Is the Utility of the GLIM Criteria Used to Diagnose Malnutrition Suitable for Bicultural Populations? Findings from Life and Living in Advanced Age Cohort Study in New Zealand (LiLACS NZ).

OBJECTIVES: To investigate associations between nutrition risk (determined by SCREEN-II) and malnutrition (diagnosed by the GLIM criteria) with five-year mortality in Maori and non-Maori of advanced age. DESIGN: A longitudinal cohort study. SETTING: Bay of Plenty and Lakes regions of New Zealand. PARTICIPANTS: 255 Maori; 400 non-Maori octogenarians. MEASUREMENTS: All participants were screened for nutrition risk using the Seniors in the Community: Risk Evaluation for Eating and Nutrition (SCREEN-II). Those at high nutrition risk (SCREEN-II score <49) had the Global Leadership Initiative in Malnutrition (GLIM) criteria applied to diagnose malnutrition or not. Demographic, physical and health characteristics were obtained by trained research nurses using a standardised questionnaire. Five-year mortality was calculated from Government data. The association of nutrition risk (SCREEN-II) and a malnutrition diagnosis (GLIM) with five-year mortality was examined using logistic regression and cox proportional hazard models of increasing complexity. RESULTS: 56% of Maori and 46% of non-Maori participants had low SCREEN-II scores indicative of nutrition risk. The prevalence of GLIM diagnosed malnutrition was lower for both Maori and non-Maori (15% and 19% of all participants). Approximately one-third of participants (37% Maori and 32% non-Maori) died within the five-year follow-up period. The odds of death for both Maori and non-Maori was significantly lower with greater SCREEN II scores (better nutrition status), (OR (95% CI); 0.58 (0.38, 0.88), P < 0.05 and 0.53 (0.38, 0.75), P < 0.001, respectively). GLIM diagnosed malnutrition was not significantly associated with five-year mortality for Maori (OR (95% CI); 0.88 (0.41, 1.91), P >0.05) but was for non-Maori. This association remained significant after adjustment for other predictors of death (OR (95% CI); 0.50 (0.29, 0.86), P< 0.05). Reduced food intake was the only GLIM criterion predictive of five-year mortality for Maori (HR (95% CI); 10.77 (4.76, 24.38), P <0.001). For non-Maori, both aetiologic and phenotypic GLIM criteria were associated with five-year mortality. CONCLUSION: Nutrition risk, but not malnutrition diagnosed by the GLIM criteria was significantly associated with mortality for Maori. Conversely, both nutrition risk and malnutrition were significantly associated with mortality for non-Maori. Appropriate phenotypic criteria for diverse populations are needed within the GLIM framework.

Assessment of Dietary Intake in Three Cohorts of Advanced Age in Two Countries: Methodology Challenges.

OBJECTIVES: Dietary intake information is key to understanding nutrition-related outcomes. Intake changes with age and some older people are at increased risk of malnutrition. Application, difficulties, and advantages of the 24-hour multiple pass recall (24hr-MPR) dietary assessment method in three cohorts of advanced age in the United Kingdom (UK) and New Zealand (NZ) is described. PARTICIPANTS: The Newcastle 85+ study (UK) recruited a single year birth cohort of people aged 85 years during 2006-7. LiLACS NZ recruited a 10-year birth cohort of Maori (indigenous New Zealanders) aged 80-90 years and a single year birth cohort of non-Maori aged 85 years in 2010. MEASUREMENTS: Two 24hr-MPR were conducted on non-consecutive days by trained assessors. Pictorial resources and language were adapted for the New Zealand and Maori contexts. Detailed methods are described. RESULTS: In the Newcastle 85+ study, 805 (93%) participants consented to the 24-MPR, 95% of whom completed two 24hr-MPR; in LiLACS NZ, 218 (82%) consented and 203 (76%) Maori and 353 (90%) non-Maori completed two 24hr-MPR. Mean time to complete each 24hr-MPR was 22 minutes in the Newcastle 85+ study, and 45 minutes for Maori and 39 minutes for non-Maori in LiLACS NZ. Dietary assessment of participants residing in residential care and those requiring proxy respondents were successfully included in both studies. Most participants (83-94%) felt that data captured by the 24hr-MPR reflected their usual dietary intake. CONCLUSIONS: Dietary assessment using 24hr-MPR was successful in capturing detailed dietary data including information on portion size and time of eating for over 1300 octogenarians in the UK and New Zealand (Maori and non- Maori). The 24hr-MPR is an acceptable method of dietary assessment in this age group.

Obesity measures in the Kiribati population: a need to reclassify body mass index cut-points.

BACKGROUND: Obesity is a public health problem in Micronesia. The objective of the study was to assess obesity, the relationship between body mass index (BMI) and body fat percentage (BF%) among adults, and determine the appropriate BMI cut-points in Kiribati. METHODS: A cross-sectional study was undertaken among 483 adults randomly selected from South Tarawa (ST) and Butaritari (BT). Weight, height, BF% and physical activity level (PAL) was measured using standard methods. Linear and quadratic regression analyses were conducted to assess the association between BF% and BMI whilst controlling for age and gender. Receiver operating characteristics (ROC) curve analyses were used to assess whether for the Kiribati population alternative BMI cut-off points for obesity are needed. RESULTS: Approximately 75% of participants were obese using standard BMI and BF% cut-offs, with the highest prevalence observed in South Tarawa. BF% was significantly (p < 0.001) and positively associated with age (males, r = 0.78; females, r = 0.67; p < 0.001) and BMI. Based on ROC-curve analyses the BMI cut-offs for predicting high BF% among I-Kiribati people were 24.5 kg/m2 for males and 32.9 kg/m2 for females. CONCLUSIONS: In conclusion, the majority of adults in Kiribati were either obese or overweight and had high BF%. We suggest that ethnic-specific BMI cut-points to define obesity for the population of Kiribati may be more appropriate than the currently used international cut-points.

Health and Social Factors Associated with Nutrition Risk: Results from Life and Living in Advanced Age: A Cohort Study in New Zealand (LiLACS NZ).

OBJECTIVES: To establish the prevalence of high nutrition risk and associated health and social risk factors for New Zealand Maori and non-Maori in advanced age. DESIGN: A cross sectional analysis of inception cohorts to LiLACS NZ. SETTING: Bay of Plenty and Lakes region of the North Island, New Zealand. PARTICIPANTS: 255 Maori and 400 non- Maori octogenarians. MEASUREMENTS: Nutrition risk was assessed using a validated questionnaire Seniors in the Community: Risk Evaluation for Eating and Nutrition (SCREEN II). Demographic, social, physical and health characteristics were established using an interviewer administered questionnaire. Health related quality of life (HRQOL) was assessed with the SF-12, depressive symptoms using the GDS-15. RESULTS: Half (49%) of Maori and 38% of non-Maori participants were at high nutrition risk (SCREEN II score <49). Independent risk factors were for Maori younger age (p=0.04), lower education (p=0.03), living alone (p<0.001), depressive symptoms (p=0.01). For non- Maori high nutrition risk was associated with female gender (p=0.005), living alone (p=0.002), a lower physical health related quality of life (p=0.02) and depressive symptoms (p=0.002). CONCLUSION: Traditional risk factors apply to both Maori and non-Maori whilst education as indicative of low socioeconomic status is an additional risk factor for Maori. High nutrition risk impacts health related quality of life for non-Maori. Interventions which socially facilitate eating are especially important for women and for Maori to maintain cultural practices and could be initiated by routine screening.

The BRIGHT Trial: what are the factors associated with nutrition risk?

OBJECTIVES: To determine the nutrition risk status and factors associated with nutrition risk among older adults enrolled in the Brief Risk Identification Geriatric Health Tool (BRIGHT Trial). DESIGN: A cluster randomised controlled trial. SETTING: Three main centres in New Zealand. PARTICIPANTS: A total of 3,893 older adults were recruited from 60 general practices in three of the District Health Board (DHB) regions aged 75 years and older (or 65 years and older if Maori). MEASUREMENTS: Nutrition risk was assessed using the Australian Nutrition Screening Initiative (ANSI). Validated questionnaires were used to establish quality of life (WHOQOL-BREF), physical function (the Nottingham Extended Activities of Daily Living) and depressive symptoms (15 item Geriatric Depression Scale). Demographic, standard of living and health data were established. RESULTS: Sixty two percent of participants were identified to be at moderate or high nutrition risk. The mean ANSI score was 4.9 (range 0-21, maximum 29). Factors which independently predicted moderate or high nutrition risk were female gender, being Maori and other ethnicities versus European, not being married, taking multiple medications, having more depressive symptoms, cardiovascular disease and diabetes. Protective factors independently related to low nutrition risk were living with others, higher physical and social health related QOL and higher functional status. WHOQOL environmental and psychological factors were not associated with nutrition risk when other predictive factors were taken into account. CONCLUSION: Nearly two thirds of participants were identified to be at higher nutrition risk. Women, living alone, taking multiple medications, with depressive symptoms, cardiovascular disease and ndiabetes were factors associated with higher nutrition risk. Those at low nutrition risk had a better functional status and physical and social health related QOL.

Validation of the nutrition screening tool 'Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II' among octogenarians.

OBJECTIVE: To determine the validity of the nutrition screening tool 'Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II' (SCREEN II) among a purposive sample of octogenarians. DESIGN: Cross-sectional validation study. SETTING: Bay of Plenty, New Zealand. PARTICIPANTS: Forty-five community-living residents aged 85-86 years. Equal proportions of participants were recruited at low, medium and high nutrition risk based on their SCREEN II score 12 months prior. MEASUREMENTS: Nutrition risk was assessed using SCREEN II. Demographic and health data were established. Using established criterion a dietitian's nutrition risk rating assessment ranked participants from low risk (score of 1) to high risk (score of 10). The assessment included a medical history, anthropometric measures and dietary intake. Dietary intake was established from three 24 hour multiple pass recalls (MPR). A Spearman's correlation determined the association between the SCREEN II score and the dietitian's risk score. Receiver operating characteristic (ROC) curves were completed to determine the sensitivity and specificity of the cut-off point for high nutrition risk. RESULTS: The SCREEN II score was significantly correlated with the dietitian's risk rating (rs = -0.76 (p<0.01). A newly defined cut-off point <49 was established for high nutrition risk derived from ROC curves and AUC (0.87, p < 0.01); sensitivity 90% and specificity 86%. CONCLUSION: SCREEN II is a simple, easy to use, 14 item questionnaire and appears to be a valid tool for detection of nutrition risk people aged 85-86 years.

What is associated with nutrition risk in very old age?

OBJECTIVES: To identify factors associated with nutrition risk among a purposive sample of those in advanced aged. DESIGN: A cross sectional feasibility study. SETTING: Three North Island locations in New Zealand. PARTICIPANTS: One hundred and eight community-living residents aged 75- 85 years. MEASUREMENTS: Nutrition risk was assessed using a validated questionnaire, Seniors in the Community: Risk Evaluation for Eating and Nutrition, Version II (SCREEN II). A Physical Activity Scale for the Elderly (PASE) was used to determine level of physical activity. Markers of body composition, grip strength and fasting blood samples were collected. RESULTS: Fifty-two percent of participants were at high nutrition risk (SCREEN II score < 50; range 29-58; out of maximum score 64). The mean score for SCREEN II was higher for older people who lived with others (50.3 ± 5.1) compared to those who lived alone (46.4 ± 5.8) p=0.001. The SCREEN II score was positively correlated with the total PASE score r= 0.20 (p=0.042), grip strength r=0.20 (p=0.041), and muscle mass percentage r=0.31 (p=0.004). Lower levels of haemoglobin, serum zinc and physical activity were associated with higher nutrition risk. CONCLUSION: Half the participants were at high nutrition risk. They tended to be widowed or live alone and had lower levels of haemoglobin and serum zinc. Those at lower nutrition risk had greater muscle mass and strength, lower body fat, consumed alcohol more frequently and engaged in more physical activity. Strategies which encourage older people to eat meals and be physically active with others may assist to improve their health.

Country of origin predicts nutrition risk among community living older people.

OBJECTIVES: To assess the nutrition risk status of community living older people and to identify associated risk factors. DESIGN: A cross-sectional study using convenience sampling. SETTING: North Shore City, Auckland, New Zealand. Data collection was carried out by a research nutritionist using computer assisted personal interviewing in the participant's own home. PARTICIPANTS: Fifty-one independently living people aged between 80 and 85 years. MEASUREMENT: A survey using three validated questionnaires: Practitioner Assessment of Network Type (PANT) to evaluate social networks; Elderly Assessment System (EASY-Care) to evaluate physical and mental wellbeing and Seniors in the Community: Risk Evaluation for Eating and Nutrition Version II (SCREEN II) to assess nutrition risk. RESULTS: A third of the participants (31%) were at high risk of malnutrition (SCREEN II score <50; range 29-58 out of maximum score of 64). The majority of participants (82%) lived alone and nearly half (47%) had supportive social networks including close relationships with local family, friends and neighbours. Low self-rated health, disability and social factors (being born outside of New Zealand, losing a spouse and loneliness) were key underlying factors associated with being at nutrition risk. CONCLUSION: Nutrition risk is common among aged individuals living in the community. Health and social factors that shape eating behaviours place older people at increased nutrition risk. Strategies are needed for the early identification of risk factors to prevent nutrition problems. Engaging older people at risk to share meal preparation and dining experiences may foster better outcomes.

How is the risk of undernutrition associated with cardiovascular disease among individuals of advanced age?

BACKGROUND: The oldest old (85+) are the fastest growing population segment in New Zealand. Cardiovascular disease (CVD) is the main cause of death and is associated with various risk factors including risk of undernutrition. OBJECTIVES: To determine if there is an association between CVD and nutrition risk in advanced age. SETTING: Three North Island locations (rural and urban areas) in New Zealand. PARTICIPANTS: 108 participants aged 85 years (75-79 for Maori). MEASUREMENTS: Comprehensive health assessments were undertaken. Clinically manifest CVD was pre-defined and ascertained from interviews and hospitalisation records. Nutrition risk was assessed using a validated questionnaire-Seniors in the Community: Risk evaluation for eating and nutrition, Version II (SCREEN II). RESULTS: 72 participants (67%) had CVD (49% men); 52% of participants had a SCREEN II score < 50. Those with CVD had lower HDL level [median(IQR)] [1.4(0.7) vs. 1.6(0.6)] (p=0.041), and higher waist circumference [97.5(19.1) vs. 89.3(20.6)] (p=0.043) compared to those without CVD. Those with CVD were at no greater nutrition risk than those without CVD (SCREEN II score: [49(7) vs. 51(10)] (p=0.365). Using logistic regression controlling for confounders, SCREEN II scores trended towards an inverse association with CVD (p=0.10). CONCLUSION: Two thirds of the study participants had CVD and half were at risk of undernutrition. Nutrition risk was mildly associated with CVD. This study provides further evidence that those in advanced age are at risk of undernutrition. Further research is needed to establish how the causes and consequences of CVD are related to nutrition risk.

Dietary iron intake and iron status of young children.

Aim. To determine the prevalence of iron deficiency in healthy young children and whether there is an association between food habits and dietary iron intake and iron status. Methods. 53 children aged 9-24 months were recruited into the study over a 12 month period from a general practice and Plunket child health clinics. Children with intercurrent infections were excluded. Iron status was determined from a full blood count and iron studies. Nutrient intake was assessed by a 24 hour food recall and dietary history questionnaire with nutrient analysis using the New Zealand Food Composition database from the New Zealand Institute of Crop and Food Research Ltd. Results. 10 children (20%) were anaemic (haemoglobin <110g/L) and 7 children were iron deficient (serum ferritin <10µg/L). The daily mean iron intake was 5.1± 3.1mg, which was 0.66 RDI for 9-12 months, and 0.80 for 12-24 months. There was no statistically significant relationship between iron status and food iron intake. Children in the top quintile for iron intake (mean 17.5 mg/day) consumed iron mainly from iron-fortified formula and baby food whereas the main source of iron in the lowest quintile (mean intake 2.0mg/day) was from a diverse range of foods including vegetables, bread and bakery goods, dairy products, breakfast cereals and fruit. In this group only one child consumed formula and three children consumed baby foods. Conclusion. A high prevalence of anaemia and of iron deficiency was found amongst the otherwise healthy children in the sample, without their being a relationship between dietary iron intake and either haemoglobin or serum iron indices, except for ferritin.