Estimation Of Random Effects Research Articles

Public health expenditure and under-five mortality in low-income Sub-Saharan African countries

IntroductionIn the year 2019 whiles the total world under-five mortalities was estimated at about 5.2 million, Sub-Saharan Africa contributed about 55% of these global under-five mortalities. In other words, the region alone recorded about 2.8 million under-five deaths out of the global 5.2 million under-five mortalities in 2019. On the other hand, public health expenditure in Sub-Saharan Africa though very low as compared to other regions has also seen a steady increase over the years. This has resulted in an increased interest of researchers and policymakers in scrutinizing the effect of healthcare spending on health status in Sub-Saharan Africa. Thus, the purpose of this study is to investigate the association between public healthcare spending and the under-five mortality rate in low-income countries of Sub-Saharan Africa. This has become necessary due to the impact of healthcare spending on the quality and quantity of the health system and the long-run effect on health outcomes and its overall link to economic growth and development. MethodsA balanced panel of data from twenty low-income countries in Sub-Saharan Africa was sourced from the World Development Indicators dataset spanning the year 2000–2019. The under-5 mortality rate was used as the outcome variable whereas domestic health expenditure was used as the independent variable of interest. Total fertility rate, percentage population of females, the practice of open defecation, and immunization against diphtheria-pertussis-tetanus (DPT) were considered potential confounding variables. The static model was applied. To arrive at the appropriate model for the study, the robust Hausman test was employed to aid in the selection between the random effect estimator and the fixed effect estimator, and the results led to the selection of the fixed effect estimator. ResultsThe results showed that domestic health spending has a significantly negative relationship (Fixed Effects = −5.275; p < 0.05) with the under-five mortality rate in low-income countries of Sub-Saharan Africa. For every additional percentage increase in domestic health spending, it is likely to result in about 5.3 units fall in under-five mortality rate. Total fertility rate, female population, and rural people practicing open defecation were positively associated while immunization against DPTwas negatively associated (p < 0.01) with an under-5 mortality rate. ConclusionThe study revealed a strong relationship between domestic health spending and the under-five mortality rate. We conclude that a sustained increase in health expenditure and improvement in social conditions are required to reduce under-5 mortalities within low-income countries of Sub-Saharan Africa.

Association of open-plan offices and sick leave-a systematic review and meta-analysis.

We aimed to systematically review and meta-analyze the association of employees working in various kinds of open-plan offices with sick leave data, compared to those working in traditional cell offices. Databases of PubMed, PubPsych, and Psyndex were systematically searched following the PRISMA statement. Pooled summary estimates of odds ratio (OR) were calculated comparing sick leave of employees in cell offices with those working in small open-plan offices (4-9 people), and those in various open-plan office solutions (≥4 people). We used Forest plots visualizing study-specific estimates and the pooled fixed and random effects estimators. Five studies were identified (2008-2020) with a total of 13,277 (range 469-6,328) participants. Compared with employees working in cell offices, those working in small open-plan offices were associated with higher odds of sick leave days (OR=1.27; 95% CI 0.99-1.54; p=0.046) as well as those working in various kinds of open-plan offices with ≥4 colleagues (OR=1.24; 95% CI 0.96-1.51; p=0.004). Our results are consistent with those of earlier reviews focusing on other effects of open-plan office solutions such as health and well-being. Different solutions for office design and architectural lay-out should be the focus of future studies to balance pros and cons of open-plan offices.

Digital Technology and Trade Performance in Sub-Saharan Africa

This study examines the relationship between digital technology and trade performance with a focus on export trade in sub-Saharan African countries. The main objectives are to examine the impact digital technology measured by ICT goods import, internet use and mobile telephone subscriptions have on export trade in Sub-Saharan Africa (SSA), to evaluate the link between the degree of the region’s development and export trade and the form of digital technology most suitable in facilitating trade in the region. The study hypotheses are that: (1) ICT goods import, internet use and mobile telephone subscriptions do not influence significantly export trade in SSA; (2) the region’s development does not link appreciably to export trade in SSA; (3) no form of digital technology can facilitate trade in the region. The panel regression estimation technique is adopted considering the panel least squares, fixed effect and random effect estimation techniques. Results show that information and communication technology imports exert greater positive and significant impact on export trade flows compared to internet usage demonstrating theoretical and practical relevance of technology in trade flows. The degree of development is low and does not show an appreciable impact on trade flows in the region indicating that trade integration can thrive better in a well-structured economy. Redundant fixed effect test confirms that the panel least squares estimation is better compared to the fixed effect estimation. Hausman test demonstrates that random effect estimation is also better than fixed effect estimation. In attaining the reality of the contribution of digitalization process in SSA, policy makers need to pursue major goals that would address problems hampering its success.

Demographic Challenges in Poland Understanding Low Fertility

Research background: The phenomenon of low fertility in Poland is a vital subject of demographic analysis. In recent years, not only have there been changes in procreative and family models, but also in the age structure of society. This is particularly significant in the context of population ageing, which is becoming increasingly evident and brings numerous challenges such as increased burden on healthcare systems, a decrease in the active workforce, and the need to secure adequate retirement funds. Despite the desire to have children, many individuals refrain from making such a decision, and the reasons for this choice are diverse. Therefore, it was essential to conduct an analysis of the factors determining fertility in Poland, considering both the economic and social aspects. Understanding how the economic situation, labour market conditions, and changes in social structure impact on the decision-making process regarding childbearing is essential. Purpose of the paper: The objective of this article was to analyse fertility rates in Poland for the period 2004-2020. The conducted research identified the factors influencing the observed state of low generational replacement and determining their intensity. Methodology/Methods/Data sources: The data used in this article were sourced from the Central Statistical Office and covered the years 2004-2020. The study was based on literature concerning demography and econometrics. Three statistical methods were applied in the analysis of fertility in Poland: the Classical Method of Least Squares (CMLS) model, the Fixed Effects (FE) estimator, and the Random Effects (RE) estimator. Fertility analysis was conducted at regional level by dividing Poland into 16 administrative units (voivodeships). A panel model was employed for the analysis, and the results were subjected to Wald, Breusch-Pagan, and Hausman tests to compare the outcomes obtained from different models. Findings: The results of the analysis indicate that the economic situation and the labour market significantly influence the decision to have children in Poland. The trend of low fertility, although showing some increase, is still characteristic of the country compared to other EU nations. The analysis of the factors determining fertility is vital for understanding the decisions of young generations of Poles regarding parenthood.

Determinants of Banks’ Risk-Taking Behaviours in Africa: A Regulatory Perspective

The intermediation role of banks between borrowers and savers exposes them to various risks which impact their risk appetite and behaviour. Using annual panel data for the period 2010 to 2019, this paper examines the determinants of risk-taking behaviours of banks within the African context. The study sampled 45 listed banks from African nations that have adopted the Basel III regulatory requirements and used the random effect estimator to fit the static panel data models established for the study. The study shows that minimum capital requirements, capital buffer premium and profitability were significant determinants of the risk-taking behaviour of the African banks. However, compared to other variables, the minimum capital requirement remained the most important factor in terms of determining the risk-taking behaviour of the selected African banks. This is because the minimum capital requirement determining measure is more significant across the three measures of the risk-taking behaviour of the African banks compared to others. The study recommends that African banks should establish risk limits, improve risk identification, and establish a platform for bank stress testing by using the key determinants of risk-taking behaviour in making strategic business decisions.

The Impact of Bank Regulation on Bank Performance: A Novel Analysis of the Pre-Covid Era with Cross-Country Evidence

Banks play a pivotal role in all economies by bringing balance to the economic flows of surplus and deficit. As a result of this, they are heavily regulated by national and globally accepted regulations such as the Basel III Accord. This research aims to ascertain the impact of the prudential Basel III regulations on the financial performance of selected listed African banks before the advent of Covid-19. The study used the fixed effects and random effect estimator to fit the static panel data established for the study. A panel of 45 listed banks from six African nations were used, covering the period from 2010 to 2019. The study concludes that the adoption of tighter and higher Basel III regulatory requirements has a double-edged-two-face implication on African banks’ financial performance. This conclusion is based on the findings that the capital adequacy ratio has a positive effect on the financial performance of African banks while the liquidity and minimum capital requirement have a negative effect.

Labor and infrastructure factors affecting provincial distribution of foreign direct investment in Vietnam

The study assesses the influence of labor and infrastructure on attracting foreign direct investment (FDI) to the provinces of Vietnam in the period of 2009 - 2020. Research results from linear regression model and random effects estimation method have confirmed the importance of human capital and infrastructure in attracting FDI. The labor-related aspects in this study confirm that tendency of MNEs focusing on labor-intensive industries in Vietnam has not changed. The study also provides policy implications as building and improving the quality of infrastructure with the main goal of reducing inequality in attracting more FDI inflows to Vietnam's provinces in the near future. In addition, the workforce needs to have a plan to prepare themselves with solid knowledge and necessary skills to hone and absorb the know-how transferred from foreign investment companies, to have an ability to contribute to the development of the quality of our country's human resources.

Fiscal Decentralisation, Provincial Economic Growth and Spillover Effects: A Spatial Panel Data Analysis

This study examines the spatial dependence, direct and indirect effects of fiscal decentralisation on the provincial economic growth of Pakistan. Due to spatial dependence, spatial econometric technique is applied on the augmented growth of Mankiw, et al. (1992) by incorporating the fiscal decentralisation variable in the theoretical framework. The empirical analysis is based on the spatial panel data set, which is used from 1990 to 2011 of provinces. Model is selected on basis of specific to general and general to specific approach, and decided two-way fixed effects Spatial Durbin model (SDM) is appropriate for our data. We have estimated the SDM by maximum likelihood (bias corrected and random effect) estimation technique, otherwise, if we applied OLS and ignore the spillover effect which makes our estimated parameters biased and inconsistent. Results show that revenue decentralisation has positive, while expenditure decentralisation has negative effect to provincial economic growth. Spillover effects are found to be significant in case of revenue decentralisation and insignificant in case of expenditure. Negative and insignificant spillover effect of expenditure decentralisation is due to weak institutions, lack of intra governmental competition, and absence of political vision which may increase the level of corruption and less accountability. On the basis of econometric analysis, it may be suggested that federal government should transfer the resources to provinces as determined in the 18th amendment, and it is the responsibility of provincial government to train their officials in the area of professional ethics, technical and administrative skills by different programmes. JEL Classification: C31, C33, H3, H50 Keywords: Fiscal Decentralisation, Spatial Econometrics, Revenue, Expenditure

Prevalence of underweight in people with severe mental illness: Systematic review and meta‐analysis

AbstractPeople with severe mental illness (SMI) have a higher prevalence of obesity as compared with the general population, however, there is mixed evidence about the prevalence of underweight. Thus, the aim of this study is to determine the pooled prevalence of underweight in people with SMI and its association with socio‐demographic factors; and to compare the prevalence of underweight between SMI and the general population. MEDLINE, PsycINFO, and EMBASE databases were searched to identify observational studies assessing the prevalence of underweight in adults with SMI (schizophrenia, major depressive disorder with psychotic features, and bipolar disorders). Screening, data extraction, and risk of bias assessments were performed independently by two co‐authors, with disagreements resolved by consensus. Random effect estimates for the pooled prevalence of underweight and the pooled odds of underweight in people with SMI compared with the general population were calculated. Subgroup analyses were conducted for the type of SMI, setting, antipsychotic medication, region of the world, World Bank country income classification, data collection, and sex. Forty estimates from 22 countries were included. The pooled prevalence of underweight in people with SMI was 3.8% (95% confidence interval [CI] = 2.9–5.0). People with SMI were less likely to be underweight than the general population (odds ratio [OR] 0.65; 95% CI = 0.4–1.0). The pooled prevalence of underweight in SMI in South Asia was 7.5% (95% CI = 5.8–14.1) followed by Europe and Central Asia at 5.2% (95% CI = 3.2–8.1) and North America at 1.8% (95% CI = 1.2–2.6). People with SMI have lower odds of being underweight compared to the general population. People with schizophrenia had the highest prevalence of underweight compared to other types of SMI. Japan and South Asia have the highest prevalence of underweight in people with SMI.

Bayesian variable selection and estimation in multivariate skew-normal generalized partial linear mixed models for longitudinal data

This paper proposes a novel generalized partial linear mixed models (GPLMMs) with the random effects distribution distributed as a multivariate skew-normal distribution for discrete longitudinal data over time. Under the Bayesian framework, we extended the Bayesian version of adaptive lasso (least absolute shrinkage and selection operator) for linear regression to the Bayesian adaptive lasso with the least squares approximation (LSA) method for generalized partial linear mixed models. A hybrid algorithm combining the Gibbs sampler and the Metropolis-Hastings algorithm in conjunction with the Bayesian adaptive lasso with LSA is used to simultaneously obtain the Bayesian estimates of unknown parameters, smoothing function and random effects, as well as select important covariates in GPLMMs. Several simulation studies and a real example are presented to illustrate the proposed methodologies.

Bayesian learners in gradient boosting for linear mixed models.

Selection of relevant fixed and random effects without prior choices made from possibly insufficient theory is important in mixed models. Inference with current boosting techniques suffers from biased estimates of random effects and the inflexibility of random effects selection. This paper proposes a new inference method "BayesBoost" that integrates a Bayesian learner into gradient boosting with simultaneous estimation and selection of fixed and random effects in linear mixed models. The method introduces a novel selection strategy for random effects, which allows for computationally fast selection of random slopes even in high-dimensional data structures. Additionally, the new method not only overcomes the shortcomings of Bayesian inference in giving precise and unambiguous guidelines for the selection of covariates by benefiting from boosting techniques, but also provides Bayesian ways to construct estimators for the precision of parameters such as variance components or credible intervals, which are not available in conventional boosting frameworks. The effectiveness of the new approach can be observed via simulation and in a real-world application.

Factors Influencing Capital Structure: An Empirical Evaluation of Major Oil and Gas Producing Companies Operating in Ghana

A company's choice of capital structure determines how successfully it will operate. This choice heavily depends on the understanding and optimisation of the capital structure factors necessary to increase industry-specific profitability and, consequently, market value. Therefore, the goal of this study is to analyse the factors that determine the capital structure of six significant oil producing companies operating in Ghana, namely: Hess Corporation, Kosmos Energy, Tullow Oil and Ghana National Petroleum Company from 2010 to 2018. In the analysis of panel data for this study, random effect estimation is used. Size, liquidity, tangibility, crude oil price, and profitability are used in conjunction with pertinent literature to describe the factors that determine capital structure, which is proxied by the debt-to-capitalisation ratio (leverage). The findings demonstrated that profitability, firm size, crude oil price, and liquidity are major capital structure factors that have a markedly adverse connection with leverage. The main finding of this study implies that, in accordance with the pecking order theory, consideration of debt may ultimately be the last resort, whereas the management of these major oil and gas companies in Ghana must exercise discretion when considering funding based on debt and rely more on generated profits (retained earnings) and shareholder equity. Appropriate crude oil price hedging instruments are recommended to minimise the impact of commodity price volatility on decisions on capital structure strategies.

Trajectories of cognitive performance in late middle‐aged adults: Bayesian random change point mixed model analysis in WRAP

AbstractBackgroundPrevious studies indicate that rates of cognitive decline in Alzheimer’s disease (AD) and other dementias may accelerate significantly as brain pathology increases. The objectives of this study included to: 1) characterize changepoints and related slope parameters across four cognitive composites in a longitudinal cohort study; and 2) examine how these parameters varied across predictors of interest.MethodsDementia‐free participants at baseline from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) with &gt; = 3 cognitive assessments were eligible (n≈1071; mean(sd) baseline age = 58.4(6.4)). We used newly‐developed Bayesian random change point mixed models (BRCPMM) to estimate fixed (group‐level) and random (person‐level) change points (CPs), slopes pre‐ and post‐CP, and intercepts at CP for four cognitive composites: three‐test preclinical Alzheimer’s cognitive composite (PACC3; primary outcome), immediate learning, delayed learning, and executive function. We used non‐parametric statistics to test whether PACC3 estimates differed by: last cognitive status observed (cognitively unimpaired‐stable or ‐declining (CU‐S, CU‐D), MCI, and dementia); sex/gender, and APOE‐e4 carrier status.ResultsPosterior median fixed and random effect estimates (corresponding 95% credible intervals from 20000 BRCPMM runs) are summarized in Table 1 by outcome. The PACC3 group‐level CP was earliest at ∼75.56 [72.98,78.44] years old with 95% of individuals hitting CP between 59.69 and 91.86. Timing of CP was significantly associated with last observed cognitive status (Table 2); those 37 (3.46%) progressing to MCI/dementia had estimated CP’s before or during study participation while those remaining unimpaired had estimated CP’s after their last visit. All random effects (person‐level) PACC3 estimates differed by worst cognitive status (Figure_1) and sex/gender (Figure_2). For example, while the CU‐D and MCI groups had similar slopes before CP, CP occurred earlier, estimated PACC3 at CP was lower, and post‐CP slope was worse in the MCI group compared to CU‐D (Figure_1). APOE‐e4 random‐effects estimates differed by CP and post‐CP slopes (Figure 3).ConclusionsThe timing and rates of change in different cognitive composites differ by cognitive status, gender, and APOE‐e4 status. Predicting individual cognition trajectories and change points may provide an opportunity for early intervention by diagnosing high‐risk subjects at the right time for treatment and/or enrollment in a clinical trial.

Information and Communication Technology Adoption and Life Insurance Market Development: Evidence from Sub-Saharan Africa

As part of the Fourth Industrial Revolution (4IR), blockchain, fintech (financial technology), and insurtech (insurance technology) are some innovations that have been rolled out in the financial landscape and have captured the imaginations of policymakers and scholars alike. The African continent lags in embracing technology and is still grappling with financial access and enhancing financial inclusion. As such, it is bewildering whether African insurance markets are at a stage where they can leverage the possibilities offered by the 4IR. Against this backdrop, the aim of the study was to investigate whether information communication technology (ICT) adoption influences the development of African life insurance markets. We utilised a sample of 31 sub-Saharan African countries for the period 2005–2020. Panel data techniques were employed, and the pooled ordinary least squares, fixed effects, and random effect estimators were used to test the relationship between life insurance density and the measures for ICT adoption (proxied by fixed telephones, internet use, mobile cellular telephones, and broadband) as well as financial freedom being the control variable. We found that the life insurance market development variable was positively related to three of the four ICT adoption variables, namely, fixed telephone, mobile cellular telephone, and broadband. Further, the life insurance market development variable is positively related to the financial freedom variable. These findings suggest that ICT adoption fosters the development of the life insurance market in Africa. The findings also lend credence to the view that the degrees of financial freedom of insurance companies (who are unencumbered by regulations) have a bearing on the levels of insurance sales and, hence, promote life insurance access in Africa. The policy imperatives that flow from this study are that African governments must ensure that they (1) institute ICT adoption-friendly policies and (2) regulate the life insurance sector optimally, in order to foster the development of their life insurance sectors.

The influence of social and commercial pension insurance differences and social capital on the mental health of older adults-Microdata from China.

The number of older adults is rising rapidly in China. Various concerns such as chronic diseases, financial inadequacy, and a feeling of loneliness have adversely affected the mental health of older adults, and this has become an important public health and social issue. To realize healthy aging, the Nineteenth National People's Congress of China put forth the Healthy China strategy, speeding up the promotion activities of mental health and pension measures, carrying out public welfare pension insurance for the entire population, and contributing to the mental health of older adults. This study used data from China Family Panel Studies. This study mainly uses the random effect estimation method (random effect, RE) and the feasible generalized least squares estimation method (FGLS) to control for heterogeneity to explore the impact of social and commercial pension insurance on the mental health of older adults, the moderating effect of social capital on pension insurance, and the mental health of older adults. The results showed that social pension insurance is proportional to the mental health of older adults, whereas commercial pension insurance is inversely proportional to mental health. Social capital had a significant moderating effect on pension insurance. When a country develops an aging economy, the emphasis on social capital helps make targeted industrial development suggestions. The government's expansion of insurance coverage is crucial for improving the mental health of older adults.

The Association Between Overweight or Obesity and the Risk of Uterine Leiomyoma: A Meta-Analysis

Aim: The present study is a meta-analysis to identify the relationship between BMI and uterine leiomyoma. Methods: The major international databases PubMed, Scopus, and Web of Sciences (WOS) were searched to identify eligible studies in English language writing from their inception to 30 of June 2019. The pooled Odds Ratios (OR), Relative Ratio (RR), and 95% Confidence Intervals (CI) were calculated as random effect estimates of association among studies. The findings of 10 studies showed an increased risk of uterine leiomyoma in the overweight and obese women compared to women with normal weight: RR=1.21 (95% CI: 1.12, 1.30) and OR=1.50 (95% CI: 1.29, 1.71) for overweight women and RR=1.34 (95% CI: 1.11, 1.57) and OR=1.99 (95% CI: 1.11, 2.87) for obese women. Result: Our meta-analysis suggests that obesity and overweight in women are associated with an increase in the risk of uterine leiomyoma. Conclusion: Therefore, clinical attention to uterine leiomyoma should be more performed, because leiomyoma can be a source of mortality in women.

Panel data analysis of profitability and employment growth of medium and large size industries in Ethiopia

Manufacturing industries are an asset or value added part of an economy, intimately linked with industrial and engineering design, and engaged in producing significant economic productions that can assist the national growth and development. The aim of the study was to estimate the profitability and employment growth of medium and large size industries in Ethiopia. The variables were chosen based on theoretical and experimental literature findings. In this study, an explanatory study design was implemented in carrying out this research with the prearrangement of secondary data collected from the panel data set of medium and large size manufacturing industries conducted annually by the central statistics agency over the period 2002–2011 E.C. The study employed panel data estimation methods to analyze the influence of medium and large size manufacturing industries on profitability and employment growth. Three panel data models are used: pooled ordinary least squares, fixed effect, and random effect estimation method. The Hausman test revealed the random model was the best fit for both profitability and employment growth. The diagnosticstest: normality, multicollinearity, heteroscedasticity, and autocorrelation tests were conducted on the data. The results obtained indicate that employment growth and profitability in Ethiopia are generally driven by medium and large-size manufacturing industries. The random model result shows that ownership, firm-size, advertising intensity and import intensity have a positive influence and substantial effect on profitability. But, the government has significant effect and a negative influence on profitability. The random model shows that government, advertising intensity and firm-size have significant effect and positive influence on employment growth. Nevertheless, import has significant effect and a negative influence on employment growth. Eventually, the employment growth and profitability have a positive influence and insignificant effect and the authors suggested further research in the areas by taking into account additional variables and newly emerging industries.

The The Effects of Annual GDP growth on Consumption Spending: Evidence from West African Countries

This study examines the effect of annual growth in gross domestic product on consumption spending in the West African Countries from the period 2005 to 2020. Consumption has been a fundamental driver of economic growth, and the insufficient consumption spending will lure firms to lay off workers which can lead to short run fluctuation in the economy. The study employed a dynamic panel model with a set of estimation strategies such as fixed and random effect, Anderson and Hsiao (1982) estimation, difference and System-Generalized Methods of Moment and Least Square Dummy Variable estimation methods to correctly assess how annual GDP growth affect consumption spending in these countries including additional variables such as, Lag consumption spending, foreign direct investment, consumer prices as a measure of inflation and a vector of control such as capital formation and annual population growth. The study found that annual GDP growth and Foreign direct investment has a significant impact on increasing consumption spending thus annual GDP growth is the most crucial factor for increasing consumption spending in these countries. Moreover, lagged consumption spending is also found to have a negative significantly effect in reducing current consumption spending while gross capital formation and annual population growth are found to have an insignificant effect in reducing consumption spending in all the estimates except in the Anderson and Hsiao (1982) estimation method which shows a positive relationship with consumption spending.

결측 종단자료의 분석에서 가중치가 3수준 다층성장모형의 모수추정량에 미치는 영향

This study seeks to clarify the effect of weighting on the fixed effect and random effect parameter estimators of the 3-level growth model. This study considered five weighting methods; ① non-weighting, ② sampling weighting, ③ longitudinal weighting, ④ multi-level weighting, ⑤ scaled multi-level weighting. The simulation study was conducted to statistically reveal the effect of weighting methods on the parameter estimation of the multi-level growth model. For the study, population, sampling data, and missing longitudinal data were each generated. The parameters of the 3-level growth model were estimated for each of the five weighting conditions using the missing longitudinal data. All conditions were repeated 100 times. The properties of the estimator were evaluated with bias, relative bias, and RMSE(root mean square error) from the viewpoint of bias and efficiency. The result is as follows. First, all fixed and random effects parameters were estimated inconsistently when non-weights or scaled multi-level weights were used in the 3-level growth model. Second, the 3-level growth model had the highest efficiency of fixed-effect and random-effect parameter estimators when non-weights or scaled multi-level weights were used. Based on the above results, suggestions for researchers and follow-up studies were presented.

Association between frequency of mass media exposure and maternal health care service utilization among women in sub-Saharan Africa: Implications for tailored health communication and education.

IntroductionAwareness creation through mass media has the potential to promoted positive behaviors and discourage negative health-related behaviors through direct and indirect pathways. In this study, we examined the association between exposure to mass media and maternal health care services utilization among women in sub-Saharan Africa.MethodsWe used data from the recent Demographic and Health Surveys (DHS) conducted between 2010 and 2020. A total of 28 countries with a survey dataset within 2010–2020 were included in our study. We included 199,146 women who had ever had a pregnancy in the last five years preceding the survey. Weighting was applied. Multilevel mixed-effect models were considered to account for cluster-level variations and correct inferences. Fixed and random effects estimates were reported. Adjusted odds ratio (aOR) with their 95% confidence intervals (CIs) were used to present the results. Also, we presented the random intercept variations, intraclass correlation coefficient, and model fitness.ResultsWomen who listened to radio at least once every week (aOR = 1.11, 95% CI = 1.07,1.15) were more likely to attend ANC as against those who did not listen to radio at all. Also, women who watched television at least once a week (aOR = 1.39, 95% CI = 1.33,1.46) were more likely to attend ANC compared to those who did not watch television at all. Women who read newspaper/magazine at least once a week (aOR = 1.27, 95% CI = 1.14,1.41); listened to radio at least once a week (aOR = 1.12, 95% CI = 1.07,1.17); and watched television at least once a week (aOR = 1.32, 95% CI = 1.24,1.40), were more likely to utilize SBA than those who did not read newspaper/magazine; listen to radio; and watch television at all. Women who read newspaper/magazine at least once a week (aOR = 1.35, 95% CI = 1.27,1.45); listened to radio at least once a week (aOR = 1.37, 95% CI = 1.32,1.42); and watched television at least once a week (aOR = 1.39, 95% CI = 1.32,1.47) were more likely to utilize PNC compared to those who did not.ConclusionsThe study identified a strong positive relationship between mass media exposure and maternal health care services utilization. Specifically, exposure to radio and television were positively associated with ANC visitations. Moreover, exposure to mass media (newspaper/magazine, radio and television) were positively associated with SBA and PNC utilization. Policymakers and other non-governmental organizations should continuously invest resources in the design and implementation of maternal health service utilization educational programs through all the mass media channels to scale up women’s maternal health service services utilization uptake in sub-Saharan Africa.