| Information component |
Pg 4 Health Summary – Indicator No. 17 |
| Subject category / domain(s) |
How long we live and what we die of |
| Indicator name (* Indicator title in health profile) |
Life expectancy – male |
| PHO with lead responsibility |
LHO |
| Date of PHO dataset creation |
Dec 2006 |
| Indicator definition |
Life expectancy at birth, years, all ages, 2003-05, males |
| Geography |
England, GOR, Local Authority: Counties, County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs. |
| Timeliness |
ONS produced data are updated annually in the Autumn of the following year. |
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Rationale:What this indicator purports to measure
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Life expectancy at birth is a summary measure of the all cause mortality rates in an area in a given period. It is the average number of years a new-born baby would survive, were he or she to experience the particular area’s age-specific mortality rates for that time period throughout his or her life. |
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Rationale:Public Health Importance
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All cause mortality is a fundamental and probably the oldest measure of the health status of a population. It represents the cumulative effect of the prevalence of risk factors, prevalence and severity of disease, and the effectiveness of interventions and treatment. Differences in levels of all-cause mortality reflect health inequalities between different population groups, e.g. between genders, social classes and ethnic groups. Life expectancy at birth is chosen as the preferred summary measure of all cause mortality as it quantifies the differences between areas in units (years of life) that are more readily understood and meaningful to the audience than those of other measures. |
| Rationale: Purpose behind the inclusion of the indicator |
To help reduce premature mortality and facilitate planning of health services at local level. |
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Rationale:Policy relevance
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There is a national health inequalities target for life expectancy which aims to increase average life expectancy at birth in England to 78.6 years for men and to 82.5 years for women, and to reduce health inequalities by 10% by 2010 as measured by life expectancy at birth (Department of Health PSA priority 1).Also life expectancy is an indicator in the following:Local basket of inequalities indicators – Indicator 13.12.Opportunity for all – Communities – Indicator 39.Quality of life indicators – Health and social well-being – Indicator 33 |
| Interpretation: What a high / low level of indicator value means |
The higher the life expectancy, the longer the estimated life expectancy for males living in that area at that time. |
| Interpretation: Potential for error due to type of measurement method |
The figures reflect the contemporary mortality among those living in the area in each time period. They are not the number of years a baby born in the area in each time period could actually expect to live, both because the death rates of the area are likely to change in the future and because many of those born in the area will live elsewhere for at least some part of their lives.Life expectancy at birth is also not a guide to the remaining expectancy of life at any other given age. For example, if female life expectancy at birth was 80 years for a particular area, life expectancy of women aged exactly 75 years in that area would exceed 5 years. This reflects the fact that survival from a particular age depends only on the mortality rates beyond that age, whereas survival from birth is based on mortality rates for all ages |
| Interpretation: Potential for error due to bias and confounding |
Older people living in nursing homes tend to be in poorer health than those not living in nursing homes. As these homes are unevenly distributed across the country, a higher death rate – consequently lower life expectancy level – in one area could simply be the result of migration of frail older people moving into nursing homes in that area. |
| 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. |
