Association between concurrence of multiple risk factors and under-5 mortality: a pooled analysis of data from Demographic and Health Survey in 61 low-and-middle-income countries

Background

Exposure to multiple risk factors is prevalent in low-and middle-income countries (LMICs), challenging one-directional strategies to address preventable under-5 mortality (U5M). This study aims to assess the associations between concurrence of multiple risk factors and U5M in LMICs.

Methods

We extracted data from the Demographic and Health Surveys conducted between 2010 and 2021 across 61 LMICs. Our primary outcome was U5M, defined as deaths from birth to 59 months. Binary logistic regression model was applied to ascertain the association between U5M and a total of 20 critical risk factors. Upon identifying the risk factors demonstrating the strongest associations, we investigated the simultaneous presence of multiple risk factors in each individual and assessed their combined effects on U5M with logistic regression models.

Findings

Of the 604,372 under-5 children, 18,166 (3.0%) died at the time of the survey. Unsatisfied family planning needs was the strongest risk factor for U5M (odds ratio [OR]: 2.0, 95% confidence interval [CI]: 1.9-2.1), followed by short birth interval (<18 months; OR: 2.0, 95% CI: 1.9-2.1), small birth size (OR: 2.0, 95% CI: 1.8-2.1), never breastfed or delayed breastfeeding (OR: 2.0, 95% CI: 1.9-2.0), and low maternal education (OR: 1.6, 95% CI: 1.4-1.8). 66.7% (66.6%-66.8%) of the children had 2 or more leading risk factors simultaneously. Simultaneous presence of multiple leading risk factors was significantly associated with elevated risk of U5M and children presenting with all 5 leading risk factors exhibited an exceedingly high risk of U5M (OR: 5.2, 95% CI: 4.3-6.3); a dose-response relationship between the number of risk factors and U5M was also observed-with the increment of numbers of leading risk factors, the U5M showed an increasing trend (p-trend < 0.001).

Interpretation

Exposure to multiple risk factors is very common in LMICs and underscores the necessity of developing multisectoral and integrated approaches to accelerate progress in reducing U5M in line with the SDG 3.2.

Funding

This research is funded by Research Fund, Vanke School of Public Health, Tsinghua University.

Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016-2021

BACKGROUND

Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana.

METHODS

The study used 2016-2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods.

RESULTS

A total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = - 13.82-15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean - 1.82, 95% credible interval = - 16.59-12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time.

CONCLUSION

This study identified high malaria risk districts in Ghana where urgent and targeted control efforts are required. Noticeable changes were also observed in malaria risk for certain districts over some periods in the study. The findings provide an effective, actionable tool to arm policymakers and programme managers in their efforts to reduce malaria risk and its associated morbidity and mortality in line with the Sustainable Development Goals (SDG) 3.2 for limited public health resource settings, where universal intervention across all districts is practically impossible.

Does mobile renewal make health insurance more responsive to clients? A case study of the National Health Insurance Scheme in Ghana

BACKGROUND

In 2018, Ghana's National Health Insurance Authority (NHIA) introduced a mobile strategy to enhance re-enrolment and improve client knowledge of their entitlements. This study investigated how Ghana's mobile strategy has influenced the NHIA's responsiveness to clients in terms of patient rights and entitlements, equity and satisfaction with health services.

METHODS

We surveyed people (n=1700) in 6 districts who had renewed their insurance in the previous 12 months, using any strategy (mobile or manual). Multiple regression analysis examined correlation between individual characteristics and renewal modality. Policy documents on the mobile programme's design and focus group discussions (n=12) on people's experiences renewing their insurance were analysed thematically.

RESULTS

While the mobile platform was designed for mobile National Health Insurance Scheme (NHIS) renewal and to provide information about insurance entitlements, few people surveyed (20%) knew about these informational features. Among those who renewed their NHIS coverage, 58% did so on the mobile renewal platform. Mobile renewal was high among those with tertiary education and those in the higher wealth quintiles. Mobile renewal was considered convenient, but required literacy in English, a phone and a mobile money wallet. For those who lacked some or all of these prerequisites but wanted to use mobile renewal, mobile vendors emerged as valued facilitators.

CONCLUSION

The mobile platform has increased the responsiveness of Ghana's NHIS through offering clients a more convenient mechanism to renew their insurance policies. It does not, however, eliminate the one month waiting period for activating the card, does not provide prompts to reassure clients of their renewal and does not empower most clients with information on entitlements. To improve the adoption and use of the mobile renewal strategy, the NHIA should publicise the platform's information-sharing functions and explore formally engaging mobile vendors.

Geospatial Analyses of Recent Household Surveys to Assess Changes in the Distribution of Zero-Dose Children and Their Associated Factors before and during the COVID-19 Pandemic in Nigeria

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and their vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the coronavirus disease 2019 (COVID-19) pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and its associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic, in 2018, and during the pandemic, in 2021, in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of the first dose of diphtheria-tetanus-pertussis-containing vaccine (DTP1), the first dose of measles-containing vaccine (MCV1), and any of the four basic vaccines (bacilli Calmette-Guerin (BCG), oral polio vaccine (OPV0), DTP1, and MCV1), and the corresponding zero-dose estimates independently at a 1 × 1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing the areas in greatest need. At the national level, risk factors related to socioeconomic/demographic status (e.g., maternal education), maternal access to and utilization of health services, and remoteness were strongly associated with the odds of being zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero-dose children in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Geostatistical modelling of child undernutrition in developing countries using remote-sensed data: evidence from Bangladesh and Ghana demographic and health surveys

Childhood chronic undernutrition, known as stunting, remains a critical public health problem globally. Unfortunately while the global stunting prevalence has been declining over time, as a result of concerted public health efforts, there are areas (notably in sub-Saharan Africa and South Asia) where progress has stagnated. These regions are also resource-poor, and monitoring progress in the fight against chronic undernutrition can be problematic. We propose geostatistical modelling using data from existing demographic surveys supplemented by remote-sensed information to provide improved estimates of childhood stunting, accounting for spatial and non-spatial differences across regions. We use two study areas-Bangladesh and Ghana-and our results, in the form of prevalence maps, identify communities for targeted intervention. For Bangladesh, the maps show that all districts in the south-eastern region are identified to have greater risk of stunting, while in Ghana the greater northern region had the highest prevalence of stunting. In countries like Bangladesh and Ghana with limited resources, these maps can be useful diagnostic tools for health planning, decision making and implementation.

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.

Predictors of mosquito bed net use among children under-fives in Ghana: a multilevel analysis of the 2019 malaria indicator survey

BACKGROUND

Morbidities and mortalities due to malaria can be prevented by the use of insecticide-treated mosquito bed nets (ITN), which has been proven for malaria control and elimination. The purpose of this study was to assess the critical factors that predict the use of ITN among children under-fives in Ghana.

METHODS

The study utilized data from the 2019 Ghana Malaria Indicator Survey (GMIS). The outcome variable was mosquito bed net use among children under-fives. To determine critical factors that independently predict ITN use, multilevel multivariable logistic regression was employed using Stata version 16. Odds ratios and associated 95% confidence intervals and p-values were reported. A p < 0.05 was used to declare statistical significance.

RESULTS

The overall prevalence of ITN usage was 57.4%. Utilization of bed nets was 66.6% in the rural areas and 43.5% in the urban areas, was highest in the Upper West region (80.6%) even when stratified to rural (82.9%) and urban areas (70.3%) whilst Greater Accra region (30.5%, rural = 41.7%, urban = 28.9%) had the least. The community level multilevel analysis showed that bed net utilization was higher among children in rural areas [AOR = 1.99, 95% CI 1.32-3.01, p = 0.001] and in household with wooden wall materials [AOR = 3.29, 95% CI 1.15-9.40, p = 0.027]. Bed net utilization was however, less for households with 3 + children under-five [AOR = 0.29, 95% CI 0.19-0.46, p < 0.001), 4 years old (AOR = 0.66, 95% CI 00.48-00.92, p = 0.014], without universal access to bed net [AOR = 0.52, 95% CI 0.37-0.73, p < 0.001], those in the Greater Accra [AOR = 0.26, 95% CI 0.13-0.51, p < 0.001], Eastern [AOR = 0.47, 95% CI 0.23-0.95, p = 0.036], Northern [AOR = 0.42, 95% CI 0.20-0.88, p = 0.022], middle [AOR = 0.57, 95% CI 0.35-0.94, p = 0.026] and rich/richest [AOR = 0.51, 95% CI 0.29-0.92, p = 0.025] household wealth quintile. Substantial unobserved household and community level differences in bed net use were found.

CONCLUSION

This study demonstrates the need to intensify promotion of ITN use to those in urban areas, Greater Accra, Eastern and Northern regions, houses without wooden wall materials, middle and rich/richest households. Interventions should be targeted at older children and households with more under-five children and to ensure full access and use of ITNs among all children under-fives in each household as part of the overall goal of achieving the health-related SDGs.

Cardiovascular physical examination as a screening tool for congenital heart disease in newborns at a teaching hospital in Ghana

Objectives

To determine the usefulness of cardiovascular physical examination (CPE) as a screening tool in a low-resource setting for detecting congenital heart disease (CHD) in newborns delivered at the Maternity Unit of Korle Bu Teaching Hospital (KBTH), Accra, Ghana.

Design

A hospital-based cross-sectional study with a comparison group component.

Setting

Maternity Unit of the KBTH, Accra, Ghana.

Participants

Over eight months, newborns aged 1-14 days delivered at ≥ 34 weeks' gestation at the Maternity Unit, KBTH, were recruited into the study.

Intervention

Each newborn was examined using a set of CPE parameters for the presence of congenital heart disease. Those with suggestive features of CHD had a confirmatory echocardiogram test.

Main Outcome Measure

Abnormal CPE features and their corresponding echocardiogram findings.

Results

A total of 1607 were screened, with 52 newborns showing signs of CHD on CPE, of which 20 newborns were proven on echocardiogram to have congenital heart disease. Abnormal CPE parameter that was associated with CHD was murmur (P=0.001), dysmorphism (p=0.01), newborns with chest recessions (p=0.01) and lethargy (p=0.02). CPE's sensitivity, specificity, and positive and negative predictive values were 95%, 60.7%, 36.5% and 98,1%, respectively. The most common acyanotic CHD found was isolated atrial septal defect (ASD), followed by patent ductus arteriosus (PDA). The only cyanotic CHD found was a case of tricuspid atresia.

Conclusion

Cardiovascular physical examination at birth is an effective and inexpensive screening tool for detecting CHD in newborns, which can easily be utilised in low-resource settings.

Funding

None declared.

Multiple indicators of violence against female sex workers and its associated factors in Ghana: Evidence from the 2015 integrated bio-behavioral surveillance survey cross-sectional study

Background and Aims

Violence against female sex workers (FSWs) is a widespread phenomenon, especially in African nations like Ghana where sex work is outlawed primarily because of the pervasive worldview that sex work is a contravention of morality. Violence against FSWs deters them from accessing critical health services and heightens their risk of STIs including HIV infection. The study examined the prevalence and the associated factors of multiple indicators of violence against FSWs.

Methods

The study utilized a cross-sectional secondary data from the 2015 Integrated Bio-Behavioral Surveillance Survey conducted among FSWs and their nonpaying partners by Ghana AIDS Commission. We analysed data on a total of 4279 participants. Bivariate, and multivariable logistic regression analyses were utilized to identify factors associated with physical and sexual violence against FSWs. Data were analysed using Stata version 15.

Results

Of the 4279 FSWs, 433 (10%) and 1059 (25%) suffered physical and sexual violence, respectively. The predictors of physical violence are being a seater (adjusted odds ratio [aOR] = 0.53, 95% confidence interval [CI]: 0.36-0.74), aged ≥40 (aOR = 0.23, 95% CI: 0.08-0.64), nonuse of drugs (aOR = 0.56, 95% CI: 0.44-0.70), not using alcohol before sex (aOR = 0.69, 95% CI: 0.56-0.86) and petty business (aOR = 1.39, 95% CI: 1.05-1.82). Sexual violence was predicted by those aged 31-40 (aOR = 0.68, 95% CI: 0.49-0.94) and age ≥40 (aOR = 0.38, 95% CI: 0.22-0.66), currently married (aOR = 0.42, 95% CI: 0.27-0.67), having no living children (aOR = 0.69, 95% CI: 0.51-0.94), nonuse of drugs (aOR = 0.80, 95% CI: 0.68-0.94), and not using alcohol before sex (aOR = 0.74, 95% CI: 0.63-0.86). Region was associated with both physical and sexual violence. Both physical and sexual violence had negative consequences on consistency of condom use and condom failure among FSWs.

Conclusion

Physical and sexual violence against FSWs is pervasive, and a critical public health issue in Ghana. The identified associated factors could be considered as part of an overall strategy aimed at addressing the menace.

Serum 25-hydroxyvitamin D and hyaluronic acid levels as markers of fibrosis in patients with chronic liver disease at the main tertiary referral hospital in Ghana: A case-control study design

Background and Aims

Liver fibrosis leading to chronic liver disease (CLD) is a major cause of morbidity, mortality and health-care expenditure worldwide. The "gold standard" for diagnosis and staging of liver fibrosis is histological analysis of liver tissue obtained by liver biopsy, an invasive procedure. Therefore, there is the need to identify noninvasive and inexpensive markers for diagnosis and staging of liver fibrosis. This study aimed at evaluating the correlation of hyaluronic acid (HA) and 25-hydroxyvitamin D (25-OH vitamin D) serum levels as markers of fibrosis with histologically staged and graded liver biopsies obtained from CLD patients.

Methods

This was a case-control study involving 40 CLD patients requiring liver biopsies and 40 controls. Liver biopsies were staged to determine the degree of fibrosis. Serum levels of 25-OH vitamin D and HA were determined using ELISA. Statistical analyses were performed to determine differences in HA and 25-OH vitamin D levels between controls and patients as well as to correlate the biomarkers with the stages of fibrosis.

Results

CLD patients showed significant (p < 0.001) increase in the levels of AST, ALT, GGT, compared to the controls. Patients also had significantly (p < 0.001) lower serum 25-OH vitamin D and higher HA (p < 0.001) levels compared to the controls. Additionally, 25-OH vitamin D levels of the CLD patients were significantly different across the stages of liver fibrosis likewise serum HA levels. Furthermore, 25-OH vitamin D levels inversely correlated with the severity of liver fibrosis. A significant negative correlation (r = -0.33, p < 0.05) between CLD patients' HA and 25-OH vitamin D were found.

Conclusion

CLD patients had significantly reduced serum 25-OH vitamin D and higher HA. Both markers correlated with the degree of liver fibrosis. These findings have major clinical translatable implication in the use of vitamin D supplementation in the management of CLD in Ghana.

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.

Conditional probability and ratio-based approaches for mapping the coverage of multi-dose vaccines

Many vaccines are often administered in multiple doses to boost their effectiveness. In the case of childhood vaccines, the coverage maps of the doses and the differences between these often constitute an evidence base to guide investments in improving access to vaccination services and health system performance in low and middle-income countries. A major problem often encountered when mapping the coverage of multi-dose vaccines is the need to ensure that the coverage maps decrease monotonically with successive doses. That is, for doses i $$ i $$ and j $$ j $$ , i < j ⇒ p i ( s ) ≥ p j ( s ) $$ i<j\Rightarrow {p}_i\left(\boldsymbol{s}\right)\ge {p}_j\left(\boldsymbol{s}\right) $$ , where p i ( s ) $$ {p}_i\left(\boldsymbol{s}\right) $$ is the coverage of dose i $$ i $$ at spatial location s $$ \boldsymbol{s} $$ . Here, we explore conditional probability (CP) and ratio-based (RB) approaches for mapping p i ( s ) $$ {p}_i\left(\boldsymbol{s}\right) $$ , embedded within a binomial geostatistical modeling framework, to address this problem. The fully Bayesian model is implemented using the INLA and SPDE approaches. Using a simulation study, we find that both approaches perform comparably for out-of-sample estimation under varying point-level sample size distributions. We apply the methodology to map the coverage of the three doses of diphtheria-tetanus-pertussis vaccine using data from the 2018 Nigeria Demographic and Health Survey. The coverage maps produced using both approaches are almost indistinguishable, although the CP approach yielded more precise estimates on average in this application. We also provide estimates of zero-dose children and the dropout rates between the doses. The methodology is straightforward to implement and can be applied to other vaccines and geographical contexts.

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

BACKGROUND

Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20,000 deaths in children annually of which 25% are those aged < 5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, the study produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities.

METHODS

This modelling and web-based mapping study utilized data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. The study produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations.

RESULTS

In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086-6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017-0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079-0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7% to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates.

CONCLUSION

The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by programme managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

Spatio-temporal variations in neonatal mortality rates in Ghana: An application of hierarchical Bayesian methods

Ghana might not meet the SDGs target 3.2 of reducing neonatal mortality to 12 deaths per 1000 live births by 2030. Identifying core determinants of neonatal deaths provide policy guidelines and a framework aimed at mitigating the effect of neonatal deaths. Most studies have identified household and individual-level factors that contribute to neonatal mortality. However, there are relatively few studies that have rigorously assessed geospatial covariates and spatiotemporal variations of neonatal deaths in Ghana. This study focuses on modeling and mapping of spatiotemporal variations in the risk of neonatal mortality in Ghana using Bayesian Hierarchical Spatiotemporal models. This study used data from the Ghana Demographic and Health Surveys (GDHS) conducted in 1993, 1998, 2003, 2008, and 2014. We employed Bayesian Hierarchical Spatiotemporal regression models to identify geospatial correlates and spatiotemporal variations in the risk of neonatal mortality. The estimated weighted crude neonatal mortality rate for the period under consideration was 33.2 neonatal deaths per 1000 live births. The results obtained from Moran's I statistics and CAR model showed the existence of spatial clustering of neonatal mortality. The map of smooth relative risk identified Ashanti region as the most consistent hot-spot region for the entire period under consideration. Small body size babies contributed significantly to an increased risk of neonatal mortality at the regional level [Posterior Mean: 0.003 (95% CrI: 0.00,0.01)]. Hot spot GDHS clusters exhibiting high risk of neonatal mortality were identified by LISA cluster map. Rural residents, small body size babies, parity, and aridity contributed significantly to a higher risk of neonatal mortality at the GDHS cluster level. The findings provide actionable and insightful information to prioritize and distribute the scarce health resources equitably to tackle the menace of neonatal mortality. The regions and GDHS clusters with excess risk of neonatal mortality should receive optimum attention and interventions to reduce the neonatal mortality rate.

Multilevel analysis of predictors of multiple indicators of childhood vaccination in Nigeria

Background

Substantial inequalities exist in childhood vaccination coverage levels. To increase vaccine uptake, factors that predict vaccination coverage in children should be identified and addressed.

Methods

Using data from the 2018 Nigeria Demographic and Health Survey and geospatial data sets, we fitted Bayesian multilevel binomial and multinomial logistic regression models to analyse independent predictors of three vaccination outcomes: receipt of the first dose of Pentavalent vaccine (containing diphtheria-tetanus-pertussis, Hemophilus influenzae type B and Hepatitis B vaccines) (PENTA1) (n = 6059) and receipt of the third dose having received the first (PENTA3/1) (n = 3937) in children aged 12–23 months, and receipt of measles vaccine (MV) (n = 11839) among children aged 12–35 months.

Results

Factors associated with vaccination were broadly similar for documented versus recall evidence of vaccination. Based on any evidence of vaccination, we found that health card/document ownership, receipt of vitamin A and maternal educational level were significantly associated with each outcome. Although the coverage of each vaccine dose was higher in urban than rural areas, urban residence was not significant in multivariable analyses that included travel time. Indicators relating to socio-economic status, as well as ethnic group, skilled birth attendance, lower travel time to the nearest health facility and problems seeking health care were significantly associated with both PENTA1 and MV. Maternal religion was related to PENTA1 and PENTA3/1 and maternal age related to MV and PENTA3/1; other significant variables were associated with one outcome each. Substantial residual community level variances in different strata were observed in the fitted models for each outcome.

Conclusion

Our analysis has highlighted socio-demographic and health care access factors that affect not only beginning but completing the vaccination series in Nigeria. Other factors not measured by the DHS such as health service quality and community attitudes should also be investigated and addressed to tackle inequities in coverage.

Assessment of oral health status in a Ghanaian population: rationale, methods, and population characteristics

Background

Oral health surveys aid in estimating the oral health of a population and provide a projection for future oral health care needs. We report the procedures and rationale of a survey carried out to assess the oral health status and risk factors for oral disease among adults in the Greater Accra Region (GAR) of Ghana. The objective was to provide prevalence estimates on dental diseases, oral health behaviour and risk factors, and to establish baseline epidemiological data on the population’s oral health for further research.

Methods

This was a population-based cross-sectional study of adults aged 25 years and above. A random, stratified two-stage sampling method was used to select participants from rural and urban communities in three types of districts (Metropolitan, Municipal, Ordinary). A semi- structured questionnaire was used to collect data on socio-demographic characteristics, oral health behaviours and risk factors for oral disease. Anthropometric data and a full-mouth clinical examination was carried out including: soft tissue assessment, tooth count, prosthodontic status, dental caries assessment and periodontal assessment.

Results

A total of 729 participants were included in the study with a mean age of 43.9 years (SD 14.6). Majority 425 (61.0%) were females. Though the metropolitan districts had more dental clinics and personnel, along with better health insurance coverage, they had a higher prevalence of missing teeth, retained roots, severe periodontitis and poorer oral health coverage. The findings also show some significant differences in disease prevalence, within the different localities and districts.

Conclusions

Availability and access to oral health services is not the most important determinant of good oral health outcomes in this region. We recommend exploring socio-behavioral and cultural factors as well. This study provides district level data to inform policy and guide further research.

Multilevel modeling, prevalence, and predictors of hypertension in Ghana: Evidence from Wave 2 of the World Health Organization's Study on global AGEing and adult health

BACKGROUND AND AIMS

Hypertension is a major public health issue, an important risk factor for cardiovascular diseases and stroke, especially in developing countries where the rates remain unacceptably high. In Africa, hypertension is the leading driver of cardiovascular disease and stroke deaths. Identification of critical risk factors of hypertension can help formulate targeted public health programs and policies aimed at reducing the prevalence and its associated morbidity, disability, and mortality. This study attempts to develop multilevel regression, an in-depth statistical model to identify critical risk factors of hypertension.

METHODS

This study used data on 4667 individuals aged ≥18 years from the nationally representative World Health Organization Study on global AGEing and adult health (SAGE) Ghana Wave 2 conducted in 2014/2015. Multilevel regression modeling was employed to identify critical risk factors for hypertension based on systolic blood pressure (SBP) (ie, SBP > 140 mmHg). Of the 4667, 27.3% were hypertensive. Final data on 4381 individuals residing in 3790 households were analyzed using multilevel models, and results were presented as adjusted odds ratios (aOR) and their associated 95% confidence intervals (CI).

RESULTS

Risk factors for hypertension identified were age (aOR) = 5.4, 95% CI: 4.11-7.09), obesity (aOR = 1.51, 95% CI: 1.19-1.91), marital status (aOR = 0.75, 95% CI: 0.64-0.89), perceived health state (moderate; aOR = 1.38, 95% CI: 1.15-1.65 and bad/very bad; aOR = 1.35, 95% CI: 1.0-1.83), and difficulty with self-care (aOR = 1.64, 95% CI: 1.1-2.44). We found unobserved significant differences in the likelihood of hypertension prevalence between different households.

CONCLUSION

Addressing the problem of obesity, targeting specific interventions to those aged over 50 years, and improvement in the general health of Ghanaians are paramount to reducing the prevalence and its associated morbidity, disability, and mortality. Lifestyle modification in the form of dietary intake, knowledge provision supported with strong public health message, and political will could be beneficial to the management and prevention of hypertension.

A predictive model, and predictors of under-five child malaria prevalence in Ghana: How do LASSO, Ridge and Elastic net regression approaches compare?

Malaria is among the leading causes of mortality and morbidity among children in Ghana. Therefore, identifying the predictors of malaria prevalence in children under-five is among the priorities of the global health agenda. In Ghana, the paradigm shifts from using traditional statistics to machine learning techniques to identifying predictors of malaria prevalence are scarce. Thus, the present study used machine learning techniques to identify variables to build the best fitting predictive model of malaria prevalence in Ghana. We analysed the data on 2867 under-five children with malaria RDT results from the 2019 Ghana Malaria Indicator Survey. LASSO, Ridge, and Elastic Net regression methods were used to select variables to build predictive models. The R freeware version 4.0.2 was used. One out of four children tested positive for malaria (25.04%). The logit models based on selected features by LASSO, Ridge, and Elastic Net contained eleven, fifteen, and thirteen features, respectively. The LASSO regression model is preferred because it contains the smallest number of predictors and the smallest prediction error. The significant predictors of malaria among children were being older than 24 months, residing in the poorest household, being severely anaemic, residing in households without electricity, and residing in a rural area. The predictors identified in our study deserve policy attention and interventions to strengthen malaria control efforts in Ghana. The machine learning techniques employed in our study, especially the LASSO regression technique could be beneficial for identifying predictors of malaria prevalence in this group of children.

Geostatistical analysis, web-based mapping, and environmental determinants of under-5 stunting: evidence from the 2014 Ghana Demographic and Health Survey

BACKGROUND

Stunting rates in children younger than 5 years are among the most important health indicators globally. At the national level, malnutrition accounts for about 40% of under-5 deaths in Ghana. Disease risk mapping provides opportunities for disease surveillance and targeted interventions. We aimed to estimate and map under-5 stunting prevalence in Ghana, with the goal of identifying communities at higher risk where interventions and further research can be targeted.

METHODS

For this modelling study, we used data from the 2014 Ghana Demographic and Health Survey. Analyses were done on 2734 children residing in 415 geographical clusters. The outcome variable was the number of stunted children younger than 5 years in each sampled cluster. We employed a Bayesian geostatistical model to investigate both measured and unmeasured spatial risk factors for child stunting, comparing the performance of non-spatial (adjusting for selected covariates without spatial correlation), spatial (including spatial correlation), and null spatial (without the selected covariates) models. We then visualised the stunting prevalence across Ghana by mapping the predicted prevalence and exceedance probabilities to resolutions as refined as 5 km × 5 km.

FINDINGS

In 2014, 535 (19·6%) of 2734 children surveyed in Ghana were stunted. Elevation (log odds mean -0·0017, 95% credible interval -0·0034 to -0·0001), precipitation (0·0403, 0·0192 to 0·0615), and aridity (-3·7013, -6·5478 to -0·8723) were environmental and climatic factors associated with stunting in the non-spatial model, but were not significant in the spatial model. Substantial geographical variations in prevalence of childhood stunting were found. The predicted mean stunting prevalence was 27·7% (SD 3·7%) with predicted prevalence ranging from 4·2% to 45·1% across Ghana. Children residing in parts of the Northern region were at highest risk of stunting, whereas parts of the Greater Accra, Brong-Ahafo, Ashanti, and Eastern regions showed some of the lowest prevalence.

INTERPRETATION

There are substantial geographical differences in childhood stunting across Ghana. Our prevalence maps can be used as an effective tool to identify communities that require targeted interventions by programme managers and implementers, as part of an overall strategy to reduce the burden of malnutrition in a country with limited public health resources.

FUNDING

None.

Geospatial analysis, web-based mapping and determinants of prostate cancer incidence in Georgia counties: evidence from the 2012-2016 SEER data

Background

Prostate cancer (CaP) cases are high in the United States. According to the American Cancer Society, there are an estimated number of 174,650 CaP new cases in 2019. The estimated number of deaths from CaP in 2019 is 31,620, making CaP the second leading cause of cancer deaths among American men with lung cancer been the first. Our goal is to estimate and map prostate cancer relative risk, with the ultimate goal of identifying counties at higher risk where interventions and further research can be targeted.

Methods

The 2012–2016 Surveillance, Epidemiology, and End Results (SEER) Program data was used in this study. Analyses were conducted on 159 Georgia counties. The outcome variable is incident prostate cancer. We employed a Bayesian geospatial model to investigate both measured and unmeasured spatial risk factors for prostate cancer. We visualised the risk of prostate cancer by mapping the predicted relative risk and exceedance probabilities. We finally developed interactive web-based maps to guide optimal policy formulation and intervention strategies.

Results

Number of persons above age 65 years and below poverty, higher median family income, number of foreign born and unemployed were risk factors independently associated with prostate cancer risk in the non-spatial model. Except for the number of foreign born, all these risk factors were also significant in the spatial model with the same direction of effects. Substantial geographical variations in prostate cancer incidence were found in the study. The predicted mean relative risk was 1.20 with a range of 0.53 to 2.92. Individuals residing in Towns, Clay, Union, Putnam, Quitman, and Greene counties were at increased risk of prostate cancer incidence while those residing in Chattahoochee were at the lowest risk of prostate cancer incidence.

Conclusion

Our results can be used as an effective tool in the identification of counties that require targeted interventions and further research by program managers and policy makers as part of an overall strategy in reducing the prostate cancer burden in Georgia State and the United States as a whole.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08254-0.

Predictive model and determinants of odds of neonates dying within 28 days of life in Ghana

BACKGROUND

One of the priorities and important current problem in public health research globally is modeling of neonatal mortality and its risk factors in using the appropriate statistical methods. It is believed that multiple risk factors interplay to increase the risk of neonatal mortality. To understand the risk factors of neonatal mortality in Ghana, the current study carefully evaluated and compared the predictive accuracy and performance of two classification models.

METHODS

This study reviewed the birth history data collected on 5884 children born in the 5 years preceding the 2014 Ghana Demographic and Health Survey (GDHS). The 2014 GDHS is a cross-sectional nationally representative household sample survey. The relevant variables were selected using leaps-and-bounds method, and the area under curves were compared to evaluate the predictive accuracy of unweighted penalized and weighted single-level multivariable logistic regression models for predicting neonatal mortality using the 2014 GDHS data.

RESULTS

The study found neonatal mortality prevalence of 2.8%. A sample of 4514 children born in the 5 years preceding the 2014 GDHS was included in the inferential analysis. The results of the current study show that for the unweighted penalized single-level multivariable logistic model, there is an increased risk of neonatal death among babies born to mothers who received prenatal care from non-skilled worker [OR: 3.79 (95% CI: 2.52, 5.72)], multiple births [OR: 3.10 (95% CI: 1.89, 15.27)], babies delivered through caesarian section [OR: 2.24 (95% CI: 1.30, 3.85)], and household with 1 to 4 members [OR: 5.74 (95% CI: 3.16, 10.43)], respectively. The predictive accuracy of the unweighted penalized and weighted single-level multivariable logistic regression models was 82% and 80%, respectively.

CONCLUSION

The study advocates that prudent and holistic interventions should be institutionalized and implemented to address the risk factors identified in order to reduce neonatal death and, by large, improve child and maternal health outcomes to achieve the SDG target 3.2.

Prevalence, socio-demographic and environmental determinants of asthma in 4621 Ghanaian adults: Evidence from Wave 2 of the World Health Organization's study on global AGEing and adult health

Background

A previous multi-site study involving lower- and middle-income countries demonstrated that asthma in older adults is associated with long-term exposure to particulate matter, male gender and smoking. However, variations may occur within individual countries, which are relevant to inform health promoting policies as populations live longer. The present study estimates asthma prevalence and examines the sociodemographic characteristics and environmental determinants associated with asthma in older adults in Ghana.

Methods

This study utilised data from the nationally representative World Health Organization Study on global AGEing and adult health (SAGE) Ghana Wave 2. A final sample of 4621 individuals residing in 3970 households was used in analytical modelling. Factors associated with asthma were investigated using single level and multilevel binary logistic regression models.

Results

Asthma was reported by 102 (2.2%) respondents. Factors associated with asthma in the univariate model were: those aged 60–69 (OR = 5.22, 95% CI: 1.24, 21.95) and 70 or more (OR = 5.56, 95% CI: 1.33, 23.26) years, Ga-Adangbe dialect group (OR = 1.65, 95% CI: 1.01, 2.71), no religion (OR = 3.59, 95% CI: 1.77, 7.28), having moderate (OR = 1.76, 95% CI: 1.13, 2.75) and bad/very bad (OR = 2.75, 95% CI: 1.58, 4.80) health state, and severe/extreme difficulty with self-care (OR = 3.49, 95% CI: 1.23, 9.88) and non-flush toilet facility (OR = 0.62, 95% CI: 0.39, 0.99). Factors independently associated with asthma in the adjusted models were: those aged 60–69 (OR = 4.49, 95% CI: 1.03, 19.55) years, father with primary education or less (OR = 0.40, 95% CI: 0.17, 0.94), no religion (OR = 2.52, 95% CI: 1.18, 5.41), and households with non-flush toilet facility (OR = 0.58, 95% CI: 0.35, 0.96). Significant residual household-level variation in asthma was observed. Over 40% of variance in asthma episodes could be attributable to residual household-level variations.

Conclusion

Individual as well as household factors were seen to influence the prevalence of asthma in this national survey. Clinical management of these patients in health facilities should consider household factors in addition to individual level factors.

Geostatistical analysis and mapping: social and environmental determinants of under-five child mortality, evidence from the 2014 Ghana demographic and health survey

BACKGROUND

Under-five mortality (U5M) rates are among the health indicators of utmost importance globally. It is the goal 3 target 2.1 of the Sustainable Development Goals that is expected to be reduced to at least 25 per 1000 livebirths by 2030. Despite a considerable reduction in U5M observed globally, several countries especially those in sub-Saharan Africa (SSA) like Ghana are struggling to meet this target. Evidence-based targeting and utilization of the available limited public health resources are critical for effective design of intervention strategies that will enhance under-five child survival. We aimed to estimate and map U5M risk, with the ultimate goal of identifying communities at high risk where interventions and further research can be targeted.

METHODS

The 2014 Ghana Demographic and Health Survey data was used in this study. Geostatistical analyses were conducted on 5884 children residing in 423 geographical clusters. The outcome variable is child survival status (alive or dead). We employed a geostatistical generalised linear mixed model to investigate both measured and unmeasured child specific and spatial risk factors for child survival. We then visualise child mortality by mapping the predictive probability of survival.

RESULTS

Of the total sampled under 5 children, 289 (4.91%) experienced the outcome of interest. Children born as multiple births were at increased risk of mortality with an adjusted odds ratio (aOR) (aOR: 8.2532, 95% CI: [5.2608-12.9477]) compared to singletons. Maternal age increased risk of mortality (aOR: 1.0325, 95% CI: [1.0128-1.0527]). Child's age (aOR: 0.2277, 95% CI: [0.1870-0.2771]) and number of children under 5 within each household (aOR: 0.3166, 95% CI: [0.2614-0.3835]) were shown to have a protective effect. Additionally, mothers with secondary education level (aOR: 0.6258, 95% CI: [0.4298-0.9114]) decreased the risk of U5M. The predicted U5M risk in 2014 was at 5.98%. Substantial residual spatial variations were observed in U5M.

CONCLUSION

The analysis found that multiple births is highly associated with increased U5M in Ghana. The high-resolution maps show areas and communities where interventions and further research for U5M can be prioritised to have health impact.

Simultaneous quantile regression and determinants of under-five severe chronic malnutrition in Ghana

BACKGROUND

Under-five malnutrition is a major public health issue contributing to mortality and morbidity, especially in developing countries like Ghana where the rates remain unacceptably high. Identification of critical risk factors of under-five malnutrition using appropriate and advanced statistical methods can help formulate appropriate health programmes and policies aimed at achieving the United Nations SDG Goal 2 target 2. This study attempts to develop a simultaneous quantile regression, an in-depth statistical model to identify critical risk factors of under-five severe chronic malnutrition (severe stunting).

METHODS

Based on the nationally representative data from the 2014 Ghana Demographic and Health Survey, height-for-age z-score (HAZ) was estimated. Multivariable simultaneous quantile regression modelling was employed to identify critical risk factors for severe stunting based on HAZ (a measure of chronic malnutrition in populations). Quantiles of HAZ with focus on severe stunting were modelled and the impact of the risk factors determined. Significant test of the difference between slopes at different selected quantiles of severe stunting and other quantiles were performed. A quantile regression plots of slopes were developed to visually examine the impact of the risk factors across these quantiles.

RESULTS

Data on a total of 2716 children were analysed out of which 144 (5.3%) were severely stunted. The models identified child level factors such as type of birth, sex, age, place of delivery and size at birth as significant risk factors of under-five severe stunting. Maternal and household level factors identified as significant predictors of under-five severe stunting were maternal age and education, maternal national health insurance status, household wealth status, and number of children under-five in households. Highly significant differences exist in the slopes between 0.1 and 0.9 quantiles. The quantile regression plots for the selected quantiles from 0.1 to 0.9 showed substantial differences in the impact of the covariates across the quantiles of HAZ considered.

CONCLUSION

Critical risk factors that can aid formulation of child nutrition and health policies and interventions that will improve child nutritional outcomes and survival were identified. Modelling under-five severe stunting using multivariable simultaneous quantile regression models could be beneficial to addressing the under-five severe stunting.

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.

Mammography examination among women aged 40 years or older in Ghana: evidence from wave 2 of the World Health Organization's study on global AGEing and adult health multicountry longitudinal study

OBJECTIVE

To determine the uptake of mammography among Ghanaian women aged 40 years or older and to examine critical risk factors that influence the uptake.

STUDY DESIGN

A cross-sectional survey.

METHODS

A nationally representative sample of 2787 women and 1948 men aged ≥18 years were surveyed in the Wave 2 (2014-2015) of the World Health Organization's multicountry study on AGEing and adult health in Ghana. Of the 2787 women aged ≥18 years, data on a total of 2301 women aged ≥40 years were included in this study. Univariable and multivariable logistic regression models were applied to examine critical risk factors for mammogram examination.

RESULTS

Of the 2301 women sampled, only 83 (3.61%) ever had mammogram. The odds of mammogram examination were lower for women aged ≥70 years (odds ratio [OR] 0.42, 95% confidence interval [CI]: 0.19, 0.93), being self-employed (OR = 0.21, 95% CI: 0.11, 0.42) and being informal sector employee (OR = 0.26, 95% CI: 0.12, 0.57) in the multivariable analyses. Belonging to the Ewe ethnic group (OR=3.41, 95% CI:1.88, 6.16) compared to the Akan group was associated with increased odds of mammogram examination in the multivariable analysis. Women aged ≥70 years, being self-employed, being an informal employee and belonging to the Ewe ethnic group were independently associated with mammography examination.

CONCLUSION

The prevalence of screening for breast cancer using mammography among Ghanaian women aged 40 years and older was 3.6%. Age, type of employer and ethnicity were associated with an older adult woman's likelihood to access mammography screening. Overall, our study provided critical data to encourage and promote good health-seeking behaviour in terms of breast cancer screening among older adult women. Further qualitative studies are warranted to explore why some of these factors influence mammography.

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

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.

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.