Screen time is negatively associated with markers of health in western youth, but very little is known about these relationships in Chinese youth. Middle-school and high-school students (n = 2625) in Wuhan, China, completed questionnaires assessing demographics, health behaviors, and self-perceptions in spring/summer 2016. Linear and logistic regression analyses were conducted to determine whether, after adjustment for covariates, screen time was associated with body mass index (BMI), eating behaviors, average nightly hours of sleep, physical activity (PA), academic performance, and psychological states. Watching television on school days was negatively associated with academic performance, PA, anxiety, and life satisfaction. Television viewing on non-school days was positively associated with sleep duration. Playing electronic games was positively associated with snacking at night and less frequently eating breakfast, and negatively associated with sleep duration and self-esteem. Receiving electronic news and study materials on non-school days was negatively associated with PA, but on school days, was positively associated with anxiety. Using social networking sites was negatively associated with academic performance, but positively associated with BMI z-score, PA and anxiety. Screen time in adolescents is associated with unhealthy behaviors and undesirable psychological states that can contribute to poor quality of life.

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Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality.

Background:Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban–rural differences in the temperature impacts on health outcomes.Objectives:We investigated whether temperature–mortality relationships vary between urban and rural counties in China.Methods:We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban–rural differences were explored using meta-regression with county-level characteristics.Results:Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban–rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban–rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types.Conclusions:Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure–response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban–rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban–rural disparity in mortality risks. https://doi.org/10.1289/EHP3556

BackgroundThe effects of airborne particulate matter (PM) are a major human health concern. In this panel study, we evaluated the acute effects of exposure to PM on peak expiratory flow (PEF) and wheezing in children.MethodsDaily PEF and wheezing were examined in 19 asthmatic children who were hospitalized in a suburban city in Japan for approximately 5 months. The concentrations of PM less than 2.5 µm in diameter (PM2.5) were monitored at a monitoring station proximal to the hospital. Moreover, PM2.5 concentrations inside and outside the hospital were measured using the dust monitor with a laser diode (PM2.5(LD)). The changes in PEF and wheezing associated with PM concentration were analyzed.ResultsThe changes in PEF in the morning and evening were significantly associated with increases in the average concentration of indoor PM2.5(LD) 24 h prior to measurement (-2.86 L/min [95%CI: -4.12, -1.61] and -3.59 L/min [95%CI: -4.99, -2.20] respectively, for 10-µg/m3 increases). The change in PEF was also significantly associated with outdoor PM2.5(LD) concentrations, but the changes were smaller than those observed for indoor PM2.5(LD). Changes in PEF and concentration of stationary-site PM2.5 were not associated. The prevalence of wheezing in the morning and evening were also significantly associated with indoor PM2.5(LD) concentrations (odds ratios = 1.014 [95%CI: 1.006, 1.023] and 1.025 [95%CI: 1.013, 1.038] respectively, for 10-µg/m3 increases). Wheezing in the evening was significantly associated with outdoor PM2.5(LD) concentration. The effects of indoor and outdoor PM2.5(LD) remained significant even after adjusting for ambient nitrogen dioxide concentrations.ConclusionIndoor and outdoor PM2.5(LD) concentrations were associated with PEF and wheezing among asthmatic children. Indoor PM2.5(LD) had a more marked effect than outdoor PM2.5(LD) or stationary-site PM2.5.

Ambient fine particulate matter (PM) has been associated with impaired lung function, but the effect of temperature on lung function and the potential interaction effect between PM and temperature remain uncertain. To estimate the short-term effects of PM2.5 combined with temperature on lung function, we measured the daily peak expiratory flow (PEF) in a panel of 37 healthy college students in four different seasons. Meanwhile, we also monitored daily concentrations of indoor and outdoor PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm), ambient temperature and relative humidity of the study area, where the study participants lived and attended school. Associations of air pollutants and temperature with lung function were assessed by generalized estimating equations (GEEs). A 10 μg/m3 increase of indoor PM2.5 was associated with a change of −2.09 L/min in evening PEF (95%CI: −3.73 L/min–−0.51 L/min) after adjusting for season, height, gender, temperature and relative humidity. The changes of −2.17 L/min (95%CI: −3.81 L/min– −0.52 L/min) and −2.18 L/min (95%CI: −3.96 L/min–−0.41 L/min) in evening PEF were also observed after adjusting for outdoor SO2 and NO2 measured by Environmental Monitoring Center 3 kilometers away, respectively. An increase in ambient temperature was found to be associated with a decrease in lung function and our results revealed a small but significant antagonistic interactive effect between PM2.5 and temperature. Our findings suggest that ambient PM2.5 has an acute adverse effect on lung function in young healthy adults, and that temperature also plays an important role.

The application of disaggregate models for predictions and policy evaluations requires as inputs detailed information on the socioeconomic characteristics of the population. The early procedure developed for population synthesis involved the generation of a joint multiway distribution of all attributes of interest using iterative proportional fitting (IPF). Recognizing its limitations, including the inability to deal with multilevel controls, several alternate methods have been proposed in the last few years. This article presents a methodology called the fitness‐based synthesis (FBS) that directly generates a list of households to match several multilevel controls without the need for determining a joint multiway distribution. The application and validation results demonstrate both the feasibility of the approach and its improved performance relative to the IPF and methods using fewer control tables. This article also presents a comprehensive validation of the synthetic populations against the true populations and thereby demonstrates the ability of the FBS method to generate the multidimensional correlations among the attributes. The number of iterations to terminations is found to be between one and three times the number of households to be synthesized. In sum, the FBS is an efficient and scalable methodology that is easy to implement and as such is a valuable tool for generating the detailed socioeconomic characteristics need for applying disaggregate travel‐demand forecasting models.

BackgroundThere was no consistent definition for heat wave worldwide, while a limited number of studies have compared the mortality effect of heat wave as defined differently. This paper aimed to provide epidemiological evidence for policy makers to determine the most appropriate definition for local heat wave warning systems.MethodsWe developed 45 heat wave definitions (HWs) combining temperature indicators and temperature thresholds with durations. We then assessed the impact of heat waves under various definitions on non-accidental mortality in hot season (May–September) in Wuhan, China during 2003–2010.ResultsHeat waves defined by HW14 (daily mean temperature ≥ 99.0th percentile and duration ≥ 3 days) had the best predictive ability in assessing the mortality effects of heat wave with the relative risk of 1.63 (95% CI: 1.43, 1.89) for total mortality. The group-specific mortality risk using official heat wave definition of Chinese Meteorological Administration was much smaller than that using HW14. We also found that women, and the elderly (age ≥ 65) were more susceptible to heat wave effects which were stronger and longer lasting.ConclusionThese findings suggest that region specific heat wave definitions are crucial and necessary for developing efficient local heat warning systems and for providing evidence for policy makers to protect the vulnerable population.Electronic supplementary materialThe online version of this article (doi:10.1186/s41256-017-0030-2) contains supplementary material, which is available to authorized users.