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Factors associated with early-onset androgenetic alopecia: A scoping review

  • Li-Ping Liu ,

    Contributed equally to this work with: Li-Ping Liu, Mary Adumo Wariboko

    Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing (LPL); (YML)

    Affiliations Department of Dermatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China, Institute of Regenerative Medicine, Jiangsu University, Zhenjiang, Jiangsu, China

  • Mary Adumo Wariboko ,

    Contributed equally to this work with: Li-Ping Liu, Mary Adumo Wariboko

    Roles Data curation, Investigation, Methodology, Writing – original draft

    Affiliations Department of Dermatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China, Institute of Regenerative Medicine, Jiangsu University, Zhenjiang, Jiangsu, China

  • Xiao Hu,

    Roles Formal analysis, Investigation, Validation, Writing – original draft

    Affiliation Department of Urology, The First People’s Hospital of Zhenjiang, Zhenjiang, Jiangsu, China

  • Zi-Han Wang,

    Roles Investigation, Writing – original draft

    Affiliations Department of Dermatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China, Institute of Regenerative Medicine, Jiangsu University, Zhenjiang, Jiangsu, China

  • Qian Wu,

    Roles Formal analysis, Visualization

    Affiliations Department of Dermatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China, Institute of Regenerative Medicine, Jiangsu University, Zhenjiang, Jiangsu, China

  • Yu-Mei Li

    Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing (LPL); (YML)

    Affiliations Department of Dermatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China, Institute of Regenerative Medicine, Jiangsu University, Zhenjiang, Jiangsu, China



Early-onset androgenetic alopecia (AGA) has been associated with various chronic conditions, including metabolic syndrome (MetS). Gaining a deep understanding of early-onset AGA may enable earlier intervention in individuals at high risks. This scoping review aims to explore the risk factors and etiology, associated conditions, and adverse effects on wellbeing in early-onset AGA.


Electronic literature searches were conducted in MEDLINE, EMBASE and CENTRIAL. Eligible studies included case-control, cohort, cross-sectional, and meta-analysis studies. Selected studies needed to clearly define early-onset AGA cases or include only cases starting before the age of 40 and compare them with appropriate controls. The exclusion criteria comprised editorials, commentaries, case series, and non-systematic reviews, among others. Data extraction involved collecting study characteristics, methodologies, main outcomes, and findings. Descriptive tables were used to summarize key information and relevant variables when necessary.


Among the 65 eligible articles, 67.69% were case-control studies and 78.46% evaluated only male patients. “Early-onset” was defined as cases developing before the age of 30 years in 43.08% of the studies. The Hamilton–Norwood scale was the most frequently used method for evaluating the severity of alopecia in men (69.23%). Reported risk factors for early-onset AGA included a family history of AGA, cigarette smoking, unhealthy dietary habits, and a high body mass index. Early-onset AGA may also be associated with hormonal profiles, 5α-reductase enzyme activity, androgen receptor genes, and some susceptibility loci. Comorbidities investigated included MetS, cardiovascular disease, insulin resistance, dyslipidemia, and Parkinson’s disease. Men with early-onset AGA may have reduced treatment efficacy with drug like rosuvastatin, metformin or lisinopril for dyslipidemia, prediabetes, or hypertension. Additionally, young men with AGA tended to suffer from psychological issues such as anxiety and low self-esteem compared to those without hair loss.


Early-onset AGA is a complex condition with various risk factors and etiology, associated comorbidities, and potential implications for treatment response and psychological health.


Androgenetic alopecia (AGA) is the most prevalent cause of non-scarring alopecia in adults, typically affecting the front and vertex regions in men and causing diffuse hair thinning over the central scalp in women [1]. The severity of AGA is commonly evaluated using the Hamilton–Norwood scale (HNS) in men [2] and the Ludwig classification in women [3]. Early-onset AGA is generally defined as AGA developing before the age of 30 [4, 5], 35 [6, 7] or 40 [8, 9] years; however, there is currently no unified definition. Although the frequency of AGA increases with age, the prevalence of early-onset cases is substantial, ranging from 19.2%-57.6% in different populations [1012]. In addition to harmfully affecting the patient’s appearance and quality of life [13, 14], AGA is closely associated with the risk of developing metabolic syndrome (MetS) [15, 16], which is a cluster of metabolic abnormalities including obesity, hyperlipidemia, insulin resistance (IR), and hypertension. A systematic review including 19 articles and 2,531 participants revealed a pooled odds ratio (OR) of 3.46 for the prevalence rate of MetS between individuals with AGA and controls [15]. Moreover, early-onset AGA has been associated with early markers of IR [6], carotid artery atherosclerosis [17], ischemic heart disease [18], and benign prostatic hyperplasia [19].

Considering the detrimental consequences and burden associated with these chronic disorders, more comprehensive characterization and in-depth understanding of early-onset AGA could aid in identifying individuals at high risk. This, in turn, would facilitate improved and earlier interventions, ultimately preventing long-term consequences during the early stages of life. This review aims to scope, collate and catalogue the existing literature on early-onset AGA. Specially, the focus will be on identifying risk factors and etiology, associated comorbidities and potential adverse effects on overall wellbeing.


We used the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) [20] for reporting this scoping review (S1 Table) and reported the flow of articles included in accordance with the Checklist. The study’s protocol was not previously published.

Research questions

The scoping review was guided by the following specific research questions. First, what are the risk factors associated with early-onset AGA? Second, what comorbidities are individuals with early-onset AGA at a higher risk of developing? Third, are there any additional adverse effects on patient well-being associated with early-onset AGA?

Search strategy

Electronic literature searches were performed in MEDLINE, EMBASE and CENTRIAL on July 28, 2023. The searches were conducted for studies published in the English language, without imposing any specific restrictions on the publication period. The search terms used in the database are shown in S2 Table. EndNote citation management software was utilized for managing the literature.

Study selection

The search strategy is shown in Fig 1. The inclusion criteria for articles were as follows: 1) Research articles based on case control, cohort, cross-sectional design, or meta-analysis that clearly described the definition of “early-onset” of AGA. Individuals without alopecia or with late-onset AGA were used as controls. Studies were also included if the definition of “early-onset” was not explicitly described but all the AGA cases involved patients under the age of 40 (the maximum age limit determined according to the initial literature review) and stratified analysis was conducted based on gender, alopecia severity, or other case features; 2) Articles had to be published in English; 3) There were no restrictions on gender or the year of publication.

The following types of papers were excluded from this scoping review: 1) letters, editorials, commentaries, unpublished manuscripts, dissertations, government reports, books and book chapters, conference proceedings, meeting abstracts, lectures and addresses, consensus development statements; 2) case reports; 3) case series; 4) qualitative studies; 5) non-systematic reviews; 6) guideline statements; 7) protocols for proposed systematic reviews or meta-analyses; 8) animal studies; 9) cell culture studies; 10) studies on the efficiency and side effects of AGA treatment.

The literature search was performed by one investigator (Li-Ping Liu). After the duplicates were removed, two reviewers (Li-Ping Liu and Mary Adumo Wariboko) screened all titles, abstracts and full texts independently based on the inclusion and exclusion criteria and solved disagreements by discussion.

Data extraction

The aim of this review is to systematically map and aggregate the available evidence, not to critically analyzing the quality of individual studies. Therefore, a descriptive analysis was performed to examine the characteristics of the included literature. Data extracted were summarized in a narrative report encompassing the following themes: study characteristics and methodologies (including year of publication, study region, research design, participant characteristics); findings related to the research questions (including main outcomes and study results). The key information and relevant variables were summarized in a descriptive table when necessary. Microsoft Excel and GraphPad Prism were employed for data analysis and graphing purposes.


Study selection and data extraction

The search produced 1,147 records (MEDLINE: n = 395, EMBASE: n = 590, CENTRIAL: n = 162) (Fig 1). When duplicated studies (n = 376) were removed, 771 studies were used for further screening. Studies were excluded if there were irrelevant (n = 623), conference abstract (n = 21), non-systematic reviews (n = 15), case reports or case series (n = 11), commentary (n = 1), lacking an appropriate control group (n = 26), non-English (n = 3), or focused on treatment side effects (n = 6). Ultimately, 65 eligible articles were identified.

Characteristics of included studies

The majority of the studies included in this scoping review were conducted using a case-control design (67.69%, n = 44). Some studies utilized a cross-sectional design (24.62%, n = 16), cohort design (1.54%, n = 1), or were systematic reviews and meta-analyses (6.15%, n = 4). The number of published articles showed a significant increase after 2020 (Fig 2). The studies originated from 21 different countries, with the highest number of research studies conducted in India (Fig 3). The majority of studies only included male participants (78.46%, n = 51).

Definition of early-onset AGA and methods for severity evaluation

Among the included studies, 43.08% (n = 28) defined “early-onset AGA” as cases developing before the age of 30 years, while 35.38% (n = 23) included cases developing before 35 or 36 years (Fig 4). The methods applied to evaluate the severity of baldness varied. The HNS was the most frequently used in men (69.23%, n = 45) while the Ludwig scale was predominantly used most in women (10.77%, n = 7). In addition, the basic and specific classification (BASP) scale and the Ebling scale were each used in 4 studies, respectively.

Fig 4. Percentage of studies using age limitation for early-onset AGA.

Topics of included studies

To address the three research questions mentioned above, the topics covered in the included studies were classified into four main categories: investigation of risk factors and etiology (23.08%, n = 15), association with potential comorbidities (61.54%, n = 40), medication effects related to early-onset AGA (10.77%, n = 7) and the impacts of alopecia on patient wellbeing (6.15%, n = 4). The last two categories focused on the potential adverse effects of early-onset AGA on patient wellbeing, with a total of 11 studies addressing this aspect.

Risk factors and etiology of early-onset AGA

Fifteen articles focused on identifying the risk factors [5, 10, 12, 2123] or etiology [4, 8, 2430] for early-onset AGA. Several risk factors were found to be significantly associated with early-onset AGA. These included family history [10, 12, 23], lifestyle factors such as cigarette smoking [10, 21] and unhealthy dietary habits [10]. Additionally, severe AGA was more prevalent in men aged between 30 and 40 years with higher body mass index (BMI) [22]. For young female cases aged 15 to 18 years, predictors of early-onset AGA included irregular menses, a history of thyroid disease, and hirsutism [12].

Two studies investigated the hormonal profile of men with early-onset AGA [4, 24], considering that AGA is an androgen-mediated disease [1]. Sanke S, et al. [4] found that men with early-onset AGA had significantly elevated levels of testosterone, dehydroepiandrosterone sulfate (DHEAS), luteinizing hormone (LH), prolactin, free androgen index and LH/follicle-stimulating hormone (FSH) ratio, while mean levels of FSH and sex hormone binding globulin (SHBG) were decreased. These findings suggest that early-onset AGA in men could be considered as a phenotypic equivalent of polycystic ovary syndrome (PCOS) in women, as it causes similar hormonal changes. However, another study showed similar levels of LH, FSH and SHBG between AGA cases and the control group, although levels of serum free testosterone and dihydrotestosterone were significantly higher in AGA patients [24]. Therefore, the consistency of LH and FSH levels appears to be inconclusive.

Because excessive activity of 5α-reductase in hair follicles is believed to be a contributing factor to AGA [31], the role of this enzyme in early-onset cases was evaluated in three studies. Among hyperandrogenic women, increased 5α-reductase activity in the scalp was found to be associated with alopecia [25]. However, no statistical significance was observed in the mean mRNA levels of three types of 5α-reductase isozymes in plucked hairs between women with AGA and controls [26]. Furthermore, no significant differences were found in allele, genotype, or haplotype frequencies for restriction fragment length polymorphisms of 5 α-reductase enzyme genes (SRD5A1 and SRD5A2) between young bald men and older non-bald men [27].

Genetic predisposition plays a crucial role in the development of AGA. Hillmer AM, et al. [28] explored the contribution of the genetic variability in androgen receptors and found that it was the cardinal prerequisite to the development of early-onset AGA. Additionally, six susceptibility loci (rs12565727, rs9287638, rs2073963, rs6945541, s12373124, rs10502861) and two AGA loci on the X chromosome and chromosome 20 were identified [8]. Moreover, forty-nine single-nucleotide polymorphisms (SNPs) located around PPARGC1A, ABCC4, CYP11B2, FSHB, and CYP19A1 were found to be significant contributors to AGA [29]. Furthermore, a genetic model was established to predict AGA risk based on SNPs identified from previous genome-wide association study [30]. The model achieved an accuracy level of 0.74 in predicting the risk of early-onset AGA. It was found that 55.8% of the genetic liability for early-onset AGA can be attributed to common autosomal SNPs, while 23.3% is attributed to X-chromosome SNPs.

Conditions associated with early-onset AGA

A total of 40 articles examined the potential comorbidities associated with early-onset AGA (Fig 5). The majority of them focused on the metabolic diseases (n = 30) [6, 7, 9, 15, 17, 18, 3255], such as MetS, cardiovascular disease (CVD), IR, dyslipidemia. Other associated conditions included prostatic hyperplasia or prostatic cancer (PC) [19, 5658] (n = 4), hyperuricemia [59, 60] (n = 2), gonadal and adrenal related problems [61, 62] (n = 2), amyotrophic lateral sclerosis [63] (n = 1), and Parkinson’s disease and fertility [8] (n = 1) (Table 1).

Fig 5. Potential conditions associated with early-onset AGA.

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While some studies did not find significant difference between AGA patients and healthy controls in terms of MetS risk [32], IR [3234], lipid profile [34], and BMI [34], the majority of studies (72.50%, n = 29) reported that patients with early-onset AGA had a higher risk to develop MetS [15, 17, 33, 3544], CVD [9, 18, 40, 4446], IR [6, 43, 4749], hyperglycemia [50], dyslipidemia [38, 5153], hypertension [7], high BMI and obesity [18, 54, 55, 61]. A systematic review including nine studies and 970 participants found that a younger onset age (before 36 years) was associated with a higher risk with MetS, with a pooled OR of 3.88 (P<0.001) [15]. Moreover, positive associations were also found between AGA severity and the risk of metabolic diseases [9, 32, 34, 46, 48, 49, 54, 55] in all but one study [42]. Two other systematic reviews indicated that early-onset cases might represent a phenotypic sign of male PCOS-equivalent [51] and be associated with an increased risk of developing Parkinson’s disease [8]. Four studies focused on the link between early-onset AGA and PC development, but their results varied greatly [19, 5658].

Drug effects

Seven articles, conducted by the same research group in Poland, investigated whether the presence of early-onset AGA altered the efficacy of specific medications for specific disorders (Table 2). These were all case-control studies. The results showed that men with early-onset AGA may experience less benefit from rosuvastatin [64], metformin [65, 66], lisinopril [67], levothyroxine [68], Vitamin D [69], or bromocriptine [70] when treating dyslipidemia, prediabetes, hypertension, autoimmune hypothyroidism, autoimmune thyroiditis, or prolactin excess, respectively, compared to the contemporaries without alopecia. However, one exception was noted, as the impact of metformin on gonadotroph secretory function appeared to be stronger in men with early-onset AGA compared to those with normal hair growth [66].

Impacts of early-onset AGA on patient wellbeing

Hair plays a significant role in an individual’s self-image and can affect how one is perceived in social perceptions. A systematic review and meta-analysis of 41 studies with 7,995 patients revealed that AGA was associated with moderate impairment of both health-related quality of life and emotional wellbeing [71]. The detrimental impacts on self-esteem and specific aspects of psychological adjustment are more pronounced in women compared to men [72]. Four included studies evaluated the negative effects of alopecia on young patients [7376]. However, all of these studies exclusively enrolled male participants. Three of these studies were descriptive cross-sectional studies focused on psychological complications. They found that young men under 30 years old affected by AGA tended to suffer from anxiety and low self-esteem compared to their peers without hair loss [73]. It is also reported that individuals with moderate to severe psychosocial morbidity may have an increased risk of sexual dysfunction [75]. Furthermore, statistically significant associations were observed between the severity of AGA and the severity of depression, loneliness, and levels of internet addiction levels [74].


This scoping review identified several reported risk factors for early-onset AGA, including family history, cigarette smoking, unhealthy dietary habits, high BMI, and irregular menses. Additionally, early-onset AGA may also be associated with hormonal profiles, 5α-reductase enzyme activity, androgen receptor gene, and some newly discovered susceptibility loci. There results highlight the multifactorial nature of the AGA, indicating that a combination of genetic, hormonal, behavioral and lifestyle factors contribute to its development. Additionally, the available studies also demonstrated a close link between early-onset AGA and MetS, CVD, IR, and dyslipidemia. Interestingly, these chronic diseases are also strongly related to the risk factors for early-onset AGA, such as smoking [77, 78] and dietary habits [7981]. Therefore, this emphasizes the importance of lifestyle modifications in individuals with early-onset AGA to prevent these co-existing health conditions. Furthermore, men with early-onset AGA may benefit to a lesser degree from treatments such as rosuvastatin [64], metformin [65, 66], or lisinopril [67] compared to individuals with normal hair growth. Therefore, young patients with AGA may not only be more susceptible to developing metabolic diseases, but also less responsive to certain treatments. These findings are of clinical significance because AGA can be easily recognized based on clinical features. Tailored treatment approaches may be necessary for this specific population. Overall, the findings underscore the importance of early detection, risk assessment, and comprehensive management of early-onset AGA. Both physicians and patients should consider not only the hair loss condition itself but also its potential associations with other health conditions. Compared to published systematic review and meta-analysis on early-onset AGA, this scoping review provides a more comprehensive understanding of AGA by examining multiple perspectives. It goes beyond focusing solely on a specific factor [51] or the correlation with a specific disease [15], offering a more holistic view of AGA.

Several limitations should be noted. Firstly, our inclusion criteria only considered articles published in English, which may introduce publication bias and limit the generalizability of our findings. Secondly, the quality of included studies were not appraised, which could potentially include studies with lower methodological quality. Thirdly, lack of data synthesis may limit the ability to provide precise statistical information and draw conclusive inferences from the results. Lastly, the heterogeneity in study design, the definition of “early-onset” and methodologies used for AGA evaluation among the included studies can also be considered limitations. The lack of standardized criteria and inconsistency may introduce variability in the findings and make comparisons between studies challenging.


These findings indicate that early-onset AGA has a complex and multifactorial cause, and it may serve as an indicator of underlying systemic health issues. Furthermore, certain drug treatments may be less effective in men with early-onset AGA, highlighting the importance of considering AGA in the management of these conditions. Additionally, the impact of AGA on psychological well-being should be emphasized in young men.


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