Differential self-report error by socioeconomic status in hypertension and hypercholesterolemia: INSEF 2015 study (original) (raw)
Related papers
Self-reported health: reliability and consequences for health inequality measurement
Health Economics, 2006
Self-reported health (SRH) is one of the most frequently employed measures for assessing income-related health inequalities between counties. A previous study has shown that 28% of respondents changed their assessment of their health status when asked a SRH question on two occasions in the same survey (first as part of self-completed questionnaire and then in a personal interview). This study re-examines this issue using another survey where SRH was again asked twice of respondents, but this time the personal interview was first and self-completion second. We find the same variation in responses, but the predominant direction is away from the 'extreme' categories 'Excellent' and 'Poor' which is the opposite direction to the previous study. We therefore conclude that the most likely explanation is a mode of administration effect that makes people less likely to choose the extreme categories in a selfcompletion questionnaire, but not a personal interview. However, this effect has a relatively minor impact on measures of inequality. This is due to a large proportion of the movement (i.e. movement to the middle) not being related to income and hence does not systematically impact on the cumulative distribution of health across this measure of socio-economic status.
Archives of Public Health
Background Accurate data on hypertension is essential to inform decision-making. Hypertension prevalence may be underestimated by population-based surveys due to misclassification of health status by participants. Therefore, adjustment for misclassification bias is required when relying on self-reports. This study aims to quantify misclassification bias in self-reported hypertension prevalence and prevalence ratios in the Portuguese component of the European Health Interview Survey (INS2014), and illustrate application of multiple imputation (MIME) for bias correction using measured high blood pressure data from the first Portuguese health examination survey (INSEF). Methods We assumed that objectively measured hypertension status was missing for INS2014 participants (n = 13,937) and imputed it using INSEF (n = 4910) as auxiliary data. Self-reported, objectively measured and MIME-corrected hypertension prevalence and prevalence ratios (PR) by sex, age group and education were estima...
European journal of public health, 2014
Non-communicable diseases (NCDs) cause 63% of deaths worldwide. The leading NCD risk factor is raised blood pressure, contributing to 13% of deaths. A large proportion of NCDs are preventable by modifying risk factor levels. Effective prevention programmes and health policy decisions need to be evidence based. Currently, self-reported information in general populations or data from patients receiving healthcare provides the best available information on the prevalence of obesity, hypertension, diabetes, etc. in most countries. In the European Health Examination Survey Pilot Project, 12 countries conducted a pilot survey among the working-age population. Information was collected using standardized questionnaires, physical measurement and blood sampling protocols. This allowed comparison of self-reported and measured data on prevalence of overweight, obesity, hypertension, high blood cholesterol and diabetes. Self-reported data under-estimated population means and prevalence for heal...
Ecuity III Project, Working …, 2004
This paper explores reporting bias and heterogeneity in the measure of self-assessed health (SAH) used in the British Household Panel Survey (BHPS). The ninth wave of the BHPS includes the SF-36 general health questionnaire, which incorporates a different wording to the self-assessed health variable used at other waves. Considerable attention has been devoted to the reliability of SAH and the scope for contamination by measurement error; the change in wording at wave 9 provides a form of natural experiment that allows us to assess the sensitivity of panel data analyses to a change in the measurement instrument. In particular, we investigate reporting bias due explicitly to the change in the question. We show how progressively more general specifications of reporting bias can be implemented using panel data ordered probit and generalised ordered probit models. Our results suggest that the distribution of SAH does shift at the ninth wave but there is little evidence that this varies with socio-economic characteristics at an individual level.
Frontiers in Public Health, 2023
Background: Generic health-related quality of life instruments, such as the EQ-D, are increasingly used by countries to monitor population health via general population health surveys. Our aim was to demonstrate analytic options to measure socio-demographic di erences in self-reported health using the EuroQol Group's archive of EQ-D-L population surveys that accumulated over the past two decades. Methods: Analyses captured self-reported EQ-D-L data on over , individuals from countries with nationally representative population surveys. Socio-demographic indicators employed were age, sex, educational level and income. Logistic regression odds ratios and the health concentration index methodology were used in the socio-demographic analysis of EQ-D-L data. Results: Statistically significant socio-demographic di erences existed in all countries (p < .) with the EQ VAS based health concentration index varying from. to. across countries. Age had generally the largest contributing share, while educational level also had a consistent role in explaining lower levels of self-reported health. Further analysis in a subset of countries with income data showed that, beyond educational level, income itself had an additional significant impact on self-reported health. Among the dimensions of the EQ-D-L descriptive system, problems with usual activities and pain/discomfort had the largest contribution to the concentration of overall self-assessed health measured on the EQ VAS in most countries. Conclusion: The EQ-D-L was shown to be a powerful multi-dimensional instrument in the analyses of socio-demographic di erences in self-reported health using various analytic methods. It o ered a unique insight of inequalities by health dimensions.
2011
Background Accurate estimates of hypertension prevalence are critical for assessment of population health and for planning and implementing prevention and health care programs. While self-report data is often more economically feasible and readily available compared to clinically measured HBP, these reports may underestimate clinical prevalence to varying degrees. Understanding the accuracy of self-reported data and developing prediction models that correct for underreporting of hypertension in self-reported data are critical tools in the development of more accurate population level estimates, and in planning population-based interventions to reduce the risk of, or more effectively treat, hypertension.. This study examines the accuracy of self-reported data in describing prevalence of clinically measured hypertension in two racially and ethnically diverse urban samples, and evaluates a mechanism to correct self-report data in order to more accurately reflect clinical hypertension p...
Statistics in Medicine, 2009
Interview Survey (NHIS), a larger survey that obtains data solely via interviews. Illustrations involving hypertension, diabetes, and obesity suggest that estimates of health measures based on the multiply imputed clinical values are different from those based on the NHIS self-reported data alone and have smaller estimated standard errors than those based solely on the NHANES clinical data. The paper discusses the relationship of the methods used in the study to two-phase/two-stage/validation sampling and estimation, along with limitations, practical considerations, and areas for future research. Published in