Geographic distribution and environmental triggers of systemic sclerosis cases from 2 large academic tertiary centers in Massachusetts

Abstract

To the Editor: Systemic sclerosis (SSc) is a chronic autoimmune sclerosing disease with the highest case fatality rate among connective tissue diseases.1Feghali-Bostwick C.A. Varga J. Systemic Sclerosis.in: Bradshaw R.A. Dennis E.A. Handbook of Cell Signaling. 2nd ed. Academic Press, 2010: 2913-2917Crossref Scopus (1) Google Scholar Since the 1980s, the annual incidence rates in North America have increased from 1.7 to 2.7 per 100,000 individuals.2Bergamasco A. Hartmann N. Wallace L. Verpillat P. Epidemiology of systemic sclerosis and systemic sclerosis-associated interstitial lung disease.Clin Epidemiol. 2019; 11: 257-273Crossref PubMed Scopus (66) Google Scholar Although the exact pathogenesis of SSc remains unclear, environmental triggers have been hypothesized to provoke disease development among genetically predisposed hosts.3Barnes J. Mayes M.D. Epidemiology of systemic sclerosis: incidence, prevalence, survival, risk factors, malignancy, and environmental triggers.Curr Opin Rheumatol. 2012; 24: 165-170Crossref PubMed Scopus (212) Google Scholar,4McCormic Z.D. Khuder S.S. Aryal B.K. Ames A.L. Khuder S.A. Occupational silica exposure as a risk factor for scleroderma: a meta-analysis.Int Arch Occup Environ Health. 2010; 83: 763-769Crossref PubMed Scopus (82) Google Scholar The assessment of high-prevalence geographic clusters may be a crucial first step in cause identification. Our objectives were to analyze SSc hotspots in Massachusetts and identify possible environmental triggers. The research patient data registry was utilized to identify 4579 potential SSc cases and zip codes from medical records between 1989 and 2019 of Massachusetts General Hospital and Brigham and Women's Hospital. Cases confirmed by dermatologists or rheumatologists were included (n = 2196). The period prevalence was calculated based on the population per zip code. QGIS3.10, a geospatial program, was used to create and analyze SSc distribution and prevalence maps (Fig 1). These maps were compared to environmental toxins and social justice maps to determine trends in etiologic triggers and demographic clusters. Statistical analysis was performed using 2 sample t tests. Hazardous waste facilities (P = .0039) and oil release or disposal sites (P = .0203) were significantly associated with a higher SSc prevalence (Fig 2). Although the association between chemical release sites and SSc prevalence was not independently significant (P = .3166), a spatial correlation was found to exist. Exposure to all 3 sites together posed a significantly increased SSc risk (P = .0002). Disease hotspots showed greater particulate pollution levels and were in proximity to ash pollution and combustion facilities (Supplemental Fig 1 available via Mendeley at https://data.mendeley.com/datasets/59zfn6fdb2/2). The maps of low-income and minority communities demonstrated a spatial relationship with SSc hotspots, suggesting a possible association between socioeconomic factors and disease (Supplemental Fig 2 available via Mendeley at https://data.mendeley.com/datasets/59zfn6fdb2/2).5Environmental justice populations in Massachusetts | Mass.gov.https://www.mass.gov/info-details/environmental-justice-populations-in-massachusettsDate accessed: January 27, 2021Google Scholar The presence of SSc regional clustering and increased density of industry and waste sites in these areas suggest that environmental pollutants play a critical role in disease development. Additionally, the clustering of SSc hotspots and environmental pollutants around low-income and minority neighborhoods indicates that these residents face a disproportionate burden of toxin exposure and disease. High-SSc prevalence pockets in Central and Western Massachusetts with few or no direct toxin sites may be impacted by their surrounding environmental factors, such as water sources collecting precipitated pollutants from nearby facilities or by cross-state pollution, both waterborne and airborne. Another possible explanation for SSc regional clustering is the social drift hypothesis, suggesting that those with chronic diseases are more likely to reside in low-income areas because of disease burden. The study limitations include potential confounders contributing to disease, such as genetic predispositions, sociodemographic factors, and proximity bias. Finally, our study demonstrated a correlation but could not prove causation, making further study of this important topic crucial. Further investigations, including wider geographies and more diverse patient populations, are warranted. Ultimately, this research may provide a greater understanding of the potential role of environmental toxins in SSc onset. Furthermore, it may be used as an advocate for environmental and health policy reforms to protect communities disproportionately burdened by their exposure to environmental toxins and their adverse health effects. None disclosed.