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NUTRITIONAL ADEQUACY AND ORAL NUTRITIONAL SUPPLEMENTATION IN OLDER COMMUNITY-DWELLING ADULTS

 

L. McKeever1, I.C. Farrar2, S. Sulo3, J. Partridge3, P. Sheean4, M. Fitzgibbon5,6

 

1. Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of  Illinois at Chicago, Chicago, IL, USA; 2. Survey Research Laboratory, University of Illinois at Chicago, Chicago, IL; USA; 3. Abbott Nutrition Research & Development, Columbus, OH, USA; 4. Marcella Niehoff School of Nursing, Loyola University, Chicago, IL, USA; 5. Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA; 6. Department of Pediatrics, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA

Corresponding Author: Liam McKeever, PhD, RDN, University of Illinois at Chicago, Department of Kinesiology and Nutrition, College of Applied Health Sciences, 1919 W. Taylor St, Applied Health Sciences Building, Room 633, Chicago, IL 60612, Email: wmckee2@uic.edu, Phone: 773-263-2492

J Aging Res Clin Practice 2019;8:7-14
Published online January 2, 2019, http://dx.doi.org/10.14283/jarcp.2019.2

 

Abstract

Background: Older adults (65 years and older) comprise a high-risk group that are susceptible to the development of malnutrition. Dietary intake and diet quality represent key modifiable risk factors to help prevent and to treat declines in nutrition status, with oral nutritional supplements (ONS) often being a cost-effective therapy for many to increase protein and caloric intake. The DETERMINE Checklist offers a series of questions capable of mapping the initial landscape of contextual factors that influence the dietary patterns of the at-risk populations. Objectives: To examine independent predictors of inadequate dietary intake and poor diet quality amongst a multi-ethnic sample of urban community-dwelling older adults in an effort to identify target groups of participants that could benefit most from an ONS intervention. Design: Cross-sectional. Participants: Chicago, Illinois, United States urban residents greater than 55 years of age who self-reported to be non-Hispanic White, non-Hispanic Black, or Hispanic. Methods: Telephone surveys were conducted to obtain basic demographic information. The DETERMINE Checklist was administered to (1) characterize participants’ nutritional risk, and (2) identify participants with inadequate intake and/or poor diet quality. Predictors of inadequate intake, defined as any participant who reported either to eat less than two meals per day and/or poor diet quality, defined as any participant who reported to eat few fruits, vegetables or dairy were used to identify groups of participants who could benefit most from ONS consumption. Mantel-Hanzel chi square, Breslow-day tests, and logistic regressions were conducted. Results: 1001 ethnically diverse participants were interviewed (37% non-Hispanic White, 37% non-Hispanic Black, and 26% Hispanic). Respondents were predominantly female (69%) with a mean age of 66.9 (± 6.4) years. The majority were found to be at either moderate or high nutrition risk (78.7%). Domains of the DETERMINE Checklist that predicted either inadequate dietary intake or poor diet quality included social isolation, lower levels of educational attainment, food insecurity, limitations in activities of daily living (ADL), polypharmacy, or three or more alcoholic drinks per day. Of the participants who met the criteria as those who would benefit from ONS, less than 50% had reported consuming ONS in the past six months. Conclusion: Older community-dwelling adults living in an urban setting, especially those with social isolation, lower levels of education, food insecurity, limitations with ADLs, polypharmacy, and those reporting heavy alcohol intake represent a population who could benefit from consuming ONS. Efforts should be made towards further understanding these contextual factors and providing nutrition education along with an ONS intervention that could be beneficial to supplement dietary inadequacies in this population.

Key words: Nutrition risk, community nutrition, older adults, oral nutritional supplement, DETERMINE Checklist.

 

Introduction

Older adults (65 years and older) comprise a high-risk group that are susceptible to the development of malnutrition. This can occur due to decreased macronutrient intake, poor diet quality (1), mental illness (2, 3) impaired mastication (3, 4) polypharmacy (4), social isolation (5, 6), poverty (1), and declines in activities of daily living (ADL) (4, 7, 8). Preventing or treating malnutrition in this population is important, as it is associated with increased mortality (9), hospital readmission (10, 11), unplanned weight loss (1), increased fractures (12, 13), and loss of independence (14).  Dietary intake and diet quality represent key modifiable risk factors to help prevent and to treat declines in nutrition status, with oral nutritional supplements (ONS) often being a cost-effective therapy for many to increase protein and caloric intake. In fact, when ONS is used independently and in combination with other nutrition interventions (e.g., education, dietary counseling, etc.) among community-dwelling adults, it may result in overall cost savings due to improving health outcomes of at-risk for malnutrition patients (15-17).
In 1993, the Nutrition Screening Initiative (NSI) developed the DETERMINE Checklist, a nutrition screening tool of 10 questions designed to identify older adult patients who would benefit from more in-depth nutrition assessment (1). This checklist was created primarily to facilitate the education of patients on the importance of nutrition as well as to inform clinicians of the unique dietary needs of older adults. While the DETERMINE Checklist was not designed as a stand-alone screening tool, its 10 questions cover a broad range of scenarios that characterize the unique challenges of the aging population. Of these 10 questions, 1 relates to inadequate intake, identifying patients who ‘eat fewer than 2 meals per day.’ One relates to poor diet quality, detecting patients who eat ‘few fruits, vegetables, or milk products,’ while the remaining 8 questions categorize possible causes for inadequate intake or poor diet quality.
To date, the literature exploring malnutrition in the United States (USA) within community settings is limited and few studies have specifically examined the independent root causes of modifiable malnutrition risk factors. Therefore, the objective of this study was to use the DETERMINE Checklist to: (1) examine the independent predictors of inadequate intake and poor diet quality amongst a multi-ethnic sample of older urban community-dwelling adults, and (2) to use those predictors to identify target groups (Predictor Groups) of participants that could benefit most from ONS intervention.

 

Methods

This cross-sectional study was conducted in community-dwelling Chicago, Illinois (USA) residents greater than 55 years of age. Respondent information was collected via a telephone survey, which was created by a multidisciplinary team of researchers in collaboration with the Survey Research Laboratory of the University of Illinois at Chicago (SRL). The telephone interviews were conducted by the Interviewing Service of America (ISA).
Interviewer Training: Twenty-nine interviewers from ISA underwent a rigorous 24-hour general training in telephone interviewing skills. They were then trained specifically on the components of the study survey by expert personnel. This included orientation to the background and purpose of the study, training in each survey question, and practice interviews.

Field Procedures

This study was conducted over 4 months. Four sample frames were used; two random digit dial (landline and cell) and two listed (landline and cell). The two listed sample frames were targeted to reach participants within the selected age range and race/ethnicity distributions. Potential participants were called up to 6 times before determining them unreachable.  Computer Assisted Telephone Interviewing (CATI) software was used to administer the survey. Interviews were conducted in English and Spanish on weekends and weekday evenings. Respondents were told the interview would last approximately 20 minutes and they would be paid $10 for their participation if they provided their mailing address.

Participants

Eligible participants for this study were any person residing within the City of Chicago, Illinois, USA who used a landline or a cell phone with a Chicago area code. To be included in the survey, participants had to self-report their race/ethnicity as non-Hispanic White, non-Hispanic Black, or Hispanic; speak either English or Spanish; be 55 years of age or older; and be willing to participate in the study.

The Survey

The goal of the survey was to characterize nutritional risk, specifically seeking information regarding ONS usage. Components of the survey included in the analysis were basic sociodemographic information (i.e., gender, age, height, weight, education, insurance status), administration of the DETERMINE Checklist, and recent ONS usage.

Nutritional Risk

The DETERMINE Checklist is a list of 10 yes/no statements surveying various predetermined risk factors related to malnutrition risk in the older adults. Originally, the DETERMINE Checklist was tested in adults greater than 70 years of age (1), but has since been used and validated in adults as young as 60 years (18, 19). Usually, a score ranging from 0 to 21 is generated from these yes/no comments on nutrition risk in general:  no nutritional risk (0-2), moderate nutritional risk (3-5) or high nutritional risk (6 or more). The current study abandons analysis of the score itself, but makes use of the questions as system of independent and dependent variables to predict groups that might benefit most from ONS.  Figure 1 lists the DETERMINE Checklist questions and details the proxy terms used to describe the study variables. For the purpose of this study, a participant with ‘Inadequate Intake’ was defined as anyone who answered ‘yes’ to the DETERMINE Checklist item for eating fewer than 2 meals per day. A participant with ‘Poor Diet Quality’ was defined as anyone who answered ‘yes’ to the DETERMINE Checklist item for eating few fruits, vegetables, or milk products. These are simple, yet efficient screening questions that directly address the root sources of malnutrition.

 

Figure 1 The NSI DETERMINE Checklist and Proxy Terms for Each Item

Figure 1
The NSI DETERMINE Checklist and Proxy Terms for Each Item

 

ONS

ONS was defined for the participants as liquid beverages found in the pharmacy section of their grocery store or in special sections of their pharmacy that are consumed in addition to food when diet alone cannot fully provide calorie, protein, and other nutrient needs. Participants were asked whether they had consumed ONS in the past six months.

Outcome Variables

The analysis centered on identifying groups of participants who had increased odds of inadequate intake and/or poor diet quality. Potential groups explored were participants who answered ‘yes’ to any of the remaining 8 domains of the DETERMINE Checklist, as well as the standard sociodemographic variables. Groups with increased odds of either inadequate nutritional intake and/or poor diet quality were labeled Predictor Groups as they were predictive of those two variables and constituted groups of participants who could benefit most from ONS consumption.

Statistical Analysis

Utilizing basic demographic information from the survey, and data from the DETERMINE Checklist, our analysis centered on identifying groups of participants who had increased odds of inadequate dietary intake and/or poor diet quality. Groups with increased odds of either inadequate intake and/or poor diet quality were labeled Predictor Groups as they were predictive of those two variables and constituted groups of participants who could benefit most from ONS consumption. Descriptive statistics were conducted to assess differences stratified by gender and race/ethnicity. Predictors of inadequate intake and poor diet quality were explored using Mantel-Hanzel chi square tests and logistic regression modeling. Potential predictors explored included the 8 other components of the DETERMINE Checklist as well as basic sociodemographic variables. Breslow-Day tests were then used to explore effect modification amongst the potential predictors. Model one explored predictors of inadequate intake and model two explored predictors of poor diet quality. Regression diagnostics were run to assess collinearity amongst variables and manual backwards elimination with an alpha cut-point of <0.05 being used to derive the final models. All statistical analyses were run in SAS 9.4.

 

Results

The ISA database contained 64,475 relevant phone numbers. Ninety percent of these numbers were unusable (n=57,381) because they were no longer working (42%; n=27,022), the participant did not answer (27%, n=17,427), they went to voicemail (19%, n=11,922), or the participant was no longer living in Chicago (2%, n=1,010). Of the 7064 remaining numbers, 1001 participants were found eligible, able and willing to complete the interview. Based on the ratio of participants eligible, able and willing to complete the survey and patients known to be eligible, but unwilling or unable, our response rate was 85.8% (n=1001/1165). Based on the sum of eligibility estimates from the larger unreachable sample and the known eligible, a more conservative response rate of 7.7% (n= 1001/12,948) was calculated. The mean age of respondents was 66.9 (± 6.4) years.  Respondents were predominantly female (69%) with fairly equal distribution by race/ethnicity [non-Hispanic White (37%), non-Hispanic Black (37%) and Hispanic (26%)]. Education attainment was high overall with approximately 60% of participants reporting they attended ‘at least some college.’ College attendance was particularly low, however, amongst Hispanics (28%) as compared to non-Hispanic Blacks (60%) and non-Hispanic Whites (82%). Over 73% of the population was either overweight or obese. Very few participants in our sample were underweight (3%) as defined by BMI<18.5 kg/m2. The DETERMINE Checklist found 28.6% of participants to be at moderate nutrition risk and 50.1% of participants to be at high nutrition risk.  Frequency tables for sociodemographic characteristics and DETERMINE Checklist risk factors stratified by oral intake status and diet quality are presented in Table 1. Inadequate dietary intake and poor diet quality were more common in participants with illness-induced diet changes, poor dentition and oral disease, food insecurity, social isolation, polypharmacy, limitations in ADL, and lower levels of educational attainment. Poor diet quality was more common in men.

Table 1 Sociodemographic and NSI DETERMINE Risk Factor Characteristics Stratified by Oral Intake and Diet Quality

Table 1
Sociodemographic and NSI DETERMINE Risk Factor Characteristics Stratified by Oral Intake and Diet Quality

a. Tests for difference between male and female and between race/ethnicity groups: Mantel Hanzel Chi Square tests were used for all variables using P-values derived from nonzero correlation for ordinal variables and general association for all other variables; b. ADL=Activities of Daily Living; c. ONS=Oral Nutritional Supplements

 

Table 2 provides the predictive modeling results for ‘inadequate dietary intake’ and ‘poor diet quality.’ Overall, inadequate dietary intake was higher in participants reporting food insecurity (P=0.0007) and social isolation (P=0.0019) compared to those who did not. Among non-Hispanic White participants, inadequate nutritional intake was more common in those who did not attend college (P<0.0001) compared to those that attended at least some college. While this association is directionally similar amongst non-Hispanic Black and Hispanic participants, it did not achieve statistical significance. Compared to those who did not have limitations in ADLs, having ADL limitations was associated with inadequate intake amongst non-Hispanic Whites (P=0.0004) and Hispanics (P=0.0302), but not amongst non-Hispanic Black participants (P=0.5922).

Table 2 Crude and Adjusted Odds Ratios (OR) for Logistic Regression Models predicting Inadequate Intake and Poor Diet Quality

Table 2
Crude and Adjusted Odds Ratios (OR) for Logistic Regression Models predicting Inadequate Intake and Poor Diet Quality

a. BMI=Body Mass Index; b. ADL=Activities of Daily Living; †Median Age, gender, BMI Category, Insurance, Illness-induced diet change, 3+ Drinks per day, Dentition/Mouth Problems, Unplanned Weight Change were assessed but were statistically insignificant and dropped from the model; ††Median Age, BMI Category, Insurance, Illness-induced diet change, Dentition/Mouth Problems, Social Isolation, and Unplanned Weight Change were assessed but were statistically insignificant and dropped from the model; *P-value <0.05; **P-value <0.0001

 

Poor Diet Quality was also higher in participants with food insecurity (P=0.0010) and in those who reported consumption of 3 or more alcoholic drinks per day (P=0.0175). Specifically, poor diet quality was more common in women (P<0.0001) and men (P=0.0209) who did not attend college versus those who did, with college attendance being over two times more protective in men compared to women. Amongst participants without ADL limitations, poor diet quality was more common in non-Hispanic Black (P=0.0061) and Hispanic (P<0.0001) participants compared to non-Hispanic Whites. Amongst those who had ADL limitations, poor diet quality was more common in participants who claimed to take 3 or more medications per day (P=0.0150).

Table 3 Analysis of Subjects Who Would Benefit from Oral Nutritional Supplementation (ONS) by Predictor Group

Table 3
Analysis of Subjects Who Would Benefit from Oral Nutritional Supplementation (ONS) by Predictor Group

a. The number and percent of subjects in the predictor group; b. The number and percent of those in the predictor group who also have either inadequate intake or poor diet quality; c. The number of participants in the predictor group who have either inadequate intake or poor diet quality and who have not taken oral nutritional supplements in the past six months. The percent represents the percent of participants in the total predictor group to target with ONS Intervention; d. ADL = Activities of Daily Living

 

In total, 585 participants (58%) reported either inadequate dietary intake or poor diet quality; thereby meeting the pre-defined criteria for requiring ONS. Of these 585, only 73 participants (13%) had reported consuming ONS in the past 6 months. Table 3 lists the predictor groups that could benefit most from ONS. Groups to target with ONS therapy include those reporting: social isolation, lower levels of educational attainment, food insecurity, ADL limitations, polypharmacy, or those who drink three or more drinks per day. The percentage of participants in these groups who met the criteria as someone who would benefit from ONS but who had not recently consumed ONS were 55%, 65%, 68%, 63%, 64%, and 54% respectively.

 

Discussion

Based upon results of the DETERMINE Checklist administered by telephone survey, this study demonstrated that social isolation, less educational attainment, low income, heavy daily alcohol intake, compromised ADL, and polypharmacy were significant independent predictors for inadequate dietary intake and/or poor diet quality among an ethnically diverse, predominantly female community sample. Although these results are consistent with existing literature (5, 6, 19-21), what is perhaps more interesting in our study is that so few participants in these predictor groups who could potentially benefit from ONS reported to be consuming ONS.  This finding reveals a large group who could benefit most from this simple and cost-effective intervention (15, 22).
Poor diet quality and inadequate dietary intake are common themes amongst older community-dwelling adults. In 2015, Borg et al. (23) published a meta-analysis of 44 trials in Western countries in community-dwelling older adults with a pooled sample size of 14,419 participants comparing energy and macronutrient intake against normal reference values. The average energy intake was approximately 13% below the estimated average requirement of 2,450 kcals/day. In general, the oral diets of these older participants were below the acceptable macronutrient distribution ranges (AMDR) for carbohydrates, on the lower end of the AMDR for protein, and on the higher end for fat. These diets were 3% above the upper acceptable range for saturated fat and low in mono- and poly-unsaturated fats. Vitamin and mineral intake is low in older adult diets as well. In one study (19) of 345 elderly homebound Georgians, 81% had intakes deficient in magnesium, 94% in vitamin E, and 51% in zinc. Perhaps more alarming was that >95.6% had deficient calcium intake and almost every participant reported inadequate vitamin D intake. In this study, skipping breakfast alone was associated with deficient energy intake as well as inadequate intake of 12 essential nutrients.
Studies exploring the effects of ONS on clinically relevant outcomes in older adults are abundant. The National Collaborating Center for Acute Care (in United Kingdom) performed a series of meta-analyses (24) exploring the pooled effects of randomizing hospital and community-dwelling subjects to receive proprietary ONS versus standard care. Randomization to receive ONS was found to significantly decrease the risk of mortality and complications, hospital length of stay, and increased weight gain. In addition, ONS has also been found to play a vital role in preventing hospital readmissions. In 2013, Stratton et al. performed a meta-analysis (25)that found a 41% reduced odds of hospital readmission amongst older adults using ONS in addition to standard care as compared to controls receiving only standard care.  Further, adherence to ONS therapy in older individuals appears to be met with minimal resistance.  A meta-analysis (26) of 32 randomized controlled trials and 14 non-randomized studies was performed to confirm compliance to ONS regimens. Overall pooled compliance in community settings was 80.9%. The mean age of the study participants overall (hospital and community-dwellers combined) was 74 years.
Despite the current evidence supporting the positive impact ONS has on various health outcomes for at-risk individuals, very few who might benefit from ONS are actually consuming ONS. In our study, of the 58% of participants classified as individuals who would benefit from ONS due to their poor dietary patterns, only approximately 12% had reported consuming an ONS in the past 6 months. These findings imply that registered dietitians and other healthcare professionals, given their patient’s dietary needs, should target their nutrition education for ONS supplementation towards the key Predictor Groups identified in this study as they are the most likely to have inadequate dietary intake and poor diet quality. These results also highlight the importance of nutrition screening and education by primary care clinicians in these populations.  It also highlights the DETERMINE Checklist as a valuable tool for identifying vulnerable individuals according to specific answers provided.  The information gathered through the DETERMINE Checklist may assist clinicians in mapping the initial landscape of contextual factors that influence the dietary patterns of the at-risk populations. Therefore, efforts should be made towards further understanding these contextual factors and providing nutrition education and ONS that could be beneficial to supplement dietary inadequacies in this population.
Our study had several limitations, which are commonly reported for survey study designs. First, the cross-sectional design of our study precludes causal inference for any of the reported associations. Second, participants without either a landline or a cell phone with a Chicago area code were excluded from the survey. To the extent to which these excluded persons differed from our included participants, our study may be vulnerable to coverage bias. Third, we had a large percentage of non-responders, leading to possible non-response error. Participants who did not respond may differ meaningfully from those who did, inadvertently omitting an important portion of our target population from our analysis. Regardless of these limitations, this study included a large sample size of a multi-ethnic group of participants and the use of a professional survey research laboratory and interviewing service to assemble and administer the survey. Another strength of this study is the use of the DETERMINE Checklist as a set of domains for predicting inadequate intake and poor diet quality rather than as a weighted score. This methodology makes use of the simple strengths of the tool while bypassing the validity issues encountered in other studies (7, 18, 27). The findings generated from this analysis could inform the designing and tailoring of future nutrition-focused interventions that could improve the nutritional outcomes of the older adult population at nutritional risk living in different community settings.

 

Conclusions

Inadequate dietary intake and/or poor diet quality are highly prevalent in community-dwelling older adults with social isolation, lower levels of educational attainment, food insecurity, ADL concerns, polypharmacy, and high alcohol intake. These adults may benefit from but are mostly not consuming ONS.  Ensuring both the quality and quantity of their oral intake represents a tangible method to potentially treat or even prevent nutritional decline amongst older community-dwelling adults.  It would be helpful to understand more about potential contextual factors in the lives of older adults, such as limited social support, poor access to healthful food options, limited food purchasing and preparation skills, depression, and others that place them at nutrition risk. Future research is needed to further identify specific barriers to proper nutritional support in this population and the potential for successful nutrition-related interventions to supplement their dietary inadequacies.

 

Funding Disclosure: This study was funded by a grant from Abbott Nutrition (#HA28). I. Farrar, M. Fitzgibbon, and P. Sheean received salary support from Abbott Nutrition. S. Sulo and J. Partridge are employees of Abbott Nutrition.

Conflicts of Interest: Jamie Patridge and Suela Sulo receive a salary and stock from Abbott.

Ethical standards: This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the University of Illinois at Chicago and Loyola University Chicago Institutional Review Boards. Verbal informed consent was obtained from all subjects. Verbal consent was witnessed and formally recorded.

 

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HIGH PREVALENCE OF NUTRITION RISK AMONG COMMUNITY LIVING OLDER PEOPLE IN WOERDEN, THE NETHERLANDS

 

T.A. Haakma, C.A. Wham

The Hague University of Applied Sciences, Johanna Westerdijkplein 75, 2521 EN The Hague, The Netherlands 

Corresponding Author: T.A. Haakma, Student at The Hague University of Applied Sciences, Design and conduct of study, data analysis, writing of manuscript. Breeveld 10a, 3445 BA Woerden, The Netherlands, Telephone: (+31) 0613684251, Email: tinekehaakma@hotmail.nl

 

Abstract

Background: Undernutrition is a common problem in Dutch older people and may cause increased length of hospitalisation, early institutionalization and decreased quality of life. Nutrition risk precedes undernutrition and can be identified by timely nutritional screening. Design: This cross-sectional study aimed to examine the prevalence of nutrition risk among older people living in the community of Woerden. Measurements: Nutrition risk was assessed using a validated questionnaire: Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II (‘SCREEN II’). Participants: The sample (n=335, mean age 80, age range 75-85) were 32% men, 40% received home care and 46% lived alone. Results: Nutrition risk was present in two thirds (67%) of the respondents (38% ‘at high risk’, 29% ‘at risk’). The most common SCREENII items that led to nutrition risk were a low intake of meat and alternatives (65%), milk products (59%), fruit and vegetables (59%) and eating alone (56%). Those who received home care were 1.8 times more likely to be at nutrition risk than people without home care (p=0.03) and those living alone were 3.3 times more likely to be at nutrition risk than those living with others (p<0.001). Conclusions: Intervention strategies are needed to encourage Dutch older people to take opportunities to eat meals with others and to improve their intake of major food group items. Training of home care staff to identify nutrition problems should be prioritised.

Key words: Nutrition Risk, The Netherlands, older people, SCREEN II, home care. 

 

Introduction 

Maintaining health and functionality in older people (>65y) is very important for the maintenance of independence (1). The Dutch government aims to keep older people healthy, to allow them to live independently as long as possible in the community with relatively little care (2). To achieve that objective, the government invests in home care staff. The Dutch population is aging, the number of older people will increase rapidly from 2013 (3). Those over 65 years are expected to increase from 2.7 million (16% of the entire population) in 2012 to a maximum of 4.7 million in 2041 (estimated to be 26% of the entire population). In the Netherlands the cost of living in an institution is estimated to be 6.000 to 16.000 euro per person per year more than living at home (4). Among older people who are in transition to move into an institution in the Netherlands the most important reason relates to a decrease in mobility (5). A large increase in institutionalized living older people is projected for those aged over 80 years (6). 

Nutrition is an important determinant of health and functionality in older people (7). Poor nutrition, which refers to an inadequate, unbalanced diet (8) leads to undernutrition (9), which is associated with an increased length of hospital stay, early institutionalization (10), decreased quality of life (11) and may contribute to the development of disease (12). Undernutrition is related to long-term mortality in community dwelling as well as institutionalized older populations (13, 14) and is likely to cause an indirect increase in healthcare costs (10, 15). 

Early recognition of undernutrition is important as nutritional intervention can reduce complications and further impairment of nutritional status (14, 16). Undernutrition is preceded by a state of nutrition risk, which can be identified by nutrition risk screening (17). Among Dutch older people almost a third (29.5%) is at risk of undernutrition in chronic care institutions (living, care and wellbeing institutions, mean age 83.6) and 22.7% are at risk of undernutrition in home care settings (mean age 79.0) (18). Using the SNAQ-criteria (Short Nutrition Assessment Questionnaire 65+), 9.2% of Dutch older people receiving home care were identified to be at nutrition risk compared to 7.7% without home care (mean ages 81.6 and 77.3 years, respectively) (14). 

The current prevalence of nutrition risk amongst independently living older people in The Netherlands is unknown. The aim of this study was to assess the prevalence of nutrition risk of community dwelling older people, identify common risk factor items and compare nutrition risk status of those with and without home care.

 

Methods 

Participants

A cross-sectional study was undertaken amongst older people from the community of Woerden. Woerden is considered to be a typical community in The Netherlands on the basis of population structures such as age, gender, income, and nationality. Inclusion criteria for recruitment were age 75-85 years (born between 1929 to1939) and  Dutch nationality. The sample size was set for 334 older people within the age range of 75-85 years, applying 95% reliability and 5% margin of error. 

Participant recruitment

Participants responded to advertisements in two regional newspapers, through home care staff working in the community, by participant acquaintances and direct contact through arranged activities across the Woerden community for older people.  

The Medical Ethics Review Committee (METC, UMC Utrecht) deemed the study to be of low risk and therefore an official approval of the study was not required under The Medical Research Involving Human Subjects Act (WMO) (reference number WAG/th/14/020125). 

Data collection

Data collection was undertaken by a postal survey in April/May 2014. Participants completed a questionnaire sent to their private home (20.5%), in groups of people, facilitated by the activity arranging organisation ‘Welzijn Woerden’ (44.4%), by face to face interviews with the researcher (29.5%) or by email (5.6%).

The questionnaire 

The questionnaire consisted of 23 items, 6 items for personal characteristics and home care, 3 items for evaluation of their acquaintance with the study and 14 items for an assessment of nutrition risk. Nutrition risk was measured using a Dutch translation of the validated questionnaire ‘Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II’ (SCREEN II) with questionnaire items about weight change, food intake and risk factors for food intake. For each item the scores ranged from zero to four and the maximum score was 64. The total score was categorized as: ‘not at risk’ (score ≥54), ‘at risk’ (score= 50-53) or ‘at high risk’ (score ≤49) (19). Participants ‘at risk’ or ‘at high risk’ were referred to a physician or dietitian.

Statistical analysis 

Descriptive statistics were completed for demographic items, living situation and professional home care data. The univariate associations between nutrition risk category and the variables gender, living situation and professional home care were tested by Pearson chi-square tests and odds ratios. Multivariate binary regression analysis was used to show whether the associations were maintained when all variables were included (gender, living situation and home care). Pearson Chi-square test was used to determine differences in nutrition risk items for participants who received home care versus who did not. P value below 0.05 was considered as significant. Statistical analyses were performed with SPSS 22.0 for Mac. 

 

Results

Participant characteristics

There were 335 participants included in the study, with a mean age of 79.9 (± 2.96) years (Table 1). There were more women (68%) and fewer participants lived alone (46%) compared to the population of 2573 older people aged 75 to 85 living in Woerden (Table 1). A total of 40% of the participants received professional home care, which was similar to the Woerden community.

 

Table 1 Participants characteristics

a. On the 13th of May 2014, information about population obtained by contact with Town Council and includes people living in institutions (n=59); b. Based on the percentage of valid AWBZ indications in Woerden on the 1st of January 2013 and number of people who receive refund for help with domestic chores on the 27th of May 2014.  AWBZ indications are statements for the right to receive chronic care (27).

 

Nutrition risk

Nutrition risk status was assessed in 335 participants. For 17 respondents (5.1%) a score could not be assigned due to missing data. Using the SCREEN II questionnaire 38.4% of the respondents were ‘at high risk’ (SCREEN II score ≤49), 28.6% were ‘at risk’ (SCREEN II score 50-53) and 33.0% were ‘not at risk’ (SCREEN II score ≥54) (Table 2). Half (50.8%) of the older people who received home care were ‘at high risk’ compared to 27.7% of people who did not receive home care. Participants more likely to be at high nutrition risk were of female gender (p=0.026), living alone (p<0.001) and receiving professional home care (p<0.001). (Table  5).

Table 2 Nutritional risk groups according to SCREEN II by gender, living situation and professional home care

 

Participants in the categories ‘at risk’ and ‘at high risk’ were combined for further analysis. Significant univariate associations were observed for living situation and home care (Table 3). People living alone were 3.31 times more likely to be at risk than people living together. People who received home care were 2.18 times more likely to be at risk than people who do not receive home care. In the multivariate model (Table 4) the association between living alone and high nutrition risk persisted (controlled for gender and home care). The univariate associations between the variables gender and home care and nutritional risk were not maintained in the multivariate model. 

 

Table 3 The odds ratiosa for gender, living situation and home care for those ‘Not at risk’ versus combined risk group)

a. Within the brackets, the 95% confidence intervals are displayed

 

Figure 1 shows the frequency of SCREENII nutrition risk items for those at risk. The six main nutrition risk items were low meat and alternatives intake (65.1%), low milk product intake (59.4%), low fruit and vegetable intake (58.5%), eating alone (55.7%), perception of own weight and difficulty cooking (both 42.5%). 

 

Figure 1 Nutrition risk items for participants at nutrition risk

 

Table 5 shows nutrition risk items for people who do and don’t receive home care. Those who receive home care are significantly more often at risk for eating alone, weight change, difficulty with grocery shopping, poor appetite, frequent use of meal replacements and unnoticed weight change.

Table 4 The odds ratiosa for gender, living situation and home care for those ‘At risk’ versus ‘At high risk’

a. Within the brackets, the 95% confidence intervals are displayed.

 

Table 5 Nutrition risk itemsa for respondents in the combined risk group who do and don’t receive professional home care

a. SCREEN II items with scores less than or equal to two out of a maximum of four potentially lead to nutrition risk (19)

 

Discussion

This is the first Dutch study to identify the prevalence of nutrition risk among older people in the community using SCREEN II. Amongst people in Woerden over a third (38.4%) were at high nutrition risk. Previously, Schilp et al. (2012) identified 7.7% of older Dutch community dwelling people were at nutrition risk using SNAQ65+-criteria. The discrepancy in nutrition risk prevalence may be due to differences in measures employed by the screening tools. The SNAQ65+ was validated by 6/15 year-mortality risk (20) and the SCREEN II is validated against the criterion of a dietitians clinical judgement of risk (Keller et al. 2005). The AUC (‘area under the curve’) of the SNAQ65+ was overall poor (55%) because people die of various other reasons than undernutrition (20). The AUC for SCREEN II was 82% and has been shown to have high inter-rater and test-retest reliability as well as excellent sensitivity and specificity in detecting malnutrition (19). The SCREEN II tool has also been identified to be more suitable for use in community dwelling older people compared to the SNAQ in general (21).

Nutrition risk items such as low intakes of meat and alternatives), milk products fruit and vegetables and eating alone found in the present study, are commonly occurring risk factors (17, 22).  Low intake of fruit and vegetables and milk products has previously been reported in the Dutch National Food Consumption Survey Older Adults 70+ 2010-2012. Also, the survey concluded that Dutch older people (mean age 77.5) consumed less meat compared to people in their fifties or sixties (23). Meat and milk products provide over half (53%) of the dietary protein for Dutch older people. Dietary protein is important for preserving bone and muscle mass in older adults (24).

Half (50.8%) of older people who received home care in Woerden, were at high nutrition risk. Similarly using the MNA (Mini Nutritional Assessment) other European studies, from Finland and Germany, reported half of older people receiving home care were at nutrition risk (25, 26). Home care is indicated for people who have a functional disability (27).  People with functional disabilities have an increased risk of undernutrition and the dietary intake of energy protein and vegetables may be lower than those without impaired function (23). A low intake of major food group items in those with and without home care in this study suggests those living in the community need to be screened for nutrition risk and provided with appropriate nutrition support. 

In this study people who lived alone and received home care were the most nutritionally vulnerable and are an easily identifiable group. Using SCREEN II, previous studies also indicate that living alone is associated with nutrition risk among older people in Canada (28), Sweden (29) and  New Zealand (17, 30). Older people living alone usually eat less than those who have the opportunity to share their meals (31).

The cross sectional design of this study does not allow us to comment on causality in factors related to nutrition risk and the findings should be interpreted cautiously. The participants involved in this study were representative of the population in Woerden on the basis of age, gender and living situation. Therefore, the findings are indicative of the nutritional risk status among older people in communities within The Netherlands. The validity of the SCREENII tool might be questionable from translation to Dutch. Although the tool was checked for comprehension, it is recommended that the SCREENII tool is validated for Dutch older people. As the SCREENII tool is suitable for self-administration and identifies nutrition risk factors screening for nutrition risk in community living older people could be cost-effective. The Dutch government has invested in a in a four-year program called ‘Visible link’, for employment of home care staff in order to keep older people living at home (32, 33). If the prevalence of nutrition risk remains unchanged, the absolute numbers of undernutrition in Dutch older people who receive home care will increase. The development of an intervention to prevent nutrition risk through home care staff could be effective to diminish nutrition risk.  Another possibility is implementation of a digital version of SCREEN II, an intervention already active in Canada, known as Nutri-eScreen© (34). This e-version of the nutrition questionnaire provides feedback on which risk factor items are in need for improvement and could be very useful for older people and their carers for early identification of nutrition risk. 

This study concludes that there are relatively high levels of nutrition risk among older community dwelling Dutch people aged 75 to 85 years living in Woerden. A low intake of essential food groups have been identified as important risk factors items.  In order to maintain the independence of the older population it is recommended that older people are screened regularly for nutrition risk and, where necessary, effective nutrition intervention is provided.

 

Acknowledgements and funding: Not applicable. No funding, no acknowledgements.

Conflict of interest: The authors declare no financial conflicts of interest.

 

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