Abstract

ObjectivesTo identify early nutritional risk in older populations, simple screening approaches are needed. This study aimed to compare nutrition risk scores, calculated from a short checklist, with diet quality and health outcomes, both at baseline and prospectively over a 2.5-year follow-up period; the association between baseline scores and risk of mortality over the follow-up period was assessed.MethodsThe study included 86 community-dwelling older adults in Southampton, UK, recruited from outpatient clinics. At both assessments, hand grip strength was measured using a Jamar dynamometer. Diet was assessed using a short validated food frequency questionnaire; derived ‘prudent’ diet scores described diet quality. Body mass index (BMI) was calculated and weight loss was self-reported. Nutrition risk scores were calculated from a checklist adapted from the DETERMINE (range 0–17).ResultsThe mean age of participants at baseline (n = 86) was 78 (SD 8) years; half (53%) scored ‘moderate’ or ‘high’ nutritional risk, using the checklist adapted from DETERMINE. In cross-sectional analyses, after adjusting for age, sex and education, higher nutrition risk scores were associated with lower grip strength [difference in grip strength: − 0.09, 95% CI (− 0.17, − 0.02) SD per unit increase in nutrition risk score, p = 0.017] and poorer diet quality [prudent diet score: − 0.12, 95% CI (− 0.21, − 0.02) SD, p = 0.013]. The association with diet quality was robust to further adjustment for number of comorbidities, whereas the association with grip strength was attenuated. Nutrition risk scores were not related to reported weight loss or BMI at baseline. In longitudinal analyses there was an association between baseline nutrition risk score and lower grip strength at follow-up [fully-adjusted model: − 0.12, 95% CI (− 0.23, − 0.02) SD, p = 0.024]. Baseline nutrition risk score was also associated with greater risk of mortality [unadjusted hazard ratio per unit increase in score: 1.29 (1.01, 1.63), p = 0.039]; however, this association was attenuated after adjustment for sex and age.ConclusionsCross-sectional associations between higher nutrition risk scores, assessed from a short checklist, and poorer diet quality suggest that this approach may hold promise as a simple way of screening older populations. Further larger prospective studies are needed to explore the predictive ability of this screening approach and its potential to detect nutritional risk in older adults.

Highlights

  • The implementation of malnutrition screening, using standardised tools, has led to better recognition of the poorer health outcomes associated with it, such as sarcopenia, frailty and mortality [1,2,3]

  • As we have previously shown that prudent diet scores are generally higher among older women, compared with older men, and diet quality is positively associated with education [22], we adjusted for sex and education in our multivariate models

  • In this study we applied a checklist adapted from the DETERMINE nutrition screening tool to identify nutritional risk, and assessed its relationships with diet quality and health outcomes in a community-dwelling group of older adults in the UK

Read more

Summary

Introduction

The implementation of malnutrition screening, using standardised tools, has led to better recognition of the poorer health outcomes associated with it, such as sarcopenia, frailty and mortality [1,2,3]. Screening approaches that enable early identification of malnutrition risk in older people could be important to prevent the development of malnutrition, and the related detrimental. To identify signs of early nutritional risk, and to allow intervention before overt malnutrition develops, a different approach to screening is required. One such tool is the ‘Determine your Nutritional Health’ (DETERMINE) tool, developed by the US Nutrition Screening Initiative to identify and treat nutritional problems in older populations [7]. Older adults with high nutritional risk, assessed using this tool, have been shown to be more likely to have low nutrient intakes and to report poorer health [7]. Studies of its prediction of mortality in older populations have yielded mixed findings [8,9,10]

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call