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Air pollution poses a serious threat to human health and the general ecosystem both in South Africa and globally. This is mostly caused by the mining and combustion of fossil fuels, such as coal. There are some known pollutants associated with coal mining and combustion that are emitted into the air, resulting in various health implications that affect children the most as they are the most vulnerable. In this study, the levels of certain air pollutants in schools in the vicinities of coal mines were assessed. A cross-sectional study design was adopted. Five schools were purposively selected for this study. Air samples were collected inside and outside the classrooms of each school. Radiello V R passive air samplers were used to measure the levels of sulphur dioxide, nitrogen dioxide and ozone while filter pumps were employed for lead (Pb). Standard laboratory analytical methods were employed for the analysis. Estimates of the possible health risks resulting from exposure to airborne sulphur dioxide, nitrogen dioxide and ozone were performed using the United States Environmental Protection Agency Human Health Risk Assessment framework. The non-cancer risk of sulphur dioxide, nitrogen dioxide and ozone was determined using the hazard quotient. The results of this study revealed that sulphur dioxide, nitrogen dioxide and ozone were detected within and outside the classrooms at various levels. For example, the concentration of sulphur dioxide within the classroom ranged from 3.0 to 38 mg/m 3. Outside the classroom, sulphur dioxide levels detected were much higher ranging from 17 to 84 mg/m 3. The results of the non-carcinogenic risks from exposure to nitrogen dioxide, sulphur dioxide and ozone via inhalation route were less than 1.0. The elevated levels of these pollutants in the vicinity of schools investigated should be a cause for concern for all the stakeholders in the education sector. Therefore, appropriate measures need to be taken urgently to safeguard the health of the concerned community.

Lead (Pb) exposure has been a serious environmental and public health problem throughout the world over the years. The major sources of lead in the past were paint and gasoline before they were phased out due to its toxicity. Meanwhile, people continue to be exposed to lead from time to time through many other sources such as water, food, soil and air. Lead exposure from these sources could have detrimental effects on human health, especially in children. UNICEF reported that approximately 800 million children have blood lead levels (BLLs) at or above 5 micrograms per deciliter (µg/dL) globally. This paper reports on the potential risks of lead exposure from early life through later life. The articles used in this study were searched from databases such as Springer, Science Direct, Hindawi, MDPI, Google Scholar, PubMed and other academic databases. The levels of lead exposure in low income and middle-income countries (LMICs) and high-income countries (HICs) were reported, with the former being more affected. The intake of certain nutrients could play an essential role in reducing (e.g., calcium and iron) or increasing (e.g., high fat foods) lead absorption in children. Elevated blood lead levels may disturb the cells’ biological metabolism by replacing beneficial ions in the body such as calcium, magnesium, iron and sodium. Once these ions are replaced by lead, they can lead to brain disorders, resulting in reduced IQ, learning difficulties, reduced attention span and some behavioral problems. Exposure to lead at an early age may lead to the development of more critical problems later in life. This is because exposure to this metal can be harmful even at low exposure levels and may have a lasting and irreversible effect on humans. Precautionary measures should be put in place to prevent future exposure. These will go a long way in safeguarding the health of everyone, most especially the young ones.

We investigated the role of Body mass index (BMI) in non-communicable diseases-polycystic ovary syndrome (PCOS), type 2 diabetes (T2DM) and coronary artery disease (CAD). Using a case control design, we compared mean BMI and its categories, in gender and disease specific samples, and computed odds ratios as well as receiver operator characteristic (ROC) curve. The 95 percentile cut off values were also determined but only for controls. We found mean BMI and prevalence of obesity to be higher in PCOS and T2DM and lower in CAD cases than controls. The ROC analysis suggested gender specific cutoff values are more sensitive than pooled sample. The area under the ROC curve which is highly significant suggests predictive utility of the BMI cut off values both for PCOS and T2DM.

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