| Information component |
Pg 4 Health Summary – Indicator No 14 |
| Subject category / domain(s) |
The way we live |
| Indicator name (* Indicator title in health profile) |
Estimated prevalence of adults who eat healthily (*Healthy eating adults) |
| PHO with lead responsibility |
SEPHO |
| Date of PHO dataset creation |
15/12/2006 |
| Indicator definition |
Prevalence of healthy eating, percentage of resident population, adults, 2000-2002, persons |
| Geography |
Local Authority: County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs. |
| Timeliness |
Updated as ad-hoc; the next generation of synthetic estimates is due for release in Summer 2007. |
|
Rationale:What this indicator purports to measure
|
Expected prevalence of adult healthy eating that is adults who consume 5 or more portions of fruit and vegetables per day. |
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Rationale:Public Health Importance
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The indicator is a measure of a protective lifestyle factor. A diet rich in fruit and vegetables confers protective effects against the development of heart disease and certain cancers. It has been estimated that eating at least 5 portions of a variety of fruit and vegetables a day could reduce the risk of deaths from chronic diseases such as heart disease, stroke, and cancer by up to 20%.It has been estimated that diet might contribute to the development of one-third of all cancers, and that increasing fruit and vegetable consumption is the second most important cancer prevention strategy, after reducing smoking. In 1998, the Department of Health’s Committee on Medical Aspects of Food Policy and Nutrition reviewed the evidence and concluded that higher vegetable consumption would reduce the risk of colorectal cancer and gastric cancer. There was also weakly consistent evidence that higher fruit and vegetable consumption would reduce the risk ofbreast cancer. These cancers combined represent about 18% of the cancer burden in men and about 30% in women.Higher consumption of fruit and vegetables also reduces the risk of coronary heart disease and stroke. A recent study found that each increase of 1 portion of fruit and vegetables a day lowered the risk of coronary heart disease by 4% and the risk of stroke by 6%. Evidence also suggests an increase in fruit and vegetable intake can help lower blood pressure. Research suggests that there are other health benefits, including delaying the development of cataracts, reducing the symptoms of asthma,improving bowel function, and helping to manage diabetes. As well as the direct health benefits, eating fruit and vegetables can help to achieve other dietary goals including increasing fibre intake, reducing fat intake, help maintain a healthy weight, and substituting for foods with added sugars (as frequent consumption of foods with added sugars can contribute to tooth decay). |
| Rationale: Purpose behind the inclusion of the indicator |
To estimate the expected proportion of adults who 5 or more portions of fruit and vegetables per day in local authorities given the characteristics of local authority populations.To help increase the prevalence of healthy eating and the health benefits associated with eating a healthy diet. |
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Rationale:Policy relevance
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Choosing Health: Making healthy choices easier.http://www.dh.gov.uk/en/Publicationsandstatistics/ Publications/PublicationsPolicyAndGuidance/DH_4094550 Department of Health National 5 A Day programmehttp://www.dh.gov.uk/en/Policyandguidance/Healthandsocialcaretopics/ FiveADay/FiveADaygeneralinformation/index.htmThe NHS Planhttp://www.dh.gov.uk/en/Publicationsandstatistics/Publications/ PublicationsPolicyAndGuidance/DH_4002960The NHS Cancer Planhttp://www.dh.gov.uk/en/Publicationsandstatistics/Publications/ PublicationsPolicyAndGuidance/DH_4009609National Service Framework for Coronary Heart Diseasehttp://www.dh.gov.uk/en/ Publicationsandstatistics/Publications/ PublicationsPolicyAndGuidance/DH_4094275 National Service Framework for Diabetes http://www.dh.gov.uk/en/Policyandguidance/ Healthandsocialcaretopics/Diabetes/DH_4015717 National Service Framework for Older People http://www.dh.gov.uk/en/Publicationsandstatistics/ Publications/PublicationsPolicyAndGuidance/DH_4003066 |
| Interpretation: What a high / low level of indicator value means |
Given the characteristics of the local population, a high indicator value (amber circle in health summary chart) represents a statistically significant higher proportion of adults who are estimated to consume 5 or more portions of fruit and vegetables per day when compared to the national value.Given the characteristics of the local population, a low indicator value (red circle in health summary chart) represents a statistically significant lower proportion of adults who are estimated to consume 5 or more portions of fruit and vegetables per day when compared to the national value. |
| Interpretation: Potential for error due to type of measurement method |
It is important that users note that as these synthetic estimates are modelled they do not take account of any additional local factors that may impact on the true healthy eating prevalence rate in an area (e.g. local initiatives designed to increase consumption of fruit and vegetables). The figures, therefore, cannot be used to monitor performance or change over time.The model is a non-aetiological model i.e. is not based on known aetiological risk factors. This may lead to estimated fruit and vegetable consumption levels which are at odds with, for example, local lifestyle survey results or modelled estimates which use known co-variates such as socio-economic status, age, gender and ethnicity such as the fruit and vegetable consumption estimates modelled in the Health Poverty Index available at www.hpi.org.uk (see variables used in generation of model in calculation of indicator section below).There may also be a discrepancy between the modelled lower tier estimates (districts) and upper tier (County geographies and above) estimates which are based on actual Health Survey for England data. This has lead to inconsistencies between lower tier and county estimates for some areas as the datasets are derived using different methods. |
| Interpretation: Potential for error due to bias and confounding |
The synthetic estimates are subject to both sampling error and modelling error. Sampling error arises from the fact that only one of a number of possible samples from the population has been selected. Generally, the smaller the sample size the larger the variability in the estimates that one would expect to obtain from all the possible samples. The use of statistical models for prediction involves making assumptions about relationships in the data. The suitability of the chosen models for the given data and the validity of the model in describing real world dynamics have a bearing on the nature and magnitude of the errors introduced. A key source of modelling error arises from omitting variables that would otherwise help improve the model predictions either by error or because there is no available or reliable data source for them.The synthetic estimate generated for a particular area is the expected measure for that area based on its population characteristics – and not an estimate of the actual prevalence. In statistical terms, the synthetic estimate is actually a biased estimate of the true value for the area and, as such, should be treated with caution. As mentioned above, the model-based estimates are unable to take account of any additional local factors that may impact on the true prevalence rate (e.g. local initiatives designed to increase fruit and vegetable consumption).Validation exercises were used to check the appropriateness of the chosen models. Confidence intervals are placed around the synthetic estimates to capture both sampling and modelling error. The confidence intervals provide a range within which we can be fairly sure the ‘true’ value for that area lies. We recommend that users need to look at the confidence interval for the estimates, not just the estimate. Estimates for two areas can only be described as significantly different if the confidence intervals for the estimates do not overlap.Users should also note that the potential sources of bias and error also apply to any ranking or banding of the small-area estimates. NatCen do not encourage any ranking of small area estimates within larger areas such as Local Authorities, Primary Care Organisations and Strategic Health Authorities. |
| 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. |
