Crude Rates and Standardisation

1. Crude Rates and Standardisation • Standardisation: used widely when making comparisons of rates between population groups and over time (ie. Number of health events per population) • Mainly used to adjust rates so that populations with different age and sex structures can be compared • 2 types: Direct and Indirect Standardisation • There is no need to age standardise for those indicators which are based on narrowly defined age bands. For these indicators crude rate comparisons are valid. • Eg infant mortality rate, teenage pregnancy rate • Direct Standardisation: allows populations with different age and sex structures to be directly compared ( Directly Standardised Rate DSR) • - the crude rates in the study population (eg Mansfield PCT) are applied to a standard population (European Standard Population): produces a rate usually per 100,000 population • Indirect standardisation: means that rates from a standard population (eg England & Wales) are applied to the study population (eg Mansfield PCT) to calculate expected events; then the observed events are divided by expected events to calculate a standardised ratio (eg Standardised Mortality Ratio = SMR) • - SMR of 100 indicates no difference in mortality between local and standard groups • - SMR of 90 indicates a local death rate 10 percent lower than standard • - SMR of 110 indicates a local death rate 10 percent higher than standard

2. Example 1: DSR comparison The age and sex specific rates over a 5 year period for each ward in Mansfield are applied to the European standard population to produce a rate per 100,000 population

3. Example 2: SMR Comparison Premature death rates in 1993 for Mansfield were 33% higher than for England in 2001 Shows a trend in the SMR: is a premature mortality <75 measure; is adjusted for age and gender differences between years: error bars show whether Mansfield ratio significantly above Trent and England ratio. The standard population rates are those for England and Wales in 2001, males and females separately, for ages <1, 1-4, then quinary ie 5-9, 10-14 etc to 85+. This explains why the national rate is 100 for 2001.

4. Example 3: Crude Rate comparison Purpose: To reduce the number of unwanted pregnancies, particularly in young girls. Definition of indicator and its variants: Estimates of conceptions (excluding pregnancies leading to spontaneous abortions), based on pregnancies which lead to a maternity at which one or more live or still birth occurs and is registered in England and Wales, or a termination of pregnancy by abortion under the 1967 Act in England and Wales.

5. Confidence Intervals & Statistical Significance • Confidence Intervals • Confidence intervals A statistical tool for indicating the accuracy of an estimated figure. • It can reasonably be assumed that the true value lies somewhere within the confidence interval. 95% confidence intervals are commonly used: there is a 5% (or one in 20) chance that the true value lies outside the confidence interval. • Estimates based on small numbers of cases are less accurate and will hence tend to have wide confidence intervals. • Statistical Significance • A statistically significant difference from the regional or national average is indicated when the confidence interval for the region or national average does not overlap with the local confidence interval. Note that this is a more stringent method of assessing whether 2 rates are statistically significantly different than would be the case in classical statistical testing. In a classical statistical test at the 5% level of significance, one would construct a rejection region for say the national rate (ie any value above or below the 95% confidence limits for the national rate), and then if the rate for the region (eg Ashfield PCT) fell inside the rejection region, it would be deemed to be a significantly different rate to the national rate at the 5% level. • Note also the issue of multiple comparisons where at the 5% level of significance, 1 in 20 difference comparisons will be significant by chance alone.

6. Rates for Small Areas • Small Areas • indicators such as suicides and peri-natal deaths tend to have very small numbers of cases per annum or even no cases at a local level • eg for a housing estate, or Sure Start, or Neighbourhood Renewal area • there will be very wide confidence intervals for such indicators, consequently it becomes difficult to demonstrate statistically significant differences with Regional or National rates • one way of getting around this is to combine several years worth of data and compute say a 5 year moving average, or combine areas to get a larger population base • In line with Government policy on “disclosure” (preventing information about an individual being identifiable in official statistics) public health information should be screened so that figures based on counts of less than five are suppressed (shown as a "-").