ABSTRACT
Nutritional risk and its predictors were assessed by evaluating longitudinal changes in body weight using data collected from elderly community-dwelling and institutionalized Canadians who participated in both phases of the Canadian Study of Health and Aging, CSHA (n=10,263). Change in body weight (% initial weight) was examined over a 5-year interval in 584 community and 237 institutionalized participants, and its predictors tested in multiple and logistic regression analyses. Average weight at CSHA-2 was 97% of initial weight at CSHA-1. Values were lower in those over 90 years and the demented. Increasing frailty on a 7-point scale (beta=-1.23, p=0.04) predicted weight loss in institutional participants, as did difficulty in eating unaided (beta=4.24, p<0.001) and reported loss of interest in life (beta=2.22, p<0.001) among community subjects. Some 16% in institutions and 9% in the community were at moderate/severe nutritional risk, disproportionately represented by the oldest subjects and the demented. These analyses support the importance of assessing dietary intakes, anthropometrics, well-being and environmental predictors of aging in the elderly.
ABREGE
Nous avons evalue le risque nutritionnel et ses predicteurs en examinant les changements longitudinaux du poids a partir de donnees recueillies aupres de Canadiens ages vivant dans la communaute ou en etablissement et ayant participe aux deux phases de I'Etude sur la sante et le vieillissement au Canada, ou ESVC (n=10 263). Les changements de poids (en pourcentage du poids initial) ont ete evalues sur un intervalle de cinq ans chez 584 participants vivant dans la communaute et 237 asilaires. Nous avons teste les predicteurs de changement par des analyses de regression multiple et logistique. Le poids moyen lots de l'ESVC-2 correspondait a 97 % du poids initial mesure lors de l'EESVC-1, avec des valeurs plus faibles chez les plus de 90 ans et les personnel atteintes de demence. Les predicteurs de perte de poids chez les participants en etablissement etaient la fi*ite accrue, mesuree sur une &chelle de sept points (b=-1,23, p=0,04), et la difficulte a s'alimenter seul (b=4,24, p<0,001); chez les sujets vivant dans la communaute, les predicteurs de perte de poids etaient l'affirmation d'avoir perdu le gout de vivre (b=2,22, p<0,001). Environ 16 % des participants asilaires et 9 % de ceux vivant dans la communaute presentaient un risque nutritionnel modere ou grave, ce risque etant plus eleve chez les plus ages et les personnes atteintes de demence. Ces analyses soulignent l'importance d'une evaluation des apports alimentaires, des mesures anthropometriques, du bien-etre et des predicteurs environnementaux du vieillissement chez les personnel agees.
Poor nutritional status in elderly individuals is considered a key determinant of morbidity and mortality.1-9 Ideally, a nutrition marker should be specific and sensitive to nutritional status changes, reproducible, easy and inexpensive to apply, and widely available." While such a global index does not exist, longitudinal anthropometric data can furnish indicators of the relationship between body composition and health.11-13
Risk of protein-energy malnutrition (PEM) increases with loss of appetite, decrease in % usual weight, and increased % weight change in the previous year.14-18 Estimates of nutritional risk in the older person vary considerably depending on the setting and the parameter assayed, ranging from 15% in the community to 30 to 60% in nursing homes or institutions.19-22
Weight changes after age 50 are generally associated with deterioration in health, increased mortality risk after age 70(23-25) and mobility problems.25 Unintentional weight loss has been linked to greater age, poorer health, and smoking, and in men, widowhood. Education and a low usual BMI appear to be protective.26 Attempts to alter weight may be related to an increase in mortality risk.27 Finally, weight loss may also be associated with the onset and/or progression of Alzheimer's disease (AD).15
Weight change, assessed as % initial weight, is a potential predictor of proteinenergy malnutrition and subsequent mortality.15-18,28-30 A 4 to 5% annual weight loss is considered clinically significant, increasing mortality especially in `involuntary weight losers'.8 In hospitalized patients, risk of undernutrition has classically been judged as low when current weight is 85-- 95% of usual weight, moderate if current weight is 75-84% of usual weight, and severe if it falls below 75%.31
Study context
The Canadian Study of Health and Aging (CSHA) was conducted in two phases, with a nation-wide prevalence study of dementia in 1991-92 (CSHA-1) in the aging Canadian population, and a longitudinal follow-up phase in 1996 (CSHA-2), designed to assess the incidence of dementia.32 People aged 65 years and over were randomly selected at CSHA-1 (from provincial health databases, except in Ontario where electoral lists were used), using recruitment procedures which differed for those living in the community (n=9,008; response rate 72% of those contacted) and in institutions (n=1,255; response rate 82%). At CSHA-2, surviving cohort subjects were re-contacted and rerecruited into the study, and questionnaires and procedures were re-administered. Community subjects were screened by interviewers for cognitive impairment using the "3 MS",33 a modified MiniMental State Examination (MMSE).34 The untestable, those testing positive, and a random sample of control subjects (having a reference person willing to complete certain study instruments) underwent a clinical examination. All institution participants who met inclusion criteria (spoke English or French, lived in study area) took part in the clinical examination. The final cognitive diagnosis was reached by consensus of the clinician, another physician, and a neuropsychologist, aided by the nurse who had administered the Clinical questionnaire, using DSM-III-R criteria.35 Participants not consistent with dementia criteria but who manifested cognitive impairment were termed "cognitively-- impaired, not demented" (CIND), by exclusion.
The present study sought to 1) assess nutritional risk, defined as % initial weight (baseline weight at CSHA-1), by evaluating longitudinal changes in body weight over the 5-year interval between the two study phases, and 2) elucidate predictors of nutritional risk, defined as extent of weight loss from CSHA-1 to CSHA-2.
METHODS AND MATERIALS
Data sources and subjects
Data were extracted from the CSHA-2 Screening and Clinical questionnaires. The subject's ability to feed him/herself, and indices relating to depression (factors with impact on dietary intake in the elderly) were taken from the CAMDEX (Cambridge Mental Disorders of the Elderly Examination) questionnaire36 administered at CSHA-2. Selected activities of daily living (ADLs), or Instrumental ADLs (IADLs) were derived from the Older Americans Resources and Services (OARS) Multidimensional Functional Assessment Questionnaire37 (ability to eat unaided, shopping, meal preparation). Data were self-reported by able participants, or by proxy when subjects were unable to respond for themselves. Weight was measured by a nurse during the clinical examination, following procedures established at training, and values were taken from CSHA-1 and CSHA-2 datasets. In CSHA-1, weight was measured in 1,529 (17%) communitybased subjects and 1,174 (93.5%) institutional subjects. In CSHA-2, 752 community subjects and 333 institutional subjects were reassessed, and weight was remeasured in 603 (80.2%) and 249 (74.8%) respectively. Participants were lost to follow-up in Phase 2 mainly due to death (39.2%-community, 68.7%-- institutions) or refusal/non-contacts (11.6%-community, 3%-institutions) (Figure 1).
Analyses
Analyses were conducted separately for institution and community subjects and subcategories of dementia were tested for internal differences. A systematic review verified participants' weight data for clinical and logical plausibility. Consequently, 31 subjects with unacceptable values (substantial and implausible divergence in weight from CSHA-1 to CSHA-2, or unlikely weight for gender or height) were excluded from analysis.
After examining longitudinal changes in weight, height, and BMI,38 weight change over the 5-year interval was re-assessed as initial weight. Predictors of weight change (or loss) were tested in multiple regression analyses in each sub-sample after assessing relationships between the dependent and independent variables in bivariate analyses. Independent variables were age, sex, 3MS score, cognitive diagnosis at CSHA-2, study region, presence of a spouse and/or recent bereavement, selfreported weight gain or loss, functional vulnerability, ability to eat unaided, appetite, depression (including self-reported interest in life), frailty (assessed via a 7-- category ascending scale derived from clinical observation, and ranging from "very fit" to "completely dependent" - see Appendix), income, and for community participants, institutionalization since CSHA-1. Region of residence (five geographic regions in Canada, potentially reflecting cultural, environmental or other regional diversity) were examined as additional possible explanatory variables.
Risk of undernutrition was categorized as none (current weight >95% of usual weight), low (current weight 85-95% of usual weight), or moderate/severe (<85% of usual weight), modified from the more severe definitions published by Blackburn et al.31 This less stringent approach allows for differences between hospitalized patients and home-dwellers, making few assumptions about baseline (CSHA-1) body weight. However, it does assume that negative weight change in the elderly is a health risk factor.23-25 To examine the relationship between weight loss and AD, it was stratified by age, sex and cognitive diagnosis.
Finally, risk of undernutrition was dichotomized into absence (% initial weight >95%) or presence of risk (% initial weight <=95%), and logistic regression analyses were carried out for each sub-sample, with % of initial weight as the dependent variable. Potential predictors of weight change leading to undernutrition included age, cognitive diagnosis at CSHA-2, study region, ability to eat independently, loss of appetite, weight loss, depression, self-reported interest in life, frailty, and for community subjects, ability to shop and bereavement. Analyses were conducted using SAS V6.12 (SAS Institute, Cary, NC) and SPSS (SPSS V8 Inc., Chicago, IL).
RESULTS
Subjects retained the recruitment status (institution or community) established at CSHA-1, whatever their situation during CSHA-2. Weight data were available for 249 institution and 603 community subjects. Review of these values resulted in retention of 237 (95.2%) in institutions, and 584 (96.8%) community subjects (Figure 1).
In both groups, CSHA-2 weight was, on average, 97.1 +/- 12.6% of initial (CSHA-1) weight. Persons aged 90+ years, and those diagnosed as demented had the lowest values in each series, especially in institutions (93.6 +/- 12.4% and 95.6 +/- 12.6%, respectively). As the median values were virtually identical to the means in both sub-samples, 50% of subjects were within 97% or more of their initial weight at CSHA-1 when reweighed at CSHA-2 (93% for those aged 90+ in institutions). However, a non-- negligable proportion of participants were at some risk of undernutrition (Table I).
Models emerging from multiple regression analyses on predictors of weight change are given in Table II. Among institution participants, increasing frailty was a predictor of greater weight loss in comparison to initial weight (beta-1.23, p=0.04). Residence in a region other than Quebec was inversely related to % initial body weight. This was statistically significant for participants in Ontario and in British Columbia (beta=-5.62, p=0.03). In community subjects, ability to eat independently (beta=4.24, p<0.001) and reported sustained interest in life (beta=2.22, p<0.01) predicted a higher % initial weight at CSHA-2.
Among institution subjects overall, 57% were assessed to be at no risk, 27% at low risk, and 16% at moderate/severe risk of undernutrition. A significantly greater proportion of those aged 90+ were in the moderate/severe risk category compared to other age groups. There was a significant, progressive inverse trend of increased nutritional risk among demented subjects, compared to CIND, compared to those diagnosed as cognitively normal (Table III). In community subjects, smaller proportions were at risk, and progressive departure from normal cognitive diagnosis to CIND to demented was related to highly significant greater proportions of subjects at moderate/severe nutritional risk. Although not significant, proportionately more women appeared to be at moderate/severe risk of undernutrition compared to men (Table IV). In institutions (where 71% of those aged 90+ were demented), a significantly higher proportion at risk were demented, compared to those diagnosed as CIND or normal. In community participants (33% were aged 90+), higher (not significant) proportions of 90+ CIND and demented were at nutritional risk (data not shown).
Finally, increasing frailty predicted a significantly greater risk of undernutrition expressed as present (<95% of initial weight) or absent (>= 95% of initial weight). In all subjects, reporting a sustained interest in life heralded a diminished risk of undernutrition, and in the community group, reporting a consistent appetite was also a positive factor in diminishing risk of undernutrition (Table V).
DISCUSSION
The present analyses examined weight change in a subset of elderly Canadians who had participated in both phases of the CSHA. An average weight loss of 3% of initial weight occurred over the 5-year interval between CSHA-1 and CSHA-2, with greater losses of baseline body weight observed in participants over 90 years of age at CSHA-2, and in the demented. These findings concur with the literature.39-43 While the mean weight loss values would appear to augur favourably for health outcome, there was a greater risk of undernutrition due to weight loss in the very elderly (90+ years) living in institutions, in the demented compared to CIND, and in CIND compared to cognitively normal participants in both recruitment groups. In the community, a diagnosis of dementia was most strongly related to risk of undernutrition due to weight loss. These findings support those of Wallace et al.,8 who observed that mortality increased in elderly weight-losing subjects (regardless of intention to lose weight), a phenomenon expected to increase with advancing age. Acute and chronic disease and psychosocial factors are believed to be the main causes of unintentional weight loss,24-27 especially among those in long-term care.28 Since "intention" could be viewed as a potential marker for weight-related illness,26 weight history is germane to understanding the origin of weight loss and its potential consequences which foster health risks in those over the age of 70 years.23,24,44,45 Still, healthy elderly do not always lose weight over time: among male participants in the New Mexico Aging Process Study weight did not change, but women lost an average of 0.14 kg annually over the 9-year study period.46
In institutionalized participants, multiple regression analyses showed that increasing frailty predicted greater weight loss, as did residence in Ontario or British Columbia compared to Quebec. We are unable to explain this latter finding, which may be an artifact of the way the dummy variable representing "region" was constructed, or may reflect cultural or environmental disparities among elderly Canadians living in a country with regional distinctions. However, as Quebecers were smaller and had lower body weights at CSHA-1 than Canadians in other regions,47 perhaps they simply had less weight to lose. In subjects living in the community during CSHA-1, ability to eat unaided and a self-reported sustained interest in life emerged as positive predictors of initial weight. In some (data not shown), reported ability to eat unaided was a negative predictor of % initial weight, suggesting more weight loss. Perhaps those who reported being able to eat unaided could do so, but they were unable to procure an adequate diet.
This study is limited in that the present analyses did not consider CSHA-1 decedents. These data thus reflect body weight in the surviving members of the cohort. Also, as very elderly subjects were oversampled in the community, the sample may not represent home-dwelling elderly. Since health status at the time of these analyses was not considered, we could not distinguish between age-related decreases in body weight (e.g., loss of lean body mass) and those caused by illness (such as cancerrelated weight loss or being confined to wheelchair or bed), or even deliberate and desirable weight loss. It must also be remembered that the models emerging from the multiple regression analyses were only weakly predictive of weight change, with variance accounted for by the models of 9.3% (institution) and 4.7% (community). However, the main predictors of risk of weight loss (and consequently, risk of undernutrition) emerging from logistic regression analyses were frailty and a reported diminished interest in life (all subjects), and loss of appetite (community participants), factors with logical coherence. It may therefore be postulated that a lack of interest in life (a marker of depression) together with a loss of appetite (associated with depression or other illness) are indicators of weight loss, concurrent undernutrition and increasing frailty, which lead to morbidity and poor quality of life. Clearly, information on food habits, dietary intakes and the dietary environment of participants could have shed more light on the anthropometric outcome measures.
In order to foster quality of life and maintenance of health and help them remain in their homes and avoid institutionalization, community-dwelling elderly should be screened regularly for indicators of nutritional status, including dietary adequacy, meal preparation ability, other functional capacities and food security.11 Hospitalized patients and residents in long-term care must also be assessed regularly with the goal of maintaining body weight.28 Finally, epidemiologic studies in elderly populations should collect longitudinal data on diet and anthropometric measurements.39
These analyses of weight change and nutritional risk over time in this cohort evoke predictors of nutritional status in aging Canadians that could be amenable to intervention, and point to the importance of including information on dietary and nutritional intakes, anthropometric indices, well-being and environmental predictors of aging in the elderly.
ACKNOWLEDGEMENTS
The data in this article were collected as part of the Canadian Study of Health and Aging. The core study was funded by the Seniors' Independence Research Program through the National Health Research and Development Program (NHRDP) of Health Canada (project no. 6606-3954-- MC(S)). Additional funding was provided by Pfizer Canada Incorporated through the Medical Research Council/Pharmaceutical Manufacturers Association of Canada Health Activity Program, NHRDP (project no. 6603-1417-302(R)), Bayer Incorporated, and the British Columbia Health Research Foundation (projects no. 38(93-2) and no. 34(96-1)). The study was coordinated through the University of Ottawa and the Division of Aging and Seniors, Health Canada.
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Received: January 11, 2000
Accepted: July 24, 2000
[Author Affiliation]
Bryna Shatenstein, PhD, PDt,1,3
Marie-Jeanne Kergoat, MD, CCFP, FCFP, CSPQ,1,2 Sylvie Nadon, MSc, DtP1
[Author Affiliation]
1. Centre de recherche, Institut universitaire de geriatrie de Montreal
2. Geriatrician, Chief, Dept. of Specialised Medicine, Institut universitaire de geriatrie de Montreal
3. Departement de nutrition, University de Montreal
Correspondence: Dr. Bryna Shatenstein, Centre de recherche, Institut universitaire de geriatric de Montreal, 4565 Queen Mary, Montreal, QC, H3W 1W5, Tel: 514-340-3540, ext. 3247, Fax: 514-340-- 2801, E-mail: bryna.shatenstein@umontreal.ca
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