Inequalities In Health Status Research Articles

Health and socioeconomic development and morbidity: A district case in Indonesia

There was a substantial inequality in health status across districts in Indonesia. The purpose of this study was to examine the association between health and socioeconomic development and morbidity in districts in Indonesia. The data used came from the Indonesia Database Policy and Economic Research (INDO-DAPOER) of the World Bank. The unit analysis was district. The observation period was 2011 and 2014. Multiple regression analysis was employed to study the impacts of health and socioeconomic development on morbidity in districts in Indonesia. The dependent variable was the morbidity rate. The health and socioeconomic development variables included the time, number of medical doctors, number of health centres and its line services, monthly per capita household health expenditure, and access to safe sanitation. The results of the study indicate that, in districts in Indonesia, lower morbidity rate was significantly associated with increasing time, higher number of medical doctor, higher number of health centres and its line services, higher monthly per capita household health expenditure, and higher access to safe sanitation. These results imply that to reduce morbidity rate, the regional governments in Indonesia should improve their health and socioeconomic development.

Describing the health-related quality of life of Māori adults in Aotearoa me Te Waipounamu (New Zealand)

PurposeIn Aotearoa me Te Waipounamu (New Zealand; NZ) there are considerable inequities in health status and outcomes for Māori, the Indigenous peoples of NZ. It is therefore important that the health status and preferences of Māori are specifically considered in healthcare policy and decision making. This paper describes the health-related quality of life of 390 Māori adults who took part in the NZ EQ-5D-5L valuation study.MethodsResponses on the five dimensions of the EQ-5D-5L were dichotomised into “no problems” and “any problems”, summarised and disaggregated by age group. Mean preference weights were reported by age group and overall. Mean utility values (calculated by applying each participant’s preference weights to their EQ-5D-5L profile) were summed and respective means and standard deviations reported by age, chronic disease status and disability.ResultsThe EQ-5D-5L dimensions with the highest proportion of participants reporting any problems were pain/discomfort (61.5%) and anxiety/depression (50%). The most commonly-reported chronic disease was mental illness/distress (24.6%). Anxiety/depression ranked as the most important dimension, with usual activities, the least important. The mean utility value was 0.83 with the lowest value (0.79) found in the 18–24 and 45–54 age groups. For participants with at least one chronic disease the mean utility value was 0.76 compared to 0.91 for those with none.ConclusionTo reduce inequities experienced by Māori it is crucial that the health status of Māori and the values Māori place on health-related quality of life are properly understood. This can only be achieved using Māori-specific data.

Health-related quality of life variation by socioeconomic status: Evidence from an Iranian population-based study.

Health-Related Quality of Life (HRQoL) values based on the accurate and reliable European Quality of Life Five Dimension (EQ-5D) questionnaire gives health-state utilities as a helpful data set for studying socio-demographic and socio-economic inequalities in health status in the general population. We aimed to do a population-based study to see how HRQoL varies by socio-demographics and socioeconomic status (SES). The study was a cross-sectional population-based study in Shiraz, Iran's southwest. Data was gathered utilizing a personal digital assistant (PDA). A trained interviewer administered the EQ-5D questionnaire to a representative sample of 1036 inhabitants. Principal component analysis (PCA) was used to create SES indices. Because of the skewed distribution, quantile regression was utilized to model the quartiles of HRQoL values. STATA 12.0 was used to perform all statistical analyses. P <0.05 was considered statistically significant. In 1036 study respondents, women had a mean HRQoL of 0.67 ± 0.28, whereas men had a mean HRQoL of 0.78 ± 0.25. Gender and age remained significant in all quartiles of HRQoL value. Participants with insurance showed 0.14 and 0.08 higher HRQoL values in the first and second HRQoL quartiles than those without coverage, respectively. Education [95% CI: 0.034, 0.111)], economy [95% CI: 0.013, 0.077], and assets [95% CI: 0.003, 0.069] all had an impact on HRQoL value in the lowest quintile. In all quartiles of HRQoL value, women had lower reported HRQoL than men. Insurance programs aimed at more disadvantaged groups with poorer HRQoL may help to minimize inequity. Education, economics, and assets all had an impact on the lower quartiles of HRQoL value, emphasizing the importance of general policies in determining public health status.

Sociodemographic and health status differences in delaying medical care during the COVID-19 pandemic among older adults: findings from the Health and Retirement Study

BackgroundDuring the COVID-19 Pandemic, adults in the United States reported delaying medical care, which may be tied risk of infection and local policies limiting appointment. Some populations may have been more likely to delay care than others, leading to other forms of health inequality during this period. To-date there is little research on delayed care among U.S. older adult. We determine the prevalence of delayed medical care among older adults and investigate sociodemographic and health status inequalities in delaying health care.MethodWe used data from the first public release of the nationally representative Health and Retirement Study COVID-19 Subsample (N = 3006). Using logistic regression, we assessed whether differences in delaying health care varied by age, sex, race/ethnicity, education, self-rated health (SRH), and having any Activity of Daily Living (ADL) limitation. We also conducted additional analysis that evaluated differences in delaying care by two care subtypes: doctor and dental care visits.ResultsAbout 30% of U.S. older adults reported delaying care with the most common types of delayed care being dental or doctor visits. Adults ages 75 and older were less likely to delay care, while women, college educated, and those with poor SRH, and any ADL limitations were more likely to delay care.ConclusionsNearly one-third of older adults delayed care during the COVID-19 pandemic. The increased likelihood of delayed care among people with worse health suggests that there may be longer-term impacts on the health care system and population health from the COVID-19 pandemic, and may contribute to health inequalities in the near future.

Health Inequalities in the Elderly with Different Socioeconomic Status in China

This study aims to examine socioeconomic inequalities in health status and health service of the elderly in China to provide basis for health promotion. The data of China Health and Retirement Longitudinal Study (CHRLS) in the year 2015 was used. Adults aged 60 and over (n=8001) were included in the analytic sample. Socioeconomic status (SES) of the elderly was assessed by annual per capita consumption expenditure, education, and regional and rural/ urban status. Health status was measured by self-rated health, activities of daily living (ADL), the prevalence rate of chronic diseases and the 1-month prevalence rate; while health service was measured by the utilization of both outpatient service and inpatient service. Overall, the elderly with higher economic level had better health status and higher ADL disability rate, but lower prevalence rate of chronic diseases, 1-month outpatient visit rate and annual hospitalization rate. The elderly with lower education level had higher self-rated "poor" health, ADL disability rate, 1-month prevalence rate and 1-month non-visit rate. The elderly in eastern region or urban areas had better health status than those in central and western regions or rural areas. However, for health service utilization, the elderly in western region used both outpatient and inpatient services more frequently. The rural elderly had higher 1-month outpatient visit rate, while the urban elderly had higher annual hospitalization rate. Socioeconomic inequalities in health existed in Chinese elderly. To promote health equity among the elderly, the government should improve health insurance and medical assistance policies, optimize health resources allocation, and narrow economic gaps between western and eastern regions, and between rural and urban areas.

Socioeconomic inequalities in health status and survival: a cohort study in Rome

ObjectivesTo analyse the association between individual and contextual socioeconomic position (SEP) with health status and to investigate the role of SEP and baseline health status on survival.DesignCross-sectional and cohort study.SettingRome,...

Socioeconomic status and self-rated health in Iran: findings from a general population study

BackgroundThere are large gaps in health and well-being among different groups of the society. Socioeconomic factors play a significant role in determining the health status of the society. The present study was conducted to examine socioeconomic inequality in health status among the adult population of Khorramabad city, the capital of Lorestan province, wester part of Iran.MethodsA cross-sectional study was conducted on 1348 participants selected through multistage sampling. A valid and reliable questionnaire was used for data collection. The wealth index as an indicator of the socioeconomic status (SES) was used to categorize the subjects in terms of the SES. The concentration index and concentration curve was used to measure socioeconomic inequity in poor self-rated health (SRH) of population. Finally, after determine the status of inequity in poor SRH, a decomposition analysis approach was used to identify the most important determinants of this inequity.ResultsThe prevalence of poor SRH was 18.91% in all subjects, 38.52% in the lowest SES group, and 11.15% in the highest SES group. The value of the concentration index for poor SRH was − 0.3243 (95% CI − 0.3996 to − 0.2490), indicating that poor SRH was more concentrated among the poor. The results of decomposition analysis showed that SES (41.2%), higher body mass index (28.6%) and lack of physical activity (26.9%) were the most important factors associated with the concentration of poor SRH in the poor groups.ConclusionIdentification of socioeconomic factors affecting on health status is the first step for proper policymaking. Policymakers and health system managers at the national and subnational levels can use the results of this study as well as other similar domestic studies to design and implement proper interventions to promote equity and improve the health status of population.

Health care utilization and expenditure inequities in India: Benefit incidence analysis

BackgroundThe transition from Millennium Development Goals to Sustainable Development Goals 2030 has yet again emphasized on the unfinished agenda of achieving efficient and equitable health systems and universal health coverage. With trifling public spending on healthcare and insignificant insurance coverage, India has recorded 55 million people descending below the poverty line in one year due to healthcare payments. Not only are these health-related payments impoverishing but also the burden of seeking care is disproportionately skewed towards deprived population groups. Against this backdrop, the present paper examines the inequality in health status, utilization of health care services, and financial risk protection. The study is further complemented by assessing who benefits from public subsidies across different economic quintiles and as per epidemiological transition level (ETL) of states. MethodsThis study used data nationwide National Sample Survey 75th round data. We perform the Benefit Incidence Analysis (BIA) using concentration indices, concentration curve, and poor-rich equity ratio to measure horizontal and vertical inequity and analyze the redistribution dimension to understand which population segment benefits more from public subsidies. ResultsFindings suggest that high out of pocket (OOP) spending on inpatient care, especially in the private sector resulted in lower utilization of health care services especially among marginalized communities. Seeking care for marginalized sub-groups is dilapidating in two major ways-, on one hand, it exhausts all their income/savings for the treatment. On the other, as a result of incapacitation, families lose their daily income. The present analysis finds a higher unmet need for treatment in the poor, and the reasons commonly reported were pertaining to affordability, availability and accessibility. The results also showed that low ETL states faced a higher percentage of catastrophic expenditure vis-à-vis other states, thereby; stressing health system reforms beyond the “one-size-fits-all” strategy. ConclusionsIt is imperative that both Central and State Governments should work together to strengthen the public healthcare system to ensure accessibility and quality of care. Central Government's Pradhan Mantri Jan Arogya Yojana (PM-JAY) health insurance program is a positive step forward to address the healthcare needs of deprived population subgroups.

Gender Inequalities in Health Status and Service Utilization of Migrant Workers in Three Large Industrial Zones of Vietnam

Gender Inequalities in Health Status and Service Utilization of Migrant Workers in Three Large Industrial Zones of Vietnam

Healthcare in Pregnancy and Access to Midwives according to Socio-Economic Situation: An Analysis with Routine Data from BARMER Health Insurance

Socio-economic status is an important cause of inequality in health status and access to healthcare. This also applies to pregnancy, birth and the postpartum period. Healthcare during pregnancy plays a crucial role in the success of the life phase around birth. On the basis of routine data from BARMER health insurance, the study investigated which services pregnant women received during pregnancy depending on their socio-economic situation. The study population comprised 237,251 women insured with BARMER with 278,237 births in 2015-2019. The services billed by gynaecologists and midwives during pregnancy were considered in relation to the socio-economic situation of the women involved. Physicians dominated the provision of preventive healthcare. For almost 98% of the pregnant women, a medical preventive healthcare flat rate was billed in at least three quarters. A regular participation of the midwife in preventive healthcare from the fourth month of pregnancy with more than four preventive services was the case in only 1.2% of women. Women from low-income backgrounds received fewer antenatal healthcare services from both gynaecologists and midwives, with 31% of women with low income having no antenatal midwife contact at all, compared to only 11% of high-income women. High-income earning women were also more likely to have had early contact with a midwife (47 vs. 37% in the first trimester). The timing of the first contact seemed to be relevant for the subsequent cooperative antenatal healthcare by both professional groups. The potentials of midwifery healthcare are not being leveraged. Midwives should be significantly more involved in prenatal healthcare overall, and access to midwives must be improved, especially for socially disadvantaged women. These women could benefit in particular from midwifery healthcare, as it takes greater account of social aspects in healthcare and also provides outreach services.

Inequalities in Health: Methodological Approaches to Spatial Differentiation

The prevalence of inequalities in the general health position of communities can be assessed by using selected determinants. The aims of this article are three-fold: (1) to apply a comprehensive approach to the assessment of inequalities in the general health position of communities, (2) to determine the spatial differentiation of determinants, and (3) to present selected assessment methods and their impact on the results. To present a quantitative assessment of these inequalities in health status in communities, a composite indicator (Health Index) was developed. This Health Index is composed of 8 areas of evaluation and 60 indicators which include, amongst others, determinants of health status and healthcare at district level (LAU 1) in the Czech Republic. The data are evaluated using multicriteria decision-making methods (the WSA and TOPSIS methods). Findings suggest that, when all eight domains are assigned the same weight of one, the spatial differentiation among the districts is similar when using both methods. If different weightings are assigned to the districts, changes occur in both the index values and the rankings of the analyzed districts. For example, the allocation of weightings in both methods results in a rearrangement of the ranking of districts for which the Health Index is around the average.

Burden of disease induced by public overexposure to solar ultraviolet radiation (SUVR) at the national and subnational levels in Iran, 2005–2019

Estimating the burden of diseases induced by overexposure to solar ultraviolet radiation (SUVR) can help to prioritize environmental health interventions. The age-sex specific and cause-specific mortality and disability-adjusted life years (DALYs) attributable to overexposure to SUVR at the national and subnational levels in Iran, 2005–2019 were estimated. The burden of disease induced by overexposure to SUVR was quantified in four steps as follows: (1) estimating exposure to SUVR, (2) estimating total incidences and deaths of target causes, (3) assessing population attributable fractions of the target causes for the SUVR, and (4) calculating the attributable burden of disease. The attributable DALYs, deaths, age-standardized DALY rate, and age-standardized death rate at the national level were determined to be respectively 21896, 252, 42.59, and 0.56 in 2005 and were respectively changed to 28665, 377, 38.76, and 0.53 in 2019. The contributions of causes in the attributable DALYs at the national level were different by year and sex and for both sexes in 2019 were as follows: 46.15% for cataract, 20.36% for malignant skin melanoma, 16.07% for sunburn, 12.41% for squamous-cell carcinoma, and 5.01% for the other five causes. The contributions of population growth, population ageing, risk exposure, and risk-deleted DALY rate in the temporal variations of the attributable burden of disease in the country were +20.73%, +20.68%, +2.01%, and −12.51%. The highest and lowest provincial attributable age-standardized DALY rates in 2019 were observed in Fars (46.8) and Ardebil (32.7), respectively. The burden of disease induced by exposure to SUVR caused relatively low geographical inequality in health status in Iran. Due to increasing trends of the SUVR as well as the attributable burden of disease, the preventive interventions against the SUVR overexposure should be considered in the public health action plan all across the country.

A decomposition analysis for socioeconomic inequalities in health status associated with the COVID-19 diagnosis and related symptoms during Brazil's first wave of infections

Recent studies have shown that COVID-19 affects different population groups asymmetrically. This work uses data from the National Survey of Households—PNAD COVID-19/IBGE—to quantify the socioeconomic inequality in health during the first wave of COVID-19 infections in Brazil. We use the concentration curve, the concentration index, and a decomposition analysis to verify the factors that most influence the inequalities in the specified health variables. We find a positive concentration index for the incidence rate, indicating a greater concentration of diagnoses (number of tests) among groups with higher income levels. When considering symptoms similar to a COVID-19 infection, inequality practically disappears. Among people with higher income, a pre-existing disease has a more significant contribution to the concentration of COVID-19 in the presence of correlated symptoms than in its diagnosis. Tests of dominance support the findings. Moreover, the decomposition results show that if the inequalities were explained only by race (non-white) and place of living (North and Northeast), there would be a concentration of COVID-19 among the poorest.

Buckets Inequitably Filled by Our Shared Histories.

The COVID-19 pandemic has disproportionately affected patients of color and illuminates long-standing inequity in health status, health outcomes, and access to health care. Maldistribution of burden of disease, risk exposure, and how vulnerable we are to our lives unraveling is not merely unfortunate, not simply due to a bad turn of the cosmic wheel, but unjust, as illustrated in this digital self-portrait.

Abstract 16752: Cumulative Social Determinant of Health Risk Score and Prevalent Atherosclerotic CVD Among National Representative Adult Population in US

Introduction: Social determinants of health (SDOH) are contextual factors and shared experiences that impact an individual’s life and health. Unfavorable SDOH are recognized as a major source of excess cardiovascular disease (CVD) risk; however, prior studies have focused on restricted sets of SDOH domains. We aimed to assess the burden of multiple unfavorable SDOH at the population level, and the association between increasing cumulative burden of unfavorable SDOH features and atherosclerotic CVD (ASCVD) prevalence. Methods: Using a nationally-representative sample of 164,696 adults from the National Health Interview Survey (2013-17) we identified 39 parameters (classified as favorable or unfavorable) from the Healthy People 2020SDOH domains: Economic stability, Education, Food access, Neighborhood conditions, Social context, Health systems. An aggregate score of these features ranging 0-36 was then divided into quartiles-- the most unfavorable scores in the highest quartile. ASCVD was ascertained via self-report. Results: 15,758 individuals (8%), representing ~19.6 million Americans, had ASCVD and were more likely to experience economic instability, adverse neighborhood and social cohesion, psychologic distress, food scarcity, and significant cost and non-cost-related healthcare barriers than those without ASCVD. The age adjusted mean (SD) SDOH risk score among ASCVD vs non-ASCVD participants was 12.5 (0.13) vs 0.9 (0.03) respectively. We observed a graded increase in ASCVD prevalence with higher SDOH quartiles (Figure). In multivariate analyses, adults with highest SDOH scores had 2-fold higher odds of having ASCVD compared to those with lowest scores (Figure). Conclusions: In the US, aggregate SDOH risk significantly discriminate risk of prevalent ASCVD among US adults. Standardized SDOH risk scores have the potential to inform risk stratification models at the individual level for addressing avoidable social inequities in health status.

Rural-urban differences in health outcomes, healthcare use, and expenditures among older adults under universal health insurance in China.

Rural-urban inequalities in health status and access to care are a significant issue in China, especially among older adults. However, the rural-urban differences in health outcomes, healthcare use, and expenditures among insured elders following China's comprehensive healthcare reforms in 2009 remain unclear. Using the Chinese Longitudinal Healthy Longevity Surveys data containing a sample of 2,624 urban and 6,297 rural residents aged 65 and older, we performed multivariable regression analyses to determine rural-urban differences in physical and psychological functions, self-reported access to care, and healthcare expenditures, after adjusting for individual socio-demographic characteristics and health conditions. Nonparametric tests were used to evaluate the changes in rural-urban differences between 2011 and 2014. Compared to rural residents, urban residents were more dependent on activities of daily living (ADLs) and instrumental ADLs. Urban residents reported better adequate access to care, higher adjusted total expenditures for inpatient, outpatient, and total care, and higher adjusted out-of-pocket spending for outpatient and total care. However, rural residents had higher adjusted self-payment ratios for total care. Rural-urban differences in health outcomes, adequate access to care, and self-payment ratio significantly narrowed, but rural-urban differences in healthcare expenditures significantly increased from 2011 to 2014. Our findings revealed that although health and healthcare access improved for both rural and urban older adults in China between 2011 and 2014, rural-urban differences showed mixed trends. These findings provide empirical support for China's implementation of integrated rural and urban public health insurance systems, and further suggest that inequalities in healthcare resource distribution and economic development between rural and urban areas should be addressed to further reduce the rural-urban differences.

A crossectional investigation of the relationship between complementary health insurance and frequency of dental visits in 15 to 64\u2009years old of Tehran population, Iran, a secondary data analysis (urban HEART-2)

BackgroundThis study aimed to investigate the relationship between complementary health insurance and frequency of dental visits.MethodsThe present study was performed using the Urban Health Equity Assessment and Response Tool (Urban HEART). A cross-sectional study was conducted in Tehran (Iran) to assess inequalities in health status among different socioeconomic and ethnic groups, genders, geographical areas, and social determinants of health. Out of 20,320 records retrieved from the original study with dental information, 17,252 had both dental insurance and dental visit information. Complementary health insurance as the main independent variable had three categories (i.e., basic insurance, with complementary medical coverage, and with dental coverage). The frequency of dental visits during the last year as a dependent variable had also three categories (i.e., no visit, one, and two, or more dental visits in the last year). In this study, in addition to investigating the relationship between complementary health insurance and frequency of dental visits, potential covariates that may affect the mentioned relationship were evaluated in the regression model. Statistical analyses included simple and multiple multinomial logistic regression considering the sampling method and sampling weights.ResultsThe meanage of 17,252 participants (Tehran citizens) was 39.36 years; 49.4%were women, 86.0%hadonly basicinsurance, 7.2% had complementary medical insurance, and 6.8% had complementary dental insurance. Of all subjects, 43.8% reported no dental visit, 26.1% reported one, and 30.1% reportedtwoor more dental visits during the lastyear. The frequency of dental visits was lower in people who had basic insurance than others such that that odds ratio (OR) was 0.73 (p-value < 0.001) for one visit and 0.68 (p-value< 0.001) for two or more visits in the last year. The frequency of dental visits was also positively associated with dental brushing, toothpaste use, high educational level, being married, having more than 20 teeth, and having dental pain.ConclusionHaving dental insurance increases the frequency of dental visits but the association between dental insurance and dental visits was independently influenced by other predictors.

Health Inequality between Migrant and Non-Migrant Workers in an Industrial Zone of Vietnam.

Vietnam has experienced massive internal migration waves from rural to industrialized zones. However, little efforts have been made to understand differences in health conditions and health-related quality of life (HRQOL) between local and migrant industrial workers. This study aimed to examine the inequality in health status and HRQOL between these workers. We conducted a cross-sectional study of 289 Vietnamese workers at three industrial areas in Hanoi and Bac Ninh. Self-reported health status and HRQOL were measured using the EuroQOL-5 dimensions-5 levels (EQ-5D-5L) instrument. Sociodemographic, working, and environmental factors were also investigated. Overall, the mean EQ-5D index was 0.74 (SD = 0.21) and the average number of health problems in the last 12 months in our sample was 1.91 (SD = 1.63) problems. Migrant people had a lower EQ-5D index (β = −0.08, p < 0.01) and more health problems (β = 0.20, p < 0.05) compared to local workers. Those being male, working in the same posture more than 60 min, and exposed to more hazards at work were correlated with a lower EQ-5D index and higher number of health problems. The results highlighted inequalities in health status and HRQOL between migrant and local workers. Reinforcing regular health check-ups, ensuring sufficient protective equipment and working conditions may help improve the health outcomes of the workers.

Variance Estimation and Confidence Intervals for 11 Commonly Used Health Disparity Measures.

There is increased interest in eliminating health disparities in the United States and worldwide. Broadly defined, health disparities refer to preventable inequalities in health status, such as cancer to ethnicity, socioeconomic status, gender, education, environment, and geographic locations. To make informed health policy decisions, it is essential to precisely measure the magnitude of disparities and assess trends over time. The Health Disparities Calculator (HD*Calc) is free statistical software that calculates 11 commonly used measures of health disparities and provides corresponding 95% CIs for the 11 measures using either an analytic method or a Monte Carlo simulation-based method; however, the derivation of SEs and coverage properties of the CIs have not been formally evaluated. We used simulation studies to assess the coverage properties of these CIs. We have also conducted bias analyses for measures implemented in HD*Calc using age-adjusted cancer incidence rates from national, state, and county level SEER data. The results of these analyses indicate that HD*Calc should be used with caution to construct CIs for some health disparity measures when the proportion of zero event counts is greater than 25%.

Decomposing gender inequalities in self-assessed health status in Liberia

ABSTRACTBackground: Understanding the magnitude of inequalities and drivers for reducing gender-related health inequalities is crucial in developing countries. This is particularly the case for Liberia with its very high level of gender-related inequalities in health and health outcomes.Objective: This paper assesses the magnitude of gender health inequalities and the relative contribution of different factors to health inequality in Liberia.Methods: Data came from the Liberian Household Income Expenditure Survey 2014. A two stage sampling methodology was used and 4,104 households were randomly selected and interviewed. The main variable of interest is dichotomised, good versus poor self-assessed health. Gender-related health inequality is assessed using the Oaxaca–Blinder decomposition for non-linear models. The decomposition reveals the magnitude of inequality and contributions of different factors.Results: We found large gender disparities (0.054, p < 0.01) characterised by women disadvantages in health status. In addition, the gender health disparities are mostly pronounced in rural areas. About 54% of the gender inequalities in health status were explained by the differences in endowments. Equalizing access to information, wealth and utilization of mosquito nets would reduce the gender gaps by 44, 5 and 4%, respectively.Conclusions: Addressing gender health inequalities inter alia requires access to health information (i.e. electronic and print media), gender responsive interventions that improve wealth in key sectors (i.e. education, employment, social protection, housing, and other appropriate infrastructure). In addition, the government, private sector and civil society should ensure that the health sector provides access to quality mosquito nets and improved health services including preventive care in order to reduce disease burden.