Understanding the Socio-Economic Drivers of Subjective Well-Being in Older Adults: Evidence from Jambi Province

1. Introduction

Indonesia is now stepping into a new chapter where the number of older adults—those aged 60 and above—is growing significantly, making up more than 10% of the population. This shift is not unique to Indonesia; it is a global phenomenon touching nations at all stages of development, from the most advanced economies to those still growing. According to data from the Central Statistics Agency (BPS), the number of elderly individuals in Indonesia increased from 7.7 million in 1980 to 29.7 million in 2020, accounting for approximately 10.76% of the total population. This increase is primarily driven by rising life expectancy, which grew from 55.3 years in 1980 to 73.6 years in 2022 [1,2]. The aging population presents new challenges, particularly in the health, social, and economic domains, especially for older people in areas with limited access to essential services.

Jambi is one of the provinces in Indonesia experiencing a significant rise in its elderly population. The percentage of elderly individuals in Jambi increased from 3.55% in 1980 to 8.59% in 2020, with a growth rate surpassing the national average [1,2]. Unlike major cities such as Jakarta or Surabaya, most areas in Jambi are characterized by semi-urban and rural settings with distinct demographic and socio-economic conditions. Jambi’s economy is primarily driven by agriculture and natural resource-based industries [3,4]. Limited access to social security, elderly-friendly healthcare services, and adequate community support pose major challenges to the well-being of older people in this region [5,6,7]. Many older adults in Jambi have spent their careers working in the informal sector [8]. Many encounter financial uncertainty as they age without the safety net of pension benefits or a consistent income.

Elderly individuals undergo physical, mental, and social changes that require adaptation to maintain their well-being [9,10,11]. Without enough support, many elderly individuals may face challenges such as low self-esteem, emotional distress, and loneliness [12,13,14]. Understanding what affects their well-being is key to creating policies that genuinely improve their quality of life.

Various studies have shown that socio-economic factors such as education level, family status, health, social support, and economic stability play a crucial role in determining the well-being of older people [15,16,17,18,19]. However, the impact of these factors is not uniform; it varies depending on geographical conditions and access to social services in different regions.

In the Indonesian context, several studies indicate that elderly individuals in urban areas have better access to healthcare services and social security than those in rural areas [20,21]. Conversely, elderly individuals in rural areas are more vulnerable to malnutrition, cognitive disorders, and dependence on family members to meet their basic needs [22].

In addition to physical health, the mental well-being of older people in Indonesia is also influenced by socio-economic factors. People with lower education levels and incomes, along with a high number of chronic health issues, often experience higher rates of depression, particularly among older adults living in rural areas [23]. However, studies also emphasize how crucial family bonds and social connections are for helping older individuals stay healthy and happy.

In communities with strong social support networks, elderly individuals tend to experience better emotional well-being. However, rural healthcare services remain more intervention-focused than preventive, making them less effective in comprehensively improving elderly well-being [24,25,26].

Differences in elderly well-being between urban and rural areas are seen in Indonesia and several Southeast Asian countries. Research in Myanmar, Vietnam, and Malaysia shows that economic conditions, social support, and cultural values influence older adults’ quality of life.

In Myanmar, research by Zin et al. [27] found that elderly individuals in peri-urban areas experience a lower quality of life compared to those in urban areas, primarily due to economic limitations, social constraints, and restricted access to healthcare services. In Vietnam, on the other hand, intergenerational relationships and social support are important predictors of elderly well-being, and urban elderly individuals receive stronger support from their children than their rural counterparts [28]. This implies geographical variation in the operation of family support systems.

In Malaysia, a study by Wan-Ibrahin & Zainab [29] revealed that while family support remains a crucial element of elderly well-being in rural areas, modernization has reduced family involvement in elderly care in urban settings.

Furthermore, [30] showed that older adults who live in rural Malaysia are likely to be more frail and undernourished than older adults who live in urban areas. This means that healthcare interventions need to be strengthened within rural societies.

Despite the extensive research on elderly well-being in various countries, studies on similar patterns in Indonesia, particularly outside Java, remain limited. Most existing research focuses on economic aspects and access to healthcare services. At the same time, social factors such as community support and family roles have not been widely explored in the context of semi-urban and rural areas.

Therefore, this study explores the socio-economic factors influencing the subjective well-being of older people in Jambi, including age, gender, education level, marital status, household roles, household size, employment status, income level, ethnicity, and place of residence (urban or rural).

2. Materials and Methods

2.1. Type and Source of Data

This study relies on primary data from respondents 60 years old and above within the Province of Jambi. The secondary data are also obtained from the respective institutions to understand the elderly population profile as a whole.

2.2. Population and Sample

The population in this study consists of all elderly individuals residing in Jambi Province. The sample selection follows a two-stage stratified method, as outlined below:

• Selection of Research Locations
  • One city (Jambi City) represents the Western Region, and one regency (Kerinci Regency) represents the Eastern Region.
  • These locations were selected based on the highest elderly population figures, according to the National Population and Family Planning Agency (BKKBN).
• Selection of Respondents
  • Two kelurahan/desa (urban villages/rural villages) were chosen in each selected region based on the highest elderly population.
  • The sample size was 10% of elderly households (with at least one elderly individual meeting the study criteria).
  • Elderly households were randomly selected using Random Number Generator (RNG) software.
  • If a household contained more than one elderly individual, one person was randomly chosen as the respondent.

Based on these stages, the sample size and its distribution are as follows:

Table 1. Sample distribution by research location.

Location	Sample Size
Kerinci Regency
Desa Koto Rendah	29
Desa Baru Sungai Tutung	24
Jambi City
Kelurahan Eka Jaya	73
Kelurahan Kenali Besar	81
Total	207

Table 1. Sample distribution by research location.

Location	Sample Size
Kerinci Regency
Desa Koto Rendah	29
Desa Baru Sungai Tutung	24
Jambi City
Kelurahan Eka Jaya	73
Kelurahan Kenali Besar	81
Total	207

2.3. Data Collection Instruments

Data was collected using a structured questionnaire to gather information on socio-economic characteristics and indicators of elderly well-being.

2.4. Analysis Tools

2.4.1. Socio-Economic Characteristics and Subjective Well-Being of the Elderly

Descriptive statistical analysis and frequency tables were used to present older people’s socio-economic characteristics and well-being levels. This study used subjective well-being (SWB) as the primary measure of elderly well-being. SWB is a key indicator of quality of life, reflecting how individuals evaluate their lives emotionally and cognitively [31,32,33,34]. This concept encompasses overall life satisfaction and emotional well-being, including the experience of positive and negative emotions in daily life.

In this study, SWB was measured using 19 indicators grouped into three main dimensions:

• Life Satisfaction Dimension (Personal and Social Life Satisfaction)
• Emotional Dimension
• Life Meaning Dimension

Respondents rated each indicator on a scale from 1 to 10, where 1 represents the lowest level of well-being, and 10 represents the highest.

The indicators used in this study were adapted from the Indonesia Happiness Index [35] and aligned with international frameworks, such as Diener’s Satisfaction with Life Scale (SWLS) and OECD well-being indicators [36,37]

Table 2. Subjective well-being indicators and measurement scale.

Dimension/Subdimension/Indicator	Measurements
	Lowest Score (1)	Highest Score (10)
Life Satisfaction Dimension
Personal Life Satisfaction Subdimension
Education and Skills	Very dissatisfied	Very satisfied
Employment/Business/Main Activities	Very dissatisfied	Very satisfied
Household Income	Very dissatisfied	Very satisfied
Health	Very dissatisfied	Very satisfied
Housing and Home Facilities	Very dissatisfied	Very satisfied
Social Life Satisfaction Subdimension
Family Harmony	Very dissatisfied	Very satisfied
Availability of Leisure Time	Very dissatisfied	Very satisfied
Social Relationships in the Community	Very dissatisfied	Very satisfied
Environmental Conditions	Very dissatisfied	Very satisfied
Security Conditions	Very dissatisfied	Very satisfied
Emotion Dimension
Feelings of Joy/Happiness	Very unhappy	Very happy
Absence of Worry/Anxiety	Very worried	Not worried
Absence of Distress	Very distressed	Not distressed
Life Meaning Dimension
Autonomy	Very incapable	Very capable
Environmental Mastery	Very incapable	Very capable
Self-Development	Very inconsistent	Very consistent
Positive Relationships with Others	Very unbeneficial	Very beneficial
Life Purpose	Very pessimistic	Very optimistic
Self-Acceptance	Very incapable	Very capable

Table 2. Subjective well-being indicators and measurement scale.

Dimension/Subdimension/Indicator	Measurements
	Lowest Score (1)	Highest Score (10)
Life Satisfaction Dimension
Personal Life Satisfaction Subdimension
Education and Skills	Very dissatisfied	Very satisfied
Employment/Business/Main Activities	Very dissatisfied	Very satisfied
Household Income	Very dissatisfied	Very satisfied
Health	Very dissatisfied	Very satisfied
Housing and Home Facilities	Very dissatisfied	Very satisfied
Social Life Satisfaction Subdimension
Family Harmony	Very dissatisfied	Very satisfied
Availability of Leisure Time	Very dissatisfied	Very satisfied
Social Relationships in the Community	Very dissatisfied	Very satisfied
Environmental Conditions	Very dissatisfied	Very satisfied
Security Conditions	Very dissatisfied	Very satisfied
Emotion Dimension
Feelings of Joy/Happiness	Very unhappy	Very happy
Absence of Worry/Anxiety	Very worried	Not worried
Absence of Distress	Very distressed	Not distressed
Life Meaning Dimension
Autonomy	Very incapable	Very capable
Environmental Mastery	Very incapable	Very capable
Self-Development	Very inconsistent	Very consistent
Positive Relationships with Others	Very unbeneficial	Very beneficial
Life Purpose	Very pessimistic	Very optimistic
Self-Acceptance	Very incapable	Very capable

2.4.2. Socio-Economic Determinants of Elderly Subjective Well-being

The socio-economic factors influencing the subjective well-being of older people are analyzed using a multiple regression model, represented by the following equation:

$$\begin{array}{l}Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_{3.D1}{X}_{3.D1}+{\beta }_{3.D2}{X}_{3.D2}+{\beta }_{3.D3}{X}_{3.D3}+{\beta }_{.4}{X}_4+{\beta }_{.5}{X}_5+\\ {\beta }_{.6}{X}_6+{\beta }_{7.D1}{X}_{7.D1}+{\beta }_{7.D2}{X}_{7.D2}+{\beta }_8{X}_8+{\beta }_{9.D1}{X}_{9.D1}+{\beta }_{9.D2}{X}_{9.D2}+{\beta }_{9.D3}{X}_{9.D3}\\ +{\beta }_{9.D4}{X}_{9.D4}+{\beta }_{9.D5}{X}_{9.D5}+{\beta }_{10}{X}_{10}+e\end{array}$$

where:

Y = total subjective well-being score

X₁ = Age (years)

X₂ = Gender (1 = male, 0 = female)

X₃ = Level of formal education (base category: no schooling/less than elementary school), where:

X_3.D1 1 = for elementary school; 0 for others: X_3.D2 1 for junior high school; 0 for others: X_3.D3 1 for senior high school and tertiary education; 0 for others

X₄ =Marital status (1 = married; 0 = others)

X₅ =Household role (1 = head of household; 0 = others)

X₆ = Number of household members

X₇ = Employment status (1 = working; 0 = others), with the base category being unemployed, where:

X_7.D1 = 1 for working; 0 for others: X_7.D2 = 1 for income earner; 0 for others

X₈ = Per capita household income (Rp per month)

X₉ = Ethnicity (base category: Malay), where:

X_9.D1 = 1 for Javanese/Sundanese; 0 for others: X_9.D2 = 1 for Minangkabau; 0 for others: X_9.D3 = 1 for Bugis/Banjar; 0 for others

X₁₀ = Rural/urban area (1 = rural; 0 = urban)

3. Results

3.1. Socio-Economic Characteristics of Older People in Jambi Province

Based on the age distribution presented in Table 3, most elderly individuals in Jambi Province fall within the 60–64 age group (41.5%), followed by those aged 65–69 (27.1%). Only 16.4% of the elderly population is 75 years or older. The average age of the respondents is 67.68 years, indicating that most elderly individuals are still in the early stages of old age. As age increases, the number of elderly individuals declines, which may suggest higher mortality rates among older age groups or reduced mobility due to physical and health conditions.

Moreover, the gender distribution in Table 4 shows that the proportion of older women (51.2%) is greater than that of older men (48.8%). This difference can impact various components of well-being like social support and finances since older women live longer but are also more likely to be financially insecure once their partner dies.

Educational attainment is also one factor that indicates older people’s well-being. As shown in Table 5, most older people within the Province of Jambi have low educational attainment. 28.0% did not complete an elementary school degree, while 27.5% only finished an elementary school degree. Meanwhile, 12.6% achieved higher education.

The poor schooling of older adults can potentially limit their economic choices during the best years of life, thus affecting the availability of greater social security benefits during old age. Lower-educated older persons are likely to be restricted from accessing healthcare and social services information, which further affects them.

Beyond education, the social conditions of older people can also be analyzed through their family status. Table 6 shows that 72.5% of elderly individuals still serve as heads of household, indicating that they play a central role in decision-making and household management. However, this role does not necessarily imply financial independence. Some elderly individuals must continue working to support their family’s economy, while others rely on pensions or financial support from family members.

Meanwhile, 27.5% of elderly individuals who are not heads of household may be more financially dependent on family members and in family decision-making.

As for the employment status, Table 7 reflects that 31.4% are still employed, while 34.8% are not working but are gaining income from other sources, such as pension or old-age allowance. 33.8% have income without working, indicating that some support systems give income to some older people who are no longer working.

Many older individuals are employed due to the necessity to earn a living or to remain part of society. Alternatively, other individuals will be retired because their physical ability has declined or because they opted to withdraw from the labor force.

However, not every senior receives a pension or a guaranteed source of income. Table 8 indicates that 72.0% of older people do not receive pensions or old-age benefits, whereas only 28.0% receive such benefits.

The high proportion of elderly individuals without pensions is largely due to the dominance of the informal sector in the labor market, where workers do not receive pension benefits or formal social security. Elderly individuals without pensions often face economic uncertainty, particularly in meeting basic needs such as food, housing, and healthcare services.

Without the guarantee of income during retirement, many elderly individuals are compelled to be financially reliant upon their children or other family members and sometimes endure economic constraints. This can create an extra financial burden on the family and negatively impact the mental health of older people.

On the other hand, pension recipients are likely to be more financially independent, making it easier to meet their necessities, which means greater well-being and life satisfaction.

3.2. Subjective Well-Being of Older People in Jambi Province

The subjective well-being (SWB) of elderly individuals in Jambi Province was measured using 19 indicators, categorized into three main dimensions: life satisfaction, emotional well-being, and life meaning. Table 9 presents the study area’s subjective well-being assessment findings.

The life satisfaction dimension recorded an average score of 7.00, reflecting a relatively high level of satisfaction among elderly individuals in Jambi Province. More specifically, personal life satisfaction had an average score of 6.78, with satisfaction with housing and facilities receiving the highest score (7.07). This indicates that most elderly individuals feel comfortable with their living environment. Conversely, satisfaction with education and skills had the lowest score (6.64), likely due to the low levels of formal education attained by the current elderly generation.

In the social life sub-dimension, elderly individuals reported higher satisfaction levels than in personal life aspects, with an average score of 7.21. Family harmony (7.39) and social relationships with neighbors (7.34) were rated particularly high, highlighting the importance of social support and interpersonal relationships in enhancing elderly well-being. However, satisfaction with leisure time was slightly lower (7.20), suggesting limited access to recreational or entertainment activities.

The emotional dimension had an average score of 6.13, lower than the other two. Although elderly individuals reported high levels of enjoyment in daily life (7.23), they also experienced considerable worry (5.69) and stress (5.47) in dealing with life’s challenges. The lower emotional well-being score suggests that despite their ability to enjoy life, many elderly individuals face psychological challenges related to economic uncertainty, health issues, or physical limitations.

The sense of meaning in life among elderly individuals scored an average of 7.04, reflecting a strong sense of purpose and control over their lives. The highest-rated aspect was the feeling of “being useful to others” (7.25), highlighting that many elderly individuals continue to see themselves as valuable members of their families and communities. Additionally, optimism about the future and the ability to accept one’s circumstances scored 7.09, suggesting that despite various challenges, many elderly individuals maintain a positive outlook on life.

Overall, the total happiness score for elderly individuals in Jambi Province reached 7.25, indicating a relatively high level of well-being. While economic and health-related difficulties persist, these findings suggest that strong social connections and active participation in family and community life play a crucial role in sustaining well-being among older people. This underscores the idea that social and psychological aspects are equally vital in shaping their overall happiness and life satisfaction beyond economic factors.

3.3. The Impact of Socio-Economic Factors on the Subjective Well-being of Older People in Jambi Province

Table 10 presents the model fit statistics and ANOVA test results for the regression model analyzing the socio-economic determinants of subjective well-being among older people. The Adjusted R² value of 0.562 indicates that the model explains approximately 56.2% of the variation in elderly subjective well-being. In comparison, the remaining 43.8% is attributed to other factors not included in the model.

The ANOVA test results also show that the regression model is statistically significant, with an F-value of 18.595 and a significance level of p < 0.001. This confirms that the model validates the relationship between socio-economic factors and subjective well-being among older people in Jambi Province.

Moreover, Table 11 shows the estimated coefficients from the regression model. From the findings, it’s clear that age (X1) has a negative effect on elderly subjective well-being with a value of -0.208 and a p-value of 0.058. This means that subjective well-being among older adults declines with age, although it’s just marginally significant.

Additionally, the gender variable (X2) shows a significant relationship, indicating that men tend to have lower subjective well-being levels than women (the reference category). This is reflected in the coefficient of -9.324, with a high level of statistical significance (p<0.001).

Beyond age and gender, education has also been found to impact the subjective well-being of older people significantly. Elderly individuals with secondary education (X3D2 ) and higher education (X3D3 ) report higher subjective well-being compared to those with no schooling or incomplete primary education (the reference category). The positive coefficients for X3D2 (9.161, p<0.001p) and X3D3 (10.228, p<0.001) suggest that education plays a crucial role in enhancing the subjective well-being of older individuals.

Marital status (X4) significantly affects subjective well-being, as indicated by a coefficient of 9.035 with p<0.001. This suggests that married elderly individuals have higher well-being levels than their unmarried counterparts (the reference category).

Similarly, elderly individuals who serve as household heads tend to have higher well-being than those who do not, as shown by a strong positive effect (X5) with a coefficient of 10.480 (p<0.001). This may be because holding a leadership role in the household provides a greater sense of responsibility, control, and authority, which can contribute to well-being.

In contrast, household size (X6) has a notable negative impact on subjective well-being, with a coefficient of -1.249 (p=0.00). This suggests that older adults in larger households may experience lower well-being due to the added financial and social responsibilities of supporting extended family members.

The regression results also reveal differences in the impact of employment status on subjective well-being. Elderly individuals who receive income without working (X7D2 ), such as pensioners or those receiving financial support from family, report higher well-being than those who are unemployed, as reflected by a positive coefficient of 6.076 (p<0.001).

However, elderly individuals still working (X7D1 ) do not exhibit a significant difference in well-being compared to those unemployed (p=0.843). This suggests that working in old age does not necessarily improve well-being, possibly because employment at an advanced age is often driven by financial necessity rather than personal fulfillment.

Interestingly, per capita household income (X8) negatively correlates with subjective well-being, with a coefficient of -3.135E-6 (p=0.039). This finding suggests that elderly individuals financially dependent on their families may experience lower well-being, possibly due to a perceived loss of financial autonomy and independence.

The regression results also indicate significant differences in well-being across ethnic groups. Elderly individuals from the Javanese/Sundanese group (X9D1 ) report lower well-being than the Malay reference group (p=0.032). In contrast, elderly individuals from the Bugis/Banjar group (X9D3 ) report significantly higher well-being (p<0.001p). These findings suggest that cultural and social differences among ethnic groups may influence perceptions of well-being, social support structures, and financial security.

Lastly, location (X10), which differentiates between urban and rural areas, does not significantly affect subjective well-being (p=0.193). This suggests that socio-economic factors such as education, marital status, and household role-play a more crucial role than geographical differences in determining elderly well-being.

4. Discussion

The research findings indicate that various socio-economic determinants influence the subjective well-being of elderly individuals in Jambi Province. As people age, their subjective well-being tends to decline, aligning with previous studies that show older individuals are more vulnerable to physical, mental, and social deterioration [38,39]. However, this negative effect can be alleviated when elderly individuals have access to proper healthcare services and strong social support from their families and communities.

Gender also plays a crucial role in elderly well-being, with older women reporting higher well-being levels than older men. This supports findings that women tend to be more socially engaged and have stronger support networks [37,40]. However, these differences are more pronounced in emotional and social well-being, whereas older women often face greater disadvantages in economic terms. Studies indicate that widowed older women are more financially insecure due to lower pension savings and limited access to social benefits [41,42]. Additionally, women are more likely to take on caregiving roles within the family, which, while providing a sense of fulfillment, can become burdensome without adequate social support. Conversely, men often struggle more with the transition into retirement, as they lose their primary identity as breadwinners [43].

Education has been proven to be a key factor that positively contributes to subjective well-being. Elderly individuals with higher levels of education tend to experience greater well-being, consistent with previous findings that education enhances financial stability, access to information, and engagement in broader social networks [44]. Higher-educated elderly individuals are also more likely to access better healthcare services and better understand and manage their health conditions, contributing to long-term well-being [45].

The capability approach concept, as measured by the Investigating Choice Experiments for the Preferences of Older People—CAPability index (ICECAP-O), emphasizes that individual well-being is determined by the opportunity to “be” and “do” the things that are considered important in life. Elderly individuals with higher education levels have greater opportunities to make life choices, both socially and economically, compared to those with lower levels of education [46].

Marital status also has a strong association with subjective well-being. Married elderly individuals tend to have higher levels of well-being than their unmarried counterparts, likely due to their spouses’ social and emotional support [39,43,47,48]. This support benefits psychological well-being and economic security, as spouses can assist each other financially and provide mutual care.

In the context of social integration, this study found that elderly individuals who play an active role in the household—such as by serving as the head of the household—have higher subjective well-being than those more dependent on other family members. Elderly individuals who remain involved in household decision-making will likely feel more valued and in control of their lives, contributing to their psychological well-being [49]. Conversely, elderly individuals living alone or entirely dependent on their families may face limitations in social interactions and be more vulnerable to discrimination and social exclusion [50].

Previous studies have shown that in some developing countries, elderly individuals are often represented in policies as a vulnerable, passive, and dependent group, which reduces their opportunities to remain active in society and contribute productively [51,52,53]. This can further deteriorate their subjective well-being, as they face economic challenges and a lack of recognition as individuals with the capacity to participate in social and economic life.

However, in some cases, elderly individuals who still serve as the head of a large household may experience economic pressure due to the many family members who depend on them. This finding aligns with research indicating that a larger household size can increase economic strain, which negatively impacts subjective well-being [54].

Regarding employment, the findings indicate that employment status itself does not significantly impact well-being. Instead, income receipt is more crucial in improving well-being. Many elderly individuals in Jambi continue working in the informal sector, such as agriculture and small trade, which does not always provide social security or financial stability [55]. As a result, receiving income from other sources, such as pensions, family support, or social assistance, positively impacts their well-being. Elderly individuals who receive income without having to work have more time for social and recreational activities, which enhances their emotional and social well-being.

Studies suggest that participation in economic activities can positively impact life satisfaction, but only if the work provides adequate financial stability and does not impose excessive physical strain [55]. Access to sustainable sources of income through labor, pension, or family support is thus a crucial factor that improves the well-being of older people.

On a larger scale, household circumstances and coping strategies within the household are determinants of the well-being of household members within poor household settings [56,57]. The household characteristics, including the age of the head of the household, the household size, and the primary activities of the family members, are crucial to well-being. In addition to this, coping strategies used by poor household heads are typically counterproductive, and the measures used end up depleting finances further in the future.

Research has shown that participation in economic life has the potential to promote life satisfaction, but only if the labor provides enough financial security. It does not take an excessive physical toll (Chia & Hartanto, 2021). Access to sustainable sources of income through labor, pension, or family support is thus a crucial factor that improves the well-being of older people.

On a larger scale, household circumstances and coping strategies within the household are determinants of the well-being of household members within poor household settings (Junaidi et al., 2020, 2022). The household characteristics, including the age of the head of the household, the household size, and the primary activities of the family members, are crucial to well-being. In addition to this, coping strategies used by poor household heads are typically counterproductive, and the measures used end up depleting finances further in the future.

Per capita household income, however, shows a negative relationship with subjective well-being, contradicting previous research that found a positive correlation between income and well-being [58,59]. One possible explanation is that in Jambi, social support and family relationships are more dominant than economic factors. Elderly individuals who depend on financial support from their families may experience a loss of independence, negatively affecting their well-being. Similarly, Zapata-Lamana et al. [60] found that income does not directly predict life satisfaction but instead influences factors that support quality of life, such as independence.

Consistent with the findings of Ranabhat [61], the regression results also indicate that ethnicity significantly influences subjective well-being. Elderly individuals from Javanese and Sundanese backgrounds report lower well-being than the Malay reference group, while those from Bugis and Banjar backgrounds report higher well-being. These differences may be explained by socio-cultural factors, such as family values and community support, which shape perceptions of well-being [62].

Residential location, whether urban or rural, does not significantly affect subjective well-being. This finding is supported by Domínguez-Párraga research [63], which highlighted that beyond geographical location, social factors within the environment—such as quality social relationships and a sense of belonging in the community—play a crucial role in elderly well-being and successful aging. Therefore, policy efforts to improve elderly well-being should prioritize socio-economic factors rather than merely distinguishing between urban and rural areas.

5. Conclusions

This study examined the socio-economic determinants of subjective well-being (SWB) among older adults in Jambi Province, Indonesia. The findings indicate that education level, household role, marital status, and income stability are the most significant factors influencing elderly well-being. Increased higher education has a positive relationship with higher well-being through greater availability of resources and social support. Married individuals and household heads indicate improved social support and resource availability, revealing the role played by household structure. Financial stability through pension payments or other constant income sources contributes more to well-being than continued labor force participation, highlighting the role played by income stability instead of labor force participation in old age.

On the other hand, older age and larger family sizes affect SWB negatively through lower physical fitness, lower mobility, and greater financial strains. Differences also exist along gender lines where older women are greater than men in SWB, perhaps due to stronger social networks and family support.

Such evidence calls for diverse policy interventions to ensure the well-being of older people, particularly in rural and semi-rural areas. Increasing lifelong learning programs will help older people remain engaged and financially empowered. More pension programs and micro-pension savings to informal sector participants will ensure enhanced economic protection. Community social support networks and elderly-accessible facilities will further address social isolation and ensure well-being.

Future research should explore the long-term impact of social policies on elderly well-being and examine regional differences across Indonesia to develop more targeted interventions.