These studies add to the evidence of a strong association between PTB, even if treated, and subsequent airflow obstruction as well as restrictive loss. Unanswered questions include extent of recovery over time, effect modification by smoking and other cofactors, and degree of reversibility by treatment.

Background-Fish processing is a common economic activity in Southern Africa. The aim of this study was to determine the prevalence and host determinants of allergic symptoms, allergic sensitization, bronchial hyper-responsiveness and asthma among workers processing saltwater fish.

The test-specific incidence of latent tuberculosis infection (LTBI) in healthcare workers from sub-Saharan Africa is unknown. 505 healthcare workers from South Africa were screened at baseline, and after 12 months, with a questionnaire, the tuberculin skin test (TST), and two T-cell assays (T-SPOT.TB and QuantiFERON-TB Gold-In-Tube). Test-specific conversion rates were calculated. The prevalence of presumed LTBI at baseline was 84, 69 and 62% using the TST, QuantiFERON-TB Gold-In-Tube and T-SPOT.TB, respectively. The annual test-specific conversion rate, depending on the cut-off point used, was as follows: TST 38%; QuantiFERON-TB Gold-In-Tube 13–22%; and T-SPOT.TB 18–22%. Annual reversion rates were 4, 7 and 16%, respectively. The annual TST conversion rate was significantly higher than that derived from published local community-based data (IRR 3.53, 95% CI 1.81–6.88). Factors associated with conversion (any test) included healthcare sector of employment, counselling of tuberculosis patients, and a baseline positive TST (for T-SPOT.TB). The annual rate of tuberculosis infection in South African healthcare workers was very high, irrespective of the testing method used, and may be explained by occupational exposure, as the rate was considerably higher than non-healthcare workers from the same community. Collectively, these data support the need for implementation of tuberculosis-specific infection control measures in Africa.

While baker's asthma has been well described, various asthma phenotypes in bakery workers have yet to be characterised. Our study aims to describe the asthma phenotypes in supermarket bakery workers in relation to host risk factors and self-reported exposure to flour dust.A cross-sectional study of 517 supermarket bakery workers in 31 bakeries used a questionnaire, skin prick tests, and specific immunoglobulin E to wheat, rye and fungal aamylase and methacholine challenge testing.The prevalence of probable occupational asthma (OA, 13%) was higher than atopic (6%), nonatopic (6%) and work-aggravated asthma (WAA, 3%) phenotypes. Previous episodes of high exposure to dusts, fumes and vapours causing asthma symptoms were more strongly associated with WAA (OR 5.8, 95% CI 1.7-19.2) than OA (2.8, 1.4-5.5). Work-related ocular-nasal symptoms were significantly associated with WAA (4.3, 1.3-13.8) and OA (3.1, 1.8-5.5). Bakers with OA had an increased odds ratio of reporting adverse reactions to ingested grain products (6.4, 2.0-19.8).OA is the most common phenotype among supermarket bakery workers. Analysis of risk factors contributes to defining clinical phenotypes, which will guide ongoing medical surveillance and clinical management of bakery workers.

In low- and middle-income countries, noise exposure and its negative health effects have been little explored. The present study aimed to assess the noise exposure situation in adults living in informal settings in the Western Cape Province, South Africa. We conducted continuous one-week outdoor noise measurements at 134 homes in four different areas. These data were used to develop a land use regression (LUR) model to predict A-weighted day-evening-night equivalent sound levels (Lden) from geographic information system (GIS) variables. Mean noise exposure during day (6:00–18:00) was 60.0 A-weighted decibels (dB(A)) (interquartile range 56.9–62.9 dB(A)), during night (22:00–6:00) 52.9 dB(A) (49.3–55.8 dB(A)) and average Lden was 63.0 dB(A) (60.1–66.5 dB(A)). Main predictors of the LUR model were related to road traffic and household density. Model performance was low (adjusted R2 = 0.130) suggesting that other influences than those represented in the geographic predictors are relevant for noise exposure. This is one of the few studies on the noise exposure situation in low- and middle-income countries. It demonstrates that noise exposure levels are high in these settings.

BackgroundThere is evidence from existing literature that ambient air pollutant exposure in early childhood likely plays an important role in asthma exacerbation and other respiratory symptoms, with greater effect among asthmatic children. However, there is inconclusive evidence on the role of ambient air pollutant exposures in relation to increasing asthma prevalence as well as asthma induction in children. At the population level, little is known about the potential synergistic effects between pollen allergens and air pollutants since this type of association poses challenges in uncontrolled real life settings. In particular, data from sub-Sahara Africa is scarce and virtually absent among populations residing in informal residential settlements.Methods/designA prospective cohort study of 600 school children residing in four informal settlement areas with varying potential ambient air pollutant exposure levels in the Western Cape in South Africa is carried-out. The study has two follow-up periods of at least six-months apart including an embedded panel study in summer and winter. The exposure assessment component models temporal and spatial variability of air quality in the four study areas over the study duration using land-use regression modelling (LUR). Additionally, daily pollen levels (mould spores, tree, grass and weed pollen) in the study areas are recorded. In the panel study asthma symptoms and serial peak flow measurements is recorded three times daily to determine short-term serial airway changes in relation to varying ambient air quality and pollen over 10-days during winter and summer. The health outcome component of the cohort study include; the presence of asthma using a standardised ISAAC questionnaire, spirometry, fractional exhaled nitric-oxide (FeNO) and the presence of atopy (Phadiatop).DiscussionThis research applies state of the art exposure assessment approaches to characterize the effects of ambient air pollutants on childhood respiratory health, with a specific focus on asthma and markers of airway inflammation (FeNO) in South African informal settlement areas by considering also pollen counts and meteorological factors. The study will generate crucial data on air pollution and asthma in low income settings in sub-Sahara Africa that is lacking in the international literature.

Air pollution can cause many adverse health outcomes, including cardiovascular and respiratory disorders. Land use regression (LUR) models are frequently used to describe small-scale spatial variation in air pollution levels based on measurements and geographical predictors. They are particularly suitable in resource limited settings and can help to inform communities, industries, and policy makers. Weekly measurements of NO2 and PM2.5 were performed in three informal areas of the Western Cape in the warm and cold seasons 2015–2016. Seasonal means were calculated using routinely monitored pollution data. Six LUR models were developed (four seasonal and two annual) using a supervised stepwise land-use-regression method. The models were validated using leave-one-out-cross-validation and tested for spatial autocorrelation. Annual measured mean NO2 and PM2.5 were 22.1 μg/m3 and 10.2 μg/m3, respectively. The NO2 models for the warm season, cold season, and overall year explained 62%, 77%, and 76% of the variance (R2). The PM2.5 annual models had lower explanatory power (R2 = 0.36, 0.29, and 0.29). The best predictors for NO2 were traffic related variables (major roads, bus routes). Local sources such as grills and waste burning sites appeared to be good predictors for PM2.5, together with population density. This study demonstrates that land-use-regression modelling for NO2 can be successfully applied to informal peri-urban settlements in South Africa using similar predictor variables to those performed in Europe and North America. Explanatory power for PM2.5 models is lower due to lower spatial variability and the possible impact of local transient sources. The study was able to provide NO2 and PM2.5 seasonal exposure estimates and maps for further health studies.

Exposure to inhalable spice dust (GM >2.06 mg/m(3)) containing garlic (GM>0.24 µg/m³) and chili pepper (GM >0.44 µg/m(3)) allergens increase the risk of allergic respiratory disease and asthma.