Comparison of Physical and Mental Health in Pre-retirement Workers in Urban and Rural Areas Using the Indonesian Health Survey 2023

Introduction

Indonesia is facing population ageing as its life expectancy increases. According to Statistics Indonesia (Badan Pusat Statistik/BPS) data for 2023, the proportion of older adults has reached 11.75%¹ It is estimated that Indonesia's elderly population will reach 20% by 2045. Therefore, it is important to pay more attention to the elderly population so that they remain healthy and productive.

Currently, the average retirement age in Indonesia is 56–58 years. When compared with other Association of Southeast Asian Nations (ASEAN) countries, such as Singapore (65) and the Philippines (60), the retirement age in Indonesia is still lower² However, based on future population projections, a large elderly population could potentially increase productivity. The Indonesian government has planned to raise the country's retirement age from 58 to 60 years. The extension of the retirement age is a complex and multi-dimensional topic, with diverse arguments from economic, social, and individual perspectives.

One of the primary arguments for extending the retirement age is the need to address the financial challenges that older workers face. With increasing life expectancy, retirees are likely to live longer post-retirement, which burdens individuals financially. Under this condition, approximately 90% of workers are likely unable to maintain their living standards upon retirement age. By extending the retirement age, the government can reduce long-term financial burdens by increasing the period of workers' contributions³

Kotun et al. (2016) found a significant correlation between adequate retirement packages and employee productivity, demonstrating that such benefits positively impact organisational efficiency. Additionally, extending the retirement age may offer individual benefits. Many people find purpose and satisfaction through their work, and a longer career can allow them to continue contributing to society while supporting their physical, mental and social well-being by staying active⁴

Raising the retirement age has a positive impact on health-supporting behaviours, physical health and health satisfaction in Italy before workers retire. For example, extending participation in the workforce by one year increases the likelihood of engaging in regular exercise by 3.2%. Furthermore, the likelihood of reducing body mass index (BMI) to below the obesity level and improving self-rated health satisfaction increases by 1.6% and 2.7%, respectively. This indicates that workers can prepare for longer working years by adopting health-supporting behaviours to help them remain active in the workforce into older age⁵

Other research related to the relationship between continuing work after retirement and the occurrence of physical frailty in the retired adult population of China has identified a significant link between continuing work after retirement and a reduced risk of physical frailty. These findings suggest the potential benefits of policies promoting social engagement and extending employment to improve the quality of life for the elderly population⁶

However, arguments also suggest that extending the retirement age could have negative social consequences. Some studies indicate that delaying retirement may impede job mobility for younger generations, as senior employees staying in the workforce longer can limit career opportunities for younger individuals⁷ The trend of intergenerational inequality is growing stronger, indicating that income mobility from parents to younger generations in Japan is relatively low⁸

Other studies have revealed that, in general, extending the working years does not significantly impact mortality rates or physical health in old age. Analyses of outcome variations based on the social class of employment or the tendency to extend working years do not provide definitive results. However, some research shows that prolonging working years can positively affect more advantaged groups in society. Conversely, disadvantaged groups or those in lower economic and social classes may experience negative effects from early retirement⁹

Additionally, extending the retirement age may worsen issues of inequality. Workers with access to flexible or independent jobs will likely continue working after retirement. At the same time, those in physically demanding roles or requiring optimal health may struggle to remain employed and risk social isolation¹⁰ This phenomenon occurs because exposure to heavy working conditions is more common among lower socioeconomic groups, contributing to a decline in health. People in lower socioeconomic positions may not be able to extend their working years at the same rate as their more advantaged counterparts due to the physical demands of their jobs or poor health; they may hope to benefit from early retirement¹¹

Thus, policies extending the retirement age should consider the health conditions of pre-retirement workers. This study aims to examine and compare the physical and mental health of pre-retirement workers, particularly those aged 50 and above, in urban and rural areas, using data from the Indonesia Health Survey 2023 (SKI).

Methods

The 2023 Indonesian Health Survey (Survei Kesehatan Indonesia/SKI) combines the Basic Health Research Survey (Riset Kesehatan Dasar/Riskesdas) and the Indonesian Toddler Nutrition Status Survey (Survei Status Gizi Indonesia/SSGI). SKI 2023 was conducted to assess the outcomes of health development efforts in Indonesia over the past five years (2019-2024). The data collected provide a health status representation from the national level to individual regencies and municipalities.

The availability of data and information on health development achievements is crucial for the Ministry of Health and provincial and local governments, serving as an evidence base for creating well-directed, targeted policies, programmes and initiatives. These data also informed the development of the National Medium-Term Health Development Plan (RPJMN 2024-2029) by the Ministry of National Development Planning (PPN)/Bappenas.

In pursuit of valid and accurate data, the Health Development Policy Agency, Ministry of Health Republic of Indonesia collaborated with the Statistics Indonesia on a methodology and sampling framework for SKI 2023. It partnered with various health programmes within the Ministry of Health, the World Health Organisation (WHO) and the World Bank for instrument development, guidelines and survey reporting.

Secondary data from SKI 2023 include responses from 103,730 individuals aged 50–58 still working, with 56,985 residing in urban areas and 46,745 in rural areas. A t-test assessed the differences between any two categories of data, while ANOVA was applied for comparisons across more than two categories.

The SKI 2023 data were collected through face-to-face interviews conducted by trained enumerators. Local enumerators conducted data collection under the technical supervision of the Technical Supervisor (PJT) at the district/city level and administrative oversight by the Operational Supervisor (PJO) at the district/city level. Each enumerator team was responsible for 10–12 census blocks (BS), each containing 10 regular households and an additional seven households with young children. The data collection process began with coordination between the PJT and the PJO at the district/city level to identify sample locations, followed by updating household data before the actual data collection took place¹²

Results

Based on the data in Table 1 above, there are significant differences in several variables. One of the most notable differences is the percentage of males and females in urban and rural areas (p-value 0.0001). In terms of education, urban areas have a higher proportion of respondents with higher education levels, such as high school graduates (34.6%) and college graduates (8.6%), compared to rural areas (18.0% and 2.8%, respectively). Conversely, a larger percentage of rural respondents only completed primary education, such as elementary school (40.6%) and those who did not complete elementary school (11.4%).

Additionally, employment status differs significantly. Urban respondents were more likely to work in formal sectors, such as civil servants, military, police, or state-owned enterprises (9.5%) or in the private sector (8.6%). In contrast, rural respondents were predominantly farmers (47.3%) and fishermen (2.5%), reflecting the influence of geographic conditions on occupational trends.

Table 1 also highlights the differences in healthcare access. Urban respondents more frequently accessed healthcare services in hospitals (4.7%) compared to rural respondents (0.8%). On the other hand, rural respondents were more likely to use community-based health centres (UKBM) (3.9%) or general service facilities (38.2%). Inpatient care is also higher in urban areas (2.9%) compared to rural areas (1.3%); hospitals are the most frequently accessed facilities in urban settings.

Another noteworthy finding is the use of healthcare services abroad. A small proportion of urban respondents utilised overseas healthcare services (0.2%) compared to rural respondents (0.1%), indicating differences in access to and preferences for more comprehensive or specialised healthcare. These significant differences underscore the varying characteristics of respondents in urban and rural areas, particularly regarding education, employment status, healthcare access and preferences for healthcare facilities.

Based on the data in Table 2, the physical health status shows that the percentage of respondents diagnosed with asthma is almost the same in urban (1.9%) and rural (1.8%) areas; this difference is not statistically significant (p = 0.089). However, for asthma, which has increased in the past 12 months, there is a significant difference between urban (1.2%) and rural (0.6%) areas, with a p-value of 0.000. This indicates that the likelihood of an asthma flare-up in the past year has been higher in urban areas.

For respondents diagnosed with cancer, the percentage was higher in urban areas (0.3%) than in rural areas (0.2%), with a p-value of 0.0001, a significant difference. Additionally, for cancer chemotherapy, the difference between urban (0.2%) and rural (0.1%) is also significant (p = 0.000), where people in urban areas are more likely to undergo chemotherapy. Furthermore, the diagnosis of diabetes was higher in urban (5.8%) than rural (3.4%) areas, with a significant difference (p = 0.0001). This shows that pre-retirement workers in urban areas are at a higher risk of diabetes. Type 2 diabetes is also more commonly diagnosed in urban areas (3.0%) than in rural areas (1.6%), a significant difference.

The data also reflect the status of mental health in the population, categorised into three main groups: a) those who have ever suffered from mental disorders, b) those showing symptoms of schizophrenia or psychosis and c) those diagnosed with mental disorders by a doctor. In the category of ever having had a mental disorder, 0.6% of the population had experienced one, while 99.4% had not. The odds ratio (OR) of 1.018 indicates no statistically significant difference between the groups who have and have not experienced mental disorders, suggesting that having experienced a mental disorder does not significantly increase the risk in this group.

In the category of schizophrenia/psychosis, 0.5% of the population reported symptoms, while 99.4% did not—a statistically significant difference. Thus, the presence of schizophrenia or psychosis symptoms was not significantly associated with the observed group. However, about 0.4% of the population has been diagnosed by a doctor with a mental disorder, with 99.5% not receiving such a diagnosis. In this category, an OR of 1.646 (95% CI: 1.09–2.46) indicated a statistically significant difference between the diagnosed and non-diagnosed groups. This suggests that a formal diagnosis by a doctor may correlate with a higher prevalence of mental disorders in the population. It also showed a significant difference between urban (0.4%) and rural (0.4%) areas, with a p-value of 0.016.

Overall, the study findings above show that the proportion of mental disorders in the population is relatively low, with only a small fraction experiencing symptoms or receiving a diagnosis. However, mental disorder diagnoses are more significant compared to other categories. These findings emphasise the importance of professional diagnosis in assessing mental health conditions and highlight the need for more proactive prevention and intervention efforts at the community level.

The figure 1 cancer treatments compare the types of cancer treatments accessed by urban and rural residents. The data reveal that surgery is the most common treatment, with a higher percentage of urban respondents (72.3%) opting for surgery than rural respondents (64.6%). Chemotherapy follows, with more significant use in urban areas (52.8%) than in rural areas (26.8%). Radiation therapy is slightly more common among urban residents (23%) than among rural residents (20.7%). Traditional/herbal treatments are more prevalent in rural areas (8.5%) than in urban areas (5.6%), possibly indicating a preference for or greater access to alternative therapies in rural settings. Other treatments were chosen by 9.1% of urban residents but only 2.4% of rural residents.

Figure 1. Cancer Treatments.

The figure 2 DM treatments shows the types of DM treatments accessed by urban and rural residents, highlighting that medication is the primary form of treatment, with similar usage in both urban (81.4%) and rural areas (80.8%). Urban residents used insulin injections more commonly (17.1%) than rural residents (13.1%). Treatment by doctors was slightly higher among urban residents (87.3%) than among rural residents (86.4%). Herbal alternatives are similarly popular in urban (34.3%) and rural (38.4%) areas. “No need for medication” was the least common response, with slightly more rural residents (4.4%) reporting no need for medication than urban residents (3.5%).

Figure 2. DM Treatments.

Figure 3 compares the utilisation of different settings for mental health care in urban and rural areas. The categories shown are mental hospitals, general hospitals, primary healthcare, clinics, and non-health facilities. Mental hospitals were used by 46.3% of the urban respondents and 47.3% of the rural respondents. General hospitals were used by 37.5% of urban and 34.5% of rural respondents. Primary healthcare was selected by 30.6% of urban residents and 54.7% of rural residents, indicating higher utilisation in rural areas. Clinics were used by 11.1% of urban residents and 8.8% of rural residents. Non-health facilities were used by 32.8% of urban respondents and 35.8% of rural respondents.

Figure 3. The Places of Mental Health Treatment.

The figure shows that rural respondents rely more on primary healthcare facilities for mental health care. In contrast, urban residents use more options, including clinics and public hospitals, suggesting possible differences in accessibility or preference for mental health services between urban and rural areas.

Discussion

The SKI 2023 data showed a higher number of female workers than male workers in urban and rural areas, with a statistically significant difference in their numbers. This increase in female workers also supports Sustainable Development Goals (SDG) No. 5, which promotes gender equality in the workplace. According to Beloskar et al. (2024), companies in the USA, the UK and Australia, consistent with SDG No. 5, are fostering demographic diversity by including women on boards and directing Corporate Social Responsibility (CSR) programmes towards women¹³ Eden and Wagstaff (2021) also proved that workplace gender inequality remains prevalent due to various complex social issues and a lack of dominant solutions¹⁴

The survey found that the most common occupation in urban areas is self-employment, while farming is more prevalent in rural areas. This finding reflects urban job opportunities that trend towards trade or entrepreneurship, whereas, in rural areas, the abundance of farmland supports more agricultural employment. This is consistent with the concept of social capital, in which non-farmers in rural areas often support or tolerate agricultural practices¹⁵

A significant difference was found between workers who sought medical treatment abroad and those who did not. Most workers, both urban and rural, had not received treatment abroad. Only 0.2% of urban and 0.1% of rural workers sought international medical care, primarily for advanced health services and plastic surgery. Those who sought treatment abroad cited more comprehensive facilities (98%), the quality of medical professionals (97%) and the quality of medical services (94.1%) as key reasons, similar to the findings of surveys of families seeking treatment in Singapore and Malaysia^16,17

The data also reveal significant differences in physical health between urban and rural workers, particularly with cancer and type 2 diabetes, which are more prevalent in urban areas. Pre-retirement workers with cancer in both urban and rural areas tend to seek treatment options, such as surgery, radiation, chemotherapy, traditional medicine, or herbal remedies, consistent with other research^18,19

Certain cancer cases among workers require particular attention due to the lingering effects, which can last longer than six months and extend up to 18 months. This presents challenges for companies, as it may lengthen the period employees rely on government-supported sick pay and increase expected work absences due to illness.²⁰

Additionally, pre-retirement workers with diabetes, whether in urban or rural areas, often follow various treatments, including medication, insulin injections, and herbal supplements. A few respondents reported not seeking medical treatment for diabetes and feeling that their condition had improved. Other studies indicate that decisions about diabetes treatment for type 2 patients are heavily influenced by personal knowledge and past experiences, while family and friend support play a lesser role²¹ McSharry et al. (2016) found that type 2 diabetes medication adherence is uniquely complex, with patients understanding the need for medication but often adjusting doses and timing in their daily routines. This highlights the need for improved management strategies to enhance opportunities and motivation for type 2 diabetes treatment adherence²²

Furthermore, a significant difference was found in mental health among workers in urban and rural areas, with more workers in urban areas diagnosed with mental disorders. Almost all workers with mental disorders receive treatment at psychiatric hospitals, general hospitals, community health centres or clinics. In addition to healthcare facilities, respondents also visit non-healthcare facilities, such as pesantren (Islamic boarding schools), rehabilitation centres, religious leaders and social welfare centres. However, a study by Yuan et al. (2022) found that working at an older age can reduce depression, especially for workers with health insurance benefits²³ A study by Oksanen et al. (2011) on Finnish public sector employees found that the use of antidepressant medication one year after retirement decreased by 0.77% compared to one year before retirement. They also found that the primary reasons for disability pensions were mental or physical health issues²⁴

Conclusions

SKI 2023 highlights significant differences in demographics, socioeconomic conditions, and physical and mental health between pre-retirement workers aged 50–58 in urban and rural areas. With Indonesia's elderly population projected to reach 20% by 2045, there is an urgent need to address these disparities to ensure that the elderly population remains healthy and productive. Overall, the significant differences between respondents in urban and rural areas reflect inequalities in access to education, employment and healthcare services.

Urban respondents tended to have higher education levels, more stable formal employment, and better access to healthcare facilities. On the other hand, rural respondents are more vulnerable to limited access to education and healthcare, with a higher proportion working in the informal sector. However, the survey on physical health status indicates that conditions such as cancer, diabetes and mental disorders are found among pre-retirement workers more frequently in urban areas than in rural areas.

Contributorship

All authors have participated in (a) the conception and design or the analysis and interpretation of the data, (b) drafting the article or revising it critically for important intellectual content, and (c) approval of the final version.

Ethics approval and consent

Not Applicable. The Indonesia Health Survey 2023 report has been published on the website and is publicly accessible. We asked for the anonymized raw data from the Health Development Policy Agency, Ministry of Health, Republic of Indonesia. The request for data was approved by making a written agreement in Bahasa Indonesia if the data was only used for this study and kept confidential.