Tina J Navin Cristina1, Jennifer A Stewart Williams2,3, Lynne Parkinson4, David W Sibbritt5, Julie E Byles2. 1. Population Health Division, Centre for Epidemiology and Evidence, NSW Ministry of Health, Sydney, New South Wales, Australia. 2. Research Centre for Gender, Health and Ageing, University of Newcastle, Callaghan, New South Wales, Australia. 3. Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden. 4. Central Queensland University, Rockhampton, Queensland, Australia. 5. Faculty of Health, University of Technology, Sydney, New South Wales, Australia.
Abstract
AIM: To estimate the prevalence of diabetes, heart disease, hypertension and stroke in self-report and hospital data in two cohorts of women; measure sensitivity and agreement between data sources; and compare between cohorts. METHODS: Women born between 1946-1951 and 1921-1926 who participated in the Australian Longitudinal Study on Women's Health (ALSWH); were New South Wales residents; and admitted to hospital (2004-2008) were included in the present study. The prevalence of diabetes, heart disease, hypertension and stroke was estimated using self-report (case 1 at latest survey, case 2 across multiple surveys) and hospital records. Agreement (kappa) and sensitivity (%) were calculated. Logistic regression measured the association between patient characteristics and agreement. RESULTS: Hypertension had the highest prevalence and estimates were higher for older women: 32.5% case 1, 45.4% case 2, 12.8% in hospital data (1946-1951 cohort); 57.8% case 1, 73.2% case 2, 38.2% in hospital data (1921-1926 cohort). Agreement was substantial for diabetes: κ = 0.75 case 1, κ = 0.70 case 2 (1946-1951 cohort); κ = 0.77 case 1, κ = 0.80 case 2 (1921-1926 cohort), and lower for other conditions. The 1946-1951 cohort had 2.08 times the odds of agreement for hypertension (95% CI 1.56 to 2.78; P < 0.0001), and 6.25 times the odds of agreement for heart disease (95% CI 4.35 to 10.0; P < 0.0001), compared with the 1921-1926 cohort. CONCLUSION: Substantial agreement was found for diabetes, indicating accuracy of ascertainment using self-report or hospital data. Self-report data appears to be less accurate for heart disease and stroke. Hypertension was underestimated in hospital data. These findings have implications for epidemiological studies relying on self-report or administrative data.
AIM: To estimate the prevalence of diabetes, heart disease, hypertension and stroke in self-report and hospital data in two cohorts of women; measure sensitivity and agreement between data sources; and compare between cohorts. METHODS:Women born between 1946-1951 and 1921-1926 who participated in the Australian Longitudinal Study on Women's Health (ALSWH); were New South Wales residents; and admitted to hospital (2004-2008) were included in the present study. The prevalence of diabetes, heart disease, hypertension and stroke was estimated using self-report (case 1 at latest survey, case 2 across multiple surveys) and hospital records. Agreement (kappa) and sensitivity (%) were calculated. Logistic regression measured the association between patient characteristics and agreement. RESULTS:Hypertension had the highest prevalence and estimates were higher for older women: 32.5% case 1, 45.4% case 2, 12.8% in hospital data (1946-1951 cohort); 57.8% case 1, 73.2% case 2, 38.2% in hospital data (1921-1926 cohort). Agreement was substantial for diabetes: κ = 0.75 case 1, κ = 0.70 case 2 (1946-1951 cohort); κ = 0.77 case 1, κ = 0.80 case 2 (1921-1926 cohort), and lower for other conditions. The 1946-1951 cohort had 2.08 times the odds of agreement for hypertension (95% CI 1.56 to 2.78; P < 0.0001), and 6.25 times the odds of agreement for heart disease (95% CI 4.35 to 10.0; P < 0.0001), compared with the 1921-1926 cohort. CONCLUSION: Substantial agreement was found for diabetes, indicating accuracy of ascertainment using self-report or hospital data. Self-report data appears to be less accurate for heart disease and stroke. Hypertension was underestimated in hospital data. These findings have implications for epidemiological studies relying on self-report or administrative data.
Authors: Rikke Langballe; Esther M John; Kathleen E Malone; Leslie Bernstein; Julia A Knight; Charles F Lynch; Rebecca M Howell; Roy Shore; Meghan Woods; Patrick Concannon; Jonine L Bernstein; Lene Mellemkjær Journal: J Cancer Surviv Date: 2017-09-29 Impact factor: 4.442