Abstract
Purpose
Few studies have quantitatively investigated potential relationships between quality of life (QOL) in long term care (LTC) and foodservices.
Objective
To investigate if dining experiences, and food and nutritional services affect elderly nursing home residents' QOL.
Design and participants
A total of 395 residents in 38 nursing homes participated in this cross-sectional study.
Measurements
Information on dining experiences and QOL was gathered by face-to-face interviews with cognitively intact residents; primary institutional caregivers completed a questionnaire for cognitively impaired residents. Additional data were also obtained from participants' medical charts and from administrators and foodservice managers. Multivariate ordinary least squares (OLS) regression was used to determine which institutional characteristics were related to QOL.
Results
Number of dining companions, autonomy in relation to food, tray meal delivery service, and ratio of residents per resident assistant were significantly related to QOL in both cognitively intact and cognitively impaired residents. For cognitively intact residents, number of medical conditions, therapeutic menus, and use of china dishes were also related to QOL. For cognitively impaired residents, independence with eating and frequency of menu revision were also related to QOL.
Conclusion
Modifying certain aspects of food and nutritional services, as well as residents' dining experience, may improve QOL of elderly LTC residents.
Key words: Long-term care, mealtime, dishes, seating, autonomy, cognitive impairment
Introduction
Although today’s nursing home residents are more functionally and cognitively impaired than they were 20 years ago (1, 2, 3, 4, 5), nursing homes still aim to preserve and promote good quality of life for their residents, however challenging this may be. While both physical and social environmental factors, such as level of recreational activities and control over physical environment, have frequently been included in determinants of quality of life among frail elderly people (6, 7, 8), very few studies have determined whether institutional factors, such as food and nutritional services and dining experience, are associated with quality of life in LTC.
Several other factors have already been identified as contributing to the quality of life of the elderly in health care institutions. For example, chronic conditions, drug consumption, functional abilities, swallowing difficulties, and nutritional status have all been linked to their quality of life (9, 10, 11, 12). Risk of malnutrition has also been found to be associated with quality of life in older adults (10, 13, 14). Winzelberg et al. (9) observed a significant correlation between residents’ quality of life scores and their mental health status (i.e., severity of cognitive dysfunction and depression).
The American Dietetic Association put forward a position paper on nutrition and aging which stipulates that, along with environmental factors, the enjoyment of food and nutritional well-being play a key part in an older adult’s quality of life (1). The psychological and social aspects surrounding mealtime can impact on elderly residents’ quality of life by influencing the pleasure of eating. Mealtimes tend to give residents a sense of security, belonging, structure and order to their day. They can also give residents a sense of independence and control over daily choices (15).
A potential link between residents’ quality of life and institutional factors, such as those related to food and dining experience, has been indicated by some researchers (16, 17, 18, 19). West et al. (17) found that many residents feel powerless when it comes to their surroundings, such as the liberty to choose food and dining companions. Residents in their study ranked a greater variety of foods, meals that are appetizing, comfortable seating during meals, calm mealtime atmosphere and respect for food preferences as being among their top ten important food-related concerns. Similarly, Kane et al. (19) found that, when asked to rate the importance of control and choice over certain areas of their everyday nursing home life, residents prioritized having choice and control over their food.
In another study, residents’ quality of life seemed to improve following the introduction of a buffet-style meal service (20). This type of service included additional assistance for residents during meals and a better dining atmosphere. Residents could choose from a greater variety of foods and could receive second helpings of favourite foods (20). High correlations were also found between residents’ quality of life and their enjoyment of food and mealtimes, and being able to receive their favourite foods (21). According to Evans et al. (22), residents could adapt better to nursing home life if their food and food service preferences were being met.
Despite studies that demonstrate that food and nutrition services and dining environment are important to LTC residents, few studies have actually tested whether these factors are significantly related to their quality of life using a valid quality of life measurement tool.
Design and Methods
Study population
The population of interest for this study was nursing home residents aged 65 or older. All public nursing homes in New Brunswick, Canada were invited to participate in this study and 38 agreed (62.3%). These homes were representative of the 61 homes solicited in terms of size and geographic location. Within each home, residents were randomly selected from a list of all eligible residents compiled by a staff member. To be eligible for the study, residents must have lived in the home for at least six months, have not been hospitalized or on nutritional support (tube feeding) in the past six months, and have no terminal illness noted in their medical chart. These criteria were re-verified prior to data collection. Signed informed consent was obtained directly from cognitively intact residents who agreed to participate and from legal guardians of cognitively impaired residents. The research protocol was approved by the Research Ethics Committees of Laval University in Quebec City and the University of Moncton in New Brunswick, Canada.
Measures
Individual characteristics, such as age, gender, medical and dietary information were collected from each participant’s medical chart during on-site visits. We compiled a list of medical conditions that affect nutritional status by increasing energy expenditure, decreasing digestion, absorption or utilization of macronutrients, or affecting appetite (23, 24), and then scrutinized each participant’s chart for the presence of these conditions. A list of prescription medications affecting nutritional status by decreasing absorption or utilization of macronutrients, affecting appetite, causing nausea, vomiting and/or diarrhea was compiled for the same purpose (25, 26). Some conditions that were commonly found in our population were arthritis, hypertension, cardiovascular disease and functional difficulties. Some of the prescription drugs that were commonly present in our population were non-steroidal anti-inflammatory drugs (NSAID), angiotension-converting enzyme (ACE) inhibitors, calcium channel blockers, and diuretics, such as thiazide.
Risk of malnutrition was measured with a valid nutritional screening tool based on body mass index (BMI) and percentage of weight loss over time (27). To determine BMI, height was estimated using knee height measures (28) that were obtained with a Harpenden Anthropometer (Holtain Ltd.). Actual weight was measured by nursing staff no more than seven days prior to or after the on-site visit. In situations where weight was not charted on a regular basis, resident’s last recorded weight was utilized to calculate percentage of weight loss over time. The nutritional screening tool used in this study can determine weight loss over time from weights taken six months or prior (27). Participants were classified into one of four risk categories: no risk, low risk, moderate risk or high risk of malnutrition.
At the beginning of each interview, the Mini-Mental State Examination (MMSE) was administered to confirm cognitively intact participants’ ability to respond to interview questions and those with a score below 23 were not included in the study (29).
Quality of life was measured using Albert et al.’s (30) Quality of Life in Dementia (QOL-D) instrument, which is based on two instruments, a modified version of Lawton’s Affect Rating Scale (31) and a modified version of the Pleasant Events Schedule-AD (32, 33). The modified version of Lawton’s Affect Rating Scale is a set of six affects, both positive and negative that can be described in terms of facial and body expressions, such as pleasure and interest in people or everyday things or signs of depression, such as crying (31). The modified version of the Pleasant Events Schedule-AD includes a set of 15 activities, such as visiting with family and friends, exercising, and reading or being read to (32, 33). Cognitively intact participants and proxy respondents for cognitively impaired participants answered how often emotions or activities were experienced in the last two weeks. For the Lawton’s Affect Rating Scale, answers ranged from “never” to “3 or more times per day”, or “don’t know”. For the Pleasant Events Schedule-AD, possible answers were: none (0), few (≤ 3 times per week) or often (> 3 times per week). The QOL-D tool has been validated for use with proxies, but it has yet to be fully validated for use with cognitively intact residents (30, 34). The QOL-D questionnaire was completed during face-to-face interviews with each cognitively intact participant, while primary institutional caregivers completed the questionnaire for each cognitively impaired participant.
Dining experience variables included number of dining companions, independence with eating (i.e., ability to feed oneself), autonomy in relation to food (i.e., having access to food between meals and receiving special foods from family and friends), and respect of food preferences. These variables were measured with a separate questionnaire during face-to-face interviews with cognitively intact participants, while the primary institutional caregiver, who consisted of nursing staff, for each cognitively impaired resident completed the same questionnaire reformulated for proxy respondents. Foodservice variables were measured by a questionnaire completed by each institution’s foodservice manager or their designated substitute; variables included type of food delivery system, last menu revision and use of china dishes. Meal delivery systems were dichotomized such that heated base and dome, insulated tray, and cart with heated and cold sections were classified as tray systems, while cart-bulk and steam tables were classified as bulk systems. Therapeutic menus, such as diabetic or high fiber diets, were noted from each participant’s medical chart. Number of full-time equivalent (FTE) nursing staff (registered nurses (RN), registered nurse assistants (RNA) and registered assistants (RA)) was measured by a questionnaire completed by each institution’s administrator or their designated substitute. Ratios of residents per RN, RNA and RA were determined by dividing the number of residents by the number of nursing staff (FTE) in the facility.
Statistical Analyses
Data were analyzed separately for cognitively intact and cognitively impaired residents, using SPSS Version 13.0, 2004 Software (SPSS Inc., Chicago, IL). Reliability of the QOL-D instrument and its three subscales (activity, positive affect and negative affect) were tested using Cronbach’s alpha, and then their means and standard errors were computed. Frequencies were used to describe residents’ health and socio-demographic characteristics and quality of life. Bivariate correlations were analyzed to eliminate colinearity between potential independent variables, and multivariate ordinary least squares (OLS) regression models were used to determine which variables were significantly related to QOL-D scores. Level of significance was set at P<.05.
Results
Health and Socio-Demographic Characteristics
A total of 395 nursing home residents participated in the study, and 66.5 percent were cognitively impaired (n=263). Socio-demographic and health characteristics of cognitively intact versus cognitively impaired residents are presented in Table 1. Age, number of conditions and consumption of drugs that affect nutritional status were significantly different between the two groups. Gender distribution was similar in both groups, with women representing just over three-quarters of study participants, and size of institution did not differ between groups. However, a significantly higher percentage of cognitively impaired residents (26.8%) had a BMI less than 20 kg/m2 compared to those who were cognitively intact (9.1%).
Table 1.
Residents’ Health and Socio-Demographic Characteristics
| Cognitively intact N=132 Mean ± SD | Cognitively impaired N=263 Mean ± SD | |||
|---|---|---|---|---|
| Age (years) * | 83.6 ± 8.5 | 85.6 ± 7.6 | ||
| Length of stay (years) | 5.6 ± 6.6 | 4.8 ± 5.6 | ||
| Drug consumptiona (number) * | 6.4 ± 3.0 | 5.0 ± 2.7 | ||
| Medical conditionsb (number) * | 2.5 ± 1.5 | 1.3 ± 1.2 | ||
| n | % | n | % | |
| Gender | ||||
| Male | 29 | 22.0 | 61 | 23.3 |
| Female | 103 | 78.0 | 202 | 76.7 |
| Size of institution | ||||
| < 69 beds | 47 | 35.6 | 105 | 39.9 |
| 70 to 109 beds | 44 | 33.3 | 75 | 28.5 |
| 110 or more beds | 41 | 31.1 | 83 | 31.6 |
| Risk of malnutrition | ||||
| High risk | 7 | 5.3 | 48 | 18.6 |
| Moderate risk | 16 | 12.2 | 79 | 30.6 |
| Low risk | 26 | 19.8 | 53 | 20.5 |
| No risk | 82 | 62.6 | 78 | 30.2 |
| BMIc ** | ||||
| Less than 20 kg/m2 | 12 | 9.1 | 69 | 26.8 |
| 20-24 kg/m2 | 20 | 15.3 | 82 | 31.9 |
| Higher than 24 kg/m2 |
99 |
75.6 |
106 |
41.2 |
Notes: a drugs that affect nutritional status; b medical conditions that affect nutritional status; c BMI = body mass index.; *P < .05; ** P < .01; Significant differences between cognitively intact and cognitively impaired residents
Quality of Life Measure
Nineteen proxy caregivers did not respond to all positive and negative affect questions on the QOL-D questionnaire. Internal consistencies for the subscales and scale were verified using only valid responses. As presented in Table 2, the QOL-D scale has acceptable levels of internal consistency; however, its alpha is higher among cognitively impaired residents (=.79). The activity and positive affect subscales have alpha coefficients similar to the full QOL-D scale; however, the alphas are lower for the negative affect subscale. Missing values for each subscale were then replaced by their mean value within each institution. Cognitively intact residents presented significantly higher mean scores for QOL-D, activity and positive affect and significantly lower scores for negative affect, than cognitively impaired residents (Table 2).
Table 2.
Reliability Alphas, Means and Standard Deviations for the QOL-D Instrument and its Subscales
| Cognitively intact | Cognitively impaired | ||||
|---|---|---|---|---|---|
| (self report) (N=132) | (caregiver report) | ||||
| Internal consistencya | |||||
| QOL-D scaleb | 0.62 | 0.78 (n=201)e | |||
| Activity subscalec | 0.60 | 0.76 (n=259) | |||
| Positive affect subscaled | 0.59 | 0.70 (n=229)e | |||
| Negative affect subscaled | 0.53 | 0.63 (n=231)e | |||
| Mean (SE) | Range | Mean (SE) | Range | n | |
| QOL-D scaleb *** | 36.5 (0.4) | 27-48 | 27.6 (0.3) | 13-49 | 259 |
| Activity subscalec,f*** | 11.7 (0.4) | 3-22 | 5.5 (0.3) | 0-26 | 259 |
| Positive Affect subscaled,f *** | 14.8 (0.5) | 12-15 | 13.6 (0.1) | 6-15 | 263 |
| Negative Affect * subscaled,f ** |
8.1 (0.2) |
6-14 |
9.4 (0.2) |
6-15 |
263 |
Notes: a. Cronbach’s alpha; b. Albert et al. 1996; c. Logsdon & Teri, 1997; Teri & Logsdon, 1991; d. Lawton, 1994; e. In order to calculate internal consistency, missing values for the positive and the negative affect subscales as well as the combined scale were left in; f. Higher scores for activity and positive affect and lower scores for negative affect indicate a better quality of life; *P < .05; ** P < .01; *** P < .001
Institutional Characteristics and Quality of Life
Results from the multivariate OLS regression models, presented in Table 3, reflect the relationships between the different independent variables and QOL-D, while controlling for all other variables in the models. Due to deletion of missing values across independent variables, the n’s dropped significantly. To verify the robustness of the results, we ran reduced forms of the models that maximized the n’s by systematically dropping independent variables with the greatest number of missing values. Both models, for cognitively impaired (R2 =.27) and for cognitively intact (R2 = .24) residents explained similar proportion of the variance in QOL-D.
Table 3.
Characteristics associated with quality of life as determined by multivariate OLS regression (QOL-D Albert et al. 1996)
| Cognitively intact (self-report) N=96 | Cognitively impaired (caregiver-report) N=178 | |||||
|---|---|---|---|---|---|---|
| eta | S.E. | P-value | eta | S.E. | P-value | |
| Health and socio-demographics | ||||||
| Medical conditions (number)a | -.659 | .291 | .026 | .187 | .352 | .596 |
| BMIb | .18 | .748 | .806 | .801 | .576 | .166 |
| Length of stay | .010 | .005 | .063 | .008 | .006 | .190 |
| Dining experiences | ||||||
| Number of dining companions | 1.093 | .530 | .042 | 1.172 | .383 | .003 |
| Autonomy in relation to food | .742 | .330 | .027 | .665 | .262 | .012 |
| Independence with eating | -.456 | .736 | .537 | 1.173 | .367 | .002 |
| Respect of food preferences | -.039 | .346 | .910 | -.111 | .580 | .849 |
| Food services | ||||||
| Tray delivery system | 3.716 | 1.026 | .001 | 2.560 | .996 | .011 |
| Therapeutic menus | 1.883 | .917 | .043 | .522 | .936 | .578 |
| Porcelain-type dishes | .789 | .304 | .011 | .127 | .317 | .690 |
| Last menu revision (months) | .028 | .056 | .610 | -.136 | .067 | .043 |
| Additional institutional factor | ||||||
| Ratio residents/RAc | .458 | .185 | .016 | .454 | .198 | .023 |
| Constant | 32.857 | 4.324 | — | 21.023 | 2.954 | — |
| Adjusted R2 |
0.24 |
0.27 |
||||
eta = Unstandardized eta coefficient; S.E. = Standard error; a. Medical conditions that affect nutritional status; b. BMI= Body mass index; c. RA=Resident assistant
Of the three health and socio-demographic variables, only number of medical conditions that affect nutritional status had a negative and significant association with QOL-D among cognitively intact residents (β = - .659, P = .026).
Dining experiences were associated with QOL-D in both groups of residents. Number of dining companions was positively associated with quality of life in both cognitively intact (β = 1.093, P = .042) and cognitively impaired residents (β = 1.172, P = .003). Similarly, autonomy in relation to food, was positively associated with QOL-D in both cognitively intact (β = .742, P = .027) and cognitively impaired residents (β = .665, P = .012). For cognitively impaired residents, independence with eating (β = 1.173, P = .002) also had a significant positive association with QOL-D.
Among foodservice factors, tray meal delivery systems was positively associated with QOL-D in both cognitively intact (β = 3.716, P = .001) and cognitively impaired residents (β = 2.560, P = .011). Last menu revision was negatively related to QOL-D in cognitively impaired residents (β = -.136, P = .043), while therapeutic menus (β = 1.883, P = .043) and the use of china dishes (β = .789, P = .011) were positively associated with QOL-D among cognitively intact residents.
The ratio of residents per resident assistant (RA) was significantly associated with QOL-D in both cognitively intact (β = .458, P = .016) and cognitively impaired residents (β = .454, P = .023). BMI, length of stay and respect for food preferences were not significantly related to QOL-D in either group of residents.
Discussion
Measurement of Quality of Life
Very few studies have attempted to use a single measure of quality of life for both cognitively impaired and cognitively intact seniors; yet, for researchers concerned with improving the quality of life of all LTC residents this is an extremely important issue. The QOL-D instrument was developed for use among cognitively impaired seniors, and though its internal consistency was higher in cognitively impaired residents, it did have acceptable reliability for use with cognitively intact residents. For cognitively impaired residents, reliability results for all three subscales were quite similar between Sloane et al.’s (31) study and ours (β = .57 to .79). Unfortunately, Sloane et al. (34) did not report on the reliability of the combined QOL-D scale.
Mean scores for QOL-D and its subscales were significantly higher in cognitively intact residents, which reflected their higher quality of life, especially in terms of activity levels. Two previous studies found that quality of life decreases with increasing level of cognitive impairment (9, 11); however, Winzelberg et al. (9) used a modified version of the Logsdon et al.’s (35) Quality of Life-Alzheimer’s Disease scale (QOL-AD) in their study, while Kerner et al. (11) used the Quality of Well-Being (QWB) Scale.
Health and Socio-Demographics
Over two-thirds of the residents in this study were cognitively impaired, which is similar to percentages found by other studies with institutionalized elderly (3, 36). A significantly larger percentage of cognitively impaired residents compared to cognitively intact residents had a BMI lower than 20 (26.8% vs 9.1%). Other studies in LTC settings have also shown that residents with dementia-related disorders are more prone to weight loss and malnutrition (3, 36). Length of stay was not significantly associated with quality of life in either cognitively intact or impaired residents, but an increase in the number of medical conditions was negatively associated with quality of life in cognitively intact residents. There was no significant difference in types of conditions reported for cognitively intact versus impaired residents. This is somewhat surprising since different conditions should have lead to the institutionalization of both groups of residents. In addition, Kempen et al. (12) also found that chronic medical conditions were negatively associated with quality of life in cognitively intact older adults in both community and institutionalized settings.
Dining Experiences and Quality of Life
Number of dining companions was positively associated with quality of life in both cognitively impaired and cognitively intact residents. This association may reflect the fact that dining with others increases social interaction, which has been found to be a key component of quality of life (37). Number of dining companions may also be related to physical surroundings. Kayser-Jones & Schell (38) observed that residents who ate in their rooms had little or no social interaction during mealtime. When residents were asked to make a list of those aspects of their lives that were most important to their quality of life, they identified choice of dining companions and where to eat their meals as their top priorities (39).
Autonomy in relation to food, such as access to food between meals and having foods brought in by family and friends, also had a positive association with quality of life in both groups of residents. This finding is in line with other studies that found that residents prioritize having choice and control over their food (16, 17, 19).
Independence with eating was positively associated with quality of life in cognitively impaired residents. Among cognitively intact residents, 96.2% were independent with eating compared with only 52.1% among the cognitively impaired (χ2 = 77.186; df = 1; P = .000). Independence in eating can give residents a sense of control over their food intake. This sense of control increases pleasure and enjoyment associated with mealtime which can impact their quality of life. Residents who need assistance with eating often have functional disabilities, swallowing difficulties or severe dementias, which affect their quality of life (9, 12).
Foodservices and Quality of Life
Three of the four foodservice factors were found to be associated with quality of life among cognitively intact residents, but only two were associated with quality of life among the cognitively impaired. Tray meal delivery systems, compared to bulk, were positively associated with quality of life in both groups of residents. This finding contradicts one previous study among LTC residents that suggested there is a positive association between buffet-style dining and quality of life (20). While this study did not measure quality of life, quality of life seemed to be enhanced through increased enjoyment of both the food and the dining environment (20). Future studies must further explore the association between meal delivery systems and residents’ quality of life.
Close to 70% of menus had been revised within the last year (mean 13.0 ± 16.9 months). More recent menu revision had a positive association with the quality of life of cognitively impaired residents. Periodic menu revision likely decreases food items that are less liked by residents and increases items that are more enjoyed by residents, such that foodservice personnel and institutional caregivers can more often satisfy the preferences and tastes of cognitively impaired residents. Improved meal satisfaction on the part of both residents and staff would then enhance quality of life in cognitively impaired residents.
Therapeutic menus was positively associated with quality of life in cognitively intact residents, and more cognitively intact residents were on therapeutic menus (54.5%) than cognitively impaired (39.9%) (χ2 = 7.598; df = 1; P = .006). The most common therapeutic diets among cognitively intact residents were diabetic, reduced salt and low-fat diets. These menus may make cognitively intact residents feel special, since they require more follow-ups from dietary and nursing staff. According to Evans et al. (22), many nursing home residents yearn for personalized nutrition care and individualized attention. It should be noted, however, that very restrictive diets may significantly reduce the pleasure of eating (1).
China dishes were also associated with quality of life in cognitively intact residents. Hackes et al. (40) found that serving meals on china dishes decreased food waste in LTC, possibly indicating greater satisfaction with mealtime. Furthermore, china dishes may give cognitively intact residents the feeling of being at home, while insulated plastic dishes could have the opposite effect, making them feel like a patient in a hospital. Cognitively impaired residents are probably much less aware of what types of dishes are used at mealtime.
Staffing and Quality of Life
The ratio of residents per RA was positively related to quality of life in both cognitively intact and cognitively impaired residents. This finding is somewhat surprising, since the assumption has always been that having a greater number of staff to assist residents should improve their quality of life (41); however, a higher ratio of residents per RA does not necessarily mean inadequate staffing. The average ratio of residents per RA in this study was 5.3, which is, according to Simmons et al. (4), quite sufficient to ensure quality care. We also found that the ratio of residents to RAs was negatively correlated with size of institution (r = -.419; P = .000). This indicates that smaller institutions tended to have higher ratios of residents per RA than larger institutions. Residents in smaller homes may develop stronger and more intimate relationships with staff and other residents. They may also simply feel more “at home” in smaller facilities. Perhaps residents living in smaller homes with a higher ratio of residents per RA feel more autonomous and less “looked after”, which may increase positive affect and decrease negative affect.
The QOL-D was one of the best measurement tools available when this research was initiated, and its reliability results with cognitively intact residents reflect the fact that it was developed primarily for use with the cognitively impaired. The QOL-D measures three dimensions of quality of life (activity and positive and negative affect), while other instruments measure additional dimensions of quality of life, such as physical conditions, interpersonal relationships and mobility. Future researchers should continue examining the validity of the QOL-D and other quality of life instruments, in both cognitively impaired and cognitively intact LTC residents.
Dining experiences, food and nutritional services, and nursing personnel each play important roles in promoting and improving quality of life among nursing home residents. Results from this study suggest that quality of life may be enhanced for both cognitively intact and cognitively impaired residents by encouraging them to dine with others and increasing their autonomy in relation to food. New LTC facilities or those under major renovation might also consider implementing tray-based meal delivery systems, though further studies are needed to confirm the benefits of these systems.
While serving meals on china dishes, instead of plastic or insulated dishes, might improve quality of life of cognitively intact residents, the proactive diagnosis and rehabilitation of eating difficulties might improve the quality of life of cognitively impaired residents. Future studies should continue to separately examine the ways in which dining experiences, food and nutritional services, and other institutional factors help determine quality of life among cognitively intact versus cognitively impaired residents in LTC settings.
Acknowledgment: We would like to thank the foodservice managers, the nursing staff, the dietitians, the administrators, the families and especially the residents in each participating nursing homes.
Funding: This project was funded by the Medical Research Fund of New Brunswick (MRFNB).
Financial disclosure: None of the authors had any financial interest or support for this paper.
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