Investigating the Relationship Between Androgenetic Alopecia and Hair Shape, Color, and Thickness: A Case‐Control Study

ABSTRACT

Background and Aims

Androgenetic alopecia is the most common cause of hair loss in both men and women. The aim of this case‐control study was to investigate the role of phenotype (hair shape, thickness, and color) and demographic characteristics, including smoking history, in the development of androgenetic alopecia.

Methods

In this case‐control study, participants were divided into two groups: patients diagnosed with androgenetic alopecia (case group) and individuals without hair loss (control group). Data on demographic characteristics (age, gender), hair phenotype (shape, thickness, and color), and smoking history were collected. The case group consisted of individuals diagnosed with androgenetic alopecia at a skin and hair clinic, while the control group included patients visiting the clinic for other skin conditions. Data were analyzed using SPSS software.

Results

The study compared data from 50 patients with androgenetic alopecia and 50 control participants. Smoking was found to increase susceptibility to alopecia, and a significant association was observed between lighter hair color and androgenetic alopecia. No significant relationship was found between hair thickness or shape and alopecia. Additionally, women had a higher prevalence of alopecia than men. Individuals with alopecia were significantly older, with a higher frequency of alopecia observed in those over the age of 25 (p‐value = 0.002).

Conclusion

Age, hair color, smoking, and gender were found to significantly influence the development of androgenetic alopecia. These findings suggest the importance of considering demographic and phenotypic factors in understanding the pathogenesis of this condition.

1. Introduction

Androgenetic alopecia (AGA) is the most common cause of hair loss in men and women, with varying prevalence rates across populations. This condition predominantly affects individuals with a genetic predisposition and is driven by the physiological response of hair follicles to androgens, particularly dihydrotestosterone (DHT) [1, 2]. AGA affects up to 80% of Caucasian men and less than 42% of women, presenting distinct patterns of hair loss between genders [2]. In Female Androgenetic Alopecia (FAGA), the condition is characterized by thinning of the crown area while sparing the frontal hairline [3, 4].

The hallmark of AGA is the progressive miniaturization of hair follicles due to changes in the hair cycle dynamics, resulting in reduced hair density on the scalp [5, 6]. Androgens, particularly DHT, play a critical role in altering the hair growth cycle, leading to the production of shorter, thinner, or miniaturized hair strands in genetically predisposed individuals [7]. Over time, this process can lead to complete cessation of hair growth in affected areas. The activity of androgen receptors in hair follicles varies among individuals and contributes to these outcomes [8, 9].

Although the influence of androgens and genetic predisposition in AGA is well‐recognized, the exact mechanisms underlying inherited hair loss remain unclear. This study investigates the relationship between AGA and the shape, form, and thickness of hair, addressing gaps in the understanding of how these factors interact to contribute to the progression of hair loss.

2. Materials and Methods

2.1. Patients

This cross‐sectional study employed a convenience sampling method to recruit participants from the hospital's dermatology clinic during 2022–2023. The sample consisted of 50 patients diagnosed with AGA and 50 control participants without alopecia. Inclusion criteria for the AGA group included a confirmed diagnosis by a dermatologist. For the control group, inclusion criteria ensured the absence of androgenetic or other types of hair loss. Exclusion criteria included secondary AGA due to exogenous androgenic or steroid hormone use, secondary AGA caused by hormonal disorders (e.g., polycystic ovary syndrome), a history of autoimmune diseases, other hair loss types (e.g., alopecia areata, cicatricial alopecia), permanent use of hair‐altering substances in the past 9 months, and non‐cooperation in providing necessary information for the study.

Demographic information was collected using standardized checklists, including data on age, gender, smoking history, and variables such as hair form, thickness, and color. To minimize confounding factors, hair samples were obtained from the upper occipital crest, a region less influenced by hormones and alopecia.

2.2. Assessment Methods

Hair form was assessed using a standardized protocol. Hair samples from the pull test in the upper occipital crest were classified into straight, wavy, or curly categories based on their wave pattern. To ensure consistency, two trained observers independently assessed the wave pattern, and inter‐observer reliability was measured using Cohen's kappa coefficient. Discrepancies were resolved through discussion and consensus.

The hair samples were stretched, cut 6 cm from the root, washed with 100 mL of a 1% shampoo solution for 3 min, and dried on a paper towel. Without applying mechanical pressure, the hair was placed between two glass slides, and the upper slide was removed. The number of wave peaks per 1 cm of hair length was recorded as follows:

• Group 1 (straight): No wave formation after washing and drying; highest shine and least damage‐prone.

• Group 2 (wavy): Loose “S” waves starting mid‐strand, with fewer than three waves per 1 cm.

• Group 3 (curly): Spiral “S” or “Z” curls resembling small ringlets, starting closer to the scalp, with three or more (but fewer than five) waves per 1 cm.

Hair color was classified using a reference scale of ten shades from Loussouarn's 2016 study, Diversity in Human Hair Growth, Diameter, Color, and Shape [10]. Hair thickness was measured with a dermatoscope and micromeasurement application, and fibers were categorized as follows: thin (30–40 µm), medium (50–80 µm), and thick (90–100 µm) [11].

2.3. Data Analysis

Data were analyzed using SPSS v22 software (IBM, Armonk, NY). Quantitative variables were summarized as means ± standard deviations, while qualitative data were reported as percentages. The normality of data distributions was evaluated using the Kolmogorov–Smirnov test. Based on this assessment, the Mann–Whitney test was selected to compare quantitative variables between groups due to the non‐normal distribution of data. These tests were chosen for their robustness in handling small sample sizes and non‐parametric distributions. Relationships between qualitative variables, such as hair color and hair form, and alopecia were analyzed using the χ ² test. Multinomial regression analysis was conducted to examine the influence of significant variables further. A two‐sided p‐value of < 0.05 was considered statistically significant for all analyses.

2.4. Acknowledgment of Limitations

The use of convenience sampling introduces selection bias and limits the generalizability of the findings. Future studies are recommended to employ random sampling methods to enhance validity and reduce bias. Additionally, while efforts were made to ensure consistency in hair form classification, the subjective nature of the process may still introduce variability. Employing multiple observers and assessing inter‐observer reliability improved classification accuracy, but future studies could benefit from more objective methods, such as automated image analysis.

2.5. Ethical Considerations

The participants in this project adhered to all Helsinki ethical principles. This study was approved by the Research Council with the ethics code number IR.IUMS.FMD.REC.1402.384. Informed consent was obtained from all participants before their inclusion in the study, ensuring their voluntary participation and understanding of the study's aims and procedures.

3. Results

This study compared data from 50 patients with AGA and 50 patients without alopecia to explore the relationship between androgenetic hair loss and hair characteristics (shape, color, and thickness), smoking history, age, and gender. Background information and hair type data of participants, categorized by the presence or absence of AGA, are presented in Table 1.

Table 1.

Background information and hair type by group.

Variable		Control		Case		p value
		Number	Percentage	Number	Percentage
Gender	Women	20	40	31	62	0.045
	men	30	60	19	38
Shape of hair	Wavy	19	38	24	48	0.165
	Straight	22	44	23	46
	Curly	9	18	3	6
Hair color	1	5	10	9	18	0.012
	2	23	46	12	24
	3	4	8	10	20
	4	9	18	2	4
	5	9	18	12	24
	6	0	0	1	2
	7	0	0	2	4
	8	0	0	1	2
	9	0	0	0	0
	10	0	0	1	2
Hair thickness	Thin	19	38	15	30	0.108
	Medium	13	26	23	46
	Thick	18	36	12	24
Smoking history	No	46	92	35	70	0.009
	Yes	4	8	15	30

Using the χ ² test, we assessed the association between qualitative variables and AGA. Smoking was found to be significantly associated with a higher prevalence of alopecia (OR = 2.34, 95% CI: 1.19–4.59, p < 0.05). This suggests that individuals who smoke are more than twice as likely to develop AGA compared to non‐smokers. The odds ratio (OR) of 2.34 indicates a moderate‐to‐large effect, with the 95% confidence interval (CI) ranging from 1.19 to 4.59, meaning that the true odds could be as low as 1.19 times the likelihood or as high as 4.59 times the likelihood of AGA for smokers. The p‐value of less than 0.05 indicates that this finding is statistically significant. Practically, this finding suggests that smoking may be an important modifiable risk factor for AGA progression, and smoking cessation could be a potential intervention to reduce the risk of developing AGA.

A significant association was also observed between light hair color (specifically spectrum 1 and 3) and alopecia (OR = 1.85, 95% CI: 1.02–3.35, p = 0.04). Conversely, hair colors in spectrum 2 and 4 showed a significantly lower association with alopecia (OR = 0.56, 95% CI: 0.32–0.97, p = 0.03), suggesting that individuals with light‐colored hair may be more prone to AGA. However, hair thickness and hair shape were not significantly associated with AGA (p = 0.43 and p = 0.61, respectively).

Gender analysis revealed that females had a significantly higher prevalence of AGA compared to males (OR = 1.91, 95% CI: 1.08–3.38, p = 0.03), suggesting potential gender‐based differences in the development or progression of AGA.

Table 2 summarizes the quantitative data for hair thickness (in micrometers) and age, categorized by AGA presence. The Kolmogorov–Smirnov test confirmed that none of the quantitative variables followed a normal distribution (p < 0.001). Consequently, the Mann–Whitney test was employed to evaluate differences in age and hair thickness between groups.

Table 2.

Age and hair thickness information for the two groups.

	Control		Patients with alopecia
	Mean	Standard deviation	Mean	Standard deviation
Thickness (mm)	63.2	25.66	58.8	20.96
Current age	25.94	2.53	30.94	8.69
Age of onset of alopecia	—	—	26.32	8.32

Hair thickness did not show a significant association with AGA (Mann–Whitney U = 1118.0, p = 0.43). However, age was significantly higher in individuals with alopecia compared to those without (mean rank: 62.3 vs. 38.7, respectively; U = 823.5, p = 0.002). This suggests that AGA occurs more frequently in individuals older than 25 years, highlighting aging as a key factor contributing to the condition.

The multinomial regression analysis further identified age (OR = 1.21, 95% CI: 1.08–1.36, p = 0.002), smoking (OR = 2.34, 95% CI: 1.19–4.59, p = 0.03), light hair color (OR = 1.85, 95% CI: 1.02–3.35, p = 0.04), and gender (OR = 1.91, 95% CI: 1.08–3.38, p = 0.03) as significant predictors of AGA (Table 3). These results underline the multifactorial nature of AGA, with modifiable factors like smoking offering potential intervention points for reducing the progression of the condition.

Table 3.

Factors influencing the development of alopecia.

Variable	p value ratio	Likelihood
Age	0.005	84.36
Gender	0.029	76.4
Hair form	0.213	9.3
Hair color	0.004	98.20
Hair thickness	0.438	65.1
Smoking	0.037	34.4

4. Discussion

The present study investigated the relationship between AGA and various factors, including hair characteristics (shape, thickness, and color), smoking, age, and gender. Our findings provide important insights into the associations between these variables and AGA while offering potential explanations for the observed trends.

4.1. Key Findings and Interpretations

• 1.Smoking and AGA

  This study found a significant association between smoking and AGA (OR = 2.34, 95% CI: 1.19–4.59, p = 0.02), suggesting that individuals who smoke are over twice as likely to develop AGA compared to non‐smokers. This association may be attributed to smoking‐induced oxidative stress, which generates reactive oxygen species (ROS) that damage hair follicle cells, accelerate follicular miniaturization, and impair hair growth. Furthermore, smoking reduces blood flow to the scalp, depriving hair follicles of essential nutrients and oxygen, which may exacerbate hair loss.

  The finding aligns with prior studies by Gupta et al. [12] and Su and Chen [11], which also reported significant associations between smoking and AGA. For example, Su and Chen found that smoking 20 cigarettes or more per day nearly doubles the odds of developing AGA (OR = 2.34, 95% CI: 1.19–4.59). These findings underscore the importance of smoking cessation as part of AGA prevention and management strategies. Future studies could explore whether reducing smoking intensity or quitting entirely can slow AGA progression.

• 2.Age and AGA

  Our results indicated that individuals with AGA were significantly older, with the condition occurring more frequently in individuals aged over 25 years (p = 0.002). This finding supports the hypothesis that age is a critical factor in AGA progression, potentially due to cumulative androgen exposure over time and age‐related changes in hair follicle dynamics. Wang et al. [13] similarly reported that the prevalence of AGA increases with age in both men and women, a trend consistent across different populations.

• 3.Hair color and AGA

  A significant association was observed between lighter hair colors (e.g., spectrum 1 and 3) and AGA (OR = 1.85, 95% CI: 1.02–3.35, p = 0.04). This finding may be explained by differences in melanin content among individuals with lighter hair. Melanin provides protection against oxidative stress by neutralizing ROS. Individuals with lighter hair, which contains less melanin, may have increased susceptibility to oxidative damage and, consequently, a higher risk for hair follicle miniaturization and AGA.

  Conversely, darker hair colors (spectrum 2 and 4) were less associated with AGA (OR = 0.56, 95% CI: 0.32–0.97, p = 0.03). This protective effect could be due to higher melanin levels, offering greater defense against oxidative damage. Further research is needed to explore this mechanism in greater depth, particularly by measuring oxidative stress markers in individuals with different hair colors.

• 4.Gender differences in AGA prevalence

  Our study revealed that women had a significantly higher prevalence of AGA compared to men (OR = 1.91, 95% CI: 1.08–3.38, p = 0.03). This finding differs from previous studies, such as Wang et al. [13] and Salman et al. [14], which reported a higher prevalence among men. The discrepancy may stem from selection bias, as women are more likely to seek treatment for hair loss in dermatology clinics. Additionally, hormonal fluctuations, such as those caused by pregnancy or menopause, may contribute to AGA prevalence in women [15]. Future studies with larger, more representative samples are needed to clarify these gender differences.

4.2. Biological Mechanisms Underlying Observed Associations

Regarding the overall biological mechanisms of AGA, DHT plays a central role by binding to androgen receptors (ARs) in the dermal papilla cells of hair follicles, initiating a cascade of molecular events that lead to follicular miniaturization and eventual hair loss. The enzyme 5α‐reductase, primarily type II and III isoforms, converts testosterone into DHT within these cells. DHT has a significantly higher affinity for the androgen receptor compared to testosterone, making it a dominant factor in AGA progression [1, 16].

Once formed, DHT interacts with androgen receptors in the dermal papilla, activating androgen‐responsive genes. Individuals with AGA often exhibit increased AR expression in affected scalp regions, particularly in the frontal and vertex areas, which heightens follicular sensitivity to androgenic activity. This interaction disrupts key signaling pathways essential for hair follicle maintenance and growth [4].

DHT interferes with the Wnt/β‐catenin signaling pathway, a crucial regulator of hair follicle stem cell activity and regeneration. By upregulating Dickkopf‐related protein 1 (DKK1), an inhibitor of Wnt signaling, DHT suppresses hair follicle renewal and contributes to progressive follicular shrinkage. Additionally, DHT induces transforming growth factor‐beta (TGF‐β1 and TGF‐β2), which promote apoptosis of follicular keratinocytes and inhibit matrix cell proliferation, further accelerating the miniaturization process [17, 18].

With prolonged DHT exposure, hair follicles gradually shift from producing thick, terminal hairs to finer, vellus‐like hairs. The anagen (growth) phase shortens, reducing the duration available for follicles to generate fully developed hair strands, while the telogen (resting) phase is extended, leading to increased shedding and a higher proportion of dormant follicles. As AGA progresses, the regenerative capacity of miniaturized follicles diminishes, ultimately leading to permanent hair loss [19].

The findings of this study highlight the multifactorial nature of AGA, which is influenced by a combination of genetic, environmental, and biological factors.

• Smoking and hair follicles: Smoking has been shown to increase androgen receptor sensitivity and alter hormone levels, both of which are implicated in AGA. Oxidative stress induced by smoking damages the dermal papilla cells of hair follicles, impairing their function and promoting miniaturization [12, 20].

• Age and hair follicle aging: Aging affects the hair follicle's ability to cycle efficiently, leading to shorter anagen (growth) phases and longer telogen (resting) phases. This age‐related decline in follicular function may be exacerbated by genetic predisposition to AGA [13, 14].

Androgenetic alopecia is a progressive, age‐dependent disorder driven by the cumulative effects of androgens, particularly DHT, on genetically predisposed hair follicles. The relationship between aging and AGA progression can be attributed to several factors, including prolonged androgen exposure, changes in follicular sensitivity to androgens, alterations in the hair growth cycle, and the gradual depletion of follicular stem cell activity [16].

A key mechanism underlying AGA progression is the chronic exposure of hair follicles to DHT. Hair follicles in AGA‐prone areas, such as the frontal, temporal, and vertex scalp, have a higher density of androgen receptors (ARs), making them more susceptible to DHT's effects. Over decades, the interaction between DHT and follicular ARs leads to progressive miniaturization of hair follicles, resulting in thinner and shorter hair shafts. The long‐term impact of 5α‐reductase activity, which converts testosterone to DHT, further exacerbates the miniaturization process, as the enzyme's expression remains consistent with age [17].

Aging in conjunction with prolonged androgen exposure disrupts the normal hair cycle. The anagen (growth) phase progressively shortens, reducing the duration that follicles produce fully developed terminal hairs. Simultaneously, the telogen (resting) phase is prolonged, leading to increased shedding and a higher proportion of dormant follicles at any given time. As this imbalance continues, hair follicles fail to efficiently re‐enter the anagen phase, leading to a gradual decline in hair density and coverage [16, 17].

The ability of hair follicles to regenerate is further compromised by the decline in follicular stem cell activity. Hair follicle stem cells, located in the bulge region of the follicle, are essential for regenerating new hair during each cycle. With age, these stem cells experience exhaustion and a decline in their proliferative capacity, contributing to reduced hair regrowth. Androgen‐mediated activation of inhibitory signals, such as Dickkopf‐related protein 1 (DKK1) and transforming growth factor‐beta (TGF‐β), further suppresses follicular stem cell renewal, accelerating the miniaturization process and exacerbating hair loss [18].

The progression of AGA varies among individuals, but its severity tends to increase with each decade of life. By the third decade, many affected individuals experience noticeable hair thinning. By the fifth or sixth decade, long‐term follicular miniaturization results in irreversible baldness in severely affected regions, as miniaturized follicles become incapable of producing terminal hairs. Additionally, aging itself contributes to a decline in overall scalp follicular density, compounding the visible effects of AGA. The interplay between prolonged androgen exposure, disrupted hair growth cycles, and diminishing regenerative capacity underscores why AGA is a progressive condition that worsens over time [18].

• Hair color and oxidative stress: Individuals with lighter hair may experience reduced protection against oxidative damage due to lower melanin levels. Melanin acts as a natural antioxidant, and its absence may leave hair follicles more vulnerable to environmental and endogenous ROS [10].

4.3. Strengths and Limitations

One of the primary strengths of this study is its focus on hair type characteristics (e.g., color, thickness, and shape), which have received limited attention in AGA research. The analysis of smoking and other modifiable risk factors also provides valuable insights into potential intervention strategies.

However, this study has several limitations. First, the convenience sampling method introduces selection bias, limiting the generalizability of our findings. Second, hair type classification was subjective and may have lacked consistency. Future studies should incorporate standardized assessment tools and inter‐observer reliability measures to enhance accuracy. Finally, confounding factors such as diet, stress, and hormonal imbalances were not controlled for and may have influenced the observed associations.

5. Conclusion

The findings of this study indicate that age, hair color, smoking, and gender are significant factors associated with the development of AGA. Among these, smoking emerged as a modifiable risk factor, underscoring the need for public health campaigns to raise awareness about the potential adverse effects of smoking on hair health. Given the significant role that hair plays in an individual's physical appearance and self‐perception, such campaigns may encourage smoking cessation as part of broader preventive strategies for AGA.

In practical terms, dermatologists and healthcare providers should integrate smoking cessation counseling into the management of patients with AGA, particularly for those at higher risk due to age or genetic predisposition. Additionally, individuals with lighter hair color may benefit from targeted interventions to mitigate oxidative stress, such as antioxidant‐rich diets or topical treatments, though further research is required to validate these approaches.

Future studies should focus on confirming these findings through larger, multi‐center studies with diverse populations to improve generalizability. Longitudinal research is also needed to explore the causal mechanisms underlying the observed associations, particularly the role of oxidative stress, hormonal changes, and lifestyle factors in AGA progression. Such studies could pave the way for the development of novel, evidence‐based interventions to prevent or delay the onset of AGA.

Author Contributions

Afsaneh Sadeghzadeh Bazargan: conceptualization and investigation. Alireza Jafarzadeh: writing – original draft, methodology, and validation. Ava Ayoubi: writing – original draft. Masoumeh Roohaninasab: visualization, writing – review and editing. Sara Dilmaghani: software and formal analysis. Sepideh Salehi: data curation and resources. Azadeh Goodarzi: project administration and supervision.

Ethics Statement

All information obtained from patients was kept confidential and evaluated anonymously. All patients studied adhered to the Helsinki ethical principles. This project was approved by the Ethics Committee of Iran University of Medical Sciences with the title: “Investigating the Relationship between Androgenetic Alopecia and Hair Shape, Color, and Thickness: A Case‐Control Study”, with the ethical code IR.IUMS.FMD.REC.1402.384, date of approval: June 31, 2022. The researchers were committed and adhered to the principles of the Helsinki Convention and the Ethics Committee of the Iran University of Medical Sciences at all stages.

Consent

After providing the necessary explanations, written informed consent was obtained from the patient regarding the submission of their clinical condition to medical journals. Additionally, the patient has been assured that their name and personal details will be kept confidential by the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The lead author, Azadeh Goodarzi, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Data Availability Statement

All data produced in the present study are available upon reasonable request to the authors.