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01.12.2012 | Research article | Ausgabe 1/2012 Open Access

BMC Health Services Research 1/2012

Hypertension: Development of a prediction model to adjust self-reported hypertension prevalence at the community level

Zeitschrift:
BMC Health Services Research > Ausgabe 1/2012
Autoren:
Graciela Mentz, Amy J Schulz, Bhramar Mukherjee, Trivellore E Ragunathan, Denise White Perkins, Barbara A Israel
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1472-6963-12-312) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

GM participated in the conception of the study, carried out the statistical analysis and drafted the manuscript. AS participated in the conception of the study, and helped to draft the manuscript. BM helped with the identification of the appropriate statistical analysis and helped draft the manuscript. TR helped with conception of the analysis, supervised the statistical analysis.BI helped to draft de manuscript. DWP helped draft the manuscript. All authors read and approved the final manuscript.

Abstract

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-reported 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 can be 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 survey data in describing prevalence of clinically measured hypertension in two racially and ethnically diverse urban samples, and evaluates a mechanism to correct self-reported data in order to more accurately reflect clinical hypertension prevalence.

Methods

We analyze data from the Detroit Healthy Environments Partnership (HEP) Survey conducted in 2002 and the National Health and Nutrition Examination (NHANES) 2001–2002 restricted to urban areas and participants 25 years and older. We re-calibrate measures of agreement within the HEP sample drawing upon parameter estimates derived from the NHANES urban sample, and assess the quality of the adjustment proposed within the HEP sample.

Results

Both self-reported and clinically assessed prevalence of hypertension were higher in the HEP sample (29.7 and 40.1, respectively) compared to the NHANES urban sample (25.7 and 33.8, respectively). In both urban samples, self-reported and clinically assessed prevalence is higher than that reported in the full NHANES sample in the same year (22.9 and 30.4, respectively). Sensitivity, specificity and accuracy between clinical and self-reported hypertension prevalence were ‘moderate to good’ within the HEP sample and ‘good to excellent’ within the NHANES sample. Agreement between clinical and self-reported hypertension prevalence was ‘moderate to good’ within the HEP sample (kappa =0.65; 95% CI = 0.63-0.67), and ‘good to excellent’ within the NHANES sample (kappa = 0.75; 95%CI = 0.73-0.80). Application of a ‘correction’ rule based on prediction models for clinical hypertension using the national sample (NHANES) allowed us to re-calibrate sensitivity and specificity estimates for the HEP sample. The adjusted estimates of hypertension in the HEP sample based on two different correction models, 38.1% and 40.5%, were much closer to the observed hypertension prevalence of 40.1%.

Conclusions

Application of a simple prediction model derived from national NHANES data to self-reported data from the HEP (Detroit based) sample resulted in estimates that more closely approximated clinically measured hypertension prevalence in this urban community. Similar correction models may be useful in obtaining more accurate estimates of hypertension prevalence in other studies that rely on self-reported hypertension.
Zusatzmaterial
Additional file 1: Accuracy is the proportion of true results (bothtrue positive and true negative). (DOC 40 KB)
12913_2011_2187_MOESM1_ESM.doc
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