014;14(1):366. DOI: 10.1186/1471-2458-14-366.
44. Mushtaq R, Shoib S, Shah T, et al. Relationship between loneliness, psychiatric disorders and physical health? A review on the psychological aspects of loneliness. J Clin Diagn Res 2014;8(9):WE01–WE04. DOI: 10.7860/JCDR/2014/10077.4828.
45. Dos Santos Quaresma MV, Marques CG, Magalhães ACO, et al. Emotional eating, binge eating, physical inactivity, and vespertine chronotype are negative predictors of dietary practices during COVID-19 social isolation: A cross-sectional study. Nutrition 2021;90:111223.
46. Frech A. Healthy behavior trajectories between adolescence and young adulthood. Adv Life Course Res 2012;17(2):59–68. DOI: 10.1016/j.alcr.2012.01.003.
47. Epstein LH, Wilfley DE, Kilanowski C, et al. Family-based behavioral treatment for childhood obesity implemented in pediatric primary care: A randomized clinical trial. JAMA 2023;329(22):1947–1956. DOI: 10.1001/jama.2023.8061.
________________________
© The Author(s). 2024 Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and non-commercial reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.