Constructing comparable intimate partner violence indicators across the DHS, MICS, and PMA health surveys.

We construct comparable indicators that measure the prevalence of recent intimate partner violence (IPV) using publicly available, integrated microdata within the IPUMS data collections across many countries. The objective of this work is to increase opportunities for comparative research by leveraging vast quantities of harmonized data. We use consistent and comparable variables that measure domestic violence in international health surveys. The most consistent indicators of domestic violence measure physical, psychological, and sexual IPV in the last 12 months. We imposed a consistent reference period and restricted to a comparable subpopulation where these differed across surveys. Aggregating IPV variables across surveys, without careful attention to question wording and subpopulations, may produce inconsistent measures leading to bias, over- or under-estimation of IPV prevalence, or spurious trends and associations. Using comparable indicators in microdata and studying the level, distribution, and covariates of IPV in multiple settings over time, we can better understand these phenomena and identify effective policy interventions.

U.S. global health aid policy and family planning in sub-Saharan Africa.

The Trump administration reinstated and expanded the Mexico City Policy (MCP) in 2017 as the Protecting Life in Global Health Assistance (PLGHA) policy, forbidding international organizations receiving all U.S. health assistance from promoting abortion. Existing evidence suggests that abortion rates rise under the MCP, but the direct effect of U.S. funding restrictions on supply and use of family planning has received less attention. By studying PLGHA's impact on health service delivery providers and women in eight sub-Saharan African countries, we are able to fill this gap. We find that health facilities provide fewer family planning services, including emergency contraception, and that women are less likely to use contraception and more likely to have given birth recently under the policy. These findings suggest that PLGHA has important unintended consequences that are detrimental to reproductive health and the autonomous decision-making of health service providers and women.

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality.

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.