Association between temperature variability, cause-specific mortality, hospital admissions, and synoptic weather types in South Africa

Abstract

Non-communicable diseases (NCDs), such as cardiovascular and respiratory diseases are weather-sensitive diseases that are regarded as a cause of premature death globally. As much as 85% of NCDs occur in low- and middle-income countries, such as South Africa. Approximately 57% of all the deaths that occurred in South Africa in 2017 were attributable to NCDs, specifically, deaths that were caused by diseases of the circulatory system (18.4%) and deaths caused by diseases of the respiratory system (9.5%). However, epidemiological understanding of the health effects of climate indicators and variability in South Africa is scarce and sparse. Evaluating the relationship between key climate indicators or meteorological variables and cause-specific health outcomes can assist in identifying the potential health risks associated with climate change, developing strategies to mitigate the associated risks, and informing policies that will reduce the burden of diseases and environmental sustainability.

Climate change does not only cause an increase in average temperatures, but also the variability of temperatures. To the author's knowledge, there are no studies conducted in Africa that assessed the combined effects of inter- and intraday temperature variability (an important meteorological indicator of climate variability) on morbidity and mortality. Correct exposure-response relationships are required to optimally assess the burden of diseases and health outcomes due to temperature variability (TV). This thesis aims to address the following research questions:

• What is the current state of knowledge or literature on the association between climate variability indicators and cause-specific health outcomes? • Are there any associations between TV and hospital admissions and mortality? • Which subpopulations are most likely to be hospitalised or die from exposure to TV? • Do season and spatial synoptic classification (SSC) weather types (i.e., an entire suite of meteorological indicators) modify the association between TV and health outcomes?

The primary research objectives of this study were answered through a series of papers (manuscripts), of which five manuscripts were identified to address these research questions. The objective of Manuscript 1 was to systematically review the current state of knowledge of time series and case-crossover epidemiological studies on the impact of TV on cardiovascular disease (CVD) and respiratory disease (RD) mortality as well as hospital admissions at various time scales. Manuscript 2 investigated the association between TV, RD, and CVD hospital admissions in Cape Town during 2011–2016. Manuscript 3 investigated whether season and SSC weather types modified the association between TV and CVD and RD hospital admissions in the City of Cape Town from 2011 to 2016. Manuscript 4 examined the association between TV, RD, and CVD mortality in five South African cities, namely Bloemfontein, Cape Town, Durban, Johannesburg, and Gqeberha (formerly known as Port Elizabeth) located in different Kӧppen-Geiger regions in South Africa during the study period 2006–2016. Manuscript 5 investigated the association between TV and cardiorespiratory (total CVD and RD) mortality in the afore-mentioned five cities from 2006–2016 and assessed whether season and SSC weather types modified the association between TV and mortality.

Manuscript 1 was achieved by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically review the current literature on the health effects of temperature variation. A literature search was conducted using PubMed, MEDLINE/ Web of Science, and Scopus. The review focused on time series and case-crossover epidemiological studies that investigated the association between TV and CVD and/or RD morbidity and mortality and reported the empirical results. The review was restricted to English studies published before the 30th of March 2023. Studies that only reported counts of hospital visitations or mortality and those that focused on outpatients or excess risks were excluded from the review.

The exposure variable of interest for this thesis was defined as a composite of intra- and interday variability using the minimum and maximum temperatures. For example, the TV for the three preceding days’ exposure before the outcome was calculated as TV0-2 = standard deviation (minimum and maximum temperature on the same day as exposure, minimum and maximum temperature a day after exposure, minimum and maximum temperature two days after exposure). To achieve the aim of Manuscripts 2, 3, 4, and 5, time series analysis using quasi-Poisson generalised linear models combined with a distributed lag nonlinear modelling framework was used. The models were adjusted for the potential confounding effects of the day of the week as a categorical variable, public holidays as a binary variable, and seasonal and long-term trends as a nonlinear spline. Furthermore, a meta-analysis was used for Manuscript 4 to combine city-specific effect estimates to obtain the national effects of TV on mortality.

In addition to achieving the aims of Manuscripts 3 and 5, the SSC framework was used to classify each day of the study period into one of the seven distinct categories, namely Dry moderate [DM], Dry polar [DP], Dry tropical [DT], Moist moderate [MM], Moist polar [MP], Moist tropical [MT], and Transition [TR]. Furthermore, modification of the TV and health outcomes association was investigated either by adding an interaction term of TV and SSC weather types to the regression models (Manuscript 3) or through stratification (Manuscript 5). In addition, stratification by age, gender, and season was performed for all the Manuscripts to identify vulnerable subgroups and determine whether hospital admissions or mortality risks differed by season. All regression analyses were performed with R software version 4.2.3 (2023-03-15 ucrt).

For Manuscript 1, of the 1 465 identified studies, only 45 met the inclusion criteria of which 23 studies investigated the association between TV indexes and CVD and RD hospital admission and the remaining 22 studies focused on CVD and RD mortality risks associated with TV. Most of these studies were conducted in Asia (particularly China), the United States, and Europe, with only two conducted in Africa. The studies investigated various TV indexes, including diurnal temperature range (DTR), temperature change between neighbouring days (TCN), and standard deviation between the minimum and maximum temperature. In most of the studies, children, people ≥ 65-years of age and males had higher risks of hospitalisation or dying from CVD and RD diseases due to exposure to TV.

For Manuscript 2, in general, a positive and statistically significant association between TV and CVD and RD hospital admissions was observed in Cape Town, even after controlling for the confounding variables. For the entire study group, TV showed the greatest effect at short exposure days, at 0-2 days for CVD and 0-1 days for RD hospitalisations. The 15-64 age group had the highest risk for CVD hospitalisation, with the effects reaching a peak at 0-3 days of exposure (3.02%, 95% CI:0.86%-5.23%). For RD hospitalisations, the highest risks were observed for the elderly, with the effects reaching a peak at 0-4 days of TV exposure (5.18%, 95% CI:2.03%-8.43%). In general people ≥65-years had higher risks of RD hospitalisation and the 15-64-years age group was more likely to be hospitalised due to CVD-related diseases. Males had higher risks of hospitalisations compared to females.

For Manuscript 3, season and SSC weather types modified the association between TV and hospital admissions in Cape Town from 2011 to 2016. Specifically, according to the seven SSC types, a stronger TV-CVD association occurred during MT weather conditions, with the most significant risks observed after four days of exposure (6.72% [95% CI:1.95%, 11.71%]). Immediate risks of TV on RD appeared with DM conditions (3.35% [95% CI:0.92%, 5.83%]). Grouping SSC categories by similar temperature and humidity characteristics (e.g., both tropical types), a modified association was observed, especially for the 15–64-year age group during tropical conditions for the CVD admissions. The 0-14- and 15-64-year age groups for RD hospital admissions appeared more vulnerable during dry and transitional weather conditions, respectively.

For Manuscript 4, a positive association between TV and mortality was observed in the five cities. Similar to Manuscript 3, the effect estimates were higher for RD health outcomes (mortality) as compared to CVD mortality. The pooled estimates showed the highest RD mortality risks were associated with a decrease of RR=1.21 (95% CI:1.04; 1.38) from the 5th to the 50th percentile in TV at 0-2 days for all ages combined. The elderly appeared more vulnerable to RD mortality than <65 years age group, with significant mortality risks per increase in TV at 0-2 days (RR=1.18, 95% CI:1.04;1.32), 0-3 days (RR=1.16, 95% CI:1.04;1.28) and at 0-7 days (RR=1.12, 95% CI: 1.02;1.22) from the 50th to the 75th percentile. No significant results were observed for CVD mortality.

For Manuscript 5, The pooled estimates showed the highest and significant increase in RD mortality of 1.21(95% CI:1.04;1.38) per an increase in TV at 0-2 days from the 25th to the 50th percentile for all ages combined. The elderly appeared more vulnerable to RD mortality than <65 years age group, with significant mortality risks per increase in TV at 0-2 days (RR=1.18, 95% CI:1.04;1.32), 0-3 days (RR=1.16, 95% CI:1.04;1.28) and at 0-7 days (RR=1.12, 95% CI: 1.02;1.22) from the 50th to the 75th percentile. A stratified analysis showed the elderly and women as more vulnerable. For the entire study population, greater association was observed during MT weather conditions in Bloemfontein (1.87 95% 0.96-3.63), DT weather conditions in Cape Town (1.27; 95% CI0.83-1.95), MM weather conditions in Johannesburg (1.35; 95% CI:0.51-3.56) and during TR weather conditions in Durban (1.17; 95% CI0.63-2.19) and Gqeberha (1.35; 95% CI:0.51-3.56).

This thesis demonstrated that climate change and variability are a huge public health threat in South Africa. Specifically, the results of this thesis showed that TV is an important risk factor for cardiorespiratory health outcomes in South Africa. Furthermore, it demonstrated that season, synoptic weather types, and age modify the association between TV and health outcomes. Application of the SSC scheme can provide insights into how atmospheric circulation patterns and synoptic weather types affect temperature and health outcomes. The occurrence of individual air masses can be forecasted, providing helpful information for planning public health resources. The results of the present study imply that the synergistic effects of other environmental and meteorological factors should be considered when conducting risk assessments for health and climate-related research. This thesis advances the knowledge of mortality risk factors in South Africa.