Modelling malnutrition among under-five-year-old children in Ghana

Childhood malnutrition is a real-life and a chronic problem and one of the global major public health challenges, especially in developing countries like Ghana. Several attempts from governmental and non-governmental organizations to address the problem have fallen below expectation. It is recognised that the existing studies and nutrition intervention strategies are inadequate and hence not working to expectation. This thesis examines childhood malnutrition in Ghana using appropriate and advanced statistical methods to help improve the understanding of childhood nutrition and to better inform targeted public health nutrition interventions in the country. In this thesis, we provided solutions to five main problems: (1) investigated the major risk factors for malnutrition; (2) investigated household level variations in nutritional outcomes of children; (3) explored, modelled and illustrated spatial variations in the risk of childhood malnutrition over Ghana; (4) explored, modelled, forecasted and illustrated spatio-temporal variations in the risk of childhood malnutrition over Ghana; (5) jointly modelled weight-for-age Z-score (WAZ) and height-for-age Z-score (HAZ) to improve accuracy and reliability in estimates. To answer the first and the second problems, multilevel models were considered. The results showed strong residual household-level variations in under-fives nutritional outcomes and that child’s age, type of birth, child’s experience of diarrhoeal episodes, size of child at birth and months of breast feeding, mother’s education, current age, BMI and national health insurance status, household toilet facility ownership and wealth status were predictive of under-fives nutrition. To answer the third problem, spatial models were employed. The study found substantial spatial variation in the predicted risk of under-fives malnutrition over Ghana and also showed that Normalised Difference Vegetation Index (a marker for vegetation cover), elevation and rural/urban residence status were predictive of under-fives nutritional outcomes. The study considered spatio-temporal models to answer the fourth problem. The results showed substantial spatio-temporal variation in the risk of under-fives chronic malnutrition over Ghana. Our forecasted map of chronic malnutrition showed substantial spatial variation with children from parts of Northern and Western regions being at the highest risk of malnutrition compared to children from other regions of the country. In our forecast maps, the effect of increasing the level of maternal education was shown to reduce the prevalence of malnutrition throughout Ghana. To answer the fifth problem, multivariate response multilevel models were considered. The study found that the residual household effects for WAZ and HAZ are very strongly correlated and that the correlation was stronger for the residual household effects than the residual child effects. This also suggests that after adjusting for risk factors in our model, it is the same as-yet unidentified factors at household level that influence both WAZ and HAZ. The results also showed that there was more accuracy and reliability in estimates from the multivariate response multilevel model over separate multilevel models and showed that the effect of some important risk factors differed substantially across WAZ and HAZ. The findings from this thesis are intended to help policymakers responsible for the health and nutrition of children to design efficient public health policies and targeted nutrition interventions amidst scarce public health resources available in Ghana to better understand, target and to reduce childhood malnutrition prevalence closer to the level expected in a healthy, well-fed population of children under-fives

A predictive model and socioeconomic and demographic determinants of under-five mortality in Sierra Leone.

Sierra Leone is among the countries that recorded high under-five child mortality rate in the world. To design and implement policies that can address this public health challenge, the present study developed a predictive model of factors that explained under-five mortality in Sierra Leone using the 2008 and 2013 Sierra Leone Demographic and Health Survey (SDHS) datasets. LASSO regression technique was used to select the predictors to build the under-five predictive single-level logit and multilevel logit models. Statistical analyses were performed in the R freeware version 3.6.1. About 588 (10.4%) and 1320 (11.1%) children under five were reported dead in 2008 and 2013, respectively. The significant predictors of under-five mortality in Sierra Leone were the total number of children ever born, number of children under five in the household, mother's birth in the last five years, mother's number of living children, and number of household members, household wealth, maternal contraceptive use and intention, number of eligible women in the household, type of toilet facility, sex of the child, and weight of the child at birth. The study identified certain predictors that deserve policy attention and interventions to strengthen the efforts of creating child welfare and survival atmosphere in Sierra Leone

Childhood malnutrition and its determinants among under-five children in Ghana

Background Childhood malnutrition adversely affects short- and long-term health and economic well-being of children. Malnutrition is a global challenge and accounts for around 40% of under-five mortality in Ghana. Limited studies are available indicating determinants of malnutrition among children. This study investigates prevalence and determinants of malnutrition among children under-five with the aim of providing advice to policymakers and other stakeholders responsible for the health and nutrition of children. Methods The study used data from the 2008 Ghana Demographic and Health Survey (GDHS). Analyses were conducted on 2083 children under 5 years old nested within 1641 households with eligible anthropometric measurements, using multilevel regression analysis. Results from the multilevel models were used to compute probabilities of malnutrition. Results This study observed that 588 (28%), 276 (13%), and 176 (8%) of the children were moderately ‘stunted’, moderately ‘underweight’, and moderately ‘wasted’ respectively. Older ages are associated with increased risk of stunting and underweight. Longer breast-feeding duration, multiple births, experience of diarrhoeal episodes, small size at birth, absence of toilet facilities in households, poor households, and mothers who are not covered by national health insurance are associated with increased risk of malnutrition. Increase in mother's years of education and body mass index are associated with decreased malnutrition. Strong residual household-level variations in childhood nutritional outcomes were found. Conclusion Policies and intervention strategies aimed at improving childhood nutrition and health should address the risk factors identified and the need to search for additional risk factors that might account for the unexplained household-level variations

Modelling and Forecasting Spatio-temporal Variations in the Risk of Chronic Malnutrition Among Under-Five Children in Ghana

Background: Spatio-temporal variation in under-five-year-old children malnutrition remains unstudied in most developing countries like Ghana. This study explores and forecasts the spatio-temporal patterns in childhood chronic malnutrition among these children. We also investigate the effect of maternal education on childhood malnutrition. Methods: We analysed data on 10,036 children residing in 1,516 geographic locations. A spatio-temporal model was fitted to the data and was used to produce predictive maps of spatio-temporal variation in the probability of stunting. Results: The study found substantial spatio-temporal variation in the prevalence of stunting. Also, higher levels of mother's education were associated with decreased risk of being stunted. Conclusion: Our spatio-temporal model captured variations in childhood stunting over place and time. Our method facilitates and enriches modelling and forecasting of future stunting prevalence to identify areas at high risk. Improving maternal education could be given greater consideration within an overall strategy for addressing childhood malnutrition

Physical distancing and risk of COVID-19 in small-scale fisheries: a remote sensing assessment in coastal Ghana

The novel coronavirus is predicted to have dire implications on global food systems including fisheries value chains due to restrictions imposed on human movements in many countries. In Ghana, food production, both agriculture and fisheries, is exempted from restrictions as an essential service. The enforcement of COVID-19 prevention protocols, particularly social distancing, has been widely reported in Ghana's agricultural markets whereas casual observations and media reports on fish landing sites suggest no such enforcements are in place. This study aimed to provide sound scientific evidence as a basis for informed policy direction and intervention for the artisanal fishing sector in these challenging times. We employed an unmanned aerial vehicle in assessing the risk of artisanal fishers to the pandemic using physical distancing as a proxy. From analysis of cumulative distribution function (G-function) of the nearest-neighbour distances, this study underscored crowding at all surveyed fish landing beaches, and identified potential "hotspots" for disease transmission. Aerial measurements taken at times of peak landing beach activity indicated that the highest proportion of people, representing 56%, 48%, 39% and 78% in Elmina, Winneba, Apam and Mumford respectively, were located at distances of less than one metre from their nearest neighbour. Risk of crowding was independent of the population at the landing beaches, suggesting that all categories of fish landing sites along the coast would require equal urgency and measured attention towards preventing and mitigating the spread of the disease

Predictive model and determinants of under-five child mortality: evidence from the 2014 Ghana demographic and health survey

Abstract Background Globally, millions of children aged below 5 years die every year and some of these deaths could have been prevented. Though a global problem, under-five mortality is also a major public health problem in Ghana with a rate of 60 deaths per 1000 live births. Identification of drivers of mortality among children aged below 5 years is an important problem that needs to be addressed because it could help inform health policy and intervention strategies aimed at achieving the United Nations SDG Goal 3 target 2. The aim of this study is to develop a predictive model and to identify determinants of under-five mortality. Method The 2014 Ghana Demographic and Health Survey data was used in this study. Analyses were conducted on 5884 children. The outcome variable is child survival status (alive or dead). Single level binary logistic and multilevel logistic regression models were employed to investigate determinants of under-five mortality. The fit of the model was checked using Variance Inflation Factor and Likelihood Ratio tests. The Receiver Operating Characteristic curve was used to assess the predictive ability of the models. A p-value< 0.05 was used to declare statistical significance. Results The study observed 289 (4.91%) deaths among children aged below 5 years. The study produced a good predictive model and identified increase in number of total children ever born, number of births in last 5 years, and mothers who did not intend to use contraceptive as critical risk factors that increase the odds of under-five mortality. Also, children who were born multiple and residing in certain geographical regions of Ghana is associated with increased odds of under-five mortality. Maternal education and being a female child decreased the odds of under-five mortality. No significant unobserved household-level variations in under-five mortality were found. The spatial map revealed regional differences in crude under-five mortality rate in the country. Conclusion This study identified critical risk factors for under-five mortality and strongly highlights the need for family planning, improvement in maternal education and addressing regional disparities in child health which could help inform health policy and intervention strategies aimed at improving child survival

Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter?

Background: Neonatal mortality accounts for an increasing share of under-five deaths, and they are declining at a slower rate than postnatal deaths. Apparently, neonatal mortality is increasingly becoming a major public health problem in Ghana and the world over. The current study sought to analyze neonatal mortality as a function of predictor variables and to estimate and understand unobserved household and community-level residual effects on neonatal mortality to provide data driven evidence to shape informed policies and interventions aimed at reducing the neonatal mortality burden. Methods: The current study extracted three-level complex data on 5884 children born in the five years preceding the 2014 Ghana Demographic and Health Survey. A two-level and three-level multilevel logistic models were applied to estimate unobserved household and community-level variations in neonatal mortality in the presence of set of predictor variables. Sampling weights were incorporated in both the descriptive and inferential analysis since the data used emanated from a complex survey. Model fit statistics such as AIC scores for a weighted two-level and three-level random intercept logistic models were compared. The model with the lowest AIC score was considered the most preferred model. Results: The household-level random intercept model suggested that the odds of neonatal mortality was higher among multiple births [OR = 3.15 (95% CI: 1.17, 8.50)], babies born to mothers who received prenatal care from non-skilled worker [OR = 5.88 (95% CI: 2.90, 11.91)], babies delivered through caesarian section [OR = 2.47 (95% CI: 1.06, 5.79)], a household with 1–4 members [OR = 10.23 (95% CI: 4.17, 25.50)], a short preceding birth interval (<24 months) [OR = 3.05 (95% CI: 1.18, 7.88)], and preceding birth interval between 24 and 47 months [OR = 2.88 (95% CI: 1.41, 5.91)]. Substantial unobserved household-level residual variations in neonatal mortality were observed. Conclusion: The findings of the current study provide an actionable information to be used by government and other stakeholders in the health sector to renew commitment to reduce neonatal mortality to an acceptable level. There is the need to intensify maternal health education by health providers to encourage pregnant women to visit antenatal clinics at least four times so they could benefit substantially from ANC services

Prevalence, awareness, and associated risk factors of hypertension in older adults in Africa:a systematic review and meta-analysis protocol

BACKGROUND: The health of older persons has not been a major priority in many African countries. Hypertension is one of the common health problems of older persons. However, there is little information on the prevalence of hypertension in older adults in Africa. This is in spite of the fact that Africa has the highest age-standardized prevalence of hypertension in the world. We therefore present this protocol to conduct a systematic review and meta-analysis on the prevalence of hypertension and the level of its awareness among older persons living in Africa. METHODS: Major databases (EMBASE, MEDLINE, Academic Search Complete, CINAHL, PsycINFO) and unpublished literature will be searched to identify population-based studies on hypertension in adults aged 50 years and older living in Africa. Eligible articles are those which use the 140/90-mmHg cutoff to diagnose hypertension and were published from 1980 to present. We will exclude subjects in restricted environments such as patients and refugees. Articles will be independently evaluated by two reviewers to determine if they meet the inclusion criteria. They will also evaluate the quality of included studies using a validated tool by Hoy and colleagues for prevalence studies. The main outcome is the prevalence of hypertension while the explanatory variables include demographic, socio-economic, dietary, lifestyle and behavioural factors. Effect sizes in bivariate and multivariate analyses will be presented as odds or prevalence ratios. We will explore for heterogeneity of the standard errors across the studies, and if appropriate, we will perform a meta-analysis using a random-effects model to present a summary estimate of the prevalence of hypertension in this population. DISCUSSION: The estimates of the prevalence, the risk factors and the level of awareness of hypertension could help in galvanizing efforts at prioritizing the cardiovascular health of older persons in Africa. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017056474

Joint modelling of systolic and diastolic blood pressure and its associated factors among women in Ghana: Multivariate response multilevel modelling methods

Elevated blood pressure is the leading cause of cardiovascular diseases related mortality and a major contributor to non-communicable diseases globally, especially in sub-Saharan Africa where about 74.7 million people live with hypertension. In Ghana, hypertension is epidemic with prevalence of over 30% and experiencing continuing burden with its associated morbidity and mortality. Using the 2014 Ghana Demographic and Health Survey, we analyzed data on 4744 women aged 15–49 years residing in 3722 households. We employed univariate and multivariate response multilevel linear regression models to analyze predictors of systolic blood pressure (SBP) and diastolic blood pressure (DBP). Geospatial maps were produced to show the regional distribution of hypertension prevalence in Ghana. Stata version 17 and R version 4.2.1 were used to analyze the data. Of the 4744 woman, 337 (7.1%) and 484 (10.2%) were found to be hypertensive on SBP and DBP, respectively. A combined prevalence of 12.3% was found. Older ages 25–34 (OR 2.45, 95%CI: 1.27, 3.63), 35–44 (OR 8.72, 95%CI: 7.43, 10.01), 45–49 (OR 15.85, 95%CI: 14.07, 17.64), being obese (OR 5.10, 95%CI: 3.62, 6.58), and having no education (OR -2.05, 95%CI: -3.40, -0.71) were associated with SBP. For DBP, we found the associated factors to be older ages 25–34 (OR 3.29, 95%CI: 2.50, 4.08), 35–44 (OR 6.78, 95%CI: 5.91, 7.64), 45–49 (OR 10.05, 95%CI: 8.85, 11.25), being obese (OR 4.20, 95%CI: 3.21, 5.19), and having no education (OR -1.23, 95%CI: -2.14, -0.33). Substantial residual household level differences in SBP (15%) and DBP (14%) were observed. We found strong residual correlation of SBP and DBP on individual women (r = 0.73) and household-level (r = 0.81). The geospatial maps showed substantial regional differences in the observed and reported hypertension prevalence. Interventions should be targeted at the identified high-risk groups like older age groups and those who are obese, and the high-risk regions

Additional file 1: of Prevalence, awareness, and associated risk factors of hypertension in older adults in Africa: a systematic review and meta-analysis protocol

PRISMA-P 2015 checklist 01 08 2017. Description of data: Contains the line numbers for the different items on the PRISMA-P checklist. (DOCX 33 kb