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Standardisation Anthea Springbett
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Topics covered in this session Population rates Why do we standardise? How do we standardise? Comparing standardised rates Which method is best?
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Diet: In 2008, 25% of men and 29% of women in England & Wales reported meeting the government ‘5 a day’ guidelines of consuming five or more portions of fruit and vegetables a day. Exercise cuts risk of developing bowel cancer polyps People who lead an active lifestyle are up to three times less likely to develop polyps which can develop into bowel cancer, according to a study. Passive smoking ‘raises breast cancer risk’ Exposure to second-hand tobacco smoke as a child or adult appears to increase a woman's risk of breast cancer, experts say. Their study of nearly 80,000 women found breast cancer risk was a third higher among those who had clocked up decades of passive smoking. Population Rates Cannabis use 'raises psychosis risk' Using cannabis as a teenager or young adult increases the risk of psychosis, a report suggests. Coronary Heart Disease The estimated prevalence of coronary heart disease based on admission to hospital is 3.3% of the Scottish population. Prevalence is higher in males (4.2%) than in females (2.5%) and is strongly related to age. An estimated 16% of the Scottish population aged 75+ is living with coronary heart disease (CHD). In some, more deprived, community health partnerships around 25% of men aged 75+ have CHD. Registrations with the NHS General Dental Service in Scotland The 6-12 age group had the highest level of population registered (94.7%) with an NHS GDS dentist. NHS Ayrshire & Arran had the highest level of population (all ages) registered with an NHS GDS dentist (77.6%).
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Why do we standardise Comparison of rates over time or between geographical areas etc. Populations differing in structure (age, sex, deprivation …). Comparisons of crude rates may not be sensible. Cardiovascular prescribing 2001-10
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Jargon Target population(s) – the population(s) that we are interested in. Standard population – the population that we use to construct comparisons with and between target populations. Directly & indirectly standardised rates – two different forms of standardisation.
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Health warning This talk concentrates on age standardisation. In real life it is likely that you will need to standardise by age, sex and possibly additional variables (eg SIMD).
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How do we standardise? Miami and Alaska
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Example (deaths in USA)
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Crude death rate for Miami or Alaska = (deaths for all age groups) (pop n s for all age groups) Age-specific death rate is the crude death rate for a specific age group.
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Example (deaths in USA) Miami and Alaska Miami crude death rate = 5022/562,887 = 8.9 per thousand Alaska crude death rate = 285/106,917 = 2.7 per thousand Is Miami really that much worse?
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Example (deaths in USA) State population distributions and age-specific rates *Age-specific death rate per thousand population
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Example (deaths in USA) State population distributions and age-specific rates *Age-specific death rate per thousand population
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Example (deaths in USA) State population distributions and age-specific rates *Age-specific death rate per thousand population
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Example (deaths in USA) State population distributions and age-specific rates *Age-specific death rate per thousand population
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Directly standardised rate Relative sizes of age groups affect crude rate comparison. Weighting of age specific rates differs between target populations. Use standard age group sizes and apply age specific rates to these. Result is a directly standardised rate.
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Directly standardised rate Standard population (USA)
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Directly standardised rate Directly age standardised rate for Miami = Σ (standard weight x age specific rate) Σ (standard weights) where sum (Σ) is over all age groups, and weight = size of standard population for each age group
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Directly standardised rate Directly age standardised rate for Miami = Σ (standard weight x age specific rate) Σ (standard weights) where sum (Σ) is over all age groups, and weight = size of standard population for each age group USA Miami
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Directly standardised rate Miami: (67 x 1.2 + 22 x 7.1 + 12 x 39.1)/100 = 6.9
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Directly standardised rate Miami: (67 x 1.2 + 22 x 7.1 + 12 x 39.1)/100 = 6.9
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Directly standardised rate Crude rates 8.9 2.7
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Direct standardisation Direct standardisation applies age specific rates from the target population(s) to the age group sizes in a standard population. Answers the question: What would the rate in the standard population be if it had the same age specific rates as the target population? Allows comparison between target populations.
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Direct standardisation Standard populations How do you choose the right standard population? –Relevant to target population(s) eg Scottish population for HB comparisons –Appropriate for comparison being made eg hospital population for surgery outcome data
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Direct standardisation Direct standardisation applies age-specific rates from the target population to the age group structure of a standard population. What do you do if you cannot get age- specific rates for the target population or if these rates are unstable (eg because of low numbers in some age groups)?
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Indirect standardisation Indirect standardisation applies age-specific rates from the standard population to the age group structure of the target population. Then constructs ratio of observed to expected population rates. Answers question: How does the observed rate compare with the expected rate?
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Methods of standardisation DirectIndirect Target population Group specific rates Group population sizes Standard population Group population sizes Group specific rates
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Indirect standardisation Indirectly standardised rates are usually presented as ratios (eg Standardised Mortality Ratio): Σ (target age specific rates x weights) Σ (standard age specific rates x weights) where sum (Σ) is over all age groups, and weight = target population for each age group
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Indirect standardisation Miami Indirectly standardised rates for Miami: Σ (target age specific rates x weights) Σ (standard age specific rates x weights) where sum (Σ) is over all age groups, and weight = target population for each age group Miami USA Miami
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Indirect standardisation Miami *Age-specific death rate per thousand population
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Indirect standardisation Miami *Age-specific death rate per thousand population Expected deaths <45 yrs for Miami = 328,049 x 1.2 / 1,000 = 383
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Indirect standardisation Miami *Age-specific death rate per thousand population Expected deaths <45 yrs for Miami = 328,049 x 1.2 / 1,000 = 383
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Indirect standardisation Miami Miami SMR = observed deaths/expected deaths = 5022/5965 = 0.84 *Age-specific death rate per thousand population
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Indirect standardisation Miami Miami SMR = observed deaths/expected deaths = 5022/5965 = 0.84 *Age-specific death rate per thousand population
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Indirect standardisation Miami Miami SMR = observed deaths/expected deaths = 5022/5965 = 0.84 *Age-specific death rate per thousand population
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Indirect standardisation Miami Miami SMR = observed deaths/expected deaths = 5022/5965 = 0.84 *Age-specific death rate per thousand population
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Indirect standardisation Miami Miami SMR = observed deaths/expected deaths = 5022/5965 = 0.84 *Age-specific death rate per thousand population
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Indirect standardisation Alaska Alaska SMR = observed deaths/expected deaths = 285/315 = 0.91 *Age-specific death rate per thousand population
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Indirect standardisation Alaska Alaska SMR = observed deaths/expected deaths = 285/315 = 0.91 *Age-specific death rate per thousand population
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Comparison of standardised rates Direct standardisation: Weighted average of target population age specific rates. Can compare standardised rates for two target populations that were calculated using same standard population weights. Indirect standardisation: Comparisons can be made only if certain conditions are met (not usually the case).
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Comparison of standardised rates Confidence limits There are several methods for calculating confidence limits for comparison of directly and indirectly standardised rates. References supplied on last slide and in folder.
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Additional points Standardisation for multiple categories Age, sex, SIMD, …. Is standardisation the right solution? Group specific rates may be more appropriate Indirect vs direct What sort of comparison do you want? What sort of data have you got?
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References 1.Eastern Region PHO technical briefing on standardisation (INphoRM 6), which calculates and comments on both directly and indirectly standardised rates and includes the calculation of confidence intervals. http://www.erpho.org.uk/ 2.APHO website has spreadsheets for calculating direct and indirectly standardised rates (Technical Briefing 3). http://www.apho.org.uk/ 3.Standardisation of rates and ratios (hard copy in course materials) 4.ISD guide to standardisation (available today)
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