Background/Purpose: Understanding the role of environmental exposures in the development of SLE and their association with SLE activity may help identify modifiable risk factors and potential etiological mechanisms. We hypothesized that changes in fine particulate matter (PM2.5) concentration, ozone concentration, temperature, resultant wind, relative humidity, and barometric pressure are predictive of organ specific flares in lupus.

Methods: 1628 patients who fulfill 4 of the 11 ACR or SLICC classification criteria for SLE were included in the analysis. The data ranged from 1999 to 2017. Maximum distance between visits was 110 days with 1 month time aggregation units. Disease activity was expressed as Physician Global Estimate (PGA), taken at every patient visit. A flare was defined as a PGA score increase of 1 point or more compared to the previous visit. Environmental and atmospheric data was obtained from the EPA, including PM2.5 and ozone concentration, temperature, residual wind, relative humidity, and barometric pressure. The average values of each factor 10 days prior to patient visit was calculated. Univariate and multivariate models were built in order to study the association of these variables with lupus disease activity. The models were adjusted for age, sex, income, racial distribution, and rural vs. urban patient residence. Multivariate logistic regression was used to identify significant determinants associated with lupus flares. Regression was performed for each organ flare outcome. Regression inference was based on generalized estimating equations (GEE) to account for the time repeated outcomes.

Results: Rash, serositis, hematologic, and joint flares were statistically significantly associated (p< 0.0.5) with an increase in temperature in univariate and multivariate analysis. Renal flares were negatively associated with increases in temperature (p< 0.05) in both univariate and multivariate analysis. Renal flares were negatively associated with increases in ozone concentration (p< 0.05) in univariate and multivariate analysis. Joint (p< 0.001), neurologic (p< 0.001), renal (p< 0.01), hematologic (p< 0.05), and pulmonary (p< 0.001) flares were directly associated with residual wind in univariate and multivariate analysis. Humidity was significantly associated with joint (p< 0.001), and serositis (p< 0.05) flares in univariate and multivariate analysis. Barometric pressure had no significant associations. PM2.5 concentration was significantly associated with rash (p< 0.001), joints (p< 0.001), serositis (p< 0.001), and hematologic flares (p< 0.001) in univariate and multivariate analysis.

Conclusion: There is a strong association between changes in atmospheric and environmental variables 10 days prior to patient visit and organ specific lupus activity at the visit. No environmental or atmospheric factor had a general association with all organ specific lupus flares. These data could add an important aspect to lupus trials, the outcomes of which may be affected by so far unrecognized environmental factors, and ultimately it could allow predictive modelling of lupus flares which would revolutionize the approach to treatment.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/environmental-and-atmospheric-factors-in-systemic-lupus-erythematosus-a-regression-analysis/