To assess social inequalities in the use of antenatal care (ANC), facility based delivery (FBD), and modern contraception (MC) in two contrasting groups of countries in sub-Saharan Africa divided based on their progress towards maternal mortality reduction. Six countries were included in this study. Three countries (Ethiopia, Madagascar, and Uganda) had 4.5% average annual reduction rate while another three (Cameroon, Zambia, and Zimbabwe) had >550 MMR in 2010 with only <1.5% average annual reduction rate. All of these countries had at least three rounds of Demographic and Health Surveys (DHS) before 2012. We measured rate ratios and differences, as well as relative and absolute concentration indices in order to examine within-country geographical and wealth-based inequalities in the utilization of ANC, FBD, and MC. In the countries which have made sufficient progress (i.e. Ethiopia, Madagascar, and Uganda), ANC use increased by 8.7, 9.3 and 5.7 percent, respectively, while the utilization of FBD increased by 4.7, 0.7 and 20.2 percent, respectively, over the last decade. By contrast, utilization of these services either plateaued or decreased in countries which did not make progress towards reducing maternal mortality, with the exception of Cameroon. Utilization of MC increased in all six countries but remained very low, with a high of 40.5% in Zimbabwe and low of 16.1% in Cameroon as of 2011. In general, relative measures of inequalities were found to have declined overtime in countries making progress towards reducing maternal mortality. In countries with insufficient progress towards maternal mortality reduction, these indicators remained stagnant or increased. Absolute measures for geographical and wealth-based inequalities remained high invariably in all six countries. The increasing trend in the utilization of maternal care services was found to concur with a steady decline in maternal mortality. Relative inequality declined overtime in countries which made progress towards reducing maternal mortality.

Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries. We applied an extension of the Blinder-Oaxaca decomposition approach to data from Demographic and Health Surveys and AIDS Indicator Surveys to quantify the differences in HIV/AIDS prevalence between women and men attributable to socio-demographic factors, sexual behaviours, and awareness of HIV/AIDS. We decomposed gender inequalities into two components: the percentage attributable to different levels of the risk factors between women and men (the “composition effect”) and the percentage attributable to risk factors having differential effects on HIV/AIDS prevalence in women and men (the “response effect”). Descriptive analyses showed that the difference between women and men in HIV/AIDS prevalence varied from a low of 0.68 % (P = 0.008) in Liberia to a high of 11.5 % (P < 0.001) in Swaziland. The decomposition analysis showed that 84 % (P < 0.001) and 92 % (P < 0.001) of the higher prevalence of HIV/AIDS among women in Uganda and Ghana, respectively, was explained by the different distributions of HIV/AIDS risk factors, particularly age at first sex between women and men. In the majority of countries, however, observed gender inequalities in HIV/AIDS were chiefly explained by differences in the responses to risk factors; the differential effects of age, marital status and occupation on prevalence of HIV/AIDS for women and men were among the significant contributors to this component. In Cameroon, Guinea, Malawi and Swaziland, a combination of the composition and response effects explained gender inequalities in HIV/AIDS prevalence. The factors that explain gender inequality in HIV/AIDS in SSA vary by country, suggesting that country-specific interventions are needed. Unmeasured factors also contributed substantially to the difference in HIV/AIDS prevalence between women and men, highlighting the need for further study.

Maternity leave reduces neonatal and infant mortality rates in high-income countries. However, the impact of maternity leave on infant health has not been rigorously evaluated in low- and middle-income countries (LMICs). In this study, we utilized a difference-in-differences approach to evaluate whether paid maternity leave policies affect infant mortality in LMICs. We used birth history data collected via the Demographic and Health Surveys to assemble a panel of approximately 300,000 live births in 20 countries from 2000 to 2008; these observational data were merged with longitudinal information on the duration of paid maternity leave provided by each country. We estimated the effect of an increase in maternity leave in the prior year on the probability of infant (<1 y), neonatal (<28 d), and post-neonatal (between 28 d and 1 y after birth) mortality. Fixed effects for country and year were included to control for, respectively, unobserved time-invariant confounders that varied across countries and temporal trends in mortality that were shared across countries. Average rates of infant, neonatal, and post-neonatal mortality over the study period were 55.2, 30.7, and 23.0 per 1,000 live births, respectively. Each additional month of paid maternity was associated with 7.9 fewer infant deaths per 1,000 live births (95% CI 3.7, 12.0), reflecting a 13% relative reduction. Reductions in infant mortality associated with increases in the duration of paid maternity leave were concentrated in the post-neonatal period. Estimates were robust to adjustment for individual, household, and country-level characteristics, although there may be residual confounding by unmeasured time-varying confounders, such as coincident policy changes. More generous paid maternity leave policies represent a potential instrument for facilitating early-life interventions and reducing infant mortality in LMICs and warrant further discussion in the post-2015 sustainable development agenda. From a policy planning perspective, further work is needed to elucidate the mechanisms that explain the benefits of paid maternity leave for infant mortality. In 1990, 12 million children—most of them living in low- and middle-income countries (LMICs)—died before their fifth birthday. Out of every 1,000 children born alive, 90 died before they were five years old. In 2000, world leaders set a target of reducing under-five mortality (deaths) to one-third of its 1990 level by 2015 as Millennium Development Goal 4 (MDG4); this goal, together with seven others, was designed to eradicate extreme poverty globally. Over the years, steady progress was made towards MDG4. Better delivery facilities and programs that encouraged breastfeeding, immunization, and other practices that improved the health of young children reduced the global under-five mortality rate. But, by 2015, the rate had only fallen to 43 deaths per 1,000 live births, and 5.9 million children under five died that year from preventable causes such as preterm birth complications, delivery complications, and infections. Nearly half of these deaths occurred among neonates (babies less than 28 days old); three-quarters of them occurred among infants (children less than 1 year old). In high-income countries, paid leave from employment for mothers is associated with reduced neonatal and infant mortality. Many LMICs now have legislation granting paid maternity leave or gender-neutral parental leave. But does paid maternity leave have the same impact on infant health in LMICs as it does in high-income countries? In this quasi-experimental study, the researchers use the difference-in-differences statistical approach to investigate whether paid maternity leave policies affect infant mortality in LMICs. A quasi-experimental study uses observational data to compare outcomes in a group of people receiving an intervention (the treatment group) with outcomes in a group of people not receiving the intervention (control group); unlike a randomized controlled trial, these groups are not chosen at random. The difference-in-differences approach compares the average change over time in an outcome variable (here, infant mortality) in a treatment group (here, babies born in countries with a change—specifically, an increase—in paid maternity leave duration) with the average change over time in the outcome variable in a control group (here, babies born in countries without a change in paid maternity leave duration). The researchers assembled a panel of about 300,000 live births in 20 LMICs between 2000 and 2008 using birth history data collected by the Demographic and Health Surveys (which collect information on the demographic, health, and other characteristics of a nationally representative sample of households). The researchers merged these observational data with information on the duration of paid maternity leave provided by each country and used the difference-in-differences approach to estimate the effect of an increase in paid maternity leave duration on the probability of infant (<1 year old), neonatal (<28 days old), and post-neonatal (between 28 days and 1 year old) mortality. Average rates of infant, neonatal, and post-neonatal mortality over the study period were 55.2, 30.7, and 23.0 per 1,000 live births, respectively. Each additional month of paid maternity leave was associated with 7.9 fewer infant deaths per 1,000 live births, a relative reduction in infant mortality of 13%. Notably, the reduction in infant mortality with increased duration of paid maternity leave was concentrated in the post-neonatal period. These findings suggest that policies that increase the duration of paid maternity leave could help to reduce infant mortality in the 20 LMICs included in this study. These findings may not be generalizable to all LMICs. Moreover, their accuracy may be limited by confounding. That is, unmeasured characteristics—rather than changes in paid...

This study aimed to examine the prevalence and types of medication errors (MEs), as well as barriers to reporting MEs, among nurses working in 7 teaching hospitals affiliated with Kermanshah University of Medical Sciences in 2016. A convenience sampling method was used to select the study participants (n=500 nurses). A self-constructed questionnaire was employed to collect information on participants' socio-demographic characteristics (10 items), their perceptions about the main causes of MEs (31 items), and barriers to reporting MEs to nurse managers (11 items). Data were collected from September 1 to November 30, 2016. Negative binomial regression was used to identify the main predictors of the frequency of MEs among nurses. The prevalence of MEs was 17.0% (95% confidence interval, 13.7 to 20.3%). The most common types of MEs were administering medications at the wrong time (24.0%), dosage errors (16.8%), and administering medications to the wrong patient (13.8%). A heavy workload and the type of shift work were considered to be the main causes of MEs by nursing staff. Our findings showed that 45.0% of nurses did not report MEs. A heavy workload due to a high number of patients was the most important reason for not reporting MEs (mean score, 3.57±1.03) among nurses. Being male, having a second unrelated job, and fixed shift work significantly increased MEs among nurses (p=0.001). Our study documented a high prevalence of MEs among nurses in the west of Iran. A heavy workload was considered to be the most important barrier to reporting MEs among nurses. Thus, appropriate strategies (e.g., reducing the nursing staff workload) should be developed to address MEs and improve patient safety in hospital settings in Iran.

Extant studies universally document a positive gradient between socioeconomic status (SES) and health. A notable exception is the apparent concentration of HIV/AIDS among wealthier individuals. This paper uses data from the Demographic Health Surveys and AIDS Indicator Surveys to examine socioeconomic inequalities in HIV/AIDS prevalence in 24 sub-Saharan African (SSA) countries, the region that accounts for two-thirds of the global HIV/AIDS burden.