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Factors associated with facial melasma severity in Brazilian women: an internet-based survey
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Ana Flávia Teixeira de Abreua, Marina Oliveira Diasa, Mayla Martins Conti Barbosaa, Rebecca Perez de Amorima, Hélio Amante Miota, Ana Cláudia Cavalcante Espósitoa,
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anaclaudiaesposito@gmail.com

Corresponding author.
a Department of Infectology, Dermatology, Imaging Diagnosis and Radiotherapy, Faculty of Medicine, Universidade Estadual Paulista, Botucatu, SP, Brazil
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Received 07 October 2023. Accepted 22 December 2023
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Table 1. Main clinical and demographic data of the 1,878 women with melasma, aged 18 to 65 years old.
Table 2. Multivariate analysis of factors associated with melasma severity in adult women (n = 1,878).
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Dear Editor,

Melasma is a chronic, recurrent, and multifactorial hypermelanosis that mainly affects women of reproductive age and, although there are known triggers (e.g., exposure to solar radiation, pregnancy, hormonal therapy, hormonal contraceptives), no study has systematically investigated the factors associated with facial melasma severity.1,2

The multifactorial nature of melasma severity requires a large sample to perform a robust multivariate analysis. In this context, internet-based surveys are the methodology that enables research requiring large samples, which are inaccessible in clinical practice.

The study aimed to explore factors associated with facial melasma severity in adult women in Brazil, based on a cross-sectional internet-based survey, which included women aged 18 to 60 years old, who reported facial melasma previously diagnosed by a dermatologist. Participants who reported other concomitant facial dermatoses or dermatoses related to photosensitivity were excluded.

The project was approved by the Ethics Committee (Counsel number 5,509,091) and the participants were invited to answer an online form consisting of items on clinical, demographic, and exposure-related data, in addition to the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the HAD (Hospital Anxiety and Depression) scale. Finally, they pointed out on a facial map (Fig. 1) the areas affected by melasma, with the number of affected areas indicating disease extent. The map was validated in person with 51 women (correlation with the mMASI severity scale: rho = 0.94, p < 0.01). Sample availability and invitation to participate occurred through discussion groups about melasma on social networks. The study was conducted during the months of June to September 2022.

Fig. 1.

Validated facial map, used by participants to point out the regions affected by melasma on their faces.

(0.16MB).

The study-dependent variable was the severity of melasma, represented by the number of areas indicated on the facial map. The independent variables were demographic information, clinical data, demographics, occupational exposure, HAD, and PSQI.

The facial areas indicated on the facial map were evaluated by cluster analysis (Ward's method) and the covariates were tested for the number of topographies using a generalized linear model with Tweedie probability distribution (identity link). The size of the effect was estimated by the β coefficient of regression and statistical significance was defined as p-value < 0.05.

Of the 2,271 responses, 1,878 were considered valid due to diagnostic confirmation, duplications, or incomplete data. Table 1 highlights the main characteristics of the studied population. The predominance of women of childbearing age, self-declared white, who had more than one pregnancy and a high frequency of positive family history stands out. The high prevalence of anxiety disorders, depression and impaired sleep quality is also worth highlighting in this sample. The main worsening factors were sun exposure, heat exposure and psychological stress.

Table 1.

Main clinical and demographic data of the 1,878 women with melasma, aged 18 to 65 years old.

VariablesValues
Age (in years), mean (SD)40.0  7.4 
Self-declared skin color, n (%)   
  White  1398  74.4% 
  Brown/Yellow  452  24.1% 
  Black  28  1.5% 
Number of pregnancies, n (%)   
  No pregnancies  682  36.3% 
  One to three  1.125  59.9% 
  More than three  71  3.8% 
Hormonal pregnancy prevention, n (%)   
  Contraceptive/pregnancy  465  24.8% 
  Menopause/hysterectomy  182  9.7% 
  Implants/IUD with hormones  235  12.5% 
Age at melasma onset (in years), mean (SD)29,8  (6,5) 
First-degree family member with melasma, n (%)954  50,8% 
Melasma extension score, median (p25-p75)(2‒6) 
Affected areas, n (%)   
  Forehead region?  841  44.8% 
  Region between the eyebrows?  407  21.7% 
  Nasal region?  355  18.9% 
  Malar region?  1399  74.5% 
  Upper lip region?  602  32.1% 
  Chin region?  209  11.1% 
  Jaw region?  261  13.9% 
  Temporal region?  733  39.0% 
Lives in a polluted area, n (%)319  17,0% 
Current smoker, n (%)70  3,7% 
Sun-exposed, n (%)32  1,7% 
Practices sports exposed to the sun, n (%)39  2,1% 
Exposure to heat at work, n (%)55  2,9% 
Goes to the sauna, n (%)0,5% 
Use of prescription glasses, n (%)794  42,3% 
Adherence to photoprotector, n (%)1553  82,7% 
Comorbidities, n (%)   
  Thyroid disease  244  13.0% 
  Migraine  362  19.3% 
  Hypertension  111  5.9% 
  Dyslipidemia  182  9.7% 
  Diabetes  68  3.6% 
Factor that triggered the melasma, n (%)   
  Sun exposure  1030  54.8% 
  Contraceptive pill, injection or IUD  587  31.3% 
  Pregnancy  560  29.8% 
  Very intense psychological stress  382  20.3% 
  Heat exposure  226  12.0% 
  I don’t know  205  10,9% 
  Facial hair removal  138  7,3% 
  Skin procedure: peeling  129  6,9% 
  Skin procedure: laser  115  6,1% 
  Medication taken  52  2,8% 
Melasma worsening factors, n (%)   
  Sun exposure  1408  75,0% 
  Heat exposure  651  34,7% 
  Psychological stress  460  24,5% 
  I don’t know  192  10,2% 
  Contraceptive pill, injection or IUD  187  10,0% 
  Skin procedure: peeling/laser  133  7,1% 
  Pregnancy  117  6,2% 
HAD-A, mean (SD)8,3  (4,0) 
  HAD-A ≥8  1001  53,3% 
HAD-D, mean (SD)6,0  (3,7) 
  HAD-D ≥8  609  32,4% 
PSQI, mean (SD)6,6  (3,5) 
  PSQI >5  1084  57,7% 

PSQI, Pittsburgh Sleep Quality Index; HAD-A, Hospital Anxiety Scale; HAD-D, Hospital Depression Scale; IUD, Intrauterine Device; SD, Standard Deviation.

According to the topographic distribution of facial melasma, three main cluster patterns were identified (Fig. 2): upper face, centro-facial and peripheral. According to the multivariate analysis (Table 2), more extensive melasma was identified in women with intermediate skin pigmentation, aged between 30 and 45 years old, who reported more than three pregnancies, who exposed themselves to the sun during work activities, who exposed themselves directly to heat, who had early onset of melasma, higher scores of anxiety, depression and impaired sleep quality. Adherence to sunscreen, however, showed a positive association with the severity of melasma, while practicing sports showed a negative association.

Fig. 2.

Cluster analysis of regions with melasma.

(0.07MB).
Table 2.

Multivariate analysis of factors associated with melasma severity in adult women (n = 1,878).

Variablesβ Coefficient  SE  p-valuea 
Self-declared skin color     
  White  ‒  ‒  ‒ 
  Brown/Yellow  0.19  0.07  0.011 
  Black  0.25  0.26  0.340 
Age     
  <30 years  ‒  ‒  ‒ 
  30‒45 years  0.27  0.11  0.016 
  >45 years  0.22  0.14  0.123 
Current smoking−0,30  0.18  0.091 
Air pollution in the region−0,09  0.08  0.245 
History of pregnancies     
  None  ‒  ‒  ‒ 
  Between one and three  0.02  0.07  0.826 
  More than three  0.35  0.18  0.047 
Sun exposure at work0,23  0.07  0.001 
Sun exposure during sports practice−0,18  0.07  0.009 
Direct exposure to heat/sauna0,22  0.09  0.020 
First degree family history0,14  0.06  0.018 
Onset of melasma <30 years of age0,30  0.06  <0.001 
Daily adherence to sunscreen0,18  0.08  0.022 
Daily use of prescription glasses/lenses0,00  0.06  0.901 
Hormone therapy     
  None  ‒  ‒  ‒ 
  Menopause  −0.25  0.12  0.035 
  IUD with hormone  −0.03  0.09  0.764 
  OC/Current pregnancy  0.09  0.08  0.260 
HAD-D ≥ 80.15  0.07  0.034 
PSQI > 50.22  0.06  0.001 

SE, Standard Error; OC, Oral contraceptive; HAD-D, Hospital Depression Scale; PSQI, Pittsburgh Sleep Quality Index.

a

adjusted p-value.

As the HAD-anxiety and HAD-depression values ​​were collinear (rho = 0.66; p < 0.01), they could not be included in the final model, and the one with the greatest statistical weight was chosen. However, both conditions were, when analyzed independently in the final model, associated with greater facial melasma severity (p < 0.05).

The clinical and demographic characteristics were similar to those found in other series of Brazilian women with melasma.1–3 The results of this study corroborate several previously mentioned aggravating factors, such as sun exposure, constitutional skin pigmentation, multiparity, genetic predisposition, and sexual hormones. Moreover, it reinforces the impact of disturbances of mental health, such as mood disorders and impaired sleep quality, as facial melasma aggravating factors.4

Affective disorders and sleep deprivation influence serum cortisol levels and increase systemic oxidative stress, substrates for the intensification of melanin pigmentation.4 Furthermore, a greater frequency of use of antidepressants and anxiolytics is observed in women with melasma, so this causality must be explored.5

High-dose infrared radiation can also induce melanogenesis, as it occurs in erythema ab igne. And, as in the present sample, a survey in India showed an association between melasma intensity and occupational exposure to heat.6,7

Female sex hormones are known risk factors, which were corroborated in the present study by multiparity and greater severity in women who started melasma at an early age (<30 years), as opposed to those who were menopausal when the disease started.

Data regarding skin color in Latin American countries are predominantly self-reported, which may differ from phenotypic classification based on ethnicity, photoreactivity, or colorimetric aspects.8 In this sample, melasma was more intense in pigmented phenotypes; however, 74.4% of the participants reported being white, which may signal a possible social bias (due to greater access to internet), but also because melasma is more prevalent among individuals self-declared as white and brown, to the detriment of black people.

Similarly, adherence to sun-exposed physical activity was low (2%), hindering the inference of causality related to this factor. These data must be confirmed regarding the aspect of a sedentary lifestyle and melasma since several dermatoses are influenced by metabolic changes triggered by sports, and people with melasma may try to avoid sports in the sun.9

Among the participants, 24.3% reported photo-exposed leisure activities. In the last decade, there has been a population increase in photoexposure during resting time.10 In the present sample, the daily use of sunscreen was associated with greater melasma intensity. However, this information must represent a confounding variable, since more severe cases must lead to a greater search for treatment, in which photoprotection is essential.9

This study has limitations as it is not randomized and is based on invitation on social networks, which may generate social selection and adherence biases. However, a multivariate analysis was carried out and the variables were adjusted, with their β coefficients being estimated, thus minimizing the individual effect of disproportions. The different factors identified should be explored in randomized studies, with population sampling proportional to age and racial quotas, which more equally represent the Brazilian population, aiming to confirm these findings.

In conclusion, factors linked to genetics, sun and heat exposure, sexual hormones, affective comorbidities and sleep disorders were associated with facial melasma severity, which allows the development of pathophysiological hypotheses, therapeutic proposals and prevention measures.

Financial support

None declared.

Authors' contributions

Ana Flávia Teixeira de Abreu: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Marina Oliveira Dias: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Mayla Martins Conti Barbosa: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Rebecca Perez de Amorim: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Hélio Amante Miot: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Ana Cláudia Cavalcante Espósito: Design and planning of the study, drafting and editing of the manuscript and approval of the final version of the manuscript.

Conflicts of interest

None declared.

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Study conducted at the Department of Infectology, Dermatology, Imaging Diagnosis and Radiotherapy, Faculty of Medicine, Universidade Estadual Paulista, Botucatu, SP, Brazil.

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