Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study

Climate Change and Cardiovascular Health: A Systematic Review

Importance

Climate change may increase the risk of adverse cardiovascular outcomes by causing direct physiologic changes, psychological distress, and disruption of health-related infrastructure. Yet, the association between numerous climate change-related environmental stressors and the incidence of adverse cardiovascular events has not been systematically reviewed.

Objective

To review the current evidence on the association between climate change-related environmental stressors and adverse cardiovascular outcomes.

Evidence Review

PubMed, Embase, Web of Science, and Cochrane Library were searched to identify peer-reviewed publications from January 1, 1970, through November 15, 2023, that evaluated associations between environmental exposures and cardiovascular mortality, acute cardiovascular events, and related health care utilization. Studies that examined only nonwildfire-sourced particulate air pollution were excluded. Two investigators independently screened 20 798 articles and selected 2564 for full-text review. Study quality was assessed using the Navigation Guide framework. Findings were qualitatively synthesized as substantial differences in study design precluded quantitative meta-analysis.

Findings

Of 492 observational studies that met inclusion criteria, 182 examined extreme temperature, 210 ground-level ozone, 45 wildfire smoke, and 63 extreme weather events, such as hurricanes, dust storms, and droughts. These studies presented findings from 30 high-income countries, 17 middle-income countries, and 1 low-income country. The strength of evidence was rated as sufficient for extreme temperature; ground-level ozone; tropical storms, hurricanes, and cyclones; and dust storms. Evidence was limited for wildfire smoke and inadequate for drought and mudslides. Exposure to extreme temperature was associated with increased cardiovascular mortality and morbidity, but the magnitude varied with temperature and duration of exposure. Ground-level ozone amplified the risk associated with higher temperatures and vice versa. Extreme weather events, such as hurricanes, were associated with increased cardiovascular risk that persisted for many months after the initial event. Some studies noted a small increase in cardiovascular mortality, out-of-hospital cardiac arrests, and hospitalizations for ischemic heart disease after exposure to wildfire smoke, while others found no association. Older adults, racial and ethnic minoritized populations, and lower-wealth communities were disproportionately affected.

Conclusions and Relevance

Several environmental stressors that are predicted to increase in frequency and intensity with climate change are associated with increased cardiovascular risk, but data on outcomes in low-income countries are lacking. Urgent action is needed to mitigate climate change-associated cardiovascular risk, particularly in vulnerable populations.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Association between ambient temperature and childhood respiratory hospital visits in Beijing, China: a time-series study (2013-2017)

Little is known on the potential impact of temperature on respiratory morbidity, especially for children whose respiratory system can be more vulnerable to climate changes. In this time-series study, Poisson generalized additive models combined with distributed lag nonlinear models were used to assess the associations between ambient temperature and childhood respiratory morbidity. The impacts of extreme cold and hot temperatures were calculated as cumulative relative risks (cum.RRs) at the 1st and 99th temperature percentiles relative to the minimum morbidity temperature percentile. Attributable fractions of respiratory morbidity due to cold or heat were calculated for temperatures below or above the minimum morbidity temperature. Effect modifications by air pollution, age, and sex were assessed in stratified analyses. A total of 877,793 respiratory hospital visits of children under 14 years old between 2013 and 2017 were collected from Beijing Children's Hospital. Overall, we observed J-shaped associations with greater respiratory morbidity risks for exposure to lower temperatures, and higher fraction of all-cause respiratory hospital visits was caused by cold (33.1%) than by heat (0.9%). Relative to the minimum morbidity temperature (25 °C, except for rhinitis, which is 31 °C), the cum.RRs for extreme cold temperature (-6 °C) were 2.64 (95%CI: 1.51-4.61) for all-cause respiratory hospital visits, 2.73 (95%CI: 1.44-5.18) for upper respiratory infection, 2.76 (95%CI: 1.56-4.89) for bronchitis, 2.12 (95%CI: 1.30-3.47) for pneumonia, 2.06 (95%CI: 1.27-3.34) for rhinitis, and 4.02 (95%CI: 2.14-7.55) for asthma, whereas the associations between extreme hot temperature (29 °C) and respiratory hospital visits were not significant. The impacts of extreme cold temperature on asthma hospital visits were greater at higher levels of ozone (O₃) exposure (> 50th percentile). Our findings suggest significantly increased childhood respiratory morbidity risks at extreme cold temperature, and the impact of extreme cold temperature on asthma hospital visits can be enhanced under higher level exposure to O₃.

Association of change in air quality with hospital admission for acute exacerbation of chronic obstructive pulmonary disease in Guangdong, China: A province-wide ecological study

AIMS

To assess possible effect of air quality improvements, we investigated the temporal change in hospital admissions for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) associated with pollutant concentrations.

METHODS

We collected daily concentrations of particulate matter (i.e., PM_2.5, PM₁₀ and PM_coarse), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and admissions for AECOPD for 21 cities in Guangdong from 2013 to 2017. We examined the association of air pollution with AECOPD admissions using two-stage time-series analysis, and estimated the annual attributable fractions, numbers, and direct hospitalization costs of AECOPD admissions with principal component analysis.

RESULTS

From 2013-2017, mean daily concentrations of SO₂, PM₁₀ and PM_2.5 declined by nearly 40%, 30%, and 26% respectively. As the average daily 8 h O₃ concentration increased considerably, the number of days exceeding WHO target (i.e.,100 μg/m³) increased from 103 in 2015-152 in 2017. For each interquartile range increase in pollutant concentration, the relative risks of AECOPD admission at lag 0-3 were 1.093 (95% CI 1.06-1.13) for PM_2.5, 1.092 (95% CI 1.08-1.11) for O₃, and 1.092 (95% CI 1.05-1.14) for SO₂. Attributable fractions of AECOPD admission advanced by air pollution declined from 9.5% in 2013 to 4.9% in 2016, then increased to 6.0% in 2017. A similar declining trend was observed for direct AECOPD hospitalization costs.

CONCLUSION

Declined attributable hospital admissions for AECOPD may be associated with the reduction in concentrations of PM_2.5, PM₁₀ and SO₂ in Guangdong, while O₃ has emerged as an important risk factor. Summarizes the main finding of the work： Reduction in PM may result in declined attributable hospitalizations for AECOPD, while O₃ has emerged as an important risk factor following an intervention.

The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China

The ambient temperature–health relationship is of growing interest as the climate changes. Previous studies have examined the association between ambient temperature and mortality or morbidity, however, there is little literature available on the ambient temperature effects on year of life lost (YLL). Thus, we aimed to quantify the YLL attributable to non-optimum ambient temperature. We obtained data from 1 January 2013 to 31 December 2017 of 70 counties in Hunan, China. In order to combine the effects of each county, we used YLL rate as a health outcome indicator. The YLL rate was equal to the total YLL divided by the population of each county, and multiplied by 100,000. We estimated the associations between ambient temperature and YLL with a distributed lag non-linear model (DNLM) in a single county, and then pooled them in a multivariate meta-regression. The daily mean YLL rates were 22.62 y/(p·100,000), 10.14 y/(p·100,000) and 2.33 y/(p·100,000) within the study period for non-accidental, cardiovascular, and respiratory disease death. Ambient temperature was responsible for advancing a substantial fraction of YLL, with attributable fractions of 10.73% (4.36–17.09%) and 16.44% (9.09–23.79%) for non-accidental and cardiovascular disease death, respectively. However, the ambient temperature effect was not significantly for respiratory disease death, corresponding to 5.47% (−2.65–13.60%). Most of the YLL burden was caused by a cold temperature than the optimum temperature, with an overall estimate of 10.27% (4.52–16.03%) and 15.94% (8.82–23.05%) for non-accidental and cardiovascular disease death, respectively. Cold and heat temperature-related YLLs were higher in the elderly and females than the young and males. Extreme cold temperature had an effect on all age groups in different kinds of disease-caused death. This study highlights that general preventative measures could be important for moderate temperatures, whereas quick and effective measures should be provided for extreme temperatures.