Respiratory health among adolescents living in the Highveld Air Pollution Priority Area in South Africa.

BACKGROUND: Air pollution is a global, public health emergency. The effect of living in areas with very poor air quality on adolescents' physical health is largely unknown. The aim of this study was to investigate the prevalence of adverse respiratory health outcomes among adolescents living in a known air pollution hotspot in South Africa. METHODS: Ambient air quality data from 2005 to 2019 for the two areas, Secunda and eMbalenhle, in the Highveld Air Pollution Priority Area in Mpumalanga province, South Africa were gathered and compared against national ambient air pollution standards and the World Health Organization Air Quality Guidelines. In 2019, adolescents attending schools in the areas completed a self-administered questionnaire investigating individual demographics, socio-economic status, health, medical history, and fuel type used in homes. Respiratory health illnesses assessed were doctor-diagnosed hay fever, allergies, frequent cough, wheezing, bronchitis, pneumonia and asthma. The relationship between presence (at least one) or absence (none) of self-reported respiratory illness and risk factors, e.g., fuel use at home, was explored. Logistic regression was used to estimate the odds ratio and 95% confidence interval (CI) of risk factors associated with respiratory illness adjusted for body mass index (measured by field assistants), gender, education level of both parents / guardians and socio-economic status. RESULTS: Particulate matter and ozone were the two pollutants most frequently exceeding national annual air quality standards in the study area. All 233 adolescent participants were between 13 and 17 years of age. Prevalence of self-reported respiratory symptoms among the participants ranged from 2% for 'ever' doctor-diagnosed bronchitis and pneumonia to 42% ever experiencing allergies; wheezing chest was the second most reported symptom (39%). Half (52%) of the adolescents who had respiratory illness were exposed to environmental tobacco smoke in the dwelling. There was a statistically significant difference between the presence or absence of self-reported respiratory illness based on the number of years lived in Secunda or eMbalenhle (p = 0.02). For a one-unit change in the number of years lived in an area, the odds of reporting a respiratory illness increased by a factor of 1.08 (p = 0.025, 95% CI = 1.01-1.16). This association was still statistically significant when the model was adjusted for confounders (p = 0.037). CONCLUSIONS: Adolescents living in air polluted areas experience adverse health impacts Future research should interrogate long-term exposure and health outcomes among adolescents living in the air polluted environment.

Effect of Rooibos (Aspalathus linearis) extract on atorvastatin-induced toxicity in C3A liver cells.

Rooibos (Aspalathus linearis) has various health benefits. Two case studies have associated chronic Rooibos consumption with conventional prescription medications, including atorvastatin (ATV), with hepatotoxicity. Statins act by inhibiting hydroxymethylglutaryl-coenzyme A reductase, a rate-limiting enzyme in cholesterol synthesis. Although rare, statins are potentially hepatotoxic. The aim was to investigate interactions between aspalathin-rich Rooibos extract GRT™ and ATV-induced hepatotoxicity in C3A liver cells cultured with and without palmitate. Effects of co-treatment of GRT + ATV on cell viability, oxidative stress, apoptosis, mitochondrial integrity, and cellular reactive oxygen species (ROS) production were assessed. Significantly increased ROS production was observed in cells exposed to ATV and palmitate. Combination therapy of GRT + ATV also showed significant increases in ROS production. Under palmitate-treated conditions, ATV-induced significant apoptosis which was not ameliorated by GRT + ATV co-treatment. Despite studies purporting hepatoprotection from Rooibos, our study showed that GRT was unable to modulate ATV-induced hepatotoxic effects in this model.

Developing a Healthy Environment Assessment Tool (HEAT) to Address Heat-Health Vulnerability in South African Towns in a Warming World.

Prolonged exposure to high temperatures can cause heat-related illnesses and accelerate death, especially in the elderly. We developed a locally-appropriate Healthy Environment Assessment Tool, or 'HEAT' tool, to assess heat-health risks among communities. HEAT was co-developed with stakeholders and practitioners/professionals from the Rustenburg Local Municipality (RLM), a setting in which heat was identified as a risk in an earlier study. Feedback was used to identify vulnerable groups and settings in RLM, consider opportunities and barriers for interventions, and conceptualize a heat-health vulnerability assessment tool for a heat-resilient town. Using information provided by the RLM Integrated Development Plan, the HEAT tool was applied in the form of eight indicators relating to heat-health vulnerability and resilience and areas were evaluated at the ward level. Indicators included population, poverty, education, access to medical facilities, sanitation and basic services, public transport, recreation/community centres, and green spaces. Out of 45 wards situated in the municipality, three were identified as critical risk (red), twenty-eight as medium-high risk (yellow), and six as low risk (green) in relation to heat-health vulnerability. Short-term actions to improve heat health resilience in the community were proposed and partnerships between local government and the community to build heat health resilience were identified.

Household Air Pollution and Respiratory Symptoms a Month Before and During the Stringent COVID-19 Lockdown Levels 5 and 4 in South Africa.

Background: Household air pollution (HAP) is associated with adverse human health impacts. During COVID-19 Lockdown Levels 5 and 4 (the most stringent levels), South Africans remained at home, potentially increasing their exposure to HAP. Objectives: To investigate changes in fuel use behaviours/patterns of use affecting HAP exposure and associated HAP-related respiratory health outcomes during COVID-19 Lockdown Levels 5 and 4. Methods: This was a cross-sectional online and telephonic survey of participants from an existing database. Logistic regression and McNemar's test were used to analyse household-level data. Results: Among 2 505 participants, while electricity was the main energy source for cooking and heating the month before and during Lockdown Levels 5 and 4, some households used less electricity during Lockdown Levels 5 and 4 or switched to "dirty fuels." One third of participants reported presence of environmental tobacco smoke in the home, a source of HAP associated with respiratory illnesses. Prevalence of HAP-related respiratory health outcomes were <10% (except dry cough). Majority of households reported cooking more, cleaning more and spending more time indoors during Lockdown Levels 5 and 4 - potentially exposed to HAP. Conclusion: Should South Africa return to Lockdown Levels 5 or 4, awareness raising about the risks associated with HAP as well as messaging information for prevention of exposure to HAP, including environmental tobacco smoke, and associated adverse health impacts will be necessary.

The Epidemiology of Skin Cancer and Public Health Strategies for Its Prevention in Southern Africa.

Skin cancer is a non-communicable disease that has been underexplored in Africa, including Southern Africa. Exposure to solar ultraviolet radiation (UVR) is an important, potentially modifiable risk factor for skin cancer. The countries which comprise Southern Africa are Botswana, Lesotho, Namibia, South Africa, and Swaziland. They differ in population size and composition and experience different levels of solar UVR. Here, the epidemiology and prevalence of skin cancer in Southern African countries are outlined. Information is provided on skin cancer prevention campaigns in these countries, and evidence sought to support recommendations for skin cancer prevention, especially for people with fair skin, or oculocutaneous albinism or HIV-AIDS who are at the greatest risk. Consideration is given to the possible impacts of climate change on skin cancer in Southern Africa and the need for adaptation and human behavioural change is emphasized.

A Comparison of Solar Ultraviolet Radiation Exposure in Urban Canyons in Venice, Italy and Johannesburg, South Africa.

Urban environments can have high-risk spaces that can provide excess personal sun exposure, such as urban or street canyons, and the spaces between buildings, among others. In these urban spaces, sun exposure can be high or low depending on several factors. Polysulphone film (PSF) was used to assess possible daily solar ultraviolet radiation (UVR) exposure in urban canyons in Venice, Italy and, for the first time in Africa, in Johannesburg, South Africa. The photodegradation of PSF upon solar exposure was monitored at a wavelength of 330 nm by ultraviolet-visible spectrophotometry, and the resultant change was converted to standard erythemal dose (SED) units (1 SED = 100 J m-2 ). Mean daily ambient solar UVR exposure measured for Venice and Johannesburg ranged between 20-28 SED and 33-43 SED, respectively. Canyon-located PSF exposures were lower in Venice (1-9 SED) than those in Johannesburg (9-39 SED), depending mainly on the sky view factor and orientation to the sun. There was large variation in solar UVR exposure levels in different urban canyons. These preliminary results should be bolstered with additional studies for a better understanding of excess personal exposure risk in urban areas, especially in Africa.

Comparison of GOME-2 UVA Satellite Data to Ground-Based UVA Measurements in South Africa.

Satellite estimates of surface ultraviolet A (UVA) (315-400 nm) from the Global Ozone Monitoring Experiment (GOME)-2 were compared to ground-based measurements at four stations in South Africa for 2015. The comparison of daily exposure and daily maximum irradiance was completed for all-sky and clear-sky conditions. There is a strong linear correlation between the satellite and ground-based data with a correlation coefficient (r) between 0.86 and 0.97 for all-sky conditions. However, at three of the stations the satellite data are underestimated compared to ground-based data with a mean bias error (MBE) between -8.7% and -20.6%. A seasonal analysis indicated that there is a link between the bias in ground-based and GOME-2 UVA and cloud fraction. Factors such as aerosols, surface albedo, altitude and data resolution may contribute to the underestimations found at the three sites. These results indicate that satellite estimates of surface UVA over South Africa do not exhibit the same behavior as other stations around the world and therefore require further validation.

Dwelling Characteristics Influence Indoor Temperature and May Pose Health Threats in LMICs.

Background: Shelter and safe housing is a basic human need that brings about a sense of ownership, self-sufficiency, and citizenship. Millions of people around the world live in inadequate dwellings in unhealthy areas, such as urban slums. These dwellings may experience indoor temperatures that impact inhabitants' health. Indoor dwelling temperatures vary depending on many factors including geographic location, such as inland versus coastal. In an era of climate change, understanding how dwelling characteristics influence indoor temperature is important, especially in low- and middle-income countries, to protect health. Objective: To assess indoor temperature in low-cost dwellings located in a coastal setting in relation to dwelling characteristics. Methods: Indoor temperature and relative humidity loggers were installed from 1 June 2017 to 15 May 2018 in 50 dwellings in two settlements in a coastal town on the east coast of South Africa. Ambient outdoor temperature data were obtained from the national weather service, indoor temperature data were converted into apparent temperature, and heat index calculations were made to consider possible heat-health risks. A household questionnaire and dwelling observation assessment were administered. A mixed-effects linear regression model was constructed to consider the impact of dwelling characteristics on indoor apparent temperature. Findings: Among 17 dwellings with all data sets, indoor temperatures were consistently higher than, and well correlated (r = 0.92) with outdoor temperatures. Average differences in indoor and outdoor temperatures were about 4°C, with statistically significant differences in percentage difference of indoor/outdoor between seasons (p < 0.001). Heat indices for indoor temperatures were exceeded mostly in summer, thereby posing possible health risks. Dwellings with cement floors were statistically significantly cooler than any other floor type across all seasons. Conclusions: Low-cost dwellings experienced temperatures indoors higher than outdoor temperatures in part due to floor type. These results help inform interventions that consider housing and human health (n = 289).