Study area
The study was conducted in Tembisa and Kempton Park areas, which fall under the EMM. Tembisa is the second largest township in Gauteng Province, with both formal and informal housing, being home mainly to people belonging to Black/African ethnic groups. The main air polluting sources in the area includes, amongst others, residential fuel burning (particularly coal), industrial and commercial fuel burning (coal-fired boilers in close proximity to residential areas) and vehicular exhaust emissions (both petrol and diesel) [19]. Kempton Park is a suburban area surrounded by industry and arterial roads connecting Gauteng Province. The OR Tambo International Airport, which is Africa’s busiest airport, is also located nearby. Vehicular exhaust emissions (both petrol and diesel), industrial and commercial fuel burning (coal-fired boilers in close proximity to residential areas), OR Tambo International Airport (contributing a small fraction of low level, concentrated NO2) and large industries associated with various stack, vent and fugitive emissions were identified as significantly contributing to air pollution [19]. The (EMM) where the two areas are located falls under the Highveld Region, which was declared an air pollution priority area in the country, due to poor air quality, which is still the worst to date [20].
Study design, population and sample selection
A cross-sectional epidemiological study was conducted between February and June 2012, following the International Study of Asthma and Allergies in Childhood (ISAAC) Phase I protocol [21]. The ISAAC was designed as a multicentre-study to investigate the epidemiology of asthma, rhinitis and atopic dermatitis amongst children using standardised definitions, allowing comparisons worldwide [21]. A list of all schools (primary and secondary) in EMM was provided by the Gauteng Department of Education. All primary schools were excluded and 16 high schools were randomly selected from the list of high schools. Each school was contacted and requested to participate in the study. Following approval by the principal and governing body in each school, all eligible children between the ages of 13 and 14 years and in Grade 8 were requested to participate. The 13 to 14 year age group was chosen because it is the age most adolescents go to school regularly, making data collection easier. Each school was requested to make available a copy of class lists. An appointment was scheduled with the school to deliver the consent forms for the children two weeks prior to the study and they were requested to return them within three days. The study population consisted of 3764, children based on the numbers given by each school prior to data collection. Data were collected using the English version of ISAAC written questionnaires. The questionnaires were completed by the children in the classroom under the supervision of the data collectors, who were specifically trained and briefed to avoid explanations which could interfere with the participant’s answers.
Health outcomes
In this study we estimated health outcomes on the basis of positive answers from the written ISAAC questionnaire for 13 to 14 years old. Answers to written questions were self-reported by children. Questions on symptoms relating to rhinitis were as follows:
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1.
Rhinitis ever: Have you ever had a problem with sneezing or runny or blocked nose, when you DID NOT have a cold or flu? (Yes/No)
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2.
Current rhinitis: In the past 12 months, have you had a problem with sneezing or a runny or blocked nose, when you DID NOT have a cold or the flu? (Yes/No)
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3.
Current rhinoconjunctivitis: In the past 12 months, has this nose problem been accompanied by itchy-watery eyes? (Yes/No)
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4.
In which of the past 12 months, has this nose problem been accompanied by itchy-watery eyes? (Month names listed).
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5.
In the past 12 months, how much did this nose problem interfere with your daily activities? (Not at all, a little, a moderate amount, a lot)
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6.
Hayfever: Have you ever had hayfever? (Yes/No)
The main independent variables
Information regarding exposure to traffic-related pollution was obtained through the following questions: how often do tucks pass near your home on weekdays? (Never, seldom, frequently through the day, almost all day).
Confounders
A priori selection of the following confounding was done: sex (male/female), being born in Tembisa/Kempton Park the area (yes/no), type of house (brick, mud, corrugated iron, combination), vigorous physical activity (never/occasionally/1–2 times per week/, ≥ 3 times per week); How do you usually get to school? walk, taxi/bus, motorcar, combination of motorcar/taxi or train; hours watching television per day (<1 h/1 h but <3 h/ 3 h but <5 h /≥5 h) in 24 h; ETS exposure at home in the past 30 days (yes/no), ETS exposure at school in the past 30 days (yes/no), tobacco smoking by participant (yes/no), mother/father smoking tobacco (yes/no), any other person smoking at home other than participant (yes/no). Children were asked to select the most frequently used energy source at home; they had to select one type of energy source: for cooking at home (electricity, gas, paraffin, open fires) and for heating (electricity, gas, paraffin, open fires). Other variables, which were included in the questionnaire but not selected as confounders and were only reported in the descriptive analysis, were: period lived in the residential area (<6 months/ 6 to 12 months/ 1 to 2 years/ ≥3 years), the variables.
Data management and statistical analysis
The data were entered into a database set up in EpiInfo V3.5.3. Stata Version 12 was applied for the data analysis. Prevalence rates for the health outcomes and proportion on risk factors under investigation were calculated by dividing the number of participants who responded affirmatively to a particular question by the number of questionnaires completed. Observations marked as “do not know”, “not stated” or “other responses” were set as missing. This resulted in each question having a slightly different sample size. Crude and adjusted odds ratios (OR) and 95 % confidence intervals (CI) were calculated with multilevel logistic regression analysis (MLRA) with random effect to estimate the likelihood of having rhinitis ever, current rhinitis, rhinoconjunctivitis and hayfever health outcomes given the presence of a potential risk factor. The multilevel data included sixteen schools nested within two districts (level 1). Confounding variables were added in a stepwise manner, starting with the most significant from the univariate analysis. Each time a new potential confounder was added to the model, if the effect estimate between the exposure of interest and respiratory outcome already in the models changed by more than 5 %, the additional variable was retained in the final multiple MLRA, otherwise the variable was removed and a different one was added [22]. This resulted in the final models having slightly different confounders. The most parsimonious multiple MLRA models were reported, i.e., those with variables having a p-value < 0.05 [22].
Ethical considerations
The Ethics and Research Committee of the Faculty of Health Sciences, University of Pretoria approved the study (Ethics Number: S121/2011). The Gauteng Department of Education, Ekurhuleni North District, school principals and governing bodies were approached and gave approval and cooperation for the study. Parents of participants were sent a letter explaining the details and nature of the study and gave consent for the children to participate in the study. All information was kept confidential.