Associations of long-term exposure to air pollution and physical activity with the risk of systemic inflammation-induced multimorbidity in Chinese adults: results from the China multi-ethnic cohort study (CMEC).

OBJECTIVE: Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM. METHODS: This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM. RESULTS: We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure). CONCLUSIONS: Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA's importance in reducing SIIM for all people, especially those living in high-level air pollution regions.

Long-term exposure to ambient PM2.5 constituents is associated with dyslipidemia in Chinese adults.

BACKGROUND: Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) consists of various toxic constituents. However, the health effect of PM2.5 may differ depending on its constituents, but the joint effect of PM2.5 constituents remains incompletely understood. OBJECTIVE: Our goal was to evaluate the joint effect of long-term PM2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. METHODS: This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C) < 1.04 mmol/L, and low-density lipoprotein cholesterol (LDL-C) ≥ 4.14 mmol/L. The logistic regression model was utilized to examine the single effect of PM2.5 constituents on dyslipidemia, while the weighted quantile sum regression model for the joint effect. RESULTS: The odds ratio with a 95 % confidence interval for dyslipidemia positively related to per-SD increase in the three-year average was 1.29 (1.20-1.38) for PM2.5 mass, 1.25 (1.17-1.34) for black carbon, 1.24 (1.16-1.33) for ammonium, 1.33 (1.24-1.43) for nitrate, 1.34 (1.25-1.44) for organic matter, 1.15 (1.08-1.23) for sulfate, 1.30 (1.22-1.38) for soil particles, and 1.12 (1.05-1.92) for sea salt. Stronger associations were observed in individuals < 65 years of age, males, and those with low physical activity. Joint exposure to PM2.5 constituents was positively related to dyslipidemia (OR: 1.09, 95 %CI: 1.05-1.14). Nitrate was identified as the constituent with the largest weight (weighted at 0.387). CONCLUSIONS: Long-term exposure to PM2.5 constituents poses a significant risk to dyslipidemia and nitrate might be the most responsible for the risk. These findings indicate that reducing PM2.5 constituent exposures, especially nitrate, could be beneficial to alleviate the burden of disease attributed to PM2.5-related dyslipidemia.

Does awareness of diabetic status increase risk of depressive or anxious symptoms? Findings from the China Multi-Ethnic cohort (CMEC) study.

INTRODUCTION: People with diabetes mellitus (DM) have increased risk of depressive symptoms (DS) or anxious symptoms (AS). This study explores whether awareness of DM will contribute to prevalence of DS or AS. METHODS: The baseline data including 81,717 adults from Southwest China was analyzed. DS and AS were assessed using PHQ-2 and GAD-2. Exposures were defined as 1) having self-reported physician diagnosis of diabetes (self-reported DM), 2) no prior diagnosis of diabetes but meeting diagnostic criteria (newly diagnosed DM), 3) having self-reported physician diagnosis or meeting criteria of non-diabetic diseases (non-diabetic patients), 4) healthy participants. Generalized linear mixed models were used to assess impact of presence and awareness of DM on DS or AS, adjusting for regional and individual related factors. RESULTS: The prevalence of DS in self-reported DM, newly diagnosed DM, non-diabetic patient and healthy participants was 7.08 %, 4.30 %, 5.37 % and 3.17 %. The prevalence of AS was 7.80 %, 5.77 %, 6.37 % and 3.91 %. After adjusting for related factors, compared with healthy participants, self-reported DM and non-diabetic patients were associated with DS [AORDS, self-reported = 1.443(1.218,1.710), AORDS, nondiabetic patients = 1.265(1.143,1.400)], while the association between newly diagnosed DM and DS was not statistically significant. The associations between self-reported DM, newly diagnosed DM, non-diabetic patients and AS were all statistically significant. LIMITATIONS: DS and AS were assessed through self-report and may suffer recall or information bias. CONCLUSIONS: The association between awareness of diabetes and DS/AS suggests to pay attention to distinguish between self-reported and newly diagnosed DM and screening for DS and AS in diabetic population.

Ambient fine particulate pollution and daily morbidity of stroke in Chengdu, China.

INTRODUCTION: Association has been reported between ambient fine particulate matter (PM) and adverse outcomes of cerebrovascular events. However, it remains unclear that whether short-term exposure to PM relates to stroke and the lag of health effects. This triggers us to examine the relationship between PM and population stroke morbidity in Chengdu. METHODS: The daily average concentration of atmospheric pollutants and meteorological factors and daily morbidity of stroke in Chengdu (2013-2015) were collected. Based on time series analysis-generalized additive models (GAM), single-pollutant, two-pollutant and multi-pollutant model were established. The effects of atmospheric PM2.5 (defined as PM less than 2.5µm in aerodynamic diameter), PMc(defined as PM less than 10µm and more than 2.5µm in aerodynamic diameter) and PM10 (defined as PM less than 10µm in aerodynamic diameter) concentration on the daily mortality of stroke were analyzed, respectively. RESULTS: The three-year mean concentrations of PM2.5, PMc and PM10 for air pollutants were 75.9, 43.9 and 119.7 µg/m3, respectively. PM2.5 on the current day (lag0) and with a moving average of 0-1 days were significantly associated with the increasing risk of stroke morbidity, and PM2.5 with a lag of 0-1 days had greater association, whereas for PMc and PM10 there were no significant association observed. In our study, every 10µg/m3 increase of PM2.5 was associated with 0.69% percent change in stroke morbidity (95%CI: 0.01~1.38). For females, every 10µg/m3 increase of PM2.5 contributes to 0.80% percent change of onset. And for the group of age less than 65, we observed 0.78% higher risk every 10µg/m3 increase of PM2.5. CONCLUSIONS: These findings suggest that short-term exposure to PM2.5 within 1 day is associated with the onset of stroke, and the younger people (age<65) and females are more sensitive than older people and males.