Together, we can help everyone to love later life Viviane Degbe-Agbeko and Marcus Green Age UK Research Department Who is at risk of undernourishment in later life?
01 Definitions and prevalence of undernourishment
How is undernourishment (malnutrition) defined? Indications for nutrition support in hospital and the community a BMI of less than 18.5 kg/m 2 unintentional weight loss greater than 10 per cent within the last 3–6 months a BMI of less than 20 kg/m 2 and unintentional weight loss greater than 5 per cent within the last 3–6 months. Extract from Nutrition Support in Adults. CG32. NICE (2006) Definitions and prevalence of undernourishment
Undernourishment prevalence in the UK 93 per cent of undernourished individuals aged 65 and over live in the community 5 per cent of undernourished individuals aged 65 and over live in care homes 2 per cent of undernourished individuals aged 65 and over are in hospital BAPEN (2009); Report on the Advisory Group on Malnutrition, led by BAPEN
What is the prevalence of undernourishment in the UK? Geographical areaProportion of those aged 65 and over with a Body Mass Index of less than 20 Number of people aged 65 and over with a Body Mass Index of less than 20 (estimates rounded to nearest thousand) UK4.5%470,000 England4.6%404,000 North5.7%94,000 Midlands, Yorkshire and Humber and the East 3.7%133,000 London5.6%51,000 South4.3%126,000 Wales4.1%23,000 Scotland3.8%34,000 Northern Ireland3.5%9,000 Definitions and prevalence of undernourishment Sources: Understanding Society (2011) and Office for National Statistics (2013)
02 Data and methodology
Data Data and methodology Understanding Society Multi-purpose UK longitudinal study of households in the community Wave 1 – 8,992 individuals aged 65 and over Wave 2 (nurse assessments) – 3,803 individuals aged 65 and over BMI measures Richness of data to build individual profiles
Methodology Data and methodology Literature review to identify factors found to be associated with being undernourished. Interactive community risk profile tool Firth logistic regression analysis used to investigate the relationship between BMI score and socio-demographic, health and attitudinal characteristics. Tool produced using characteristics found to be associated with having a BMI score of less than 20. Logit function used to derive the estimated probability (risk) of being undernourished. Measuring changes in BMI Wave one and wave two (nurse assessments) allowed us to captured BMI score changes of varying magnitude.
03 Identifying individuals at risk of undernourishment in the community at the national level
What are the findings? Identifying individuals at risk of undernourishment in the community at the national level CovariatesResponse values Parameter estimates P-value chi- square Odds ratio Sex1.Female (r) male < Age groupB:65-69 (r) C: D: E:>= < Single in household1.No (r) Yes0.6888< Felt downhearted and depressed1.Most of the time Some of the time A little of the time None of the time (r)
More findings Identifying individuals at risk of undernourishment in the community at the national level CovariatesResponse values Parameter estimates P-value chi- square Odds ratio General health1.Very good (r) Good Fair Poor GHQ: problem overcoming difficulties1.Not at all No more than usual Rather more than usual (r) Satisfaction with amount of leisure time1.Dissatisfied Neither satisfied nor dissatisfied Satisfied (r) Satisfaction with life overall1.Dissatisfied Neither satisfied nor dissatisfied Satisfied (r)
And some more findings… Identifying individuals at risk of undernourishment in the community at the national level CovariatesResponse values Parameter estimates P-value chi- square Odds ratio Local friends mean a lot1.Agree (r) Neither agree nor disagree Disagree Arthritis1.not mentioned (r) mentioned < government office region1.North East North West Yorkshire and the Humber East Midlands West Midlands East of England London South East (r)
And just a few more. Identifying individuals at risk of undernourishment in the community at the national level CovariatesResponse values Parameter estimates P-value chi- square Odds ratio 9.South West Wales Scotland Northern Ireland Total monthly personal income - grossA:Low income (r) B:Median income C:High income
Key findings Females are over twice as likely as males to be undernourished. Individuals aged 80 and over are two times more likely to be undernourished than those aged 65 to 69. Those who live on their own are almost twice as likely to be undernourished as those who are not sole residents. Surprisingly it was found that individuals with arthritis were half as likely as those who did not have arthritis to be undernourished. There is little significant variation in the factors associated with varying levels of decrease in BMI score. Identifying individuals at risk of undernourishment in the community at the national level
04 Going local
How can this research be applied? Going local Targeting people at risk of undernourishment at the local level. There is a lack of local data through surveys and clinical datasets however we can use 2011 Census data to produce neighbourhood level analysis. Using the findings to understand a typology of undernourishment. Testing for local and regional variation in the importance of risk factors – to be undertaken in Spring We are adding modules to our tools that we provide to local partners to help them target older people at risk of undernourishment in their area. The risk profile tool could be useful to healthcare professionals, commissioners and those bidding or delivering health services.