Predicting Malnutrition Risk with Data from Routinely Measured Clinical Biochemical Diagnostic Tests in Free-Living Older Populations.

Saskia P M Truijen,Ailsa A Welch,Lee Hooper,Richard P G Hayhoe,Inez Schoenmakers,Alastair Forbes

doi:10.3390/nu13061883

Saskia P M Truijen, Ailsa A Welch + Show 4 more

Open Access

https://doi.org/10.3390/nu13061883

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Journal: Nutrients	Publication Date: May 31, 2021
Citations: 7	License type: CC BY 4.0

Affiliation: University of East Anglia, Anglia Ruskin University

Abstract

Malnutrition (undernutrition) in older adults is often not diagnosed before its adverse consequences have occurred, despite the existence of established screening tools. As a potential method of early detection, we examined whether readily available and routinely measured clinical biochemical diagnostic test data could predict poor nutritional status. We combined 2008–2017 data of 1518 free-living individuals ≥50 years from the United Kingdom National Diet and Nutrition Survey (NDNS) and used logistic regression to determine associations between routine biochemical diagnostic test data, micronutrient deficiency biomarkers, and established malnutrition indicators (components of screening tools) in a three-step validation process. A prediction model was created to determine how effectively routine biochemical diagnostic tests and established malnutrition indicators predicted poor nutritional status (defined by ≥1 micronutrient deficiency in blood of vitamins B6, B12 and C; selenium; or zinc). Significant predictors of poor nutritional status were low concentrations of total cholesterol, haemoglobin, HbA1c, ferritin and vitamin D status, and high concentrations of C-reactive protein; except for HbA1c, these were also associated with established malnutrition indicators. Additional validation was provided by the significant association of established malnutrition indicators (low protein, fruit/vegetable and fluid intake) with biochemically defined poor nutritional status. The prediction model (including biochemical tests, established malnutrition indicators and covariates) showed an AUC of 0.79 (95% CI: 0.76–0.81), sensitivity of 66.0% and specificity of 78.1%. Clinical routine biochemical diagnostic test data have the potential to facilitate early detection of malnutrition risk in free-living older populations. However, further validation in different settings and against established malnutrition screening tools is warranted.

Highlights

IntroductionMalnutrition (or “undernutrition”) is a major cause of poor health in older age and is associated with loss of body weight and skeletal muscle mass
In order to provide a more readily available tool for early malnutrition screening and detection of at-risk free-living individuals in the community, we investigated the potential of blood measurement data from clinical “routine biochemical diagnostic tests” to predict poor nutritional status
This study has demonstrated that biochemical diagnostic tests routinely used in clinical practice for determining risk of cardiovascular disease, anaemia, diabetes, renal failure, or vitamin D deficiency, could potentially facilitate early screening of poor nutritional status in free-living older individuals

Summary

Introduction

Malnutrition (or “undernutrition”) is a major cause of poor health in older age and is associated with loss of body weight and skeletal muscle mass. As such, it is linked with sarcopenia [1], the loss of skeletal muscle mass and function with age [2] and reduced immuno-resilience [3], as well as with frailty, falls and fractures [4,5,6] and premature mortality [7,8]. Health and social care costs associated with the detrimental effects of malnutrition are estimated to be £23.5 billion in the UK, with costs for malnourished patients estimated to be three times higher than for others [14], due to increased visits to primary care, hospital admissions and duration of hospitalisation [8,14]

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