Spatio-Temporal Trend and Geographic Disparity of Infertility Prevalence in Burkina Faso, 2011 to 2020

Background: Infertility affected 10% to 25% of couples globally, and about half of the infertility cases were reported in sub-Saharan Africa. Infertility poses significant social, cultural, and health challenges, particularly for women who often face stigmatization. However, comprehensive and nationally representative data, including prevalence, temporal trends, and risk factors, are lacking, prompting a study in Burkina Faso to address the need for informed policies and programs in infertility care and management. Objectives: This study aims to better understand the spatiotemporal trend of infertility prevalence in Burkina Faso. Methodology: This is a retrospective population-based study of women infertility from healthcare facilities in Burkina Faso, during January 2011 to December 2020. We calculated the prevalence rates of infertility and two disparity measures, and examined the spatiotemporal trend of infertility. Results: Over the 10-year period (2011 to 2020), 143,421 infertility cases were recorded in Burkina Faso healthcare facilities, resulting of a mean prevalence rate of 3.61‰ among childbearing age women and 17.87‰ among women who consulted healthcare facilities for reproductive issues (except contraception). The findings revealed a significant increase of infertility, with the prevalence rate varied from 2.75‰ in 2011 to 4.62‰ in 2020 among childbearing age women and from 13.38‰ in 2011 to 26.28‰ in 2020 among women who consulted healthcare facilities for reproductive issues, corresponding to an estimate annual percentage change of 8.31% and 9.80% respectively. There were significant temporal and geographic variations in the prevalence of infertility. While relative geographic disparity decreased, absolute geographic disparity showed an increasing trend over time. Conclusion: The study highlights an increasing trend of infertility prevalence and significant geographic variation in Burkina Faso, underscoring the urgent necessity for etiologic research on risk factors, psychosocial implications, and economic consequences to inform effective interventions and mitigate the socioeconomic impact of infertility.

A cluster-randomized trial comparing two SWITCH implementation support strategies for school wellness intervention effectiveness

Background:The School Wellness Integration Targeting Child Health(SWITCH)intervention has demonstrated feasibility as an implementation approach to help schools facilitate changes in students’physical activity(PA),sedentary screen time(SST),and dietary intake(DI).This study evaluated the comparative effectiveness of enhanced(individualized)implementation and standard(group-based)implementation.Methods:Twenty-two Iowa elementary schools participated,with each receiving standardized training(wellness conference and webinars).Schools were matched within region and randomized to receive either individualized or group implementation support.The PA,SST,and DI outcomes of 1097 students were assessed at pre-and post-intervention periods using the Youth Activity Profile.Linear mixed models evaluated differential change in outcomes by condition,for comparative effectiveness,and by gender.Results:Both implementation conditions led to significant improvements in PA and SST over time(p<0.01),but DI did not improve commensurately(p value range:0.02‒0.05).There were no differential changes between the group and individualized conditions for PA(p=0.51),SST(p=0.19),or DI(p=0.73).There were no differential effects by gender(i.e.,non-significant condition-by-gender interactions)for PA(p_(for interaction)=0.86),SST(p_(for interaction)=0.46),or DI(p_(for interaction)=0.15).Effect sizes for both conditions equated to approximately 6 min more PA per day and approximately 3 min less sedentary time.Conclusion:The observed lack of difference in outcomes suggests that group implementation of SWITCH is equally effective as individualized implementation for building capacity in school wellness programming.Similarly,the lack of interaction by gender suggests that SWITCH can be beneficial for both boys and girls.Additional research is needed to understand the school-level factors that influence implementation(and outcomes)of SWITCH.

Genome-Wide Likelihood Ratio Tests under Heterogeneity

The commonly used statistical methods in medical research generally assume patients arise from one homogeneous population. However, the existence and importance of significant heterogeneity have been widely documented. It is well known that common and complex human diseases usually have heterogeneous disease etiology, which often involves interplay of multiple genetic and environmental factors, leading to latent population substructure. Genome-wide association studies (GWAS) is a useful tool to uncover genetic association with disease of interest, while linkage analysis is a commonly used method to identify statistical association between the inheritance of a human disease and inheritance of marker loci that are in linkage with disease causing loci. We propose a likelihood ratio test for genome-wide linkage analysis under genetic heterogeneity using family data. We derive a closed-form formula for the LRT test statistic and provide explicit asymptotic null distribution. The closed form asymptotic distribution allows easy determination of the asymptotic p-values. Our extensive simulation studies indicate that the proposed test has proper type I error and good power under genetic heterogeneity. In order to simplify application of the proposed method for non-statisticians, we develop an R package gLRTH to implement the proposed LRT for genome-wide linkage analysis as well as Qian and Shao’s LRT for GWAS under heterogeneity. The newly developed open source R package gLRTH is available at CRAN.

Statistical Assessment of Neighborhood Socioeconomic Deprivation Environment in Spatial Epidemiologic Studies

Neighborhood socioeconomic deprivation has been associated with health behaviors and outcomes. However, neighborhood socioeconomic status has been measured inconsistently across studies. It remains unclear whether appropriate socioeconomic indicators vary over geographic areas and geographic levels. The aim of this study is to compare the composite socioeconomic index to six socioeconomic indicators reflecting different aspects of socioeconomic environment by both geographic areas and levels. Using 2000 U.S. Census data, we performed a multivariate common factor analysis to identify significant socioeconomic resources and constructed 12 composite indexes at the county, the census tract, and the block group levels across the nation and for three states, respectively. We assessed the agreement between composite indexes and single socioeconomic variables. The component of the composite index varied across geographic areas. At a specific geographic region, the component of the composite index was similar at the levels of census tracts and block groups but different from that at the county level. The percentage of population below federal poverty line was a significant contributor to the composite index, regardless of geographic areas and levels. Compared with non-component socioeconomic indicators, component variables were more agreeable to the composite index. Based on these findings, we conclude that a composite index is better as a measure of neighborhood socioeconomic deprivation than a single indicator, and it should be constructed on an area- and unit-specific basis to accurately identify and quantify small-area socioeconomic inequalities over a specific study region.

Associations of Gestational Exposure to Air Pollution and Polycyclic Aromatic Hydrocarbons with Placental Inflammation

Restricted fetal growth(RFG)is a leading contributor to perinatal mortality and has been associated with gestational exposure to air pollution,such as fine particulate matter(PM_(2.5)),nitrogen dioxide(NO2),and polycyclic aromatic hydrocarbons(PAHs).This study examines the association between trimester-specific and weekly means of air pollution throughout gestation and placental inflammatory markers at delivery.In a prospective cohort study of 263 pregnant women in Rochester,NY,we measured interleukin-6(IL-6)and tumor necrosis factor-alpha(TNF-α)in placental tissue and estimated gestational exposure to PM_(2.5)and NO_(2)using a high-resolution spatial-temporal model.Exposure to PAHs was estimated using urinary 1-hydroxypyrene(1-OHP)concentrations collected once per trimester.Using distributed lag models with a penalized spline function,each interquartile range(2.6μg/m^(3))increase in PM_(2.5)concentration during gestational weeks 6−11 was associated with decreased placental IL-6 levels(−22.2%,95%CI:−39.0%,−0.64%).Using multiple linear regression models,each interquartile range increase of 1-OHP was associated with an increase in TNF-αin the first trimester(58.5%,95%CI:20.7%,74.2%),third trimester(22.9%,95%CI:0.04%,49.5%),and entire pregnancy(29.6%,95%CI:3.9%,60.6%).Our results suggest gestational exposure to air pollution may alter the inflammatory environment of the placenta at delivery.