Abstract
Background
The prevalence of acne vulgaris among rosacea patients is significantly higher than that of the general population, but the risk factors for acne vulgaris among rosacea patients remain unclear.
Objective
Explore the potential risk factors for the occurrence of acne vulgaris among rosacea patients, focusing on lifestyle, skincare habits, and dietary habits.
Methods
A total of 300 rosacea patients were included. Lifestyle, skincare habits, and dietary habits were collected using a validated questionnaire survey. A Multivariate logistic regression model was employed to analyze risk factors associated with acne vulgaris. Further subgroup analysis and restricted cubic spline function was used to analyze the related risk factors.
Results
The prevalence of acne vulgaris was 30.33% in 300 rosacea patients, which is significantly higher than the 14.83% observed in the general population. Multivariate logistic regression analysis revealed that sufficient sleep duration was a protective factor against acne vulgaris in rosacea patients [OR = 0.738 (0.589–0.926)] (p < 0.05), while the use of sunscreen products was identified as a risk factor [OR = 2.602 (1.083–6.249)], (p < 0.05). Additionally, restricted cubic spline analysis indicated a significant linear dose–response relationship between longer sleep duration and a lower risk of acne vulgaris (Poverall < 0.05, Pnonlinear = 0.86).
Conclusion
Adequate sleep appears to be a protective factor, while frequent sunscreen use may increase the risk of acne vulgaris among rosacea patients. Tailored lifestyle recommendations may contribute to improved comorbidity management.
Keywords: acne vulgaris, comorbidity, correlation analysis, risk factors, rosacea
1. Introduction
Rosacea and acne vulgaris are two common chronic inflammatory dermatoses. Rosacea is characterized by vascular hyperreactivity and neurosensory hyperresponsiveness (1), whereas acne vulgaris primarily manifests as abnormal follicular keratinization and sebaceous gland dysfunction (2). Although these conditions exhibit significant differences in pathophysiology, susceptible populations, and clinical manifestations, conventional perspectives suggest their pathogenic mechanisms are mutually independent. However, the comorbidity of these two conditions is frequently observed in clinical practice. From the epidemiological investigation data of 2023 surveillance of chronic diseases and risk factors in Shenzhen (SCDRFS), we observed that the prevalence of acne among rosacea patients was significantly higher than that in the general population. This finding suggests that rosacea may constitute a potential risk factor for the development of acne.
Rosacea and acne vulgaris both involve cutaneous barrier dysfunction, aberrant innate immunity (Toll-like receptor 2 activation), pilosebaceous unit dysregulation, and microbial dysbiosis (3). Furthermore, lifestyle factors including dietary patterns (4), sleep–wake cycles (5, 6), and skincare habits (7) are recognized as significant contributors to the pathogenesis and progression of both diseases. In recent years, several studies have begun to investigate the impact of lifestyle factors on chronic inflammatory skin diseases. For instance, sleep deprivation may exacerbate skin inflammation by activating the hypothalamic–pituitary–adrenal axis and increasing cortisol levels (8). An epidemiological survey in the Chinese community shows that the prevalence of acne among women of childbearing age who have a sweet tooth and are sedentary is significantly higher than that in the control group (9). Similarly, the use of irritating skincare products can disrupt the skin barrier (10), triggering or worsening symptoms of acne and rosacea. Although these mechanisms have been partially validated, current research on how these factors specifically induce acne in rosacea patients remains limited, particularly regarding comprehensive assessments of specific risk factors. Existing studies have primarily focused on analyzing risk factors for individual diseases, without exploring in depth how lifestyle factors influence the risk of acne development in comorbid states.
Based on the above, present study intends to systematically evaluate the relationship between various lifestyle factors and the prevalence of acne, focusing on living habits, skincare habits, and dietary patterns, using a Multivariate logistic regression analysis approach and with rosacea patients as the study subjects. The findings of this study will fill the evidentiary gap in the field of comorbidity management for rosacea, providing theoretical support for the development of targeted lifestyle intervention strategies, such as sleep management guidelines, personalized skincare education, and dietary adjustment recommendations. Additionally, it lays the foundation for exploring multi-dimensional prevention and control models for skin comorbidities.
2. Methods
2.1. Participant recruitment
The SCDRFS project was employed a stratified sampling method to recruit 12,182 adult participants from the general population. After excluding individuals with missing data on key variables or study outcomes, participants diagnosed with rosacea by board-certified dermatologists were identified from the remaining dataset. A total of 300 individuals with rosacea were included in the present analysis (Figure 1). The research was approved by the Ethics Committee of Shenzhen Chronic Disease Prevention and Control Center (SZCCC-2023-034-01-PJ) and obtained written informed consent from all participants. The characteristics of these participants are presented in Table 1.
Figure 1.
Schematic diagram of the participant enrollment process.
Table 1.
Sociodemographic characteristics of rosacea participants.
| Variables | Total (N = 300) | Acne (N = 91) | Non-acne (N = 209) | p-value |
|---|---|---|---|---|
| Age (years), mean±SD | 43.82 ± 12.86 | 37.76 ± 10.61 | 46.46 ± 12.88 | <0.0001 |
| Gender, n (%) | 0.0077 | |||
| Male | 120 (40.00) | 26 (28.57) | 94 (44.98) | |
| Female | 180 (60.00) | 65 (71.43) | 115 (55.02) | |
| BMI (kg/m2), mean ± SD | 24.25 ± 3.52 23.17 ± 3.19 24.72 ± 3.56 |
24.25 ± 3.52 23.17 ± 3.19 24.72 ± 3.56 |
24.25 ± 3.52 23.17 ± 3.19 24.72 ± 3.56 |
0.0004 |
| Skintype, n (%) | 0.0102 | |||
| Dry | 39 (13.09) | 6 (6.59) | 33 (15.94) | |
| Oil | 129 (43.29) | 52 (57.14) | 77 (37.20) | |
| Normal | 50 (16.78) | 10 (10.99) | 40 (19.32) | |
| Mix | 62 (20.81) | 19 (20.88) | 43 (20.77) | |
| Sensitive | 18 (6.04) | 4 (4.40) | 14 (6.76) | |
| Education, n (%) | 0.0035 | |||
| Tertiary education or above | 173 (57.67) | 41 (45.05) | 132 (63.16) | |
| High school or below | 127 (42.33) | 50 (54.95) | 77 (36.84) | |
| Nation, n (%) | 0.0313 | |||
| Han nationality | 288 (96.00) | 84 (92.31) | 204 (97.61) | |
| Other nationality | 12 (4.00) | 7 (7.69) | 5 (2.39) | |
| Marital status, n (%) | 0.0049 | |||
| Married or cohabitation | 232 (77.33) | 61 (67.03) | 171 (81.82) | |
| Unmarried | 68 (22.67) | 30 (32.97) | 38 (18.18) | |
| Insurance, n (%) | 0.1011 | |||
| Yes | 286 (95.33) | 84 (92.31) | 202 (96.65) | |
| No | 14 (4.67) | 7 (7.69) | 7 (3.35) | |
| Annual income (RMB) | 0.6453 | |||
| <50,000 | 28 (9.33) | 10 (10.99) | 18 (8.61) | |
| 50,000 ~ 250,000 | 199 (66.33) | 57 (62.64) | 142 (67.94) | |
| ≥250,000 | 73 (24.33) | 24 (26.37) | 49 (23.44) | |
| Smoking, n (%) | 0.3018 | |||
| Current | 58 (19.33) | 15 (16.48) | 43 (20.57) | |
| Former | 25 (8.33) | 5 (5.49) | 20 (9.57) | |
| Never | 217 (72.33) | 71 (78.02) | 146 (69.86) | |
| Alcohol intake, n (%) | 0.6551 | |||
| Yes | 187 (62.33) | 55 (60.44) | 132 (63.16) | |
| No | 113 (37.67) | 36 (39.56) | 77 (36.84) | |
| Sleep time (hours/day), mean ± SD | 7.96 ± 1.40 | 7.76 ± 1.33 | 8.05 ± 1.42 | 0.0921 |
| Sedentary (hours/day), mean ± SD | 6.84 ± 3.46 | 7.43 ± 3.19 | 6.58 ± 3.54 | 0.0504 |
| Physical activity level, n (%) | 0.0983 | |||
| Low | 49 (16.33) | 21 (23.08) | 28 (13.40) | |
| Moderate | 140 (46.67) | 41 (45.05) | 99 (47.37) | |
| High | 111 (37.00) | 29 (31.87) | 82 (39.23) | |
| Clean product, n (%) | 0.0021 | |||
| Yes | 115 (38.33) | 23 (25.27) | 92 (44.02) | |
| No | 185 (61.67) | 68 (74.73) | 117 (55.98) | |
| Moisturizing product, n (%) | 0.0008 | |||
| Yes | 126 (42.00) | 25 (27.47) | 101 (48.33) | |
| No | 174 (58.00) | 66 (72.53) | 108 (51.67) | |
| Mask, n (%) | 0.0012 | |||
| Yes | 180 (60.00) | 42 (46.15) | 138 (66.03) | |
| No | 120 (40.00) | 49 (53.85) | 71 (33.97) | |
| Sunscreen product, n (%) | 0.0002 | |||
| Yes | 245 (81.67) | 63 (69.23) | 182 (87.08) | |
| No | 55 (18.33) | 28 (30.77) | 27 (12.92) | |
| Cosmetic, n (%) | 0.0073 | |||
| Yes | 225 (75.00) | 59 (64.84) | 166 (79.43) | |
| No | 75 (25.00) | 32 (35.16) | 43 (20.57) | |
| Spicy food, n (%) | 0.6974 | |||
| Yes | 183 (61.00) | 54 (59.34) | 129 (61.72) | |
| No | 117 (39.00) | 37 (40.66) | 80 (38.28) | |
| Fruit, n (%) | 0.6549 | |||
| Yes | 292 (97.33) | 88 (96.70) | 204 (97.61) | |
| No | 8 (2.67) | 3 (3.30) | 5 (2.39) | |
| Milk, n (%) | 0.1285 | |||
| Yes | 245 (81.67) | 79 (86.81) | 166 (79.43) | |
| No | 55 (18.33) | 12 (13.19) | 43 (20.57) | |
| Beverages, n (%) | 0.1286 | |||
| Yes | 185 (61.67) | 62 (68.13) | 123 (58.85) | |
| No | 115 (38.33) | 29 (31.87) | 86 (41.15) | |
| Aquatic, n (%) | 0.9029 | |||
| Yes | 281 (93.67) | 85 (93.41) | 196 (93.78) | |
| No | 19 (6.33) | 6 (6.59) | 13 (6.22) | |
| Hypertension, n (%) | 0.0348 | |||
| Yes | 62 (20.67) | 12 (13.19) | 50 (23.92) | |
| No | 238 (79.33) | 79 (86.81) | 159 (76.08) | |
| Diabetes, n (%) | 0.0258 | |||
| Yes | 31 (10.33) | 4 (4.40) | 27 (12.92) | |
| No | 269 (89.67) | 87 (95.60) | 182 (87.08) | |
| Dyslipidemia, n (%) | 0.1619 | |||
| Yes | 110 (36.67) | 28 (30.77) | 82 (39.23) | |
| No | 190 (63.33) | 63 (69.23) | 127 (60.77) |
2.2. Clinical diagnosis and classification of rosacea and acne
The diagnosis of acne and rosacea was made face-to-face by a professional dermatologist on site. Rosacea was diagnosed according to the Chinese Guidelines for the Diagnosis and Treatment of Rosacea (2021 edition) (11). The required manifestations diagnostic criteria were as follows: (1) Persistent erythema on the cheeks, accompanied by episodic flushing and possible periodic exacerbation; or (2) Persistent erythema involving the perioral or nasal area, with possible periodic exacerbation. Supportive features: (1) flushing; (2) telangiectasia; (3) papules and pustules; (4) phymatous changes; and (5) ocular manifestations, including lid-margin telangiectasia, blepharitis, keratitis, conjunctivitis, or sclerokeratitis.
Rosacea was diagnosed when either of the following criteria was met: (1) Persistent erythema on the cheeks, regardless of the presence or absence of supportive features; or (2) Persistent erythema in the perioral or nasal area, together with at least one supportive feature, while excluding secondary causes of facial erythema.
Acne vulgaris was diagnosed if at least one of the following was present: (1) presence of current acne lesions; or (2) acne-related scarring, including moderate-to-severe scarring or hypertrophic/keloid scars, whereas acne-negative participants were required (1) no history of acne-related scarring and (2) no current acne lesions.
2.3. Covariate investigation
Demographic and lifestyle information was collected using a structured face-to-face questionnaire administered by trained public health professionals. The questionnaire covered socio-demographic characteristics, including age, sex, ethnicity, marital status, annual income level, educational attainment, dietary habits, skincare behaviors and lifestyle factors. Another section focused on health-related features, including blood glucose levels, BMI, hypertension and dyslipidemia. Height and weight were measured using standardized procedures by trained investigators. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). Hypertension was defined based on the 2018 Guidelines of the European Society of Hypertension, which includes a self-reported diagnosis by a physician, the use of antihypertensive medications, or a systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg. Participants’ blood pressure was measured after sitting and resting for 5 min, using automated equipment, three measurements were taken at one-minute intervals, and the average of the last two readings was used for analysis. Diabetes mellitus was defined according to the National Guidelines for the Prevention and Management of Diabetes in Primary Care (2022) as physician-diagnosed diabetes (12), current use of glucose-lowering medication, or fasting plasma glucose ≥7.0 mmol/L. Dietary habits were assessed using a retrospective self-administered questionnaire based on participants’ usual dietary intake over the past 1 year. Participants were asked to recall whether they consumed specific food groups in their daily life. The food groups included spicy foods, beverages, fruits, milk, and aquatic products. Skincare habits were assessed via self-report, including the frequency of use of cleansers, moisturizers, facial masks, sunscreen products, and cosmetics. Participants were asked: “How often do you use this product in your daily skincare routine?” Responses were categorized into four levels: almost never, occasionally, frequently, and daily. Smoking status was assessed using the question: “Do you currently smoke?” Smoking was defined as smoking at least one cigarette per day for a continuous or cumulative period of ≥6 months. Alcohol consumption was assessed using the question: “Do you drink alcohol?” Alcohol consumption was defined as the intake of any alcoholic beverages, including both commercially purchased and homemade drinks containing alcohol. Sedentary behavior was assessed using the question: “On a typical day, how much time do you usually spend sitting?” Sedentary behavior was defined as total sitting time at work or at home and during transportation, including activities such as desk work, car or bus travel, reading, playing cards, watching television, or using a computer, but excluding sleep time. Sleep duration was assessed using the question: “On average, how many hours do you sleep in a 24-hour period?”, referring to total daily sleep duration including naps. Physical activity level were assessed using the International Physical Activity Questionnaire, and based on total MET scores categorized into low, moderate, and high groups.
2.4. Statistical analysis
We utilized Analysis of Variance (ANOVA) for continuous variables and the Wald Chi-square test for categorical variables to compare participant characteristics, including gender, age, race, education level, marital status, income level, sleep duration, skin type, smoking status, drinking status, BMI, hypertension, diabetes and dyslipidemia. A multivariate logistic regression model was employed to estimate the odds ratios (ORs) and their 95% confidence intervals (CIs) between skincare habits, dietary habits, lifestyle habits and acne vulgaris among rosacea patients. After identifying relevant risk factors, restricted cubic spline functions were utilized to further analyze dose–response relationships or subgroup analysis.
All p-values were presented as two-sided, and statistical significance was determined based on a false discovery rate of less than 0.05. All statistical analyses were conducted using SAS software (version 9.4).
3. Result
3.1. Baseline characteristics of participants
A total of 300 participants were included in this study, with a mean age of 43.82 ± 12.86 years. Among them, 91 were diagnosed with acne vulgaris, corresponding to a prevalence rate of 30.33%, which was significantly higher than 14.83% in the general population (Supplementary Table S1). The mean BMI of the participants was 24.25 ± 3.52. Acne vulgaris was more common among younger, oil skin type, unmarried individuals, and those with lower education levels and incomes, static occupations and alcohol consumer (p < 0.05). Participants with acne had a lower prevalence of chronic conditions, including hypertension, diabetes, and dyslipidemia (p < 0.05) (Table 1).
3.2. Variables associated with acne in rosacea patients
After adjusting for all covariates, the results of the multivariate logistic regression analysis indicated that sleep duration with an OR = 0.738(0.589, 0.926) and the use of sunscreen products with an OR = 2.602(1.083, 6.249) were significantly associated with acne vulgaris among patients with rosacea (Table 2). Interestingly, independent risk factors for acne vulgaris in the general population, such as annual income level, nation, marital status, sedentary, and the use of cleansing products, did not show significant associations with acne vulgaris among rosacea patients (Supplementary Table S2).
Table 2.
Multivariate logistic regression analysis of acne inducing factors in rosacea patients.
| Variables | Odds ratio (95% CI) | p-value |
|---|---|---|
| Dietary habits | ||
| Spicy food | 0.664(0.352, 1.255) | 0.207 |
| Beverages | 0.553(0.260, 1.176) | 0.123 |
| Fruit | 0.515(0.074, 3.577) | 0.501 |
| Milk | 1.439(0.596, 3.473) | 0.417 |
| Aquatic | 0.815(0.238, 2.792) | 0.745 |
| Skin care habits | ||
| Clean product | 0.983(0.375, 2.580) | 0.972 |
| Moisturizing product | 1.405(0.493, 4.005) | 0.524 |
| Mask | 0.621(0.243, 1.584) | 0.318 |
| Sunscreen product | 2.602(1.083, 6.249)* | 0.033 |
| Cosmetic | 1.027(0.431, 2.450) | 0.951 |
| Living habits | ||
| Smoking | ||
| Never | Ref(1.00) | |
| Current smoker | 1.624(0.578, 4.564) | 0.358 |
| Former smoker | 0.948(0.265, 3.389) | 0.934 |
| Alcohol intake | 0.853(0.421, 1.730) | 0.659 |
| Physical activity level | ||
| Low | Ref(1.00) | |
| Moderate | 1.308(0.514, 3.329) | 0.573 |
| High | 1.040(0.505, 2.141) | 0.915 |
| Sleep time | 0.738(0.589, 0.926)* | 0.008 |
| Sedentary | 1.012(0.906, 1.130) | 0.834 |
*Bold mean p < 0.05.
3.3. Dose–response and stratified analyses of key exposures
We further stratified sunscreen product usage by frequency into never use, occasional use, frequent use, and daily use. A subgroup analysis was conducted to investigate the association between sunscreen usage frequency and the risk of acne vulgaris in rosacea patients. The results indicated that, compared to those who never used sunscreen products, the ORs for the risk of acne vulgaris in rosacea patients who used sunscreen occasionally, frequently, and daily were 1.408 (0.521, 3.806), 2.338 (0.522, 10.47), and 3.395 (1.153, 9.992), respectively (Table 3). Linear regression analysis of the dose–response relationship between sleep times and acne prevalence using a restricted cubic spline model showed a linear association (Poverall < 0.05, Pnonlinear = 0.86) (Figure 2).
Table 3.
Multivariate logistic regression analysis of sunscreen product usage frequency and acne.
| Variable | n | Model 1a | Model 2b | Model 3c | Model 4d |
|---|---|---|---|---|---|
| Sunscreen product usage frequency | |||||
| Never | 202 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Occasionally | 43 | 1.942 (0.965, 3.907) | 1.339 (0.593, 3.023) | 1.202 (0.503, 2.869) | 1.408 (0.521, 3.806) |
| Frequently | 14 | 2.457 (0.812, 7.440) | 1.600 (0.474, 5.397) | 2.121 (0.554, 8.119) | 2.338 (0.522, 10.47) |
| Daily | 41 | 4.005 (1.982, 8.092)* | 2.433 (1.056, 5.609)* | 2.721 (1.082, 6.842)* | 3.395 (1.153, 9.992)* |
aCrude model.
bAdjusted for age, gender and BMI based on model 1.
cFurther adjusted for nation, marital status, education level, health insurance, smoking status, alcohol intake, sleeptime, skintype based on model 2.
dFurther adjusted for lifestyle, skincare habits and dietary habits based on model 3.
*mean p < 0.05.
Figure 2.
Dose–response curve between sleeptime and acne in restricted cubic spline model (Pnonlinear = 0.86). The variables were adjusted by age, gender, BMI, nation, marital status, education level, physical activity level, sedentary, hypertension, diabetes, cleanning product, moisturizing product, mask, sunscreen product, cosmetic. X-axis, self-reported sleep duration (hours/day). Left y-axis, distribution of study participants’ sleep duration corresponding to the blue histogram (%). Right y-axis, odds ratio (OR) for acne vulgaris, representing the association between sleep duration and acne occurrence. Blue histogram: distribution of sleep duration in the study population. Red solid line: estimated OR trend derived from the restricted cubic spline model. Green shaded area: 95% confidence interval (CI) of OR. Black dashed horizontal line: reference line at OR = 1.0.
4. Discussion
In this cross-sectional study involving 300 adult patients with rosacea, two modifiable lifestyle factors, sleep duration and the use of sunscreen products, were identified to be associated with acne vulgaris. Specifically, longer sleep duration was found to be a protective factor, whereas sunscreen use was correlated with an increased prevalence of acne vulgaris. Further subgroup analysis stratified by sunscreen application frequency revealed a dose-dependent relationship, with higher frequencies of sunscreen use associated with greater acne vulgaris prevalence, particularly among daily users who exhibited the highest risk.
There is still controversy over the relationship between sunscreen use and acne. Some studies suggest that sunscreen has a protective effect on acne, for examlpe, a clinical randomized controlled trial (n = 33) on acne patients who received multiple acne medications treatment indicated that daily use of sunscreen SPF30 with moisturizing properties could improve skin tolerance, assist in the treatment of patients, and reduce epidermal water loss (13). While a cross-sectional study on the skincare awareness of 450 patients with acne vulgaris found that individuals who used sunscreen had a significantly higher prevalence of mild acne, while the incidence of severe acne was significantly reduced (p < 0.001) (14). Others studies show that some chemical UV filters, such as benzophenone-4 and para-aminobenzoic acid derivatives, may induce cutaneous irritation, leading to varying degrees of erythematous papules and vesicles (15, 16). However, different from previous studies, this research focused on patients with rosacea, for whom the association between sunscreen use and acne risk may be attributed to the occlusive or comedogenic properties of certain sunscreen formulations. Although physical sunscreens containing zinc oxide and titanium dioxide are generally safer for sensitive skin, certain formulations may cause pore occlusion due to their thick texture (17). Furthermore, the incorporation of “water-resistant” or “sweat proof” ingredients in modern sunscreens often necessitates thorough cleansing. Incomplete removal of these residues may exacerbate follicular occlusion, while the required use of potent cleansers could compromise stratum corneum integrity. This detrimental effect is particularly pronounced in rosacea patients who exhibit pre-existing abnormalities in stratum corneum structure and skin barrier function (18). Interestingly, other variables considered risk factors for acne in the general population, such as ethnicity, marital status, annual household income, occupation, and the use of cleaning products, did not show significant associations with acne prevalence in the rosacea population. This suggests that the pathological process of rosacea may have changed the spectrum of common risk factors for acne to a certain extent. The inducing mechanism of acne in patients with rosacea is different from that in the general population and deserves further exploration.
The protective effect of longer sleep duration is consistent with previous research. Existing studies have shown that adequate sleep plays an important role in reducing systemic inflammation levels and promoting the repair of the skin barrier, which may have a positive impact on alleviating the severity of acne or rosacea (6). In addition, the disorder of the circadian rhythm is also regarded as a factor that aggravates the inflammatory response of rosacea. Studies have found that circadian rhythm disorders can affect the polarization of macrophages, causing them to polarize towards type M1, thereby promoting the expression of inflammatory factors such as tumor necrosis factor-α, interleukin-6, and interleukin-1β, which exacerbates the inflammatory response of skin lesions (19). Therefore, maintaining a regular schedule and getting sufficient sleep may play a key role in the treatment and management of rosacea.
This study emphasizes that when managing patients with rosacea complicated with acne, individualized skin care and lifestyle advice should be provided. Clinicians should be more cautious when recommending sun protection products. They should give priority to physical sun protection measures such as sun umbrellas and sun hats, or sun protection products that do not cause acne and are suitable for sensitive skin. At the same time, they should encourage patients to ensure adequate sleep to promote the improvement of acne.
5. Strengths and limitations
This study has the following strengths: First, the large sample size enabled us to identify a representative population of rosacea patients from the general population and comprehensively analyze risk factors associated with acne comorbidity. Second, the diagnosis of both rosacea and acne was performed by two board-certified dermatologists rather than relying on self-report or guideline-based criteria, significantly enhancing the reliability of subsequent analyses and conclusions. Third, this study innovatively investigated risk factors for acne in rosacea patients, along with subgroup analyses and linear association analyses, providing crucial evidence for developing scientific treatment and daily skincare guidelines for this patient population.
However, several limitations should be acknowledged: First, as a cross-sectional study, causality between risk factors and acne cannot be established, necessitating further validation through cohort studies. Second, several key exposures, including sleep duration and skincare behaviors were assessed using self-reported questionnaires, which may not capture the complexity of behavioral patterns (such as the composition of sunscreen, sleep quality, etc.), and introduce potential recall bias. Finally, the relatively low overall prevalence of rosacea in the general population may have limited the in-depth analysis of the relationship between risk factors and acne, potentially obscuring some associations. The observed associations require the use of more objective and comprehensive exposure assessment methods in the future and verification through prospective cohort studies to validate.
6. Conclusion
This study reveals that insufficient sleep time and frequent use of sunscreen products play an important role in the comorbidity of rosacea and acne vulgaris. It is worth noting that the risk factors for acne in patients with rosacea are different from those in the general population, suggesting that in clinical diagnosis, treatment and management of patients, there should be more targeted plans for the prevention and treatment of acne in patients with rosacea. In the future, it is necessary to further clarify the potential physiological mechanisms between the use of sunscreen products and sleep duration and the occurrence of acne through longitudinal research design and mechanism exploration and verify these associations in different populations.
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the Sanming Project of Medicine in Shenzhen (Grant No. SZSM202311020) and the Shenzhen Medical Key Discipline Construction Fund (Grant No. SZXK065). The funding bodies had no role in the design of the study; the collection, analysis, and interpretation of data; the writing of the manuscript; or the decision to submit the article for publication.
Footnotes
Edited by: Mohiuddin Md. Taimur Khan, Washington State University Tri-Cities, United States
Reviewed by: Tianhao Li, Hospital of Chengdu University of Traditional Chinese Medicine, China
Heni Muflihah, Bandung Islamic University, Indonesia
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.
Ethics statement
The studies involving humans were approved by Institutional Review Board of Shenzhen Center for Chronic Diseases Control, Shenzhen, China (SZCCC-2023-034-01-PJ). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
SH: Writing – original draft. XC: Investigation, Writing – original draft. JZ: Data curation, Writing – review & editing. YZ: Writing – original draft. YG: Project administration, Resources, Writing – review & editing. JL: Data curation, Writing – original draft. HG: Data curation, Writing – original draft, Writing – review & editing. XH: Data curation, Writing – review & editing. MH: Project administration, Writing – review & editing. NN: Investigation, Writing – review & editing. JH: Investigation, Writing – review & editing. ZZ: Project administration, Writing – review & editing. YL: Project administration, Writing – review & editing. XL: Investigation, Project administration, Resources, Writing – review & editing.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2026.1859962/full#supplementary-material
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Data Availability Statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.