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Figure.  Trends in Obesity Prevalence Among US Adolescents Aged 10 to 19 Years by Household Income and Head of Household Education Level, 1999 to 2018
Trends in Obesity Prevalence Among US Adolescents Aged 10 to 19 Years by Household Income and Head of Household Education Level, 1999 to 2018

Obesity prevalence was adjusted for race and ethnicity, height, and marital status of the head of household. Obesity was defined as age- and sex-specific body mass index in the 95th percentile or greater based on the 2000 Centers for Disease Control and Prevention growth charts. Plots are adjusted differences in obesity prevalence between groups and changes in the differences over time (4-year cycles) relative to 1999 to 2002. Sampling weights were used to account for the National Health and Nutrition Examination Survey design and produce data representative of the general US population. FPL indicates federal poverty level.

Table.  Characteristics of 1999 to 2018 National Health and Nutrition Examination Survey Participants Aged 10 to 19 Years in This Study
Characteristics of 1999 to 2018 National Health and Nutrition Examination Survey Participants Aged 10 to 19 Years in This Study
1.
Skinner  AC, Ravanbakht  SN, Skelton  JA, Perrin  EM, Armstrong  SC.  Prevalence of obesity and severe obesity in US children, 1999-2016.   Pediatrics. 2018;141(3):e20173459. doi:10.1542/peds.2017-3459 PubMedGoogle ScholarCrossref
2.
Grossman  DC, Bibbins-Domingo  K, Curry  SJ,  et al; US Preventive Services Task Force.  Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement.   JAMA. 2017;317(23):2417-2426. doi:10.1001/jama.2017.6803 PubMedGoogle ScholarCrossref
3.
He  J, Zhu  Z, Bundy  JD, Dorans  KS, Chen  J, Hamm  LL.  Trends in cardiovascular risk factors in US adults by race and ethnicity and socioeconomic status, 1999-2018.   JAMA. 2021;326(13):1286-1298. doi:10.1001/jama.2021.15187 PubMedGoogle ScholarCrossref
4.
Ali  MK, Bullard  KM, Beckles  GL,  et al.  Household income and cardiovascular disease risks in U.S. children and young adults: analyses from NHANES 1999-2008.   Diabetes Care. 2011;34(9):1998-2004. doi:10.2337/dc11-0792 PubMedGoogle ScholarCrossref
5.
Decker  SL, Kostova  D, Kenney  GM, Long  SK.  Health status, risk factors, and medical conditions among persons enrolled in Medicaid vs uninsured low-income adults potentially eligible for Medicaid under the Affordable Care Act.   JAMA. 2013;309(24):2579-2586. doi:10.1001/jama.2013.7106 PubMedGoogle ScholarCrossref
6.
Hellevik  O.  Linear versus logistic regression when the dependent variable is a dichotomy.   Qual Quan. 2009;43(1):59-74. doi:10.1007/s11135-007-9077-3 Google ScholarCrossref
1 Comment for this article
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Racial Disparity in Obesity Among US Adolescents
Shabih Manzar, MD, MPH | Ochsner LSU Health, Shreveport, LA
I read with interest the recent article by Goto et al. [1] describing higher obesity (22.8%) prevalence among adolescents from low-socioeconomic status (SES) households. They further stated those adolescents were more likely to be non-Hispanic Black (21.7%) (Table)1. However, the data showed that the percentage of non-Hispanic White was more in low SES households. In the data (Table)[1], it was interesting to note that non-Hispanic White constituted 39.6 % of the low SES households.

If we categorically look at the data, we could better document the racial disparity. Among the 32.1 % (10.4 + 21.7) of total non-Hispanic
Black, 67% (21.7/32.1) were in the low-SES category (federal poverty level < 138%), while among non-Hispanic White (total =108, 68.4+39.6), 36.6% (39.6/108) were in the low-SES category. Applying Chi-square statistics (rounding numerical values to 10, 21, 68, 39), a significant difference, p<0.001, was noted (Table 1).

Racial/ethnic disparity in obesity among US youth has been shown [2], with increasing prevalence from 1999-2013. Among non-Hispanic White, it went up from 10.05% to 13.14%, and for non-Hispanic Black from 12.31 to 15.76%.


References:

1. Goto R, Nianogo R, Okubo Y, Inoue K. Evaluation of Obesity Trends Among US Adolescents by Socioeconomic Status, 1999-2018. JAMA Pediatr. 2022;176(9):937-940. doi:10.1001/jamapediatrics.2022.1838

2. An R. Racial/ethnic disparity in obesity among US youth, 1999-2013. Int J Adolesc Med Health. 2015;29(4):/j/ijamh.2017.29.issue-4/ijamh-2015-0068/ijamh-2015-0068.xml. Published 2015 Nov 4. doi:10.1515/ijamh-2015-0068


Table 1: Racial Disparity in the Prevalence of Obesity as per SES

Race and Ethnicity >138% FPL 138% FPL
Non-Hispanic Black 10.4 (10) 21.7 (21)
Non-Hispanic White 68.4 (68) 39.6 (39)

FPL- Federal Poverty Level
SES- Socioeconomic status
CONFLICT OF INTEREST: None Reported
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Research Letter
June 21, 2022

Evaluation of Obesity Trends Among US Adolescents by Socioeconomic Status, 1999-2018

Author Affiliations
  • 1Department of Pediatrics, University of Tokyo Hospital, Tokyo, Japan
  • 2Department of Epidemiology, University of California, Los Angeles
  • 3Department of Social Medicine, National Center for Child Health and Development, Tokyo, Japan
  • 4Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
JAMA Pediatr. 2022;176(9):937-940. doi:10.1001/jamapediatrics.2022.1838

The high prevalence of obesity among US adolescents is a public health concern,1 as obesity is a risk factor for cardiovascular disease.2 An association between obesity and low socioeconomic status (SES) was observed in a 2021 study of trends among US adults.3 However, obesity trends by SES among adolescents have not been fully described since 2008.4 We evaluated obesity trends among US adolescents from 1999 to 2018, stratified by household income and head of household education level.

Methods

The Kyoto University Institutional Review Board approved this cross-sectional study. Data were extracted from the 1999-2018 National Health and Nutrition Examination Surveys (NHANES). Written informed consent was obtained from adults (aged ≥18 years), and parental consent and child assent were obtained for adolescents (aged 10-17 years) for NHANES participation. This study followed the STROBE reporting guideline.

Obesity among adolescents (aged 10-19 years) was defined as age- and sex-specific body mass index greater than or equal to the 95th percentile based on the 2000 Centers for Disease Control and Prevention growth charts.2 Individuals were stratified by household income (≤138% vs >138% federal poverty level)5 and head of household education level. Race and ethnicity data were included owing to their association with obesity prevalence among US children and adolescents.

We first described 1999-2018 trends in obesity prevalence in 4-year increments stratified by income and education. We then investigated the association of SES and obesity prevalence using ordinary least-squares regressions with robust SEs,6 adjusting for race and ethnicity, height, and marital status of the head of household. After fitting the models, we estimated obesity prevalence under hypothetical exposure levels (income and education) with the observed distribution of covariates at each 4-year cycle. We included additive interaction terms between SES and each cycle (as a categorical variable) to evaluate changes over time in socioeconomic differences in obesity prevalence using Wald tests. We also examined linear trends in socioeconomic differences in obesity prevalence using the 4-year cycle as an ordinal variable. Sampling weights were used to account for the NHANES design in all analyses. Analyses were conducted using R, version 4.1.1.

Results

Of 21 296 individuals in this study, the mean (SD) age was 14.5 (2.8) years; 49.3% were female. Information on household income and head of household education levels was available for 19 465 (91.0%) and 20 302 (95.0%), respectively (Table). Adolescents from low-SES households were more likely to be non-Hispanic Black (21.7%), have obesity (22.8%), or have an unmarried parent (45.5%) (Table). The trend in adjusted obesity prevalence increased over 20 years, particularly among adolescents from low-SES households (Figure). Living in a low-income household was associated with a 4.2–percentage point increase in obesity prevalence (95% CI, 2.4-5.9), and lower head of household education level was associated with a 9.0–percentage point increase (95% CI, 7.2-10.7). The gap in obesity prevalence between adolescents from low-income households vs others was 6.4 percentage points greater (95% CI, 1.5-11.4) in 2015-2018 vs 1999-2002.

We found a similar trend for education, with 4.2–percentage point greater prevalence (95% CI, –0.8 to 9.3) for individuals with lower head of household education levels in 2015-2018 vs 1999-2002. When we assessed linear trends, the gap in obesity prevalence by income and education increased by an average of 1.5 (95% CI, 0.4-2.6) and 1.1 (95% CI, 0.0-2.3) percentage points every 4 years, respectively.

Discussion

The findings of this cross-sectional study suggest that socioeconomic disparities existed in obesity prevalence among US adolescents during 1999-2018, building on a previous study using NHANES 1999-2008 data,4 and suggest that socioeconomic disparities in obesity have widened during the last 2 decades. Obesity during adolescence can have immediate health consequences and long-term outcomes in adulthood.2 Accordingly, the larger obesity prevalence among adolescents from lower-SES households may exacerbate socioeconomic disparities in chronic diseases into adulthood.

Study limitations include potential unmeasured confounding and misclassification due to self-reported SES. Future studies should assess strategies to reduce socioeconomic disparities in obesity among US adolescents and evaluate their long-term health consequences.

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Article Information

Accepted for Publication: February 16, 2022.

Published Online: June 21, 2022. doi:10.1001/jamapediatrics.2022.1838

Corresponding Author: Kosuke Inoue, MD, PhD, Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan (inoue.kosuke.2j@kyoto-u.ac.jp).

Author Contributions: Drs Goto and Inoue had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Goto, Okubo, Inoue.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Goto, Inoue.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Goto, Okubo, Inoue.

Obtained funding: Inoue.

Administrative, technical, or material support: Goto, Inoue.

Supervision: Okubo, Inoue.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by grants 21K20900 and 22K17392 from the Japan Society for the Promotion of Science (Dr Inoue).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Skinner  AC, Ravanbakht  SN, Skelton  JA, Perrin  EM, Armstrong  SC.  Prevalence of obesity and severe obesity in US children, 1999-2016.   Pediatrics. 2018;141(3):e20173459. doi:10.1542/peds.2017-3459 PubMedGoogle ScholarCrossref
2.
Grossman  DC, Bibbins-Domingo  K, Curry  SJ,  et al; US Preventive Services Task Force.  Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement.   JAMA. 2017;317(23):2417-2426. doi:10.1001/jama.2017.6803 PubMedGoogle ScholarCrossref
3.
He  J, Zhu  Z, Bundy  JD, Dorans  KS, Chen  J, Hamm  LL.  Trends in cardiovascular risk factors in US adults by race and ethnicity and socioeconomic status, 1999-2018.   JAMA. 2021;326(13):1286-1298. doi:10.1001/jama.2021.15187 PubMedGoogle ScholarCrossref
4.
Ali  MK, Bullard  KM, Beckles  GL,  et al.  Household income and cardiovascular disease risks in U.S. children and young adults: analyses from NHANES 1999-2008.   Diabetes Care. 2011;34(9):1998-2004. doi:10.2337/dc11-0792 PubMedGoogle ScholarCrossref
5.
Decker  SL, Kostova  D, Kenney  GM, Long  SK.  Health status, risk factors, and medical conditions among persons enrolled in Medicaid vs uninsured low-income adults potentially eligible for Medicaid under the Affordable Care Act.   JAMA. 2013;309(24):2579-2586. doi:10.1001/jama.2013.7106 PubMedGoogle ScholarCrossref
6.
Hellevik  O.  Linear versus logistic regression when the dependent variable is a dichotomy.   Qual Quan. 2009;43(1):59-74. doi:10.1007/s11135-007-9077-3 Google ScholarCrossref
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