Standardisation Anthea Springbett. Topics covered in this session Population rates Why do we standardise? How do we standardise? Comparing standardised

Standardisation

Anthea Springbett

Topics covered in this session

• Population rates

• Why do we standardise?

• How do we standardise?

• Comparing standardised rates

• Which method is best?

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 RatesCannabis use 'raises psychosis risk'

Using cannabis as a teenager or young adult increases the risk of

psychosis, a report suggests.

Coronary Heart DiseaseThe 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%).

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.

0

6,000,000

12,000,000

18,000,000

24,000,000

30,000,000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Num

ber o

f Pre

scrib

ed It

ems

0

50,000,000

100,000,000

150,000,000

200,000,000

250,000,000

Gross Ingredient Cost (£)

Number of Prescribed Items Gross Ingredient Cost (£)

Cardiovascular prescribing 2001-10

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.

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).

How do we standardise?Miami and Alaska

Example (deaths in USA)

Age (yrs)Population

sizeDeaths

Population size

Deaths

<45 328,049 401 89,893 114

45-64 142,670 1,016 14,947 90

65+ 92,168 3,605 2,077 81

Total 562,887 5,022 106,917 285

Miami Alaska

Example (deaths in USA)

Crude death rate for Miami or Alaska =

(deaths for all age groups)

(popns for all age groups)

Age-specific death rate is the crude death rate for a specific age group.

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?

Example (deaths in USA) State population distributions and age-specific rates

Miami Alaska

Age (yrs) Population size

Population (%)

Age-specific

rate*Population

sizePopulation

(%)

Age-specific

rate*

<45 328,049 58 1.2 89,893 84 1.3

45-64 142,670 25 7.1 14,947 14 6.0

65+ 92,168 16 39.1 2,077 2 39.0

Total 562,887 100 8.9 106,917 100 2.7

*Age-specific death rate per thousand population

Example (deaths in USA) State population distributions and age-specific rates

Miami Alaska


Population (%)

Age-specific

rate*Population

sizePopulation

(%)

Age-specific

rate*

<45 328,049 58 1.2 89,893 84 1.3

45-64 142,670 25 7.1 14,947 14 6.0

65+ 92,168 16 39.1 2,077 2 39.0

Total 562,887 100 8.9 106,917 100 2.7


Example (deaths in USA)State population distributions and age-specific rates

Miami Alaska


Population (%)

Age-specific

rate*Population

sizePopulation

(%)

Age-specific

rate*

<45 328,049 58 1.2 89,893 84 1.3

45-64 142,670 25 7.1 14,947 14 6.0

65+ 92,168 16 39.1 2,077 2 39.0

Total 562,887 100 8.9 106,917 100 2.7


Example (deaths in USA)State population distributions and age-specific rates

Miami Alaska


Population (%)

Age-specific

rate*Population

sizePopulation

(%)

Age-specific

rate*

<45 328,049 58 1.2 89,893 84 1.3

45-64 142,670 25 7.1 14,947 14 6.0

65+ 92,168 16 39.1 2,077 2 39.0

Total 562,887 100 8.9 106,917 100 2.7


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.

Directly standardised rateStandard population (USA)

USA Miami Alaska

Age (yrs) Population (%)

Population (%)

Population (%)

<45 67 58 84

45-64 22 25 14

65+ 12 16 2

Total 100 100 100


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


Directly age standardised rate for Miami =

Σ(standard weight x age specific rate)

Σ(standard weights)


weight = size of standard population for each age group

USA

Miami


Age (yrs) US Population (%)

Age-specific rate (Miami)

Age-specific rate (Alaska)

<45 67 1.2 1.3

45-64 22 7.1 6.0

65+ 12 39.1 39.0

Total 100 6.9 6.7

Directly standardised rates for Miami and Alaska

Miami: (67 x 1.2 + 22 x 7.1 + 12 x 39.1)/100 = 6.9





<45 67 1.2 1.3

45-64 22 7.1 6.0

65+ 12 39.1 39.0

Total 100 6.9 6.7


Miami: (67 x 1.2 + 22 x 7.1 + 12 x 39.1)/100 = 6.9





<45 67 1.2 1.3

45-64 22 7.1 6.0

65+ 12 39.1 39.0

Total 100 6.9 6.7


Crude rates 8.9

2.7

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.

Direct standardisationStandard 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

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)?

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?

Methods of standardisation

Direct Indirect

Target population

Group specific rates

Group population

sizes

Standard population

Group population

sizes

Group specific rates

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)


weight = target population for each age group

Indirect standardisationMiami

Indirectly standardised rates for Miami:

Σ(target age specific rates x weights)

Σ(standard age specific rates x weights)


weight = target population for each age group

Miami

USA Miami


Miami Miami US MiamiAge (yrs) Population Observed

DeathsAge-specific

rate*Expected

deaths

<45 328,049 401 1.2 383

45-64 142,670 1,016 7.1 1,019

65+ 92,168 3,605 49.5 4,563Total 562,887 5,022 8.1 5,965




DeathsAge-specific

rate*Expected

deaths

<45 328,049 401 1.2 383

45-64 142,670 1,016 7.1 1,019

65+ 92,168 3,605 49.5 4,563Total 562,887 5,022 8.1 5,965


Expected deaths <45 yrs for Miami = 328,049 x 1.2 / 1,000 = 383



DeathsAge-specific

rate*Expected

deaths

<45 328,049 401 1.2 383

45-64 142,670 1,016 7.1 1,019

65+ 92,168 3,605 49.5 4,563Total 562,887 5,022 8.1 5,965


Expected deaths <45 yrs for Miami = 328,049 x 1.2 / 1,000 = 383


Miami Miami Miami US MiamiAge (yrs) Population Observed

DeathsAge-specific

rate*Age-specific

rate*Expected

deaths

<45 328,049 401 1.2 1.2 383

45-64 142,670 1,016 7.1 7.1 1,019

65+ 92,168 3,605 39.1 49.5 4,563

Total 562,887 5,022 8.9 8.1 5,965

Miami SMR = observed deaths/expected deaths

= 5022/5965

= 0.84




DeathsAge-specific

rate*Age-specific

rate*Expected

deaths

<45 328,049 401 1.2 1.2 383

45-64 142,670 1,016 7.1 7.1 1,019

65+ 92,168 3,605 39.1 49.5 4,563

Total 562,887 5,022 8.9 8.1 5,965


= 5022/5965

= 0.84




DeathsAge-specific

rate*Age-specific

rate*Expected

deaths

<45 328,049 401 1.2 1.2 383

45-64 142,670 1,016 7.1 7.1 1,019

65+ 92,168 3,605 39.1 49.5 4,563

Total 562,887 5,022 8.9 8.1 5,965


= 5022/5965

= 0.84




DeathsAge-specific

rate*Age-specific

rate*Expected

deaths

<45 328,049 401 1.2 1.2 383

45-64 142,670 1,016 7.1 7.1 1,019

65+ 92,168 3,605 39.1 49.5 4,563

Total 562,887 5,022 8.9 8.1 5,965


= 5022/5965

= 0.84




DeathsAge-specific

rate*Age-specific

rate*Expected

deaths

<45 328,049 401 1.2 1.2 383

45-64 142,670 1,016 7.1 7.1 1,019

65+ 92,168 3,605 39.1 49.5 4,563

Total 562,887 5,022 8.9 8.1 5,965


= 5022/5965

= 0.84


Indirect standardisationAlaska

Alaska Alaska Alaska US AlaskaAge (yrs) Population Observed

DeathsAge-specific

rateAge-specific

rateExpected

deaths

<45 89,893 114 1.3 1.2 105

45-64 14,947 90 6.0 7.1 107

65+ 2,077 81 39.0 49.5 103

Total 106,917 285 2.7 8.1 315

Alaska SMR = observed deaths/expected deaths

= 285/315

= 0.91


Indirect standardisationAlaska

Alaska Alaska Alaska US AlaskaAge (yrs) Population Observed

DeathsAge-specific

rateAge-specific

rateExpected

deaths

<45 89,893 114 1.3 1.2 105

45-64 14,947 90 6.0 7.1 107

65+ 2,077 81 39.0 49.5 103

Total 106,917 285 2.7 8.1 315

Alaska SMR = observed deaths/expected deaths

= 285/315

= 0.91


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).

Comparison of standardised ratesConfidence 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.

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?

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)

http://www.erpho.org.uk/

http://www.apho.org.uk/

Documents

Standardisation Anthea Springbett. Topics covered in this session Population rates Why do we standardise? How do we standardise? Comparing standardised