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Background: Beneficial effects of greenness on birth outcomes have been reported, but few studies have investigated the associations in both urban and non-urban settings. We aimed to evaluate and compare linear and nonlinear associations between greenness and birth outcomes in urban and non-urban settings.Methods: From October 2015 to December 2018, participants were recruited into the Maoming Birth Cohort Study. A total of 11 258 live birth records were obtained. Greenness exposure was assessed using the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Linear regression and nonlinear restricted cubic spline models were implemented to investigate the associations between greenness and birthweight, birth length, gestational age, preterm birth, low birthweight, small for gestational age and the potential for effect variation under urban or non-urban settings, after adjusting for covariates.Results: A 0.1-unit increase in NDVI-500m was significantly associated with an increase of 35.4 g in birthweight [95% confidence interval (CI): 13.2, 57.7], 0.15 cm in birth length (95% CI: 0.03, 0.26), 0.88 days in gestational age (95% CI: 0.05, 1.71) and lower odds of low birthweight [odds ratio (OR) = 0.69, 95% CI: 0.56, 0.85] and preterm birth (OR = 0.70, 95% CI: 0.58, 0.85). No association with head circumference was observed. For all outcomes, no significant linear associations were observed among non-urban dwellers. Inversed 'U-shaped' associations between greenness exposure and birth outcomes were observed in the total study population.Conclusions: Greenness exposure was associated with increased gestational age, birthweight and birth length in urban dwellers. Nonlinear associations assessed by restricted cubic splines suggested that health benefits could be larger when increasing greenness levels from low to medium compared with increasing greenness from medium to high levels. Further studies adopting nonlinear methods are warranted to verify our findings. [ABSTRACT FROM AUTHOR]

Recent research attention has been paid to anthropogenic heat emissions (AE), temperature increase generated by human activity such as lighting, transportation, manufacturing, construction, and building climate controls. However, there is no epidemiological data available to investigate the association between anthropogenic heat emissions and metabolic syndrome (MetS), a cluster of conditions that increase risk of stroke, heart disease and diabetes. To explore the relationships between AE and MetS in China. We recruited 15,477 adults from the 33 Communities Chinese Health Study, a cross-sectional study in northeastern China. We retrieved anthropogenic heat flux by collecting socio-economic and energy consumption data as well as satellite-based nighttime light and Normalized Difference Vegetation Index datasets, including emissions from buildings, transportation, human metabolism, and industries. We also measured MetS components consisting of triglycerides, high density lipoprotein cholesterol, fasting glucose, systolic blood pressure, and diastolic blood pressure, and waist circumference. Restricted cubic spline models were applied to assess the associations between AE and MetS. The median flux of total AE was 30.98 W/m2 and industrial AE was the dominant contributor (87.64%). The adjusted odds ratio and 95% confidence interval (CI) of MetS for the 75th and 95th percentiles of the total AE against the threshold were 1.29 (95% CI: 1.21, 1.38) and 1.65 (95% CI: 1.47, 1.85). Greater AE was associated with higher odds of MetS in a dose-response pattern, and the lowest point of U-shape curve indicated the threshold effect. Participants who are young and middle-aged exhibited stronger associations between AE and MetS. Our novel findings reveal that AE are positively associated with MetS and that associations are modified by age. Further investigations into the mechanisms of the effects are needed. [ABSTRACT FROM AUTHOR]