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Summary: Background: Hypertension is a leading cause of morbidity and mortality worldwide, yet a substantial proportion of cases are undiagnosed. Understanding the scale of undiagnosed hypertension and identifying groups most at risk is important to inform approaches to detection. Methods: In this cross-sectional cohort study, we used data from the 2015 to 2019 Health Survey for England, an annual, cross-sectional, nationally representative survey. The survey follows a multi-stage stratified probability sampling design, involving a random sample of primary sampling units based on postcode sectors, followed by a random sample of postal addresses within these units. Within each selected household, all adults (aged ≥16 years) and up to four children, were eligible for participation. For the current study, individuals aged 16 years and over who were not pregnant and had valid blood pressure data were included in the analysis. The primary outcome was undiagnosed hypertension, defined by a measured blood pressure of 140/90 mmHg or above but no history of diagnosis. Age-adjusted prevalence of undiagnosed hypertension was estimated across sociodemographic and health-related characteristics, including ethnicity, region, rural-urban classification, relationship status, highest educational qualification, National Statistics Socio-Economic Classification (NS-SEC), Body Mass Index (BMI), self-reported general health, and smoking status. To assess the independent association between undiagnosed hypertension and each characteristic, we fitted a logistic regression model adjusted for sociodemographic factors. Findings: The sample included 21,476 individuals, of whom 55.8% were female and 89.3% reported a White ethnic background. An estimated 30.7% (95% confidence interval 29.0–32.4) of men with hypertension and 27.6% (26.1–29.1) of women with hypertension were undiagnosed. Younger age, lower BMI, and better self-reported general health were associated with an increased likelihood of hypertension being undiagnosed for men and women. Living in rural areas and in regions outside of London and the East of England were also associated with an increased likelihood of hypertension being undiagnosed for men, as were being married or in a civil partnership and having higher educational qualifications for women. Interpretation: Hypertension is commonly undiagnosed, and some of the groups that are at the lowest risk of hypertension are the most likely to be undiagnosed. Given the high lifetime risk of hypertension and its strong links with morbidity and mortality, our findings suggest a need for greater awareness of the potential for undiagnosed hypertension, including among those typically considered ‘low risk’. Further research is needed to assess the impact of extending hypertension screening to lower-risk groups. Funding: None.

Summary: Background: Public policy measures and clinical risk assessments relevant to COVID-19 need to be aided by risk prediction models that are rigorously developed and validated. We aimed to externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England. Methods: We did a population-based cohort study using the UK Office for National Statistics Public Health Linked Data Asset, a cohort of individuals aged 19–100 years, based on the 2011 census and linked to Hospital Episode Statistics, the General Practice Extraction Service data for pandemic planning and research, and radiotherapy and systemic chemotherapy records. The primary outcome was time to COVID-19 death, defined as confirmed or suspected COVID-19 death as per death certification. Two periods were used: (1) Jan 24 to April 30, 2020, and (2) May 1 to July 28, 2020. We assessed the performance of the QCovid algorithms using measures of discrimination and calibration. Using predicted 90-day risk of COVID-19 death, we calculated r2 values, Brier scores, and measures of discrimination and calibration with corresponding 95% CIs over the two time periods. Findings: We included 34 897 648 adults aged 19–100 years resident in England. 26 985 (0·08%) COVID-19 deaths occurred during the first period and 13 177 (0·04%) during the second. The algorithms had good discrimination and calibration in both periods. In the first period, they explained 77·1% (95% CI 76·9–77·4) of the variation in time to death in men and 76·3% (76·0–76·6) in women. The D statistic was 3·761 (3·732–3·789) for men and 3·671 (3·640–3·702) for women and Harrell's C was 0·935 (0·933–0·937) for men and 0·945 (0·943–0·947) for women. Similar results were obtained for the second time period. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths in the first period was 65·94% for men and 71·67% for women. Interpretation: The QCovid population-based risk algorithm performed well, showing high levels of discrimination for COVID-19 deaths in men and women for both time periods. QCovid has the potential to be dynamically updated as the pandemic evolves and, therefore, has potential use in guiding national policy. Funding: UK National Institute for Health Research.