The association between temperature and cause-specific mortality in the Klang Valley, Malaysia

Association between ambient temperature and cause-specific mortality: An individual-level case-crossover study in Suzhou, China

The changing climate poses a growing challenge to the population health. The objective of this study was to assess the association between ambient temperature and cause-specific mortality in Suzhou. Based on the non-accidental mortality data collected during 2008-2022 in Suzhou, China, this study utilized an individual-level case-crossover design to evaluate the associations of temperature with cause-specific mortality. We applied a distributed lag nonlinear model with a maximum lag of 14 days to account for lag effects. Mortality risk due to extreme cold (<2.5th percentile) and extreme heat (>97.5th percentile) was analyzed. A total of 634,530 non-accidental deaths were analyzed in this study. An inverse J-shaped exposure-response relationship was observed between ambient temperature and non-accidental mortality, with the minimum mortality temperature (MMT) at 29.1℃. The relative risk (RR) of mortality associated with extreme cold (2.5th percentile) was 1.37 [95 % confidence interval (CI): 1.30, 1.44], higher than estimate of 1.09 (95 %CI: 1.07, 1.11) for extreme heat (97.5th percentile) relative to the MMT. Heat effect lasted for 2-3 days, while cold effect could persist for almost 14 days. Higher mortality risk estimates were observed for cardiorespiratory deaths compared to total deaths, with statistically significant between-group differences. Consequently, this study provides first-hand evidence on the associations between ambient temperatures and mortality risks from various causes, which could help local government and policy-makers in designing targeted strategies and public health measures against the menace of climate change.

Lag effect of ambient temperature on respiratory emergency department visits in Beijing: a time series and pooled analysis

BACKGROUND

Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China.

METHODS

Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China.

RESULTS

The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0-21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender.

CONCLUSIONS

Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Heat and Cardiovascular Mortality: An Epidemiological Perspective

As global temperatures rise, extreme heat events are projected to become more frequent and intense. Extreme heat causes a wide range of health effects, including an overall increase in morbidity and mortality. It is important to note that while there is sufficient epidemiological evidence for heat-related increases in all-cause mortality, evidence on the association between heat and cause-specific deaths such as cardiovascular disease (CVD) mortality (and its more specific causes) is limited, with inconsistent findings. Existing systematic reviews and meta-analyses of epidemiological studies on heat and CVD mortality have summarized the available evidence. However, the target audience of such reviews is mainly limited to the specific field of environmental epidemiology. This overarching perspective aims to provide health professionals with a comprehensive overview of recent epidemiological evidence of how extreme heat is associated with CVD mortality. The rationale behind this broad perspective is that a better understanding of the effect of extreme heat on CVD mortality will help CVD health professionals optimize their plans to adapt to the changes brought about by climate change and heat events. To policymakers, this perspective would help formulate targeted mitigation, strengthen early warning systems, and develop better adaptation strategies. Despite the heterogeneity in evidence worldwide, due in part to different climatic conditions and population dynamics, there is a clear link between heat and CVD mortality. The risk has often been found to be higher in vulnerable subgroups, including older people, people with preexisting conditions, and the socioeconomically deprived. This perspective also highlights the lack of evidence from low- and middle-income countries and focuses on cause-specific CVD deaths. In addition, the perspective highlights the temporal changes in heat-related CVD deaths as well as the interactive effect of heat with other environmental factors and the potential biological pathways. Importantly, these various aspects of epidemiological studies have never been fully investigated and, therefore, the true extent of the impact of heat on CVD deaths remains largely unknown. Furthermore, this perspective also highlights the research gaps in epidemiological studies and the potential solutions to generate more robust evidence on the future consequences of heat on CVD deaths.

Heatwave Definition and Impact on Cardiovascular Health: A Systematic Review

Objectives: We aimed to analyze recent literature on heat effects on cardiovascular morbidity and mortality, focusing on the adopted heat definitions and their eventual impact on the results of the analysis. Methods: The search was performed on PubMed, ScienceDirect, and Scopus databases: 54 articles, published between January 2018 and September 2022, were selected as relevant. Results: In total, 21 different combinations of criteria were found for defining heat, 12 of which were based on air temperature, while the others combined it with other meteorological factors. By a simulation study, we showed how such complex indices could result in different values at reference conditions depending on temperature. Heat thresholds, mostly set using percentile or absolute values of the index, were applied to compare the risk of a cardiovascular health event in heat days with the respective risk in non-heat days. The larger threshold's deviation from the mean annual temperature, as well as higher temperature thresholds within the same study location, led to stronger negative effects. Conclusion: To better analyze trends in the characteristics of heatwaves, and their impact on cardiovascular health, an international harmonization effort to define a common standard is recommendable.

Analysis of heatwave characteristics under climate change over three highly populated cities of South India: a CMIP6-based assessment

Climate change is arguably the most alarming global concern of the twenty-first century, particularly due to the increased frequency of meteorological extremes, e.g., heatwaves, droughts, and floods. Heatwaves are considered a potential health risk and urge further study, robust preparedness, and policy framing. This study presents an analysis of heatwave characteristics for historical (1980-2014), near-future (2021-2055), and far-future (2056-2090) scenarios over three highly populated cities of South India, i.e., Bangalore, Chennai, and Hyderabad. Two different approaches, i.e., the India Meteorological Department (IMD) criterion and the percentile-based criterion, are considered for defining the threshold of a heatwave day. Nine general circulation models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) experiment are selected, evaluated after bias correction, and the best performer was utilized to obtain the temperature projections corresponding to two shared socioeconomic pathways (SSP 2-4.5 and 5-8.5) for the future periods. The results reveal a high frequency of heatwave days over the cities in recent years from both approaches, which may further exacerbate in the future, thereby putting a large population at risk. The number of heatwave days is much higher for SSP5-8.5 than that for SSP2-4.5, depicting the direct effects of anthropogenic activities on the frequency of heatwaves. The detailed analysis of heatwave projections will help develop equitable heat resilient mitigation and adaptation strategies for the future, thereby alleviating their pernicious impacts.

The Scorching Truth: Investigating the Impact of Heatwaves on Selangor's Elderly Hospitalisations

Global climate change has contributed to the intensity, frequency, and duration of heatwave events. The association between heatwaves and elderly mortality is highly researched in developed countries. In contrast, heatwave impact on hospital admissions has been insufficiently studied worldwide due to data availability and sensitivity. In our opinion, the relationship between heatwaves and hospital admissions is worthwhile to explore as it could have a profound impact on healthcare systems. Therefore, we aimed to investigate the associations between heatwaves and hospitalisations for the elderly by age group in Selangor, Malaysia, from 2010 to 2020. We further explored the impact of heatwaves on the risks of cause-specific hospital admissions across age groups within the elderly. This study applied generalized additive models (GAMs) with the Poisson family and distributed lag models (DLMs) to estimate the effect of heatwaves on hospitalisations. According to the findings, there was no significant increase in hospitalisations for those aged 60 and older during heatwaves; however, a rise in mean apparent temperature (ATmean) by 1 °C significantly increased the risk of hospital admission by 12.9%. Heatwaves had no immediate effects on hospital admissions among elderly patients, but significant delay effects were identified for ATmean with a lag of 0-3 days. The hospital admission rates of the elderly groups started declining after a 5-day average following the heatwave event. Females were found to be relatively more vulnerable than males during heatwave periods. Consequently, these results can provide a reference to improve public health strategies to target elderly people who are at the greatest risk of hospitalisations due to heatwaves. Development of early heatwave and health warning systems for the elderly would assist with preventing and reducing health risks while also minimising the burden on the whole hospital system in Selangor, Malaysia.

Cold spells linked with respiratory disease hospitalization, length of hospital stay, and hospital expenses: Exploring cumulative and harvesting effects

BACKGROUND

Previous studies have revealed the relationship between cold spells and morbidity and mortality due to respiratory diseases, while the detrimental effects of cold spells on the length of hospital stay and hospitalization expenses remain largely unknown.

METHODS

We collected hospitalization data for respiratory diseases in 11 cities of Shanxi, China during 2017-2019. In each case, exposure to meteorological variables and air pollution was estimated by the bilinear interpolation approach and inverse distance weighting method, respectively, and then averaged at the city level. Cold spells were defined as the daily mean temperature below the 10^th, 7.5^th, or 5^th percentiles for at least 2 to 5 consecutive days. We applied distributed lag non-linear models combined with generalized additive models to assess cumulative effects and harvesting effects.

RESULTS

There were significant associations between cold spells and hospital admissions, length of hospital stay, and hospital expenses for respiratory diseases. Compared with the non-cold spell period, the overall (lag 0-21) cumulative risk of hospitalization for total respiratory diseases was 1.232 (95 % CI: 1.090, 1.394) on cold spell days, and the increased length of hospital stay and hospitalization expenses were 112.793 (95 % CI: 10.755, 214.830) days and 127.568 (95 % CI: 40.513, 214.624) thousand Chinese yuan. The overall cumulative risks of cold spells on total respiratory diseases and pneumonia were statistically significant. We further observed harvesting effects in the associations between cold spells and hospital admission, length of hospital stay, and hospitalization expenses for respiratory diseases.

CONCLUSIONS

Cumulative cold-spell exposure for up to three weeks is associated with hospitalization, length of hospital stay, and hospital expenses for respiratory diseases. The observed harmful effects of cold spells on respiratory diseases can be partly attributable to harvesting effects.

Daily temperature effects on under-five mortality in a tropical climate country and the role of local characteristics

BACKGROUND

Climate change and its subsequent effects on temperature have raised global public health concerns. Although numerous epidemiological studies have shown the adverse health effects of temperature, the association remains unclear for children aged below five years old and those in tropical climate regions.

METHODS

We conducted a two-stage time-stratified case-crossover study to examine the association between temperature and under-five mortality, spanning the period from 2014 to 2018 across all six regions in Malaysia. In the first stage, we estimated region-specific temperature-mortality associations using a conditional Poisson regression and distributed lag nonlinear models. We used a multivariate meta-regression model to pool the region-specific estimates and examine the potential role of local characteristics in the association, which includes geographical information, demographics, socioeconomic status, long-term temperature metrics, and healthcare access by region.

RESULTS

Temperature in Malaysia ranged from 22 °C to 31 °C, with a mean of 27.6 °C. No clear seasonality was observed in under-five mortality. We found no strong evidence of the association between temperature and under-five mortality, with an "M-" shaped exposure-response curve. The minimum mortality temperature (MMT) was identified at 27.1 °C. Among several local characteristics, only education level and hospital bed rates reduced the residual heterogeneity in the association. However, effect modification by these variables were not significant.

CONCLUSION

This study suggests a null association between temperature and under-five mortality in Malaysia, which has a tropical climate. The "M-" shaped pattern suggests that under-fives may be vulnerable to temperature changes, even with a small temperature change in reference to the MMT. However, the weak risks with a large uncertainty at extreme temperatures remained inconclusive. Potential roles of education level and hospital bed rate were statistically inconclusive.

Effects of ambient temperature on influenza-like illness: A multicity analysis in Shandong Province, China, 2014-2017

Background

The associations between ambient temperature and influenza-like illness (ILI) have been investigated in previous studies. However, they have inconsistent results. The purpose of this study was to estimate the effect of ambient temperature on ILI in Shandong Province, China.

Methods

Weekly ILI surveillance and meteorological data over 2014-2017 of the Shandong Province were collected from the Shandong Center for Disease Control and Prevention and the China Meteorological Data Service Center, respectively. A distributed lag non-linear model was adopted to estimate the city-specific temperature-ILI relationships, which were used to pool the regional-level and provincial-level estimates through a multivariate meta-analysis.

Results

There were 911,743 ILI cases reported in the study area between 2014 and 2017. The risk of ILI increased with decreasing weekly ambient temperature at the provincial level, and the effect was statistically significant when the temperature was <-1.5°C (RR = 1.24, 95% CI: 1.00-1.54). We found that the relationship between temperature and ILI showed an L-shaped curve at the regional level, except for Southern Shandong (S-shaped). The risk of ILI was influenced by cold, with significant lags from 2.5 to 3 weeks, and no significant effect of heat on ILI was found.

Conclusion

Our findings confirm that low temperatures significantly increased the risk of ILI in the study area. In addition, the cold effect of ambient temperature may cause more risk of ILI than the hot effect. The findings have significant implications for developing strategies to control ILI and respond to climate change.

Environmental variable importance for under-five mortality in Malaysia: A random forest approach

BACKGROUND

Environmental factors have been associated with adverse health effects in epidemiological studies. The main exposure variable is usually determined via prior knowledge or statistical methods. It may be challenging when evidence is scarce to support prior knowledge, or to address collinearity issues using statistical methods. This study aimed to investigate the importance level of environmental variables for the under-five mortality in Malaysia via random forest approach.

METHOD

We applied a conditional permutation importance via a random forest (CPI-RF) approach to evaluate the relative importance of the weather- and air pollution-related environmental factors on daily under-five mortality in Malaysia. This study spanned from January 1, 2014 to December 31, 2016. In data preparation, deviation mortality counts were derived through a generalized additive model, adjusting for long-term trend and seasonality. Analyses were conducted considering mortality causes (all-cause, natural-cause, or external-cause) and data structures (continuous, categorical, or all types [i.e., include all variables of continuous type and all variables of categorical type]). The main analysis comprised of two stages. In Stage 1, Boruta selection was applied for preliminary screening to remove highly unimportant variables. In Stage 2, the retained variables from Boruta were used in the CPI-RF analysis. The final importance value was obtained as an average value from a 10-fold cross-validation.

RESULT

Some heat-related variables (maximum temperature, heat wave), temperature variability, and haze-related variables (PM10, PM10-derived haze index, PM10- and fire-derived haze index, fire hotspot) were among the prominent variables associated with under-five mortality in Malaysia. The important variables were consistent for all- and natural-cause mortality and sensitivity analyses. However, different most important variables were observed between natural- and external-cause under-five mortality.

CONCLUSION

Heat-related variables, temperature variability, and haze-related variables were consistently prominent for all- and natural-cause under-five mortalities, but not for external-cause.

Impacts of climate change and environmental degradation on children in Malaysia

The impacts of climate change and degradation are increasingly felt in Malaysia. While everyone is vulnerable to these impacts, the health and wellbeing of children are disproportionately affected. We carried out a study composed of two major components. The first component is an environmental epidemiology study comprised of three sub-studies: (i) a global climate model (GCM) simulating specific health-sector climate indices; (ii) a time-series study to estimate the risk of childhood respiratory disease attributable to ambient air pollution; and (iii) a case-crossover study to identify the association between haze and under-five mortality in Malaysia. The GCM found that Malaysia has been experiencing increasing rainfall intensity over the years, leading to increased incidences of other weather-related events. The time-series study revealed that air quality has worsened, while air pollution and haze have been linked to an increased risk of hospitalization for respiratory diseases among children. Although no clear association between haze and under-five mortality was found in the case-crossover study, the lag patterns suggested that health effects could be more acute if haze occurred over a longer duration and at a higher intensity. The second component consists of three community surveys on marginalized children conducted (i) among the island community of Pulau Gaya, Sabah; (ii) among the indigenous Temiar tribe in Pos Kuala Mu, Perak; and (iii) among an urban poor community (B40) in PPR Sg. Bonus, Kuala Lumpur. The community surveys are cross-sectional studies employing a socio-ecological approach using a standardized questionnaire. The community surveys revealed how children adapt to climate change and environmental degradation. An integrated model was established that consolidates our overall research processes and demonstrates the crucial interconnections between environmental challenges exacerbated by climate change. It is recommended that Malaysian schools adopt a climate-smart approach to education to instill awareness of the impending climate change and its cascading impact on children's health from early school age.

Exploring a more reasonable temperature exposure calculation method based on individual exposure survey and city-scale heat exposure impact assessment

The inability to quantify the difference between ambient temperature (AT) and personal exposure temperature (PET) is a common limitation in environmental health research. The actual exposure variability is underestimated when we used measurements from fixed monitoring stations to estimate PET. The study aims to explore a more reasonable temperature exposure calculation method to relate PET to AT and links heat exposure to adverse health events. We measured hourly PET of 129 participants from July 8th to July 13th, 2021 in Xinyi City, China. The linear mixed-effects model was used to build the relationship between hourly PET and AT in rural and town. Several calculation methods that can capture the intensity, frequency and duration of daily exposure were used to calculate the daily PET and AT and establish the relationship between the two factors. A generalized linear model was used to establish the relationship between city-scale AT indicators and health endpoints from January 1st, 2013 to December 31st, 2015 in Shanghai, China. The result showed that the hourly PET was significantly related to AT, wind speed, air pressure, precipitation, outside time, and air-conditioning use. Among several daily temperature indicators, we found that AT_DHAT (Degree Hours Above Threshold (27.4 °C)) was tight with the PET_DHAT in different regions (R² > 0.99). DHAT strengthened the relationship between daily AT and health endpoint in the urban-scale heat-related health impact study, especially in respiratory diseases. The method proposed in this study can improve the accuracy of future epidemiological studies on the effects of heat exposure.