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This study aimed to describe the relationship between long-term PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and kidney disease, including eGFR, level of albuminuria, and incident CKD.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design, setting, participants, &amp; measurements<\/jats:title>\n                    <jats:p>\n                      The study included 10,997 participants from the Atherosclerosis Risk in Communities cohort who were followed from 1996\u20131998 through 2016. Monthly mean PM\n                      <jats:sub>2.5<\/jats:sub>\n                      concentrations (\n                      <jats:italic toggle=\"yes\">\u03bc<\/jats:italic>\n                      g\/m\n                      <jats:sup>3<\/jats:sup>\n                      ) were estimated at geocoded participant addresses using geographic information system\u2013based, spatiotemporal generalized additive mixed models\u2014including geospatial covariates such as land use\u2014and then averaged over the 12-month period preceding participant examination. Covariate-adjusted, cross-sectional associations of PM\n                      <jats:sub>2.5<\/jats:sub>\n                      , baseline eGFR, and urinary albumin-creatinine ratio (UACR) were estimated using linear regression. PM\n                      <jats:sub>2.5<\/jats:sub>\n                      and incident CKD (defined as follow-up eGFR &lt;60 ml\/min per 1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      with \u226525% eGFR decline relative to baseline, CKD-related hospitalization or death based on International Classification of Diseases 9\/10 codes, or development of ESKD) associations were estimated using Cox proportional hazards regression. Modeling was stratified by study site, and stratum-specific estimates were combined using random-effects meta-analyses.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Baseline mean participant age was 63 (\u00b16) years and eGFR was 86 (\u00b116) ml\/min per 1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      . There was no significant PM\n                      <jats:sub>2.5<\/jats:sub>\n                      -eGFR association at baseline. Each 1-\n                      <jats:italic toggle=\"yes\">\u03bc<\/jats:italic>\n                      g\/m\n                      <jats:sup>3<\/jats:sup>\n                      higher annual average PM\n                      <jats:sub>2.5<\/jats:sub>\n                      was associated with higher UACR after adjusting for demographics, socioeconomic status, and clinical covariates (percentage difference, 6.6%; 95% confidence interval [95% CI], 2.6% to 10.7%). Each 1-\n                      <jats:italic toggle=\"yes\">\u03bc<\/jats:italic>\n                      g\/m\n                      <jats:sup>3<\/jats:sup>\n                      higher annual average PM\n                      <jats:sub>2.5<\/jats:sub>\n                      was associated with a significantly higher risk of incident CKD (hazard ratio, 1.05; 95% CI, 1.01 to 1.10).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Exposure to higher annual average PM\n                      <jats:sub>2.5<\/jats:sub>\n                      concentrations was associated with a higher level of albuminuria and higher risk for incident CKD in a community-based cohort.\n                    <\/jats:p>\n                  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