Information component |
Pg 4 Health Summary – Indicator No 24 |
Subject category / domain(s) |
Health and ill health in our community |
Indicator name (* Indicator title in health profile) |
Self Assessed general Health: ‘Not Good’ (*Feeling in poor health) |
PHO with lead responsibility |
NWPHO |
Date of PHO dataset creation |
Dec. ‘06 |
Indicator definition |
Self Assessed General Health: ‘Not Good’, directly age standardized percentage, All Ages, 2001, persons |
Geography |
England, GOR, Local Authority: Counties, County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs |
Timeliness |
Every 10 years, next update available in 2012. Time trend analysis is appropriate. |
Rationale:What this indicator purports to measure
|
Perception of General Health. |
Rationale:Public Health Importance
|
The indicator was chosen as the best available measure of self assessed population health. Self reported single item of health has a good correlation with mortality and health care utilisation.For further information see: Where Wealth means Health (www.nwpho.org.uk/inequlaities) |
Rationale: Purpose behind the inclusion of the indicator |
To help monitor likely health care burden. |
Rationale:Policy relevance
|
No direct policy driver. |
Interpretation: What a high / low level of indicator value means |
A high indicator value (red blob in spine chart) represents a statistically significant higher level of estimated self assessed “not good” health for that local authority when compared to the national value.A low indicator value (yellow blob) represents a statistically significant lower level of estimated self assessed “not good” health for that local authority when compared to the national value. |
Interpretation: Potential for error due to type of measurement method |
Self reported health status can be subject to variation according to non causative effects (e.g. good weather). |
Interpretation: Potential for error due to bias and confounding |
The following groups may be under-sampled within the census: · Areas with high non-white population · Full-time students aged 18-74 (out of term time residents) · Prisoners · Men aged 20-39 · Residential homes, nursing homes, hospitals · Rough sleepers · Areas with high population density · Areas with high numbers of multi-occupancy households · Migrants: someone who spends 3 to 12 months in the country for certain purposes (excluding tourism), ?asylum seekers, ?migrant / seasonal workers, This can result in an underestimate or overestimate of self assessed ill-health in some areas. |
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. |