English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Background Reliable and precise estimates of high blood pressure (HBP) prevalence are essential to inform decision-making and policies evaluation. Self-reported HBP may be underestimated by surveys due to misclassification of health status by participants. Misclassification may lead to inaccurate inference. We aimed to assess a feasibility of correcting misclassification bias in self-reported HBP in the Portuguese component of the European Health Interview Survey (INS2014) using data on objective blood pressure measurements from a smaller health examination survey (INSEF). Methods We assumed that “true” measured HBP status was missing at random for INS2014 participants (n = 13937). Using a multiple imputation method of logistic regression for monotone missing data patterns, HBP was imputed for INS2014 sample. Auxiliary data on measured HBP from INSEF (n = 4910) was used. Crude and corrected HBP prevalence rates stratified by sex and age group were calculated. Results HBP prevalence based on INS2014 increased significantly after multiple imputation correction, from 22.0% [CI95%:20.6-23.5%] to 38.8% [35.4-41.9%] for men and from 26.8% [25.3-28.3%] to 33.0% [30.5-35.4%] for women. Corrected estimates were similar to the objectively measured from INSEF, 39.6% for men and 32.7% for women. Corrected HBP prevalence in INS2014 increased from 4.1% [2.9-5.9%] to 7.9% [4.0-11.8%] in 25-34 years old (yo); from 9.3% [7.8-11.0%] to 17.6% [14.0-21.3%] in 35-44 yo; from 22.5% [20.3-24.8%] to 38.7% [34.2-43.2%] in 45-54 yo; from 39.8% [37.2-42.4%] to 53.8% [49.1-58.5%] in 55-64 yo and from 54.3% [51.5-57.1%] to 67.7% [63.1-72.3%] in 65-74 yo. Corrected rates were similar to the obtained by INSEF (5.7%, 17.0%, 35.8%, 54.8% and 71.3%, respectively). Conclusions Our results highlight the importance of bias analysis when using self-reported data on HBP. Multiple imputation is a feasible approach to adjust misclassification bias in health outcomes collected by population surveys. Key messages The magnitude and direction of misclassification bias in self-reported health outcomes should be investigated. Multiple imputation is a feasible approach to misclassification bias correction in self-reported survey data.

Bias correction in self-reported high blood pressure prevalence based on objectively measured data