Long term conditions

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Introduction

Advances in medicine mean that people can increasingly live with conditions such as diabetes or some cancers that would have taken many years off their lives in the past.  These long-term conditions (LTCs) – most of which are normally incurable – can place considerable restrictions on daily activities.  Many of the conditions show a higher prevalence in more deprived communities.

THIS ANALYSIS IS LARGELY DERIVED FROM THE JSNA FOCUSED REPORT ON 'AGEING WELL' AND WHILST THE OVERALL PICTURE IS UNLIKELY TO HAVE CHANGED SIGNIFICANTLY MOST DETAILED LOCAL FIGURES ARE NO LONGER CURRENT 

Current Picture of the Population

Many of the data sources on illness are based on specific points in time, such as diagnosis, hospital admission or death.  An examination of long term illness relies on information about the numbers of people living with conditions within the population, as can be found in the Quality Outcomes Framework (QOF) and Symphony databases.

Symphony data are derived directly from health records in Somerset; QOF also uses Somerset data from a national data collection – and gives some different numbers, especially for chronic kidney disease (CKD).  It is not clear why this should be the case; the fact that some QOF measures are only for adults (Depression 18+, Diabetes 17+,CKD 18+) may explain some of the difference but as these conditions are generally rare amongst children that is unlikely to be enough. It is more likely that the definitions and/or data extraction protocols differ.  The prevalences from the two sources are shown in the table below. The conditions shown are the priority conditions included in the Symphony co-morbidity cohort: Depression, Cancer, Diabetes, Coronary heart disease (CHD), Stroke, Chronic Obstructive Pulmonary Disease (COPD), Dementia and Chronic Kidney Disease (CKD)

Population Prevalence of Long Term Conditions in Somerset 2013/14

The graph below is taken from Symphony and shows the relationship of prevalence of multi-morbidity with age.

Number of Episode Treatment Groups by Age (click to enlarge)

(ETGs are “episode treatment groups”)

The graph shows clearly how the large majority of people are born with no (diagnosed) long term conditions.  This proportion declines with age until at 55 years of age only half the population does not have an LTC.  By 85 years of age only about 10% of the population does not have one of these conditions (and indeed may have others).  The risk of these long term conditions developing earlier is highest amongst people affected by lifestyle factors, notably smoking, poor diet, lack of exercise, excessive alcohol consumption and social isolation.

Click here to download a series of graphs showing the prevalence of conditions by age.  It is clear that the pattern of increasing prevalence is common to many of the conditions considered.  Some, though (asthma, depression, mental ill health, epilepsy and obesity) show less of a relationship with age, with the highest prevalence in the younger and middle years). 

Prevalence by deprivation quintile

Given the link to lifestyle it is no surprise that the prevalence of LTCs is related to social inequality in Somerset.  Click here to download a series of graphs showing prevalence values plotted against quintiles in the Index of Multiple Deprivation, based on residence.  Quintile 1 represents the most deprived areas and Quintile 5 the least deprived (using National quintiles).  Prevalence values are only plotted when there are at least 100 cases. 

In general the prevalence is highest in the more deprived areas, and lowest in the least deprived.  The trends of some conditions (Hypertension, Diabetes, CHD, Stroke, COPD, LVD HF and Dementia) suggest,  to varying degrees, a diminishing inequality with deprivation as age increases.  Rather than improving equality it is likely that this reflects higher death rates from the conditions amongst more deprived groups, leaving an overall healthier cohort behind.

Future Needs of the Population

It is possible to apply condition prevalence rates to population projections to estimate future prevalence.  This is done for population aged 65 and over by the POPPI project (www.poppi.org.uk) and for adults aged 16-64 by PANSI (www.pansi.org.uk).  Examples are shown below.

References

Current data are from Quality Outcomes Framework (http://content.digital.nhs.uk/qof) and Symphony (http://www.symphonyintegratedhealthcare.com/).  Projections are taken from POPPI (www.poppi.org.uk) and PANSI (www.pansi.org.uk) .

Author: Pip Tucker

Review: Figures updated in 2021.  Next review in 2023