The influence of smoking status on malnutrition risk and 1-year mortality in outpatients with chronic obstructive pulmonary disease.

Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).

The influence of deprivation domains on malnutrition risk in outpatients with chronic obstructive pulmonary disease

Deprivation assessed using the Index of Multiple Deprivation (IMD) has been shown to be an independent risk factor for both malnutrition and mortality in outpatients with chronic obstructive pulmonary disease (COPD) (Collins et al., 2010a, b). IMD consists of a range of different deprivation domains, although it is unclear which ones are most closely linked to malnutrition. The aim of the current study was to investigate whether the relationship between malnutrition and deprivation was a general one, affecting all domains in a consistent manner, or specific, affecting only certain domains.

Malnutrition screening tools : comparison against two validated nutrition assessment methods in older medical inpatients

Objective Although several validated nutritional screening tools have been developed to “triage” inpatients for malnutrition diagnosis and intervention, there continues to be debate in the literature as to which tool/tools clinicians should use in practice. This study compared the accuracy of seven validated screening tools in older medical inpatients against two validated nutritional assessment methods. Methods This was a prospective cohort study of medical inpatients at least 65 y old. Malnutrition screening was conducted using seven tools recommended in evidence-based guidelines. Nutritional status was assessed by an accredited practicing dietitian using the Subjective Global Assessment (SGA) and the Mini-Nutritional Assessment (MNA). Energy intake was observed on a single day during first week of hospitalization. Results In this sample of 134 participants (80 ± 8 y old, 50% women), there was fair agreement between the SGA and MNA (κ = 0.53), with MNA identifying more “at-risk” patients and the SGA better identifying existing malnutrition. Most tools were accurate in identifying patients with malnutrition as determined by the SGA, in particular the Malnutrition Screening Tool and the Nutritional Risk Screening 2002. The MNA Short Form was most accurate at identifying nutritional risk according to the MNA. No tool accurately predicted patients with inadequate energy intake in the hospital. Conclusion Because all tools generally performed well, clinicians should consider choosing a screening tool that best aligns with their chosen nutritional assessment and is easiest to implement in practice. This study confirmed the importance of rescreening and monitoring food intake to allow the early identification and prevention of nutritional decline in patients with a poor intake during hospitalization.

Malnutrition and falls risk in community-dwelling older adults

Background and Aims: Falls and fall-related injuries result in reduced functioning, loss of independence, premature nursing home admissions and mortality. Malnutrition is associated with falls in the acute setting, but little is known about malnutrition and falls risk in the community. The aim of this study was to assess the association between malnutrition risk, falls risk and falls over a one-year period in community-dwelling older adults. Methods: Two hundred and fifty four subjects >65 years of age were recruited to participate in a study in order to identify risk factors for falls. Malnutrition risk was determined using the Mini Nutritional Assessment–Short Form. Results: 28.6% had experienced a fall and according to the Mini Nutritional Assessment-Short Form 3.9% (n=10) of subjects were at risk of malnutrition. There were no associations between malnutrition risk, the risk of falls, nor actual falls in healthy older adults in the community setting. Conclusions: There was a low prevalence of malnutrition risk in this sample of community-dwelling older adults and no association between nutritional risk and falls. Screening as part of a falls prevention program should focus on the risk of developing malnutrition as this is associated with falls.

Prevalence of malnutrition in community-dwelling adults with Parkinson's disease

People with Parkinson’s disease (PD) have been reported to be at higher risk of malnutrition than an age-matched population due to PD motor and non-motor symptoms and pharmacotherapy side effects. The prevalence of malnutrition in PD has yet to be well-defined. Community-dwelling people with PD, aged > 18 years, were recruited (n = 97, 61 M, 36 F). The Patient-Generated Subjective Global Assessment (PGSGA) was used to assess nutritional status, the Parkinson’s Disease Questionnaire (PDQ-39) was used to assess quality of life, and the Beck’s Depression Inventory (BDI) was used to measure depression. Levodopa equivalent doses (LEDs) were calculated based on reported Parkinson’s disease medication. Weight, height, mid-arm circumference (MAC) and calf circumference were measured. Cognitive function was measured using the Addenbrooke’s Cognitive Examination. Average age was 70.0 (9.1, 35–92) years. Based on SGA, 16 (16.5%) were moderately malnourished (SGA B) while none were severely malnourished (SGA C). The well-nourished participants (SGA A) had a better quality of life, t(90) = −2.28, p < 0.05, and reported less depressive symptoms, t(94)= −2.68, p < 0.05 than malnourished participants. Age, years since diagnosis, cognitive function and LEDs did not signifi cantly differ between the groups. The well-nourished participants had lower PG-SGA scores, t(95) = −5.66, p = 0.00, higher BMIs, t(95) = 3.44, p < 0.05, larger MACs, t(95) = 3.54, p < 0.05 and larger calf circumferences, t(95) = 2.29, p < 0.05 than malnourished participants. Prevalence of malnutrition in community-dwelling adults with PD in this study is comparable to that in other studies with community-dwelling adults without PD and is higher than other PD studies where a nutritional status assessment tool was used. Further research is required to understand the primary risk factors for malnutrition in this group.

Risk factors for malnutrition in community-dwelling people with Parkinson’s disease

In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.

Malnutrition in a sample of community-dwelling people with Parkinson’s disease

Objective: Malnutrition results in poor health outcomes, and people with Parkinson’s disease may be more at risk of malnutrition. However, the prevalence of malnutrition in Parkinson’s disease is not yet well defined. The aim of this study is to provide an estimate of the extent of malnutrition in community-dwelling people with Parkinson’s disease. Methods: This is a cross-sectional study of people with Parkinson’s disease residing within a 2 hour driving radius of Brisbane, Australia. The Subjective Global Assessment (SGA) and scored Patient Generated Subjective Global Assessment (PG-SGA) were used to assess nutritional status. Body weight, standing or knee height, mid-arm circumference and waist circumference were measured. Results: Nineteen (15%) of the participants were moderately malnourished (SGA-B). The median PG-SGA score of the SGA-B group was 8 (4 – 15), significantly higher than the SGA-A group, U=1860.5,p<.05. The symptoms most influencing intake were loss of appetite, constipation, early satiety and problems swallowing. Conclusions: As with other populations, malnutrition remains under-recognised and undiagnosed in people with Parkinson’s disease. Regular screening of nutritional status in people with Parkinson’s disease by health professionals with whom they have regular contact should occur to identify those who may benefit from further nutrition assessment and intervention.

Comparison of two methods to assess malnutrition in community-dwelling people with Parkinson's disease

Nutritional status in people with Parkinson’s disease (PD) has previously been assessed in a number of ways including BMI, % weight loss and the Mini-Nutritional Assessment(MNA). The symptoms of the disease and the side effects of medication used to manage them result in a number of nutrition impact symptoms that can negatively influence intake. These include chewing and swallowing difficulties, lack of appetite, nausea, and taste and smell changes, among others. Community-dwelling people with PD, aged >18 years, were recruited (n=97, 61 M, 36 F). The Patient-Generated Subjective Global Assessment(PG-SGA) and (MNA) were used to assess nutritional status. Weight, height, mid-arm circumference(MAC) and calf circumference were measured. Based on SGA, 16(16.5%) were moderately malnourished (SGA B) while none were severely malnourished (SGA C). The MNA identified 2(2.0%) as malnourished and 22(22.7%) as at risk of malnutrition. Mean MNA scores were different between the three groups,F(2,37)=7.30,p<.05 but not different between SGA B (21.0(2.9)) and MNA at risk (21.8(1.4)) participants. MAC and calf circumference were also different between the three groups,F(2,37)=5.51,p<.05 and F(2,37)=15.33,p<.05 but not between the SGA B (26.2(4.2), 33.3(2.8)) and MNA at risk (28.4(5.6), 36.4(4.7)) participants. The MNA results are similar to other PD studies using MNA where prevalence of malnutrition was between 0-2% with 20-33% at risk of malnutrition. In this population, the PG-SGA may be more sensitive to assessing malnutrition where nutrition impact symptoms influence intake. With society’s increasing body size, it might also be more appropriate as it does not rely on MAC and calf circumference measures.

Malnutrition and poor food intake are associated with prolonged hospital stay, frequent readmissions, and greater in-hospital mortality: Results from the Nutrition Care Day Survey 2010

Background & aims The Australasian Nutrition Care Day Survey (ANCDS) ascertained if malnutrition and poor food intake are independent risk factors for health-related outcomes in Australian and New Zealand hospital patients. Methods Phase 1 recorded nutritional status (Subjective Global Assessment) and 24-h food intake (0, 25, 50, 75, 100% intake). Outcomes data (Phase 2) were collected 90-days post-Phase 1 and included length of hospital stay (LOS), readmissions and in-hospital mortality. Results Of 3122 participants (47% females, 65 ± 18 years) from 56 hospitals, 32% were malnourished and 23% consumed ≤ 25% of the offered food. Malnourished patients had greater median LOS (15 days vs. 10 days, p < 0.0001) and readmissions rates (36% vs. 30%, p = 0.001). Median LOS for patients consuming ≤ 25% of the food was higher than those consuming ≤ 50% (13 vs. 11 days, p < 0.0001). The odds of 90-day in-hospital mortality were twice greater for malnourished patients (CI: 1.09–3.34, p = 0.023) and those consuming ≤ 25% of the offered food (CI: 1.13–3.51, p = 0.017), respectively. Conclusion The ANCDS establishes that malnutrition and poor food intake are independently associated with in-hospital mortality in the Australian and New Zealand acute care setting.

How do Australasian hospitals identify and manage malnutrition in their acute care wards?

One aim of the Australasian Nutrition Care Day Survey was to explore nutrition care practices in acute care hospital wards across Australia and New Zealand. Managers of Dietetic departments completed a questionnaire regarding ward nutrition care practices. Overall, 370 wards from 56 hospitals participated. The median ward size was 28 beds (range: 8–60 beds). Although there was a wide variation in full-time equivalent availability of dietitians (median: 0.3; range: 0–1.4), their involvement in providing nutrition care across ward specialities was signifi cantly higher than other staff members (χ2, p < 0.01). Feeding assistance, available in 89% of the wards, was provided mainly by nursing staff and family members (χ2, p < 0.01). Protected meal times were implemented in 5% (n = 18) of the wards. Fifty-three percent of the wards (n = 192) weighed patients on request and 40% (n = 148) on admission. Routine malnutrition screening was conducted in 63% (n = 232) of the wards and 79% (n = 184) of these wards used the Malnutrition Screening Tool, 16% (n = 37) the Malnutrition Universal Screening Tool, and 5% (n = 11) other tools. Nutrition rescreening was routinely conducted in 20% of the wards. Among wards that implemented nutrition screening, 41% (n = 100) routinely referred patients “at risk” of malnutrition to dietitians as part of their standard protocol for malnutrition management. Results of this study provide new knowledge regarding current nutrition care practice, highlight gaps in existing practice, and can be used to inform improved nutrition care in acute care wards across Australia and New Zealand.

The impact of malnutrition and decreased food intake on length of stay, readmission, and mortality in acute care patients

Rationale: The Australasian Nutrition Care Day Survey (ANCDS) evaluated if malnutrition and decreased food intake are independent risk factors for negative outcomes in hospitalised patients. Methods: A multicentre (56 hospitals) cross-sectional survey was conducted in two phases. Phase 1 evaluated nutritional status (defined by Subjective Global Assessment) and 24-hour food intake recorded as 0, 25, 50, 75, and 100% intake. Phase 2 data, which included length of stay (LOS), readmissions and mortality, were collected 90 days post-Phase 1. Logistic regression was used to control for confounders: age, gender, disease type and severity (using Patient Clinical Complexity Level scores). Results: Of 3122 participants (53% males, mean age: 65±18 years) 32% were malnourished and 23% consumed�25% of the offered food. Median LOS for malnourished (MN) patients was higher than well-nourished (WN) patients (15 vs. 10 days, p<0.0001). Median LOS for patients consuming �25% of the food was higher than those consuming �50% (13 vs. 11 days, p<0.0001). MN patients had higher readmission rates (36% vs. 30%, p = 0.001). The odds ratios of 90-day in-hospital mortality were 1.8 times greater for MN patients (CI: 1.03 3.22, p = 0.04) and 2.7 times greater for those consuming �25% of the offered food (CI: 1.54 4.68, p = 0.001). Conclusion: The ANCDS demonstrates that malnutrition and/or decreased food intake are associated with longer LOS and readmissions. The survey also establishes that malnutrition and decreased food intake are independent risk factors for in-hospital mortality in acute care patients; and highlights the need for appropriate nutritional screening and support during hospitalisation. Disclosure of Interest: None Declared.