Model development including interactions with multiple imputed data

Abstract Background Multiple imputation is a reliable tool to deal with missing data and is becoming increasingly popular in biostatistics. However, building a model with interactions that are not specified a priori, in the presence of missing data, presents a challenge. On the one hand, the interactions are needed to impute the data, while on the other hand, the data is needed to identify the interactions. The objective of this study was to present a way in which this challenge can be addressed. Methods This paper investigates two strategies in which model development with interactions is achieved using a single data set generated from the Expectation Maximization (EM) algorithm. Imputation using both the fully conditional specification approach and the multivariate normal approach is carried out and results are compared. The strategies are illustrated with data from a study of ambient pollution and childhood asthma in Durban, South Africa. Results The different approaches to model building and imputation yielded similar results despite the data being mainly categorical. Both strategies investigated for building the model using the multivariate normal imputed data resulted in the identical set of variables and interactions being identified; while models built using data imputed by fully conditional specification were marginally different for the two strategies. It was found that, for both imputation approaches, model building with backward elimination applied to the initial EM data set was easier to implement, and produced good results, compared to those from a complete case analysis. Conclusions Developing a predictive model including interactions with data that suffers from missingness is easily done by identifying significant interactions and then applying backward elimination to a single data set imputed from the EM algorithm. It is hoped that this idea can be further developed and, by addressing this practical dilemma, there will be increased adoption of multiple imputation in medical research when data suffers from missingness.http://deepblue.lib.umich.edu/bitstream/2027.42/110125/1/12874_2014_Article_1145.pd

Harbor and intra-city drivers of air pollution: findings from a land use regression model, Durban, South Africa

Multiple land use regression models (LUR) were developed for different air pollutants to characterize exposure, in the Durban metropolitan area, South Africa. Based on the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology, concentrations of particulate matter (PM; 10; and PM; 2.5; ), sulphur dioxide (SO; 2; ), and nitrogen dioxide (NO; 2; ) were measured over a 1-year period, at 41 sites, with Ogawa Badges and 21 sites with PM Monitors. Sampling was undertaken in two regions of the city of Durban, South Africa, one with high levels of heavy industry as well as a harbor, and the other small-scale business activity. Air pollution concentrations showed a clear seasonal trend with higher concentrations being measured during winter (25.8, 4.2, 50.4, and 20.9 µg/m; 3; for NO; 2; , SO; 2; , PM; 10; , and PM; 2.5; , respectively) as compared to summer (10.5, 2.8, 20.5, and 8.5 µg/m; 3; for NO; 2; , SO; 2; , PM; 10; , and PM; 2.5; , respectively). Furthermore, higher levels of NO; 2; and SO; 2; were measured in south Durban as compared to north Durban as these are industrial related pollutants, while higher levels of PM were measured in north Durban as compared to south Durban and can be attributed to either traffic or domestic fuel burning. The LUR NO; 2; models for annual, summer, and winter explained 56%, 41%, and 63% of the variance with elevation, traffic, population, and Harbor being identified as important predictors. The SO; 2; models were less robust with lower R; 2; annual (37%), summer (46%), and winter (46%) with industrial and traffic variables being important predictors. The R; 2; for PM; 10; models ranged from 52% to 80% while for PM; 2.5; models this range was 61-76% with traffic, elevation, population, and urban land use type emerging as predictor variables. While these results demonstrate the influence of industrial and traffic emissions on air pollution concentrations, our study highlighted the importance of a Harbor variable, which may serve as a proxy for NO; 2; concentrations suggesting the presence of not only ship emissions, but also other sources such as heavy duty motor vehicles associated with the port activities

Lagged acute respiratory outcomes among children related to ambient pollutant exposure in a high exposure setting in South Africa

BACKGROUND : Acute ambient air pollution impacts on the respiratory health of children may be lagged across time. We determined the short-term lagged effects of particulate matter (PM2.5), sulphur dioxide (SO2), and oxides of nitrogen (NOx) on the respiratory health of children living in low-income communities. METHODS : A school-based study was conducted using a repeated measures design, across summer and winter, in four schools in each of four suburbs in the Vaal Triangle, South Africa. Data for PM2.5, NOx, and SO2 were obtained from monitoring stations within close proximity of the schools. Over 10 school days in each phase, grade 4 children completed a symptoms log and lung function tests. Parents completed a child respiratory questionnaire. Generalized estimation equations models adjusted for covariates of interest in relation to lung function outcomes and air pollutants including lag effects of 1–5 days. RESULTS : Daily PM2.5, NOx, and SO2 median concentration levels were frequently higher than international standards. Among the 280 child participants (mean age 9 years), the prevalence of symptoms based on probable asthma was 9.6%. There was a consistent increased pollutant-related risk for respiratory symptoms, except for NOx and shortness of breath. Lung function, associated with pollutant fluctuations across the different lags, was most pronounced for peak expiratory flow rate (PEFR) for PM2.5 and SO2. A preceding 5-day average SO2 exposure had the largest loss (7.5 L/minute) in PEFR. CONCLUSIONS : Lagged declines in daily lung function and increased odds of having respiratory symptoms were related to increases in PM2.5 and SO2 among a school-based sample of children.The South African National Department of Forestry, Fisheries and the Environment.https://journals.lww.com/environepidem/Pages/default.aspxam2023Geography, Geoinformatics and Meteorolog

Radiographic outcomes among South African coal miners

Objectives : This study, the first to document the prevalence of pneumoconiosis among a living South African coal mining cohort, describes dose–response relationships between coal workers’ pneumoconiosis and respirable dust exposure, and relationships between pneumoconiosis and both lung function deterioration and respiratory symptoms. Methods : A total of 684 current miners and 188 ex-miners from three bituminous-coal mines in Mpumalanga, South Africa, was studied. Chest radiographs were read according to the International Labour Organization (ILO) classification by two experienced readers, one an accredited National Institute for Occupational Safety and Health (NIOSH) “B” reader. Interviews were conducted to assess symptoms, work histories (also obtained from company records), smoking, and other risk factors. Spirometry was performed by trained technicians. Cumulative respirable dust exposure (CDE) estimates were constructed from historical company-collected sampling and researcher-collected personal dust measurements. κ-Statistics compared the radiographic outcomes predicted by the two readers. An average profusion score was used in the analysis for the outcomes of interest. Because of possible confounding by employment status, most analyses were stratified on current and ex-miner status. Results : The overall prevalence of pneumoconiosis was low (2%–4%). The degree of agreement between the two readers for profusion was moderate to high (κ=0.58). A significant association ( P <0.001) and trend ( P <0.001) was seen for pneumoconiosis with increasing categories of CDE among current miners only. A significant ( P <0.0001) additional 58 mg-years/m 3 CDE was seen among those with pneumoconiosis compared to those without. CDE contributed to a statistically significant 0.19% and 0.11% greater decline in the percent predicted 1-second forced expiration volume (FEV 1 ) and forced vital capacity (FVC), respectively, among current miners with pneumoconiosis than among those without. Logistic regression models showed no significant relationships between pneumoconiosis and symptoms. Conclusions : The overall prevalence of pneumoconiosis, although significantly associated with CDE, was low. The presence of pneumoconiosis is associated with meaningful health effects, including deterioration in lung function. Intervention measures that control exposure are indicated, to reduce these functional effects.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47414/1/420_2004_Article_532.pd

Exposure-response relationship of residential dampness and mold damage with severe lower respiratory tract infections among under-five children in Nigeria

Background: Previous epidemiological studies demonstrated an increased risk of respiratory health effects in children and adults exposed to dampness or mold. This study investigated associations of quantitative indicators of indoor dampness and mold exposure with severe lower respiratory tract infections (LRTI) among children aged 1-59 months in Ibadan, Nigeria. Methods: In-home visits were conducted among 178 children hospitalized with LRTI matched by age (±3 months), sex, and geographical location with 180 community-based children without LRTI. Trained study staff evaluated the indoor environment using a standardized home walkthrough checklist and measured visible dampness and mold damage. Damp-moldy Index (DMI) was also estimated to quantify the level of exposure. Exposure-response relationships of dampness and mold exposure with severe LRTI were assessed using multivariable restricted cubic spline regression models adjusting for relevant child, housing, and environmental characteristics. Results: Severe LRTI cases were more often male than female (61.8%), and the overall mean (SD) age was 7.3 (1.35) months. Children exposed to dampness <0.3 m2 (odds ratio [OR] = 2.11; 95% confidence interval [CI] = 1.05, 4.36), and between 0.3 and 1.0 m2 (OR = 2.34; 95% CI = 1.01, 7.32), had a higher odds of severe LRTI compared with children not exposed to dampness. The restricted cubic spline showed a linear exposure-response association between severe LRTI and residential dampness (P < 0.001) but a nonlinear relationship with DMI (P = 0.01). Conclusions: Residential dampness and DMI were exposure-dependently associated with higher odds of severe LRTI among under-five children. If observed relationships were causal, public health intervention strategies targeted at reducing residential dampness are critically important to mitigate the burden of severe LRTI among under-five children

Indoor bacterial and fungal aerosols as predictors of lower respiratory tract infections among under-five children in Ibadan, Nigeria

Background: This study aimed to investigate the association between exposure to diverse indoor microbial aerosols and lower respiratory tract infections (LRTI) among children aged 1 to 59 months in Ibadan, Nigeria. Methods: One hundred and seventy-eight (178) hospital-based LRTI cases among under-five children were matched for age (± 3 months), sex and geographical location with 180 community-based controls (under-five children without LRTI). Following consent from caregivers of eligible participants, a child’s health questionnaire, clinical proforma and standardized home-walkthrough checklist were used to collect data. Participant homes were visited and sampled for indoor microbial exposures using active sampling approach by Anderson sampler. Indoor microbial count (IMC), total bacterial count (TBC), and total fungal count (TFC) were estimated and dichotomized into high (> median) and low (≤ median) exposures. Alpha diversity measures including richness (R), Shannon (H) and Simpson (D) indices were also estimated. Conditional logistic regression models were used to test association between exposure to indoor microbial aerosols and LRTI risk among under-five children. Results: Significantly higher bacterial and fungal diversities were found in homes of cases (R = 3.00; H = 1.04; D = 2.67 and R = 2.56; H = 0.82; D = 2.33) than homes of controls (R = 2.00; H = 0.64; D = 1.80 and R = 1.89; H = 0.55; D = 1.88) p < 0.001, respectively. In the multivariate models, higher categories of exposure to IMC (aOR = 2.67, 95% CI 1.44–4.97), TBC (aOR = 2.51, 95% CI 1.36–4.65), TFC (aOR = 2.75, 95% CI 1.54–4.89), bacterial diversity (aOR = 1.87, 95% CI 1.08–3.24) and fungal diversity (aOR = 3.00, 95% CI 1.55–5.79) were independently associated with LRTI risk among under-five children. Conclusions: This study suggests an increased risk of LRTI when children under the age of five years are exposed to high levels of indoor microbial aerosols

Accepted: 2011-10-04.) © SAJEI South Afr

Original Research: GGSTM1, GSTP1 and NQO1 polymorphisms and susceptibility to asthma among South African children Gluthathione-S-transferase (GSTM1 and GSTP1) and nicotinamide quinone oxidoreductase (NQO1) genes play an important role in cellular protection against oxidative stress, which has been linked to asthma pathogenesis. We investigated whether common, functional polymorphisms in GSTM1, GSTP1, and NQO1 influence susceptibility to asthma among schoolchildren in South Africa. Genomic deoxyribonucleic acid (DNA) was extracted from 317 primary schoolchildren, aged 9-11 years, from the urban, underprivileged socio-economic communities of Durban. GSTM1 (null vs. present genotype), GSTP1 (Ile105Val; AA →AG+GG) and the NQO1 (Pro/Ser; CC →CT/TT) genotypes were determined using polymerase chain reaction. Among the children, 30% were GSTM1 null, 65% carried the G allele for GSTP1, and 36% carried the C allele for NQO1.There was a high prevalence of asthma of any severity (46.1%), with 20.4% reporting persistent asthma. The GSTP1 AG+GG polymorphic genotype was significantly associated with persistent asthma (adjusted OR = 3.98; CI = 1.39, 11.36, p-value = 0.01). Neither the GSTM1, nor the NQO1, genotype was a significant predictor of persistent asthma. Therefore, the GSTP1 A/G variant may modulate the risk of persistent asthma among our sample

Prevalence of asthma and respiratory symptoms in south-central Durban, South Africa

The prevalence of asthma and respiratory symptoms in south-central Durban, one of the most heavily polluted areas of South Africa, has been determined using a cross-sectional survey of 213 households in the communities of Merewent (97% Indians) and Austerville (98% coloreds). The study population consisted of 367 children (less than 17 years old) and 693 adults. About 10% of the children and 12% of adults reported doctor diagnosed asthma. The self-reported prevalence rates for wheezing (37–40%) and attacks of shortness of breath with wheeze (16–28%) were much higher than that for doctor diagnosed asthma and common co-occurrence of the three symptoms is found. The prevalence rates for other respiratory symptoms include 33–35% for chronic cough, 31–32% for chronic phlegm, 44–50% for frequent blocked-runny nose, and 16–27% for sinusitis. Factors in the community that were associated with asthma, wheeze and shortness of breath with wheeze among the adult population included cigarette smoking, use of insecticides (coils and pump spray) and home ownership. An association between asthma among children and a number of household risk factors including dampness, carpet, pets or use of pesticides was not apparent in the community. Asthma prevalence was strongly correlated with missing of school by children (odds ratio (OR): 44; 95% confidence interval (CI): 13–141). The study serves to draw attention to a growing but neglected public health problem in urban areas of Africa.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42660/1/10654_2004_Article_240241.pd