Androgenic alopecia patients at increased risk of developing metabolic syndrome

The association of androgenetic alopecia with metabolic syndrome has been investigated in several studies, with conflicting results.

Researchers conducted a meta-analysis to quantitatively evaluate the risk grade of metabolic syndrome and the metabolic profile in patients with androgenetic alopecia compared with controls. In total, 19 articles (2,531 participants) satisfied the inclusion criteria.

The pooled odds ratio for the prevalence rate of metabolic syndrome between the group with androgenetic alopecia and controls was 3.46 (95% CI 2.38–5.05; p < 0.001). Female sex, early-onset, and African ethnicity were associated with an increased risk of metabolic syndrome.

Furthermore, patients with androgenetic alopecia had significantly poorer metabolic profiles, such as body mass index, waist circumference, fasting glucose, blood lipids, and blood pressure.

It is important for physicians to screen metabolism-related indicators in patients with androgenetic alopecia. More rigorously designed studies and larger sample sizes are required in future studies.

The results of the study are:

This systematic review and meta-analysis found that compared with controls, patients with androgenic alopecia (AGA) had 3.46 times the risk of developing metabolic syndrome, and AGA patients with metabolic syndrome had worse metabolic profiles. Younger age of onset, female sex, and African ancestry was associated with higher odds of developing metabolic syndrome.

Thus, the study concludes that patients with AGA have an increased risk of developing metabolic syndrome, and appropriate counselling and screening may be warranted.

Reference:

Systematic Review and Meta-analysis of the Association Between Metabolic Syndrome and Androgenetic Alopecia by Yueqi Qiu et. al published in the Acta Dermato-Venereologica

DOI: https://doi.org/10.2340/actadv.v101.1012

Keywords:

Patients, AGA, increased risk, developing, metabolic syndrome, Acta Dermato-Venereologica, Yueqi Qiu, Xingyu Zhou, Siqi Fu, Shuaihantian Luo, Yaping Li