Multidimensional Analysis of Well-Being Domains in Japan: Fulfillment, Importance, and Contribution to Overall Well-Being

Abstract

Efforts to measure citizen Well-Being (WB) and integrate the results into policymaking have gained momentum globally. In this study, we evaluate the domains comprising WB indicators based on three dimensions—fulfillment, importance, and contribution to overall WB—to effectively apply these findings to policies and urban development strategies. An online survey of 1394 Japanese adults (630 women, 764 men) was conducted to analyze the rankings of the 24 domains (comprising 46 items) of the Liveable Well-being City indicator, a widely used framework in Japan, across these three dimensions. The analysis revealed that items in domains related to Life Environment ranked highest regarding fulfillment, whereas domains related to Living Authentically or Life Environment ranked highest in importance. Meanwhile, items in the domains associated with Community Relationships or Living Authentically tended to rank higher in contribution to overall WB; however, this was not statistically significant. These results suggest inconsistencies in evaluation across dimensions and highlight the necessity of incorporating three-dimensional evaluations into policymaking and policy improvement. Furthermore, the findings indicate that strategies targeting Community Relationships could be particularly effective in enhancing WB and providing actionable policy design and implementation guidance.

1. Introduction

Japan is currently the world’s fourth-largest economy by Gross Domestic Product (GDP) [1]; however, it ranks 51st in the World Happiness Ranking [2], a notably low position among developed nations. This contrast underscores the urgent need for policies to improve Japanese citizens’ Well-Being (WB). Thus, Japan’s scientific and technological policies seek to improve its WB. For example, in the 6th Science, Technology, and Innovation Basic Plan, the Japanese Cabinet Office articulated the future vision of Society 5.0 (Society 5.0 was first proposed in the 5th Basic Plan and is defined as “a human-centered society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space” [3]): “a society that is sustainable and resilient, that secures the safety and security of the people, and that enables each and every one of them to realize diverse happiness (well-being) [4]”.

To achieve this, it is crucial to understand the multifaceted nature of WB first. Specifically, it is necessary to consider that WB comprises multiple domains [5]. Therefore, to effectively enhance the overall WB (overall WB is commonly assessed through happiness or subjective WB [6]), policymakers must accurately assess each WB domain’s current state (e.g., living environment, work–life balance, and health) and allocate resources appropriately. Japanese national and local governments have begun to measure fulfillment levels within WB domains—specifically, the degree of achievement and people’s satisfaction—and incorporate these results into policymaking processes [7,8,9]. This approach—measuring the satisfaction levels across the WB domains and incorporating the results into policy—is also employed in other countries [10,11].

However, prioritizing the WB domain based on fulfillment levels may involve certain risks. Costanza et al. emphasized that, when measuring WB domains, it is crucial to consider not only fulfillment levels but also the degree to which people place importance on each domain [12]. This occurs because, in cases where multiple WB domains are unfulfilled, policymakers can more effectively garner public support by prioritizing resource allocation to the domains deemed most important by the people. In practice, the importance of each WB domain is often considered equal [13] or weighted by those involved in using the indicators [14]. Therefore, incorporating the measurement of domain importance and fulfillment is a promising approach to mitigate these risks.

Nevertheless, including the dimension of importance to the resource allocation considerations may not eliminate the risks, as recognizing importance reflects how citizens perceive each WB domain’s contribution to overall WB, a perception that may differ from their substantive contribution (e.g., the substantive regression coefficients of WB domain fulfillment on overall WB fulfillment). Consequently, there is a risk of overallocating resources to domains perceived as important despite their low substantial contribution to overall WB. In contrast, domains with a substantial contribution may be overlooked and receive insufficient resource allocation.

To mitigate such risks and achieve an appropriate allocation of resources, it is essential to comprehensively evaluate the three dimensions of fulfillment, importance, and overall contribution to WB (hereafter referred to as contribution). Fulfillment helps prevent excessive resource investment, is important as a measure of citizens’ level of support, and contributes as an indicator of its impact on improving WB. Therefore, this study employs this comprehensive approach to prioritize resources and appropriately mitigate risks. Furthermore, this study aims to measure the three evaluation dimensions for each WB domain among Japanese citizens and elucidate the interrelationships among these dimensions. This analysis provides specific insights to improve resource allocation in policymaking and urban development. The findings of this study will offer valuable implications not only for Japan, but also for policies aimed at enhancing WB in other countries. Although the specific WB domains assessed may vary across countries, measuring fulfillment remains a fundamental approach to understanding the current situation. Therefore, including the dimensions of importance and contribution alongside fulfillment provides a universally applicable framework for refining the analysis of WB domains.

1.1. Development of WB Indicators

The concept of WB is multifaceted, encompassing not only economic prosperity but also various elements, such as mental and physical health and a sense of social fulfillment [5]. To measure overall WB, which integrates these elements, subjective WB has been proposed, comprising life satisfaction, positive emotions, and negative emotions [6]. Several theoretical frameworks have also been introduced to explain different elements of WB. Psychological WB encompasses self-acceptance, positive relations with others, autonomy, environmental mastery, purpose in life, and personal growth [15]. The PERMA model has been proposed recently, suggesting that WB consists of positive emotions, engagement, relationships, meaning, and accomplishments [16]. While WB emphasizes psychological factors such as happiness and life satisfaction, Quality of Life (QoL) is primarily applied to health-related aspects, including physical functioning, with standardized scales widely used in medicine and the health sciences to measure this construct [17]. Moreover, the capability approach views QoL as an individual’s ability and freedom to choose how to live their life [18]. Since then, QoL has evolved into a more comprehensive construct, encompassing social support, economic stability, work, and the living environment [12].

Based on this academic perspective, several WB indicators have been proposed to reflect overall WB and its diverse elements. For example, the Sustainable Development Solutions Network (SDSN) ranks countries by happiness using three criteria to measure overall WB (life evaluation, positive affect, and negative affect) and six key domains to predict these criteria (GDP, life expectancy, generosity, social support, freedom, and corruption). The SDSN publishes the ranked results in the World Happiness Report [2]. Similarly, other indicators have been developed to evaluate WB from various perspectives, such as the Organization for Economic Co-operation and Development (OECD) Better Life Index (BLI) [14], assessing 11 WB domains, and the Gallup–Sharecare Well-Being Index, focusing on five WB domains [19].

Japanese national and local governments and research firms have developed and utilized their WB indicators in response to practical needs. For example, the Japanese Cabinet Office’s Satisfaction and Quality of Life Survey measures subjective life satisfaction and 13 WB domains based on the BLI [20]. Moreover, the Japanese Digital Agency uses the Livable Well-being City (LWC) indicator to measure aspects of regional WB, such as happiness and satisfaction, along with 24 distinct WB domains [21]. In addition, private Japanese research firms conduct surveys using their own WB indices. For example, the Mitsubishi Research Institute (MRI) version of the Well-Being Index measures overall individual and societal satisfaction and 21 WB domains based on nine elements [22]. This diversity of WB indices reflects the wide range of WB domains and various survey entities’ differing emphasis on these domains.

The fulfillment of WB domains can be measured using two main approaches. One involves using objective indicators such as average income and healthy life expectancy, whereas the other utilizes subjective indicators primarily obtained through surveys. In this study, we are interested in individuals’ evaluation tendencies. As capturing the degree of importance using objective measures is challenging, we focus on subjective indicators as the primary subject of our research.

1.2. LWC Indicators in Focus

In this study, we obtain more practical and direct insights by analyzing the WB indicators utilized in policy reviews and other practical applications. In line with this approach, we focus on the LWC indicator, which is widely used in Japan. We obtained permission from SCI-Japan, the developer, to use the LWC indicator. SCI-Japan developed this indicator as a tool to support the Japanese government’s vision of addressing local challenges and enhancing regional attractiveness through digital technology (i.e., Vision for a Digital Garden City Nation) [23]. The LWC indicator was designed to regularly measure the WB of the residents in each local government.

The 24 WB domains of the LWC indicator are assessed using both objective and subjective indicators. Although the LWC indicator guidebook refers to them as categories or factors [9], we standardize the terminology as domains in this study. The subjective indicators analyzed in this study comprise 46 question items, with one to five items per domain. Overall WB is measured exclusively using subjective indicators comprising five question items.

Table 1. Details of the Liveable Well-being City Indicator.

Category	Well-Being Domains
Life Environment	Medical Care and Welfare, Shopping and Eating Out, Housing Environment, Mobility and Transportation, Recreation and Entertainment, Parenting and Childcare, Primary and Secondary Education, Local Government, Digital Life, Public Space, City Scape, Natural Landscape, Natural Blessings, Symbiosis with the Environment, Natural Disasters, Accidents and Crimes
Community Relationships	Community Connections, Diversity, and Inclusion
Living Authentically	Self-Efficacy, Health Status, Culture and the Arts, Educational Opportunities, Employment and Income, Business Creation

lists the 24 WB domains included in the LWC indicator. Each WB domain is classified into three categories: Life Environment, Community Relationships, or Living Authentically. The LWC indicator does not follow a specific theoretical framework but incorporates multiple perspectives on well-being that are practically relevant to policy and city planning. Detailed information on the questions can be found in Table S1 in the Supplementary Material. In line with other WB indicators, the three categories of the LWC indicator reflect key constructs in WB theory: Life Environment encompasses QoL factors such as subsistence, security, and leisure; Community Relationships draws from both PERMA (positive relationships) and QoL (participation); and Living Authentically aligns with eudaimonic WB, particularly with Ryff’s psychological WB model, which emphasizes autonomy, purpose, and growth.

1.3. Previous Findings

The LWC indicator has been surveyed annually since 2022, and the results of analyses on the fulfillment and contribution of WB domains have been reported. The fulfillment of subjective indicators is calculated based on the survey respondents’ ratings. In contrast, the contribution is determined using the regression coefficients (or correlation coefficients) of the fulfillment of each WB domain to the overall WB.

According to the latest report on the LWC indicator [21], the WB domains with high fulfillment scores include Housing Environment, Public Spaces, and Natural Blessings—most of which belong to the Life Environment category. In contrast, the WB domains that demonstrated strong contributions to overall WB include Health Status, Self-Efficacy, and Community Connection, most of which are classified under the Living Authentically and Community Relationships categories. Although the importance score is not reported in the LWC indicator, analyses of other Japanese WB indicators have exhibited that health, income, employment environment, and resilience to shocks receive high importance ratings [20,22]. These are considered fundamental aspects, as any impairment in them would have a substantial impact on WB.

However, there are several points to consider when analyzing the results. First, when measuring the importance of each WB domain, universally important domains (e.g., being healthy, fewer accidents, and less crime) may exhibit a ceiling effect in their score distribution. In these cases, methods that assume a normal distribution, such as comparing domains based on average scores, have inherent limitations. Therefore, it is essential to carefully determine the most suitable statistical measures for comparing the importance of the WB domains. Next, multiple regression analysis is used to calculate the contribution, assuming independence among the WB domains. If a high correlation exists among the WB domains, the regression coefficients may become unstable owing to multicollinearity, requiring caution in their interpretation. In addition, demographic variables, such as household income, have been reported to affect the rating of WB domains [24]. However, the findings of previous studies do not fully account for these methodological considerations.

In this study, we consider these issues to enhance the accuracy of the analysis regarding fulfillment, importance, and overall contribution in WB. Additionally, we aim to clarify the essential relationships among these three evaluation dimensions after controlling for demographic characteristics. In doing so, we seek to provide deeper insights into the evaluation trends of WB domains among Japanese citizens.

1.4. Exploratory Hypotheses

It has been reported that the fulfillment and importance of the WB domains vary widely among individuals and across countries. Accordingly, the hypotheses presented below are exploratory approaches based on observations from Japan. Even as exploratory hypotheses, their validation is crucial to uncover new insights and identify potential patterns. In this study, we predict the following relationships based on the classification of LWC indicators depicted in Table 1 and the trends inferred from prior research.

First, many WB domains with high fulfillment levels in the LWC indicator are presumed to fall under the category of Life Environment [21]. Second, WB domains deemed highly important are often fundamental aspects of life [20,22] which are predicted to align with concepts such as Living Authentically or Life Environment within the LWC indicator. Third, WB domains with significant contributions to the LWC indicator are expected to be predominantly associated with Community Relationships or Living Authentically [21]. Based on these predictions, the following hypotheses were formulated:

H1. 

Items in the WB domain related to Life Environment will exhibit high levels of fulfillment.

H2. 

Items in the WB domain related to Living Authentically or Life Environment will exhibit high levels of importance.

H3. 

Items in the WB domain related to Community Relationships or Living Authentically will exhibit high levels of contribution.

2. Methods

2.1. Participants

In this study, we surveyed the overall WB and WB domains of the LWC indicator by measuring participants’ ratings of fulfillment and importance. Based on these ratings, the contribution was calculated using the ratings for overall WB and the fulfillment of each WB domain. Before the measurements, a power analysis was performed, assuming a small effect size (ρ = 0.10, α = 0.05, 1 − β = 0.95) for the correlation between overall WB ratings and WB domains’ fulfillment ratings. The analysis determined that the required sample size was N = 1289. We conducted an online survey with 1408 Japanese adults (633 women, 775 men) based on these results. The participants had a mean age of 43.38 years (range: 18–75 years; SD = 10.63). They were recruited through Lancers, a major Japanese crowdsourcing platform, and each was compensated with 110 yen for their participation.

The questionnaire included the following instruction to identify satisficing behavior [25,26]: “Please select ‘Not very applicable’, the second option from the bottom”. Participants who failed to follow this instruction (n = 14) were deemed to have not carefully read the items and were excluded from the analysis. After these exclusions, the final sample consisted of 1394 participants (630 women, 764 men), with a mean age of 43.47 (range: 18–75 years, SD = 10.62).

2.2. Procedure

Participants read the research description on the opening page of the survey, provided informed consent, and completed the survey. Participants first rated five items assessing overall WB, followed by 46 items addressing three specific categories: Life Environment, Community Relationships, and Living Authentically. The overall WB questions were fixed, initially, to ensure that participants could respond intuitively and comprehensively. This order was adopted to prevent responses to the WB domains from influencing the overall WB responses (i.e., the carryover effect). The participants rated each item’s perceived fulfillment and importance on a five-point Likert scale. The fulfillment items were framed as “To what extent do you think these items apply to you?”, while the importance items were framed as “To what extent do you think these items are important to your happiness?”.

The response order was randomized, with participants answering all 46 items on fulfillment, followed by importance or the reverse order. The order of presentation of the three categories was randomized to achieve counterbalancing. Finally, participants provided demographic information such as age, gender, marital status, residential area (at the municipal level), length of residence, and household income.

2.3. Analysis Strategy

This study’s hypotheses identify which categories of WB domains tend to be included at high levels within the three evaluation dimensions (fulfillment, importance, or contribution). The study’s findings can be examined by aggregating WB domain scores by category and comparing their averages. This result requires consistent measurement scales for the three evaluation dimensions. The same scale can be applied to fulfillment and importance, as they are derived from participant ratings. However, applying the same scale is challenging, since the relationship between fulfillment and overall WB determines contribution. Consequently, rankings were created for the three evaluation dimensions and compared systematically.

Regarding the rankings, we originally intended to analyze the WB domain (i.e., factor) level. However, due to insufficient internal consistency observed in the preliminary analysis, we decided to treat individual question items independently in the ranking process. Cronbach’s alpha coefficient (or Pearson’s correlation coefficient for domains with two items) indicated low internal consistency (defined as α < 0.70; r < 0.70) in 73.3% of the WB domains for fulfillment and 53.3% for importance (see Table S2 in the Supplemental Materials). This low consistency may stem from the practical nature of the LWC indicator, in which necessary questions are first identified and then grouped into domains rather than being initially designed to measure each WB domain with high internal reliability. The change has a limited impact on hypothesis testing, as hypotheses can still be tested by comparing the “average ranking for each category”. This is because our hypothesis testing focuses on the category level, offering a robust basis for interpretation regardless of whether the average rankings are derived from the 24 domains or the 46 question items. However, since contributions are ranked through regression analysis, it is necessary to consider the potential effects of multicollinearity. This issue is examined in detail in the following section.

Next, we examined the distribution of fulfillment and importance ratings provided by participants (N = 1394) on a five-point Likert scale for the 46 question items in the LWC indicator. Normality was confirmed for fulfillment, demographic variables, or overall WB. In contrast, deviation from normality was found with respect to the 12 items of importance ratings (see Figures S1–S4 in the Supplemental Materials). The sample size in this study was large (N = 1394). Given such a large sample size, normality tests such as the Shapiro–Wilk test tend to detect even minor deviations from normality, often leading to rejection. To address this, we assessed normality using kurtosis and skewness. Following the criteria established in previous studies [27], we considered the data to be approximately normal if the absolute kurtosis and skewness values were less than 1. As presented in Figures S1–S4, many of the items of importance ratings exhibit a strong concentration of responses at the highest rating (i.e., a ceiling effect), suggesting that certain items are perceived as essential by participants. As non-normality was observed in the distribution of importance, a nonparametric analysis method robust against deviations from normality was applied to the ranking analysis of fulfillment and importance.

In addition, for the overall WB, we focused on Happiness (“How happy are you currently?”) within the five items provided in the LWC. This focus was the most comprehensive question; therefore, it aligns with the importance rating criterion of “these items are important to your happiness”.

2.4. Derivation of Rankings

The following procedure was used to control for the effects of demographic variables on the development of fulfillment and importance rankings. First, a dataset that included the ratings for question item i, demographic variables, and an identification variable (d = 1) was created. This dataset was then stacked on top of another dataset corresponding to question item j (d = 0). Finally, a partial correlation analysis was applied to this stacked dataset to calculate the partial correlation coefficient r between the ratings and the identification variable d.

After controlling for demographic variables, the partial correlation coefficient r reflects the relative magnitude of question items i and j ratings. A positive value indicates that the rating of question item i is quantitatively greater than that of item j, and the larger the value, the stronger the numerical relationship. This calculation was repeated by iteratively replacing question item j with another item, and the average value of the partial correlation coefficient r for question item i was derived. The partial correlation coefficient used was Spearman’s rank correlation coefficient, consistent with the decision to adopt a nonparametric analysis. Finally, this process was conducted for all question items, and a ranking was created based on the average partial correlation coefficients across all items.

Multiple regression analysis was conducted to rank the 46 question items based on their relative contributions. In this analysis, the independent variables were the fulfillment ratings of the 46 questions, the dependent variable was the overall WB rating, and the control variables were demographics. Considering the potential for significant multicollinearity among the questions, we employed partial least squares regression. This choice was made because the method provides stable estimates of partial regression coefficients under such conditions [28]. Specifically, this approach mitigates the effects of multicollinearity by extracting latent components that maximize the covariance between the predictors and the outcome variable, thereby providing more stable coefficient estimates.

All the above analyses and data visualization were performed using R software (ver. 4.4.2). The dataset, R code, and supplemental results are publicly available from the Open Science Framework (OSF) repository (https://osf.io/m28tx, accessed on 27 April 2025).

3. Results

3.1. Ranking Results

The ranking of the 46 question items for the three evaluation dimensions is displayed in Figure 1 (see Table S3 in the Supplementary Material for statistical values). Figure 1 illustrates the rankings as a color-coded tile plot, with lighter colors indicating higher rankings and darker colors indicating lower rankings. The top five rankings for fulfillment and importance were as follows:

• Fulfillment: Housing Environment 1; Shopping and Eating Out 1; Primary and Secondary Education 2; Public Spaces 2; Primary and Secondary Education 1.
• Importance: Health Status 2; Health Status 1; Housing Environment 1; Shopping and Eating Out 1; Housing Environment 2.
• Contribution: Self-Efficacy 1; Health Status 2; Housing Environment 1; Business Creation 1; Culture and the Arts 2.

To examine the similarity of the rankings for the three evaluation dimensions, we examined Spearman’s correlation coefficient and found a strong correlation between fulfillment and importance (r = 0.69, 95% CI [0.50, 0.82], p < 0.001). However, no significant correlation was found between fulfillment and contribution (r = 0.09, 95% CI [−0.20, 0.37], p = 0.532) or between importance and contribution (r = 0.08, 95% CI [−0.22, 0.36], p = 0.616).

3.2. Hypothesis Testing

To test H1, we performed a one-tailed Wilcoxon rank-sum test based on the ranking of fulfillment levels. The ranking of the question items related to Life Environment, i.e., m_rk = 17.5 (n = 27), with this value representing the average ranking of the corresponding question item, was higher than that of the items in other categories (m_rk = 32.0, n = 19), demonstrating a significant difference (r = 0.53, 95% CI [0.29, 0.74], p < 0.001). This value of r represents the Wilcoxon effect size, and, according to Cohen’s guidelines [29], values from 0.10 to 0.3 indicate a small effect, values from 0.30 to 0.5 indicate a medium effect, and values of 0.5 or greater indicate a large effect. Therefore, H1, which hypothesized that items in the WB domain related to Life Environment exhibit high levels of fulfillment, was supported.

Similarly, to test H2, we performed a one-tailed Wilcoxon rank-sum test based on the ranking of importance, and the results indicated that the question items related to Living Authentically or Life Environment (m_rk = 19.2, n = 36) were ranked higher than those in other categories (m_rk = 39.1, n = 10), exhibiting a significant difference (r = 0.61, 95% CI [0.44, 0.74], p < 0.001). This finding supports H2; that is, items in the WB domain related to Living Authentically or Life Environment exhibit high levels of importance.

H3 was also tested using a one-tailed Wilcoxon rank-sum test based on the contribution ranking. The results demonstrated that the rankings of the items related to Community Relationships or Living Authentically (m_rk = 19.9, n = 19) were higher than those of other items (m_rk = 26.0, n = 27); however, this difference was not statistically significant (r = 0.22, 95% CI [0.02, 0.49], p = 0.068). Therefore, H3, which hypothesized that items in the WB domain related to Community Relationships or Living Authentically exhibit high levels of contribution, was not supported.

3.3. Additional Analysis

A closer look at the results in Figure 1 reveals that the ranking of the importance of Community Relationships (m_rk = 39.1, n = 10) was notably lower than that of their contributions (m_rk = 22.7, n = 10), with a statistically significant difference (r = 0.63, 95% CI [0.26, 0.85], p = 0.003). Furthermore, the variance in the importance of each question item for Community Relationships (m_var = 1.09, n = 10) was significantly greater than that for each of the other question items (m_var = 0.91, n = 36), as revealed by the Wilcoxon rank-sum test (r = 0.33, 95% CI [0.11, 0.55], p = 0.012). These findings suggest that the level of importance attached to Community Relationships varies greatly among individuals compared with other question items.

To explore these differences further, additional analyses were conducted to examine how individuals who rated Community Relationships as important differed from those who did not. In additional analyses, we calculated the partial correlation coefficients among the 10 items in Community Relationships (five items each for Community Connections and Diversity and Inclusion domains) and both demographic variables and overall WB.

Table 2. Partial correlation coefficients between the importance of community relationships and demographic variables or overall well-being.

	Importance of Community Relationships
	Community Connections					Diversity and Inclusion
Item	1	2	3	4	5	1	2	3	4	5
Demographic variable
Age	0.11	0.09	0.02	0.06	0.01	0.02	0.08	0.01	0.02	−0.01
Gender	−0.07	0.01	−0.08	0.02	0.02	−0.06	0.01	−0.01	−0.04	−0.02
Marital status	0.00	0.00	−0.05	0.05	0.04	0.01	0.00	0.06	−0.02	0.02
Residential area	−0.06	−0.03	−0.07	−0.06	−0.02	−0.08	−0.07	−0.07	−0.05	−0.06
Length of residence	0.04	0.00	0.03	0.05	0.09	0.01	−0.02	0.03	0.01	0.00
Household income	0.01	0.05	0.02	0.00	0.01	0.04	0.01	0.01	−0.01	0.03
Overall well-being
Happiness	0.20	0.20	0.14	0.20	0.23	0.12	0.16	0.01	0.17	0.15

Note: Bold and italicized numbers indicate items with the most significant absolute partial correlation coefficients in each column.

presents the results of the study.

These findings suggest that the partial correlation coefficient for overall WB (r_wb) is generally larger than that for demographic variables (e.g., age, gender). Specifically, r_wb was the largest for nine out of ten question items, and this result was statistically significant according to the binomial test (p_mx = 0.90, 95% CI [0.61, 1.00], p < 0.001). The magnitude of the partial correlation coefficient was compared based on absolute values. If there was no difference in the partial correlation coefficients between demographic variables (six variables) and overall WB (one variable), the probability that a given partial correlation coefficient was the largest was 1 ÷ (6 + 1) = 14.3%. Accordingly, the null hypothesis was defined as follows: “The probability that the partial correlation coefficient with overall WB is the largest does not exceed 14.3%”. However, for items from Life Environment and Living Authentically, the probability (p_mx) of r_wb being the largest was lower (p_mx = 0.26, 95% CI [0.13, 1.00], p = 0.080; p_mx = 0.56, 95% CI [0.25, 1.00], p = 0.004, respectively).

From the above, it was found that the importance of Community Relationships was more strongly associated with individual WB than with demographic variables, and this trend was more robust than for other categories. However, it should be noted that the results of this analysis represent correlations only and do not imply causation.

4. Discussion

This study evaluated the degree of fulfillment, importance, and contribution to overall WB (happiness) across each WB domain using the LWC indicator. We found that the WB domain related to Life Environment exhibited high levels of fulfillment, supporting H1. Additionally, items in the domains related to Living Authentically or Life Environment exhibited high levels of importance, supporting H2. However, items in the domains related to Community Relationships or Living Authentically did not exhibit sufficiently high levels of contribution to provide statistical support for H3.

Furthermore, additional analyses indicated considerable individual differences in the importance of WB domains in Community Relationships. The differences between individuals who prioritized these domains and those who did not were more strongly associated with individual WB than with demographic variables.

4.1. Interpretation of Findings

4.1.1. Fulfillment (H1)

Support for H1 suggests that Japan’s Life Environment, including the Housing Environment and Public Spaces domains, is well developed. This result can be attributed to the relatively abundant resource allocation (the fourth-largest GDP in the world) and long-standing policies aimed at developing living infrastructure. This result reflects and is consistent with Japan’s economic and structural foundations.

4.1.2. Importance (H2)

Support for H2 indicates that the fundamental aspects of the WB domains are prioritized. High rankings for Health Status, Housing Environment, and Shopping and Eating Out reflect this prioritization. Furthermore, this finding aligns with the results of previous research by Tay and Diener [24], who demonstrated that “basic needs (securing food and housing)” are the strongest predictors of life evaluation.

However, the importance of question items related to Community Relationships tended to be relatively low. This result contradicts findings in cross-cultural psychology which exhibit a tendency in East Asia to place significant importance on relationships with others [30,31]. One possible explanation for this discrepancy is that the LWC indicator is designed to assess WB from the residents’ perspective in a local community. As such, it does not explicitly include items addressing the importance of close relationships with family, friends, and colleagues in the workplace. Another potential factor is Japan’s weakening of community interactions in recent years [32]. The development of social services and infrastructure has diminished the reliance on relationships with neighbors in daily life, contributing to the weakening of neighborhood ties and the relatively low importance of Community Relationships. Compared to interpretations emphasizing the negative aspects of Community Relationships—such as social pressure or conformity—this explanation of how community dynamics have changed over time appears to align more closely with trends observed in Japanese society.

4.1.3. Contribution (H3)

One possible reason why H3 was not supported is the presence of low-contribution items within the Community Relationships and Living Authentically categories. For instance, Diversity and Inclusion 4 (“The area where I live has an atmosphere where women can thrive”) and Educational Opportunities 1 (“The area where I live provides opportunities to learn what I want to learn”) ranked last (46th) and second to last (45th), respectively. Additionally, both had negative contributions (see Table S3). This may be because these items benefit a narrower group, leading to their contributions being underrepresented. Furthermore, even eligible individuals may not fully benefit from these provisions for various reasons. In such cases, individuals may perceive a gap between their ideals and reality or feel societal pressure from their local community. This psychological burden may negatively affect their level of contribution. Further research is required to identify and address specific aspects of this issue.

Another possible explanation for H3 not being supported is that, as mentioned in the discussion of H2, the LWC indicator does not measure questions about close relationships with family and friends, and the decline of local communities in Japan continues. These factors suggest their direct contribution to subjective WB may be smaller than expected.

On the other hand, the top-ranked question items with high contribution ratings included those from the Living Authentically category, such as Self-Efficacy 1 (ranked first), Health Status 2 (ranked second), and Culture and the Arts 2 (ranked fourth), as well as items from the Community Relationships category, such as Community Connections 4 (ranked sixth). Although H3 was not supported, these results suggest the potential of identifying groups contributing to WB through an in-depth examination of the items in these categories.

Interestingly, Accidents and Crimes 1 (44th) was included among the items with low contribution rankings. This reflects the assumption that high levels of public safety are generally taken for granted in Japan. However, even a single crime incident is known to have a significantly negative impact on WB [33]. Therefore, it is essential to acknowledge that certain WB domains should not be disregarded, even when their contribution rankings are low. High levels of fulfillment and importance for these items can serve as critical cues for identifying such WB domains. The findings of this study support this view.

4.2. Additional Analysis

The tendency to value the Community Relationships category was more strongly associated with individual WB than demographic variables. These results suggest that the tendency to value this category is more closely related to subjective WB than an individual’s circumstances, such as age or income. This insight provides a valuable perspective for policymaking. If raising awareness of the importance of Community Relationships were to enhance overall WB, it might be possible to design policies that could apply to a broader population, rather than focusing solely on changes in individual circumstances.

There are several possible explanations for the association between overall WB (happiness) and the importance of Community Relationships. One explanation is that individuals with high levels of WB are more likely to foster and maintain positive and frequent interactions with others [34]. Second, such interactions provide psychological support and satisfaction, enhancing WB [35]. These interactions create as a bidirectional influence, where WB and positive human relationships mutually reinforce each other. The broaden-and-build theory, proposed by Fredrickson and Joiner, explains how positive emotions broaden attention and cognition, foster the discovery of novel perspectives, and contribute to the development of social and psychological resources [36]. This theory highlights a cyclical relationship in which WB and positive emotions mutually reinforce each other and are facilitated by broadened thinking and social resources. These dynamics are consistent with the findings of this study.

4.3. Study Implications

The rankings for the three evaluation dimensions (fulfillment, importance, and contribution) for each WB domain exhibited a strong correlation in one case; however, as a whole, they were not consistent. In particular, the lack of correlation between the rankings of importance and contribution highlights the discrepancy between their perceived contribution to overall WB (i.e., importance) and their substantive contribution to overall WB (i.e., contribution). This finding is noteworthy and warrants further investigation of the underlying causes of this discrepancy. Furthermore, inconsistencies among the evaluation dimensions suggest a risk of resource misallocation if any single dimension is absent or overlooked. Therefore, this study empirically validates the significance of evaluating WB domains by combining these three evaluation dimensions. This analysis can be conducted simply by incorporating the dimension of importance into the conventional measures of overall WB and WB domain fulfillment, thus extending the existing LWC indicator. With minimal modifications, this approach significantly enhanced analytical outcomes.

The rankings for each WB domain provide insights into why Japanese people tend to have low WB. In particular, it is noteworthy that Community Relationships contribute relatively well to overall WB, despite being perceived as unimportant and having low fulfillment. Therefore, interventions aimed at consciously improving Community Relationships will likely enhance WB. Such interventions could include activities that raise awareness about the importance of community ties, create spaces that foster community bonds, and provide opportunities for mutual support among community members. This trend is also seen in Recreation and Entertainment 1 (“The area where I live has recreational facilities for enjoying a good time”) and Culture and the Arts 1 (“The area where I live is proudly home to a thriving culture, arts, and performing arts scene”) items. Therefore, improving these areas is considered effective for enhancing overall WB. However, it is crucial to recognize that if the beneficiaries of such measures are limited or if individuals cannot access the benefits, there may be a risk of decreasing the overall WB levels.

The above findings are meaningful, as they offer specific and practical perspectives for resource allocation in policy and urban development. Moreover, these findings provide valuable insights into WB improvement policies in Japan and other countries. For example, WB domains with high importance but low contributions, such as Accidents and Crime, are likely essential for supporting daily life, and efforts to address them should be maintained. In contrast, WB domains with high contributions but low perceived importance, such as Community Relationships, are often overlooked but should be actively improved. Patterns in these three evaluation dimensions do not necessarily appear in other countries’ WB domains. However, if similar patterns emerge in different WB domains, they can be interpreted similarly, allowing for the examination of corresponding policy strategies. Therefore, the results of this study provide novel insights beyond the conventional framework of evaluating WB domains based solely on fulfillment levels, contributing to a new framework for WB evaluation. It should be noted that the policy suggestions presented in this study are illustrative in nature, intended to demonstrate the potential practical applicability of the findings.

4.4. Limitations and Directions for Future Research

This study has several limitations. One limitation is the scope of the overall WB measurement scale. Various measurement scales have been proposed in previous studies, including Cantril’s Ladder [2], the Satisfaction with Life Scale (SWLS) [37], and the Positive and Negative Affect Schedule (PANAS) [38]. In addition to Happiness, the LWC indicator measures Anticipated Happiness in Five Years, Satisfaction with Community Life, Happiness of Local Residents, and Positive Emotions of Neighbors [9]. However, this study focuses exclusively on happiness, as it represents the most comprehensive aspect of overall WB and aligns well with the criteria used to evaluate importance. Nonetheless, using a different scale as the focus of the analysis might lead to variations in the evaluation of WB domains and their relationships. This issue warrants careful consideration for each scale and remains an important topic for future research.

Furthermore, both fulfillment and importance were measured using single items to reduce participant burden in this study. However, future studies may consider using multi-item measures to allow for more nuanced analysis, while carefully balancing measurement precision and respondent burden. Finally, as this survey was conducted online only, it is possible that the sample is not fully representative. To address this issue, a mixed-mode approach should be considered, including postal surveys and other offline methods which would allow for wider participation.

As a direction for future research, we propose the inclusion of additional individual variables beyond demographic factors. For instance, previous studies have identified a relationship between subjective WB and personality traits [30,39]. However, personality is a unique individual characteristic. Therefore, it is challenging to apply it to policymaking broadly. Nevertheless, advancements in digital technology (e.g., the collection of individual data and the application of AI) may enable the estimation of personality traits and the development of flexible interventions tailored to individual differences. From this perspective, conducting detailed analyses incorporating personality traits is an intriguing point for future research.

5. Conclusions

In this study, we measured the degree of fulfillment, importance, and contribution to overall WB for each WB domain using an online survey based on the LWC indicator utilized in Japan. We then compared and analyzed the relationships among these dimensions using the rankings for each evaluation criterion. The results revealed that items in the WB domain related to Life Environment ranked high in fulfillment, whereas those associated with Living Authentically or Life Environment ranked high in importance. Meanwhile, items in the domains related to Community Relationships or Living Authentically tended to rank high in contribution, although this tendency was not statistically significant. These findings highlight the limited agreement among evaluation dimensions and underscore the necessity of integrating information from all three dimensions when formulating policies and enhancing interventions.

Furthermore, the ranking of the importance of Community Relationships was significantly lower than that of its contribution. This result suggests that Japan’s advanced living infrastructure and the weakening of local communities may influence this discrepancy. As a policy implication, interventions that consciously foster Community Relationships effectively enhance WB. Thus, a comprehensive evaluation of WB domains provides a robust foundation for appropriately prioritizing policies and urban development strategies while facilitating more effective and sustainable improvements in WB. The applicability of this framework extends beyond Japan, as its structure allows for adaptation to different cultural and policy contexts. Future research could further validate this approach, reinforcing its potential for broader application.