Weather, air pollution and rheumatic diseases: a prospective and correlational study of influence of weather and air pollution on the perception of joint pain in patients with chronic rheumatic diseases
N.R. Ziade Osteoarthritis and Cartilage VOLUME 26, SUPPLEMENT 1, S212-S213, APRIL 01, 2018
To evaluate the association between weather variables, pollution indices and the perception of joint pain in patients with chronic rheumatic diseases (CRD).
Methods: We conducted a prospective correlational study. Consecutive adult patients with CRD (Osteoarthritis (OA), Rheumatoid Arthritis (RA) and Spondyloarthritis (SpA)) living in a predefined catchment area were included. Demographic data were collected including disease activity, anxiety and depression evaluation (PHQ4) and treatments. Patients were given a specifically designed calendar and asked to fill their level of pain daily using a 0–10 scale. Weather variables (temperature, humidity, atmospheric pressure) and pollution indices (PM10, PM2.5 and NO2) were recorded during the same period, using sensors located in the same catchment area. A variable “Delta Pain” was calculated by subtraction between the maximum and minimum of reported pain across the study. Patients with high variability were identified and associated factors were studied. Correlation with weather variables and pollution indices was studied using correlational methods (Pearson correlation). Data from January to September 2017 was analysed using SPSS V23 and Origin Pro V8 statistical software.
Results: 94 out of the 106 invited patients accepted to participate (89%): 39 RA, 27 OA and 28 SpA (Table 1, Patients Characteristics). Baseline pain level was 3.58/10 and handicap level was 3.36. Subjectively, 57% of patients stated that their pain was associated with weather changes (74% with cold, 20% with humidity and 6% with heat).The “Delta Pain” value of 3 corresponded to the 25th percentile and the value of 7 corresponded to the 75th percentile of the population, and was used to define “high pain variability”. High variability correlated with high disease activity and body mass index. In all disease categories, pain increased slightly from week 1 (January) to Week 9 then decreased between week 9 (End of February) and week 39 (September). This decrease was in clear opposition with the increase in temperatures during the same period. A small increase in pain was observed in week 22 (May), mirroring an increase in humidity rates in week 21 (Fig. 1). We found a statistically significant negative correlation between the CRD and temperature (P < 0.001). There was a trend towards a negative correlation between CRD and humidity rates (P 0.07). There was also a positive correlation between the CRD and NO2 levels (P < 0.01) and between RA and PM10 levels (P 0.04).
Conclusions: We identified a clear seasonal trend in pain perception in CRD. There was an inverse correlation with temperature and a trend towards inverse correlation with humidity. For the first time, a positive correlation was found with pollution indices (CRD and NO2, RA and PM10). The study needs to be pursued in a new cold season to confirm the reproducibility of these trends.