The path to universal health coverage in five African and Asian countries: examining the association between insurance status and health-care use.

Despite major efforts to achieve universal health coverage (UHC), progress has lagged in many African and Asian countries. A key strategy pursued by many countries is the use of health insurance to increase access and affordability. However, evidence on insurance coverage and on the association between insurance and UHC is mixed. We analysed nationally representative cross-sectional data collected between 2022 and 2023 in Ethiopia, Kenya, South Africa, India, and Laos. We described public and private insurance coverage by sociodemographic factors and used logistic regression to examine the associations between insurance status and seven health-care use outcomes. Health insurance coverage ranged from 25% in India to 100% in Laos. The share of private insurance ranged from 1% in Ethiopia to 13% in South Africa. Relative to the population with private insurance, the uninsured population had reduced odds of health-care use (adjusted odds ratio 0·68, 95% CI 0·50-0·94), cardiovascular examinations (0·63, 0·47-0·85), eye and dental examinations (0·54, 0·42-0·70), and ability to get or afford care (0·64, 0·48-0·86); private insurance was not associated with unmet need, mental health care, and cancer screening. Relative to private insurance, public insurance was associated with reduced odds of health-care use (0·60, 0·43-0·82), mental health care (0·50, 0·31-0·80), cardiovascular examinations (0·62, 0·46-0·84), and eye and dental examinations (0·50, 0·38-0·65). Results were highly heterogeneous across countries. Public health insurance appears to be only weakly associated with access to health services in the countries studied. Further research is needed to improve understanding of these associations and to identify the most effective financing strategies to achieve UHC.

Diagnostic Accuracy of Unattended Automated Office Blood Pressure Measurement in Screening for Hypertension in Kenya.

Despite increasing adoption of unattended automated office blood pressure (uAOBP) measurement for determining clinic blood pressure (BP), its diagnostic performance in screening for hypertension in low-income settings has not been determined. We determined the validity of uAOBP in screening for hypertension, using 24-hour ambulatory BP monitoring as the reference standard. We studied a random population sample of 982 Kenyan adults; mean age, 42 years; 60% women; 2% with diabetes mellitus; none taking antihypertensive medications. We calculated sensitivity using 3 different screen positivity cutoffs (≥130/80, ≥135/85, and ≥140/90 mm Hg) and other measures of validity/agreement. Mean 24-hour ambulatory BP monitoring systolic BP was similar to mean uAOBP systolic BP (mean difference, 0.6 mm Hg; 95% CI, -0.6 to 1.9), but the 95% limits of agreement were wide (-39 to 40 mm Hg). Overall discriminatory accuracy of uAOBP was the same (area under receiver operating characteristic curves, 0.66-0.68; 95% CI range, 0.64-0.71) irrespective of uAOBP cutoffs used. Sensitivity of uAOBP displayed an inverse association (P<0.001) with the cutoff selected, progressively decreasing from 67% (95% CI, 62-72) when using a cutoff of ≥130/80 mm Hg to 55% (95% CI, 49-60) at ≥135/85 mm Hg to 44% (95% CI, 39-49) at ≥140/90 mm Hg. Diagnostic performance was significantly better (P<0.001) in overweight and obese individuals (body mass index, >25 kg/m2). No differences in results were present in other subanalyses. uAOBP misclassifies significant proportions of individuals undergoing screening for hypertension in Kenya. Additional studies on how to improve screening strategies in this setting are needed.