Panel Data Research Center, Keio University
PDRC Discussion Paper Series

How did the COVID-19 pandemic affect the well-being of people living
alone in Japan? A comparison of older adults and their characteristics
Kazuma Sato, Ryotaro Fukahori, Yoshio Higuchi
9 March, 2024
DP2023-004
https://www.pdrc.keio.ac.jp/en/publications/dp/9001/

Panel Data Research Center, Keio University
2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
info@pdrc.keio.ac.jp
9 March, 2024

How did the COVID-19 pandemic affect the well-being of people living alone in Japan? A comparison of older
adults and their characteristics

Kazuma Sato, Ryotaro Fukahori, Yoshio Higuchi
PDRC Keio DP2023-004
9 March, 2024
JEL Classification: D1; I31
Keywords: living alone; well-being; COVID-19

Abstract
This study examines the association between living arrangements and older adults’ well-being
measured by happiness and K6 levels before and after the coronavirus disease 2019 (COVID-19)
pandemic using Japanese panel data. The data used in this study are from the Japan Household Panel
Survey, which are representative panel data. The study conducts surveys before and after the spreadof COVID-19. The differences-in-differences estimation that controls for individual fixed effects
generates three findings. First, the happiness of older men living alone decreased during the spreadof COVID-19. However, we did not find a significant impact of living alone among older women. Second,
when we used the detailed living arrangements variables, including living alone, living together as acouple, a couple living with others, and living without a spouse but with others, the well-being of men
living alone or living together as a couple worsened. Meanwhile, the well-being of women did not varysignificantly for either living arrangement. Last, additional analysis, including the sample of otherage groups, such as those under 39 years and 40–64 years, revealed that the mental health of women
under 39 years deteriorated when they lived alone during the COVID-19 pandemic. The overall
analysis shows distinct gender differences in the impact of living alone, and the adverse effects ofliving alone were substantial for older men and younger women.

Kazuma Sato
Faculty of Political Science, Takushoku University
Kohinata 3-4-14, Bunkyo-ku, Tokyo 112-8585
ksqwt864@gmail.com
Ryotaro Fukahori
Faculty of Economics, Chukyo University
101-2 Yagotohonmachi, Showa-ku, Nagoya, Aichi Prefecture
r.fukahori@gmail.com
Yoshio Higuchi
Faculty of Commerce, Keio University
2-15-45 Mita, Minato-ku, Tokyo
higuchi@fbc.keio.ac.jp

Acknowledgement: This research was supported by Grant-in-Aid for Scientific Research (22H04911,
JPJSJRP20211706). Additionally, the data used in this study was provided by the Keio University Panel
Data Design and Analysis Center. We would like to express our gratitude to them for their support.

How did the COVID-19 pandemic affect the well-being of people living alone in Japan? A comparisonof older adults and their characteristics
Authors: Kazuma Sato, Ryotaro Fukahori, Yoshio Higuchi

Corresponding author: Kazuma Sato
Faculty of Political Science, Takushoku University, Kohinata 3-4-14, Bunkyou-ku, Tokyo 112-8585, Japan
Tel.: +81-90-7016-2801
E-mail: Kazuma Sato (skazuma@ner.takushoku-u.ac.jp), Ryotaro Fukahori (r.fukahori@gmail.com), andYoshio Higuchi (higuchi@fbc.keio.ac.jp)

Acknowledgments: Data from the Japan Household Panel Survey were provided by the Panel Data
Research Center at Keio University.

Funding: This work was supported by JSPS Grants-in-Aid for Scientific Research (KAKENHI) in Japan(22H04911, JPJSJRP20211706).

1

Abstract
This study examines the association between living arrangements and older adults’ well-being measured byhappiness and K6 levels before and after the coronavirus disease 2019 (COVID-19) pandemic using
Japanese panel data. The data used in this study are from the Japan Household Panel Survey, which are
representative panel data. The study conducts surveys before and after the spread of COVID-19. The
differences-in-differences estimation that controls for individual fixed effects generates three findings. First,
the happiness of older men living alone decreased during the spread of COVID-19. However, we did not
find a significant impact of living alone among older women. Second, when we used the detailed living
arrangements variables, including living alone, living together as a couple, a couple living with others, andliving without a spouse but with others, the well-being of men living alone or living together as a couple
worsened. Meanwhile, the well-being of women did not vary significantly for either living arrangement.
Last, additional analysis, including the sample of other age groups, such as those under 39 years and 40–
64 years, revealed that the mental health of women under 39 years deteriorated when they lived alone during
the COVID-19 pandemic. The overall analysis shows distinct gender differences in the impact of living
alone, and the adverse effects of living alone were substantial for older men and younger women.

Keywords: living alone, well-being, COVID-19
JEL classification codes: D1, I31,

2

1. Motivation
The spread of coronavirus disease 2019 (COVID-19) has sparked a public health crisis worldwide. The
World Health Organization (WHO) declared the COVID-19 outbreak a public health emergency ofinternational concern on January 30, 2020, and many lives have been lost due to COVID-19. Many
governments have implemented countermeasures, such as stay-at-home policies, full lockdowns, and public
place closures, to control the spread of infection. Although these policies effectively reduced the spread of
COVID-19, they also restricted face-to-face communication, leading to social isolation, which can affectwell-being. Social isolation could negatively affect well-being because social relationships critically impact
our well-being (Hwang et al., 2020; Brodeur et al., 2021; Henssler et al., 2021). In addition, the extent of
the impact of social isolation may depend on two factors. The first factor is people’s age. As older adults
are vulnerable to social isolation (WHO 2020), the negative impact of COVID-19 could be highly
significant for these age groups. The second factor is living arrangements. As face-to-face communication
declined because of the spread of COVID-19, the importance of who people usually live with has increased.
Particularly, people living alone who lost the opportunity to talk with others could be negatively affected.
Considering these points, the adverse impact of a decline in face-to-face communication because of the
spread of COVID-19 may be substantial for older adults living alone. This study examines this point using
Japanese panel data obtained from two special surveys conducted in May–June and October–November
2020.
Increasing studies using data from EU countries have examined the impact of the COVID-19 pandemic
on the well-being of older people. However, this study focuses on the case of Japan because the household
structure for older people in this country has changed in recent decades. Moreover, the number of older
people living alone has increased. According to the Comprehensive Survey of Living Conditions conductedby the Ministry of Health, Labor, and Welfare, the ratio of one-person households among those with persons
aged 65 and over was 13% in 1985. This ratio has increased gradually and reached 29% in 2019. Based on
this result, several older people live alone and are expected to be affected by the spread of COVID-19. We
empirically examine how the well-being of older people living alone varied during the first and second
waves of the COVID-19 pandemic relative to the pre-COVID-19 period.
The literature examining the effect of the COVID-19 pandemic on well-being has been rapidly growing.
Studies have reported that the spread of COVID-19 has deteriorated the well-being of people (Vindegaard& Benros, 2020; Wang et al., 2020; Xiong et al., 2020). In addition, the number of studies focusing on theassociation between the COVID-19 pandemic and the well-being of older people has recently increased.
For example, Mendez-Lopez et al. (2022) examined how the mental health of people over 50 years changed
during the COVID-19 pandemic based on the stringency of pandemic responses and protection. They
showed that the mental health of people in countries with great stringency of physical distancing decreased.
However, the decline in the mental health of people in countries with high social protection expenditures
was alleviated. García-Prado et al. (2022) investigated the causal association between the well-being of3

people over 50 years old and lockdown policies. They revealed that insomnia, anxiety, and depression
deteriorated because of the lockdown policies. They also found a heterogeneous impact of lockdown
policies and showed that the negative effect was strong for women, those aged between 50 and 65, andpeople living alone. Litwin and Levinsky (2021) examined the relationship between social networks andthe mental health of people over 50 years. They reported that although face-to-face communication was
positively related to mental health, electronic communication had adverse effects.
Although some studies focused on the effect of living arrangements of older people on their well-being
during the COVID-19 pandemic, the number of studies is limited. Berniell et al. (2023) examined the impactof the COVID-19 pandemic on the well-being of people over 50 years varied based on their living
arrangements and housing conditions. Using data from European countries, they showed that older people
living alone or living only with a spouse experienced worsening depression, loneliness, and trouble sleeping
in the first wave of the pandemic. Meanwhile, having children in the same building improved those
symptoms. Atzendorf and Gruber (2021) analyzed the impact of individual attributes and macroindicators
using the Oxford COVID-19 Government Response Tracker on the mental health of older adults, including
retired respondents over 60 years. Their study, which used data from European countries, showed that
although macroindicators and individual attributes deteriorated mental health, the magnitude of individual
attributes was more substantial than the former. In addition, they found that the mental health of older adults
declined when they lived alone after the first wave of the COVID-19 pandemic. Ryu et al. (2022)
investigated changes in social relationships and mental health of older adults living alone before and after
the pandemic. Their study, which used data from South Korea, revealed that although social activity andinteraction with neighbors declined, interaction with family members improved. In addition, they foundthat depression and suicide ideation did not significantly change during the pandemic. Meanwhile, Noguchi
et al. (2023) examined the association between living alone and depressive symptoms in older people over
65 years. They focused on the moderating effect of non-face-to-face social interactions, including phone
calls or emails with families or friends. Empirical analysis using Japanese data indicated that althoughliving alone worsened depressive symptoms, non-face-to-face social interactions alleviated the adverse
effects of living alone. The aim of their study coincides with that of the present study. However, their study
employed data from one city in Japan, Minokamo City, and there is a risk that the analysis is based on datathat are not representative. In addition, their study did not control for the individual fixed effect (FE), which
may lead to biased estimates.
This study examines the association between living arrangements and older adults’ well-being measured
by happiness and K6 levels before and after the COVID-19 pandemic using the Japan Household Panel
Survey (JHPS/Keio Household Panel Survey (KHPS)). JHPS/KHPS is representative panel data conducted
before the COVID-19 pandemic. The differences-in-differences (DID) estimation that controls forindividual FEs generates three findings. First, the happiness of older men living alone decreased during the
COVID-19 pandemic. However, we did not find a significant impact of living alone among older women.

4Second, when we used the detailed living arrangements variables, including living alone, living together asa couple, a couple living with others, and living without a spouse but with others, the well-being of men
living alone or living together as a couple worsened. Meanwhile, the well-being of women did not varysignificantly for either living arrangement. Last, additional analysis, including the sample of other age
groups, such as those under 39 years and 40–64 years, revealed that the mental health of women under 39
years deteriorated when they lived alone during the COVID-19 pandemic. The overall analysis shows thegender difference in the impact of living alone, that is, the adverse effects of living alone were substantial
for older men.
The remainder of this paper is organized as follows. Section 2 explains the data, and Section 3 describes
the empirical strategy. Finally, Section 4 discusses the estimation results, and Section 5 concludes the study.

2. Data
The JHPS/KHPS data integrate the Keio Household Panel Survey (KHPS) and the Japan Household
Panel Survey (JHPS) conducted by the Panel Data Research Center at Keio University. The KHPS started
in 2004 and covers 4,000 men and women aged 20–69 years. The JHPS survey began in 2009 and covered
4,000 men and women aged 20 years. Both data are surveyed annually, and the survey targets are selectedusing a stratified two-stage random sampling method. Both surveys had high similarities in survey items
and survey methods and were conducted by the same research institution; therefore, they were merged in2014 and renamed JHPS/KHPS. JHPS/KHPS has a questionnaire about education, well-being, health, andmedical care, including economic and employment status.
As the ordinal survey period of JHPS/KHPS is January each year, the latest survey before the spread of
COVID-19 is January 2020. JHPS/KHPS conducted two special surveys in May–June (special survey 1)
and October–November (special survey 2) 2020 to investigate the impact of the COVID-19 pandemic. In
special surveys, changes related to COVID-19 and shortened regular survey items were asked.
The first confirmed COVID-19 case in Japan was announced in January 2020, and the first death occurredin February 2020. The first wave of the COVID-19 pandemic was from March to June 2020, and the second
wave was from July to October 2020. The JHPS/KHPS 2020 survey was conducted just before the spreadof COVID-19, and special survey 1 was conducted during the first wave. Special survey 2 corresponds tothe second wave period. Additionally, in Japan, the government declared a state of emergency from April
to May 2020, requiring people to refrain from going out unless necessary, requiring restaurants to close,
and restricting the use of schools and welfare facilities. With the rapid increase in the number of infected
people, together with the declaration of a state of emergency during the first wave of the COVID-19
pandemic, people’s stress and anxiety are expected to increase.
This study mainly focuses on men and women over 65 years old.1 The estimations are conducted by

Elderly persons are usually defined as individuals aged 65 and over by institutions such as the OECD and WHO.
Following this definition, we analyze a sample of people over 65.
1

5

gender because some previous studies, such as García-Prado et al. (2022) and Pierce et al. (2020), havereported gender differences in the impact of the COVID-19 pandemic. We use happiness and K6 as
measures of well-being. As both variables are available after 2019, we restrict the sample of men andwomen over 65 in 2019 and 2020 in special survey 1 (May–June 2020) and special survey 2 (October–
November 2020). The wave-person observations for men are 2,428, and the sample size for women is 2,583.

3. Estimation method and variables
3.1 Estimation method
This study aims to examine the effect of living arrangements, particularly living alone, on the well-beingof older adults during the COVID-19 pandemic. We estimate the following FE ordinary least squares (OLS)
to investigate this association.

𝑀𝐻𝑖𝑡 = 𝛼𝐿𝑖𝑡 + 𝛽𝐶𝑂𝑉𝐼𝐷𝑖𝑡 + 𝛾𝐿𝑖𝑡 ∗ 𝐶𝑂𝑉𝐼𝐷𝑖𝑡 + 𝛿𝑋𝑖𝑡 + 𝜇𝑖 + 𝜀𝑖𝑡(1)where 𝑀𝐻𝑖𝑡 indicates happiness and k6 of individual i at time t. 𝐿𝑖𝑡 indicates the living alone dummy
and 𝐶𝑂𝑉𝐼𝐷𝑖𝑡 is assigned a value of 1 for the wave of special survey 1 and 0 for special survey 2.
𝐿𝑖𝑡 ∗ 𝐶𝑂𝑉𝐼𝐷𝑖𝑡 is an interaction term between the living alone dummy and the COVID-19 period dummy
to examine how the impact of living alone on the well-being of older adults changed before and after the
COVID-19 pandemic. This process is a simple DID estimation. The estimated coefficient 𝛾 is the primary
focus of this analysis. A positive 𝛾 indicates that older adults living alone had great well-being during the
COVID-19 pandemic. Meanwhile, a negative 𝛾 indicates that older adults living alone had worse wellbeing during the COVID-19 pandemic. We estimate this coefficient using FE OLS and determine theoutcome. 𝑋𝑖𝑡 indicates individual attributes, including age, subjectively rated health, marriage, children,
education, and working status. 𝜇𝑖 shows the individual FE, and 𝜀𝑖𝑡 is the error term.
In this analysis, the reverse causality between well-being and living arrangements may be a concern.
Although we assume that living arrangements affect the well-being of older adults, well-being may impact
the type of housing people choose. For example, if people with worse well-being tend to select living alone,
the coefficient of living alone can be negatively overestimated. However, the prime interest of this study isthe change in the effect of living arrangements before and after the COVID-19 pandemic, which is
unexpected and considered a natural experiment. In addition, this study employs an FE model that cancontrol for individual FEs. Therefore, the impact of reverse causality may be mitigated.

3.2 Well-being outcomes
We use happiness and K6 as measures of well-being. The following question measures happiness: Pleaseprovide answers as to how your feeling of happiness was during the following periods, on a scale of 0 to
10, with 0 being “having no feeling of happiness at all,” and 10 being “having a feeling of complete

6happiness.” The respondents answered this question from 0 to 10, where a high number indicates greathappiness. Regarding K6, respondents were asked the following questions: During the past 30 days, howoften did you feel nervous, hopeless, restless, or fidgety, so depressed that nothing could cheer you up, thateverything was an effort, and worthless? For each question, respondents select the answer from “1 = All of
the time” to “5 = None of the time.” We sum the answers to the six questions and use them as the dependent
variable, showing that a high number indicates excellent mental health.

3.3 Living arrangements and individual attributes
For the living arrangements variable, we use a living alone dummy, which is assigned a value of 1 if
respondents live alone and 0 if otherwise. In addition, our analysis uses age, subjectively rated health,marriage, children, and working status as individual attributes. Age dummies are categorized as 65–69, 70–
79, and over 80 years. Subjectively rated health is the variable evaluating the respondent’s health from 1 =bad to 5 = good. The marriage dummy is assigned a value of 1 if the respondent is married and 0 if otherwise.
The having children dummy is assigned a value of 1 if the respondent has any children and 0 if otherwise.
The working status is the dummy variable, which is assigned a value of 1 if the respondent is employed and
0 if otherwise. Table 1 shows the summary statistics of the variables by gender.

3.4 Descriptive statistics of well-being before and after the COVID-19 pandemic
Figure 1 shows the change in well-being before and after the COVID-19 pandemic by gender. Figure 1(a) and (b) show the results for men, and Figure 1 (c) and (d) are the results for women. As shown in Figure
1 (a), the happiness of older men differs by living arrangement. Compared with older men living with others,
the average happiness of older men living alone was lower than that before the spread of COVID-19 andsubstantially declined during special survey 1 when the COVID-19 cases rapidly increased. The happinessof older men living alone recovered during special survey 2. The result of Figure 1 (a) indicates that thedifference in happiness by living arrangements magnified, particularly during the first wave of the COVID19 pandemic. Figure 1 (b) shows a similar trend, that is, the mental health of men living alone was poor
before the COVID-19 pandemic and deteriorated further at the time of special survey 1 and then recoveredat the time of special survey 2. Different results can be found when we look at the figures for women. Figure
1 (c) shows that average happiness was almost similar in living arrangements before and after the COVID19 pandemic. This case also is the same with the mental health results, as shown in Figure 1 (d), indicatingthat almost no differences exist between the women living alone and those living with others.
Figure 1 shows that the differences in well-being based on the living arrangement were distinct, mainly
for men. This result leads us to expect that the negative impact of living alone will be substantial for men
and not women.

4. Estimation results

74.1 Base result
Table 2 shows the results of the FE OLS. Columns (1) and (2) indicate the men’s results, and columns(3) and (4) show the women’s results. Happiness is used as the dependent variable in columns (1) and (3),and K6 is used as the dependent variable in columns (2) and (4). In the analysis, all individual attributes areused in addition to the variables shown in Table 1. The primary interest in Table 2 is the coefficients of theinteraction term between living alone and the COVID-19 period dummy. In the men’s results, thecoefficient of the interaction term is negatively significant for happiness, which indicates that the happinessof older men living alone decreases during the COVID-19 pandemic. Meanwhile, the interaction term is
not statistically significant for K6, showing that the mental health of older men living alone does not
significantly change during the COVID-19 pandemic. In the results for women, we cannot find significant
coefficients of the interaction term. This result indicates that women living alone during the COVID-19
pandemic did not experience significant changes in well-being.
Table 3 indicates the result of splitting the COVID-19 dummy into two-period dummies: the special
survey 1 (May–Jun 2020) and special survey 2 (Oct–Nov 2020) dummies. The result is almost the same asthat in Table 2, and the interaction terms between living alone and COVID-19 dummies are negatively
significant only for men’s happiness. Both interaction terms are negatively significant, revealing that thehappiness of older men living alone deteriorates in special surveys 1 and 2. The magnitude of the coefficientis larger for the special survey 1 period, showing a substantial decline in the happiness of older men during
the first wave of the pandemic when the number of infected people increased rapidly. Meanwhile, forwomen, all coefficients of the interaction terms between living alone and COVID-19 dummies were notstatistically significant, indicating that the well-being of older women living alone did not change for both
special survey periods.
The results in Tables 2 and 3 indicate the gender difference in the effect of living alone during the
COVID-19 pandemic. The negative impact of living alone is significant only for men. This result isinteresting because some previous studies have pointed out the opposite effect, which means a more
substantial negative impact of living alone for women than men (García-Prado et al. 2022; Pierce et al.
2020). Why is there such a difference? The reason may be that older men in Japan living alone tend to havelower well-being and higher mortality rates (Ishikawa 1990; Matsuura & Ma 2022), and their social
networks with the community and friends are weaker than women (Kino et al., 2023; Raymo 2015). Oldermen living alone, who already have vulnerable social networks, are thought to have become even moreisolated because of the spread of COVID-19, worsening their well-being.
Meanwhile, older Japanese women are likely to feel happy when they live alone (Matsuura & Ma, 2022).
The reason is that a sense of gender division of labor still exists in Japan, and women have a heavy burdenof housework. However, living alone allows them to escape this burden. Older women living alone werealso expected to experience a decline in communication with others during the COVID-19 pandemic, but
the actual negative impact of restricted communication was slight. One of the reasons may be that they8compensated for the decrease in contact by means such as telephone and email. As Noguchi et al. (2023)
pointed out, the decline in well-being of older Japanese over 65 years who live alone was low when theyused communication tools, including telephone and email. Perhaps, older women living alone used thephone and email frequently to contact friends or family, preventing a decrease in well-being.

4.2 Robustness check
We conduct three robustness checks. First, we exclude subjectively rated health from independent
variables because subjectively rated health is one of the well-being indicators and may cause bias in theestimate owing to the correlation with the dependent variable. Columns (1)–(4) of Table 4 present theestimated results. The result of the interaction term between living alone and the COVID-19 period dummyis the same as that in Table 2, indicating a significant decline in well-being only in the case of men’shappiness. Second, we use other estimation methods. We use the FE ordered logit model because happinessand K6 are ordinal variables. Columns (5)–(8) of Table 4 show the estimated results. We find results similar
to those in Table 2, showing that the interaction term between living alone and the COVID-19 period
dummy is negatively significant only for men’s happiness. Finally, we changed the age range for the
analysis sample to check whether the impact of living alone during the COVID-19 pandemic varied. We
estimate the FE OLS by changing the age range to three years before and after 65 years. Table 5 shows theresults, and the trend of the result hardly changes with respect to Table 2. In addition, notably, the magnitudeof the coefficients of the interaction term between living alone and the COVID-19 dummy in men’shappiness slightly increases with age. This result indicates that the older a man lives alone, the greater his
decline in happiness during the COVID-19 pandemic.

4.3 Additional analysis
In this section, we conduct two additional analyses. First, we use the detailed living arrangement
variables. Following Berniell et al. (2023), four living arrangements dummies, such as living alone, living
together as a couple, a couple living with others, and living without a spouse but with others, were used as
independent variables to assess how living arrangements other than living alone affect the well-being ofolder people during the COVID-19 pandemic2. Table 6 shows the estimated results using the FE OLS and
FE ordered logit models. Columns (1)–(4) present the results for men, and columns (5)–(8) show the results
for women. In this analysis, we are interested in the interaction terms between living arrangements dummies
and COVID-19 period dummies. In columns (1) and (2), using happiness as the dependent variable, only
the interaction term between living alone and the COVID-19 period dummy is negatively significant. ThisThe reference group of the living arrangement dummies is the dummy for living without a spouse but with others.
The composition ratio of living arrangement dummies for men is as follows: living alone (12.0%), living together as acouple (51.3%), a couple living with others (33.3%), and living without a spouse but with others (3.4%). In addition,
the composition ratio of living arrangements dummies for women is as follows: living alone (21.8%), living together
as a couple (40.1%), a couple living with others (21.0%), and living without a spouse but with others (17.1%).
2

9

result is in line with the findings in Table 2. Meanwhile, only the interaction term between living together
as a couple and the COVID-19 period dummy is negatively significant, as shown in columns (3) and (4),using K6 as the dependent variable. This result indicates that older men living only with their spouses haveworse mental health. This result is consistent with the findings of Berniell et al. (2023), who indicated thatolder people living together as a couple are more likely to be depressed, feel lonely, and have trouble
sleeping. The reason for the adverse effects of living together as a couple may be that people spend lesstime going out owing to the spread of COVID-19, which increases stress as the couple spends more timealone. This interpretation contrasts with the prediction of Hamermesh (2020), who indicates a positive
association between life satisfaction and time spent together by married individuals. However, it isconsidered appropriate when freedom of movement is restricted because of COVID-19. From anotheraspect, women’s results show no significant coefficients between living arrangements and COVID-19
period dummies. This result indicates that the well-being of older women was not affected by living
arrangements even during the COVID-19 pandemic. However, notably, the coefficients of the COVID-19
period dummy are negatively significant, indicating that women’s well-being declined during the COVID19 epidemic. In other words, although the well-being of all older women decreased during the COVID-19
pandemic, substantial differences in well-being did not occur depending on living arrangements.
The results in Table 6 show the distinct gender differences in the effect of living arrangements. Oldermen living alone or with their spouses are negatively affected by the spread of COVID-19, whereas older
women are intact in the same situation. These women’s results are intriguing as previous studies have founda conspicuously negative impact of living arrangements on women. In Japan, using remote communication
tools such as phone and email by older people may cover the decrease in the opportunity to contact others,
preventing the effects of living arrangements (Noguchi et al. 2023).
In the second additional analysis, we used other age groups to compare the impact of living alone. Twoage groups, namely, young people under 39 years old and middle-aged people between 40 and 64 years old,
were used in the estimate. Table 7 shows the results estimated using the FE OLS and FE ordered logit model.
Panel (A) of Table 7 indicates the result of a sample less than 39 years old, and panel (B) of Table 7 showsthat of 40–64 years old. In both panels, columns (1)–(4) show the results for men, and columns (5)–(8)indicate the results for women.
The results for men in panel (A) of Table 7 indicate no significant coefficients of the interaction term
between living alone and the COVID-19 dummy. Meanwhile, the results of women in panel (A) of Table 7
show negatively significant coefficients of the interaction term with K6. This result indicates that women
living alone under the age of 39 years have relatively worse mental health during the COVID-19 pandemic.
This result contrasts with the finding of older women over 65, that is, living alone during the COVID-19
pandemic has no significant impact. The negative impact may be caused by the harsh conditions faced byyoung women. As younger women tend to work in nonregular employment and face economic instability
during the COVID-19 pandemic, they are likely to experience stress. This stress could be magnified in10

young women who lived alone and were likely to feel loneliness. In this regard, suicide statistics by the
National Police Agency have reported that the suicide rate of young women has risen during the COVID19 pandemic. The results of men in panel (B) of Table 7 indicate that middle-aged men living alone did notexperience a change in well-being during the COVID-19 pandemic. Meanwhile, the interaction terms
between living alone and the COVID-19 dummy show positively significant coefficients to K6 for women.
This result indicates that middle-aged women living alone had great mental health during the COVID-19
pandemic.
The results in Table 7 show the distinct gender differences in the effect of living arrangements, as in
Table 6. Although young and middle-aged men did not experience a change in well-being based on theirliving arrangements during the COVID-19 pandemic, the mental health of younger women living alone
deteriorated. The negative impact on younger women may be attributed to economic instability owing to
the COVID-19 pandemic, and this result coincides with a rise in the suicide rate among younger women.

5. Conclusion
This study investigated the relationship between living arrangements and the well-being of older adults
during the COVID-19 pandemic. Although research examining the effect of the spread of COVID-19 has
been increasing, studies investigating the impact of living arrangements on older adults are limited. In
addition, regarding Japanese research, there are issues with the representativeness of data. We analyze theeffect of living arrangements using Japanese panel data by addressing these issues. The analysis using the
FE models generates three findings. First, the happiness of older men living alone deteriorated during the
spread of COVID-19, whereas the well-being of older women did not change significantly regardless ofwhether they lived alone. Second, the estimates using the detailed living arrangements variables showedthat although the men’s well-being of living alone or living together as a couple worsened, the women’swell-being did not vary significantly for either living arrangement. Last, additional analysis, including thesample of other age groups, such as those under 39 years and those 40–64 years, revealed that the mental
health of women under 39 years deteriorated when they lived alone during the COVID-19 pandemic.
The overall analysis shows distinct gender differences in the impact of living alone. The adverse effects
of living alone were highly pronounced for men in the older age groups and women in the younger age
groups. The result of substantial adverse effects for older men is intriguing, as previous studies using
European countries have shown a considerable negative impact on older women. The gap in the results may
be caused by the fact that older Japanese men tend to be socially isolated (Kino et al., 2023). Older Japanese
men were likely to be socially isolated before the pandemic, and this social isolation could have deepened
further due to COVID-19. These differences in the environment surrounding older people between
countries may have led to differences in the effects of living alone.
The findings of this study lead to policy implications in the context of COVID-19. Social isolation
because of the COVID-19 pandemic was an issue, and its impact was expected to be substantial for older

11people. Although this expectation was reasonable, the negative impact was highly prominent in older men.
Therefore, providing care that focuses on older men living alone is essential. By contrast, for young women
living alone, economic insecurity owing to unstable employment environments caused a decline in wellbeing. The government’s employment stabilization measures have effectively addressed this problem. Thus,
differences exist in the necessary policies depending on age groups and gender, and this research contributes
by clarifying this point.
This study has several strengths, such as the representativeness of data, its longitudinal nature, which cancompare the same respondents before and after the COVID-19 pandemic, and the use of representativewell-being indicators, such as happiness and K6. However, the study has some limitations. First, the data
used in this study do not survey the mental health measures, such as depression, loneliness, and trouble
sleeping, which are employed in European studies. Therefore, making strict comparisons with the resultsof previous studies is difficult because the effect of living alone can change depending on the indicators
used in the study. Furthermore, this study examined the impact of COVID-19 in 2020 and failed to analyze
the changes in the impact since then. Whether the effects of the COVID-19 pandemic will be long-lastingis a critical issue, and research using long-term data is needed.

12References

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14

Table 1 Summary statistics

Men
Variables

Women

Mean

SD

Mean

SD

Happiness

6.101

2.075

6.261

2.118

K6

26.4993.671

25.863

4.003

Living alone

0.120

0.325

0.218

0.413

COVID

0.369

0.483

0.339

0.474

COVID*Living alone

0.039

0.194

0.067

0.251

Age 65-69

0.333

0.471

0.304

0.460

Age 70-79

0.536

0.499

0.568

0.496

Age 80+

0.131

0.337

0.129

0.335

Subjective rated health

3.312

0.967

3.329

0.929

Marriage

0.859

0.348

0.634

0.482

Having children

0.847

0.360

0.866

0.341

Working

0.437

0.496

0.318

0.466

2,428

N

15

2,583

Figure 1 (b) K6: men

Figure 1 (a) Happiness: men
7.00

27.50

Living alone

Living alone

Living with others

6.50

Living with others

27.00

6.00

26.50

5.50
26.00

5.00
25.50
4.50

25.00
4.00
24.50
3.50
2019

2020

S P EC I ALS URVE Y1

S P EC I ALS URVE Y2

24.00
2019

2020

Figure 1 (c) Happiness: womenS P EC I ALS URVE Y1

S P EC I ALS URVE Y2

Figure 1 (d) K6: women
27.50

7.00

Living alone

Living alone

Living with others

6.50

27.00

6.00

26.50

5.50

26.00

5.00

25.50

4.50

25.00

4.00

24.50

3.50

Living with others

24.00
2019

2020

S P EC I ALS URVE Y1

S P EC I ALS URVE Y2

2019

16

2020

S P EC I ALS URVE Y1

S P EC I ALS URVE Y2

Table 2 Effect of living alone on the well-being of older adults

(1)

(2)

(3)

Men

(4)
Women

Happiness

K6

Happiness

K6-0.579**

0.126

0.176

0.191

(0.242)(0.499)(0.186)(0.391)0.176

1.779**

0.203

0.088

(0.469)(0.709)(0.632)(1.122)-0.275***-1.245***-0.538***-1.691***(0.076)(0.151)(0.084)(0.181)

Estimation method

FE OLSFE OLSFE OLSFE OLS

Observations

2,428

2,428

2,583

2,583

R-squared

0.039

0.077

0.043

0.097

Living alone×COVID
Living alone
COVID

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

17

Table 3 Effect of living alone on the well-being of older adults using the split COVID-19 period dummies

(1)

(2)

(3)

Men

(4)
Women

Happiness

K6

Happiness

K6-0.717**-0.261

0.136

0.169

(0.299)(0.613)(0.204)(0.420)-0.429*

0.546

0.204

0.183

(0.253)(0.488)(0.216)(0.458)0.153

1.720**

0.178

0.033

(0.474)(0.729)(0.639)(1.127)-0.375***-1.450***-0.725***-2.121***(0.085)(0.184)(0.101)(0.214)-0.168*-1.025***-0.331***-1.212***(0.088)(0.162)(0.095)(0.202)Estimation method

FE OLSFE OLSFE OLSFE OLS

Observations

2,428

2,428

2,583

2,583

R-squared

0.044

0.084

0.053

0.110

Living alone×COVID(May-Jun)
Living alone×COVID(Oct-Nov)
Living alone
COVID(May-Jun)
COVID(Oct-Nov)

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

18

Table 4 Robustness check for the effect of living alone on the well-being of older adults

(1)

(2)

(3)

(4)

(5)

(6)

Excluding the subjective rated health
Men

(7)

(8)

Using FE ologit model

Women

Men

Women

Happiness

K6

Happiness

K6

Happiness

K6

Happiness

K6-0.589**

0.109

0.138

0.109

-0.823**

0.203

0.280

0.148

(0.240)(0.498)(0.189)(0.398)(0.337)(0.410)(0.287)(0.297)0.151

1.737**

0.227

0.139

-0.254

1.613**

0.086-0.107(0.466)(0.779)(0.640)(1.161)(0.780)(0.760)(0.916)(0.653)-0.196***-1.114***-0.471***-1.546***-0.450***-1.092***-0.829***-1.230***(0.075)(0.143)(0.083)(0.180)(0.125)(0.133)(0.131)(0.137)

Estimation method

FE OLSFE OLSFE OLSFE OLS

FE Ologit

FE Ologit

FE Ologit

FE Ologit

Observations

2,428

2,428

2,583

2,583

1,905

2,000

1,933

2,175

R-squared
Log conditional likelihood

0.023

0.064

0.032

0.085
-1625.201-2795.516-1679.408-3290.275

Living alone×COVID
Living alone
COVID

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

19

Table 5 Robustness check using samples aged 3 and 65 years before and after the pandemic
Panel (A) Men

Living alone×COVID
Living alone

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

age>=62age>=63age>=64age>=66age>=67age>=68age>=62age>=63age>=64age>=66age>=67age>=68

Happiness

Happiness

Happiness

Happiness

Happiness

Happiness

K6

K6

K6

K6

K6

K6

-0.515**-0.524**-0.544**-0.555**-0.603**-0.637**

0.193

0.193

0.148

0.290

0.007

-0.228(0.221)(0.231)(0.233)(0.256)(0.279)(0.308)(0.438)(0.448)(0.456)(0.512)(0.550)(0.636)2.050**

0.525

0.536

0.084

0.078

0.110

0.177

1.239**

1.288**

1.735**

1.725**

1.901**(0.484)(0.487)(0.429)(0.432)(0.441)(0.465)(0.625)(0.645)(0.748)(0.778)(0.807)(0.815)-0.263***-0.269***-0.243***-0.275***-0.263***-0.297***-1.207***-1.185***-1.203***-1.291***-1.238***-1.207***(0.066)(0.068)(0.070)(0.076)(0.080)(0.084)(0.137)(0.140)(0.144)(0.158)(0.164)(0.170)Estimation method

FE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLS

Observations

2,876

2,737

2,596

2,272

2,103

1,958

2,876

2,737

2,596

2,272

2,103

1,958

R-squared

0.042

0.047

0.044

0.045

0.050

0.057

0.081

0.083

0.086

0.095

0.095

0.093

COVID

Panel (B) Women

Living alone×COVID
Living alone

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

age>=62age>=63age>=64age>=66age>=67age>=68age>=62age>=63age>=64age>=66age>=67age>=68

Happiness

Happiness

Happiness

Happiness

Happiness

Happiness

K6

K6

K6

K6

K6

K6

0.194

0.172

0.120

0.104

0.097

0.066

0.192

0.138

0.052

-0.107-0.112-0.198(0.180)(0.179)(0.179)(0.190)(0.199)(0.206)(0.360)(0.363)(0.369)(0.390)(0.409)(0.425)

0.124

0.150

0.177

0.148

-0.064-0.062-0.019

0.108

0.194

-0.035-0.412-0.466(0.571)(0.571)(0.571)(0.678)(0.760)(0.758)(0.943)(0.958)(0.956)(1.117)(1.254)(1.250)-0.521***-0.540***-0.544***-0.565***-0.569***-0.557***-1.637***-1.740***-1.765***-1.707***-1.740***-1.678***(0.075)(0.077)(0.081)(0.087)(0.090)(0.093)(0.160)(0.165)(0.174)(0.186)(0.197)(0.207)

Estimation method

FE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLSFE OLS

Observations

3,074

2,905

2,748

2,457

2,306

2,149

3,074

2,905

2,748

2,457

2,306

2,149

R-squared

0.043

0.047

0.047

0.053

0.055

0.057

0.108

0.113

0.118

0.118

0.121

0.118

COVID

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

20

Table 6 Effect of living arrangements on the well-being of older adults
(1)

(2)

(3)

(4)

(5)

Men

(6)

(7)

(8)

K6

K6

Women

Happiness Happiness

K6

K6-0.946**-1.347**-0.970-0.7320.062-0.011

0.383

0.313

(0.459)(0.630)(0.806)(0.674)(0.259)(0.350)(0.483)(0.371)

Living only with a couple-0.543-0.870-1.224*-1.133**-0.150-0.405

0.057

0.031

×COVID
couple living with others(0.411)(0.580)(0.665)(0.562)(0.233)(0.311)(0.401)(0.312)-0.468-0.660-1.125-0.905-0.059-0.232

0.712

0.576

×COVID(0.421)(0.586)(0.690)(0.578)(0.249)(0.338)(0.521)(0.379)

Living alone

0.125-0.124

1.863

1.195

-0.038-0.210-1.287-1.313(0.701)(1.304)(1.518)(0.811)(0.726)(1.015)(1.017)(0.994)

0.441

0.419

0.238

-1.137-0.879-1.512-3.828**-2.373**(0.855)(1.574)(1.608)(1.368)(0.795)(1.184)(1.723)(1.038)

0.352

0.536

0.370

-1.099-0.996-1.819-3.670**-2.396**(0.848)(1.521)(1.613)(1.370)(0.766)(1.198)(1.685)(0.989)

0.217

0.291

-0.102-0.090-0.451**-0.585**-1.921*** -1.423***(0.403)(0.559)(0.641)(0.540)(0.205)(0.246)(0.337)(0.261)

Estimation method

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

Observations

2,428

1,905

2,428

2,000

2,583

1,933

2,583

2,175

R-squared
Log conditional likelihood

0.036

Living alone×COVID

Living only with a couple
couple living with others

COVID

0.079

Happiness Happiness

0.044-1631.264-2786.771

0.104-1674.602-3263.524

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

21

Table 7 Effect of living alone on the well-being of young and middle-aged people
Panel (A) under 39 years old
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Happiness

K6

K6

Men
Happiness
Living alone×COVID

Happiness

Women
K6

K6

Happiness-0.373-0.324-0.660-0.484

0.331

0.310

-1.938*-0.935*(0.429)(0.440)(0.616)(0.400)(0.408)(0.460)(1.106)(0.527)-1.069-0.927

0.176

0.111

1.433**

2.043**

0.073

0.253

(0.667)(0.605)(1.080)(0.689)(0.704)(0.853)(1.719)(0.853)-0.373**-0.458**-0.917***-0.580***-0.387***-0.424***-1.123***-0.678***(0.151)(0.183)(0.300)(0.180)(0.142)(0.157)(0.272)(0.169)Estimation method

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

Observations

1,837

1386

1,837

1426

1,962

1578

1,962

1626

R-squared
Log conditional likelihood

0.020

Living alone
COVID

0.027

0.026

-1447.306-2850.281

0.038-1736.840-3120.550

Panel (B) 40 to 64 years old
(1)

(2)

(3)

(4)

(5)

(6)

Men
Happiness
Living alone×COVID
Living alone

Happiness

(7)

(8)

K6

K6

Women
K6

K6

Happiness

Happiness

0.077

0.119

0.099

0.077

0.139

0.234

0.863*

0.605*(0.226)(0.308)(0.450)(0.305)(0.254)(0.324)(0.459)(0.320)

0.637

0.663

0.285

0.137

0.672

0.890

-0.382-0.547(0.632)(0.667)(0.927)(0.550)(0.773)(0.889)(0.578)(0.561)-0.383***-0.537***-1.136***-0.850***-0.667***-0.893***-2.013***-1.394***(0.092)(0.133)(0.171)(0.133)(0.084)(0.115)(0.166)(0.117)

Estimation method

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

FE OLS

FE Ologit

Observations

3,781

3043

3,781

3143

4,236

3459

4,236

3768

R-squared

0.019

COVID

Log conditional likelihood

0.038

0.052

-2837.967-5177.256

0.087-3358.747-6512.914

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Heteroscedasticity robust standard errors are reported in parentheses.

22