Temperature as a modifier of the effects of air pollution on cardiovascular disease hospital admissions in Cape Town, South Africa

Source apportionment of fine atmospheric particles in Bloemfontein, South Africa, using positive matrix factorization

Air pollution is of major health and environmental concern globally and in South Africa. Studies on the sources of PM2.5 air pollution in low- and middle-income countries such as South Africa are limited. This study aimed to identify local and distant sources of PM2.5 pollution in Bloemfontein. PM2.5 samples were collected from June 16, 2020 to August 18, 2021. Trace element concentrations were determined by EDXRF spectroscopy. By use of the US EPA PMF 5.0 program, local sources were determined to be combustion/wood burning (49%), industry (22%), soil dust (10%), base metal/pyrometallurgical and traffic (9.6%) and water treatment/industry (9.4%). The HYSPLIT program was applied to determine distant PM2.5 source areas and the following clusters were identified: Mpumalanga province (52%), Northern Cape province (35%), Indian Ocean (8%) and Atlantic Ocean (6%). The majority of the air was found to come from the Mpumalanga province in the north-east, while the majority of local sources are ascribed to combustion/wood burning. Results from this study can be used to develop an Air Quality Management Plan for Bloemfontein.

Understanding the connections between climate change, air pollution, and human health in Africa: Insights from a literature review

Climate change and air pollution are two interconnected global challenges that have profound impacts on human health. In Africa, a continent known for its rich biodiversity and diverse ecosystems, the adverse effects of climate change and air pollution are particularly concerning. This review study examines the implications of air pollution and climate change for human health and well-being in Africa. It explores the intersection of these two factors and their impact on various health outcomes, including cardiovascular disease, respiratory disorders, mental health, and vulnerable populations such as children and the elderly. The study highlights the disproportionate effects of air pollution on vulnerable groups and emphasizes the need for targeted interventions and policies to protect their health. Furthermore, it discusses the role of climate change in exacerbating air pollution and the potential long-term consequences for public health in Africa. The review also addresses the importance of considering temperature and precipitation changes as modifiers of the health effects of air pollution. By synthesizing existing research, this study aims to shed light on complex relationships and highlight the key findings, knowledge gaps, and potential solutions for mitigating the impacts of climate change and air pollution on human health in the region. The insights gained from this review can inform evidence-based policies and interventions to mitigate the adverse effects on human health and promote sustainable development in Africa.

Temperature modifies the association between air pollution and respiratory disease mortality in Cape Town, South Africa

The aim of this 10-year study was to investigate whether and how temperature modifies the association between daily ambient PM10, NO2, SO2 air pollution and daily respiratory disease mortality in Cape Town. A time-stratified case-crossover epidemiological design was applied. Susceptibility by sex and age groups (15-64 years and ≥65 years) was also investigated. On days with medium Tapp levels, NO2 displayed a stronger association with respiratory mortality than PM10 or SO2. Females appeared to be more susceptible to NO2 at medium Tapp levels to males. The 15-64-year-old age group seemed to be more vulnerable to NO2 and PM10 at medium Tapp levels compared to the elderly (≥65 years). At high Tapp levels, females were more susceptible to PM10. The 15-64-year-old group were more vulnerable to NO2 and SO2. The results can be used in present-day early warning systems and in risk assessments to estimate the impact of increased air pollution and temperature.

A New Global Air Quality Health Index Based on the WHO Air Quality Guideline Values With Application in Cape Town

Objectives: This study developed an Air Quality Health Index (AQHI) based on global scientific evidence and applied it to data from Cape Town, South Africa. Methods: Effect estimates from two global systematic reviews and meta-analyses were used to derive the excess risk (ER) for PM2.5, PM10, NO2, SO2 and O3. Single pollutant AQHIs were developed and scaled using the ERs at the WHO 2021 long-term Air Quality Guideline (AQG) values to define the upper level of the "low risk" range. An overall daily AQHI was defined as weighted average of the single AQHIs. Results: Between 2006 and 2015, 87% of the days posed "moderate to high risk" to Cape Town's population, mainly due to PM10 and NO2 levels. The seasonal pattern of air quality shows "high risk" occurring mostly during the colder months of July-September. Conclusion: The AQHI, with its reference to the WHO 2021 long-term AQG provides a global application and can assist countries in communicating risks in relation to their daily air quality.

Towards a climate-resilient primary health care service

Climate change has been declared as the biggest threat to human health in the 21st century. Not all family doctors are aware of the threats and how to tackle them. There are three key aspects to consider: the health and social effects of climate change, the challenge of climate change to primary health care (PHC) facilities and services, and the contribution of health services to the problem of climate change. Climate change and global pollution are ecological drivers associated with significant health and social effects that are often seen in PHC services. These ecological drivers impact health and society via a number of proximate causes, such as air pollution and decreased food production. The health and social effects include malnutrition, infectious diseases, non-communicable diseases, displacement and migration, and mental health problems. Climate change-induced extreme weather events are associated with immediate loss of life and injuries, destruction of homes and livelihoods, and disruption of PHC facilities and services. For adapting to these challenges, the World Health Organization has developed an operational framework for a climate-resilient health system. The Global Green and Healthy Hospitals agenda provides practical guidance for mitigating the contribution of health services to climate change. This article uses these frameworks to suggest practical steps that family doctors can take in leading climate adaptation and mitigation within PHC.

Effect of particulate matter (PM2.5 and PM10) on health indicators: climate change scenarios in a Brazilian metropolis

Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM₁₀ and PM_2.5 considering the new limits recommended by the WHO: 15 µg/m³ (PM₁₀) and 5 µg/m³ (PM_2.5) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM_2.5 and PM₁₀ were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM_2.5 and PM₁₀, with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.

Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011-2016

Epidemiological studies have provided compelling evidence of associations between temperature variability (TV) and health outcomes. However, such studies are limited in developing countries. This study aimed to investigate the relationship between TV and hospital admissions for cause-specific diseases in South Africa. Hospital admission data for cardiovascular diseases (CVD) and respiratory diseases (RD) were obtained from seven private hospitals in Cape Town from 1 January 2011 to 31 October 2016. Meteorological data were obtained from the South African Weather Service (SAWS). A quasi-Poisson regression model was used to investigate the association between TV and health outcomes after controlling for potential effect modifiers. A positive and statistically significant association between TV and hospital admissions for both diseases was observed, even after controlling for the non-linear and delayed effects of daily mean temperature and relative humidity. TV showed the greatest effect on the entire study group when using short lags, 0-2 days for CVD and 0-1 days for RD hospitalisations. However, the elderly were more sensitive to RD hospitalisation and the 15-64 year age group was more sensitive to CVD hospitalisations. Men were more susceptible to hospitalisation than females. The results indicate that more attention should be paid to the effects of temperature variability and change on human health. Furthermore, different weather and climate metrics, such as TV, should be considered in understanding the climate component of the epidemiology of these (and other diseases), especially in light of climate change, where a wider range and extreme climate events are expected to occur in future.

The Association between Apparent Temperature and Hospital Admissions for Cardiovascular Disease in Limpopo Province, South Africa

Cardiovascular diseases (CVDs) have a high disease burden both globally and in South Africa. They have also been found to be temperature-sensitive globally. The association between temperature and CVD morbidity has previously been demonstrated, but little is known about it in South Africa. It is important to understand how changes in temperature in South Africa will affect CVD morbidity, especially in rural regions, to inform public health interventions and adaptation strategies. This study aimed to determine the short-term effect of apparent temperature (T_app) on CVD hospital admissions in Mopani District, Limpopo province, South Africa. A total of 3124 CVD hospital admissions records were obtained from two hospitals from 1 June 2009 to 31 December 2016. Daily T_app was calculated using nearby weather station measurements. The association was modelled using a distributed lag non-linear model with a negative binomial regression over a 21-day lag period. The fraction of morbidity attributable to non-optimal T_app, i.e., cold (6-25 °C) and warm (27-32 °C) T_app was reported. We found an increase in the proportion of admissions due to CVDs for warm and cold T_app cumulatively over 21 days. Increasing CVD admissions due to warm T_app appeared immediately and lasted for two to four days, whereas the lag-structure for the cold effect was inconsistent. A proportion of 8.5% (95% Confidence Interval (CI): 3.1%, 13.7%) and 1.1% (95% CI: -1.4%, 3.5%) of the total CVD admissions was attributable to cold and warm temperatures, respectively. Warm and cold T_app may increase CVD admissions, suggesting that the healthcare system and community need to be prepared in the context of global temperature changes.

Effect modification by maximum temperature of the association between PM2.5 and short-term cardiorespiratory mortality and emergency room visits in Lima, Peru, 2010-2016

BACKGROUND

The health effects of fine particulate matter (PM_2.5) may be worse at higher temperatures.

OBJECTIVE

To investigate temperature's effect on PM_2.5-mortality/morbidity associations in Lima, Peru.

METHODS

Time-series regressions relating PM_2.5 and temperature to mortality and emergency room (ER) visits during 2010-2016. Daily PM_2.5 levels (assigned to 40 Lima districts) and daily maximum temperature (Lima-wide) were estimated based on ground monitors, remote sensing, and modeling. We analyzed all-cause, cardiovascular (ICD codes I00-I99), and respiratory (ICD codes J00-J99) mortality, and cardiovascular and respiratory causes for ER visits.

RESULTS

The average PM_2.5 concentration was 20.9 µg/m³ (IQR 17.5-23.5). The mean daily maximum temperature was 23.8 °C (IQR 20.8-26.9). PM_2.5's effect on all-cause, respiratory, and circulatory disease mortality was significantly (p < 0.05) stronger at temperatures above the maximum temperature median. The rate ratios per increase of 10 µg/m³ of PM_2.5 for all cause, respiratory, and circulatory mortality respectively were 1.03 (1.00-1.06), 1.04 (0.98-1.10), and 1.04 (0.98-1.10) at temperatures below the median, vs. 1.08 (1.04-1.12), 1.11 (1.03-1.19), and 1.14 (1.05-1.25) when temperatures were above the median. Results were analogous for ER visits for respiratory but not circulatory disease.

SIGNIFICANCE

Results strengthen the evidence that air pollution may be more dangerous when temperatures are higher.

IMPACT

Our data contribute to a growing body of literature which indicates that the damaging effects of PM_2.5 may be worse at higher temperature, adding new evidence from Lima, Peru.

Short-Term Joint Effects of PM10, NO2 and SO2 on Cardio-Respiratory Disease Hospital Admissions in Cape Town, South Africa

Background/Aim: In sub-Sahara Africa, few studies have investigated the short-term association between hospital admissions and ambient air pollution. Therefore, this study explored the association between multiple air pollutants and hospital admissions in Cape Town, South Africa. Methods: Generalized additive quasi-Poisson models were used within a distributed lag linear modelling framework to estimate the cumulative effects of PM₁₀, NO₂, and SO₂ up to a lag of 21 days. We further conducted multi-pollutant models and stratified our analysis by age group, sex, and season. Results: The overall relative risk (95% confidence interval (CI)) for PM₁₀, NO₂, and SO₂ at lag 0–1 for hospital admissions due to respiratory disease (RD) were 1.9% (0.5–3.2%), 2.3% (0.6–4%), and 1.1% (−0.2–2.4%), respectively. For cardiovascular disease (CVD), these values were 2.1% (0.6–3.5%), 1% (−0.8–2.8%), and −0.3% (−1.6–1.1%), respectively, per inter-quartile range increase of 12 µg/m³ for PM₁₀, 7.3 µg/m³ for NO₂, and 3.6 µg/m³ for SO₂. The overall cumulative risks for RD per IQR increase in PM₁₀ and NO₂ for children were 2% (0.2–3.9%) and 3.1% (0.7–5.6%), respectively. Conclusion: We found robust associations of daily respiratory disease hospital admissions with daily PM₁₀ and NO₂ concentrations. Associations were strongest among children and warm season for RD.

Exploring rural hospital admissions for diarrhoeal disease, malaria, pneumonia, and asthma in relation to temperature, rainfall and air pollution using wavelet transform analysis

BACKGROUND

Climate variables impact human health and in an era of climate change, there is a pressing need to understand these relationships to best inform how such impacts are likely to change.

OBJECTIVES

This study sought to investigate time series of daily admissions from two public hospitals in Limpopo province in South Africa with climate variability and air quality.

METHODS

We used wavelet transform cross-correlation analysis to monitor coincidences in changes of meteorological (temperature and rainfall) and air quality (concentrations of PM_2.5 and NO₂) variables with admissions to hospitals for gastrointestinal illnesses including diarrhoea, pneumonia-related diagnosis, malaria and asthma cases. We were interested to disentangle meteorological or environmental variables that might be associated with underlying temporal variations of disease prevalence measured through visits to hospitals.

RESULTS

We found preconditioning of prevalence of pneumonia by changes in air quality and showed that malaria in South Africa is a multivariate event, initiated by co-occurrence of heat and rainfall. We provided new statistical estimates of time delays between the change of weather or air pollution and increase of hospital admissions for pneumonia and malaria that are addition to already known seasonal variations. We found that increase of prevalence of pneumonia follows changes in air quality after a time period of 10 to 15 days, while the increase of incidence of malaria follows the co-occurrence of high temperature and rainfall after a 30-day interval.

DISCUSSION

Our findings have relevance for early warning system development and climate change adaptation planning to protect human health and well-being.

Source apportionment of fine atmospheric particles using positive matrix factorization in Pretoria, South Africa

In Pretoria South Africa, we looked into the origins of fine particulate matter (PM_2.5), based on 1-year sampling campaign carried out between April 18, 2017, and April 17, 2018. The average PM_2.5 concentration was 21.1 ± 15.0 µg/m³ (range 0.7-66.8 µg/m³), with winter being the highest and summer being the lowest. The XEPOS 5 energy dispersive X-ray fluorescence (EDXRF) spectroscopy was used for elemental analysis, and the US EPA PMF 5.0 program was used for source apportionment. The sources identified include fossil fuel combustion, soil dust, secondary sulphur, vehicle exhaust, road traffic, base metal/pyrometallurgical, and coal burning. Coal burning and secondary sulphur were significantly higher in winter and contributed more than 50% of PM_2.5 sources. The HYSPLIT model was used to calculate the air mass trajectories (version 4.9). During the 1-year research cycle, five transportation clusters were established: North Limpopo (NLP), Eastern Inland (EI), Short-Indian Ocean (SIO), Long-Indian Ocean (LIO), and South Westerly-Atlantic Ocean (SWA). Local and transboundary origin accounted for 85%, while 15% were long-range transport. Due to various anthropogenic activities such as biomass burning and coal mining, NLP clusters were the key source of emissions adding to the city's PM rate. In Pretoria, the main possible source regions of PM_2.5 were discovered to be NLP and EI. Effective control strategies designed at reducing secondary sulphur, coal burning, and fossil fuel combustion emissions at Southern African level and local combustion sources would be an important measure to combat the reduction of ambient PM_2.5 pollution in Pretoria.

Major climate change-induced risks to human health in South Africa

There are many climatic changes facing South Africa which already have, or are projected to have, a detrimental impact on human health. Here the risks to health due to several alterations in the climate of South Africa are considered in turn. These include an increase in ambient temperature, causing, for example, a significant rise in morbidity and mortality; heavy rainfall leading to changes in the prevalence and occurrence of vector-borne diseases; drought-associated malnutrition; and exposure to dust storms and air pollution leading to the potential exacerbation of respiratory diseases. Existing initiatives and strategies to prevent or reduce these adverse health impacts are outlined, together with suggestions of what might be required in the future to safeguard the health of the nation. Potential roles for the health and non-health sectors as well as preparedness and capacity development with respect to climate change and health adaptation are considered.

PM2.5 chemical composition and geographical origin of air masses in Cape Town, South Africa

PM2.5 in the indoor and outdoor environment has been linked in epidemiology studies to the symptoms, hospital admissions and development of numerous health outcomes including death. The study was conducted during April 2017 and April 2018. PM2.5 samples were collected over 24 h and every third day. The mean PM2.5 level was 13.4 μg m-3 (range: 1.17-39.1 μg m-3). PM2.5 levels exceeded the daily World Health Organization air quality guideline (25 μg m-3) on 14 occasions. The mean soot level was 1.38 m-1 × 10-5 (range: 0 to 5.38 m-1 × 10-5). Cl-, NO3 -, SO4 2-, Al, Ca, Fe, Mg, Na and Zn were detected in the PM2.5 samples. The geographical origin of air masses that passed Cape Town was estimated using the Hybrid Single Particle Lagrangian Integrated Trajectory software. Four air masses were identified in the cluster analysis: Atlantic-Ocean-WSW, Atlantic-Ocean-SW, Atlantic-Ocean-SSW and Indian-Ocean. The population of Cape Town may experience various health outcomes from the outdoor exposure to PM2.5 and the chemical composition of PM2.5.