| Information component |
Pg 4 Health Summary – Indicator No 20 |
| Subject category / domain(s) |
How long we live and what we die of |
| Indicator name (* Indicator title in health profile) |
Mortality rate from all circulatory diseases (*Early deaths: heart disease & stroke) |
| PHO with lead responsibility |
SEPHO |
| Date of PHO dataset creation |
December 2006 |
| Indicator definition |
Mortality from all circulatory diseases, directly age-standardised rate, persons, under 75, 2003-05 (pooled), per 100,000 European Standard population |
| Geography |
England, GOR, Local Authority: Counties, County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs (boundaries as at April 2006). |
| Timeliness |
The Compendium mortality from all circulatory diseases indicator is updated annually, usually around November following the publication by ONS of the new year’s mortality extract (usually in May) and mid-year population estimates (usually August-September). |
|
Rationale:What this indicator purports to measure
|
Early mortality from all circulatory diseases. |
|
Rationale:Public Health Importance
|
Circulatory disease accounts for 40% of all deaths (30% under 75). Mortality is a direct measure of health care need reflecting the overall circulatory disease burden on the population, both the incidence of disease and the ability to treat it. The mortality rate may be improved by reducing the population’s risk (e.g. encouraging healthier lifestyles and reducing exposure to smoking), by earlier detection of disease and by more effective treatment. |
| Rationale: Purpose behind the inclusion of the indicator |
To estimate premature mortality due to circulatory diseases.To reduce premature deaths from circulatory diseases. |
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Rationale:Policy relevance
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The under 75 circulatory disease mortality rate is a key target indicator in the 1999 Public Health White Paper ‘Saving Lives: Our Healthier Nation’. The target is to reduce the number of deaths from circulatory disease in people aged under 75 years by at least two-fifths by 2010. The baseline for monitoring this target was the three year period 1995-97.This measure supports delivery of the Department of Health PSA targets and LDP and is relevant to Choosing Health, Coronary Heart Disease NSF and Programme for Action. |
| Interpretation: What a high / low level of indicator value means |
A high indicator value (red circle in health summary chart) represents a statistically significant higher rate of early deaths from circulatory disease for that local authority when compared to the national value.A low indicator value (amber circle in health summary chart) represents a statistically significant lower rate of early deaths from circulatory disease for that local authority when compared to the national value. |
| Interpretation: Potential for error due to type of measurement method |
Coverage can be considered to be complete as the registration of deaths is a legal requirement. Data quality for the relevant fields (age, sex, underlying cause of death, area of residence) is extremely high. There is the potential for the underlying cause of death to be incorrectly attributed on the death certificate and, therefore, the cause of death misclassified. |
| Interpretation: Potential for error due to bias and confounding |
The rates are age-standardised. This improves the comparability of rates for different areas, or between different time periods, by taking into account differences in the age structures of the populations being compared. |
| Confidence Intervals: Definition and purpose |
A confidence interval is a range of values that is normally used to describe the uncertainty around a point estimate of a quantity, for example, a mortality rate. This uncertainty arises as factors influencing the indicator are subject to chance occurrences that are inherent in the world around us. These occurrences result in random fluctuations in the indicator value between different areas and time periods. In the case of indicators based on a sample of the population, uncertainty also arises from random differences between the sample and the population itself.The stated value should therefore be considered as only an estimate of the true or ‘underlying’ value. Confidence intervals quantify the uncertainty in this estimate and, generally speaking, describe how much different the point estimate could have been if the underlying conditions stayed the same, but chance had led to a different set of data. The wider is the confidence interval the greater is the uncertainty in the estimate.Confidence intervals are given with a stated probability level. In Health Profiles 2007 this is 95%, and so we say that there is a 95% probability that the interval covers the true value. The use of 95% is arbitrary but is conventional practice in medicine and public health. The confidence intervals have also been used to make comparisons against the national value. For this purpose the national value has been treated as an exact reference value rather than as an estimate and, under these conditions, the interval can be used to test whether the value is statistically significantly different to the national. If the interval includes the national value, the difference is not statistically significant and the value is shown on the health summary chart with a white symbol. If the interval does not include the national value, the difference is statistically significant and the value is shown on the health summary chart with a red or amber symbol depending on whether it is worse or better than the national value respectively. |
