Environmental exposures associated with early childhood recurrent wheezing in the mother and child in the environment birth cohort: a time-to-event study.

BACKGROUND: Antenatal factors and environmental exposures contribute to recurrent wheezing in early childhood. AIM: To identify antenatal and environmental factors associated with recurrent wheezing in children from birth to 48 months in the mother and child in the environment cohort, using time-to-event analysis. METHOD: Maternal interviews were administered during pregnancy and postnatally and children were followed up from birth to 48 months (May 2013-October 2019). Hybrid land-use regression and dispersion modelling described residential antenatal exposure to nitrogen dioxide (NO2) and particulate matter of 2.5 µm diameter (PM2.5). Wheezing status was assessed by a clinician. The Kaplan-Meier hazard function and Cox-proportional hazard models provided estimates of risk, adjusting for exposure to environmental tobacco smoke (ETS), maternal smoking, biomass fuel use and indoor environmental factors. RESULTS: Among 520 mother-child pairs, 85 (16%) children, had a single wheeze episode and 57 (11%) had recurrent wheeze. Time to recurrent wheeze (42.9 months) and single wheeze (37.8 months) among children exposed to biomass cooking fuels was significantly shorter compared with children with mothers using electricity (45.9 and 38.9 months, respectively (p=0.03)). Children with mothers exposed to antenatal ETS were 3.8 times more likely to have had recurrent wheeze compared with those not exposed (adjusted HR 3.8, 95% CI 1.3 to 10.7). Mean birth month NO2 was significantly higher among the recurrent wheeze category compared with those without wheeze. NO2 and PM2.5 were associated with a 2%-4% adjusted increased wheezing risk. CONCLUSION: Control of exposure to ETS and biomass fuels in the antenatal period is likely to delay the onset of recurrent wheeze in children from birth to 48 months.

Bayesian modeling of quantiles of body mass index among under-five children in Ethiopia.

BACKGROUND: Body Mass Index (BMI) is a measurement of nutritional status, which is a vital pre-condition for good health. The prevalence of childhood malnutrition and the potential long-term health risks associated with obesity in Ethiopia have recently increased globally. The main objective of this study was to investigate the factors associated with the quantiles of under-five children's BMI in Ethiopia. METHODS: Data on 5,323 children, aged between 0-59 months from March 21, 2019, to June 28, 2019, were obtained from the Ethiopian Mini Demographic Health Survey (EMDHS, 2019), based on the standards set by the World Health Organization. The study used a Bayesian quantile regression model to investigate the association of factors with the quantiles of under-five children's body mass index. Markov Chain Monte Carlo (MCMC) with Gibbs sampling was used to estimate the country-specific marginal posterior distribution estimates of model parameters, using the Brq R package. RESULTS: Out of a total of 5323 children included in this study, 5.09% were underweight (less than 12.92 BMI), 10.05% were overweight (BMI: 17.06 - 18.27), and 5.02% were obese (greater than or equal to 18.27 BMI) children's. The result of the Bayesian quantile regression model, including marginal posterior credible intervals (CIs), showed that for the prediction of the 0.05 quantile of BMI, the current age of children [ ß = -0.007, 95% CI :(-0.01, -0.004)], the region Afar [ ß = - 0.32, 95% CI: (-0.57, -0.08)] and Somalia[ ß = -0.72, 95% CI: (-0.96, -0.49)] were negatively associated with body mass index while maternal age [ ß = 0.01, 95% CI: (0.005, 0.02)], mothers primary education [ ß = 0.19, 95% CI: (0.08, 0.29)], secondary and above [ ß = 0.44, 95% CI: (0.29, 0.58)], and family follows protestant [ ß = 0.22, 95% CI: (0.07, 0.37)] were positively associated with body mass index. In the prediction of the 0.95 (or 0.85?) quantile of BMI, in the upper quantile, still breastfeeding [ ß = -0.25, 95% CI: (-0.41, -0.10)], being female [ ß = -0.13, 95% CI: (-0.23, -0.03)] were negatively related while wealth index [ ß = 0.436, 95% CI: (0.25, 0.62)] was positively associated with under-five children's BMI. CONCLUSIONS: In conclusion, the research findings indicate that the percentage of lower and higher BMI for under-five children in Ethiopia is high. Factors such as the current age of children, sex of children, maternal age, religion of the family, region and wealth index were found to have a significant impact on the BMI of under-five children both at lower and upper quantile levels. Thus, these findings highlight the need for administrators and policymakers to devise and implement strategies aimed at enhancing the normal or healthy weight status among under-five children in Ethiopia.

The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model.

Background: Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity. Method: This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure. Result: Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it. Conclusion: Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Spatial patterns and predictors of unintended pregnancy among reproductive age women in Ethiopia.

INTRODUCTION: Unintended pregnancy is amajor sexual and reproductive health problem that imposes substantial health, economical and psychosocial costs to individuals and society as well as significant emotional distress to women, families, and society. The main aim of this study was to investigate the spatial distribution and predictors of unintended pregnancy in Ethiopian regions and administrative zones. METHODS: This study was conducted based on data from 2016 Ethiopian Demographic and Health Survey. The prevalence of unintended pregnancy across regions and or zones was assessed using spatial analysis, and the effect of different factors on unintended pregnancy in Ethiopia was investigated using a generalized linear mixed model with a multistage clustered sampling strategy. The crude and best linear unbiased predictor estimations of zones were integrated with the shape file data to demonstrate the performance of each zone on maps. RESULTS: The prevalence of unintended pregnancy for reproductive women in Ethiopia was29.49%. The highest rates of unintended pregnancy were recorded in the North Gondar zone of the Amhara region and the Jima zone in the Oromiya region. The mixed effects model revealed that age [AOR = 0.78, 95% CI, 0.62-0.97], residence [AOR = 2.62, 95%CI, 1.94, 7.27], marital status [AOR = 0.05, 95%CI, 0.01-0.38], women education [AOR = 1.34, 95%CI, 0.75-2.39], smoking cigarettes [AOR = 3.67, 95CI, 1.17-11.56], and poorer wealth index [AOR = 1.89, 95% CI, 1.51-2.31] were significantly associated with unintended pregnancy. CONCLUSION: In Ethiopia, unintended pregnancy is a public health issue, and prevention stratagem for unintended pregnancy among reproductive women need to be focused based on the identified predictors. The spatial distribution of unintended pregnancy varied greatly at zonal and regional levels in Ethiopia. Hence, we recommended that, creating awareness of sexual and reproductive health with special priority to the identified hotspot areas (Amhara, Oromiya and SNN regions) to reduce unintended pregnancy. Emphasis on fertility and contraceptive techniques should be given to couples by health professionals.

Household food insecurity levels in Ethiopia: quantile regression approach.

Introduction: Numerous natural and man-made factors have afflicted Ethiopia, and millions of people have experienced food insecurity. The current cut-points of the WFP food consumption score (FCS) have limitations in measuring the food insecurity level of different feeding patterns due to the diversified culture of the society. The aim of this study is to adapt the WFP food security score cut-points corrected for the different feeding cultures of the society using effect-driven quantile clustering. Method: The 2012, 2014, and 2016 Ethiopian socio-economic household-based panel data set with a sample size of 3,835 households and 42 variables were used. Longitudinal quantile regression with fixed individual-specific location-shift intercept of the free distribution covariance structure was adopted to identify major indicators that can cluster and level quantiles of the FCS. Result: Household food insecurity is reduced through time across the quintiles of food security score distribution, mainly in the upper quantiles. The leveling based on effect-driven quantile clustering brings 35.5 and 49 as the FCS cut-points corrected for cultural diversity. This corrected FCS brings wider interval for food insecure households with the same interval range for vulnerable households, where the WFP FCS cut-points under estimate it by 7 score. Education level, employment, fertilizer usage, farming type, agricultural package, infrastructure-related factors, and environmental factors are found to be the significant contributing factors to food security. On the other hand, the age of the head of the household, dependency ratio, shock, and no irrigation in households make significant contributions to food insecurity. Moreover, households living in rural areas and farming crops on small lands are comparatively vulnerable and food insecure. Conclusion: Measuring food insecurity in Ethiopia using the WFP FCS cut-off points underestimates households' food insecurity levels. Since the WFP FCS cut-points have universality and comparability limitations, there is a need for a universally accepted local threshold, corrected for local factors those resulted in different consumption patterns in the standardization of food security score. Accordingly, the quantile regression approach adjusts the WFP-FCS cut points by adjusting for local situations. Applying WFP cut-points will wrongly assign households on each level, so the proportion of households will be inflated for the security level and underestimated for the insecure level, and the influence of factors can also be wrongly recommended the food security score for the levels. The quantile clustering approach showed that cropping on a small land size would not bring about food security in Ethiopia. This favors the Ethiopian government initiative called integrated farming "ኩታ ገጠም እርሻ" which Ethiopia needs to develop and implement a system that fits and responds to this technology and infrastructure.

Spatio-temporal pattern of short birth interval and associated factors on women in Ethiopia: Using Ethiopian demographic and health surveys 2000-2016.

Background: A short birth interval is a critical factor that contributes to a large number of maternal and infant mortality in low- and middle-income countries. It is the major cause of maternal and child mortality in Ethiopia. This study aimed to explore the spatiotemporal distribution of short birth intervals in Ethiopia using data from four (2000, 2005, 2011, and 2016) consecutive demographic and health surveys. Methods: A total of 34,930 women were included in four consecutive Ethiopian Demographic and Health Surveys (EDHS). Thus, spatial autocorrelation, hotspot analysis, cluster analysis, and spatial interpolation were carried out for each survey separately to show the geographical and temporal pattern of at-risk areas for short birth intervals in Ethiopia. Finally, the highest proportion of short birth interval risk areas in each survey period was mapped. Geospatial analysis was conducted by using ArcGIS V.10.8 and R version 4.2. Results: The results of the study indicated that the overall proportion of short birth intervals of women in Ethiopia was highest in 2000 (47.5%), 2005 (46.4%), 2011 (44.7%), and the lowest in 2016 (44.0%). The values for Global Moran's I (MI = 0.177665 p = 0.0016, MI = 0.2024, p = 0.001, MI = 0.10023, p = 0.002, and MI = 0.764, p = 0.008) showed that the presence of significant short birth interval clustering in Ethiopian administrative zones in 2000, 2005, 2011, and 2016, respectively. The hotspot areas for short birth intervals were consistently observed in the zones in the Somali Region and the zones in the Harari Region for all the EDHS years. In addition, the survival status of the index child, residence, breastfeeding practice, religion, and the spatial variable (Si) were significantly associated with the short birth interval of women in all the EDHS years. Conclusion: Spatial distribution of short birth intervals differs across Ethiopian administrative zones. Survival status of the index child being dead, rural residential, and no breastfeeding practice are the risk factors for short birth intervals of women that increase the risk of a short birth interval among women in all the EDHS years. Therefore, the hotspot areas and indicators need interventions to decrease the short birth interval of women.

Impact of ambient air pollution exposure during pregnancy on adverse birth outcomes: generalized structural equation modeling approach.

BACKGROUND: Air pollution and several prenatal factors, such as socio-demographic, behavioural, physical activity and clinical factors influence adverse birth outcomes. The study aimed to investigate the impact of ambient air pollution exposure during pregnancy adjusting prenatal risk factors on adverse birth outcomes among pregnant women in MACE birth cohort. METHODS: Data for the study was obtained from the Mother and Child in the Environment (MACE) birth cohort study in Durban, South Africa from 2013 to 2017. Land use regression models were used to determine household level prenatal exposure to PM2.5, SO2 and NOx. Six hundred and fifty-six births of pregnant females were selected from public sector antenatal clinics in low socio-economic neighbourhoods. We employed a Generalised Structural Equation Model with a complementary log-log-link specification. RESULTS: After adjustment for potential prenatal factors, the results indicated that exposure to PM2.5 was found to have both significant direct and indirect effects on the risk of all adverse birth outcomes. Similarly, an increased level of maternal exposure to SO2 during pregnancy was associated with an increased probability of being small for gestational age. Moreover, preterm birth act a mediating role in the relationship of exposure to PM2.5, and SO2 with low birthweight and SGA. CONCLUSIONS: Prenatal exposure to PM2.5 and SO2 pollution adversely affected birth outcomes after controlling for other prenatal risk factors. This suggests that local government officials have a responsibility for better control of air pollution and health care providers need to advise pregnant females about the risks of air pollution during pregnancy.

Spatial pattern and predictors of malaria in Ethiopia: Application of auto logistics regression.

INTRODUCTION: Malaria is a severe health threat in the World, mainly in Africa. It is the major cause of health problems in which the risk of morbidity and mortality associated with malaria cases are characterized by spatial variations across the county. This study aimed to investigate the spatial patterns and predictors of malaria distribution in Ethiopia. METHODS: A weighted sample of 15,239 individuals with rapid diagnosis test obtained from the Central Statistical Agency and Ethiopia malaria indicator survey of 2015. Global Moran's I and Moran scatter plots were used in determining the distribution of malaria cases, whereas the local Moran's I statistic was used in identifying exposed areas. The auto logistics spatial binary regression model was used to investigate the predictors of malaria. RESULTS: The final auto logistics regression model was reported that male clients had a positive significant effect on malaria cases as compared to female clients [AOR = 2.401, 95% CI: (2.125-2.713) ]. The distribution of malaria across the regions was different. The highest incidence of malaria was found in Gambela [AOR = 52.55, 95%CI: (40.54-68.12)] followed by Beneshangul [AOR = 34.95, 95%CI: (27.159-44.963)]. Similarly, individuals in Amhara [AOR = 0.243, 95% CI:(0.195-0.303], Oromiya [AOR = 0.197, 955 CI: (0.158-0.244)], Dire Dawa [AOR = 0.064, 95%CI(0.049-0.082)], Addis Ababa[AOR = 0.057,95%CI:(0.044-0.075)], Somali[AOR = 0.077,95%CI:(0.059-0.097)], SNNPR[OR = 0.329, 95%CI: (0.261-0.413)] and Harari [AOR = 0.256, 95%CI:(0.201-0.325)] were less likely to had low incidence of malaria as compared with Tigray. Furthermore, for one meter increase in altitude, the odds of positive rapid diagnostic test (RDT) decreases by 1.6% [AOR = 0.984, 95% CI: (0.984-0.984)]. The use of a shared toilet facility was found as a protective factor for malaria in Ethiopia [AOR = 1.671, 95% CI: (1.504-1.854)]. The spatial autocorrelation variable changes the constant from AOR = 0.471 for logistic regression to AOR = 0.164 for auto logistics regression. CONCLUSIONS: This study found that the incidence of malaria in Ethiopia had a spatial pattern which is associated with socio-economic, demographic, and geographic risk factors. Spatial clustering of malaria cases had occurred in all regions, and the risk of clustering was different across the regions. The risk of malaria was found to be higher for those who live in soil floor-type houses as compared to those who lived in cement or ceramics floor type. Similarly, households with thatched, metal and thin, and other roof-type houses have a higher risk of malaria than ceramics tiles roof houses. Moreover, using a protected anti-mosquito net was reducing the risk of malaria incidence.

Survival analysis of women breast cancer patients in Northwest Amhara, Ethiopia.

Introduction: Breast cancer, the most common cause of cancer death and the most frequently diagnosed cancer among women worldwide, ranks as the second cause of death next to lung cancer. Thus, the main objective was to assess the factors that affect the survival time of breast cancer patients using the shared frailty model. Methods: A retrospective study design was used to collect relevant data on the survival time of breast cancer patients from the medical charts of 322 breast cancer patients under follow-up at the Felege Hiwot Comprehensive Specialized Hospital (FHCSH). The data were explored using the Cox proportional hazard model, the accelerated failure time model, and shared frailty models. The model comparison was done using AIC and BIC. As a result, the Weibull gamma shared frailty model had a minimum AIC and BIC value. Result: From a total of 322 patients, about 95 (29.5%) died and 227 (70.5%) were censored. The overall mean and median estimated survival times of breast cancer patients under study were 43.7 and 45 months, respectively. The unobserved heterogeneity in the population of clusters (residence) as estimated by the Weibull-gamma shared frailty model was 0.002 (p-value = 0.000), indicating the presence of residential variation in the survival time of breast cancer patients. The estimated hazard rate of patients who had not had recurrent breast cancer was 0.724 (95% CI: 0.571, 0.917) times the estimated hazard rate of patients who had had recurrent breast cancer. Conclusion: The prevalence of breast cancer was considerably high. Under this investigation, older patients, patients in stages III and IV, anemic and diabetes patients, patients who took only chemotherapy treatment, metastasized patients, patients with an AB blood type, patients with a positive breast cancer family history, and patients whose cancer was recurrent had high death rates. Patient characteristics such as age, stage, complications, treatment, metastasis, blood type, family history, and recurrence were significant factors associated with the survival time of women with breast cancer.

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

BACKGROUND: Noncommunicable diseases (NCDs) like cancer are posing a challenge in the health system especially in low- and middle-income countries (LMICs). In South Africa, cancer is under-reported due to the lack of a comprehensive cancer surveillance system. The limited knowledge on the extent of cancer burden has led to inaccurate allocation of public health resources. The aim of this study was to describe cancer incidence and spatial distribution of cancer cases seen at 3 main public oncology facilities in KwaZulu-Natal. METHODS: In this retrospective study, cases of cancer observed from year 2015 to 2017 were extracted from medical records. The crude incidence rate was estimated for the total cancer cases and for different type of cancer reported over that period. Age-standardised incidence rates (ASR) per 100 000 was calculated per year using age groups and sex according to the district population data of KwaZulu-Natal. The comparisons of cancer diagnosed incidences were made between 11 districts using the ASR. Choropleth spatial maps and Moran's Index were used to assess the ASR cancer spatial distribution along with geographical patterns among the districts. One sample chi-square test was used to assess the significant increase/decrease over time. RESULTS: The study lost numerous cases due to incompleteness. A total of 4909 new cases were diagnosed with cancer during 2015 to 2017, 62% of which were female. Both uMgungundlovu and eThekwini districts had the highest ASR among district municipalities of KwaZulu-Natal for both male and female (83.6 per 100 000 per men year for men, 158.2 per 100 000 women per year, and 60.1 per 100 000 men per year and 96.9 per 100 000 women per year, respectively). Random distribution of reported cancer cases in KwaZulu-Natal was observed with a high concentration being in and around 2 metropolitan districts. Spatial variation showed a significant difference from year to year between the districts with the random spatial distribution. Overall, there was a significant decline of cancer incidences observed from 2015 to 2017 (P < .05) in the province. CONCLUSION: The overall cancer incidence in the study shows that female cancers (breast and cervical) are still on the rise and still need to be given priority as they were most prevalent in KwaZulu-Natal. Spatial analysis (choropleth maps) was used to show a pattern of higher concentration of cancer incidence in the north-western parts of the province.

Effects of prenatal exposure factors on birth outcomes through mediation of favorable fetal growth conditions using structural equation modeling.

BACKGROUND: Birth weight, birth length, and gestational age are major indicators of newborn health. Several prenatal exposure factors influence the fetal environment. The aim of the study was to investigate the effect of prenatal exposure factors, including socio-demographic, behavioural, dietary, physical activity, clinical and environmental on birth outcomes through the mediation of Favourable Fetal Growth Conditions (FFGC). METHODS: Data was obtained from six hundred and fifty-six Mother and Child in the Environment birth cohort study in Durban, South Africa from 2013 to 2017. We adopted structural equation models which evaluate the direct and indirect effects by allowing multiple simultaneous equations to incorporate confounding and mediation. RESULTS: A significant direct and indirect effect of FFGC on newborn weight, length, and gestational age was seen. Gestational weight gain and maternal body mass index in the first trimester exerted a mediation effect between maternal behavioural risk factors and FFGC. Similarly, the level of physical activity during pregnancy was associated with decreased gestational weight gain. The effects of maternal characteristics on newborn weight, length, and gestational age were largely indirect, operating through FFGC as a latent variable. CONCLUSIONS: Gestational weight gain and maternal pre-gestational BMI were observed to mediate the association between prenatal behavioural risk factors and favourable fetal growth conditions. TRIAL REGISTRATION: Retrospectively registered from 01 March 2013.

Maternal demographic and antenatal factors, low birth weight and preterm birth: findings from the mother and child in the environment (MACE) birth cohort, Durban, South Africa.

BACKGROUND: Low birthweight (LBW) and preterm birth (PB) remain the leading cause of morbidity and mortality in neonates worldwide. The aim of this study was to identify maternal demographic and antenatal factors associated with PB and LBW among low socio-economic communities. METHODS: Pregnant women (n = 1099) were recruited in the first trimester into the Mother and Child in the Environment (MACE) birth cohort in Durban, South Africa. Maternal factors such as demographic information, health status, residential area, occupational, personal and environmental smoking and biomass fuel use were obtained through standardised interviews, while clinical status was obtained in each trimester and antenatal information on HIV status and treatment, syphilis and conditions such as pregnancy induced hypertension, diabetes etc. was extracted from the antenatal assessments. Key outcomes of interest were preterm birth and low birthweight. The latter data was obtained from the clinical assessments performed by midwives at delivery. Logistic regression models identified factors associated with PB and LBW. RESULTS: Of the 760 live births, 16.4 and 13.5% were preterm and LBW, respectively. Mothers who delivered by caesarean section had an increased odds of having LBW babies (Adjusted odds ratio (AOR): 1.7; 95% CI: 1.1-2.7) and PB (AOR: 1.7, 95% CI: 1.1-2.7) versus normal vaginal deliveries. Mothers > 30 years (AOR: 1.8, 95% CI: 1.1-2.9) and current smokers (AOR: 2.7, 95% CI: 1.3-5.8) had an increased odds of having PB babies. Compared to younger mothers and non-smokers respectively. An effect of PB and LBW was seen among mothers with high BMI (25.0-29.9 kg/m2) (PB: AOR: 0.5, 95% CI: 0.3-0.9 and LBW: AOR: 0.5, 0.5, CI: 0.3-0.8), and obese BMI (> 30 kg/m2) (PB: AOR: 0.5, 95% CI: 0.3-0.9 and LBW: AOR: 0.4, CI: 0.2-0.7). Maternal HIV (PB AOR: 1.4 and LBW AOR: 1.2) and history of sexually transmitted infections (PB AOR: 2.7 and LBW AOR: 4.2) were not statistically significant. CONCLUSION: Maternal age, cigarette smoking and caesarean delivery were associated with LBW and PB. Findings highlight the need of maternal health interventions to improve new-born health outcomes.

The differential effect of maternal dietary patterns on quantiles of Birthweight.

BACKGROUND: Maternal dietary habits during pregnancy are considered essential for development and growth of the fetus as well as maternal health. It has an effect on the birthweight of infants. However, little is known about the effect of dietary patterns on birthweight in urban South Africa. This study aimed to investigate differential effect of dietary patterns of pregnant women on quantiles of birthweight. METHODS: Data for the study were obtained from a Mother and Child in the Environment birth cohort study in Durban South Africa. Quantile regression was used to investigate the effect of maternal dietary patterns on quantiles of birthweight. Data collection was conducted during the period of 2013 to 2017 in Durban South Africa. Using factor analysis, eight dietary groups were identified from 687 pregnant women in the cohort. Quantile regression analysis was employed to identify the differential effects of the seven dietary groups and demographic factors on the birthweight. RESULTS: The quantile regression estimates at the 50th quantile and the ordinary regression estimates painted the same picture about the conditional mean effect of covariates on the birthweight. But unlike the quantile regression the ordinary regression fails to give insights about the covariates effect disparities at the low and/or upper birthweight quantiles. All the dietary groups show a significant differential effect at different birthweight quantiles. For instance, increased frequency of protein rich foods intake was associated with reduction in birthweight at lower and upper quantiles; increased frequency of junk foods intake has a slight increase in birthweight at the lower quantiles but significantly higher increase at the 95th quantile (p < 0.001); increase in consuming vegetable rich foods, reduced birthweight at 95th quantile (p < 0.001). The results further showed that employment (p = 0.006) and family size (p = 0.002) had differential effects across different birthweight quantiles. CONCLUSIONS: Both maternal undernutrition and overnutrition of protein rich foods, junk foods, snack and energy foods and vegetable rich foods have shown a substantial varying effects on those infants with birthweights in the lower and upper birthweight quantiles.

Exploratory Data Analysis of Adverse Birth Outcomes and Exposure to Oxides of Nitrogen Using Interactive Parallel Coordinates Plot Technique.

We propose that a parallel coordinates plot can be used to study multidimensional data particularly to explore discovery of patterns across the variables. This can assist researchers from the health sciences to visualize their cohort data with interactive data analysis. The study used data from Mother and Child in the Environment birth cohort in Durban, South Africa for the period 2013 to 2017 retrospectively registered. In this paper, we demonstrate that the exploration of multidimensional data with parallel coordinates plot and use of brushing using different colours assists with the identification of relationships and patterns. Parallel coordinates plot visualization facilitates the researcher's skills to find trends, identify outliers and perform quality checks in large multivariate data. We have identified trends in the data that provide directions for further research, and illustrated thereby the potential of parallel coordinates plot to explore patterns and relationships of prenatal oxides of nitrogen exposure with multidimensional birth outcomes. The study recognized the co-occurrence of adverse birth outcomes among infants and these infants had mothers with moderate to high level of NOx exposure during pregnancy. Brushing using different colours facilitated the detection of patterns of relationships to perform basic and advanced statistical model-based analysis.

The spatial modification of the non-linear effects of ambient oxides of nitrogen during pregnancy on birthweight in a South African birth cohort.

Birthweight is strongly associated with infant mortality and is a major determinant of infant survival. Several factors such as maternal, environmental, clinical, and social factors influence birthweight, and these vary geographically, including across low, middle, and economically advanced countries. The aim of the study was to investigate the geographical modification of the effect of oxides of nitrogen exposure on birthweight adjusted for clinical and socio-demographic factors. Data for the study was obtained from the Mother and Child in the Environment birth cohort study in Durban, South Africa. Pregnant females were selected from public sector antenatal clinics in low socioeconomic neighborhoods. Land use regression models were used to determine household level antenatal exposure to oxides of nitrogen (NOx). Six hundred and seventy-seven births were analysed, using the geoadditive model with Gaussian distribution and identity link function. The newborns in the cohort had a mean birthweight of 3106.5 g (standard deviation (SD): 538.2 g and the maternal mean age was 26.1 years (SD: 5.7). A spatially modified NOx exposure-related effect on birthweight was found across two geographic regions in Durban. Prenatal exposure to NOx was also found to have a non-linear effect on the birthweight of infants. The study suggested that incorporating spatial variability is important to understand and design appropriate policies to reduce air pollution in order to prevent risks associated with birthweight.

Modeling Differential Effects of Maternal Dietary Patterns across Severity Levels of Preterm Birth Using a Partial Proportional Odds Model.

Preterm birth is a common cause of death worldwide of children under the age of five years. This condition is linked with short and long term neonatal morbidity and mortality. Maternal nutrition during pregnancy has a profound effect on fetal growth and development and subsequently also on the incidence of preterm birth. The aim of this study was to assess the differential effect of dietary patterns of pregnant women across ordered levels of preterm birth. Dietary assessments were performed using a food frequency questionnaire, presented to 687 pregnant women, in the "Mother and Child in the Environment" birth cohort during the period of 2013 to 2017. Each pregnancy resulted in a live birth. Eight dietary patterns were extracted, using exploratory factor analysis. The partial proportional odds model was employed to model severity levels of preterm birth. The partial proportional odds model has been recognized to be a flexible approach since it allows the effect of predictor variables to vary across categories of the ordinal response variable of interest. Women with increased consumption of vegetable-rich foods showed a reduced risk of very to moderately preterm birth incidence (AOR = 0.73, 95% CI = (0.531, 0.981), p = 0.036). Lower odds of very/moderately preterm birth compared to late preterm or term birth were observed for women following "nuts and rice foods" dietary pattern (AOR = 0.25, 95% CI = (0.099, 0.621), p = 0.003). High dietary consumption of starch foods dietary pattern (AOR = 2.09, 95% CI = (1.158, 3.769), p = 0.014) was associated with the most severe level of preterm birth outcome incidence, i.e. very/moderately preterm birth. The partial proportional odds modeling allowed the description of the effect of maternal dietary patterns across the different severity levels of preterm birth.