Associations between metabolic syndrome and anthropogenic heat emissions in northeastern China

The association between anthropogenic heat and parent-report symptoms of childhood attention deficit hyperactivity disorder in China: A novel perspective reflecting climate change

Anthropogenic climate change will have a negative impact on worldwide well-being over and above the direct consequences of rising average temperatures. But anthropogenic heat (AH) relationship with childhood attention deficit hyperactivity disorder (ADHD) is unknown. To assess the relationship with AH exposure and childhood ADHD symptoms in the context of global climate change, this study was conducted in a cross-sectional survey from April 2012 to May 2018 in the northeastern, northwestern, and southern regions of China, with a total enrollment of 179,846 children aged 6-18 years. Exposure to AH was evaluated by gathering socioeconomic and energy usage data along with nighttime light data from satellites and data on the Normalized Difference Vegetation Index. This encompassed four types of AH exposure: industrial processes, transportation, buildings, and human metabolism. The statistical analysis used generalized linear mixed-effects modeling to determine the association between the types of AH exposure and childhood ADHD symptoms. The mean (SD) age of the 179,846 study participants was 11.7 (2.9) years, and 7343 participants (4.1%) had ADHD symptoms. In adjusted models, increased levels of AH exposure per IQR from total AH, industry, transportation, buildings, and human metabolism all increased the odds of ADHD (odds ratios, 3.60 [95% CI, 3.42, 3.80]; 5.71 [95% CI, 5.32, 6.14]; 1.79 [95% CI, 1.75, 1.84]; 2.10 [95% CI, 2.03, 2.17]; 1.95 [95% CI, 1.89, 2.02]). The association remained robust after various sensitivity analyses. Prolonged exposure to AH is associated with the development of ADHD symptoms in children.

Associations between anthropogenic heat emissions and serum lipids among adults in northeastern China

Few epidemiological studies have investigated associations between anthropogenic heat emissions (AE) and serum lipids. We recruited 15,477 adults from 33 communities in northeastern China in 2009. We estimated AE flux by using data on energy consumption and socio-economic statistics covering building, transportation, industry, and human metabolism. We assessed the associations between AE and blood lipids and dyslipidemia prevalence using the restricted cubic spline models. The regression coefficients (β) and the 95% CI of total cholesterol for the 75th and 95th percentiles of the exposure were 0.23 mmol/L (95% CI: 0.15, 0.30) and 0.25 mmol/L (95% CI: 0.18, 0.32). We also found AE was positively associated with dyslipidemia. Participants who were female or who had low incomes exhibited more pronounced associations. Our research showed that exposure to AE was significantly associated with serum lipids. These novel, valuable findings are useful to inform policymakers to estimate the risks to human health from anthropogenic heat.

Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China

As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.

Application of wearable devices for monitoring cardiometabolic dysfunction under the exposome paradigm

Environmental factors, including chemical/physical pollutants, as well as lifestyle and psychological factors, contribute greatly to the pathways leading to cardiometabolic diseases with a heavy disease burden and economic loss. The concept of exposomes provides a novel paradigm for combining all exposure characteristics to evaluate disease risk. A solution-like exposome requires technological support to provide continuous data to monitor vital signs and detect abnormal fluctuations. Wearable devices allow people to conveniently monitor signals during their daily routines. These new technologies empower users to more actively prevent and manage cardiometabolic disease by reviewing risk factors of the disease, especially lifestyle factors, such as sleeping time, screen time, and mental health condition. Devices with multiple sensors can monitor electrocardiography data, oxygen saturation, intraocular pressure, respiratory rate, and heart rate to enhance the exposome study and provide precise suggestions for disease prevention and management.