Project description:BackgroundEthiopia has low malaria prevalence compared to most other malaria-endemic countries in Africa. However, malaria is still a major public health problem in the country. The binary logistic regression model has been widely used to analyse malaria indicator survey (MIS) data. However, most MIS have a hierarchical structure which may result in dependent data. Since this model assumes that conditional on the covariates the malaria statuses of individuals are independent, it ignores potential intra-cluster correlation among observations within a cluster and may generate biased analysis results and conclusions. Therefore, the aim of this study was to quantify the variation in the prevalence of malaria between sample enumeration areas (SEAs) or clusters, the effects of cluster characteristics on the prevalence of malaria using the intra-class correlation coefficient as well as to identify significant factors that affect the prevalence of malaria using the multilevel logistic regression modelling in three major regions of Ethiopia, namely Amhara, Oromia and Southern Nations, Nationalities and Peoples' (SNNP).MethodsDataset for three regional states extracted from the 2011 Ethiopian National Malaria Indicator Surveys (EMIS) national representative samples was used in this study. It contains 9272 sample individuals selected from these regions. Various multilevel models with random sample SEA effects were applied taking into account the survey design weights. These weights are scaled to address unequal probabilities of selection within clusters. The spatial clustering of malaria prevalence was assessed applying Getis-Ord statistic to best linear unbiased prediction values of model random effects.ResultsAbout 53.82 and 28.72 per cents of the sampled households in the study regions had no mosquito net and sprayed at least once within the last 12 months, respectively. The results of this study indicate that age, gender, household had mosquito nets, the dwelling has windows, source of drinking water, the two SEA-level variables, i.e. region and median altitude, were significantly related to the prevalence of malaria. After adjusting for these seven variables, about 45% of the residual variation in the prevalence of malaria in the study regions was due to systematic differences between SEAs, while the remaining 55% was due to unmeasured differences between persons or households. The estimated MOR, i.e. the unexplained SEA heterogeneity, was 4.784. This result suggests that there is high variation between SEAs in the prevalence of malaria. In addition, the 80% interval odds ratios (IORs) related to SEA-level variables contain one suggesting that the SEA variability is large in comparison with the effect of each of the variable.ConclusionsThe multilevel logistic regression with random effects model used in this paper identified five individual / household and two SEA-level risk factors of malaria infection. Therefore, the public health policy makers should pay attentions to those significant factors, such as improving the availability of pure drinking water. Further, the findings of spatial clustering provide information to health policymakers to plan geographically targeted interventions to control malaria transmission.

Project description:BackgroundAnemia is a major public health problem affecting more than half of children under the age of five globally. It has serious short- and long-term consequences including growth retardation, impaired motor and cognitive development, and increased morbidity and mortality. Despite anemia is the leading cause of child mortality in sub-Saharan Africa, there is limited evidence on the prevalence and determinants of anemia among under-five children in sub-Saharan Africa. Therefore, this study aimed to investigate the prevalence and determinants of severity levels of anemia among children aged 6-59 months in sub-Saharan Africa.MethodsThis study was based on the most recent Demographic and Health Survey (DHS) data of 32 sub-Saharan African countries. A total weighted sample of 135,619 children aged 6-59 months was included in the study. Considering the hierarchical nature of DHS data and the ordinal nature of anemia, a multilevel ordinal logistic regression model was applied. Proportional odds assumption was tested by Brant test and it was satisfied (p-value = 0.091). Besides, deviance was used for model comparison. Variables with a p-value ≤0.2 in the bivariable analysis were considered for the multivariable analysis. In the multivariable multilevel proportional odds model, the Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) were reported for potential determinant factors of severity levels of anemia.ResultsThe overall prevalence of anemia among children aged 6-59 months in sub-Saharan Africa was 64.1% [95% CI: 63.9%, 64.4%]. Of which, 26.2% were mildly anemic, 34.9% moderately anemic and 3% severely anemic. Poor maternal education, lower household wealth status, large family size, being male child, multiple births, having fever in the last two weeks, having diarrhea in the last two weeks, higher-order birth, maternal anemia, underweight, wasted, and stunted were significantly associated with increased odds of higher levels of anemia. Whereas, being 24-59 months age, taking drugs for an intestinal parasite, and born from mothers aged ≥ 20 years were significantly associated with lower odds of higher levels of anemia.ConclusionSeverity levels of anemia among children aged 6-59 months in sub-Saharan Africa was a major public health problem. Enhancing maternal education, providing drugs for an intestinal parasite, designing interventions that address maternal anemia, febrile illness, and diarrheal disease, and strengthening the economic status of the family are recommended to reduce childhood anemia. Furthermore, it is better to strengthen the strategies of early detection and management of stunted, wasted, and underweight children to decrease childhood anemia.

Project description:BackgroundMore than one out of every ten married women in the world, and one out of every five women in Africa, have unmet family planning needs. Despite this, studies concerning sub-Saharan Africa as well as the community-level factors that may influence the unmet need for family planning are scarce.ObjectiveTo assess factors associated with unmet need for family planning in sub-Saharan Africa.MethodsThis study used the nineteen demographic and health surveys (DHS) conducted between 2015 and 2020 in sub-Saharan Africa. A total weighted sample of 175, 820 women of reproductive age who were married during the survey was used for this study. To assess the factors associated with unmet need for family planning, I have employed a multilevel multinomial logistic regression model. After selecting variables using the bivariable analysis, a multivariable model was fitted. Finally, an adjusted relative risk ratio with its 95% Confidence Interval was reported and variables with a p-value less than 0.05 were declared to be significant predictors of unmet need for family planning.ResultThe overall prevalence of unmet need for family planning in sub-Saharan Africa was 23.70%, of which unmet need for spacing and limiting was 15.81% and 7.90% respectively. In the multivariable multilevel multinomial model, women's age, women's education, age at cohabitation, heard about family planning through media, parity, number of under-five children, and knowledge about modern contraceptive methods were among the individual-level factors that were associated with both the unmet need for spacing and limiting. Place of residence, community level of women illiteracy, and region were among the community-level factors that were associated with both unmet needs for spacing and limiting. Household size and visiting the health facility in the last 12 months were associated with unmet need for spacing only and husband education was associated with unmet need for limiting only.ConclusionUnmet need for family planning in sub-Saharan Africa was high. Both individual and community level factors were associated with both unmet need for spacing and limiting. Therefore, it is better to consider interventions at both individual and community levels.

Project description:IntroductionSocio-behavioural factors may contribute to the wide variance in HIV prevalence between and within sub-Saharan African (SSA) countries. We studied the associations between socio-behavioural variables potentially related to the risk of acquiring HIV.MethodsWe used Bayesian network models to study associations between socio-behavioural variables that may be related to HIV. A Bayesian network consists of nodes representing variables, and edges representing the conditional dependencies between variables. We analysed data from Demographic and Health Surveys conducted in 29 SSA countries between 2010 and 2016. We predefined and dichotomized 12 variables, including factors related to age, literacy, HIV knowledge, HIV testing, domestic violence, sexual activity and women's empowerment. We analysed data on men and women for each country separately and then summarized the results across the countries. We conducted a second analysis including also the individual HIV status in a subset of 23 countries where this information was available. We presented summary graphs showing associations that were present in at least six countries (five in the analysis with HIV status).ResultsWe analysed data from 190,273 men (range across countries 2295 to 17,359) and 420,198 women (6621 to 38,948). The two variables with the highest total number of edges in the summary graphs were literacy and rural/urban location. Literacy was negatively associated with false beliefs about AIDS and, for women, early sexual initiation, in most countries. Literacy was also positively associated with ever being tested for HIV and the belief that women have the right to ask their husband to use condoms if he has a sexually transmitted infection. Rural location was positively associated with false beliefs about HIV and the belief that beating one's wife is justified, and negatively associated with having been tested for HIV. In the analysis including HIV status, being HIV positive was associated with female-headed household, older age and rural location among women, and with no variables among men.ConclusionsLiteracy and urbanity were strongly associated with several factors that are important for HIV acquisition. Since literacy is one of the few variables that can be improved by interventions, this makes it a promising intervention target.

Project description:IntroductionHandwashing is fundamentally an inexpensive means of reducing the spread of communicable diseases. In developing countries, many people die due to infectious diseases that could be prevented by proper hand hygiene. The recent coronavirus (COVID-19) pandemic is a threat to people who are living in resource-limited countries including sub-Saharan Africa (SSA). Effective hand hygiene requires sufficient water from reliable sources, preferably accessible on premises, and access to handwashing facility (water and or soap) that enable hygiene behaviors. Therefore, this study aims to determine the prevalence of limited handwashing facility and its associated factors in sub-Saharan Africa.MethodsData from the Demographic and Health Surveys (DHS) were used, which have been conducted in 29 sub-Saharan African countries since January 1, 2010. A two-stage stratified random cluster sampling strategy was used to collect the data. This study comprised a total of 237,983 weighted samples. The mixed effect logistic regression model with a cluster-level random intercept was fitted. Meta-analysis and sub-group analysis were performed to establish the pooled prevalence.ResultsThe pooled prevalence of limited handwashing facility was found to be 66.16% (95% CI; 59.67%-72.65%). Based on the final model, household head with age group between 35 and 60 [AOR = 0.89, 95% CI; 0.86-0.91], households with mobile type of hand washing facility [AOR = 1.73, 95% CI; 1.70-1.77], unimproved sanitation facility [AOR = 1.58, 95% CI; 1.55-1.62], water access more than 30 min round trip [AOR = 1.16, 95% CI; 1.13-1.19], urban residential area [AOR = 2.08, 95% CI; 2.04-2.13], low media exposure [AOR = 1.47, 95% CI; 1.31-1.66], low educational level [AOR = 1.30, 95% CI; 1.14-1.48], low income level [AOR = 2.41, 95% CI; 2.33-2.49] as well as lower middle-income level [AOR = 2.10, 95% CI; 2.14-2.17] and households who had more than three children [AOR = 1.25, 95% CI; 1.20-1.31] were associated with having limited handwashing facility.Conclusion and recommendationThe pooled coverage of limited handwashing facility was high in sub-Saharan Africa. Raising awareness of the community and promoting access to handwashing materials particularly in poorer and rural areas will reduce its coverage.

Project description:BackgroundDespite the intended 50% reduction in anemia in women of reproductive age, this tendency has only worsened. Even though iron deficiency is the most prevalent cause of anemia, anemia and chronic illnesses like HIV are closely associated; in fact, 48.6% of people living with HIV who were 15 years of age or older had anemia. However, the burden of anemia among HIV-positive women in sub-Saharan African (SSA) countries is not well documented. Therefore, the goal of our research was to investigate anemia and the factors that are linked to it in SSA women who had HIV infections.MethodsA cross-sectional study was conducted using demographic and health survey datasets from 18 SSA countries. A total of 7823 weighted samples were included. STATA version 16 software was used for analysis. A multilevel logistic regression model was fitted. An adjusted odds ratio with a 95% CI and a p-value < 0.05 was used to declare significantly associated factors.ResultThe overall prevalence of anemia was found to be 45.1% [95% CI: 43.97-46.18%]. Of those 5.05%, 37.97%, and 56.97% were severely, moderately, and mildly anemic, respectively. Education level of primary [AOR = 0.74, 95% CI: 0.62, 0.89], secondary [AOR = 0.81, 95% CI: 0.68, 0.98], and higher [AOR = 0.74, 95% CI: 0.55, 0.99], as well as current contraceptive use [AOR = 0.74, 95% CI: 0.63, 0.87] were negatively associated with anemia. While pregnancy [AOR = 1.51, 95% CI: 1.17, 1.94], breast feeding [AOR = 1.38, 95% CI: 1.17, 1.64], health insurance [AOR = 1.50, 95% CI: 1.25, 1.80], and menstruation within six weeks prior to data collection [AOR = 1.36, 95% CI: 1.20, 1.54] had a significant positive relation with anemia among HIV-infected women in SSA countries.ConclusionAnemia is a serious public health problem among HIV-infected women in SSA countries. Pregnancy, breast feeding, health insurance, and menstruation within six weeks prior to data collection were significant risk factors. On the other education and current contraceptive use were significant protective factors for anemia among HIV-infected women in SSA countries. Therefore, strategies aimed at early identification of anemia may lead to an improvement in the health of HIV-infected women.

Project description:BackgroundPostnatal care (PNC) is the care of a newborn and mother for up to six weeks from one hour of placenta birth. The postnatal period is one of the most hazardous stages for mothers and their baby's health. The PNC is influenced by several maternal, family, biological, and socio-economic factors and it is necessary to identify the most significant factors of PNC. Therefore, the authors focus on determining the significant determinants of postnatal care in Bangladesh.Methods and materialsThis study is based on a secondary dataset extracted from the Bangladesh Demographic and Health Survey (BDHS)-2017/18. Descriptive statistics, chi-square test, and multilevel logistic regression have been used to determine the contributing factors of PNC.ResultsThe rate of postnatal care was highest in Sylhet (73.7%) and lowest in Dhaka (57.1%). Female babies had 10.1% less odds of having postnatal care than male babies. Findings depict that the children with 1-3 siblings have 1. 82 times more odds (odds ratio (OR):1.82, 95% confidence interval (CI):0.03-3.21) of PNC than babies without any siblings. Children who suffered from fever recently had 1.25 times (OR = 1.25, 95% CI:1.09-1.45) more odds of taking PNC than their counterparts. Children of working mothers had 1.33 times (OR:1.33, 95% CI:1.14-1.56) more odds of having PNC than children of non-working mothers.ConclusionThe sex of a child, birth order number, place of residence, region, receiving Bacillus Calmette-Guérin (BCG) vaccine, number of antenatal care visits, having fever recently, number of household members, media exposure, and household facilities are significantly linked with PNC in Bangladesh. To ensure the good health of a child, it is necessary to focus on the targeted groups and put emphasis on the identified variables. The authors believe that the findings will be helpful to the policymakers of Bangladesh to lessen childhood morbidities which will be helpful in achieving the target of the Sustainable Development Goals (SDGs) for reducing preventable maternal and under-five deaths by 2030.

Project description:BackgroundIn medical, social, and behavioral research we often encounter datasets with a multilevel structure and multiple correlated dependent variables. These data are frequently collected from a study population that distinguishes several subpopulations with different (i.e., heterogeneous) effects of an intervention. Despite the frequent occurrence of such data, methods to analyze them are less common and researchers often resort to either ignoring the multilevel and/or heterogeneous structure, analyzing only a single dependent variable, or a combination of these. These analysis strategies are suboptimal: Ignoring multilevel structures inflates Type I error rates, while neglecting the multivariate or heterogeneous structure masks detailed insights.MethodsTo analyze such data comprehensively, the current paper presents a novel Bayesian multilevel multivariate logistic regression model. The clustered structure of multilevel data is taken into account, such that posterior inferences can be made with accurate error rates. Further, the model shares information between different subpopulations in the estimation of average and conditional average multivariate treatment effects. To facilitate interpretation, multivariate logistic regression parameters are transformed to posterior success probabilities and differences between them.ResultsA numerical evaluation compared our framework to less comprehensive alternatives and highlighted the need to model the multilevel structure: Treatment comparisons based on the multilevel model had targeted Type I error rates, while single-level alternatives resulted in inflated Type I errors. Further, the multilevel model was more powerful than a single-level model when the number of clusters was higher. A re-analysis of the Third International Stroke Trial data illustrated how incorporating a multilevel structure, assessing treatment heterogeneity, and combining dependent variables contributed to an in-depth understanding of treatment effects. Further, we demonstrated how Bayes factors can aid in the selection of a suitable model.ConclusionThe method is useful in prediction of treatment effects and decision-making within subpopulations from multiple clusters, while taking advantage of the size of the entire study sample and while properly incorporating the uncertainty in a principled probabilistic manner using the full posterior distribution.

Dataset Information

Determinants of anemia level among reproductive-age women in 29 Sub-Saharan African countries: A multilevel mixed-effects modelling with ordered logistic regression analysis

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