The effect of population-based blood pressure screening on long-term cardiometabolic morbidity and mortality in Germany: A regression discontinuity analysis

Abstract

Background Hypertension represents one of the major risk factors for cardiovascular morbidity and mortality globally. Early detection and treatment of this condition is vital to prevent complications. However, hypertension often goes undetected, and even if detected, not every patient receives adequate treatment. Identifying simple and effective interventions is therefore crucial to fight this problem and allow more patients to receive the treatment they need. Therefore, we aim at investigating the impact of a population-based blood pressure (BP) screening and the subsequent “low-threshold” information treatment on long-term cardiovascular disease (CVD) morbidity and mortality. Methods and findings We examined the impact of a BP screening embedded in a population-based cohort study in Germany and subsequent personalized “light touch” information treatment, including a hypertension diagnosis and a recommendation to seek medical attention. We pooled four waves of the KORA study, carried out between 1984 and 1996 (N = 14,592). Using a sharp multivariate regression discontinuity (RD) design, we estimated the impact of the information treatment on CVD mortality and morbidity over 16.9 years. Additionally, we investigated potential intermediate outcomes, such as hypertension awareness, BP, and behavior after 7 years. No evidence of effect of BP screening was observed on CVD mortality (hazard ratio (HR) = 1.172 [95% confidence interval (CI): 0.725, 1.896]) or on any (fatal or nonfatal) long-term CVD event (HR = 1.022 [0.636, 1.641]) for individuals just above (versus below) the threshold for hypertension. Stratification for previous self-reported diagnosis of hypertension at baseline did not reveal any differential effect. The intermediate outcomes, including awareness of hypertension, were also unaffected by the information treatment. However, these results should be interpreted with caution since the analysis might not be sufficiently powered to detect a potential intervention effect. Conclusions The study does not provide evidence of an effect of the assessed BP screening and subsequent information treatment on BP and behavior, but also on long-term CVD mortality and morbidity. Future studies should consider larger datasets to detect possible effects and a shorter follow-up for the intermediate outcomes (i.e., BP and behavior) to detect short-, medium-, and long-term effects of the intervention along the causal pathway.

Does home-based screening and health information provision improve hypertension diagnosis, treatment, and control? A regression discontinuity analysis in urban India

“…14 Lastly, in Germany, home-based screening and referral for hypertension had no long-term effect on cardiometabolic morbidity or mortality. 27 In our specific study context in urban India, there are several potential reasons why the home-based screening and information provision intervention did not increase hypertension diagnosis and treatment or reduce BP levels. At the individual level, the health information and referral provided by the survey team need to encourage individuals to visit a healthcare facility for a formal hypertension diagnosis, obtain a prescription, and then take the medication regularly.…”

“…14 Lastly, in Germany, home-based screening and referral for hypertension had no long-term effect on cardiometabolic morbidity or mortality. 27 These mixed effects across contexts suggest that contextual circumstances substantially influence whether home-based screening interventions are effective. For example, intervention effectiveness may depend on (1) the underlying population and their beliefs and health-seeking behavior patterns; (2) the healthcare system in each context and how accessible care is; and (3) the design of the health information provided as part of the intervention including who provides individuals information and what information is provided.…”

“…For this reason, we standardized and combined the two measurements into one running variable, resulting in one threshold. 26,27 First, we standardized each value by subtracting the threshold value (140 for systolic and 90 for diastolic BP) from an individual's average measurement result and then dividing it by the sample's standard deviation. This resulted in an individual's standardized distance from the threshold for the systolic and diastolic BP measurements, respectively.…”