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. 2023 Apr 1;159(4):411-418.
doi: 10.1001/jamadermatol.2023.0002.

Trends in Prevalence and Incidence of Alopecia Areata, Alopecia Totalis, and Alopecia Universalis Among Adults and Children in a US Employer-Sponsored Insured Population

Arash Mostaghimi  1 , Wei Gao  2 , Markqayne Ray  3 , Lauren Bartolome  4 , Travis Wang  2 , Christopher Carley  2 , Nicolae Done  2 , Elyse Swallow  2
Affiliations

Trends in Prevalence and Incidence of Alopecia Areata, Alopecia Totalis, and Alopecia Universalis Among Adults and Children in a US Employer-Sponsored Insured Population

Arash Mostaghimi et al. JAMA Dermatol. .

Abstract

Importance: Alopecia areata (AA) is characterized by nonscarring hair loss of the scalp, face, and/or body. Alopecia totalis (AT) and alopecia universalis (AU) involve complete loss of the scalp and body hair, respectively. The epidemiology of AA in the US remains unclear, having previously been extrapolated from older studies that were limited to specific geographic areas or clinical settings, or from self-reported data.

Objective: To estimate the annual prevalence and incidence of AA and AT and/or AU (AT/AU) in the US.

Design, setting, and participants: This retrospective, population-based cohort study was conducted from January 2016 to December 2019 and included enrollees in the IBM MarketScan Commercial Claims and Encounters and Medicare Supplemental databases and their dependents, with plan enrollment during each study calendar year and the year prior.

Exposures: Prevalent cases were identified by 1 or more claims for AA or AT/AU (International Statistical Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] codes L63.x, L63.0, L63.1) during each year of interest or the year prior. Incident cases were identified by 1 or more claims for AA or AT/AU during a specific year and no diagnosis the year prior.

Main outcomes and measures: Annual incidence and prevalence rates were calculated and stratified by age, sex, and region. National employer-sponsored insurance population estimates were obtained using population-based weights.

Results: Among eligible patients (2016: n = 18 368 [mean (SD) age, 40.6 (17.9) years; 12 295 women (66.9%)]; 2017: n = 14 372 [mean (SD) age, 39.6 (17.7) years; 9195 women (64.0%)]; 2018: n = 14 231 [mean (SD) age, 38.9 (17.3) years; 8998 women (63.2%)]; 2019: n = 13 455 [mean (SD) age, 39.1 (17.4) years; 8322 women (61.9%)]), AA prevalence increased from 0.199% (95% CI, 0.198%-0.200%) in 2016 to 0.222% (95% CI, 0.221%-0.223%) in 2019. Roughly 5% to 10% of prevalent and incident cases of AA were AT/AU. The prevalence of AT/AU increased from 0.012% (95% CI, 0.012%-0.013%) to 0.019% (95% CI, 0.018%-0.019%) from 2016 to 2019. Incidence of AA per 100 000 person-years ranged from 87.39 (95% CI, 86.84-87.96) in 2017 to 92.90 (95% CI, 92.35-93.45) in 2019. Incidence of AT/AU ranged from 7.09 (95% CI, 6.94-7.25) in 2017 to 8.92 (95% CI, 8.75-9.09) in 2016. Prevalence and incidence of AA and AT/AU were higher among female vs male individuals, adults vs children and adolescents, and in the Northeast vs other regions.

Conclusions and relevance: The results of this cohort study suggest that these recent AA prevalence and incidence estimates could help improve current understanding of the disease burden. Further research is warranted to elucidate subpopulation differences and trends in AA in the broader US population.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Mostaghimi reported personal fees from Pfizer, hims, Digital Diagnostics, Concert, Lilly, AbbVie, Equillium, Boehringer Ingelheim, and LEO and grants from Pfizer outside the submitted work. Drs Gao and Done reported grants from Pfizer and employment with Analysis Group, Inc during the conduct of the study. Drs Ray and Bartolome reported being an employee of and stockholder in Pfizer. Dr Wang reported personal fees from Pfizer and employment with Analysis Group, Inc during the conduct of the study. Dr Carley reported being a former employee of Analysis Group, Inc during the conduct of the study. Dr Swallow reported being an employee of Analysis Group, Inc during the conduct of the study.

Figures

Figure 1.
Figure 1.. Study Design
AA indicates alopecia areata; AT, alopecia totalis; AU, alopecia universalis.
Figure 2.
Figure 2.. Annual Prevalence of Alopecia Areata (AA) and Alopecia Totalis (AT)/Alopecia Universalis (AU) by Sex and Age Group From 2016 to 2019
Individual weights in each year (2016-2019) were assigned using data from the American Community Survey based on census division, age, sex, and policy holder status. Annual prevalence was calculated as the number of patients who had at least 1 inpatient or outpatient claim with a diagnosis for AT/AU during the year of analysis or the year prior divided by the number of patients who were continuously enrolled during that period. Binomial exact intervals are shown. The annual prevalence rate during each subsequent calendar year was compared with the annual prevalence rate in 2016 using weighted logistic regression models, with prevalent case status as the dependent variable (cases were coded as 1, noncases were coded as 0) and calendar year indicators included as covariates.
Figure 3.
Figure 3.. Incidence Rate per 1000 Person-Years of Alopecia Areata (AA) by Sex and Age Group From 2016 to 2019
Individual weights in each year (2016-2019) were assigned using data from the American Community Survey based on census division, age, sex, and policy holder status. Incidence rate was calculated as the number of patients who had at least 1 inpatient or outpatient claim with a diagnosis for AA during the year of analysis but not the year prior divided by the total patient-years of continuous enrollment during that period. Wilson score intervals are shown. Changes in annual incidence rates from 2016 onward were estimated using weighted Poisson regression models with a log link function, with incident case counts as the dependent variable, the log of the population at risk included as an offset term, and binary indicators for calendar year included as covariates.
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