Background Large-for-gestational-age (LGA) births are associated with adverse perinatal outcomes and increased risks of offspring obesity, metabolic syndrome, and cardiovascular diseases later in life. Beyond traditional risk factors, exposure to environmental factors, especially fine particulate matter (PM_2.5), before and during pregnancy may contribute to excessive fetal growth; however, the roles of specific chemical constituents and critical exposure windows remain unclear. Objective To examine the associations between maternal exposures to PM_2.5 and its chemical constituents before and during pregnancy and the risk of delivering LGA infants. Methods Singleton pregnancies from the National Free Preconception Health Examination Project between 2010 and 2014 were included. Individual exposures to PM_2.5 and its constituents were estimated for preconception and pregnancy windows using geocoded residential addresses. The associations of single and mixed exposures with LGA risk were analyzed using generalized linear models (GLMs) and qg-computation. Results Exposures to PM_2.5 and its major chemical constituents were significantly associated with an increased LGA risk, with differences in effect magnitude across components. Secondary inorganic aerosols showed the strongest associations. For full-pregnancy exposure, nitrate (OR=1.330, 95%CI: 1.313, 1.347), ammonium (OR=1.279, 95%CI: 1.263, 1.295), and sulfate (OR=1.242, 95%CI: 1.227, 1.257) had larger effects on LGA risk than black carbon and organic matter. Analysis by exposure window indicated that the month preceding conception and the third trimester of pregnancy were critical exposure windows for susceptibility, while the strongest effect was observed for full-pregnancy exposure, suggesting a cumulative effect over time. Mixed exposure analysis further showed that nitrate and sulfate consistently accounted for the main positive contributions across different time windows. Conclusion Maternal exposures to PM_2.5 and its chemical components before and during pregnancy are associated with an elevated LGA risk. Nitrate and sulfate show consistent and strong associations across pregnancy stages, underscoring the importance of component composition and exposure timing in fetal overgrowth.

Background Dengue fever is a mosquito-borne disease transmitted by Aedes aegypti and Aedes albopictus. Under the background of climate change, there are great challenges in the prevention and control of dengue fever, posing a serious health risk to the population. Objective To analyze the mechanism of temperature on dengue fever transmission and estimate the risk of dengue fever under different climate change scenarios by establishing a coupled human-mosquito dynamics model using Guangzhou as a research site, and to provide reference for adaptation to climate change. Methods Reported dengue fever cases and meteorological data from January 1, 2015 to December 31, 2019 in Guangzhou were collected from Guangdong Provincial Center for Disease Control and Prevention and China Meteorological Data Service Centre, respectively. The temperature data under three Representative Concentration Pahtyway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2030s (2031–2040), 2060s (2061–2070), and 2090s (2091–2099) were calculated by five general circulation models (GCMs) provided by the fifth phase of the Coupled Model Intercomparison Project. A dengue fever transmission dynamics (ELPSEI-SEIR) model was constructed to analyze the mechanism of temperature affecting dengue fever transmission by fitting the dengue fever epidemic trend from 2015–2019, and then the daily mean temperature under selected RCP scenarios for 2030s, 2060s, and 2090s was incorporated into the established dynamics model to predict the risk of dengue fever under different climate change scenarios in the future. Results From January 1, 2015 to December 31, 2019, a total of 4 234 cases of dengue fever were reported in Guangzhou, including 3741 local cases and 493 imported cases. The regression results showed that the model well fitted the dengue fever cases in Guangzhou from 2015 to 2019, and the coefficient of determination R2 to evaluate goodness of fit and the root mean squared error were 0.82 and 1.96, respectively. A U-shaped or inverted U-shaped relationship between temperature and mosquito habits could directly affect the number of mosquitoes and the transmission of dengue fever. We also found that temperature increase in most future scenarios could promote the transmission of dengue fever, and the epidemic period was significantly wider than the baseline stage. The epidemic of dengue fever would peak in the 2060s under the scenarios of RCP2.6 and RCP4.5. The estimated incidence of dengue fever was predicated to be highest in the 2030s and then decrease in the following years under RCP8.5, and in the 2090s, the incidence would decrease significantly, but the incidence peak would be earlier in each year, mainly from May to July. Conclusion Temperature can directly affect mosquito population and dengue fever transmission by affecting mosquito habits. The cases of dengue fever will increase under most climate scenarios in the future. However, the epidemic risk of dengue fever may be suppressed, and the epidemic season may be advanced under RCP8.5.