Satisfaction with the Living Environment in Indonesia: Social Class, Adverse Environmental Conditions, and Regional Development

1. Introduction

1.1 Background

Understanding how environmental conditions shape subjective well-being (SWB) has gained increasing prominence in academic and policy discourse, as scholars and policymakers alike recognize that quality of life extends beyond material or economic dimensions. Central to this body of research is the life satisfaction approach, which frames SWB as individuals' self-evaluations of various life domains, including their living environment (Krekel & MacKerron, 2020). Within this framework, a growing number of studies have linked environmental stressors to diminished well-being, highlighting that the conditions in which people live, breathe, and interact with natural resources have a tangible impact on life satisfaction.

Empirical evidence confirms that adverse environmental conditions—such as air and water pollution, noise disturbances, and exposure to natural hazards—negatively affect how people perceive their lives. For instance, poor air quality has been consistently linked to lower life satisfaction (Ferrer-i-Carbonell & Gowdy, 2007; Liao et al., 2015; Schmitt, 2013), while water pollution has been similarly shown to undermine well-being (Ejechi & Ejechi, 2007; Li & Zhou, 2020). Noise pollution, though often overlooked, has also been linked to negative life evaluations (van Praag & Baarsma, 2005). Beyond chronic environmental stressors, acute events such as floods and extreme weather further depress subjective well-being, especially in vulnerable populations (Purba et al., 2018; Rahman et al., 2022; Sekulova & van den Bergh, 2016).

However, much of this literature centers on general life satisfaction or happiness rather than on satisfaction with specific environmental dimensions. As van Praag et al. (2003) argue, life satisfaction is multi-dimensional, encompassing domains such as health, financial status, and environmental quality. Nevertheless, among these, environmental satisfaction remains relatively understudied—particularly in low- and middle-income countries, where environmental inequalities are often most severe. To address this gap, the present study focuses explicitly on satisfaction with environmental conditions as a distinct and policy-relevant component of subjective well-being.

This focus is especially relevant in Indonesia, where environmental well-being has become increasingly visible in national development priorities. The Central Statistics Agency [Badan Pusat Statistik; BPS] includes satisfaction with the living environment as a component of the National Happiness Index, where it contributes 3.6% to the broader "social life satisfaction" domain (BPS, 2021). Between 2017 and 2021, average environmental satisfaction scores increased from 76.09 to 81.56 (on a scale of 0 to 100), indicating a general improvement in public perceptions. However, these aggregate gains may conceal substantial disparities across social and regional groups. Limited empirical evidence exists on which populations have benefited most from these improvements or whether perceptions of environmental well-being are equitably distributed.

Environmental sociology and environmental justice research emphasize that environmental conditions are unequally experienced across social strata. Lower-income groups are more likely to be exposed to environmental harms and often lack the resources to mitigate or avoid them (Bullard, 2000; Schlosberg, 2009). These disparities are material and perceptual, shaped by differing expectations, coping strategies, and cultural capital (Bourdieu, 1984). Thus, environmental satisfaction reflects objective and socially mediated interpretations of those conditions.

Spatial infrastructure, service provision, and environmental quality disparities further reinforce existing inequalities. Urban and economically advanced regions typically offer better access to environmental amenities, while rural or underdeveloped areas face heightened exposure to risks and limited institutional capacity (Roberts et al., 2019). Given that environmental satisfaction is shaped by both physical conditions and socially embedded perceptions—filtered through class, expectations, and place—its distribution cannot be understood without reference to both individual and contextual factors.

This study addresses this need by examining how social class, exposure to adverse environmental conditions, and the broader regional economic context jointly influence satisfaction with the living environment in Indonesia. The findings aim to inform more inclusive, equitable, and context-sensitive environmental policy.

1.2 Study Objectives and Research Questions

This study investigates how individual satisfaction with the living environment in Indonesia is influenced by socioeconomic status and direct exposure to adverse environmental conditions. In the context of rapid urbanization and uneven regional development, the quality of one’s surroundings—encompassing air and water cleanliness and broader physical conditions—represents a critical but often overlooked dimension of subjective well-being.

The study's first objective is to assess the extent to which social class affects satisfaction with the living environment. Individuals from higher socioeconomic backgrounds may enjoy better physical environments due to access to superior housing, neighborhood amenities, and infrastructure. The second objective is to evaluate how individual-level exposure to environmental hardships—such as foamy or polluted water, smelly or smoky air, and the impact of natural disasters—shapes environmental satisfaction. These experiences reflect real and immediate burdens that disproportionately affect disadvantaged populations.

The third and central objective of the study is to examine whether the broader regional economic context conditions the relationship between social class and satisfaction with the living environment. Specifically, the study investigates the moderating role of provincial-level economic development, as measured by Gross Regional Domestic Product (GRDP) per capita. This approach enables understanding whether socioeconomic advantages translate into higher environmental satisfaction more strongly in wealthier provinces than less developed ones.

This study employs a multilevel analytical framework using nationally representative longitudinal data from Indonesia, enabling the integration of individual-level and provincial-level variables in a single empirical model. Such an approach captures both vertical (social) and horizontal (spatial) dimensions of inequality in environmental satisfaction, offering a comprehensive understanding of how personal and contextual factors interact to shape subjective perceptions of the living environment.

To address these aims, the study is guided by the following research questions (RQs):

• RQ1: To what extent does social class influence individual satisfaction with the living environment in Indonesia?

• RQ2: How do direct exposures to adverse environmental conditions—such as poor water quality, polluted air, and natural disasters—affect individuals' satisfaction with their living environment?

• RQ3: Does provincial GRDP per capita moderate the relationship between social class and satisfaction with the living environment?

By integrating individual and contextual variables within a multilevel analytical framework, the study offers a policy-relevant and empirically grounded contribution to understanding environmental inequality, spatial disparity, and subjective well-being in Indonesia.

1.3 Contribution of the Study

This study contributes to the literature on environmental well-being by examining how social class and environmental exposure shape satisfaction with the living environment in Indonesia. It advances a sociological perspective by linking environmental satisfaction to social stratification, applying environmental justice theory in a context often underrepresented in global research. Methodologically, the study employs a multilevel framework that combines individual-level exposure to environmental hardship with provincial economic development (GRDP per capita). This approach highlights how regional contexts condition the relationship between socioeconomic status and perceived environmental quality.

The study also offers policy-relevant insights by identifying whether economic growth leads to equitable improvements in local living environments or reinforces class-based disparities. By integrating subjective perceptions, exposure data, and structural context, it provides a practical tool for assessing environmental inequality in decentralized settings. Its findings contribute to interdisciplinary debates on equity, well-being, and sustainable development in the Global South.

2. Conceptual Framework

This study is grounded in a social justice perspective, emphasizing the equitable distribution of environmental quality and well-being across social groups and geographic regions. The living environment—defined here as the immediate physical and environmental conditions surrounding one's residence, including air and water quality—is conceptualized as both a determinant and a manifestation of structural inequality in contemporary Indonesia.

Drawing on environmental justice theory, the study frames satisfaction with the living environment as a subjective yet meaningful indicator of how environmental resources and burdens are unequally distributed. Environmental justice literature highlights that disadvantaged communities are systematically more likely to reside in environmentally degraded and under-serviced areas with limited access to clean air, safe water, and resilient infrastructure (Bullard, 2000; Mohai et al., 2009; Schlosberg, 2009). This unequal distribution of environmental goods and harms constitutes a form of distributive environmental injustice (Walker, 2011), contributing to lower environmental satisfaction among marginalized groups.

This perspective aligns with sociological theories of stratification, particularly Bourdieu's (1984) view that economic capital shapes individuals' ability to access desirable and secure residential environments. The environment is not merely a physical backdrop but a socially structured and classed space, where inequalities in material and symbolic resources manifest in differentiated access to environmental quality.

The conceptual model also incorporates insights from spatial justice and contextual inequality literature. In Indonesia, subnational disparities in infrastructure, environmental regulation, and public services mean that individuals' experiences with their environment are shaped by personal class position and regional-level economic conditions (Nasution, 2016; Roberts et al., 2019). Provinces with higher Gross Regional Domestic Product (GRDP) per capita may offer improved infrastructure and environmental quality. However, whether these collective benefits translate into more equal environmental satisfaction across social classes remains empirically uncertain. This study thus applies a contextual moderation approach—similar to the multilevel strategy employed by Subramanian et al. (2003) in public health research—to examine how provincial GRDP may strengthen or weaken the relationship between social class and environmental satisfaction.

Including direct environmental exposure—such as experiencing polluted water, smoky air, or recent natural disasters—further operationalizes environmental inequality at the experiential level. These proximate environmental stressors are expected to influence all individuals' environmental satisfaction negatively but may disproportionately impact those already facing class-based disadvantages (Evans & Kantrowitz, 2002; Hajat et al., 2015). They also serve as indicators of environmental vulnerability, capturing localized and often chronic environmental burdens within communities.

Empirical studies support this multilevel conceptual framing. Using household data from OECD countries, Rehdanz and Maddison (2008) found that higher-income individuals consistently report greater satisfaction with local environmental quality, indicating that economic resources influence actual and perceived environmental conditions. Welsch (2006) demonstrated that air pollution negatively affects life satisfaction in European countries, with more pronounced effects among lower-income individuals who may be more exposed or less protected. In the UK context, MacKerron and Mourato (2009) linked real-time self-reported happiness to urban environmental conditions using mobile app data, showing that personal socioeconomic status and city-level pollution jointly shape subjective well-being. Similar findings have emerged in Southeast Asia: Priyanto et al. (2024) found that higher CO₂ emissions were associated with lower life satisfaction across multiple countries, with the effect being moderated by individuals’ financial and health status. Krekel and MacKerron (2020) further emphasized the value of combining subjective well-being data with objective environmental indicators to understand how environmental quality and unequal distribution affect life satisfaction.

By situating environmental satisfaction at the intersection of class-based inequality, environmental hardship, and regional development, this study contributes to broader debates in environmental sociology, subjective well-being, and environmental governance in Indonesia and comparable middle-income contexts. It positions environmental satisfaction as a reflection of ecological conditions and a lens through which to interrogate broader systems of environmental injustice and spatial inequality.

This two-level multilevel framework—integrating individual-level factors (social class and exposure to adverse environmental conditions) and a provincial-level variable (GRDP per capita)—provides a structured approach to examining how personal circumstances and regional contexts influence satisfaction with the living environment. It underscores the importance of accounting for material environmental conditions and the social and spatial dimensions of inequality that shape environmental well-being (Evans & Kantrowitz, 2002).

3. Methodology and Data

3.1 Multilevel Mixed-Effects Ordered Logistic Model

This study employs a multilevel mixed-effects ordered logistic regression model to account for both the hierarchical data structure and the ordinal nature of the dependent variable—satisfaction with the living environment. Theoretically, this approach aligns with ecological and stratification frameworks that emphasize the influence of both individual characteristics and broader contextual conditions. Empirically, individuals (level 1) are nested within provinces (level 2), warranting a multilevel specification to avoid biased estimates from ignoring clustered observations. The ordered logistic framework is appropriate given the dependent variable’s rank-ordered response format. Random intercepts are included at the provincial level to capture unobserved heterogeneity and account for variations in macroeconomic and structural conditions across provinces. This modeling strategy enables a robust examination of the relationship between social class and environmental satisfaction by incorporating both micro- and macro-level determinants within a single, coherent analytical framework (Rabe-Hesketh & Skrondal, 2022).

The empirical model is based on a latent variable that represents individuals' underlying satisfaction with the living environment. It examines the relationship between this latent construct and a set of explanatory variables, including individual-level characteristics, household attributes, and province-level contextual factors. The specification of the model is as follows:

The link between the observed ordinal outcome  and the underlying latent variable  is specified using a standard threshold model:

where  denotes the unobserved (latent) satisfaction with the living environment for individual i residing in province j;  is the corresponding observed ordinal outcome. The vector  includes individual and household characteristics for individual i in province j, such as social class and direct exposure to adverse environmental conditions. The vector  represents province-level contextual variables, specifically GRDP per capita. The term  denotes covariates associated with the random effects; since this is a random intercept model,  is a scalar equal to 1. The term  captures unobserved province-level random effects, while  represents the individual-level error term, assumed to follow a standard logistic distribution with mean 0 and variance 𝜋2/3, and is independent of.

3.2 The Happiness Level Measurement Survey (SPTK)

This study utilizes data from the 2021 wave of the Survei Pengukuran Tingkat Kebahagiaan [Happiness Level Measurement Survey; SPTK], conducted by Indonesia’s Central Statistics Agency (BPS, 2021). The SPTK is a nationally representative survey covering all provinces and districts, including regencies (kabupaten) and municipalities (kota). The household serves as the unit of analysis, with one adult respondent—typically the household head or their spouse—randomly selected to represent each household. To ensure consistency and relevance to the study’s focus, the analytical sample is restricted to 70 508 respondents aged 25 to 80 who are either employed or primarily engaged in household care, thereby capturing individuals whose daily routines are likely to be directly influenced by local environmental conditions.

Satisfaction with environmental conditions was assessed using the Cantril ladder scale (Cantril, 1965), as implemented in the 2021 SPTK survey. Respondents were presented with a visual ladder ranging from 0 (indicating complete dissatisfaction) to 10 (indicating complete satisfaction) and asked, “How satisfied are you with the state of the living environment?” This scale provides a standardized and intuitive measure of subjective environmental well-being, allowing individuals to position themselves along a continuum of perceived environmental quality.

Figure 1 presents the distribution of self-reported satisfaction with the living environment in 2021. The data reveal a left-skewed pattern, with most respondents reporting higher satisfaction levels. The most frequently selected response was the eighth rung, chosen by 39.1% of respondents, while fewer individuals selected lower rungs (0–7), and a notable share selected the top rungs (9–10). This pattern suggests a generally positive evaluation of local environmental conditions, with a concentration of responses reflecting moderate to high satisfaction. These descriptive findings provide essential context for interpreting the variation examined in the multilevel regression models.

Figure 1: Satisfaction with Living Environment, 2021

Source: Author’s calculation

Due to the small proportion of respondents selecting satisfaction levels between zero and six, these categories were combined to ensure a more balanced and analytically meaningful distribution. This recoding allows for more robust comparisons across response groups in subsequent analyses (Liu & Agresti, 2005).

3.3 Social Class

This study employs a structured methodological approach, using monthly per capita household expenditures (PCE) as the primary determinant of social class. While the information on employment status and the sector is available for the household head and spouse, these variables alone do not adequately reflect the multidimensional nature of the class. PCE is therefore used for its practicality and suitability for large-scale household surveys. As Barone et al. (2022) noted, income-based indicators are widely accessible and commonly used in social class research, although they may overlook non-economic dimensions and be subject to reporting variability. This classification approach is consistent with previous studies, such as Piff and Moskowitz (2018), who examined emotional well-being across income groups in the United States, and Zhang and Chen (2023), who investigated health disparities by social class in China.

This study categorizes individuals into four income-based social classes based on reported monthly household income. The lower class includes those earning less than IDR 1.8 million monthly, comprising 27.7% of the sample. The lower-middle class consists of individuals earning between IDR 1.8 million and IDR 3.0 million, accounting for 31.5% of respondents. The upper-middle class, representing 20.6% of the sample, includes those with incomes between IDR 3.0 million and IDR 4.8 million. Lastly, the upper class comprises individuals earning more than IDR 4.8 million per month, making up 20.3% of the population. This classification enables a clear, policy-relevant segmentation of socioeconomic groups and supports the study’s broader goal of examining inequality in environmental satisfaction and related life outcomes .

3.4 Exposure to Adverse Environmental Conditions

Before rating their satisfaction with the living environment, respondents were first presented with three preliminary questions designed to prompt reflection on recent environmental conditions. The first question asked whether, in the past month, they had experienced issues with local groundwater—specifically, whether it appeared turbid (cloudy), discolored, had an unpleasant taste, produced foam, or emitted an unpleasant odor. Responses were recorded as "yes" or "no" for each condition. The second question followed a similar format, inquiring about air quality, specifically malodorous air, dust-laden air, and smoke-filled air in the respondent's neighborhood. The third question addressed natural disaster exposure, asking how often the respondent's neighborhood had been affected by events such as floods or flash floods in the past year, with response options of "more than once," "once," or "never." These preliminary items were included to help anchor respondents' subsequent evaluations of their environmental satisfaction by encouraging recall of concrete experiences.

As illustrated in Figure 2, fewer than 10% of respondents reported experiencing any single adverse water or air condition in the past month. By contrast, approximately 15% indicated that their neighborhood had been affected by a natural disaster at least once in the past year. These descriptive patterns highlight that while routine water and air pollution exposure appear relatively limited, natural disasters remain a more prominent environmental concern for a significant population segment. These indicators provide essential contextual grounding for interpreting how specific environmental experiences may shape broader perceptions of ecological well-being.

Figure 2: Exposure to Adverse Environmental Conditions, 2021

Source: Author’s calculation

Notes: The presence of a natural disaster indicates whether respondents have been affected by a natural disaster at least once in the past year. 

3.5 Data Summary

Table 1 presents the means and standard deviations of all variables used in the analysis. The variables cover individual, household, and provincial-level contextual characteristics.

Table 1: Mean and Standard Deviation of Data

Source: SPTK and BPS 

4. Estimation Results and Discussions

The multilevel mixed-effects ordered logistic regression results, summarized in Table 2, are presented across three model specifications, with all coefficients reported as odds ratios for ease of interpretation. Column [1] presents the Baseline Model, which includes individual- and household-level variables and a province-level contextual variable—GRDP per capita—to account for broader structural influences. Column [2] introduces the Extended Model, which builds upon the Baseline Model by incorporating measures of adverse environmental exposure, specifically perceived water and air quality problems, and experience with natural disasters in the past year. Column [3] presents the Interaction Model, which extends the Extended Model by including interaction terms between social class and provincial GRDP per capita to assess whether regional economic conditions moderate the relationship between social class and satisfaction with the living environment. This stepwise modeling strategy systematically explores both main effects and context-dependent mechanisms shaping environmental satisfaction.

Table 2: Multilevel Mixed-effects Ordered Logistic Estimates

Notes: *** statistically significant at the 1% level, ** 5%, * 10%.

An initial null model was estimated to assess the extent of clustering in satisfaction with the living environment across provinces. This intercept-only model, which includes a random intercept at the provincial level but excludes explanatory variables, serves as a baseline for evaluating contextual variation. This model's intraclass correlation coefficient (ICC) was 0.027, indicating that approximately 2.7% of the total variation in environmental satisfaction is attributable to differences between provinces. Although this value falls below the conventional 5% threshold, multilevel modeling remains appropriate. Snijders and Bosker (2012) noted that even relatively small ICCs can warrant hierarchical models, especially when contextual factors are theoretically relevant. This approach is further supported by a likelihood ratio test comparing the multilevel model with a single-level ordered logistic regression, yielding a chi-square statistic of 1,348.69 (p < 0.001), which confirms a significantly better model fit. Furthermore, ignoring the multilevel structure, even when between-group variance is modest, can result in biased standard errors and an elevated risk of Type I error (Hox et al., 2017). While the detailed results of the null model are not reported in Table 2, they provide essential justification for the multilevel analytical approach used in the subsequent models.

Following the null model, a variance inflation factor (VIF) test was conducted to assess the presence of multicollinearity among the explanatory variables. Using an ordinary least squares regression that included the same set of covariates specified in the Baseline Model, the test results show that all independent variables have VIF scores below 2. This confirms that multicollinearity is not a concern in the data and that the estimated coefficients in the subsequent multilevel ordered logistic regression can be interpreted with confidence (Kutner et al., 2004).

Based on model fit statistics, the progression from the Baseline to the Extended and Interaction models demonstrates a clear improvement in explanatory power. Log-likelihood values increasing with each step confirm that each successive model significantly outperforms the previous one. The slight increase in the intraclass correlation coefficient (from 0.027 to 0.031) indicates that provincial-level clustering explains a modest yet meaningful share of the variance in environmental satisfaction. The model selection criteria further support this improvement. The AIC decreases across models, with the Interaction model showing the best overall fit (AIC = 202,284.1). However, the BIC, which penalizes complexity more stringently, favors the Extended model (BIC = 202,495.7), suggesting it achieves a more efficient balance between fit and parsimony. Together, these model diagnostics indicate that the Extended model provides a strong improvement by accounting for the direct effects of environmental exposure, while the Interaction model adds analytical nuance by incorporating contextual moderation. Both models underscore the combined influence of individual-level and structural factors in shaping satisfaction with the living environment in Indonesia.

4.1 Stratification and Perceptions of the Living Environment (RQ1)

Estimates from the Baseline model (Column [1]) reveal a clear association between social class and satisfaction with the living environment. Compared to individuals in the lower class, those in the upper class are significantly more likely to report higher levels of satisfaction (OR = 1.172, p < 0.001), indicating a 17.2% greater likelihood of reporting higher satisfaction. Individuals in the upper-middle class are also somewhat more likely to be satisfied (OR = 1.037), though this effect is only marginally significant (p = 0.085). In contrast, those in the lower-middle class do not differ significantly from the lower class (OR ≈ 1.000, p = 0.990), suggesting no meaningful advantage in environmental satisfaction for this group.

The results indicate a clear socioeconomic gradient in perceived environmental quality, with higher satisfaction levels concentrated among individuals from the upper class (Rehdanz & Maddison, 2008). This pattern suggests that individuals with greater economic resources are either more likely to reside in areas with superior infrastructure and environmental conditions or to perceive their surroundings more favorably due to increased autonomy and comfort (Evans & Kantrowitz, 2002). The absence of significant differences among lower and lower-middle classes suggests that improvements in environmental satisfaction only emerge at the top end of the class spectrum.

These findings directly address Research Question 1 (RQ1) by demonstrating that social class significantly influences individuals’ satisfaction with their living environment. The analysis shows that individuals in the upper class report notably higher satisfaction levels, indicating a pronounced disparity linked to socioeconomic status. This pattern suggests that environmental well-being in Indonesia is not uniformly experienced but is instead structured by broader social hierarchies. The results support the environmental justice perspective, which emphasizes that more privileged groups often disproportionately enjoy environmental benefits (Walker, 2011).

4.2 Effects of Environmental Hardship on Living Environment Satisfaction (RQ2)

The analysis includes nine variables capturing direct exposure to environmental hardship: five related to water quality, three to air quality, and one to the experience of natural disasters. The five water-related items—cloudiness, discoloration, unpleasant taste, foaming, and odor—reflect different aspects of perceived water pollution in respondents' neighborhoods. Given their conceptual alignment and high internal consistency (Cronbach's α = 0.792), these items were combined into a composite index representing adverse water conditions exposure (Tavakol & Dennick, 2011). This index was calculated as the average of the five binary items and used as a continuous predictor in the regression model.

In contrast, when tested as a unified scale, the three air-related items—perceived malodor, dust-laden air, and smoke-filled air—did not exhibit sufficient internal consistency (Cronbach's α = 0.454). Due to this low reliability and their distinct physical characteristics, these items were retained as separate variables. The natural disaster variable was also treated independently, which captures whether the respondent's neighborhood experienced events such as floods or flash floods in the past year. This decision reflects the conceptual difference between sudden environmental events and ongoing environmental conditions. Unlike continuous exposures such as poor air or water quality, natural disasters are episodic and represent acute environmental shocks.

The estimation results from the Extended model (Column [2]) reveal that exposure to adverse environmental conditions—both chronic and acute—significantly reduces individuals' satisfaction with their living environment. All five environmental variables in the model are statistically significant, with odds ratios below 1, indicating negative associations with the outcome.

Exposure to adverse water conditions, captured through the composite index, shows the strongest effect (Ejechi & Ejechi, 2007; Li & Zhou, 2020). Respondents experiencing turbid, discolored, unpleasant-tasting, foamy, or malodorous water are approximately 62.7% less likely to report higher levels of environmental satisfaction (OR = 0.373, p < 0.001). Similarly, those exposed to malodorous air are 53.5% less likely to express higher satisfaction (OR = 0.465, p < 0.001), and exposure to dust-laden air is associated with a 33.7% reduction in the odds of higher satisfaction (OR = 0.663, p < 0.001). While the impact of smoke-filled air is smaller, it remains statistically significant, with an odds ratio of 0.844 (p = 0.005), suggesting a 15.6% reduction in the likelihood of greater satisfaction (Ferrer-i-Carbonell & Gowdy, 2007; Liao et al., 2015; Schmitt, 2013). Additionally, within the past year, individuals who reported that their neighborhoods had been affected by a natural disaster—such as floods or flash floods—are 52.7% less likely to report higher satisfaction with their local environment (OR = 0.473, p < 0.001). (Purba et al., 2018; Rahman et al., 2022; Sekulova & van den Bergh, 2016).

These findings provide direct and robust support for Research Question 2 (RQ2) by showing that exposure to adverse environmental conditions significantly undermines individuals’ satisfaction with their living environment. The consistent and statistically significant negative associations across all indicators confirm that environmental hardships, whether chronic (e.g., water and air pollution) or acute (e.g., disasters), substantially impact perceived environmental well-being. This reinforces the argument that subjective satisfaction with the living environment is strongly shaped by individuals' lived experiences of environmental degradation and risk.

4.3 Multilevel Dynamics: Class and Economic Context in Environmental Satisfaction (RQ3)

The estimation results from the Interaction model (Column [3]) reveal important nuances in the relationship between social class and satisfaction with the living environment, particularly in the provincial economic context. Compared to individuals in the lower class, those in the upper-middle and upper classes are significantly more likely to report higher satisfaction (OR = 1.047, p = 0.032; OR = 1.181, p < 0.001, respectively), indicating a clear stratification in perceived environmental well-being. However, the lower-middle class does not differ significantly from the lower class in this regard (OR = 0.990, p = 0.582).

While provincial GRDP per capita’s main effect is not statistically significant (OR = 0.915, p = 0.404), a pattern consistent with earlier findings that contextual income indicators often lack direct explanatory power for well-being when individual characteristics are controlled for (Knight et al., 2009), the interaction terms between social class and GRDP per capita reveal significant moderation effects. Specifically, the positive effects of upper-middle and upper-class status on environmental satisfaction are significantly attenuated in wealthier provinces (upper-middle × GRDP: OR = 0.888, p = 0.014; upper × GRDP: OR = 0.906, p = 0.034). These negative interaction terms suggest that as provincial economic development increases, the relative advantage of higher social class in shaping satisfaction with the living environment diminishes. This pattern may reflect rising expectations or increased awareness of environmental problems in more developed regions, which could narrow perceived differences across social groups.

These findings directly address Research Question 3 (RQ3) by demonstrating that the influence of social class on environmental satisfaction varies depending on the level of provincial economic development. The results support this hypothesis by showing that the strength of the class-based advantage in environmental satisfaction is not uniform across provinces but is significantly shaped by regional economic conditions. This underscores the importance of considering both individual socioeconomic positions and broader structural contexts when analyzing environmental well-being. These patterns align with Morrison’s (2011) observation that urban and economically advanced regions while offering greater objective opportunities, may paradoxically reduce subjective well-being due to increased stressors, rising expectations, and heightened awareness of environmental shortcomings. The observed attenuation of class-based environmental satisfaction in wealthier provinces may thus reflect a broader trade-off, wherein high development and productivity coincide with diminishing marginal returns to well-being among higher-status individuals.

4.4 Discussion: Environmental Justice and Unequal Environmental Satisfaction

The findings of this study strongly align with environmental justice theory, which emphasizes that environmental quality—like other public goods—is unequally distributed along lines of social class and geographic location. This theory provides a compelling framework for understanding how structural disadvantage and contextual development shape individuals’ satisfaction with their living environments. The most disadvantaged communities are systematically exposed to greater environmental hazards and have less access to environmental amenities, reinforcing and reproducing broader social and spatial inequality (Bullard, 2000; Mohai et al., 2009; Schlosberg, 2009).

Empirically, the study demonstrates that individuals from upper and upper-middle classes report significantly higher satisfaction with their living environments, while those in the lower and lower-middle classes are notably less satisfied. This social gradient reflects what environmental justice literature refers to as distributive environmental injustice—a pattern in which environmental benefits (e.g., clean air and water, safe surroundings) accrue to the more privileged, while environmental harms are concentrated among the less advantaged (Agyeman et al., 2002; Walker, 2011). In the Indonesian context, this suggests that wealthier individuals may enjoy better housing conditions, more resilient infrastructure, and greater access to basic environmental services—factors that positively shape their perceptions of the environment.

Furthermore, the study highlights the strong and consistent adverse effects of direct environmental exposures—inferior water quality, smoke, dust, bad odors, and disaster experience—on environmental satisfaction. These findings lend empirical weight to the environmental justice argument that exposure to environmental degradation is not randomly distributed but disproportionately affects those already facing socioeconomic disadvantage. Lower-class respondents, who are more likely to reside in vulnerable areas, face compounding disadvantages as they deal with both material hardship and environmental stressors. This supports the notion of cumulative environmental burdens, a key concern in environmental justice research (Chakraborty & Maantay, 2011; Morello-Frosch et al., 2001).

Crucially, the moderating role of provincial GRDP per capita offers new insights into the interaction between individual and contextual inequalities. The finding that class-based differences in environmental satisfaction diminish in wealthier provinces suggests that broader regional economic development can partially mitigate environmental disparities. This aligns with more recent strands in environmental justice theory that emphasize place-based structural interventions, highlighting how improved public infrastructure, environmental services, and governance at the regional level can benefit lower-income groups and help narrow class-based disparities in environmental well-being (Pellow, 2018; Reed & George, 2011). These perspectives argue that environmental justice must move beyond distributive outcomes to address the structural, institutional, and spatial factors that produce unequal exposure and access to environmental goods—making regional economic context a critical component in addressing environmental inequalities.

These findings suggest that satisfaction with the living environment in Indonesia is not merely an individual or subjective phenomenon but is embedded in systems of social stratification and regional inequality. The unequal distribution of environmental quality and the differentiated effects of environmental exposures underscore the need to frame environmental well-being as a justice issue, not just a technical or infrastructure challenge. Addressing these inequalities calls for integrated policy responses—such as equitable urban planning, targeted environmental investment in underserved areas, and stronger institutional frameworks for environmental protection—particularly in communities that are historically marginalized in the development process.

5. Conclusion

5.1 Summary of Key Findings

The results of this study demonstrate that a combination of social class, environmental exposure, and regional economic conditions shapes satisfaction with the living environment in Indonesia. A clear stratification is observed, with individuals in the upper and upper-middle classes reporting significantly higher levels of environmental satisfaction, while those in the lower and lower-middle classes report notably lower satisfaction. This pattern suggests that environmental well-being is not equally experienced across socioeconomic groups and tends to favor those with greater access to resources, more secure housing, and better-quality environments.

In parallel, direct exposure to environmental stressors—such as adverse water conditions, polluted air, and natural disasters—shows strong and consistent negative effects on environmental satisfaction. Poor water quality exerts the most substantial impact, followed by malodorous air, dust-laden air, smoke, and disaster experience. These findings emphasize that chronic environmental degradation and acute shocks significantly undermine people’s evaluations of their local environment.

Furthermore, the analysis reveals that the provincial economic context shapes the relationship between social class and environmental satisfaction. In wealthier provinces, the relative advantage enjoyed by upper-class individuals diminishes, suggesting that regional development may help reduce class-based disparities in environmental well-being. This may be due to broader environmental improvements or more uniform expectations among residents in economically advanced areas.

These findings address all three research questions by demonstrating that satisfaction with the living environment is not only stratified by social class but also profoundly influenced by environmental exposures and moderated by the broader economic context in which individuals live. They underscore the importance of integrating social and spatial dimensions into efforts to improve environmental well-being and ensure that environmental benefits are equally shared across people and places.

5.2 Policy Implications

The findings highlight several key priorities for improving environmental well-being in Indonesia. First, the apparent disparities in environmental satisfaction across social classes suggest that environmental programs must be complemented by targeted outreach and engagement strategies, particularly in lower-income communities. Increasing awareness, trust, and community participation will ensure that interventions are understood, accepted, and sustained in areas where environmental risks are high and perceived benefits are low. Second, the substantial adverse effects of exposure to poor water and air quality and natural disasters point to the urgent need for investments in basic environmental services—such as clean water access, waste management, flood mitigation, and urban greening. These investments should prioritize underserved areas, where the impact on residents' well-being will likely be greatest. Instruments like the Specific Allocation Grant (DAK) and Village Funds (Dana Desa) can be critical in financing visible, locally relevant improvements directly affecting residents' satisfaction.

Third, regional planning processes—such as the Regional Medium-Term Development Plan (RPJMD)—should better incorporate socioeconomic differentiation into environmental target-setting. The study shows that in more affluent provinces, satisfaction is shaped by service availability and expectations for higher environmental standards and government responsiveness. This calls for a more context-sensitive policy design reflecting material conditions and subjective perceptions across different communities. Finally, the weak and inconsistent relationship between GRDP per capita and environmental satisfaction highlights the limitations of relying on economic growth alone to improve well-being. Regional governments should develop integrated monitoring systems that combine environmental, social, and perceptual indicators to more effectively track progress, guide interventions, and build public trust. Promoting environmental justice and well-being requires a multidimensional approach beyond infrastructure provision to address inequality, exposure, and local voice.

5.3 Directions for Future Research

Future research should explore the psychological, cultural, and institutional mechanisms that mediate the relationship between social class and satisfaction with the living environment. Factors such as environmental expectations, perceived fairness, trust in government, and underlying environmental values (Stern, 2000) may help explain why individuals in similar physical environments report differing levels of satisfaction. Empirical studies have shown that institutional trust, environmental concern, and risk perception shaped by public awareness significantly influence subjective environmental well-being (Helliwell & Wang, 2011). Incorporating these attitudinal and normative dimensions would deepen understanding of how environmental satisfaction is socially constructed, particularly in the context of unequal class positions and divergent lived experiences.

Longitudinal or panel data would enable the analysis of changes in environmental satisfaction over time, particularly in response to infrastructure upgrades, policy reforms, or environmental shocks. Such designs could also capture life-course dynamics and the long-term effects of chronic exposure or mobility across class and place. Previous research has emphasized the value of panel data in controlling for unobserved individual heterogeneity and capturing the causal impact of environmental changes on subjective well-being (Rehdanz & Maddison, 2008). Comparative studies across countries or regions could help determine whether the class-based and contextual patterns observed in Indonesia are specific to its development trajectory or reflect broader global trends in environmental inequality.

Finally, future studies should examine how environmental improvements are perceived, interpreted, and valued across different socioeconomic groups. Understanding these perceptions is essential for designing inclusive and equitable environmental policies, ensuring that interventions resonate with local priorities and foster public engagement. Mixed-methods research—including qualitative interviews and participatory approaches—could be especially valuable in capturing these nuanced perspectives and bridging the gap between technical solutions and lived experience (Phillip et al., 2025).

Author Contributions: The author solely conceived and designed the study, performed the data analysis, interpreted the results, and prepared the manuscript.

Funding: The author received no financial support for the research, authorship, and/or publication of this article.

Conflicts of Interest: The author declares no competing interests.

Informed Consent Statement/Ethics approval: Ethical approval and informed consent were not applicable, as the study did not involve human subjects directly engaged by the author.

Data Availability Statement: Access to the 2021 Happiness Level Measurement Survey (SPTK) dataset is restricted due to contractual agreements with Badan Pusat Statistik (BPS). Interested researchers may obtain the dataset directly from BPS via https://www.bps.go.id.

Declaration of Generative AI and AI-assisted Technologies: This study has not used any generative AI tools or technologies in the preparation of this manuscript.