Age and Ageing 2022; 51: 1–9
https://doi.org/10.1093/ageing/afac022© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics
Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

RESEARCH PAPER

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The lack of opportunity to eat together isassociated with an increased risk of weight loss
among independent older adults: a prospective
cohort study based on the JAGES
Taro Kusama1,2 , Sakura Kiuchi2 , Yukako Tani3 , Jun Aida4 , Katsunori Kondo5,6 , Ken Osaka2
1

Division for Regional Community Development, Liaison Center for Innovative Dentistry, Tohoku University Graduate School of
Dentistry, Sendai, Miyagi, 980-8575, Japan2
Department of International and Community Oral Health, Tohoku University Graduate School of Dentistry, Sendai, Miyagi,
980-8575, Japan3
Department of Global Health Promotion, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University,
Bunkyo-ku, 113-8510, Tokyo, Japan
4
Department of Oral Health Promotion, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University,
Bunkyo-ku, 113-8510, Tokyo, Japan
5
Department of Social Preventive Medical Sciences, Center for Preventive Medical Sciences, Chiba University, Chuo-ku, Chiba,263-8522, Japan
6
Department of Gerontological Evaluation, Center for Gerontology and Social Science, National Center for Geriatrics andGerontology, Obu, Aichi, 474-8511, Japan
Address correspondence to: T. Kusama, Division for Regional Community Development, Liaison Center for Innovative Dentistry,
Tohoku University Graduate School of Dentistry 4-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8575, Japan.
Tel: (+81) 22 717 7639. Email: taro.kusama.a2@tohoku.ac.jp

Abstract
Objective: the present study aimed to investigate the relationship between the frequency of eating together and the risk ofweight loss in older adults.
Methods: this was a three-year follow-up prospective cohort study based on a self-reported questionnaire. We used data fromthe Japan Gerontological Evaluation Study (JAGES) conducted in 2016 and 2019. The participants were independent older
adults aged ≥65 years in Japan. We used >5% weight loss during follow-up as the outcome variable and frequency of eating
together as the explanatory variable. The relative risks (RRs) and 95% conﬁdence intervals (95% CIs) were estimated based on
the Poisson regression model with a Huber–White sandwich estimator for standard errors, including possible confounders.
Results: among 56,919 participants, the mean age was 73.0 years (1SD = 5.5) at baseline, and 47.9% were male. About
15.1% (n = 8,596) of the participants experienced >5% weight loss during follow-up. The proportion of each category of
the eating together frequency was 36.6% for ‘every day’, 10.3% for ‘several times a week’, 26.8% for ‘several times a month’,
20.5% for ‘several times a year’ and 5.8% for ‘seldom’. Compared to ‘every day’, only ‘several times a year (RR = 1.07, 95%
CI = 1.01–1.13)’ and ‘seldom (RR = 1.17, 95% CI = 1.08–1.27)’ were signiﬁcantly associated with the increased risk of>5% weight loss.
Conclusion: there is a temporal association between less frequent opportunities to eat together and the increased risk ofweight loss among independent older adults.
Keywords: malnutrition, weight loss, eating behaviour, older adults, cohort study1

T. Kusama et al.
Key Points• Weight loss is a critical health problem among older adults.
• Eating together is one of the factors aﬀecting older adults’ health conditions.
• The lack of opportunity to eat together was associated with an increased risk of weight loss among older adults.
• A clear dose-response relationship by frequency of eating together was not observed.
• The opportunity to eat together may contribute to maintaining older adults’ nutritional status.

Introduction

Methods
Study design and participants

The present study was a three-year follow-up prospective
cohort design based on a self-reported questionnaire. We
used data from the Japan Gerontological Evaluation Study(JAGES), which aims to investigate social determinants of2

Outcome variables

We used the clinically signiﬁcant level of weight loss duringfollow-up as the outcome variable. We determined those who
experienced >5% weight loss as a clinically signiﬁcant levelof weight loss. Previous studies have reported an association
between >5% weight loss and an increased risk of mortality[16, 17]. We obtained the participants’ weight at baseline
and follow-up using a self-reported questionnaire, divided
the weight in 2019 by that in 2016 and calculated the
proportional change of weight per participant. A decrease inweight >5% was categorized as an incidence of weight loss.
The previous study conﬁrmed the accuracy of self-reported
height and weight of the participants in the JAGES [18].
The interclass correlation coeﬃcient between self-reported
and measured weight was 0.97. We excluded participants
who reported invalid weights and heights (more than 4
SD of the distribution of these variables in the Japanese
population, as obtained from the Japanese National Healthand Nutrition Survey) from the analysed population [19].
For the sensitivity analysis, we also used >10% weight loss
as the outcome variable.
Explanatory variable

We used the frequency of eating together as an explanatory
variable. We asked the participants, ‘How often do you eat
meals with someone else?’ The response options were ‘every
day’, ‘several times a week’, ‘several times a month’, ‘several
times a year’ and ‘seldom’. Their responses were directly
used as categorical variables. We also used the dichotomous
variable ‘several times a month or more’ and ‘less than several
times a month’ for sensitivity analysis because the bias due
to misclassiﬁcation can be interpreted more accessible byemploying the dichotomous variables.

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Deterioration of nutritional status is a signiﬁcant health issue
among older adults. Weight loss is one of the clinical signsof malnutrition among older adults, and 15–20% of older
adults experienced >5% weight loss in the last six months[1]. Weight loss in later life leads to subsequent health problems, including cognitive decline [2] or disability [3], and it
ultimately leads to an increased risk of mortality [4]. Most
risk factors for weight loss, such as limitation of physicalactivity, poor oral health and comorbidity, are commonly
found in older adults [5, 6]; therefore, the elucidation of
modiﬁable factors that prevent weight loss among older
adults is required.
Previous studies have emphasized the importance of social
relationships in maintaining health conditions [7–9]. Social
isolation and loneliness, which are subordinate concepts ofsocial relationships [7], are prevalent among older adults dueto the progression of an ageing society [9]. The opportunity
to have a meal with someone is a kind of eating behaviour
related to social isolation or loneliness [10]. Previous studies have revealed that eating with someone contributes tofavourable health conditions, including mental health [11]and a decreased risk of mortality [12, 13].
Previous studies also suggested an association between
eating alone and poor nutritional status among communitydwelling older adults [14], and eating alone may increase therisk of malnutrition. However, these previous studies werecross-sectional designs and did not mention their causality[14]. Additionally, most studies treated the status of ‘eating
alone’ as just the presence or absence of ‘eating alone’. They
did not evaluate the dose–response relationship between thefrequency of eating together and nutritional status. Elucidating the suﬃcient frequency of eating together to maintain the
nutritional status of older adults will contribute to planningan eﬀective intervention for weight loss prevention. Thus, weinvestigated the relationship between the frequency of eating
together and the incidence of weight loss among older adults
using cohort data.

health under the collaboration of multiple universities andmunicipalities, and it targeted independent older adults
above 65 years of age who were not certiﬁed to be eligible forlong-term public care [15]. Baseline and follow-up surveys
were conducted in 2016 and 2019, respectively, and 32
municipalities in Japan were included in these surveys. The
questionnaires were sent to the participants by mail andretrieved by mail if they consented. We excluded participants
whose information about gender, age, weight and height
was missing or invalid. Those whose activities of daily living
were not independent were also excluded from the analysed
population.

The lack of opportunity to eat together is associated with an increased risk
Covariates

Statistical analysis

We employed Poisson regression models to evaluate the eﬀectof eating together on weight loss and calculated the relative
risks (RRs) and 95% conﬁdence intervals (95% CIs). The
proportion of >5% weight loss incidence was >10%, andlogistic regression analysis would overestimate the relative
risk; therefore, we employed the Poisson regression modelwith a Huber–White sandwich estimator for standard errors[28, 29]. For >10% weight loss incidence, we estimatedodds ratios (ORs) and 95% CIs based on the logistic regression model. We built three models: model 1 was a crude
model, model 2 included gender and age, and model 3
included all covariates. We also created the models including the interaction terms between gender or living status
and the frequency of eating together to conﬁrm the eﬀect
modiﬁcation of gender and living status in the relationships
between eating together and excessive weight loss. We also
conducted the analysis with the stratiﬁcation by gender andliving status [30]. In the analysis with the ‘Living alone’ stratum, we changed the reference category to ‘Several times amonth’, considering the distribution of the participants. We
conducted multiple imputations to reduce selection bias. We
created 20 imputed datasets using multivariate imputations

Ethical issues

The JAGES in 2016 and 2019 followed the procedures
approved by the Ethics Committee on Research of Human
Subjects at the National Center for Geriatrics and Gerontology (No. 992 and No. 1274-2), Chiba University (No.
2493 and 3442), and the Japan Agency for Gerontological
Evaluation Study (2019–01). Additionally, we followed
the STROBE statement to report our observational
study.

Results
Figure 1 presents a ﬂowchart of the participants’ inclusion.
The response rate of participants was 70.3%, and thefollow-up rate was 56.2%. Finally, 56,919 participants were
included in our analysis. Supplementary Table S1 presents
the characteristics of the participants before the multiple
imputations.
Initially, MICE imputed 15,328 participants withmissing values, and Table 1 and Supplementary Table S2show the characteristics of participants after multiple
imputations. The average age of participants at baseline was
73.0 years (1 SD = 5.5), with 47.9% male. About 15.1%(n = 8,596) of the participants experienced >5% weight
loss, and 4.8% (n = 2,736) experienced >10% weightloss during the follow-up. The proportion of participantsin each category of the frequency of eating together atbaseline, i.e. ‘every day’, ‘several time a week’, ‘several times
a month’, ‘several times a year’ and ‘seldom’ was 36.6%(n = 20,818), 10.3% (n = 5,895), 26.8% (n = 15,271),
20.5% (n = 11,656) and 5.8% (n = 3,279), respectively.
The proportion of those who experienced >5% weight loss
in each category of the eating together frequency was 14.3%
for ‘every day’, 14.8% for ‘several times a week’, 14.6% for‘several times a month’, 16.2% for ‘several times a year’ and19.0% for ‘seldom’ (Table 2). The incidence proportions of>5% weight loss were high among the categories of ‘several
times a year’ and ‘seldom’. For >10% weight loss, a similar
trend in the proportional diﬀerence was observed.
Table 3 shows the association between the frequencyof eating together and weight loss. In model 3, thefrequency of eating together ‘several times a year (RR =1.07, 95% CI = 1.01–1.13)’ and ‘seldom (RR = 1.17,
95% CI = 1.08–1.27)’ was signiﬁcantly associated withan increased risk of >5% weight loss, respectively. For>10% weight loss, the frequency of eating together ‘seldom(OR = 1.29, 95% CI = 1.10–1.52)’ was also associated.
In the complete case analysis, the point estimates wereconsistent with those obtained from the imputed datasets(Supplementary Table S3). The sensitivity analysis using

3

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We selected possible confounders as covariates based on clinical knowledge and previous studies [5, 20–23]. The covariates included in the analysis were gender (male/female) andage (65-69/70-74/75-79/80-84/≥85) as sociodemographic
factors; living status (living with someone/living alone) andmarital status (with/without spouse) as family structures;
equivalent income (<2.00 million JPY/2.00–3.99 million
JPY/≥4.00 million JPY: 100 JPY ≈ 1USD) and the numberof years of education (≤9 years/10-12 years/≥13 years) as
socioeconomic status; comorbidities (stroke, diabetes, cancer
and dementia), cognitive decline, depressive symptoms andnumber of remaining teeth (≤19/≥20) as current general,mental and oral health conditions; instrumental activities ofdaily living (IADL) and body mass index (BMI) at baseline. We evaluated IADL using the Tokyo Metropolitan
Institute of Gerontology Index of Competence [24]. Cognitive decline was assessed by Kihon Checklist-Cognitive
Function, and we treated those who corresponded to atleast one of the three options as having a cognitive decline[25]. Depressive symptoms were assessed by the geriatricdepressive scale-15 with a cut-oﬀ of 5 points [26]. We also
included the frequency of meeting friends (≥1 times/week,≥1 time/month, or several times a year/never) as the degreeof social isolation, which is widely used to measure social
isolation [27], and the frequency of vegetable/fruit intake(≥1 time/day or <1 time/day) and frequency of meat/ﬁshintake (≥1 time/day or <1 time/day) as a current daily diet.
Additionally, we considered gender and living status as eﬀect
modiﬁers in the relationship between the frequency of eating
together and weight loss because previous studies on eating
together or solitary eating reported diﬀerences within genderand living status in the results [20, 21].

by chained equations (MICE) and combined the estimatesobtained from each dataset using Rubin’s rule [31]. For
the sensitivity analysis, we also conducted a complete caseanalysis, excluding those with any missing values. We used
Stata/MP version 16.1 (Stata Corp., College Station, TX,
USA) to perform the statistical analysis.

T. Kusama et al.

the dichotomous variable suggested that the frequencyof eating together ‘less than several times a month’ werehigher risk of >5% weight loss compared to ‘several times
a month or more’ (RR = 1.08, 95% CI = 1.03–1.13)(Supplementary Table S4).
We also evaluated the interaction eﬀect between genderor living status and the frequency of eating together.
However, the interaction eﬀects of both variables on
the multiplicative scale were not signiﬁcant (all P > 0.1)
(Supplementary Tables S5 and S6). Table 4 shows the results
stratiﬁed by gender and living status.

4

Discussion
The present study results revealed that among independent
older adults, those who had the opportunity to eat together
less than several times a month were at an increased risk ofclinically signiﬁcant level of weight loss. Further, the association remained statistically signiﬁcant even after adjustingfor social isolation and daily diet. We could not ﬁnd asigniﬁcant eﬀect modiﬁcation by gender and living status in
the association between the frequency of eating together andweight loss.

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Figure 1. The participants ﬂow for analytic sample (n=56,919).

The lack of opportunity to eat together is associated with an increased risk

Table 1. Descriptive characteristics of the participants at baseline after multiple imputations
Characteristics n(%)

All participants (n = 56,919)

Weight loss during three-year follow-up≤5% (n = 48,323)>5% (n = 8,596)

20,818 (36.6)
5,895 (10.3)
15,271 (26.8)
11,656 (20.5)
3,279 (5.8)

17,846 (36.9)
5,020 (10.4)
13,035 (27.0)
9,766 (20.2)
2,656 (5.5)

2,972 (34.6)
875 (10.2)
2,236 (26.0)
1,890 (22.0)
623 (7.2)

27,259 (47.9)
29,660 (52.1)

23,164 (47.9)
25,159 (52.1)

4,095 (47.6)
4,501 (52.4)

18,992 (33.4)
17,113 (30.0)
13,078 (23.0)
5,986 (10.5)
1,750 (3.1)

16,610 (34.4)
14,771 (30.6)
10,969 (22.7)
4,686 (9.7)
1,287 (2.6)

2,382 (27.7)
2,342 (27.3)
2,109 (24.5)
1,300 (15.1)
463 (5.4)

48,579 (85.3)
8,340 (14.7)

41,200 (85.3)
7,123 (14.7)

7,379 (85.8)
1,217 (14.2)

43,263 (76.0)
13,656 (24.0)

36,838 (76.2)
11,485 (23.8)

6,425 (74.7)
2,171 (25.3)

25,995 (45.7)
24,044 (42.2)
6,880 (12.1)

21,729 (45.0)
20,637 (42.7)
5,957 (12.3)

4,266 (49.6)
3,407 (39.7)
923 (10.7)

14,167 (24.9)
24,971 (43.9)
17,781 (31.2)

11,695 (24.2)
21,316 (44.1)
15,312 (31.7)

2,472 (28.8)
3,655 (42.5)
2,469 (28.7)

1,242 (2.2)
7,014 (12.3)
2,138 (3.8)
62 (0.1)

1,039 (2.2)
5,607 (11.6)
1,790 (3.7)
49 (0.1)

203 (2.4)
1,407 (16.4)
348 (4.1)
13 (0.2)

34,570 (60.7)
22,349 (39.3)

29,849 (61.8)
18,474 (38.2)

4,721 (54.9)
3,875 (45.1)

34,686 (60.9)
22,233 (39.1)

29,716 (61.5)
18,607 (38.5)

4,970 (57.8)
3,626 (42.2)

40,206 (70.6)
16,713 (29.4)

34,331 (71.0)
13,992 (29.0)

5,875 (68.3)
2,721 (31.7)

46,847 (82.3)
10,072 (17.7)

40,043 (82.9)
8,280 (17.1)

6,804 (79.2)
1,792 (20.8)

28,974 (50.9)
13,399 (23.5)
14,546 (25.6)

24,847 (51.4)
11,402 (23.6)
12,074 (25.0)

4,127 (48.0)
1,997 (23.2)
2,472 (28.8)

46,906 (82.4)
10,013 (17.6)

40,033 (82.8)
8,290 (17.2)

6,873 (80.0)
1,723 (20.0)

30,961 (54.4)
25,958 (45.6)

26,517 (54.9)
21,806 (45.1)

4,444 (51.7)
4,152 (48.3)

22.8 (3.0)

22.7 (3.0)

23.5 (3.3). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Frequency of eating together
EverydaySeveral times a week
Several times a month
Several times a year
SeldomGenderMale
FemaleAge at 2016
65–69
70–74
75–79
80–84
≥85
Living status
Living with someone
Living alone
Marital status
With spouse
Without spouse
Equivalent income (100 JPY ≈ 1 USD)
<200 million JPY
200–399 million JPY≥400 million JPY
Education≤9 years
10–12 years≥13 years
Comorbidities
StrokeDiabetes
CancerDementia
Number of teeth≥20≤19
Instrumental activities of daily living
Good
Poor
Cognitive decline
No
Yes
Depressive symptoms
GDS-15 ≤ 4
GDS-15 ≥ 5Frequency of meeting friends≥1 time/week≥1 time/month
Several times a year/seldom
Frequency of vegetable/fruits intake≥1 time/day<1 time/day
Frequency of meat/ﬁsh intake≥1 time/day<1 time/day
BMI at baseline
Mean (SD)NOTE: Each response was the average of 20 imputed datasets. Abbreviation: GDS-15, geriatric depressive scale-15.

5T. Kusama et al.
Table 2. The proportion of those who experienced weight loss during follow-up by the frequency of eating together(n = 56,919)% (n)Frequency of eating together
EverydaySeveral times a week

Several times a month

Several times a year

SeldomTotal

14.8 (875)85.2 (5,020)
4.8 (283)
95.2 (5,612)
100.0 (5,895)

14.6 (2,236)
85.4 (13,035)
4.5 (689)
95.5 (14,582)
100.0 (15,271)

16.2 (1,890)
83.8 (9,766)
5.2 (611)
94.8 (11,045)
100.0 (11,656)

19.0 (623)81.0 (2,656)
6.9 (227)
93.1 (3,052)
100.0 (3,279)

15.1 (8,596)
84.9 (48,323)
4.8 (2,736)
95.2 (54,183)
100.0 (56,919). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Weight loss during the follow-up>5%
14.3 (2,972)≤5%
85.7 (17,846)>10%
4.5 (927)≤10%
95.5 (19,891)
Total
100.0 (20,818)

NOTE: Each response was the average of 20 imputed datasets. Bold values indicate P <0.05

Model 1aModel 2bModel 3c

>5% weight loss
RR (95% CI)>10% weight loss
OR (95% CI)>5% weight loss
RR (95% CI)>10% weight loss
OR (95% CI)>5% weight loss
RR (95% CI)>10% weight loss
OR (95% CI)

Ref.
1.04 (0.97–1.11)
1.03 (0.97–1.08)
1.14(1.08–1.20)∗∗∗1.33(1.23–1.44)∗∗∗Ref.
1.08 (0.94–1.24)
1.01 (0.92–1.12)
1.19(1.07–1.32)∗∗
1.60(1.37–1.86)∗∗∗Ref.
1.02 (0.95–1.09)
0.99 (0.94–1.04)
1.08(1.03–1.14)∗∗
1.26(1.16–1.36)∗∗∗Ref.
1.06 (0.92–1.21)
0.97 (0.87–1.07)
1.11 (1.00–1.23)

Ref.
1.05 (0.98–1.13)
1.01 (0.96–1.07)
1.07 (1.01–1.13)∗

Ref.
1.09 (0.95–1.26)
1.00 (0.90–1.11)
1.08 (0.97–1.21)

1.46(1.25–1.70)∗∗∗1.17(1.08–1.27)∗∗∗1.29(1.10–1.52)∗∗. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Frequency of eating together
EverydaySeveral times a week
Several times a month
Several times a year
SeldomAbbreviations: RR, relative risk; OR, odds ratio; 95% CI, 95% conﬁdence interval. a Model 1: Crude model. b Model 2: Adjusted for gender and age. c Model
3: Adjusted for gender, age, living status, marital status, equivalent income, education, number of teeth, comorbidities (stroke, diabetes, cancer and dementia),
instrumental activities of daily living, cognitive decline, depressive symptoms, frequency of meeting friends, frequency of vegetable/fruits intake, frequency ofmeat/ﬁsh intake and BMI at baseline. ∗ P < 0.05. ∗∗ P < 0.01. ∗∗∗ P < 0.001. Bold values indicate P <0.05

A previous cross-sectional study revealed that eating
alone was associated with underweight among communitydwelling older adults [20]. Our cohort study also conﬁrmed
the longitudinal relationship between eating alone/together
and the increased risk of a clinically signiﬁcant level ofweight loss. Most studies investigating the association
between eating alone/together and health conditions did
not consider the frequency of eating together [14]. The
present study considered the frequency of eating together,and we evaluated the dose–response relationship between
the frequency of eating together and the risk of weightloss. However, a clear dose–response relationship could
not be observed. When the frequency of eating together
was less than several times a month, the risk of weight loss
was statistically signiﬁcant. A previous study also reported
this kind of non-linear association between the frequencyof eating together and nutritional status [32]. The study
suggested that those who have the opportunity to eat
together less than once a month reported signiﬁcantly
lower dietary intake of foods and, among those having theopportunity to eat together one or more times a month, asigniﬁcant diﬀerence was not observed.
From the result of the present study, the association
between the frequency of eating together and weight loss wasobserved even after controlling for social isolation and daily
diet. There is the possibility that general social interaction

6

or daily intake of foods may not have contributed to themechanism between eating together and weight loss. One
possible mechanism that explains the relationship between
the frequency of eating together and weight loss is ‘social
facilitation of eating’. It is a phenomenon in which whenpeople eat with others, they tend to eat more food than when
they eat alone [33]. Among older adults, anorexia (the lack ofappetite) is a prevalent health problem, and anorexia in later
life is caused by physiological changes due to ageing, multiple medications, comorbidities and social isolation [34].
Subsequently, it increases the risk of malnutrition in older
adults [35]. Therefore, it can be considered that, intrinsically,
most older adults are at risk of malnutrition due to anorexia.
However, the opportunity to eat together could increase theenergy and nutrient intake through the social facilitationof eating and protect against the risk of weight loss due toanorexia. The eﬀect may prolong after the opportunity to eat
together. A higher protein intake was associated with a lower
risk of weight loss [36]. Previous studies have reported thatthe intake of protein or meat was higher when eating withothers than when eating alone [37, 38].
We did not observe a linear dose–response relationshipbetween the frequency of eating together and the risk ofweight loss. The result implied no diﬀerence in the risk ofweight loss within the frequency of eating together several
times a month or more. A previous qualitative study also

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Table 3. The association between weight loss and the frequency of eating together (n = 56,919)

The lack of opportunity to eat together is associated with an increased risk
Table 4. The association between weight loss and the frequency of eating together by gender and living status
Stratiﬁed by gender>5% weight loss
Male (n = 27,259)
RR (95% CI)a>10% weight loss
Female(n = 29,660)
RR (95% CI)a

Male (n = 27,259)
OR (95% CI)aFemale(n = 29,660)
OR (95% CI)aRef.
1.03 (0.94–1.14)
1.03 (0.96–1.10)
1.09 (1.01–1.18)∗
1.16 (1.02–1.32)∗

Ref.
1.22 (0.99–1.50)
1.01 (0.86–1.17)
1.04 (0.90–1.21)
1.26 (1.02–1.56)∗

Ref.
1.01 (0.83–1.23)
0.98 (0.85–1.14)
1.12 (0.96–1.32)
1.37 (1.07–1.77)∗. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Frequency of having the meal with someone
EverydayRef.
Several times a week
1.08 (0.97–1.21)
Several times a month
0.99 (0.92–1.07)
Several times a year
1.05 (0.97–1.13)
Seldom1.17 (1.05–1.30)∗∗
Stratiﬁed by living status>5% weight loss

>10% weight loss
Living alone(n = 8,340)

RR (95% CI)b
Frequency of having the meal with someone
EverydayRef.
Several times a week
1.08 (1.00–1.17)
Several times a month1.01 (0.96–1.07)
Several times a year
1.06 (1.00–1.12)∗
Seldom1.18 (1.07–1.29)∗∗

Living alone(n = 8,340)

RR (95% CI)b

Living withsomeone(n = 48,579)
OR (95% CI)b1.10 (0.87–1.40)
0.98 (0.85–1.14)
Ref.c
1.10 (0.96–1.27)
1.11 (0.92–1.33)

Ref.
1.04 (0.88–1.22)
1.01 (0.90–1.13)
1.10 (0.99–1.24)
1.27 (1.06–1.53)∗

1.11 (0.66–1.86)
1.33 (1.00–1.76)
Ref.c
0.99 (0.73–1.33)
1.38 (0.97–1.96)

OR (95% CI)b

Abbreviations: RR, relative risk; OR, odds ratio; 95% CI, 95% conﬁdence interval. a Adjusted for age, living status, marital status, equivalent income, education,
number of teeth, comorbidities (stroke, diabetes, cancer and dementia), instrumental activities of daily living, cognitive decline, depressive symptoms, frequency of
meeting friends, frequency of vegetable/fruits intake, frequency of meat/ﬁsh intake and BMI at baseline. b Adjusted for gender, age, marital status, equivalent income,education, number of teeth, comorbidities (stroke, diabetes, cancer and dementia), instrumental activities of daily living, cognitive decline, depressive symptoms,
frequency of meeting friends, frequency of vegetable/fruits intake, frequency of meat/ﬁsh intake and BMI at baseline. c The reference category was changed to‘Several times a month’ because, among the living alone stratum, the most signiﬁcant number of participants was included in this category. ∗ P < 0.05. ∗∗ P < 0.01.
∗∗∗ P < 0.001.

reported that eating alone does not necessarily mean a lonely
thing but felt autonomous for community-dwelling older
adults living alone [10]. Additionally, a previous study did
not ﬁnd diﬀerences in food intake among those whose frequency of eating together was more than once a month [32].
Based on the discussion so far, there is the possibility that thefrequent opportunity of eating together would contribute topreventing malnutrition among older adults; meanwhile, thefrequency may not need to be high, such as every day.
Among those living alone, we could not observe a clear
association between the frequency of eating together andweight loss. We consider that there are two explanations
for the present result. One is that small sample size andrandom error aﬀected the estimates, and the other is thatthe context of eating together diﬀers between those living
alone and those living with others. Further analysis withthe more detailed survey for the eating circumstance among
those living alone would provide new insight.
From a public health perspective, maintaining or providing opportunities to eat together for older adults would
contribute to keeping their nutritional status. Even under the
pandemic of airborne infectious disease, eﬀective prevention
measures in the restaurant or dining room, including limiting the number of people and ventilation, would maintainthe opportunities to eat together [39, 40].
The present study has several limitations. First, we usedself-reported weight and frequency of eating together as theoutcome variable and explanatory variable, respectively. The
accuracy of weight in JAGES was conﬁrmed elsewhere, andthe proportional change of weight of an individual was usedin the present study, which may have reduced information
bias [18]. The variable we used to measure the frequency ofeating together is not validated; however, a similar ordinalvariable was also used in the previous studies [32]. The
self-reported measure generally leads to misclassiﬁcation.
In the present study, we consider that the misclassiﬁcationof outcome and explanatory variable were non-diﬀerential,
and it would have biased the estimates towards the null.
Second, we evaluated only the frequency of eating together
and did not consider who they ate with. The type of person
whom one eats with may have diﬀerent eﬀects on individual
nutritional status. A previous meta-analysis suggested thatsocial facilitation of eating was observed when ‘eating withfriends’ compared to ‘eating alone’ and not when ‘eating withstranger or acquaintance’ was compared [33]. Therefore, further research considering the person one eats with is required
to elucidate the relationship between eating together andnutritional status. Third, for representativeness, although
the baseline survey included large populations from manymunicipalities in Japan, the follow-up rate of the present
study was not high. Possible reasons for loss to follow-up
were considered to be death, being certiﬁed in long-termcare, moving to other municipalities, non-response or not
being included in the participants at the follow-up survey.

7

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Living with someone(n = 48,579)

T. Kusama et al.

Conclusion
The present study revealed the temporal association between
the lack of opportunity to eat together and increased riskof weight loss among independent older adults using a large
prospective cohort data. However, signiﬁcant diﬀerences in
the risk of weight loss were not observed within the frequencyof eating together several times in a month or more.
Supplementary Data: Supplementary data mentioned in
the text are available to subscribers in Age and Ageing online.
Declaration of Conﬂicts of Interest: None.
Declaration of Sources of Funding: This study used datafrom the Japan Gerontological Evaluation Study (JAGES).
This study was supported by the JSPS (Japan Society for
the Promotion of Science) KAKENHI (Grant Number
15H01972), Health Labour Sciences Research Grant (H28Choju-Ippan-002), Japan Agency for Medical Research andDevelopment (AMED) (JP18dk0110027, JP18ls0110002,
JP18le0110009,
JP20dk0110034,
JP21lk0310073,
JP21dk0110037), Open Innovation Platform with Enterprises, Research Institute and Academia (OPERA,JPMJOP1831) from the Japan Science and Technology(JST), a grant from Innovative Research Program on
Suicide Countermeasures (1-4), a grant from Sasakawa
Sports Foundation, a grant from Japan Health Promotion

8& Fitness Foundation, a grant from Chiba Foundationfor Health Promotion & Disease Prevention, the 8020
Research Grant for ﬁscal 2019 from the 8020 Promotion
Foundation (adopted number: 19-2-06), a grant from
Niimi University (1915010), grants from Meiji Yasuda LifeFoundation of Health and Welfare and the Research Fundingfor Longevity Sciences from National Center for Geriatrics
and Gerontology (29-42, 30-22, 20-19, 21-20). The sponsor
played no role.

References
1. Gaddey HL, Holder K. Unintentional weight loss in older
adults. Am Fam Physician 2014; 89: 718–22.
2. Eymundsdottir H, Ramel A, Geirsdottir OG et al. Body
weight changes and longitudinal associations with cognitive decline among community-dwelling older adults.
Alzheimer’s Dement (Amsterdam, Netherlands) 2021; 13:e12163.
3. Nishida MM, Okura M, Ogita M, Aoyama T, Tsuboyama T,
Arai H. Two-year weight loss but not body mass index predicts
mortality and disability in an older Japanese communitydwelling population. J Am Med Dir Assoc 2019; 20: e11–1654.e18.
4. Alharbi TA, Paudel S, Gasevic D, Ryan J, Freak-Poli R, Owen
AJ. The association of weight change and all-cause mortality
in older adults: a systematic review and meta-analysis. Age
Ageing 2020; 50: 697–704.
5. Streicher M, van Zwienen-Pot J, Bardon L et al. Determinantsof incident malnutrition in community-dwelling older adults:
a MaNuEL multicohort meta-analysis. J Am Geriatr Soc
2018; 66: 2335–43.
6. O’Keeﬀe M, Kelly M, O’Herlihy E et al. Potentially modiﬁable determinants of malnutrition in older adults: a systematic
review. Clin Nutr 2019; 38: 2477–98.
7. Holt-Lunstad J, Smith TB, Layton JB. Social relationships
and mortality risk: a meta-analytic review. PLoS Med 2010;
7: e1000316.
8. Kuiper JS, Zuidersma M, Oude Voshaar RC et al. Social
relationships and risk of dementia: a systematic review andmeta-analysis of longitudinal cohort studies. Ageing Res Rev
2015; 22: 39–57.
9. Santini ZI, Koyanagi A, Tyrovolas S, Mason C, Haro JM.
The association between social relationships and depression:a systematic review. J Aﬀect Disord 2015; 175: 53–65.
10. Thomas N, Emond R. Living alone but eating together:
exploring lunch clubs as a dining out experience. Appetite
2017; 119: 34–40.
11. Tani Y, Sasaki Y, Haseda M, Kondo K, Kondo N. Eating alone
and depression in older men and women by cohabitation
status: the JAGES longitudinal survey. Age Ageing 2015; 44:
1019–26.
12. Tani Y, Kondo N, Noma H, Miyaguni Y, Saito M, Kondo K.
Eating alone yet living with others is associated with mortality
in older men: the JAGES cohort survey. J Gerontol B Psychol
Sci Soc Sci 2018; 73: 1330–4.
13. Huang Y-C, Cheng H-L, Wahlqvist ML, Lo Y-TC, Lee M-S.
Gender diﬀerences in longevity in free-living older adults who
eat-with-others: a prospective study in Taiwan. BMJ Open2017; 7: e016575.

Downloaded from https://academic.oup.com/ageing/article/51/3/afac022/6540137 by guest on 14 April 2022

The distribution of baseline characteristics showed that thoselost to follow-up tended to be older and had a risk factor for
deteriorating health conditions (Supplementary Table S7).
Both the lack of eating together and weight loss increase therisk of mortality [4, 12, 13]. Therefore, the risk of weight loss
among those who had less opportunity to eat together may
be underestimated because those who had less opportunity to
eat together were considered to be lost due to death. The estimated RR of the present study may also be underestimated.
Fourth, there is the concern about the inﬂuence of timevarying exposure on the estimates. We checked the association between the frequency of eating together at baseline
and follow-up (Supplementary Table S8). The frequency ofeating together changed over the period among almost half ofthe participants. Suppose there are time-varying confounders
in the association between the frequency of eating together
and weight loss. In that case, the marginal structural modelwith three-point-panel data will provide more appropriate
estimates [41]. Lastly, we included possible confounders
as covariates based on the hypothesized causal diagram.
However, the existence of unknown confounders or residual
confounding may have aﬀected the estimates. The strengthsof the present study are as follows: ﬁrst, it used a longitudinal
design, and we could infer the temporal association between
the frequency of eating together and weight loss. Second, as
we already mentioned, our results were consistent with theknowledge obtained from previous studies on eating together
and the social facilitation of eating [14, 33]. They contributeto the generalizability of our results.

The lack of opportunity to eat together is associated with an increased risk
follow-up study in Japan and England. Geriatr Gerontol Int
2021; 21: 209–14.
28. McNutt L-A, Wu C, Xue X, Hafner JP. Estimating the relativerisk in cohort studies and clinical trials of common outcomes.
Am J Epidemiol 2003; 157: 940–3.
29. Chen W, Qian L, Shi J, Franklin M. Comparing performance
between log-binomial and robust Poisson regression models
for estimating risk ratios under model misspeciﬁcation. BMC
Med Res Methodol 2018; 18: 63.
30. VanderWeele TJ. On the distinction between interaction andeﬀect modiﬁcation. Epidemiology 2009; 20: 863–71.
31. Sullivan TR, Lee KJ, Ryan P, Salter AB. Multiple imputation for handling missing outcome data when estimating therelative risk. BMC Med Res Methodol 2017; 17: 134.
32. Ishikawa M, Takemi Y, Yokoyama T et al. ‘Eating together’is associated with food behaviors and demographic factors ofolder Japanese people who live alone. J Nutr Health Aging
2017; 21: 662–72.
33. Ruddock HK, Brunstrom JM, Vartanian LR, Higgs S. A
systematic review and meta-analysis of the social facilitationof eating. Am J Clin Nutr 2019; 110: 842–61.
34. Landi F, Calvani R, Tosato M et al. Anorexia of aging: risk
factors, consequences, and potential treatments. Nutrients
2016; 8: 69.
35. Fávaro-Moreira NC, Krausch-Hofmann S, Matthys C et al.
Risk factors for malnutrition in older adults: a systematic
review of the literature based on longitudinal data. Adv Nutr
2016; 7: 507–22.
36. Gray-Donald K, St-Arnaud-McKenzie D, Gaudreau P,
Morais JA, Shatenstein B, Payette H. Protein intake protects against weight loss in healthy community-dwelling older
adults. J Nutr 2014; 144: 321–6.
37. Patel KA, Schlundt DG. Impact of moods and social context
on eating behavior. Appetite 2001; 36: 111–8.
38. Horgan GW, Scalco A, Craig T, Whybrow S, Macdiarmid JI.
Social, temporal and situational inﬂuences on meat consumption in the UK population. Appetite 2019; 138: 1–9.
39. Chang S, Pierson E, Koh PW et al. Mobility network models of COVID-19 explain inequities and inform reopening.
Nature 2021; 589: 82–7.
40. Morawska L, Tang JW, Bahnﬂeth W et al. How can airborne
transmission of COVID-19 indoors be minimised? Environ
Int 2020; 142: 105832.
41. Shinozaki T, Suzuki E. Understanding marginal structuralmodels for time-varying exposures: pitfalls and tips. J Epidemiol 2020; 30: 377–89.
Received 1 September 2021;editorial decision 7 December
2021

9

Downloaded from https://academic.oup.com/ageing/article/51/3/afac022/6540137 by guest on 14 April 2022

14. Björnwall A, Mattsson Sydner Y, Koochek A, Neuman N.
Eating alone or together among community-living older
people-a scoping review. Int J Environ Res Public Health
2021; 18: 3495.
15. Kondo K. Progress in aging epidemiology in Japan: the JAGES
project. J Epidemiol 2016; 26: 331–6.
16. Son KY, Kwon H, Park JH et al. Association between weightchange over a period of 4 years and mortality in Korean older
adults. Geriatr Gerontol Int 2020; 20: 474–81.
17. Dey DK, Rothenberg E, Sundh V, Bosaeus I, Steen B. Body
mass index, weight change and mortality in the elderly. A 15
y longitudinal population study of 70 y olds. Eur J Clin Nutr
2001; 55: 482–92.
18. Yazawa A, Inoue Y, Kondo N et al. Accuracy of self-reported
weight, height and body mass index among older people inJapan. Geriatr Gerontol Int 2020; 20: 803–10.
19. Katanoda K, Matsumura Y. National Nutrition Survey inJapan–its methodological transition and current ﬁndings. J
Nutr Sci Vitaminol (Tokyo) 2002; 48: 423–32.
20. Tani Y, Kondo N, Takagi D et al. Combined eﬀects ofeating alone and living alone on unhealthy dietary behaviors,
obesity and underweight in older Japanese adults: results of
the JAGES. Appetite 2015; 95: 1–8.
21. Chae W, Ju YJ, Shin J, Jang S-I, Park E-C. Association
between eating behaviour and diet quality: eating alone vs.
eating with others. Nutr J 2018; 17: 117.
22. Kusama T, Nakazawa N, Kiuchi S, Kondo K, Osaka K, Aida
J. Dental prosthetic treatment reduced the risk of weightloss among older adults with tooth loss. J Am Geriatr Soc
2021; 69: 2498–2506.
23. Kinugawa A, Kusama T, Yamamoto T et al. Association ofpoor dental status with eating alone: a cross-sectional Japangerontological evaluation study among independent older
adults. Appetite 2021; 168: 105732.
24. Koyano W, Shibata H, Nakazato K, Haga H, Suyama Y.
Measurement of competence: reliability and validity of the
TMIG index of competence. Arch Gerontol Geriatr 1991; 13:
103–16.
25. Tomata Y, Sugiyama K, Kaiho Y, Sugawara Y, Hozawa A,
Tsuji I. Predictive ability of a simple subjective memory
complaints scale for incident dementia: evaluation of Japan’snational checklist, the ‘Kihon checklist’. Geriatr Gerontol Int
2017; 17: 1300–5.
26. Pocklington C, Gilbody S, Manea L, McMillan D. The diagnostic accuracy of brief versions of the Geriatric Depression
Scale: a systematic review and meta-analysis. Int J Geriatr
Psychiatry 2016; 31: 837–57.
27. Saito M, Aida J, Cable N et al. Cross-national comparison ofsocial isolation and mortality among older adults: a 10-year