The population structure of Korea has recently undergone rapid changes. In the recent past, four-person households were the most typical. However, the number of single-person households has been steadily increasing. As of 2010, single-person households made up 23.9% of all households, but by 2021, this had increased to 33.4% (Statistics Korea, 2022). This widespread prevalence of single-person households means that policy approaches directed toward them have significant importance. In particular, some studies have reported that single-person households exhibit lower quality of life (QoL) and life satisfaction than multi-person households (Min, 2022). Moreover, the dying alone of single-person households is a notable issue in Korea, and the low quality of life is one of the factors that significantly affects the solitude death of single-person households (B. N. Kim, 2023). Therefore, the purpose of this study is to present policy implications for increasing life satisfaction of people living in single-person households.

Most studies on life satisfaction hitherto have focused on the causal relationship with socioeconomic factors, such as income and education (Deaton, 2008; S. A. Kim & Jung, 2019; Sacks et al., 2010; Stevenson & Wolfers, 2013). These studies have shown that low income is a critical cause of low life satisfaction. However, the local environment residents encounter every day can also have a significant effect on life satisfaction. For example, if convenient facilities are present in the community, or the environment is naturally pleasant, subjective satisfaction may increase. Thus, this study considered the environment to be an important factor influencing the life satisfaction and therefore assessed the subjective perception of the local environment.

The effect of the local environment on life satisfaction is important for everyone regardless of household type. However, subcomponents of the local environment that significantly affect life satisfaction may differ between multi-person households and single-person households (Bennett & Dixon, 2006). For example, it is important for multi-person households with children to have high-quality educational institutions in their residential areas, but not for single-person households without children (Mohanty & Raut, 2009). In addition, even within single-person households, there are differences in the subcomponents of the local environment that are considered important across generations. This is because lifestyle or considerations for residence selection differ between generations (Clark & Onaka, 1983; J. H. Park et al., 2021).

Based on the above discussion, this study addressed the following research questions. First, how does the local environment affect life satisfaction of single-person households? Second, what are the differences between generations in the effects of the local environment on the life satisfaction of those living in single-person households? Data from the 2020 Residents’ Quality of Life Survey in Gyeonggi Province were used for this study, and regression analysis was conducted step-by-step on all samples together as well as on samples by generation.

Literature Review

Life satisfaction

Gross domestic product (GDP) is an insufficient index for measuring personal happiness (S. J. Lee et al., 2021), and several attempts have been made to measure happiness with measures that can take the place of GDP. Among these, QoL has emerged as having major importance for measuring happiness. QoL is a subjective concept that is composed of various emotions, such as the satisfaction and disappointment experienced by individuals or groups, as well as socially objectified conditions, such as education and income (Yoo et al., 2021). Studies on QoL that value objectivity have used social indicators as measurement tools, while those that emphasize subjectivity have largely adopted life satisfaction (S. K. Kim et al., 2008). Thus, life satisfaction can be considered as a representative measure of an individual’s QoL from a subjective point of view.

Previous studies of life satisfaction have had limited success in exploring factors that influence it. Most have emphasized the importance of socioeconomic factors, such as and income and educational level (Deaton, 2008; Sacks et al., 2010; Stevenson & Wolfers, 2013). This is because an individual’s socioeconomic level has long been recognized as an important indicator of QoL (J.-W. Lee & Kang, 2018). These studies indicate that life satisfaction may be greater for those with higher levels of income. Meanwhile, individuals primarily seek to satisfy their needs within their community (K.-Y. Lee & Jeong, 2021). This means that the local environment may constitute an important factor in life satisfaction.

Local Environment and Life Satisfaction of Single-Person Households

The local environment refers to the physical and social conditions within an individual’s community (K.-Y. Lee & Jeong, 2021). This environment is composed of various subcomponents. Here, the local environment is divided into the subcomponents of convenience, comfort, safety, healthcare, and neighborhood relationship. These factors meet the criteria proposed by the Organization for Economic Co-operation and Development (OECD) and the World Health Organization (WHO) to evaluate the quality of the local environment (OECD, 2013; WHO Expert Committee on the Public Health Aspects of Housing & World Health Organization, 1961). For example, the WHO suggested safety, health, and convenience as criteria for evaluating the quality of the local environment. In addition, the OECD emphasized that not only the physical environment but also social factors, such as neighborhood relationships, are important components of the local environment.

This study also used subjective perceptions of the local environment. While objective data, such as the number of commercial facilities in the community, can provide accuracy, residents’ perceptions of the local environment are necessarily relative. Not all residents evaluate the same conditions in the same way. For example, if a commercial facility is located within a 10-minute walk, some may evaluate consider it very close, while others may consider it too far. In this respect, subjective perceptions are important.

In addition, although there have not been many studies of single-person households, those that have been conducted show a positive relationship between life satisfaction and the local environment. For example, Hill et al. (2009) emphasized the risk of isolation of those living in single-person households and explained that it was necessary to establish a social network as an alternative. Some studies also explained that the formation of social networks between neighbors can make an important contribution to increasing the place attachment of those in single-person households (Choi et al., 2018; J. H. Park et al., 2021; Scannell & Gifford, 2010). In fact, most of the single-person household-related plans promoted by local governments in Korea are focused on revitalizing social networks (Noh et al., 2022). Moreover, the level of satisfaction of those with access to convenient facilities and satisfaction with comfort had a significant effect on the residential environment satisfaction of those in single-person households (Kwon & Park, 2014). On the other hand, Noh, Lee, and Hwang (2018) explained that females in single-person households care the most about a safe residential environment. Finally, single-person households do not have cohabitating family members, so they should be able to receive healthcare services from non-family members quickly when they are sick (Garay Villegas et al., 2014). Therefore, this study presented the following hypothesis.

H1: Perceptions of the local environmental factors of (a) convenience, (b) comfort, (c) safety, (d) healthcare, and (e) neighborhood relationship have a positive effect on life satisfaction of single-member households.

Generational Comparison

Most previous studies on single-person households in Korea have focused on the elderly population (M. S. Kim & Kim, 2020). This is because, due to population aging, the problems of the elderly living alone have attracted increased attention as an important social issue (Garay Villegas et al., 2014). On the other hand, studies of single-person households that compare generations have been relatively rare. However, the social groups that belong to each generation are different, and therefore, the factors that are considered most important may also differ by generation (J.-W. Lee & Kang, 2018).

Meanwhile, the Korean criteria for classifying generations based on age have changed somewhat. Kim and Jung (2019) classified those 65 years old and older as elderly, and people under the age of 35 were defined as youth. S. S. Park (2019) classified individuals 40 years old and older as middle-aged, and classified those 35 years old and older as middle-aged. The Ministry of Employment and Labor also defines the age of 35 as the threshold for middle age. This study followed this trend: those under 35 years old were considered youth, those aged 35 to 65 were middle-aged, and those aged 65 or older were categorized as elderly.

More specifically, the discussion on the generational comparison is as follows. First, most youth in single-person households live alone away from their families due to their jobs. Therefore, they are likely to prefer areas with good commuting conditions (Choi et al., 2018; Clark & Onaka, 1983). In general, traffic accessibility is also good in areas where convenient facilities are well established. Next, middle-aged people in single-person households often live alone due to divorce or their children studying abroad. Previous studies have shown that, in terms of emotions, they often feel lonely (S. S. Park, 2019). Finally, elderly people in single-person households have the highest health concerns and interests. Therefore, we can expect the need for healthcare facilities to be the greatest in this age group (Piekut, 2020). Due to these discussions, this study presents the following hypothesis.

H2: The effects of subcomponents of the local environment on life satisfaction of those living in single-person households are differentiated by age group.

Method

Study Area and Data

The study area is located in Gyeonggi Province, Korea. Gyeonggi Province consists of 31 districts. As of 2022, the population was 13,589,432, and it is the largest province in Korea (Gyeonggi Province Website, 2022). Gyeonggi Province is adjacent to Seoul, the capital of Korea, and has developed as a satellite of Seoul. Beginning in 2015, when statistics on single-person households began to be kept, the proportion of single-person households among general households in Gyeonggi Province has steadily increased. The proportion of single-person households was 23.4% in 2015, but it increased to 29.2% in 2021 (Statistics Korea, 2022). This means that Gyeonggi Province is suitable as a study area for single-person household research.

This study analyzed the data gathered from the 2020 Residents’ Quality of Life Survey in Gyeonggi Province. The survey was conducted by the Gyeonggi Research Institute from September 22 to November 15, 2020 with face-to-face interviews. In addition, it applied a multistage stratified sampling method as the sample design. In total, 16,000 households were included in this survey; 400 respondents were selected from each of the 31 districts in Gyeonggi Province for a total of 12,400 respondents. In addition, 3,600 respondents were selected based on the proportion of the population of the 31 districts. When selecting households, the ratio of apartments and single-person households in a district and the aging index were used. The above methods can contribute to increasing the representativeness of the sample (Yoo et al., 2021).

In all, 16,000 responses were collected, of which 3,263 were from single-person households. The specific characteristics of the respondents are shown in Table 1. First, 444 respondents (13.6%) were under the age of 35, 1,539 (47.2%) were aged 35 to 64, and 1,280 (39.2%) were over the age of 64. Women accounted for the highest proportion in the elderly group population at 73.5%. The average monthly income was relatively high for the middle-aged population, between KRW 2 million and KRW 3 million per month (approximately $1,447-$2,171 US), but the proportion of respondents who earned under 1 million won ($724 US) per month (58.3%) was highest in the elderly population. The older the age group, the lower the rate of college graduates or above. There was no significant difference in housing types between generations. However, homeowners were the highest in the elderly population at 78.4%. Finally, 73.4% of the youth population had lived in their current residence for less than three years, but the elderly population was the largest at more than seven years(69.1%).

Table 1.Respondent Characteristics
Total Youth
(under 35 years old)
Middle-aged
(35–64 years old)
Elderly
(over 64 years old)
Total 3,263
(100.0%)
444
(100.0%)
1,539
(100.0%)
1,280
(100.0%)
Sex
Male 1,139
(34.9%)
225
(50.7%)
575
(37.4%)
339
(26.5%)
Female 2,124
(65.1%)
219
(49.3%)
964
(62.6%)
941
(73.5%)
Monthly household income (KRW)
Below 1 million won below 1,036
(31.7%)
57
(12.8%)
233
(15.1%)
746
(58.3%)
1–2 million won 783
(24.0%)
137
(30.9%)
370
(24.0%)
276
(21.6%)
2–3 million won 832
(25.5%)
171
(38.5%)
494
(32.1%)
167
(13.0%)
Above 3 million won 612
(18.8%)
79
(17.8%)
442
(28.7%)
91
(7.1%)
Eduacational level
Above college graduate 1,015
(31.1%)
363
(81.8%)
613
(39.8%)
39
(3.0%)
Other 2,248
(68.9%)
81
(18.2%)
926
(60.2%)
1,241
(97.0%)
Housing type
Apartment 2,170
(66.5%)
122
(27.5%)
525
(34.1%)
446
(34.8%)
Other 1,093
(33.5%)
322
(72.5%)
1,014
(65.9%)
834
(65.2%)
Housing tenure
Homeowner 1,759
(53.9%)
29
(6.5%)
727
(47.2%)
1,003
(78.4%)
Renter 1,504
(46.1%)
415
(93.5%)
812
(52.8%)
277
(21.6%)
Length of Residence
Less than 3 years 1,003
(30.7%)
326
(73.4%)
514
(33.4%)
163
(12.7%)
3–7 years 887
(27.2%)
100
(22.5%)
555
(36.1%)
232
(18.1%)
Above 7 years 1,373
(42.1%)
18
(4.1%)
470
(30.5%)
885
(69.1%)

Variables

The following variables are used in this study. First, the survey assessed overall life satisfaction on a 10-point scale, as a single question. Next, convenience, comfort, safety, healthcare, and neighborhood relations were considered as subcomponents of the local environment. These were measured using a 4-point scale of very dissatisfied (1), dissatisfied (2), satisfied (3), and very satisfied (4). Convenience was assessed with a single question, directly measuring satisfaction with the infrastructure, including public institutions, cultural facilities, and commercial facilities. Next, comfort was understood to refer to satisfaction with the natural environment. This value consisted of multiple items, including accessibility to green spaces areas, water quality and river pollution, odor, and air pollution. Safety was measured from satisfaction with the number of traffic accidents, other accidents, fires accidents, violent crime, and infectious diseases. Finally, healthcare was measured using the ratings of the sufficiency of medical services and emergency services nearby and the sufficiency of infectious disease management services. Neighborhood relationships were investigated through the degree of interaction and trust between neighbors. In addition, demographic characteristics, such as gender, monthly income, education level, housing type, housing tenure, and length of residence, which can significantly affect life satisfaction, were considered together as control variables (Moreno-Jiménez et al., 2017; Mouratidis, 2020; Sirgy et al., 2008).

This study measured perceptions of the local environment in terms of comfort, safety, healthcare, and neighborhood relationships in the nearby area using multiple items. Among these factors, the internal validity between the factors and the measurement items was verified using exploratory factor analysis (EFA) and reliability analysis (Table 2). As a result, it was verified that an acceptable level of internal validity was secured between all items.

Table 2.EFA and Reliability Analysis
Category Measurements Factor loading Eigenvalue/Cronbach’s α
Comfort Satisfaction with accessibility to green areas .570 3.445
/.804
Satisfaction with air pollution .511
Satisfaction with water quality pollution .696
Satisfaction with garbage collection service .601
Satisfaction with hazardous chemical materials exposure .627
Satisfaction with odors .647
Satisfaction with noise .592
Satisfaction with climate change .645
Safety Traffic safety .615 2.770
/.795
Industrial safety .543
Fire safety .699
Crime safety .758
Disease safety .778
Healthcare Adequacy of local healthcare .828 2.131
/.724
Adequacy of infectious diseases management service .736
Adequacy of local emergency medical service .801
Neighborhood relationships Degree of getting help from residents .873 2.008
/.773
Degree of helping residents .859
Degree of trust in residents .690

Kaiser-Meyer-Olkin (KMO) = .874; Bartlett sphericity test = .000.

Table 3 shows the results of descriptive and correlation analyses on subcomponents of the local environment and life satisfaction. First, among the subcomponents for local environment, convenience (2.89) and comfort (2.86) were found to have high satisfaction relative to other factors. On the other hand, neighborhood relations were the lowest, with 2.54. Next, life satisfaction was scored as 6.06 (on a 10-point scale), slightly over the middle value. Meanwhile, all individual factors showed a statistically significant positive correlation.

Table 3.Descriptive Statistics and Correlations Between Factors
Factor Mean Std. Dev. 1 2 3 4 5 6
1 Convenience 2.89 ±.576 1
2 Comfort 2.86 ±.464 .158** 1
3 Safety 2.67 ±.568 .083** .609** 1
4 Healthcare 2.69 ±.585 .298** .264** .242** 1
5 Neighborhood relationships 2.54 ±.642 .040* .210** .206** .148** 1
6 Life satisfaction 6.06 ±1.391 .165** .227** .223** .222** .149** 1

Note. * p < .05, ** p < .01. Life satisfaction: 10-point scale, Others: 4-point scale

Results

Relationship Between Perceptions of the Local Environment and Life Satisfaction of Single-Person Households Based on the Generation

Regression analysis was first conducted on all samples and then divided by age group (Table 4). As in this study, when generations are classified based on a specific age, there is an advantage that the policy target group can be clearly set. On the other hand, when age is treated as a continuous variable, it is difficult to set the criteria for classifying age groups. For example, if convenience is more important when a person is younger, the criteria for young may be relative to each individual.

Table 4.Influencing Factors for Life Satisfaction of Single-Person Households
Total
(β)
Generation
Youth
(β)
Middle-aged
(β)
Elderly
(β)
Control variable
Gender
(ref. male)
.099** .111* .122** .072**
Generation (ref. Youth)
- Middle-aged
- Elderly
-.116**
-.089**
-
 
-
 
-
 
Monthly income .193** .140** .205** .149**
Educational level
(ref. less than college graduates)
.103** .056 .117** .001
Housing type
(ref. non-apartments)
-.008 -.003 -.029 .020
Housing tenure
(ref. renters)
.105** .122** .039 .163**
Length of residence .002 −.058 .022 −.001
Local environment
Convenience .090** .156** .087** .071*
Comfort .093** .115* .092** .096**
Safety .108** .155** .121** .075*
Healthcare .104** .024 .036 .199**
Neighborhood relationships .110** .117* .158** .056*
n 3,263 444 1,539 1,280
F 50.786** 9.278** 31.612** 24.045**
R2 .169 .191 .185 .173

Note. * p < .05, ** p < .01.

First, an analysis of the complete sample shows that all of the subcomponents of the local environment had positive effects on the life satisfaction of those in single-person households. In particular, examining the influence between factors based on the standardized coefficient, it was found that neighborhood relationships had a relatively large effect among subcomponents of local environment. This is a similar result to previous studies that emphasized the importance of social networks (Choi et al., 2018; Hill et al., 2009; Noh et al., 2022; J. H. Park et al., 2021; Scannell & Gifford, 2010). It was also found that the control variables of gender, age, monthly income, educational level, and housing tenure had significant effects on life satisfaction.

Next, we looked at the different age groups. First, in the youth group, convenience and safety were found to be relatively important to the life satisfaction of single-person household members. Comfort and neighborhood relationships were also found to have a significant effect, but the significance level was low. Healthcare, on the other hand, had no significant effect. Next, in the middle-aged group, convenience, comfort, safety, and neighborhood relationships, i.e., all the factors excluding healthcare, were found to have a significant effect on life satisfaction. Among them, it was found that the influence of neighborhood relations was the greatest. Finally, in the elderly group, all factors had a significant effect on life satisfaction. In particular, the standardized coefficient of healthcare was .199, which was very large compared to other factors. This means that healthcare may be the most important for the life satisfaction of elderly people living in single-person households.

The above results mean that the factors influencing the life satisfaction of people in single-person households may vary depending on their generation. Specifically, it was found that convenience and safety are important for the youth, neighborhood relationships for the middle-aged, and healthcare for the elderly are important for life satisfaction.

Analysis of Covariance (ANCOVA)

In addition, this study conducted ANCOVA analysis for more sophisticated verification of generational differences (Table 5). ANCOVA is used in comparative analysis between groups and has the advantage of being able to consider control variables together (H. S. Lee & Lim, 2017). This study analyzed the comparison between generations for individual factors through ANCOVA, and in this process, control variables, including gender, monthly income, educational level, housing type, housing tenure, and length of residence were introduced together as covariates. If individual factors show significant differences between generations, the acceptability of the second hypothesis of this study will increase. The analysis results are as follows. Except for healthcare, there were significant differences between generations for the rest of the factors. More specifically, regarding convenience, comfort, safety, and neighborhood relationships, the older the age group, the higher the satisfaction level. On the other hand, life satisfaction was highest in the low-age group. Similarly, H. Kim (2020) verified that there was a negative relationship between QoL and age.

Table 5.ANCOVA
Factor Youth Middle-aged Elderly F-value
1 Convenience 2.80 2.89 2.95 8.140**
2 Comfort 2.79 2.84 2.91 6.690**
3 Safety 2.58 2.68 2.69 3.334*
4 Healthcare 2.69 2.71 2.66 .834
5 Neighborhood relationships 2.14 2.48 2.76 39.069**
6 Life satisfaction 6.19 6.08 5.99 6.444**

Note. * p < .05, ** p < .01. Covariates: gender, monthly income, educational level, housing type, housing tenure, length of residence

Discussion

Perceptions of the local environment had a positive effect on life satisfaction in people living in single-person households. In other words, if satisfaction with the local environment was high, life satisfaction of single-person households was also high. Similarly, previous studies have found a causal relationship between the community environment and the residential satisfaction in single-person household members (S. A. Kim & Jung, 2019). Moreover, this study confirmed that the effect of neighborhood relationships was relatively large compared to other subcomponents of the local environment. As mentioned earlier, this is due to the greater sense of isolation or depression in the case of people in single-person households than in multi-person households (Hill et al., 2009; Noh et al., 2022; J. H. Park et al., 2021). In particular, considering the recent increase in single-person households, it will be necessary to prepare policies to improve the neighborhood relationships of people in single-person households.

The influencing subcomponents of the local environment on life satisfaction of people in single-person households differed by generation. Specifically, convenience and safety were relatively important for the youth, neighborhood relationships for the middle-aged, and healthcare for the elderly. The reason why factors that significantly affect life satisfaction differ between generations is because their lifestyle and criteria for selecting residential areas are different (Choi et al., 2018; Clark & Onaka, 1983). For example, youth in single-person households often live alone due to their work. Therefore, commuting to work plays a large role, and the effect of convenience is large. In addition, Noh, Lee, and Hwang (2018) showed that female youth in single-person households have the greatest demand for safety. In Korea, the incidence of crimes against female youth in single-person households is high (D. S. Kim, 2023). On the other hand, because the elderly use healthcare services more frequently than other age groups, access to healthcare services is important for life satisfaction.

Based on the above discussion, this study suggests the following policy implications. Various community programs should be developed and promoted to increase the frequency of contact with residents. According to previous studies, more frequent meetings between neighbors lead to good relationships between neighbors (Jun & Hur, 2015; Lund, 2002). In fact, Gyeonggi Province is planning many programs for single-person households, including the establishment of communities and the prevention of isolation, lead by the Women and Family Bureau (Noh et al., 2022). Second, to increase the life satisfaction of members of single-person households, a differential approach is needed, depending on the generation. This study showed that the influencing factors on life satisfaction among people in single-person households differs between generations. In areas where the proportion of youth single-person households is high, efforts should be made to improve access to convenience and transportation facilities. In particular, it is necessary to expand police activities for safety accidents where the proportion of female youth single-person households is high. E.H. Kim (2022) verified a positive correlation between the number of police officers and the level of safety. In addition, where the proportion of middle-aged single-person households is high, programs in which residents can participate together should be developed to increase the frequency of contact between neighbors, contributing to the improvement of neighborhood relations. Finally, it is necessary to improve healthcare services in areas where the proportion of elderly single-person households is high.

Conclusion

This study discussed life satisfaction in single-person households. Specifically, this study focus on Gyeonggi Province, Korea as a study area and analyzed the data on single-person households from the 2020 Residents’ Quality of Life Survey in Gyeonggi Province. As a result, it was found that the local environmental factors of convenience, comfort, safety, healthcare and neighborhood relationships had a positive effect on the life satisfaction of those in single-person households. In particular, the effect of neighborhood relationships was a relatively large. Moreover, the effect of perception of local environmental factors on the life satisfaction of single-person households differed between generations. Specifically, convenience and safety were important for the youth, neighborhood relationships for the middle-aged, and healthcare for the elderly.

Recently, single-person households have been increasing worldwide (Lim, 2019). In some countries, the proportion of single-person households has already exceeded 40%. The single-person household policies of countries around the world emphasize the need for a targeted approach according to individual characteristics such as gender and age (H. G. Kim, 2019). In this regard, this study provides the implication that differentiation between generations is necessary.

Meanwhile, this study had several limitations. First, in this study, it was difficult to verify validity and reliability by measuring life satisfaction, which is a dependent variable, as a single question. Second, it used secondary data, and the proportion of the youth population is lower than that of other generations. Therefore, the possibility that the characteristics of the youth population were somewhat less reflected in the analysis cannot be excluded. A more sophisticated sample design will be needed in the future. Finally, this study did not fully consider the possibility that age may be related to other variables that are not measured in this study. For example, age is highly related to job status, which can also affect life satisfaction of those in single-person households. In subsequent studies, these parts should be supplemented.