Evidence for the causal relationship of particulate matters (PMs) exposure with kidney disease, especially PM1, PM1-2.5 and PM2.5-10, remained scarce among developing countries with severe pollution. We conducted a longitudinal cohort study involving 13,041 adults with free kidney disease from 150 Chinese counties. PMs concentrations were generated using a well-established satellite-based spatiotemporal model. And the time-varying Cox regression model along with stratified analyses were performed to determine the association and potential modifiers, respectively. We also calculated the population-attributable fraction to evaluate the burden of kidney disease attributable to PMs pollution. Between Jan 2011 and Dec 2018, 985 kidney disease incidents were identified with an incidence rate of 12.69 per 1000 person-years. Significant dose-response relationships were observed for all 5 kinds PMs. Specifically, an increased risk of kidney disease was associated with per 10 μg/m3 increment of PM1 (HR = 1.187, 95%CI: 1.114 to 1.265), PM1-2.5 (1.326, 1.212 to 1.452), PM2.5 (1.197, 1.139 to 1.258), PM2.5-10 (1.297, 1.240 to 1.357), and PM10 (1.137, 1.108 to 1.166). A mixture analysis method of weighted quantile regression model revealed that PM2.5-10 predominated the PMs mixture index (57.1 %), and followed with PM10 (26.4 %). Stratified analyses indicated the elder, overweight persons, smokers, respiratory patients and urban residents were more vulnerable to PMs pollution than their counterparts. Calculated population attributable fractions of kidney disease attributable to PMs pollution was 16.67-39.47 %. Higher PMs pollution was associated with the increased risk of kidney disease development in China. Acceleration of efforts to reduce PMs pollution was therefore urgently needed to alleviate kidney disease burden.
Keywords: Disease burden; Kidney disease; Nation-wide cohort study; Particulate matter pollution.
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