OBJECTIVES: The purpose of this study was to describe trends in maternal pre-pregnancy hypertension among women in rural and urban areas in 2007 to 2018 in order to inform community-engaged prevention and policy strategies.
METHODS: We performed a nationwide, serial cross-sectional study using maternal data from all live births in women age 15 to 44 years between 2007 and 2018 (CDC Natality Database). Rates of pre-pregnancy hypertension were calculated per 1,000 live births overall and by urbanization status. Subgroup analysis in standard 5-year age categories was performed. We quantified average annual percentage change using Joinpoint Regression and rate ratios (95% confidence intervals [CIs]) to compare yearly rates between rural and urban areas.
RESULTS: Among 47,949,381 live births to women between 2007 and 2018, rates of pre-pregnancy hypertension per 1,000 live births increased among both rural (13.7 to 23.7) and urban women (10.5 to 20.0). Two significant inflection points were identified in 2010 and 2016, with highest annual percentage changes between 2016 and 2018 in rural and urban areas. Although absolute rates were lower in younger compared with older women in both rural and urban areas, all age groups experienced similar increases. The rate ratios of pre-pregnancy hypertension in rural compared with urban women ranged from 1.18 (95% CI: 1.04 to 1.35) for ages 15 to 19 years to 1.51 (95% CI: 1.39 to 1.64) for ages 40 to 44 years in 2018.
CONCLUSIONS: Maternal burden of pre-pregnancy hypertension has nearly doubled in the past decade and the rural-urban gap has persisted.
SETTING: Asian regional cohort incorporating 16 pediatric HIV services across 6 countries.
METHODS: Data from PHIVA (aged 10-19 years) who received combination antiretroviral therapy 2007-2016 were used to analyze LTFU through (1) an International epidemiology Databases to Evaluate AIDS (IeDEA) method that determined LTFU as >90 days late for an estimated next scheduled appointment without returning to care and (2) the absence of patient-level data for >365 days before the last data transfer from clinic sites. Descriptive analyses and competing-risk survival and regression analyses were used to evaluate LTFU epidemiology and associated factors when analyzed using each method.
RESULTS: Of 3509 included PHIVA, 275 (7.8%) met IeDEA and 149 (4.3%) met 365-day absence LTFU criteria. Cumulative incidence of LTFU was 19.9% and 11.8% using IeDEA and 365-day absence criteria, respectively. Risk factors for LTFU across both criteria included the following: age at combination antiretroviral therapy initiation <5 years compared with age ≥5 years, rural clinic settings compared with urban clinic settings, and high viral loads compared with undetectable viral loads. Age 10-14 years compared with age 15-19 years was another risk factor identified using 365-day absence criteria but not IeDEA LTFU criteria.
CONCLUSIONS: Between 12% and 20% of PHIVA were determined LTFU with treatment fatigue and rural treatment settings consistent risk factors. Better tracking of adolescents is required to provide a definitive understanding of LTFU and optimize evidence-based models of care.