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Objective To evaluate the interactive effects of fine particulate matter and temperature on non-accidental mortality of residents in Pudong, Shanghai. Methods Daily mortality, air pollutants and meteorological data from Jan 1st.2016 to Dec 31st.2017 were collected.Generalized additive Poisson regression models was used to estimate the effects of PM2.5 pollution on daily mortality, bivariate response surface models and temperature stratified models were applied to examine the interaction of temperature with PM2.5 on mortality. Results A total of 43 345 non-accidental deaths were included, daily mean PM2.5 concentration was 39.1 μg/m3, daily mean temperature was 17.7 ℃.A 10 μg/m3 increase in the daily PM2.5 at lag 1 day was associated with a 0.56%(95%CI:0.11%-1.01%), 0.49%(95%CI:-0.19%-1.18%) and 0.22%(95%CI:-1.14%-1.60%) increase in non-accidental, cardiovascular and respiratory mortality, respectively.Higher risks were identified for males and the older (≥65 years).The effect estimates per 10 μg/m3 increase in PM2.5 in medium temperature level were 0.59%(95%CI:0.04%-1.14%)for non-accidental, 0.51%(95%CI:-0.32%-1.35%)for cardiovascular and 0.51%(95%CI:-0.32%-1.35%) for respiratory mortalities.The PM2.5 effects were approximately 2-4 times higher in higher temperature level for non-accidental and cardiovascular mortalities compared with other temperature levels; for respiratory mortality, the PM2.5 effects was approximately 2-fold higher in lower temperature levels than the medium, although the interactions between temperature and PM2.5 were statistically insignificant. Conclusions Temperature may modify the effects of PM2.5 on mortality in Pudong, Shanghai and the interactive pattern may be different across disease-specific mortalities.
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<p><b>OBJECTIVE</b>To investigate the association of ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors (PPARα, δ, γ) with lipid accumulation product (LAP) and the additional role of a gene-gene interactions among the 10 SNPs.</p><p><b>METHODS</b>Participants were recruited under the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu province) cohort populations survey in the urban community of Jiangsu province of China. A total of 820 subjects were randomly selected and no individual was related. Ten SNPs (rs135539, rs4253778, rs1800206, rs2016520, rs9794, rs10865710, rs1805192, rs709158, rs3856806 and rs4684847) were selected from the HapMap database, which covered PPARα, PPARδ and PPARγ. A linear regression model was used to analyze the relations between ten SNPs in the PPARs and LAP. Mean difference (Difference) and 95% confident interval (95%CI)were calculated. Interactions were explored by using the method of Generalized Multifactor Dimensionality Reduction (GMDR).</p><p><b>RESULTS</b>After adjusting the factors as age, gender, smoking status, occupational physical activity, educational level, high-fat diet as well as low-fiber diet, both rs1800206, s1805192 and rs3856806 were significantly associated with the increased level of LAP. Difference (95% CI) values were 32.47 (22.62-42.31), 12.97 (4.61-21.33) and 12.49 (4.24-20.75). Whereas rs2016520 was significantly associated with the decreased level of LAP. Difference (95%CI) values was -14.67 ( -22.97--6.55). GMDR analysis showed a significant gene-gene interaction among rs135539, rs1800206 of PPARα, rs2016520 of PPARδ and rs10865710, rs3856806, rs709158, rs1805192, rs4684847 of PPARγ for eight-dimension models (P < 0.05), in which prediction accuracy was 0.5902 and cross-validation consistency was 10/10.</p><p><b>CONCLUSION</b>The rs1800206 of PPARα and rs1805192, rs3856806 of PPARγ were significantly associated with the increased level of LAP; rs2016520 of PPARδ was associated with the decreased level of LAP. There was a gene-gene interaction between multiple SNPs.</p>