BackgroundSeveral recent studies have attempted to measure the prevalence of disrespect and abuse (D&A) of women during childbirth in health facilities. Variations in reported prevalence may be associated with differences in study instruments and data collection methods. This systematic review and comparative analysis of methods aims to aggregate and present lessons learned from published studies that quantified the prevalence of Disrespect and Abuse (D&A) during childbirth.MethodsWe conducted a systematic review of the literature in accordance with PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Five papers met criteria and were included for analysis. We developed an analytical framework depicting the basic elements of epidemiological methodology in prevalence studies and a table of common types of systematic error associated with each of them. We performed a head-to-head comparison of study methods for all five papers. Using these tools, an independent reviewer provided an analysis of the potential for systematic error in the reported prevalence estimates.ResultsSampling techniques, eligibility criteria, categories of D&A selected for study, operational definitions of D&A, summary measures of D&A, and the mode, timing, and setting of data collection all varied in the five studies included in the review. These variations present opportunities for the introduction of biases – in particular selection, courtesy, and recall bias – and challenge the ability to draw comparisons across the studies’ results.ConclusionOur review underscores the need for caution in interpreting or comparing previously reported prevalence estimates of D&A during facility-based childbirth. The lack of standardized definitions, instruments, and study methods used to date in studies designed to quantify D&A in childbirth facilities introduced the potential for systematic error in reported prevalence estimates, and affected their generalizability and comparability. Chief among the lessons to emerge from comparing methods for measuring the prevalence of D&A is recognition of the tension between seeking prevalence measures that are reliable and generalizable, and attempting to avoid loss of validity in the context where the issue is being studied.Electronic supplementary materialThe online version of this article (10.1186/s12978-017-0389-z) contains supplementary material, which is available to authorized users.

Aim To evaluate whether history of pregnancy complications [pre-eclampsia, gestational hypertension, preterm delivery, or small for gestational age (SGA)] improves risk prediction for cardiovascular disease (CVD). Methods and results This population-based, prospective cohort study linked data from the HUNT Study, Medical Birth Registry of Norway, validated hospital records, and Norwegian Cause of Death Registry. Using an established CVD risk prediction model (NORRISK 2), we predicted 10-year risk of CVD (non-fatal myocardial infarction, fatal coronary heart disease, and non-fatal or fatal stroke) based on established risk factors (age, systolic blood pressure, total and HDL-cholesterol, smoking, anti-hypertensives, and family history of myocardial infarction). We evaluated whether adding pregnancy complication history improved model fit, calibration, discrimination, and reclassification. Among 18 231 women who were parous, ≥40 years of age, and CVD-free at start of follow-up, 39% had any pregnancy complication history and 5% experienced a CVD event during a median follow-up of 8.2 years. While pre-eclampsia and SGA were associated with CVD in unadjusted models (HR 1.96, 95% CI 1.44–2.65 for pre-eclampsia and HR 1.46, 95% CI 1.18–1.81 for SGA), only pre-eclampsia remained associated with CVD after adjusting for established risk factors (HR 1.60, 95% CI 1.16–2.17). Adding pregnancy complication history to the established prediction model led to small improvements in discrimination (C-index difference 0.004, 95% CI 0.002–0.006) and reclassification (net reclassification improvement 0.02, 95% CI 0.002–0.05). Conclusion Pre-eclampsia independently predicted CVD after controlling for established risk factors; however, adding pre-eclampsia, gestational hypertension, preterm delivery, and SGA made only small improvements to CVD prediction among this representative sample of parous Norwegian women.