Background
The current life expectancy at birth (81.7 years) for New Zealand is among the top life expectancies within the Organisation for Economic Co-operation and Development countries [
1]. This raises the issue of whether efficient strategies have been put in place to ensure this growth in life expectancy will go along with good quality of life [
2,
3]. Since ageing is a well-documented risk factor for hospitalisation [
4‐
6], there is great need to come up with strategies that help older people to continue living healthily in the community. Although ageing is inexorable, several factors contributing to hospital admission in older adults can be modified, for example, nutrition status. Despite being well documented as a preventable condition, hospital malnutrition is highly prevalent among older adults (20–60%) [
7‐
9]. It remains unclear whether malnutrition occurs before or after admission since at hospital admission, nutrition screening is not mandatory and is conducted infrequently [
10‐
12].
Malnutrition is preceded by a state of malnutrition risk thus nutrition risk screening may identify those who show nutritional compromise before they reach a state of malnutrition, enabling intervention and prevention. Although several international studies assessed malnutrition risk at hospital admission [
13‐
21], the wide range of malnutrition risk prevalence (15–78%) observed from these studies raises questions. Differences in methodology used to assess malnutrition risk may partly explain the reported discrepancies. Several methods of malnutrition risk screening have been established and the choice of method used should consider participants age and setting [
22,
23]. The Mini Nutritional Assessment Short-Form, (MNA®-SF) is a validated tool for assessment of malnutrition risk in older adults in multiple settings, including the hospital [
24]. The MNA®-SF is used globally and has a sensitivity of 89% and specificity of 82% for assessing malnutrition risk in older adults [
22,
25].
Studies suggest that malnutrition risk factors are multidimensional. These include sociodemographic (e.g. age, gender, living arrangements and employment status), psychological (e.g. individuals’ thoughts and feelings), and health status (e.g. functional ability, presence of comorbidities, polypharmacy, impaired chewing and swallowing) [
26‐
30]. Understanding these factors may be helpful for identifying those at malnutrition risk and providing timely preventative interventions. Levels of cognitive impairment often increase with ageing [
31], and have the potential to influence nutrition status. Previous studies have reported positive associations between satisfactory dietary intake and better cognition [
32]. Furthermore, older adults are more vulnerable to dysphagia (swallowing difficulties) [
33], which can lead to malnutrition through decline in food intake. Among healthy community-dwelling older adults, a positive correlation between posterior tongue strength (swallowing strength) and hand grip strength (a measure of muscle strength) was observed [
34]. This suggests that loss of muscle strength at one site e.g. hand grip, may be indicative of weakness at other sites e.g. oral cavity. To date, there is limited literature supporting a strong association between tongue strengthening and swallow outcomes. However, among older adults in long term care, reduced tongue strength was found to be associated with observable signs of swallowing difficulty and reduced food consumption [
35]. Therefore, exploring associations between muscle strength, dysphagia and malnutrition appears warranted.
In New Zealand, malnutrition risk screening is not mandatory and knowledge of prevalence of malnutrition in older adults is lacking. Using the MNA®-SF, the aim of the current study was to investigate the magnitude and potential predictors of malnutrition risk in older adults, at hospital admission.
Discussion
This is the first study in New Zealand to assess prevalence and predictors of malnutrition risk in older adults at hospital admission. Almost three-quarters were either malnourished (26.9%) or at malnutrition risk (46.6%), congruent with previously published international findings (15–78%) [
13‐
21]. Dysphagia risk, low BMI, decreased muscle strength and cognitive decline, were identified as statistically significant predictors of malnutrition risk, at hospital admission. As 88% of participants were admitted from the community, this suggests that the high prevalence of hospital malnutrition may be a result of unrecognised community malnutrition; hence routine screening is essential on hospital admission. Furthermore, it suggests that community based assessment and intervention may be important for identifying at-risk adults and providing early supportive measures.
The prevalence of malnutrition (26.9%) observed in this study is congruent with previously reported hospital malnutrition prevalence (20–60%) internationally [
7‐
9]. This suggests that both malnutrition risk and malnutrition are present in older adults prior to hospital admission. This study is an extension of our pilot investigation that reported malnutrition risk prevalence in adults (
n = 88) of advanced age (85+ years), wherein a similar prevalence of malnutrition risk was observed [
46]. Previously, malnutrition has been identified in New Zealand older adults (
n = 55) hospitalised for hip fracture; where 42% were found to have at least two indices of protein energy malnutrition as evidenced by low triceps skinfold thickness, reduced mid-upper arm circumference, and low serum pre-albumin [
47]. Moreover, using the MNA®-SF, a New Zealand hospital audit of older adults (
n = 72) found 24% were malnourished and 44% were at nutrition risk [
48]. The insights from the aforementioned reports and findings from our study suggest the need for routine screening at hospital admission in New Zealand.
Previous studies reported chewing and swallowing problems as common phenomena in older people, which may lead to decline in food intake [
49‐
51]. Reduced food intake is one of the main causes of malnutrition. Thus, understanding both dental status and dysphagia risk may be helpful in devising strategies intended to prevent malnutrition. In contrast to previous studies [
52,
53], no significant association between dental status and malnutrition risk status was observed in the current study. However, as expected, we observed that with increasing risk of dysphagia (increasing EAT-10 scores), the prevalence ratio of malnutrition risk also increased. This concurs with findings of a previous study that assessed the association between swallowing difficulties and hospital malnutrition [
28]. In the current study, 22% of the participants demonstrated EAT-10 scores ≥3 which suggests that in older people who are malnourished or at malnutrition risk, consideration of swallow assessment would be prudent. This may identify contributory problems and define treatment targets. Furthermore, for treatment of malnutrition, it may be helpful if future studies investigate the clinically relevant cut-off points for the EAT-10 associated with malnutrition risk, since an EAT-10 score ≥ 3 is merely suggestive of dysphagia [
39].
Greater muscle strength as indicated by greater hand grip strength was associated with lower malnutrition risk. Similar findings were observed in an Australian study that explored the potential of hand grip strength to independently predict nutrition status in a hospital population [
54]. A Canadian study that assessed malnutrition at hospital admission observed hand grip strength to be an independent factor associated with hospital stay [
14]. Several factors explain the occurrence of poor muscle strength in older adults and how they may create a vicious cycle resulting in malnutrition. Reduced physical activity and functional decline commonly observed in older adults contribute to muscle atrophy and poor muscle strength [
55‐
57]. In addition, malnutrition promotes body weight loss (low BMI), particularly muscle mass loss, including the deglutitive muscles, which consequently increases swallowing problems and hence malnutrition risk [
58,
59].
Muscle weakness and low BMI often occur together in undernourished people [
60,
61]. Our study supports this association, as a positive correlation (
r = 0.236,
p < 0.046) between BMI and muscle strength was observed. BMI is an integral part of the MNA®-SF and in older adults high BMI values are associated with low malnutrition risk [
28,
62], better functional status [
63] and may be protective against mortality [
62,
64,
65]. Accordingly, a BMI ≥23kg/m
2 has been proposed as the healthy cut-off point for older adults [
45]. In the current study, 41% of the participants had a BMI < 23 kg/m
2 which may explain the high prevalence of malnutrition risk observed.
Two-thirds of participants required daily help with various tasks such as cooking, cleaning, showering and dressing. This may suggest loss of physical function among these participants which may contribute to the low muscle strength and high malnutrition risk observed. Previous studies reported that malnutrition risk is higher in older adults who rely on others for assistance with daily activities like grocery shopping and cooking [
8,
14,
26]. Although not statistically significant (
p = 0.061), our data demonstrated an increased risk of malnutrition among older adults who required help with ADL. Whether this incremental decrease in nutrition status can be detected clinically is not clear from this study.
Medications and comorbidities are well documented factors associated with malnutrition [
8,
26]. In the current study, on average each participant had six comorbidities and was taking seven medications. Although these factors were not significantly associated with malnutrition risk in this study, they may contribute to decreased physical activity, decline in muscle mass and consequently poor muscle strength. These factors negatively influence malnutrition risk [
58,
59]. Two-thirds (65%) of the participants did not take any nutritional supplements and among those who took supplements, on average only one supplement was taken. This may explain why taking nutrition supplements did not impact malnutrition risk. A recent study in New Zealand observed low micronutrient intake in older adults and noted that with some of the micronutrients, those who took nutritional supplements were less likely to be nutrient deficient [
66]. Further education in this area may assist older adults in determining whether supplementation is appropriate.
In agreement with previous studies [
26], malnutrition risk was associated with decline in cognitive status. Cognitive impairment is associated loss of independence which may negatively affect older adults’ lifestyle, specifically food intake and physical activity. Malnutrition and cognitive impairment have been reported as predictors of all-cause mortality among hospitalised adults (> 70 years) [
67]. In the current study, 62% of the participants indicated some level of cognitive impairment (MoCA score ≤ 26). Although about a quarter of the participants declined taking the MoCA test, the high prevalence of cognitive impairment among the test takers suggests the importance of performing cognitive assessments in older adults.
The strengths of this study include the use of validated screening tool MNA®-SF and the use of a critical time point for data collection i.e. at hospital admission. These factors enable understanding of malnutrition risk in older New Zealanders at hospital admission, which provides helpful insights towards promoting good nutritional status not only during hospitalisation but also prior in the community and after discharge. However, the use of an observational study design hinders us from determining causality. Additionally, investigations were done using a convenience sample (n = 234), which limits generalisability of the findings. Hand grip strength and cognitive status assessments were undertaken with about three-quarters of the participants, therefore interpretation of these results should be made with caution, as the missing data may have introduced bias in our findings. Overall, the participants had low MoCA scores which may have influenced the malnutrition risk outcome, since some of the MNA®SF items rely on memory. Due to poor physical strength and/or presence of metals in the body, only 16 participants completed muscle mass measurement using bio-impedance analysis scale, thus we could not report muscle mass findings. As significant changes in body composition occur with ageing, inability to assess muscle mass in this study limited our ability to understand the impact of body composition on malnutrition risk. To understand participants’ general health status, the current study recorded comorbidities and medications taken. However, the study did not capture reason for admission, which would have helped clarify participants’ health upon admission.