1. Introduction
The COVID-19 pandemic had a profound impact on many aspects of peoples’ psychological conditions, including loneliness. Several studies report that loneliness among both younger and older people has considerably increased during the pandemic due to maintaining virus mitigating measures such as social distancing, self-isolation, shelter in place, work from home, etc. [
1,
2,
3,
4,
5,
6,
7]. The uncertainties and mitigating measures surrounding the pandemic have changed peoples’ normal lifestyle and social relationships in such a way that their psychological conditions and loneliness have become vulnerable. The concern about loneliness among older people is particularly worrying due to their living status, need for long-term care, and vulnerable physical and mental health conditions [
8,
9,
10].
Loneliness is a psycho-sociological state of mind in which a person feels a lack of companionship or social connectedness quantitatively, qualitatively, or both. Social connectedness is a fundamental requirement that provides mental soundness. The literature defines loneliness as the unpleasant subjective experience that occurs when a person’s desire for social relations is deficient, either quantitatively or qualitatively [
11,
12,
13]. Loneliness is not similar to living alone or social isolation, although these factors could contribute to loneliness. As a subjective feeling, people may experience loneliness even when they are physically accompanied and socially connected. Cacioppo and Patrick [
14] argue that the mere presence of others does not make people feel less lonely; rather, they need the presence of someone whom they trust and can share common goals, plan for future, and work together to survive and prosper. In this study, we perceive loneliness as peoples’ subjective feeling of being isolated, left out, and lack of companionship. Loneliness appears across various demographic and socio-economic groups [
15,
16] and is intensifying due to social issues such as lower rates of marriage, fewer children in families, and shrinking household sizes [
15,
16,
17]. The recent COVID-19 pandemic clearly disrupted social connectedness, causing people to be lonelier [
18,
19].
Understanding loneliness is important for its connection with mental and physical health and the consequent economic outcomes. Social isolation and the feeling of loneliness lead to feelings of continuous stress and depression, creating physiological changes connected to the immune system and inflammatory responses, which further exacerbate physical and mental health conditions [
13,
15,
16,
20,
21]. Previous studies also provide evidence that loneliness is associated with mental health conditions such as chronic stress [
22]; anxiety and anger [
23]; depression and neuroticism [
12,
13,
24]; lower cognition, dementia, and Alzheimer’s disease [
25,
26,
27]; and so on. Loneliness is associated with physical health conditions such as higher inflammation and fatigue [
28,
29], higher blood pressure [
30], cardiovascular disease [
30,
31], and so on. The American Psychological Association [
17] warned that the risk exposure of loneliness was greater than that of obesity and the impact was growing and would continue to grow in the future. In addition to the effect on physical and mental health, loneliness has consequences for people’s role as a social entity. When a person remains in a prolonged state of loneliness, negative social attitudes tend to develop such as shyness, negative moods, fear of negative evaluation, lower social skills, and so on. The greater negative social expectations in lonely persons can lead to the development of distrust, hostility, and intolerance [
12].
The COVID-19 pandemic affected the individual, community, and social life of people such that their potential loneliness must be observed with due emphasis. The government-imposed restrictive measure such as the state of emergency in Japan, which was imposed during the early stage of the pandemic and continued throughout the year, had affected peoples’ usual personal and social lives. Although health authorities asked populations to maintain physical and social distancing, this measure is likely to exacerbate loneliness because social isolation and loneliness tend to occur together [
32,
33]. It has already been evident that the pandemic and its mitigating measures have increased loneliness among both younger and older people [
1,
3,
5,
6,
7]. However, the contributing factors to the loneliness of younger and older people should be discussed carefully because social expectations and social networks might have differing effect on their loneliness [
2,
3,
5,
6]. For example, Weissbourd et al. [
5] argue that changes in social network contribute differently to younger and older peoples’ loneliness. It appears that social isolation impacts more on younger peoples’ social network and older peoples’ cognitive and health issues [
5,
34]. Victor and Sullivan [
35] argue that loneliness among older people is determined not only by individual factors but also by factors related to community and society. This finding shows that older peoples’ lifestyle and living conditions should be carefully thought before imposing social distancing measures. Older people generally depend on family members for assistance in performing daily activities or on institutional long-term care at home or in old care homes. While social distancing is important to limit the spread of viral infection, the health requirement can affect the receipt of care and sense of social connectedness, which could ultimately affect the physical and mental health of older people negatively. The consequence could be more serious for those with pre-existing loneliness and mental conditions.
Despite being an important public health issue, there are no longitudinal studies on how the pandemic influenced loneliness among older and younger people in Japan. To fill this gap, this study investigates the conditions of loneliness before and during the pandemic among older people and compares them with their younger counterparts in Japan to determine whether older people suffered more from loneliness during the pandemic. Additionally, we investigate the socio-demographic and psychological factors that led to loneliness during this pandemic. We hypothesize that older people became lonelier due to maintaining social distancing, enhanced precaution, lack of health and family care, fear, and anxiety.
2. Materials and Methods
2.1. Participants and Instruments
This study uses panel data from the Household Behavioral and Financial Survey funded by Hiroshima University. Nikkei Research, a leading research company in Japan, conducted the online survey. Nikkei Research has one of the largest databases in Japan, which includes a representative population from many socio-economic backgrounds. The first wave of the online survey was conducted at the outset of the COVID-19 pandemic from 20 to 25 February 2020. The second wave of the survey was conducted a year after the first wave from 19 to 26 February 2021 and targeted individuals who responded to the 2020 survey. The survey was conducted following a random sampling procedure while maintaining the representativeness of sample in both waves. All prospective participants were approached through online and they agreed to participate in the survey. Data were collected through questionnaires sent to each participant. The questionnaire included dichotomous, multiple, and scaling questions on demographic, socio-economic, and psychological characteristics and preferences of the prospective participants. The minimum age of the prospective participants was 20 years. The dataset had 17,463 and 6103 total observations in 2020 and 2021, respectively.
Data on loneliness, marital status, living status, employment status, household income, household assets, current health status, anxiety, feelings of depression, financial satisfaction, and future orientation were available in both 2020 and 2021 waves. However, data on gender, age, education, children in the household, living in rural areas, and financial literacy were available only in the 2020 wave. The inclusion criteria for this study were that minimum age of respondents had to be at least 20 years at the time of the survey and they have to answer all the questions included in this study. Thus, we had to exclude several observations due to missing socio-economic data such as household income, household assets, and financial literacy. Our final sample consists of 4253 respondents.
2.2. Ethical Statement and Conflict of Interest
This is a socio-economic study, which does not involve any invasiveness nor identifiable human aspects. Thus, the ethical review and approval were not necessary according to institutional requirements (the ethics committee of Hiroshima University, Higashihiroshima, Japan). However, all participants were informed about the purpose of the study before the survey and they agreed to take part in it. We also declare that there is no conflict of interest.
2.3. Variable Definitions
Loneliness is the main variable of interest, which we also use as the dependent variable in the regression analysis. We primarily followed the UCLA methodology to measure loneliness [
36]. We measured loneliness as a binary variable where 1 indicates that the respondents are lonely and 0 otherwise. Respondents are classified as lonely if they responded that they felt a lack of companionship, left out, and isolated often or some of the time. To check the robustness of our results, we use a more direct alternative question to measure loneliness: “how often do you feel lonely?” Participants responded on a five-point scale ranging from often or always to never. The alternative measure of loneliness is also binary, where 1 indicates the respondent is lonely, and 0 otherwise. Respondents are classified as lonely if they reported feeling lonely always or often, some of the time, and occasionally.
As explanatory variables, we include gender, age, education, marital status, living status, living in a rural area, employment status, household income, and household assets as demographic and socio-economic variables. We also include financial literacy as a proxy for rational decision-making ability related to savings, investment, and health-related behaviors [
37,
38,
39,
40,
41,
42]. Furthermore, we include subjective health status, feelings of depression, future anxiety, financial satisfaction, and myopic view of the future to account for respondents’ subjective psychological and health concerns.
Table 1 provides the definitions of all the variables.
2.4. Statistical Analysis
We use descriptive statistics to show the distribution of loneliness of the respondents and their demographic, socio-economic, and psychological characteristics. Moreover, we use a mean-comparison test to compare loneliness before and during the pandemic. In this study, loneliness before the pandemic means loneliness among respondents measured from data of the February, 2020 wave while loneliness during the pandemic means loneliness among respondents measured from data of the February, 2021 wave. Although the first case of the COVID-19 was detected in January 2020 in Japan, we labelled loneliness measured from the February, 2020 wave as “loneliness before pandemic” because the virus did not spread much during the time of the data collection. Moreover, the WHO declared the COVID-19 outbreak a global pandemic on 11 March 2020, which is after the first wave of the survey was conducted. Thus, we believe the loneliness among respondents and socio-economic conditions during February, 2020 largely reflect the situation when the COVID-19 was not considered a pandemic in Japan. Finally, we examine the association between loneliness and respondents’ demographic, socio-economic, psychological, and health-related factors using Equation (1).
where
is loneliness,
is a vector of individual characteristics, and
is the error term. We use a logit regression to estimate Equation (1), as the dependent variable is binary. Because a logit model is used to model the probability of an event falling into one of the specified categories, we have used this model to predict loneliness against a set of socio-economic and psychological variables.
As the explanatory variables are potentially multicollinear, we conducted correlation and multicollinearity tests (results are unreported here to save space but are available upon request). The correlation matrix shows a weak relationship between the explanatory variables (lower than 0.70). In addition, the variance inflation factors of the explanatory variables are below 10, indicating that multicollinearity is not significant in the model.
Equation (2) provides the full model specifications of Equation (1):
5. Conclusions
This study investigated loneliness among older and younger people before and during the COVID-19 pandemic in Japan. We provide evidence on the increasing magnitude of loneliness among both older and younger people in Japan during the pandemic. However, the magnitude of increase in loneliness is slightly higher for older people compared to their younger counterparts. People with younger ages, poor subjective health status and feelings of depression were lonely before and during the pandemic. Household income and financial satisfaction are found to be associated with loneliness among older people during the pandemic who were not lonely before while gender, marital status, living status, and feelings of depression are found to be associated with loneliness among younger people who were not lonely before. We suggest that needs-based special social networks should be established for those with a higher likelihood of becoming lonely during the pandemic. Authorities can publicize and patronize the formation of such special social networks through educational institutions, private and public offices, and social groups. Moreover, authorities could introduce psychological intervention programs such as mindfulness therapy, cognitive enhancement programs, and so on, through online and digital platforms for people suffering from acute loneliness.