Abstract
Purpose
Previous research suggests that poor nutrition, physical activity, sleep, and social/emotional
climate are associated with weight gain. However, few empirical studies have examined
how these factors relate to each other in adolescents who are later obese. Are these
factors uniformly present, or do some co-occur or occur independently? This study
seeks to identify subgroups of obese individuals at ages 24–32 years who exhibited
unique, co-occurring behavioral and emotional contexts for obesity at ages 14–17 years.
Methods
To identify subgroups of behavioral and contextual profiles in adolescence, the study
applies latent class analysis to a sample of individuals who were obese in the fourth
wave of the National Longitudinal Study of Adolescent to Adult Health (Add Health,
N = 1,889). The study then explored covariates (e.g., gender, race) of class membership.
Results
Considerable heterogeneity exists in risk profiles of adolescents obese as adults.
For example, 21.1 percent of the sample is in a class with no differentiating risk
factors, whereas two classes containing 22.1 percent of the sample exhibit high levels
of depression, and nearly all the emotional factors are considered. Although some
covariates are predictive of class membership, clear patterns are difficult to discern.
However, poor physical health is clearly predictive of membership in the classes exhibiting
a high risk of depression.
Discussion
Clinicians should be aware that at younger ages, people who are ultimately obese display
a range of factors linked to obesity. Although some exhibit behaviors such as high
screen time and processed food consumption, others exhibit mainly poor social/emotional
climate.
Keywords
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References
- The renin–angiotensin–aldosterone system as a link between obesity and coronavirus disease 2019 severity.Obes Rev. 2020; 21: e13077
- Prevalence of obesity and severe obesity among adults: United States, 2017–2018.National Center for Health Statistics, Hyattsville, MD2020
- ([Dataset])The national longitudinal study of adolescent to adult health.University of North Carolina, Chapel Hill, NC2018
- Fruit juice intake predicts increased adiposity gain in children from low-income families: Weight status-by-environment interaction.Pediatrics. 2006; 118: 2066-2075
- Food portion patterns and trends among US children and the relationship to total eating occasion size, 1977–2006.J Nutr. 2011; 141: 1159-1164
- Dietary patterns and longitudinal change in body mass in European children: A follow-up study on the IDEFICS multicenter cohort.Eur J Clin Nutr. 2013; 67: 1042-1049
- Differences in home food and activity environments between obese and healthy weight families of preschool children.J Nutr Educ Behav. 2013; 45: 222-231
- Fast-food restaurant advertising on television and its influence on childhood obesity. vol. I10. National Bureau of Economic Research, Cambridge, MA2005: 1-45
- The association of neighborhood design and recreational environments with physical activity.Am J Health Promot. 2005; 19: 304-309
- The association between community physical activity settings and youth physical activity, obesity, and body mass index.J Adolesc Health. 2010; 47: 496-503
- Sleep duration and adolescent obesity.Pediatrics. 2013; 131: e1428-e1434
- The protective role of family meals for youth obesity: 10-year longitudinal associations.J Pediatr. 2015; 166: 296-301
- Is frequency of shared family meals related to the nutritional health of children and adolescents?.Pediatrics. 2011; 127: e1565-e1574
- Does depression cause obesity? A meta-analysis of longitudinal studies of depression and weight control.J Health Psychol. 2008; 13: 1190-1197
- Associations between overweight and obesity with bullying behaviors in school-aged children.Pediatrics. 2004; 113: 1187-1194
- Peer victimization, psychosocial adjustment, and physical activity in overweight and at-risk-for-overweight youth.J Pediatr Psychol. 2007; 32: 80-89
- Identifying patterns of eating and physical activity in children: A latent class analysis of obesity risk.Obesity. 2011; 19: 652-658
- Clustering patterns of physical activity, sedentary and dietary behavior among European adolescents: The HELENA study.BMC Public Health. 2011; 11: 328
- Latent class analysis of obesity-related characteristics and associations with body mass index among young children.Obes Sci Pract. 2020; 6: 390-400
- Eating behaviour, physical activity, TV exposure and sleeping habits in five year olds: A latent class analysis.BMC Pediatr. 2021; 21: 180
- The national longitudinal study of adolescent to adult health: Research design.(Available at:)http://www.cpc.unc.edu/projects/addhealth/designDate accessed: March 1, 2021
- Uncovering peer effects mechanisms with weight outcomes using spatial econometrics.Soc Sci J. 2014; 51: 645-651
- Nutrition and the health of young people.(Available at:)
- How much physical activity do children need?.(Available at:)
- The media, children, and adolescents.(Available at:)https://www.acpeds.org/the-college-speaks/position-statements/parenting-issues/the-media-children-and-adolescentsDate: 2014Date accessed: March 1, 2021
- Teens and sleep.(Available at:)
- Screening for adolescent depression: A comparison of depression scales.J Am Acad Child Adolesc Psychiatry. 1991; 30: 58-66
- Software.(Available at:)
- McCutcheon A.L. Latent Class Analysis. no. 64. Sage, Newbury Park, CA1987
- A new SAS procedure for latent transition analysis: Transitions in dating and sexual risk behavior.Dev Psychol. 2008; 44: 446-456
- Sensitivity and specificity of information criteria. The Methodology Center and Department of Statistics.The Pennsylvania State University, Penn State, PA2012
- Effect size, statistical power, and sample size requirements for the bootstrap likelihood ratio test in latent class analysis.Struct Equ Modeling. 2014; 21: 534-552
- Latent class analysis: A guide to best practice.J Black Psychol. 2020; 46: 287-311
- Finite mixture models.John Wiley & Sons, New York, NY2004
- Addressing childhood obesity: Opportunities for prevention.Pediatr Clin North Am. 2015; 62: 1241-1261
- Risk factors for overweight/obesity in preschool children: An ecological approach.Child Obes. 2013; 9: 399-408
- Evidence of a possible link between obesogenic food advertising and child overweight.Obes Rev. 2005; 6: 203-208
- Children’s food consumption during television viewing.Am J Clin Nutr. 2004; 79: 1088-1094
- Depression and type 2 diabetes: Inflammatory mechanisms of a psychoneuroendocrine co-morbidity.Neurosci Biobehav Rev. 2012; 36: 658-676
- Communities of color creating health environments to combat childhood obesity.AJPH Pract. 2016; 106: 79-86
Article info
Publication history
Published online: February 11, 2022
Accepted:
November 23,
2021
Received:
May 27,
2021
Footnotes
Conflicts of interest: The authors have no conflicts of interest to declare.
Identification
Copyright
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