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Linking the Scottish Health Survey to routine data: CHD incidence and sample representativeness

Linking the Scottish Health Survey to routine data: CHD incidence and sample representativeness. Alastair H Leyland MRC Social & Public Health Sciences Unit University of Glasgow. The purpose of health surveys. Central components of a comprehensive health monitoring system

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Linking the Scottish Health Survey to routine data: CHD incidence and sample representativeness

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  1. Linking the Scottish Health Survey to routine data: CHD incidence and sample representativeness Alastair H Leyland MRC Social & Public Health Sciences Unit University of Glasgow

  2. The purpose of health surveys • Central components of a comprehensive health monitoring system • Valuable information on health status, illnesses, lifestyles... • Interviews/questionnaires are the only way to obtain data on perceived health, symptoms, and health related behaviour Aromaa et al, EJPH 2003; 13:S67-S72.

  3. The Scottish Health Survey • Conducted 1995/6, 1998/9 (and 2003/4) • 1995 survey “a nationally representative sample of adults in the 16-64 age group” • Provided (for the first time) detailed information on the prevalence of specific health conditions, their associated risk factors and the socio-demographic characteristics of the respondents • 3-stage design to make comparisons between (7) regions • 7932 respondents (81%) from 312 postcode sectors • Focus on cardiovascular disease and risk factors

  4. Drawbacks of cross-sectional surveys • Can only be used to indicate prevalence of disease, risk factors etc. (and not incidence) • Can only be used to examine association (and not causation)

  5. Linkage of register data to SHS • 1995 and 1998 Scottish Health Surveys • Linked to death records, acute hospital discharges, psychiatric discharges and cancer registrations • Register data cover 1980-2002

  6. Linkage of 1995 survey data: numbers and percentages • Original survey: 7932 respondents (81%) • Gave permission for linkage of survey to NHS central register: 7363 (92.8%) • Any event: 5077 (69.0%) • All cause mortality: 243 (3.3%) • Psychiatric hospital admissions: 220 (3.0%) • CHD hospital admission: 283 (3.8%)

  7. Analysis of 1995 linked survey • 6 year follow-up from date of interview • Outcomes considered: • Deaths: all-cause, AMI and CHD • First MI or CHD event (hospitalisation or death) • Use linkage to exclude anyone hospitalised with CHD prior to interview • Analysis restricted to 1564 men and 1913 women aged 40-64 at the time of interview with no prior hospitalisation for CHD since 1980

  8. Standardised rates by sex Standardised rates per 100,000 PYAR, ages 40-64

  9. Adjustment for risk factors • Univariate and multivariate adjustment for risk factors: • Marital status, social class, area deprivation, smoking, alcohol use, exercise, BMI • All models adjusted for age and sex • Multilevel logistic regression to take account of clustering of individuals within areas • Results presented as odds ratios (95% C.I.s)

  10. Results for all-cause mortality

  11. Results for all-cause mortality

  12. Results for all-cause mortality

  13. Results for all-cause mortality

  14. Results for all-cause mortality

  15. Results for all-cause mortality

  16. Results for CHD incidence

  17. Results for CHD incidence

  18. Results for CHD incidence

  19. Results for CHD incidence

  20. Results for CHD incidence

  21. Results for CHD incidence

  22. Summary - all-cause mortality • Married participants were at significantly lower risk • Social class gradient disappeared and effect of area deprivation was attenuated following adjustment • Effect of smoking was attenuated but heavy smokers remained at 80% higher risk than non-smokers • Lower risk associated with consumption of up to 28 units of alcohol per week (not significant) • Those taking no exercise had double the odds • BMI <20 associated with increase in risk, 25+ with a decrease relative to BMI 20<25

  23. Summary - CHD incidence • No difference by marital status • Social class gradient disappeared and effect of area deprivation was attenuated following adjustment • Increased incidence among moderate and heavy smokers • Decreasing risk with increasing alcohol consumption • Lowest risk amongst those exercising 0<3 times per week • BMI 25+ associated with high incidence

  24. The utility of a health survey • Depends on it being representative of the population • Or on knowing how it differs from the population • Events in a representative sample should occur at the same rate as in the general population

  25. A Scottish comparison dataset • All people aged 40-64 on 1 July 1995 • Excluding anyone with prior admission for CHD • Six year follow-up • Record of all deaths and hospital admissions by cause • 1.4 million people with 55,000 incident events of CHD • Breakdown by region and deprivation category • Regional population data based on 1995 estimates • Small area population data from 2001 Census

  26. Standardised rates (men) Standardised rates per 100,000 PYAR, ages 40-64

  27. Comparison of CHD mortality rates across deprivation categories Population Survey Mortality per 100,000 PYAR, men aged 40-64

  28. Standardised rates (women) Standardised rates per 100,000 PYAR, ages 40-64

  29. Comparison of CHD hospitalisation rates across deprivation categories Survey Population Hospitalisations per 100,000 PYAR, women aged 40-64

  30. Summary • Men in the SHS have lower CHD mortality than the population • This differential is greater in the most deprived areas • CHD incidence is the same, but these figures are dominated by hospitalisations • Women in the SHS have higher CHD hospitalisation • No difference in affluent or deprived areas • This results in higher incidence but no difference in mortality

  31. Potential sources of bias • Response to the original interview • Agreement to linkage of records

  32. Agreement to NHSCR linkage Proportion agreeing to linkage, by sex and deprivation

  33. Implications • If the surveys are unrepresentative then the estimated prevalence of cardiovascular risk factors may also be unreliable • What are the differences between the sample and the population? • Do they differ in terms of the prevalence of risk factors? • Do they differ in the magnitude of the effect?

  34. Conclusions - general • Linking survey data to routine mortality, hospitalisation and cancer registration data provides a useful epidemiological resource • Enables the study of the effect of risk factors on subsequent development of disease and mortality • Provides a means of looking at representativeness of the survey population • Utility will increase as follow-up increases

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