Abstract
Background:
Lunch clubs are community-based projects where meals are offered with opportunities for social interaction, and a unique dining experience of dual commercial and communal nature.
Aim:
The aim of the present cross-sectional study was to assess differences in the dietary intake between lunch club and non-lunch club days among community-dwelling elderly, living in Dorset, UK.
Methods:
A total of 39 elderly individuals attending local lunch clubs were recruited. Socioeconomic factors were recorded, anthropometric measurements were taken and the dietary intake was assessed in lunch club and non-lunch club days via 24 hour dietary recalls.
Results:
For the majority of participants, having a hot meal (74.4%), meeting with friends (92.3%), dining outside home (76.9%), having a home-styled cooked meal (71.8%) and skipping cooking (43.6%) were considered as important factors for lunch club dining. Absolute energy intake, protein, fat, carbohydrate, saturated fatty acids, fibre, potassium, calcium, iron, vitamins A, C and folate and water from drinks were significantly greater on lunch club days. When intake was expressed as a percentage of the dietary reference values, all examined nutrients were consumed in greater adequacy during lunch club days, except potassium and vitamin D.
Conclusions:
Lunch clubs appear to be an effective means for ameliorating nutrient intake among older adults, while in parallel, offer the opportunity for socializing and sharing a hot meal with peers.
Keywords: Dietary survey, older people, ageing, social dining, community meals, cooked hot meal
Introduction
During the last decades, the elderly population has grown faster than any other age group (Stokes and Preston, 2013). With increased morbidity characterizing older age (Kingston et al., 2018; Shlisky et al., 2017), this substantial increase in longevity is hallmarked by a need to promote healthier ageing (Grammatikopoulou et al., 2019; Marsman et al., 2018). On the other hand, nutritional status, and in particular malnutrition, appears to be a pivotal health effector among the elderly, triggering the development of several health issues (Shlisky et al., 2017), while in parallel, increasing mortality risk.
A high proportion of elderly individuals are malnourished (Grammatikopoulou et al., 2019), mainly as a result of altered nutritional needs, decreased appetite, chewing problems, sensory decline, food insecurity, social isolation and poor psychological health (Agarwal et al., 2013; Clegg and Williams, 2018; Feldblum et al., 2007; Grammatikopoulou et al., 2012). Therefore, developing effective interventions to tackle malnutrition among older adults is an important public health priority. Community-based projects such as lunch clubs are a fairly recent approach in the UK and other countries (Brunet, 1987). Lunch clubs are community places where meals are offered in a social setting such as a day centre, or a village hall. They are delivered by community, faith or charitable groups, meeting on average once a week and recruiting participants via word of mouth, advertising or referral from health and social care professionals. Apart from a healthy meal, lunch clubs also offer opportunities for social interaction, and a unique dining experience of dual commercial and communal nature (Thomas and Emond, 2017).
Lunch clubs can allow commnesality and in this way the psychology of the elderly and their feelings of happiness can be improved (Yiengprugsawan et al., 2015; Thomas and Emond, 2017); however we lack data concerning the effects of luch clubs on dietary intake of older adults. Limited research suggests that regular attendance of lunch clubs can increase compliance with the recommendations for key nutrient intake, including calcium, iron, folate and vitamin D (Burke et al., 2011). Given that elderly malnutrition is also associated with lower income tiers (Donini et al., 2013), lunch clubs could also serve as a means for improving dietary intake. Based on this hypothesis, the present pilot cross-sectional study was designed, aiming to compare dietary intake between lunch club and non-lunch club days, among elderly people in the UK.
Methods
The present cross-sectional study was carried out at lunch clubs in Dorset, UK, between November 2015 and January 2016. Lunch clubs with a target audience of attendees over 65 years old were approached with details of the study. Once agreed, a mutually convenient date was arranged for the researcher to visit on the day of a lunch. Five lunch clubs in total were visited in the Dorset area. Participants were recruited from these clubs on a convenience sampling basis, with the only criteria being (a) age greater than 65 years old; (b) attending a lunch club at least once per week; (c) being able to communicate effectively in the English language; and (d) willing to participate. In further detail, 10 older adults were recruited from Briantspuddle, 12 from Wareham Parish Hall, six from the United Reform Church, five from the Gateway Church and seven from the Church Knowle. A total of 40 participants were recruited, but the final sample included 39 elderly with complete data. All participants were provided with an information letter, a consent form and a questionnaire, making it clear that they could withdraw at any point. The study was approved by Bournemouth's University Ethics Committee, ethics checklist ID 11511. Written informed consent was obtained from all participants prior to participation. The study followed the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines for cross-sectional studies (Supplementary file).
The questionnaire was designed specifically for this project and standardized with pilot testing to be used in more than one location. It was piloted twice on three older adults who were willing to take part in the preliminary phase of the questionnaire’s development. Subsequently, modifications were performed including transposing all responses into a Likert scale or closed-question tick boxes with an additional option for those opting for exclusion from the answer, for increased ease and accuracy. Questions included length and frequency of lunch club attendance, meal enjoyment, reasons for attending and participants’ perceived influence of dining in the clubs on their dietary habits.
Anthropometric measurements included height, weight, waist circumference and hand grip strength. Due to the season (winter) and the variety of participants’ mobility issues, it was safer to complete the weight and height measurements with shoes and one layer of top clothing on. Additionally, body mass index (BMI) was calculated and body fat, as a percentage of body weight, was estimated with the Lean et al. (1996) method.
Self-reported food intake was assessed using three 24 hour dietary recalls. This was taken on the day of the interview (including their breakfast, lunch club meal and what they anticipated eating for the rest of the day) and two recent days that they were not at a lunch club. Validity of self-reporting has been suggested to decrease with age (Ortiz-Andrellucchi et al., 2009) due to memory loss, impairments such as hearing difficulties, and with the overweight elderly tending towards under-reporting energy and unhealthy food (Cade and Hutchinson, 2015). In order to obtain as much accuracy as possible, several measures were taken. To aid dietary recall, the researcher led recovery of missed food items and preparation methods by providing assistance with writing, particularly in the case of hearing or sight problems. In further detail, a structured dietary recall was used to provide helpful prompts, in addition to visual aids, similar in size and shape to anticipated portions of a ruler, to better estimate solid foods. These props were consistent at all clubs and helped to refine estimations of portion sizes.
NetWisp version 4.0 dietary software (Tinuviel Software Ltd, UK) was used to analyse the 39 completed dietary recalls. Micronutrient intake was compared to the dietary reference values (DRVs) (Department of Health, 1991), while the energy and carbohydrate intake were compared to the estimated average requirements (EAR) (Scientific Advisory Committee on Nutrition, 2011, 2015) and water from drinks was based on the British Dietetic Association guidelines (British Dietetic Association, 2017).
Data is presented as means ± standard deviations (SD) for normally distributed variables or medians with their interquartile range (IQR) for non-normal variables and frequencies/percentages for categorical variables. Normality was assessed with the Shapiro-Wilk test. Independent t-tests assessed differences in age and anthropometric characteristics between the genders. Fisher’s exact test was used to compare categorical variables. Differences in nutrient intake between lunch club and non-lunch club days were assessed with paired t-test or Wilcoxon signed rank tests when the assumption of normality was violated. Multivariable linear regression models tested the relationship among the difference (Δ) in nutrient intake between lunch club and non-lunch club days (dependent variables) and male sex, age (continuous) and being married (independent variables), and were adjusted for non-lunch club days’ nutrients (continuous) (regression to the mean) (Barnett et al., 2004). All analyses were conducted on SPSS version 23.0 (IBM, SPSS Inc., Chicago, IL, USA) and STATA 12.0 (Stata Corp., College Station, Texas, USA), and the significance level was set at α=0.05.
Results
The sample comprised 39 individuals with a mean age of 82.1 (SD 8.2) years, and no difference in the gender distribution (43.6% male; 56.4% female; P=0.423). Overall, participants were overweight (BMI 27.4; SD 4.3; kg/m2), abdominally obese (waist circumference 100.2; SD 12.7; cm), with low hand-grip strength (18.0; SD 6.4; kg). Table 1 stresses the sample’s characteristics and between-gender tests of differences. Men were taller and heavier than women (P=0.006 and P<0.001), and demonstrated a stronger hand grip strength (P<0.001); however, the two genders did not differ in BMI, waist circumference, or body fat (all P>0.05).
Table 1.
Participants’ characteristics of older people attending lunch clubs (mean ± SD, or n and %).
| All (N=39) |
Males (n=17) |
Females (n=22) |
Significancea | |
|---|---|---|---|---|
| Age (years) | 82.1±8.2 | 81.1±7.5 | 82.9± 8.8 | 0.504 |
| Anthropometrics: | ||||
| Body weight (BW) (kg) | 72.8±13.8 | 79.5±12.5 | 67.6±12.6 | 0.006 |
| Height (cm) | 162.9±9.9 | 171.2±5.8 | 156.4±7.2 | <0.001 |
| Body mass index (kg/m2) | 27.4± 4.3 | 27.2±4.7 | 27.5±4.1 | 0.836 |
| Waist circumference (cm) | 100.2± 12.7 | 104.6±12.6 | 96.8±12.1 | 0.057 |
| Body fat (% BW) | 44.6±10.2 | 46.2±11.1 | 43.3±9.5 | 0.384 |
| Hand grip strength (kg) | 18.0±6.4 | 22.9±4.8 | 14.2±4.6 | <0.001 |
| Marital status: | ||||
| Married | 8 (20.5%) | 5 (29.4%) | 3 (13.6%) | 0.261 |
| Other (single/divorced/windowed) | 31 (79.5%) | 12 (70.6%) | 19 (86.4%) | |
| Living arrangements: | ||||
| Alone | 25 (64.1%) | 9 (52.9%) | 16 (72.7%) | 0.314 |
| With one or more adultsb | 14 (35.9%) | 8 (47.1%) | 6 (27.3%) | |
| Retirement status: | ||||
| Pension/savings/benefits | 37 (94.9%) | 15 (88.2%) | 22 (100%) | 0.184 |
| Work income | 2 (5.1%) | 2 (11.8%) | 0 (0%) | |
| Transportation means: | ||||
| By vehicle | 25 (64.1%) | 10 (58.8%) | 15 (68.2%) | 0.738 |
| On foot | 14 (35.9%) | 7 (41.2%) | 7 (31.8%) | |
| Residential proximity to the lunch club: | ||||
| Less than 1 mile | 28 (71.8%) | 13 (76.5%) | 15 (68.2%) | 0.725 |
| More than 1 mile | 11 (28.2%) | 4 (23.5%) | 7 (31.8%) | |
| Duration of attendance at lunch: club: | ||||
| Less than 1 year | 6 (15.4%) | 1 (5.9%) | 5 (22.7%) | 0.206 |
| More than 1 year | 33 (84.6%) | 16 (94.1%) | 17 (77.3%) | |
| Reasons for lunch club attendance: | Important | Neither | Unimportant | |
| To have a hot meal | 29 (74.4%) | 7 (17.9%) | 3 (7.7%) | |
| To meet with friends | 36 (92.3%) | 3 (7.7%) | 0 (0.0%) | |
| To dine outside home | 30 (76.9%) | 8 (20.5%) | 1 (2.6%) | |
| For a home-styled cooked meal | 28 (71.8%) | 5 (12.8%) | 6 (15.4%) | |
| To skip cooking at home | 17 (43.6%) | 16 (41.0%) | 6 (15.4%) | |
| For an affordable meal | 15 (38.5%) | 19 (48.7%) | 5 (12.8%) | |
| For the extra activities | 6 (15.4%) | 28 (71.8%) | 5 (12.8%) | |
BW: Body weight; SD: Standard deviation.
a Significance values refer to either independent t-tests or Fisher’s exact test for continuous and categorical variables, respectively.
b One female individual was in warden-controlled housing.
Reasons for lunch club attendance, proximity to the lunch clubs, attendance duration and means of transport to and from the clubs are also detailed in Table 1. The majority of participants reported that having a hot meal (74.4%), meeting with friends (92.3%), dining outside home (76.9%), having a home-styled cooked meal (71.8%) and skipping cooking (43.6%) were perceived as important factors in relation to their lunch club dining experience. Meal affordability and participating in the activities offered at the lunch clubs were not deemed as important factors among the elderly. The majority of participants had been attending lunch clubs for more than a year and had chosen lunch clubs at a distance less than a mile from their home (84.6% and 71.8% of participants respectively). Transportation to the lunch clubs was performed by vehicle for most of the elderly.
Table 2 compares the dietary intake of participants between lunch club and non-lunch club days. In terms of absolute energy intake, protein, fat, carbohydrate, saturated fatty acids (SFA), fibre, potassium, calcium, iron, vitamins A, C and folate and water from drinks were significantly greater among lunch club days. When intake was expressed as a percentage of the DRVs, all examined nutrients were consumed in greater adequacy during lunch club days, except for potassium and vitamin D.
Table 2.
Dietary intake of participants on the day of lunch club and non-lunch club days (mean ± SD, or median with respective IQR) (N=39).
| Absolute intakes | Significance | % DRVa | Significanceb | |||
|---|---|---|---|---|---|---|
| Lunch club day | Non-lunch club days | Lunch club day | Non-lunch club days | |||
| Energy (kcal) | 1,850.1±4839 | 1,367.3±5168 | <0.001 | 83.2 (28.0) | 62.7 (26.0) | <0.001 |
| Protein (g) | 77.6±27.2 | 65.3±26.6 | 0.023 | 148.4 (92.0) | 132.0±526 | 0.019 |
| Protein (%) | 17.0±4.9 | 19.3 (7.0) | 0.021 | |||
| Total fat (g) | 67.0 (31.0) | 57.6±24.7 | 0.001 | |||
| Total fat (%) | 37.2±8.6 | 38.0±10.0 | 0.702 | |||
| SFA (g) | 26.0 (21.0) | 23.3±10.6 | 0.037 | |||
| Total Carbohydrate (g) | 205.0 (80.0) | 147.0 (87.0) | <0.001 | |||
| Total Carbohydrate (%) | 47.4±8.6 | 43.4±10.6 | 0.065 | |||
| Dietary Fibre (g) | 12.0 (6.0) | 9.0 (9.0) | 0.013 | 41.0 (21.0) | 31.0 (36.0) | 0.031 |
| Na (mg) | 2,252.0 (1,387.0) | 1,966.0 (1,452.0) | 0.089 | 141.0 (87.0) | 124.0 (81.0) | 0.11 |
| K (mg) | 2,783.0 (1,225.0) | 1,995.0 (1,129.0) | <0.001 | 80.0 (35.0) | 58.0 (27.0) | <0.001 |
| Ca (mg) | 909.0±337.6 | 634.0 (353.0) | <0.001 | 129.7±48.3 | 90.0 (50.0) | <0.001 |
| Fe (mg) | 8.9 (5.0) | 8.0 (7.0) | 0.028 | 102.0 (53.0) | 90.0 (77.0) | 0.026 |
| Vitamin A (µg) | 1185.0 (1438.0) | 865.0 (960.0) | 0.020 | 202.7 (290.0) | 123.6 (153.0) | 0.015 |
| Vitamin D (µg) | 1.8 (2.0) | 1.1 (1.0) | 0.130 | 18.0 (18.0) | 11.0 (14.0) | 0.133 |
| Folate (µg) | 235.0 (173.0) | 172.0 (116.0) | 0.003 | 117.0 (87.0) | 86.0 (58.0) | 0.003 |
| Vitamin C (µg) |
73.0 (70.0) | 33.0 (43.0) | 0.002 | 183.0 (177.0) | 80.0 (95.0) | 0.002 |
| Water from drinks (ml) | 970.0 (400.0) | 850.0 (437.0) | 0.003 | 57.8 (24.0) | 52.5 (28.0) | 0.005 |
BDA: British Dietetic Association; DRV: Dietary reference value; EAR: Estimated average requirements; IQR: Interquartile range; SD: Standard deviation; SFA: Saturated fatty acids.
a Based on either the EAR or BDA guidelines.
b Significance values refer either to paired t-tests or to the Wilcoxon signed rank test.
Male sex, age and being married did not have a significant relationship with the difference (Δ) in energy, total protein and fat, or SFA, intake between lunch club and non-lunch club days in multivariable linear regression models (Table 3). However, it was observed that being married had a significant, positive relationship with Δ carbohydrate intake, expressed as a percentage of the total daily energy consumption (ß =9.26, 95% CI=1.62 to 16.91, P=0.019). When the models were repeated for the micronutrients intake, only age had a positive relationship with the Δ sodium intake (ß =74.78, 95% CI=3.43 to 146.12, P=0.040). Finally, being married had a positive relationship with the Δ %DRV water intake (ß =10.59, 95% CI=0.89 to 20.28, P=0.033).
Table 3.
Multivariable linear regression modelsa of the relationships among male sex, age, married status and the dietary intake difference between lunch club and non-lunch club days.
| DV/IV | Male sex | Age | Married |
|---|---|---|---|
| ß (95% CI), significance | ß (95% CI), significance | ß (95% CI), significance | |
| Δ Energy intake (EI) | 38.30 (−156.73 to 233.33), P=0.692 | 5.36 (−7.41 to 18.12), P=0.400 | 45.65 (−222.85 to 314.14), P=0.732 |
| Δ Protein (g) | −4.34 (−22.74 to 14.07), P=0.635 | −0.15 (−1.39 to 1.09), P=0.808 | 10.60 (−15.35 to 36.54), P=0.412 |
| Δ Protein (%DRV) | −0.46 (−3.81 to 2.88), P=0.780 | 0.01 (−0.22 to 0.24), P=0.936 | −2.35 (−6.96 to 2.28), P=0.310 |
| Δ Total fat (g) | 8.69 (−13.77 to 31.16), P=0.437 | −0.82 (−2.37 to 0.74), P=0.292 | −20.08 (−52.02 to 11.87), P=0.210 |
| Δ Fat (%EI) | 4.59 (−1.44 to 10.61), P=0.131 | −0.01 (−0.41 to 0.39), P=0.953 | −4.91 (−13.01 to 3.19), P=0.226 |
| Δ SFA (g) | −0.11 (−10.62 to 10.39), P=0.983 | −0.52 (−1.24 to 0.20), P=0.151 | −8.39 (−22.80 to 6.02), P=0.245 |
| Δ Carbohydrate (g) | −4.95 (−44.10 to 34.21), P=0.799 | 0.98 (−1.61 to 3.56), P=0.447 | 52.63 (−2.22 to 107.48), P=0.059 |
| Δ Carbohydrate (%EI) | −4.65 (−10.27 to 0.97), P=0.102 | 0.11 (−0.26 to 0.49), P=0.540 | 9.26 (1.62 to 16.91), P=0.019 |
Δ denotes the difference in nutrient intakes between lunch club and non-lunch club days; ß denotes linear regression beta coefficient; CI: Confidence interval; DRV: Dietary reference value; DV/IV: Dependent/independent variables; EI: Energy intake; SFA: Saturated fatty acids.
a Multivariable linear regression models included differences in nutrient intakes as DV and IV were male sex, age (continuous) and being married, and were adjusted for non-lunch club days’ nutrients (continuous).
Discussion
The present study reveals that the dietary intake of the elderly is substantially improved on the days when dining at lunch clubs. In particular, energy, and macronutrient intake, as well as the consumption of several micronutrients, is greater during the lunch club days compared with the non-lunch club days. Additionally, being married was associated with increased carbohydrate and water consumption on lunch club, compared to non-lunch club, days.
The positive effect of lunch clubs on improving dietary intake and quality in the elderly appears to stem from two main factors: improved psychology and ameliorated diet quality. Research has shown that dining with company increases both the intake of key nutrients and the appetites of those living alone (Conklin et al., 2014; Vesnaver and Keller, 2011). The community spirit, social support, social network and reduction in social isolation has recently been highlighted by older people as a pivotal factor in affecting diet quality (Bloom et al., 2016, 2017; McIntosh et al., 1989). In addition, the elderly perceive lunch clubs as an opportunity to reduce the feeling of loneliness (Thomas and Emond, 2017). In this context, lunch clubs have been shown to negate some of the psychological effects caused by social isolation, including depression, poor cognitive performance and low perceived health status (Thomas, 2015). In a qualitative study (Thomas and Emond, 2017), older people reported lunch club dining as an out-of-routine procedure, while dining in and alone as being the commonest everyday method of dining.
As far as diet quality is concerned, lunch clubs provide older people with regular shared meals, and a wider variety of food compared with their norm (Thomas and Emond, 2017). This previous finding may explain the increased dietary intakes and quality of nutrients that were noted amongst participants attending lunch clubs in this study. In addition, the elderly consider lunch club meals as appetizing, and perceive the experience as a ‘treat’ (Thomas and Emond, 2017).
In our study, there were no differences in dietary intake between age and gender on lunch club and non-lunch club days. However, it was observed that there was a significant increase in carbohydrate and fluid intake among the married elderly on lunch club days. Overall, literature indicates that being married is associated with increased dietary intake during older age (Horwath, 1989; McIntosh et al., 1989), while widowhood is associated with increased depressive symptoms and less enjoyment of meals, which may lead to reduced dietary intake and quality (Vesnaver et al., 2015, 2016). Thus, it is highly likely that the improved intake of the married elderly is further increased on lunch club days.
Caveats of the present research include its pilot nature, allowing for a relatively small, although homogenous, sample of participants. Additionally, the cross-sectional nature of the design does not allow for a prospective understanding of the effects of lunch club dining on the dietary intake and health of the elderly. Future research should aim to recruit more participants and evaluate the psychological status of the elderly, as well as compare the diet quality of lunch club meals compared with those eaten at home.
To summarize, the present pilot study shows that lunch club dining is associated with increased dietary intake and nutrient quality among older people. This finding is important for stakeholders and policy makers in supporting better dietary intake among community-dwelling older people.
Supplemental material
Supplemental Material, STROBE-checklist for Effects of lunch club attendance on the dietary intake of older adults in the UK: A pilot cross-sectional study by Fotini Tsofliou, Maria G Grammatikopoulou, Rosie Lumley, Konstantinos Gkiouras, Jose Lara and Carol Clark in Nutrition and Health
Acknowledgements
The authors appreciate the cooperation of all participants.
Footnotes
Author contributions: FT (corresponding author) conceived the idea, designed and supervised the study. MGG prepared the first draft of the manuscript, which was adapted by FT. RL collected all data, analysed the dietary data and drafted part of the methodology. KG performed all statistical analyses and drafted the results. JL and CC edited and revised study procedures. FT was responsible for the final content of the paper. All authors read and approved the final manuscript.
Availability of data: Due to the personal nature of the data, they will be available blind, upon request.
Ethical statement: All study procedures were approved by the ethics committee of Bournemouth University (Reference Id 1151).
Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The present study did not receive any funding; however, during the study, MGG was a visiting scholar at Bournemouth University, funded by the Erasmus programme.
ORCID iDs: Fotini Tsofliou 
https://orcid.org/0000-0003-1605-5826
Konstantinos Gkiouras
https://orcid.org/0000-0002-6407-8494
Carol Clark
https://orcid.org/0000-0002-9296-7141
Supplemental material: Supplemental material for this article is available online.
References
- Agarwal E, Miller M, Yaxley A, et al. (2013) Malnutrition in the elderly: A narrative review. Maturitas 76: 296–302. [DOI] [PubMed] [Google Scholar]
- Barnett AG, van der Pols JC, Dobson AJ. (2004) Regression to the mean: What it is and how to deal with it. International Journal of Epidemiology 34(1): 215–220. [DOI] [PubMed] [Google Scholar]
- Bloom I, et al. (2016) Influences on diet quality in older age: The importance of social factors. Age and Ageing 46(2): 277–283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bloom I, et al. (2017) What influences diet quality in older people? A qualitative study among community-dwelling older adults from the Hertfordshire Cohort Study, UK. Public Health Nutrition 20(15): 2685–2693. [DOI] [PMC free article] [PubMed] [Google Scholar]
- British Dietetic Association (2017) Food Fact Sheets: Fluids. London, UK: Available at: https://www.bda.uk.com/resource/fluid-water-drinks.html (accessed: 25 February 2019). [Google Scholar]
- Brunet D. (1987) Lunch clubs for the elderly in England: A study. Canadian Family Physician / Medecin de famille canadien 33: 1299–1306. [PMC free article] [PubMed] [Google Scholar]
- Burke D, et al. (2011) Community luncheon clubs benefit the nutritional and social well-being of free living older people. Journal of Human Nutrition and Dietetics 24(3): 278. [Google Scholar]
- Cade J, Hutchinson J. (2015) Study design: Population-based studies. In: Lovegrove JA, Hodson L, Sharma S, et al. (eds) Nutrition Research Methodologies. Chichester: John Wiley & Sons Ltd, 13–27. [Google Scholar]
- Clegg ME, Williams EA. (2018) Optimizing nutrition in older people. Maturitas 112: 34–38. [DOI] [PubMed] [Google Scholar]
- Conklin AI, et al. (2014) Social relationships and healthful dietary behaviour: Evidence from over-50s in the EPIC cohort, UK. Social Science & Medicine 100(100): 167–175. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Department of Health (1991) Dietary reference values for food energy and nutrients for the United Kingdom: Report of the Panel on Dietary Reference Values of the Committee on Medical Aspects of Food Policy. London: TSO. [PubMed] [Google Scholar]
- Donini LM, et al. (2013) Malnutrition in elderly: Social and economic determinants. The Journal of Nutrition, Health & Aging 17(1): 9–15. [DOI] [PubMed] [Google Scholar]
- Feldblum I, et al. (2007) Characteristics of undernourished older medical patients and the identification of predictors for undernutrition status. Nutrition Journal 6(1): 37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Grammatikopoulou M, et al. (2012) Food insecurity among elderly in Athens, Clinical Nutrition S7: 46. [Google Scholar]
- Grammatikopoulou MG, et al. (2019) Food insecurity increases the risk of malnutrition among community-dwelling older adults. Maturitas 119: 8–13. [DOI] [PubMed] [Google Scholar]
- Horwath CC. (1989) Marriage and diet in elderly Australians: Results from a large random survey. Journal of Human Nutrition and Dietetics 2(3): 185–193. [Google Scholar]
- Kingston A, et al. (2018) Projections of multi-morbidity in the older population in England to 2035: Estimates from the Population Ageing and Care Simulation (PACSim) model. Age and Ageing 47(3): 374–380. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lean ME, Han TS, Deurenberg P. (1996) Predicting body composition by densitometry from simple anthropometric measurements. The American Journal of Clinical Nutrition 63(1): 4–14. [DOI] [PubMed] [Google Scholar]
- Marsman D, et al. (2018) Healthy ageing: The natural consequences of good nutrition – a conference report. European Journal of Nutrition 57(S2): 15–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- McIntosh WA, Shifflett PA, Picou JS. (1989) Social support, stressful events, strain, dietary intake, and the elderly. Medical Care 27(2): 140–153. [DOI] [PubMed] [Google Scholar]
- Ortiz-Andrellucchi A, et al. (2009) Dietary assessment methods for micronutrient intake in elderly people: A systematic review. British Journal of Nutrition 102(S1): S118. [DOI] [PubMed] [Google Scholar]
- Shlisky J, et al. (2017) Nutritional considerations for healthy aging and reduction in age-related chronic disease. Advances in Nutrition 8(1): 17–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stokes A, Preston SH. (2013) Population change among the elderly: International patterns. Population and Development Review 38(Suppl. 1): 309–321. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Scientific Advisory Committee on Nutrition (2011) Dietary reference values for energy. London: TSO. [Google Scholar]
- Scientific Advisory Committee on Nutrition (2015) Carbohydrates and health. London: TSO. [Google Scholar]
- Thomas J. (2015) Insights into loneliness, older people and well-being. London: Measuring National Well-being, Office for National statistic. [Google Scholar]
- Thomas N, Emond R. (2017) Living alone but eating together: Exploring lunch clubs as a dining out experience. Appetite 119: 34–40. [DOI] [PubMed] [Google Scholar]
- Vesnaver E, et al. (2015) Food behavior change in late-life widowhood: A two-stage process. Appetite 95: 399–407. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vesnaver E, et al. (2016) Alone at the table: Food behavior and the loss of commensality in widowhood: Table 1. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 71(6): 1059–1069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vesnaver E, Keller HH. (2011) Social influences and eating behavior in later life: A review. Journal of Nutrition in Gerontology and Geriatrics 30(1): 2–23. [DOI] [PubMed] [Google Scholar]
- Yiengprugsawan V, Banwell C, Takeda W, et al. (2015) Health, happiness and eating together: what can a large Thai cohort study tell us? Global Journal of Health Science 14(4): 270–277. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental Material, STROBE-checklist for Effects of lunch club attendance on the dietary intake of older adults in the UK: A pilot cross-sectional study by Fotini Tsofliou, Maria G Grammatikopoulou, Rosie Lumley, Konstantinos Gkiouras, Jose Lara and Carol Clark in Nutrition and Health