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

The impact of environmental conditions on non-communicable diseases in sub-Saharan Africa: A scoping review of epidemiologic evidence

Background

The burden of non-communicable diseases (NCDs) in sub-Saharan Africa (SSA) is increasing. Environmental conditions such as heavy metals and air pollution have been linked with the incidence and mortality of chronic diseases such as cancer, as well as cardiovascular and respiratory diseases. We aimed to scope the current state of evidence on the impact of environmental conditions on NCDs in SSA.

Methods

We conducted a scoping review to identify environmental conditions linked with NCDs in SSA by identifying studies published from January 1986 through February 2023. We searched African Index Medicus, Ovid Medline, Scopus, Web of Science, and Greenfile. Using the PICOS study selection criteria, we identified studies conducted in SSA focussed on physical environmental exposures and incidence, prevalence, and mortality of NCDs. We included only epidemiologic or quantitative studies.

Results

We identified 6754 articles from electronic database searches; only 36 met our inclusion criteria and were qualitatively synthesised. Two studies were conducted in multiple SSA countries, while 34 were conducted across ten countries in SSA. Air pollution (58.3%) was the most common type of environmental exposure reported, followed by exposure to dust (19.4%), meteorological variables (13.8%), heavy metals (2.7%), soil radioactivity (2.7%), and neighbourhood greenness (2.7%). The examined NCDs included respiratory diseases (69.4%), cancer (2.7%), stroke (5.5%), diabetes (2.7%), and two or more chronic diseases (19.4%). The study results suggest an association between environmental exposures and NCDs, particularly for respiratory diseases. Only seven studies found a null association between environmental conditions and chronic diseases.

Conclusions

There is a growing body of research on environmental conditions and chronic diseases in the SSA region. Although some cities in SSA have started implementing environmental monitoring and control measures, there remain high levels of environmental pollution. Investment can focus on improving environmental control measures and disease surveillance.

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.

Causal Associations of Air Pollution With Cardiovascular Disease and Respiratory Diseases Among Elder Diabetic Patients

Extensive researches have linked air pollutants with cardiovascular disease (CVD) and respiratory diseases (RD), however, there is limited evidence on causal effects of air pollutants on morbidity of CVD or RD with comorbidities, particularly diabetes mellitus in elder patients. We included hospital admissions for CVD or RD among elder (≥65 years) diabetic patients between 2014 and 2019 in Beijing. A time-stratified case-crossover design based on negative-control exposure was used to assess causal associations of short-term exposure to air pollutants with CVD and RD among diabetic patients with the maximum lag of 7 days. A random forest regression model was used to calculate the contribution magnitude of air pollutants. A total of 493,046 hospital admissions were recorded. Per 10 μg/m³ uptick in PM₁, PM_2.5, PM₁₀, SO₂, NO₂, O₃, and 1 mg/m³ in CO was associated with 0.29 (0.05, 0.53), 0.14 (0.02, 0.26), 0.06 (0.00, 0.12), 0.36 (0.01, 0.70), 0.21 (0.02, 0.40), -0.08 (-0.25, 0.09), and 4.59 (0.56, 8.61) causal effect estimator for admission of CVD among diabetic patients, corresponding to 0.12 (0.05, 0.18), 0.09 (0.05, 0.13), 0.05, 0.23 (0.06, 0.41), 0.10 (0.02, 0.19), -0.04 (-0.06, -0.01), and 3.91(1.81, 6.01) causal effect estimator for RD among diabetic patients. The effect of gaseous pollutants was higher than particulate pollutants in random forest model. Short-term exposure to air pollution was causally associated with increased admission of CVD and RD among elder diabetic patients. Gaseous pollutants had a greater contribution to CVD and RD among elder diabetic patients.

Ambient nitrogen dioxide and cardiovascular diseases in rural regions: a time-series analyses using data from the new rural cooperative medical scheme in Fuyang, East China

Most of studies relating ambient nitrogen dioxide (NO₂) exposure to hospital admissions for cardiovascular diseases (CVDs) were conducted among urban population. Whether and to what extent these results could be generalizable to rural population remains unknown. We addressed this question using data from the New Rural Cooperative Medical Scheme (NRCMS) in Fuyang, Anhui, China. Daily hospital admissions for total CVDs, ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke in rural regions of Fuyang, China, were extracted from NRCMS between January 2015 and June 2017. A two-stage time-series analysis method was used to assess the associations between NO₂ and CVD hospital admissions and the disease burden fractions attributable to NO₂. In our study period, the average number (standard deviation) of hospital admissions per day were 488.2 (117.1) for total CVDs, 179.8 (45.6) for ischaemic heart disease, 7.0 (3.3) for heart rhythm disturbances, 13.2 (7.2) for heart failure, 267.9 (67.7) for ischaemic stroke, and 20.2 (6.4) for haemorrhagic stroke. The 10-μg/m³ increase of NO₂ was related to an elevated risk of 1.9% (RR: 1.019, 95% CI: 1.005 to 1.032) for hospital admissions of total CVDs at lag0-2 days, 2.1% (1.021, 1.006 to 1.036) for ischaemic heart disease, and 2.1% (1.021, 1.006 to 1.035) for ischaemic stroke, respectively, while no significant association was observed between NO₂ and hospital admissions for heart rhythm disturbances, heart failure, and haemorrhagic stroke. The attributable fractions of total CVDs, ischaemic heart disease, and ischaemic stroke to NO₂ were 6.52% (1.87 to 10.94%), 7.31% (2.19 to 12.17%), and 7.12% (2.14 to 11.85%), respectively. Our findings suggest that CVD burdens in rural population are also partly attributed to short-term exposure to NO₂. More studies across rural regions are required to replicate our findings.

Exploring the impact of particulate matter on mortality in coastal Mediterranean environments

Air pollution is one of the most important problems the world is facing nowadays, adversely affecting public health and causing millions of deaths every year. Particulate matter is a criteria pollutant that has been linked to increased morbidity, as well as all-cause and cause-specific mortality. However, this association remains under-investigated in smaller-size cities in the Eastern Mediterranean, which are also frequently affected by heat waves and dust storms. This study explores the impact of particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀) and ≤ 2.5 μm (PM_2.5) on mortality (all-cause, cardiovascular, respiratory) in two coastal cities in the Eastern Mediterranean; Thessaloniki, Greece and Limassol, Cyprus. Generalized additive Poisson models were used to explore overall and gender-specific associations, controlling for long- and short-term patterns, day of week and the effect of weather variables. Moreover, the effect of different lags, season, co-pollutants and dust storms on primary associations was investigated. A 10 μg/m³ increase in PM_2.5 resulted in 1.10 % (95 % CI: -0.13, 2.34) increase in cardiovascular mortality in Thessaloniki, and in 3.07 % (95 % CI: -0.90, 7.20) increase in all-cause mortality in Limassol on the same day. Additionally, significant positive associations were observed between PM_2.5 as well as PM₁₀ and mortality at different lags up to seven days. Interestingly, an association with dust storms was observed only in Thessaloniki, having a protective effect, while the gender-specific analysis revealed significant associations only for the males in both cities. The outcome of this study highlights the need of city- or county-specific public health interventions to address the impact of climate, population lifestyle behaviour and other socioeconomic factors that affect the exposure to air pollution and other synergistic effects that alter the effect of PM on population health.

Air pollution and its effects on emergency room visits in tertiary respiratory care centers in Delhi, India

Environmental pollution has harmful effects on human health, particularly the respiratory system. We aimed to study the impact of daily ambient air pollution on daily emergency room visits for acute respiratory symptoms. This study was conducted in two tertiary respiratory care centres in Delhi, India. Daily counts of emergency room visits were collected. All patients attending the emergency room were screened for acute onset (less than 2 weeks) of respiratory symptoms and were recruited if they were staying in Delhi continuously for at least 4 weeks and having onset (≤2 weeks) of respiratory symptoms. Daily average air pollution data for the study period was obtained from four continuous ambient air quality monitoring stations. A total of 61,285 patients were screened and 11,424 were enrolled from June 2017 to February 2019. Cough and difficulty in breathing were most common respiratory symptoms. Poor air quality was observed during the months of October to December. Emergency room visits with acute respiratory symptoms significantly increased per standard deviation increase in PM10 from lag days 2-7. Increase in wheezing was primarily seen with increase in NO2. Pollutant levels have effect on acute respiratory symptoms and thus influence emergency room visits. *************************************************************** *Appendix Authors list Kamal Singhal,1 Kana Ram Jat,2 Karan Madan,3 Mohan P. George,4 Kalaivani Mani,5 Randeep Guleria,3 Ravindra Mohan Pandey,5 Rupinder Singh Dhaliwal,6 Rakesh Lodha,2 Varinder Singh1 1Department of Paediatrics, Lady Hardinge Medical College and associated Kalawati Saran Children's Hospital, New Delhi, India 2Department of Paediatrics, All India Institute of Medical Sciences, New Delhi, India 3Department of Pulmonary Medicine, Critical Care and Sleep Disorders, All India Institute of Medical Sciences, New Delhi, India 4Department of Environment, Delhi Pollution Control Committee, Kashmere Gate, New Delhi, India 5Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India 6Department of Non-communicable Diseases, Indian Council of Medical Research, New Delhi, India.

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.

Synergistic or Antagonistic Health Effects of Long- and Short-Term Exposure to Ambient NO2 and PM2.5: A Review

Studies on adverse health effects associated with air pollution mostly focus on individual pollutants. However, the air is a complex medium, and thus epidemiological studies face many challenges and limitations in the multipollutant approach. NO₂ and PM_2.5 have been selected as both originating from combustion processes and are considered to be the main pollutants associated with traffic; moreover, both elicit oxidative stress responses. An answer to the question of whether synergistic or antagonistic health effects of combined pollutants are demonstrated by pollutants monitored in ambient air is not explicit. Among the analyzed studies, only a few revealed statistical significance. Exposure to a single pollutant (PM_2.5 or NO₂) was mostly associated with a small increase in non-accidental mortality (HR:1.01-1.03). PM_2.5 increase of <10 µg/m³ adjusted for NO₂ as well as NO₂ adjusted for PM_2.5 resulted in a slightly lower health risk than a single pollutant. In the case of cardiovascular heart disease, mortality evoked by exposure to PM_2.5 or NO₂ adjusted for NO₂ and PM_2.5, respectively, revealed an antagonistic effect on health risk compared to the single pollutant. Both short- and long-term exposure to PM_2.5 or NO₂ adjusted for NO₂ and PM_2.5, respectively, revealed a synergistic effect appearing as higher mortality from respiratory diseases.

Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa

There is a paucity of air quality data in sub-Saharan African countries to inform science driven air quality management and epidemiological studies. We investigated the use of available remote-sensing aerosol optical depth (AOD) data to develop spatially and temporally resolved models to predict daily particulate matter (PM₁₀) concentrations across four provinces of South Africa (Gauteng, Mpumalanga, KwaZulu-Natal and Western Cape) for the year 2016 in a two-staged approach. In stage 1, a Random Forest (RF) model was used to impute Multiangle Implementation of Atmospheric Correction AOD data for days where it was missing. In stage 2, the machine learner algorithms RF, Gradient Boosting and Support Vector Regression were used to model the relationship between ground-monitored PM₁₀ data, AOD and other spatial and temporal predictors. These were subsequently combined in an ensemble model to predict daily PM₁₀ concentrations at 1 km × 1 km spatial resolution across the four provinces. An out-of-bag R² of 0.96 was achieved for the first stage model. The stage 2 cross-validated (CV) ensemble model captured 0.84 variability in ground-monitored PM₁₀ with a spatial CV R² of 0.48 and temporal CV R² of 0.80. The stage 2 model indicated an optimal performance of the daily predictions when aggregated to monthly and annual means. Our results suggest that a combination of remote sensing data, chemical transport model estimates and other spatiotemporal predictors has the potential to improve air quality exposure data in South Africa's major industrial provinces. In particular, the use of a combined ensemble approach was found to be useful for this area with limited availability of air pollution ground monitoring data.

Long-Term Effects of Ambient Particulate and Gaseous Pollutants on Serum High-Sensitivity C-Reactive Protein Levels: A Cross-Sectional Study Using KoGES-HEXA Data

Ambient air pollutants reportedly increase inflammatory responses associated with multiple chronic diseases. We investigated the effects of long-term exposure to ambient air pollution on high-sensitivity C-reactive protein (hs-CRP) using data from 60,581 participants enrolled in the Korean Genome and Epidemiology Study-Health Examinees Study between 2012 and 2017. Community Multiscale Air Quality System with surface data assimilation was used to estimate the participants' exposure to criteria air pollutants based on geocoded residential addresses. Long-term exposure was defined as the 2-year moving average concentrations of PM₁₀, PM_2.5, SO₂, NO₂, and O₃. Multivariable linear and logistic regression models were utilized to estimate the percent changes in hs-CRP and odds ratios of systemic low-grade inflammation (hs-CRP > 3 mg/L) per interquartile range increment in air pollutants. We identified positive associations between hs-CRP and PM₁₀ (% changes: 3.75 [95% CI 2.68, 4.82]), PM_2.5 (3.68, [2.57, 4.81]), SO₂ (1.79, [1.10, 2.48]), and NO₂ (3.31, [2.12, 4.52]), while negative association was demonstrated for O₃ (-3.81, [-4.96, -2.65]). Elevated risks of low-grade inflammation were associated with PM₁₀ (odds ratio: 1.07 [95% CI 1.01, 1.13]), PM_2.5 (1.08 [1.02, 1.14]), and SO₂ (1.05 [1.01, 1.08]). The odds ratios reported indicated that the exposures might be risk factors for inflammatory conditions; however, they did not reflect strong associations. Our findings suggest that exposure to air pollutants may play a role in the inflammation process.

Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006–2015

Background: The health effect of air pollution is rarely quantified in Africa, and this is evident in global systematic reviews and multi-city studies which only includes South Africa. Methods: A time-series analysis was conducted on daily mortality (cardiovascular (CVD) and respiratory diseases (RD)) and air pollution from 2006–2015 for the city of Cape Town. We fitted single- and multi-pollutant models to test the independent effects of particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ozone (O3) from co-pollutants. Results: daily average concentrations per interquartile range (IQR) increase of 16.4 µg/m3 PM10, 10.7 µg/m3 NO2, 6 µg/m3 SO2 and 15.6 µg/m3 O3 lag 0–1 were positively associated with CVD, with an increased risk of 2.4% (95% CI: 0.9–3.9%), 2.2 (95% CI: 0.4–4.1%), 1.4% (95% CI: 0–2.8%) and 2.5% (95% CI: 0.2–4.8%), respectively. For RD, only NO2 showed a significant positive association with a 4.5% (95% CI: 1.4–7.6%) increase per IQR. In multi-pollutant models, associations of NO2 with RD remained unchanged when adjusted for PM10 and SO2 but was weakened for O3. In CVD, O3 estimates were insensitive to other pollutants showing an increased risk. Interestingly, CVD and RD lag structures of PM10, showed significant acute effect with evidence of mortality displacement. Conclusion: The findings suggest that air pollution is associated with mortality, and exposure to PM10 advances the death of frail population.