Elsevier

Clinical Nutrition

Volume 32, Issue 6, December 2013, Pages 1007-1011
Clinical Nutrition

Original article
Prevalence and determinants for malnutrition in geriatric outpatients

https://doi.org/10.1016/j.clnu.2013.05.007Get rights and content

Summary

Background & aims

Few data is available on the nutritional status of geriatric outpatients. The aim of this study is to describe the nutritional status and its clinical correlates of independently living geriatric older individuals visiting a geriatric outpatient department.

Methods

From 2005 to 2010, all consecutive patients visiting a geriatric outpatient department in the Netherlands were screened for malnutrition. Nutritional status was assessed by the Mini Nutritional Assessment (MNA). Determinants of malnutrition were categorized into somatic factors (medicine use, comorbidity, walking aid, falls, urinary incontinence), psychological factors (GDS-15 depression scale, MMSE cognition scale), functional status (Activities of Daily Life (ADL), Instrumental ADL (IADL)), social factors (children, marital status), and life style factors (smoking, alcohol use). Univariate and multivariate logistic regression analyses, adjusted for age and sex and all other risk factors were performed to identify correlates of malnutrition (MNA < 17).

Results

Included were 448 outpatients, mean (SD) age was 80 (7) years and 38% was men. Prevalence of malnutrition and risk for malnutrition were 17% and 58%. Depression, being IADL dependent, and smoking were independently associated with an increased risk of malnutrition with OR's (95%CI) of 2.6 (1.3–5.3), 2.8 (1.3–6.4), 5.5 (1.9–16.4) respectively. Alcohol use was associated with a decreased risk (OR 0.4 (0.2–0.9)).

Conclusion

Malnutrition is highly prevalent among geriatric outpatients and is independently associated with depressive symptoms, poor functional status, and life style factors. Our results emphasize the importance of integrating nutritional assessment within a comprehensive geriatric assessment. Future longitudinal studies should be performed to examine the effects of causal relationships and multifactorial interventions.

Introduction

Aging may come with an accumulation of diseases and impairments, including cognitive and physical decline, depressive symptoms and emotional changes, all of which may directly influence the balance between nutritional needs and intake.1 Dietary behavior of older individuals may change because of health or social reasons, decrease in taste and smell, or a reduced ability to purchase and prepare food. This combination of symptoms or conditions put older individuals at a higher risk of malnutrition.1, 2 Malnutrition is a prognostic factor associated with morbidity, mortality and costs of care.3, 4 It is therefore important to detect those older individuals who are at risk for malnutrition.

The reported prevalence rates of malnutrition in the Netherlands are relatively low in community dwelling older persons (2%–12%), but rise considerably in older individuals receiving home care (18%–35%) or in the hospitalized or institutionalized older patients (30%–60%).5, 6, 7, 8, 9

Data on the prevalence of malnutrition and clinical correlates of nutritional status of geriatric patients who visit geriatric outpatient departments is not available. These patients are referred to an outpatient clinic with multiple problems in somatic functioning, psychological functioning, and/or with functional or social problems.10 Multimorbidity is thought to have a direct influence on the balance between nutritional needs and nutritional intake and to contribute to a high prevalence of malnutrition.11

In this study we aimed to investigate the malnutrition prevalence rates among older patients visiting a geriatric outpatient department of a large teaching hospital in the Netherlands. Furthermore, we investigated which somatic, psychological, functional, social or life style characteristics were associated with malnutrition.

Section snippets

Study design and population

For this cross-sectional study, aiming to investigate the clinical correlates of nutritional status of geriatric patients, we included 448 consecutive patients at their first visit to a geriatric outpatient clinic of a large teaching hospital in the Netherlands between October 2005 and March 2010. All patients were living independently (in their own home or in an assisted care facility). Patients living in a nursing home were excluded. Patients were referred for multiple problems in the

Results

Mean (SD) age of the total population (n = 448) was 80 (7) years and 38% was male. In this population of geriatric outpatients, 17% was malnourished (MNA < 17.0), and 58% were at risk for malnutrition (MNA 17.0–23.5).

Table 1 presents the patient characteristics across categories of MNA. Patients with malnutrition had a lower weight, BMI and smaller waist circumference, and less frequently drank alcohol than patients with better nutritional status. Also, patients with malnutrition used more

Discussion

The present study among 448 independently living geriatric outpatients indicates a high prevalence of malnutrition and risk of malnutrition (17% and 58%). Multimorbidity, poor functional status, depressive symptoms and smoking were independently associated with an increased risk of malnutrition. Also, the more somatic, psychological, social, or functional problems a patient experienced, the higher the risk of being malnourished. Alcohol use was associated with a decreased risk of malnutrition.

Statement of authorship

MAEvB, SLM and MM designed the study. SLM collected the data. MAEvB and MM performed the data analyses. MAEvB drafted the manuscript. All authors contributed to the writing of the manuscript. All authors approved the final version of the manuscript.

Funding sources

No external funding was obtained to perform this study.

Conflict of interest statements

None of the authors declared a conflict of interest.

Acknowledgments

The authors wish to thank Yoni van Duivenvoorde, Miranda van Lunteren, Liesbeth van Oostenbrugge and Ruben Verhagen for their contribution to data cleaning, building the data base and performing preliminary data analyses.

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