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The US Preventive Services Task Force recently released a recommendation on screening for prediabetes and type 2 diabetes among adults,¹ but no recommendation has been issued for youths to date. A recent study² estimated that among youths aged 12 to 19 years, approximately 1 in 5 had prediabetes, with large variations across sociodemographic characteristics. However, trends in the prevalence of prediabetes among youths and associated disparities by population subgroups over the past 2 decades have not been reported to our knowledge, and such information is important for future diabetes prevention. In this study, we assessed trends in prediabetes among US youths from 1999 through 2018.

This survey study used data from 10 cycles of the National Health and Nutrition Examination Survey (NHANES) from 1999-2000 through 2017-2018 and combined every 2 consecutive cycles to obtain sufficient sample sizes. We included youths aged 12 to 19 years who completed the interview and examination. NHANES is a series of cross-sectional surveys using a complex, multistage probability design to sample the civilian, noninstitutionalized population. The NHANES protocol was approved by the US Centers for Disease Control and Prevention National Center for Health Statistics Ethics Review Board, and all participants provided written informed consent, or assent was obtained from participants or their guardians, respectively. This study was exempt from the Mount Sinai institutional review board review because it used publicly deidentified data sets. Details on NHANES survey methods and analytic methods are documented elsewhere.³ This study followed the American Association for Public Opinion Research () reporting guideline.

Sociodemographic variables included sex, age, race and ethnicity (Hispanic, non-Hispanic Asian, non-Hispanic Black, and non-Hispanic White), parental educational level (less than high school, high school, and some college and above), income level (family income to poverty ratio <1.3, 1.3 to <3.0, and ≥3.0; adjusted for household size and based on poverty guidelines specific to the survey year), household food-security status (full, marginal, low, and very low; categorized based on the US Household Food Security Survey Module developed by the US Department of Agriculture⁴), and body mass index category (underweight or normal weight, overweight, and obesity; age- and sex-specific body mass index z scores were calculated using US Centers for Disease Control and Prevention reference data⁵). Information on race and ethnicity was collected by trained NHANES interviewers according to the fixed categories provided by the National Center for Health Statistics. Blood samples were obtained by trained phlebotomists according to a standardized protocol, and data were recorded directly into a computerized database. Prediabetes was defined as no recorded diagnosis of diabetes but a hemoglobin A_1c level of 5.7% to 6.4% (to convert to proportion of total hemoglobin, multiply by 0.01) or a fasting plasma glucose level of 100 mg/dL to 125 mg/dL (to convert to millimoles per liter, multiply by 0.02586).²

Survey analysis procedures were used to account for sampling weights, stratification, and clustering in the NHANES complex sampling design to derive nationally representative estimates. Logistic regression was used to estimate trends by treating the survey cycle as a continuous variable. A survey-weighted Wald F statistic was used to test for the interaction. All analyses were performed using Stata, version 14 (StataCorp LLC). Significance was set at 2-sided P = .05. Data were analyzed from August to September 2021.

A total of 6598 youths (mean [SD] age, 15.5 [2.76] years; 3412 [51.2% weighted] male) were included in this analysis (Table 1). The mean response rate was 79.2% (range, 59.3%-86.4%). Overall, the prevalence of prediabetes among US youths increased significantly from 11.6% (95% CI, 9.49%-14.1%) in 1999-2002 to 28.2% (95% CI, 23.3%-33.6%) in 2015-2018 (Table 2). The increasing trend was observed across population subgroups. Disparities in prevalence of prediabetes remained stable and were most pronounced in subgroup analyses of sex and body mass index category. For example, from 1999-2002 to 2015-2018, the prevalence of prediabetes increased from 15.8% (95% CI, 12.3%-20.1%) to 36.4% (95% CI, 30.1%-43.1%) among male youths and from 7.1% (95% CI, 5.1%-9.9%) to 19.6% (95% CI, 14.7%-25.7%) among female youths (P < .001 for trend). During the same period, the prevalence increased from 9.41% (95% CI, 7.50%-11.8%) to 24.3% (95% CI, 18.9%-30.7%) among youths with underweight or normal weight (P < .001 for trend), from 15.3% (95% CI, 9.45%-23.8%) to 27.5% (95% CI, 19.7%-36.9%) among youths with overweight (P = .005 for trend), and from 18.2% (95% CI, 12.8%-25.2%) to 40.4% (95% CI, 30.2%-51.5%) among youths with obesity (P < .001 for trend).

In this survey study, the prevalence of prediabetes increased significantly among US youths from 1999 to 2018. Several limitations should be noted. First, there was only 1 measure of blood biomarkers for prediabetes, and thus, seasonal variations were not accounted for in the analysis. Second, we did not use the oral glucose tolerance test to define prediabetes because the information was not available in some of the NHANES cycles; thus, our results may have underestimated the prevalence of prediabetes. Third, owing to the small sample sizes, the statistical power might not have been sufficient to detect an interaction.

Accepted for Publication: December 9, 2021.

Published Online: March 28, 2022. doi:10.1001/jamapediatrics.2022.0077

Corresponding Author: Junxiu Liu, PhD, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 (junxiu.liu@mountsinai.org).

Author Contributions: Dr Junxiu Liu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Junting Liu, Junxiu Liu.

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

Drafting of the manuscript: Junting Liu, Junxiu Liu.

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

Statistical analysis: Junting Liu, Junxiu Liu.

Obtained funding: Li, Zhang, Yi.

Administrative, technical, or material support: Junxiu Liu.

Supervision: Yi, Junxiu Liu.

Conflict of Interest Disclosures: None reported.

Funding/Support: This research was supported by grant QML20191302 from the Beijing Hospitals Authority Youth Programme (Dr Junting Liu); grant R01HL141427 from the National Heart, Lung and Blood Institute, National Institutes of Health (Drs Li and Yi); and grant R01MD013886 from the National Institute on Minority Health and Health Disparities, National Institutes of Health (Dr Zhang).

Role of the Funder/Sponsor: The funders 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.