Associations between socio-demographics, nutrition knowledge, nutrition competencies and attitudes in community-dwelling older adults in Singapore: Findings from the SHIELD study

Objectives Nutrition literacy refers to an individual’s knowledge, motivation and competencies to access, process, and understand nutrition information needed to make appropriate nutrition-related decisions. It is known to influence dietary habits of older adults. This cross-sectional study was designed to: (1) understand the nutrition knowledge, competencies and attitudes of community-dwelling older adults in Singapore (2) examine the differences between their nutrition knowledge, and socio-demographic factors, competencies and attitudes, and (3) identify factors associated with better nutrition knowledge in community-dwelling older adults in Singapore. Methods 400 (183 males and 217 females) nourished community-dwelling older adults aged 65 years and above took part in this study. Malnutrition Universal Screening Tool (MUST) was used to determine individuals who were at low risk of undernutrition. Nutrition knowledge, competencies, attitudes and sources of nutrition information were measured using a locally developed scale. Nutrition knowledge scores were summed to form the Nutrition Knowledge Index (NKI). Associations between NKI, competencies, attitudes and socio-demographic variables were examined using Chi-square and Fisher’s Exact tests. Factors associated with NKI were determined using a stepwise regression model with resampling based methods for model averaging. Results Bivariate analyses found significant differences in NKI scores for gender, monthly household earnings, type of housing, the self-reported ability to seek and understand nutrition information and having access to help from family/friends. Females had higher NKI scores compared to males ( p < 0.001). Compared to females, more males left food decisions to others ( p < 0.001), and fewer males reported consuming home cooked food ( p = 0.016). Differences in educational level were found for competencies like the self-reported ability to seek ( p < 0.001) and verify nutrition information ( p < 0.001).

Stepwise regression analysis showed that being female, Chinese, self-reported ability to understand nutrition information and having access to help from family/friends were associated with higher NKI scores.
Conclusions Our study revealed that nutrition knowledge of older males in Singapore was lower than females and more left food decisions to others. Hence, nutrition education programs could be targeted at both the older male and their caregivers.

Background
Singapore is a multi-ethnic urban city state with the second-fastest aging population in Asia (1). The proportion of older adults in Singapore aged 65 years and above has increased from 8.8% in 2008 to 14.4% in 2019 (2). In Singapore, about 30% of communitydwelling older adults aged 55 years and above were at risk of poor nutritional status (3).
For older adults, it is well recognized that poor nutrition is associated with adverse clinical and functional outcomes like physical frailty, higher mortality, longer inpatient stays and increased intensive care need (4)(5)(6)(7).
Nutrition literacy is a subset of health literacy (8). It is defined as the extent to which individuals are able to attain, assess, and understand basic nutrition information required to make appropriate nutrition-related decisions (8,9). Key elements of nutrition literacy include nutrition knowledge, competencies and attitudes (10).
Although associations between nutrition literacy and health related outcomes have not been established in existing literature, studies have shown that elements of nutrition literacy can influence dietary habits. Wardle and colleagues reported that nutrition knowledge plays a pivotal role in healthy dietary habits, and partially mediates sociodemographic variations in dietary intakes (11). A recent meta-analysis reported a significant, albeit weak positive association between nutrition knowledge and healthy eating (12). It is also well recognized that healthy eating in older adults is multi-faceted and shaped by both individual and collective factors (13)(14)(15)(16)(17). An individual's competency in obtaining, understanding nutrition information, and knowing how to access nutrition health services have an impact on the nutrition knowledge of the individual. Studies have reported that the lack of aforementioned skills may contribute to poor nutrition health (10,18). Nutrition attitudes is centered on the perceptions and beliefs influencing food choices (13,14), mediating the link between nutrition knowledge and dietary habits (19). A systematic review reported associations between better nutrition knowledge, positive dietary attitudes and healthy dietary habits (20). This is supported by more recent research noting similar associations within Asian and Western older adults (14,21).
Socio-demographic factors such as higher educational qualification, were associated with better nutrition knowledge (22), and positive nutrition attitudes in older adults (14,23).
Gender differences were also reported to be associated with nutrition knowledge, with some studies reporting older adult females having higher nutrition knowledge scores than males (24,25), and other studies noting the opposite (14,22).
There are several published instruments in existing literature which measure levels of nutrition knowledge, competencies and attitudes of participants. However, these instruments vary widely and were mostly either developed for Caucasians or validated in a predominantly Caucasian population (26). This is important as there is a cultural aspect to nutrition literacy and behaviour (10,27,28). Given the cultural diversity of the Asian population, it is important to develop instruments that are tailored to each culture and group. Aihara and Minai had previously developed a nutrition literacy instrument for older Japanese people (24), however, items were based on dietary guidelines specific to Japan.
The nutrition knowledge, attitudes and behavior scale in Taiwan's Elderly Nutrition and Health Survey consisted of questions on Chinese traditional beliefs on food ("heaty" or "cooling") and food-texture (14), which might not be applicable to older adults of different ethnicities. There is no instrument that is currently relevant for Singapore's multi-ethnic population; hence, the nutrition literacy questionnaire (NLQ) was developed for the purpose of this study.
To design nutrition interventions for older adults, it is crucial to understand their current levels of nutrition knowledge, attitudes and competencies gaps and to understand factors associated with nutrition knowledge. However, there is a dearth of local studies that examine the nutrition knowledge of older adults. Hence, the aims of this study are to: (1) understand the nutrition knowledge, competencies and attitudes of community-dwelling older adults in Singapore (2) examine the associations between nutrition knowledge, and socio-demographic factors, competencies (e.g. ability to obtain and understand information on nutrition) and attitudes, and (3) identify factors associated with better nutrition knowledge.

Participants
Data was collected as part of the Strengthening Health In ELDerly through nutrition (SHIELD) study. In this cross-sectional study, we analysed a subgroup of older adults (N = 400) recruited between September 2017 and January 2018 from four study sites located in the eastern part of Singapore, namely Changi General Hospital (CGH), Bedok Polyclinic, Marine Parade Polyclinic, and Tampines Polyclinic. Participants were eligible for this study if they met the following criteria: aged 65 years and above, Malnutrition Universal Screening Tool (MUST) score was 0, a community dweller, community ambulant with or without aid, able to communicate and follow instructions, and with or without any stable chronic disease(s), which is defined as a controlled disease state (29). Participants were ineligible for the study if they were diagnosed with any of the following: type 1 or type 2

Measures
Nutritional status of participants was assessed by trained study personnel using the Malnutrition Universal Screening Tool (MUST) (30). The MUST consists of three main scoring components, namely body mass index (BMI), recent unplanned weight loss, and effects of acute disease. Low risk of undernutrition was defined as MUST score = 0 (31,32). BMI was calculated to the nearest 0.1 kg/m 2 . Height was measured to the nearest 0.01 m, and weight was measured to the nearest 0.1 kg using a weight and height machine (Avamech B1000) calibrated according to the manufacturer's specifications.
Information on medical history, socio-demographics (i.e., age, sex, ethnicity, education, marital status, living arrangements, residential type, and financial situation), and lifestyle (i.e., smoking, alcohol consumption) of the participants were also collected via selfadministered questionnaires. Age was categorized into < 75 or ≥ 75 years. Education was categorized into primary, secondary, pre-university, and university and above. Information on physical health was obtained through the Charlson Comorbidity Index (CCI) (33) and Modified Barthel Index (MBI) instruments (34).

Nutrition Knowledge, Competencies and Attitudes
The NLQ was developed using evidence from published literature, nutritional knowledge materials published by the local health promotion agency (35) and expert inputs. The instrument was piloted and tested among some of Dietitians and found to be acceptable and able to capture the nutrition literacy level of older adults. The instrument was then translated and back translated into Chinese and Malay, the two other most commonly used languages in Singapore.
The NLQ consisted of three main components namely nutrition knowledge, competencies, and attitudes. Sources of nutrition information and factors influencing food choices were also collected and analysed separately. Firstly, nutrition knowledge of participants was assessed based on their knowledge of local nutritional recommendations outlined in The Recipe For Healthy Ageing: Nutrition Guide (35). There were 7 multiple choice questions, each question had three possible answers to choose from, and there was only one correct answer. Questions covered food groups and recommended portion sizes. A score of 1 was assigned for a correct response and 0 for otherwise. Scores were summed to form the Nutrition Knowledge Index (NKI). Total scores ranged from 0 to 7, with higher scores indicating better knowledge level. Secondly, nutrition competencies of participants were assessed using 9 binary questions. For example, "Do you know where to go to find information about nutrition? (Yes/No)". Thirdly, nutrition attitudes of participants were measured using 4 statements (e.g. "It is not important to eat nutritious meals at my age") related to their dietary habits and the participants were asked to rate each of these statements on a four-point Likert scale (4 = Strongly Agree, 3 = Agree, 2 = Disagree, 1 = Strongly Disagree). Participants could choose more than one option(s) for sources of nutrition information and factors influencing their food choices.

Statistical analysis
All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA), and significance level was set at 0.05. The responses on the Likert scale were also re-categorized. "Strongly agree" and "Agree" were categorised together as "Agree", while "Strongly disagree" and "Disagree" were categorised together as "Disagree". The option "Refused to answer/don't know" for monthly household earnings (SGD) was excluded from analyses. Chi-square and where appropriate, Fisher's exact tests were used for tests of associations between nutrition knowledge, competencies, attitudes and socio-demographic factors. Stepwise multiple linear regression modeling was used to examine the factors associated with the nutrition knowledge index. Bivariate analyses results were taken into consideration together with literature in this area for variables selection. Model inputs consisted of 20 potential variables (gender, ethnicity, education level, marital status, living arrangements, caregiving arrangements, residences type, NLQ questions on competencies and attitudes). Resampling based methods for model averaging were used to mitigate for known limitations of stepwise selection including selection bias in parameter estimates and reliance on a single best model (36).

Participant Characteristics
The demographic profile of the study sample is shown in Table 1. Of the 400 participants, 217 (54.2%) were females. Majority were married (74.2%), of Chinese ethnicity (83.0%), and had education levels of secondary level and above (84.5%) with a mean age of 71.2 years. Majority were independent according to MBI (93.0%) and a Charlson Comorbidity score of 0 (98.0%). [Insert Table 2 here] Table 3 shows nutrition knowledge index by socio-demographic factors, competencies and attitudes. A higher nutrition index was noted for females, those who reported and average household earnings of less than SGD$2,000, individuals who lived in private properties.
For nutrition related competencies, a higher NKI score was noted for individuals who selfreported an ability to seek nutrition information (p = 0.011), understood nutrition information (p = 0.008), did not leave food decisions to others (p = 0.012), had access to help from family or friends (p = 0.009), and did not consume simpler meals when alone/ or only with spouse (p = 0.016).
[Insert Table 3 Here] Table 4 shows the associations of sociodemographic factors with competencies and attitudes. Compared to those with primary level education or below, more individuals with higher educational qualification reported having ability to seek (p < 0.001) and verify nutrition information (p < 0.001). Compared to currently married individuals, those who were single were less likely to report leaving food decisions to others (p = 0.002) Compared to those who lived alone, those who were living with others were more likely to report leaving food decisions to others (p = 0.004). In terms of caregiving arrangements, for older adults who reported self-caregiving, majority (81.0%) made their own food decisions and was able to access healthcare services (94.0%). However, they reported lower rates of consuming home-cooked food compared to those who were cared for by family or others (p = 0.011).
The results of the stepwise regression are shown in Table 5, it was observed that being female (p < 0.001), of Chinese ethnicity (p = 0.026), self-reported ability to understand nutrition information (p = 0.035), and having access to help from family/friends (p = 0.051) was associated with higher NKI.

Discussion
To the best of our knowledge, this is the first study of its kind to examine the nutrition knowledge, competencies and attitudes amongst relatively healthy Singapore older adults, and the results might be useful for guiding nutrition strategies in the population.
Though some studies have been conducted on nutrition literacy among Asian older adults (14,24), their instruments were specially designed for their respective local populations.
Thus, it is difficult to compare the nutrition literacy levels of our participants with that of other studies. We found nutrition knowledge and other aspects of nutrition competencies and attitudes (such as responsibility of food decisions, consumption of home-cooked meals, and consumption of simpler meals when alone/with spouse) differ significantly between the genders. Education might have a role in the ability of older adults to seek and verify nutrition information while caregiving arrangements might have an influence on the responsibility of food decisions and consumption of home-cooked meals among the study population. Moreover, higher nutrition knowledge index is found to be associated with being female, of Chinese ethnicity, self-reported ability to understand nutritional information, and having access to help from family/friends.
Males were found to have a lower nutrition knowledge index. They were also more likely to leave food decisions to others, less likely to consume home-cooked meals, and more likely to consume simpler meals when alone/with spouse. These suggest that more support might need to be offered to older male adults to improve their nutrition knowledge so that they are able to make appropriate food choices, especially when they are dining out. On the other hand, it remains unclear why males prefer to leave food decisions to others and this could potentially be explored as a future research study.
Education is known to contribute to an individual's ability to better understand, and remember different information (37), and educated adults were suggested to be more motivated and interested in nutritional health (13,23). This is in line with our bivariate analyses which showed that older adults with higher education levels had a higher proportion with the self-reported ability to seek and verify nutrition related information compared to those with primary education levels. The current study did not find an association between age and nutrition knowledge index. Previous studies on older adults noted that nutrition knowledge decreased as age increased (13,14,38 (24,25). This could be due to females taking on more domestic responsibilities, including meal preparation and food choices (40), and are thus more likely to be familiar with nutrition related information. It is also important to note the self-reported ability to understand nutrition information and having access to family and friends for help are contributing factors to the learning and encoding of nutrition knowledge, and therefore yielding a higher nutrition knowledge index. Nutritional educational programs which offer small incremental blocks of information content was suggested to booster learning and maximize retention of nutrition among adults (41).
Such an approach may be useful in designing of the nutrition strategies to mitigate agerelated declines in comprehension amongst older learners. The role that social networks play in the nutritional well-being of older adults has been well established in literature (42)(43)(44). In this study, about 14-20% of older adults reported obtaining their nutrition information through their social networks. This highlights the importance of social and community aspects when designing nutrition strategies.

Sources of Nutrition Information
Understanding the sources for nutrition information among the older population is crucial in developing nutrition educational outreach methods. Studies on Asian older adults have found television to be one of the most commonly cited resource of nutritional information, which range from 49.7-79.8%, followed by printed materials, social networks and health professionals (14,24). Internet was not included as an option in these studies and hence it is difficult to establish the proportion of older adults who considered the internet as a source. Similarly, our study reported television (40.0%) as one of the most common sources of information, followed by printed materials like newspapers (39.3%). Our study's reported proportion of internet as a source of information was higher compared to recent studies done in Midwest US on older adults aged 60 years and above (0.4%) (46) and in Australia older adults aged 65 years and above (19.0%) (47). This could be due to the higher education levels and socioeconomic status seen in our participants compared to Singapore's general population aged 65 years and above.

Limitations
There are four limitations in this study. Firstly, the participants in this study were relatively healthy and educated with normal nutritional status (MUST = 0). Caution should be taken when generalizing these results to other older population groups. Secondly, the cross-sectional design means that causal relationship between nutrition knowledge, competencies, attitudes, and factors associated with them could not be established.
Future studies are needed to understand and confirm the associations in this study.

Consent for publication
Not applicable.

Availability of data and materials
The datasets from this current study are available from the corresponding author on reasonable request.

Competing interests
WX, GB, DTTH and SLT are employees of Abbott Nutrition. STHC reports receiving honoraria for speaking engagement and travel grant from Abbott. All other authors have declared that no competing interests.

Funding
The SHIELD study is supported by the Singapore Economic Development Board (EDB), Changi General Hospital and Abbott Nutrition.     Sources of Nutrition information