Adherence to antihypertensives in the United States: A comparative meta-analysis of 23 million patients.

Adherence to antihypertensives is crucial for control of blood pressure. This study analyzed factors and interventions that could affect adherence to antihypertensives in the US. PubMed, Scopus, Web of Science, and Embase were searched on January 21, 2022 and December 25, 2023 for studies on the adherence to antihypertensives in the US. Nineteen studies and 23 545 747 patients were included in the analysis, which showed that adherence to antihypertensives was the highest among Whites (OR: 1.47, 95% CI 1.34-1.61 compared to African Americans). Employment status and sex were associated with insignificant differences in adherence rates. In contrast, marital status yielded a significant difference where unmarried patients demonstrated low adherence rates compared to married ones (OR: 0.8, 95% CI 0.67-0.95). On analysis of comorbidities, diabetic patients reported lower adherence to antihypertensives (OR: 0.95, 95% CI 0.92-0.97); furthermore, patients who did not have Alzheimer showed higher adherence rates. Different BMIs did not significantly affect the adherence rates. Patients without insurance reported significantly lower adherence rates than insured patients (OR: 3.93, 95% CI 3.43-4.51). Polypill users had higher adherence rates compared with the free-dose combination (OR: 1.21, 95% CI 1.2-1.21), while telepharmacy did not prove to be as effective. Lower adherence rates were seen among African Americans, uninsured, or younger patients. Accordingly, interventions such as fixed-dose combinations should be targeted at susceptible groups. Obesity and overweight did not affect the adherence to antihypertensives.

Global COVID-19 case fatality rates influenced by inequalities in human development and vaccination rates.

Aim: COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions. Subject and methods: Using population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators. Results: The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [-3.3389 (-5.570.033 -1.208)], and Inequality-Adjusted Human Development Index (IHDI) [-0.014 (-0.023 -0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19. Conclusion: Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.

Predictors of placental malaria in Upper West Regional Hospital-Ghana.

BACKGROUND: Placental malaria (PM) poses life-threatening complications to pregnant women as they are at increased risk of maternal and perinatal morbidity and mortality associated with malaria. This study examined the factors associated with placental malaria in the Upper West Regional Hospital (UWR). METHODS: A cross-sectional hospital-based study was carried out among pregnant women delivering at Upper West Regional Hospital. A cross-sectional screening survey was conducted from January 2019 to April 2019. Three hundred eligible mothers were consecutively recruited. A record review of their maternal and child history was assessed using a checklist. Placental blood samples were taken for microscopy to determine placental malaria parasitemia. Logistic regression analysis was done to determine the factors associated with placental malaria at 95 % confidence level. RESULTS: The proportion of mothers with placental malaria was 7 % (21/300), (95 % CI, 4.3-10.5 %). Plasmodium falciparum was the only species identified in those with PM. Majority of the women 66.7 % (14/21) with placental malaria had parasite density in the range 501 to 5,000 parasites/µL. Obstetric and health service factors that were significantly associated with placental malaria were gravidity and antenatal care (ANC) attendance. Primigravida (aOR = 3.48, 95 %CI = 1.01-12.01) and having less than 4 ANC attendance (aOR = 9.78, 95 %CI = 2.89-33.11) were found to be significantly associated with placental malaria. CONCLUSIONS: The proportion of women with PM was relatively low. Primigravid mothers reporting less than 4 ANC visits had the highest risk of placental malaria. Expectant mothers should be encouraged to attend at least 4 ANC visits prior to delivery.

Descriptive Epidemiology of Childhood Disability Prevalence by Sex in the Mississippi Delta and Appalachian Regions.

BACKGROUND: Evidence suggests a rise in childhood disability rates across the United States with males and those with lower socioeconomic status bearing greater burden. We investigated childhood disability rates in the Mississippi Delta (MDR) and Appalachian regions (AR) in comparison to other parts of the country. METHODS: Using data from the US Census Bureau, we calculated childhood disability rates by type and sex at national, regional, and subregional levels. We used risk ratios (RR) to compare childhood disability rates by sex, type, and region. We generated choropleth maps to represent the geographic distribution of disability. RESULTS: Childhood disability was more prevalent, at the national level, among boys (6.64%) than girls (4.08%). Children in the MDR (boys = 8.60%; girls = 5.08%) and AR (boys = 7.81%; girls = 4.83%) had greater risk of disability than those elsewhere in the country (boys = 6.47%; girls = 3.98%), with rates generally higher in rural compared to urban areas in said regions. CONCLUSIONS: Childhood disability affects rural areas of the country more extensively, with the MDR and AR affected to an even greater extent. School-based health centers, in particular, which are disproportionately located in urban areas, could benefit disabled children living in the MDR and AR.

Social determinants of cancer incidence and mortality around the world: an ecological study.

Cancer continues to be a leading cause of mortality and morbidity the world over. While the incidence of cancer is projected to increase by 70% over the next two decades, some research findings suggest a disproportionate distribution of new cancer cases and attendant fatalities across certain regions of the world, with poor and lower income countries worse affected at a time when advances in cancer research, medical technology, and drug development are giving rise to better cancer survival in developed countries. In this study, the role of selected social determinants of health in gauging cancer outcomes relative to incidence across various countries in different regions of the world was explored. The results indicated that the education index, income index, Gini coefficient, availability of cancer control policies and programs, as well as health system performance have an association with and are good predictors of the mortality to incidence ratio (MIR) of lung, breast, cervical, and colorectal cancers. In other words, populations with better education, higher incomes and lower inequalities, active cancer control policies and programs and high performing health systems have better cancer outcomes as reflected in lower MIRs relative to other populations.

Effect of healthcare spending on the relationship between the Human Development Index and maternal and neonatal mortality.

Background: Several factors affect morbidity and mortality the world over. Previous research shows mortality rates are higher among individuals of lower socio-economic status. We investigated the trajectory of neonatal (NM) and maternal (MM) mortality between 2010 and 2014 and the effect of healthcare spending on the relationship between the Human Development Index (HDI) and NM and MM. Methods: Data were obtained from the United Nations Development Program and World Bank. Latent growth curve models (LGCMs) were estimated to determine the trajectory of NM and MM across the study period and the effect of the HDI on NM and MM. Mediation analysis was used to determine if healthcare expenditure mediated the relationship between HDI and NM and MM rates. ArcGIS (Esri, Redlands, CA, USA) was used to generate a choropleth map of changes in NM and MM between 2010 and 2014. Findings: Results showed many countries in Africa enjoyed decreases in NM and MM between 2010 and 2014, but other countries (Algeria, Libya and Sudan) showed little or no improvement. The LGCM for NM (Comparative Fit Index=0.956) and MM (CFI=0.963) demonstrated good fit to the data and showed that the HDI was negatively related to NM and MM. Mediation analysis showed that healthcare spending mediated the relationship between NM and MM in each year. Conclusions: Given that healthcare spending can mediate the relationship between HDI and NM and MM, increases in healthcare spending among countries with low HDI could improve NM and MM outcomes.

Inequality as a Powerful Predictor of Infant and Maternal Mortality around the World.

BACKGROUND: Maternal and infant mortality are highly devastating, yet, in many cases, preventable events for a community. The human development of a country is a strong predictor of maternal and infant mortality, reflecting the importance of socioeconomic factors in determinants of health. Previous research has shown that the Human Development Index (HDI) predicts infant mortality rate (IMR) and the maternal mortality ratio (MMR). Inequality has also been shown to be associated with worse health in certain populations. The main purpose of the present study was to determine the correlation and predictive power of the Inequality Adjusted Human Development Index (IHDI) as a measure of inequality with the Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR), Early Neonatal Mortality Rate (ENMR), Late Neonatal Mortality Rate (LNMR), and the Post Neonatal Mortality Rate (PNMR). METHODS AND FINDINGS: Data for the present study were downloaded from two sources: infant and maternal mortality data were downloaded from the Global Burden of Disease 2013 Cause of Death Database and the Human Development Index (HDI) and Inequality-Adjusted Human Development Index (IHDI) data were downloaded from the United Nations Development Program (UNDP). Pearson correlation coefficients were estimated, following logarithmic transformations to the data, to examine the relationship between HDI and IHDI with MMR, IMR, ENMR, LNMR, and PNMR. Steiger's Z test for the equality of two dependent correlations was utilized in order to determine whether the HDI or IHDI was more strongly associated with the outcome variables. Lastly, we constructed OLS regression models in order to determine the predictive power of the HDI and IHDI in terms of the MMR, IMR, ENMR, LNMR, and PNMR. Maternal and infant mortality were both strongly and negatively correlated with both HDI and IHDI; however, Steiger's Z test for the equality of two dependent correlations revealed that IHDI was more strongly correlated than HDI with MMR (Z = 4.897, p < 0.001), IMR (Z = 2.524, p = 0.012), ENMR (Z = 2.936, p = 0.003), LNMR (Z = 2.272, p = 0.023), and PNMR (Z = 2.277, p = 0.023). Furthermore, side-by-side OLS regression models revealed that, when IHDI was used as the predictor variable instead of HDI, the R2 value was 0.053 higher for MMR, 0.025 higher for IMR, 0.038 higher for ENMR, 0.029 higher for LNMR, and 0.026 higher for PNMR. CONCLUSIONS: Even when both the HDI and the IHDI correlate with the infant and maternal mortality rates, the IHDI is a better predictor for these two health indicators. Therefore, these results add more evidence that inequality is playing an important role in determining the health status of various populations in the world and more efforts should be put into programs to fight inequality.