Comparing self‐reported and measured high blood pressure and high cholesterol status using data from a large representative cohort study
To examine the relationship between self‐reported and clinical measurements for high blood pressure (HBP) and high cholesterol (HC) in a random population sample. A representative population sample of adults aged 18 years and over living in the north‐west region of Adelaide (n=1537) were recruited t...
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Veröffentlicht in: | Australian and New Zealand journal of public health 2010-08, Vol.34 (4), p.394-400 |
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Sprache: | eng |
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Zusammenfassung: | To examine the relationship between self‐reported and clinical measurements for high blood pressure (HBP) and high cholesterol (HC) in a random population sample.
A representative population sample of adults aged 18 years and over living in the north‐west region of Adelaide (n=1537) were recruited to the biomedical cohort study in 2002/03. In the initial cross‐sectional component of the study, self‐reported HBP status and HC status were collected over the telephone. Clinical measures of blood pressure were obtained and fasting blood taken to determine cholesterol levels. In addition, data from a continuous chronic disease and risk factor surveillance system were used to assess the consistency of self‐reported measures over time.
Result: Self‐report of current HBP and HC showed >98% specificity for both, but sensitivity was low for HC (27.8%) and moderate for HBP (49.0%). Agreement between current self‐report and clinical measures was moderate (kappa 0.55) for HBP and low (kappa 0.30) for HC. Demographic differences were found with younger people more likely to have lower sensitivity rates. Self‐reported estimates for the surveillance system had not varied significantly over time.
Although self‐reported measures are consistent over time there are major differences between the self‐reported measures and the actual clinical measurements. Technical aspects associated with clinic measurements could explain some of the difference.
Monitoring of these broad population measures requires knowledge of the differences and limitations in population settings. |
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ISSN: | 1326-0200 1753-6405 |
DOI: | 10.1111/j.1753-6405.2010.00572.x |