Abstract
Background:
Hidradenitis suppurativa (HS) is an inflammatory condition associated with cysts of the folliculopilosebaceous unit primarily affecting intertriginous areas. HS has been correlated with smoke exposure in the adult population, but there is a knowledge gap in understanding its effect in pediatric and adolescent patients. This study assesses correlations between active and passive smoke exposure and the development of HS in the pediatric and adolescent population.
Methods:
A retrospective case–control study was conducted at Mayo Clinic (2010–2023) of patients diagnosed with HS before the age of 18 years who were age-, sex-, and race-matched to healthy controls in a 1:3 ratio, analyzed using Fisher exact for categorical variables and Kruskal–Wallis for continuous.
Results:
One hundred and seventy-four cases and 522 controls met inclusion criteria. The prevalence of active and passive smoke exposure was significantly higher in patients with HS compared to controls (p = 0.001), with passive smoke accounting for 64.6% (N = 31/48) of smoke exposure in patients with HS. Smoke exposure was associated with a significant increase in the odds of an HS diagnosis, with an odds ratio of 4.8 (95% CI: 3.06–7.61) for passive and/or active exposure, and 1.64 (95% CI: 1.01–2.61) for passive exposure alone. Smoke exposure was associated with a later age of diagnosis than those with no smoke exposure (p < 0.001).
Conclusion:
Prevalence of active and passive smoke exposure was higher in pediatric and adolescent patients with HS compared to age, sex, and race-matched healthy controls. Smoke exposure increased the odds of having HS and was associated with a later age at diagnosis.
Keywords: active smoke, hidradenitis suppurativa, HS, passive smoke, pediatric dermatology, secondhand smoke, smoke exposure, smoking
1 |. Introduction
Hidradenitis suppurativa (HS) is an inflammatory condition characterized by chronic inflammation, tunneling and abscess formation primarily in intertriginous regions [1]. HS lesions can be incredibly painful and are often associated with malodorous drainage and scarring, affecting quality of life and self-esteem [1]. Those who develop HS in childhood or adolescence face distinct challenges related to development, including issues with self-identity, sexuality, and mood disorders. Children and adolescents with HS are often affected by bullying at school, self-isolation, and low self-esteem [2]. Treating HS in pediatric and adolescent patients is also more difficult as many of the systemic therapies have only been tested for safety and efficacy in adults [2].
Many risk factors have been described for HS, with the strongest being female sex, smoking, and obesity [3]. Studies have consistently shown a correlation between HS and smoking [4–7]. Rates of active smoke exposure in adults with HS have been reported to be as high as 90% [8], with passive (environmental, or secondhand smoke) exposure reported in up to half of nonsmoking patients [9]. Although a definite causal relationship has not been established, smoking is thought to play a crucial role in the pathophysiology of HS. The overall adjusted odds ratio of developing HS has been reported as high as 1.90 among smokers compared to nonsmokers when accounting for differences in age, sex, obesity, and race [4]. Despite the onset of HS often occurring in adolescence (reported in up to 51.5% [10] of patients), the prevalence of smoking in children and adolescents with HS [2] is much lower than the prevalence shown in adult studies [1, 8]. A possible explanation for this discrepancy may be attributed to passive smoke exposure, which disproportionately affects children [11]. While passive exposure has been shown to negatively impact HS in adults [9], this relationship has not been evaluated in pediatric and adolescent patients. The aim of this study is to evaluate the effects associated with active and passive smoke exposure of reported substances via any delivery mechanism (including but not limited to substances inhaled via cigarettes, cigars, and E-cigarettes) on the development of HS in pediatric and adolescent patients through an age, sex, and race-matched case–control study.
2 |. Materials and Methods
2.1 |. Patients and Variables
A case–control study was conducted with patients who presented to Mayo Clinic in Rochester, MN, between 2010 and 2023. The study was reviewed and deemed exempt by the Mayo Clinic IRB. Cases were patients diagnosed with HS prior to 18 years of age and were identified by ICD-10 codes L73.0–L73.9. Controls were obtained from patients presenting for well-child visits identified by ICD-10 code Z00.129, excluding those with HS. For cases and controls, medical records were reviewed to obtain biologic sex, age, race, body mass index (BMI) and smoking status. For cases, HS treatments were reviewed to determine the history of biologic use.
Smoking status was obtained by review of pre-visit questionnaires in the medical record. Provider-documented social histories were used to obtain smoking status in cases who had not completed a pre-visit questionnaire, while controls who had not completed a pre-visit questionnaire were excluded. The types of smoke and smokeless substances were recorded in cases and controls with active exposure only (this information was not available in those with passive exposure) and included the use of E-cigarettes.
2.2 |. Matching
Groups of interest were 1:1 propensity score matched to account for baseline differences in variables, derived from multivariable logistic regression using the potential known confounders in a 1:3 ratio. Controls were matched to cases by age at the time of HS diagnosis, race, and sex assigned at birth. Nearest neighbor matching was performed using the caliper width of the standard deviation of the scores multiplied by 0.2.
2.3 |. Categorizing Smoke Exposure
Pre-visit questionnaires from birth to 18 years of age were reviewed, and patients were divided into one of three groups: (1) No smoke exposure, (2) passive smoke exposure, or (3) active smoke exposure according to the process in Figure 1.
FIGURE 1 |.
Grouping of patients into three categories: (1) “No smoke exposure”, (2) “passive smoke exposure”, and (3) “active smoke exposure” based on patient-provided answers to pre-visit questionnaires.
2.4 |. Statistical Analysis
Univariate comparisons between patients with HS and healthy controls were performed using chi-squared and Kruskal–Wallis tests as appropriate. Multivariable logistic regression was used to calculate odds ratios to determine the association between smoke exposure and HS after controlling for potential confounders. Continuous variables are reported as mean (standard deviation) and categorical variables are reported as N (%). P < 0.05 defined significance. Analysis was conducted in RStudio version 4.1.3 (RStudio, PBC, USA) and BlueSky Commercial Server Edition version 7.40.
3 |. Results
One hundred and seventy-four patients with HS and 522 healthy controls met inclusion criteria for the study. Pediatric and adolescent patients with HS had higher rates of active and passive smoke exposure than healthy controls of similar age, sex, and race. Active smoke exposure in patients with HS was predominantly attributed to cigarettes at 94.1% (N = 16/17), with 5.9% (N = 1/17) using a cannabis e-cigarette, while healthy controls who smoked had higher rates of e-cigarettes, cannabis, or did not specify a substance on their questionnaire. In patients with HS, 64.6% (N = 31/48) of smoke exposure was attributed to passive smoke. The prevalence of passive smoke exposure was significantly higher in patients with HS compared to healthy controls (p = 0.039) and increased the odds of an HS diagnosis to 1.64 (CI: 1.01–2.61). Additionally, the odds of an HS diagnosis when accounting for active and/or passive smoke exposure were higher (OR 4.82; CI: 3.06–7.61) than the odds of an HS diagnosis when considering only active smoking (OR=2.87; CI: 1.44–5.66). Results comparing patient demographics, smoke exposure, and comorbidities between cases and controls are reported in Table 1. Analysis comparing age of diagnosis and smoke exposure in patients with HS is included in Figure 2.
TABLE 1.
Summary of demographics in cases and controls.
| Healthy controls (N = 522) | HS cases (N = 174) | Total (N = 696) | Odds ratio | p | |
|---|---|---|---|---|---|
| Age in years | 1.000a | ||||
| Mean (SD) | 14.3 (2.3) | 14.3 (2.3) | 14.3 (2.3) | ||
| Sex, N (%) | 1.000b | ||||
| Female | 447 (85.6%) | 149 (85.6%) | 596 (85.6%) | ||
| Male | 75 (14.4%) | 25 (14.4%) | 100 (14.4%) | ||
| Race | 1.000b | ||||
| White | 354 (67.8%) | 118 (67.8%) | 472 (67.8%) | ||
| Non-White | 168 (32.2%) | 56 (32.2%) | 224 (32.2%) | ||
| Black/African American | 46 (9.8%) | 22 (15.0%) | 68 (11.0%) | ||
| Native Hawaiian/other Pacific Islander | 29 (6.2%) | 1 (0.7%) | 30 (4.9%) | ||
| Other/unknown | 38 (8.1%) | 6 (4.1%) | 44 (7.1%) | ||
| Body mass index (BMI) | 0.001a | ||||
| kg/m2, mean (SD) | 23.4 (7.0) | 26.1 (8.2) | 24.0 (7.4) | ||
| Classification | 0.001b | ||||
| Underweight (< 18.5) | 93 (17.8%) | 37 (21.3%) | 130 (18.7%) | ||
| Normal weight (18.5–24.9) | 266 (51.0%) | 55 (31.6%) | 321 (46.1%) | ||
| Overweight (25–29.9) | 93 (17.8%) | 31 (17.8%) | 124 (17.8%) | ||
| Obese (> 30) | 70 (13.4%) | 51 (29.3%) | 121 (17.4%) | ||
| History of smoke exposure prior to the age of 18 years | |||||
| Active or passive | 80 (15.3%) | 48 (27.6%) | 128 (20.5%) | 4.82 (3.06–7.61) | < 0.001b |
| Passive | 61 (11.7%) | 31 (17.8%) | 92 (13.2%) | 1.64 (1.01–2.61) | 0.040b |
| Active | 19 (3.6%) | 17 (9.8%) | 36 (5.2%) | 2.87 (1.44–5.66) | 0.002b |
| Substances | N = 19 | N = 17 | N = 36 | ||
| Cigarettes | 3 (15.8%) | 16 (94.1%) | 19 (52.8%) | ||
| Cannabis | 5 (26.3%) | 0 (0%) | 5 (13.9%) | ||
| E-cigarettes | |||||
| Nicotine | 2 (10.5%) | 0 (0%) | 2 (5.6%) | ||
| Cannabis | 2 (10.5%) | 1 (5.9%) | 3 (8.3%) | ||
| Substance unknown | 10 (52.6%) | 0 (0%) | 10 (27.8%) | ||
Abbreviations: BMI, body mass index; HS, hidradenitis suppurativa; SD, standard deviation.
Kruskal–Wallis rank sum test.
Pearson’s chi-squared test.
FIGURE 2 |.
Smoke exposure (including active and passive exposure) was correlated with an older age of hidradenitis suppurativa diagnosis compared to those who reported no smoke exposure.
4 |. Discussion
The higher prevalence of active smoke exposure seen among those with HS compared to controls is consistent with past studies in pediatric and adolescent patients [12, 13]. Interestingly, passive smoke exposure comprised more than half of smoke exposure in patients with HS which differs from adult HS studies in which the greatest smoke exposure is attributed to active smoking [9], but aligns with the US Surgeon General Report detailing that children and adolescents are significantly more likely than adults to experience passive smoke exposure at home [11]. Both active and passive smoke exposure increased the odds of an HS diagnosis when considered independently, and the odds ratio increased further when all exposures were analyzed together as active and/or passive exposure (Table 2). These results suggest both active and passive smoke exposure may contribute to an HS diagnosis and are supported by the overall older age of diagnosis seen in patients with smoke exposure (active and/or passive) compared to those with no smoke exposure (p < 0.001) shown in Figure 2. Older age of diagnosis in patients with smoke exposure has been previously reported and may point to smoke being a trigger for HS onset in those without a strong genetic predisposition [9].
TABLE 2.
Prevalence of biologic medication use in patients with HS who had active and/or passive smoke exposure compared to those with no smoke exposure.
| History of smoke exposure prior to the age of 18 years in patients with HS | Active and/or passive (N = 48) | No exposure (N = 126) | Total (N = 174) | p |
|---|---|---|---|---|
| Biologic use | 0.6941a | |||
| Yes | 4 (8.3%) | 13 (10.3%) | 48 (27.6%) | |
| No | 44 (91.7%) | 113 (89.7%) | 126 (72.4%) |
Abbreviation: HS, hidradenitis suppurativa.
Pearson’s chi-squared test.
While the mechanism underlying smoke as a trigger for HS is speculative, studies postulate smoke induces activation of nicotinic acetylcholine receptors (nAchRs) and aryl hydrocarbon receptors that suppress the Notch signaling pathway, thereby leading to inflammation [14]. Additionally, smoking has been shown to change the ratio of perifollicular regulatory and helper T cells, causing inflammation and dissection of terminal hair follicles that give rise to abscesses [15]. Considering the disease mechanism, it is logical that smoke exposure could impact disease severity and treatment response, and previous studies have shown disease severity and treatment response are worsened with increasing pack-year history [16, 17]. Our results showed no significant overall difference in the prevalence of biologic use between cases with active and/or passive smoke exposure compared to those with no exposure; however, the sample size is very small with four HS patients exposed to smoking being on biologics while 13 patients in the non-exposed group were on biologics.
Regarding weight, the percentage of patients with a BMI in the overweight category was the same for both cases and controls, but BMI categorization differed significantly due to a higher prevalence of underweight and obese patients in the HS group. While obesity poses a potential confounder to our study, passive smoke exposure is associated with an increased risk of lifetime obesity in the child [18], making this a difficult variable to control for without altering the detection of differences in smoke exposure between cases and controls. The higher prevalence of obesity seen in patients with HS in our study is consistent with previous reports [3, 19] and underscores the importance of holistic management for patients with HS.
In light of the overall results of this study suggesting both active and passive smoke exposure are correlated with HS in pediatric and adolescent patients, care should focus on limiting all forms of smoke exposure as much as possible. Studies have shown that motivation to quit smoking in adults is highest when emphasis is placed on the risk posed to those around them rather than the risk posed to themselves [20]. Thus, knowing a correlation exists between passive smoke exposure and HS could be an effective motivational factor to include when counseling parents and caregivers of pediatric and adolescent patients with HS on smoking cessation.
5 |. Limitations
Questionnaires are considered a common and advantageous method to assess smoking status by the US Office of Smoking and Health [21]; however, in our study these did not allow quantification of smoke exposure or ability to assess a dose-dependent relationship, nor were we able to obtain granular data on the source or substance of passive smoke exposure. Additionally, the possibility that patients were misclassified due to respondent recall bias regarding smoke exposure throughout the duration of childhood cannot be excluded. Other weaknesses include the retrospective design and smaller sample size, which limit the generalizability of the study and preclude establishing a definite causal relationship between passive smoke exposure and HS. Lastly, to avoid over-matching, controls were race-matched to cases based on white versus non-white categories, resulting in uneven distribution of Black/African American and Pacific Islander patients.
6 |. Conclusion
This study demonstrates a correlation between passive and active smoke exposure in pediatric and adolescent patients with HS as compared to healthy controls of similar age, sex, and race. Patients with active and/or passive smoke exposure were diagnosed at a later age than those with no smoke exposure, suggesting smoke as a possible trigger for disease development. Holistic care should focus on limiting passive and active smoke exposure in pediatric and adolescent patients with HS, and counseling on the risk of passive smoke should be emphasized to parents and caregivers who smoke.
Funding:
This work was supported by the National Institute of Health (NIH), and National Institute of General Medical Sciences Grant (T32 GM145408).
Footnotes
Conflicts of Interest
Author A.A. is a consultant for and/or has received consultation fees from InflaRx, AbbVie, Boehringer Ingelheim, Novartis, UCB, Processa Pharmaceuticals, Incyte Corporation, Almirall, and Kymera Therapeutics; however, this is solely the primary author’s work without any connection to these companies. N.A.M. has received one time consultation fee from Mosaic Research Management. This is solely the primary authors work with no connection to any company. The other authors (A.N., R.L.Z., A.T., D.M.D.) declare no conflicts of interest.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.