With the advancement in medical technology and the consequent extension of life expectancy, aging has become one of the major public health challenges worldwide (1, 2). South Korea has the fastest-aging population globally (3). In 2017, more than 14% of the Korean population was in the ≥65 year-age group, and this proportion increased to 16.6% in 2022 (4). Depression among older adults is an important risk factor for suicide in many countries (5) and diminishes the quality of life (6). The suicide rate in Korea has remained the highest among the Organization for Economic Co-operation and Development (OECD) countries since 2013 (7). Notably, the suicide rate of the older adult population is approximately 2.26 times that of Korea’s other age groups. The middle-aged group (40–64 years) has the second highest suicide rate (8), underscoring the mental health needs of both the middle-aged and older adults.

Approximately 280 million people worldwide have depression (9), and 20–35% of older adults in Korea have experienced depression (10), with 27.8% of the total population with depression in Korea being in their 40s or 50s (11). Depression is a highly recurrent health problem, with 60% of those who recover from the first episode being at risk of additional episodes and approximately 70% of those with a history of two episodes having another recurrence (12). However, most previous studies investigating the prevalence of depressive symptoms and associated factors have used cross-sectional designs (13–15). Consequently, the studies are inherently limited to establish a causal relationship or demonstrate consistent associations with depressive symptoms.

The World Health Organization (WHO) posited the concept of healthy aging, defined as “the process of developing and maintaining the functional ability that enables wellbeing in older age.” Health aging is not a new concept, but rather, an inclusive concept related to successful, active, and optimized aging (16). Healthy aging decreases the risks of requiring long-term care (17) and all-cause mortality (18). Due to the large proportion of older adults in Korea, healthy aging has increasingly garnered focus, and previous reports on the relationship between healthy aging and depression indicate that unhealthy aging is a predictor of a higher risk of depression (19, 20). In particular, most studies using the Korean Longitudinal Study on Aging (KLoSA) – a nationally representative sample of Koreans older adults – explored the factors that influence depression (21, 22). Individual factors, including women, having a lower income, living alone, consuming alcohol, and being visually impaired, are known risk factors for increased depressive symptoms (10, 13, 14, 23). Recent studies have reported differences in the neighborhood effect on depression (24, 25). These neighborhood-level factors include infrastructural, interactive social, and demographic characteristics of residents, as well as political and environmental characteristics (26). Residential areas (urban/rural) affect inhabitants in various contexts, especially older adults versus young adults (27). Hwang and Kim (24) reported that urban residents have lower depressive symptoms in Korea in association with spatial distribution patterns, as urban areas have various facilities, such as healthcare services, employment opportunities, transportation, and social capital. However, the opposite results have been reported previously (28). Studies and resources on the relationship between depressive symptoms and neighborhood-level variables in Korea are scarce, and the existing studies are small-sized convenience samples (14) or cross-sectional studies (29, 30) that do not reflect changes in the differences over time. To generate robust results by recognizing that depressive symptoms do not end as a single event and recur subsequently, we applied a new statistical model – the Anderson–Gill model (31) – which is effective wherein the event of interest occurs more than once in a participant, for example, the incidence of depression after injury or readmission outcome analysis (32, 33). In contrast to previous studies that focused on the prevalence of depressive symptoms and the influencing factors, this study is meaningful as it expanded the focus on the incidence of recurrent depressive symptoms using longitudinal data.

This study aimed to (1) compare how depressive symptoms change over time in urban and rural areas in Korea; (2) assess whether regional differences in the effects of healthy aging on depressive symptoms in Korean adults vary over time; and (3) assess whether risk factors for depressive symptoms differ between urban and rural areas over time (Figure 1).

This study conducted an analysis of longitudinal data from 2006 to 2020 to further understand the relationship between health aging and depressive symptoms, focusing specifically on regional differences in Korea. The adjusted analysis showed that the incidence of depressive symptoms was significantly higher in urban areas than in rural areas, and the risk of depressive symptoms was 3.04 times higher in unhealthy adults than in those with healthy aging.

Differences in depressive symptoms among individuals from urban and rural areas have been an interesting research topic. Previous studies investigating the prevalence of depressive symptoms in urban and rural areas have reported inconsistent results (15, 28, 45). China Family Panel Studies examined 8,025, 7,808, and 4,887 older adults aged 60 years and above in 2016,2018, and 2020 and found that rural residents had a higher prevalence of depressive symptoms than urban residents (46). In contrast, a cross-sectional study of a cohort from the Canadian Longitudinal Study on Aging, which analyzed 21,241 adults aged 45–85 years from 2010 to 2014, showed that rural and peri-urban residents had lower scores of depressive symptoms than urban residents (47). Similarly, in a systematic review and meta-analysis that compared residential areas (48), urban residents had a significantly higher prevalence of depressive symptoms than rural residents in developed countries, although this trend was not observed in developing countries. Purtle et al. (48) attributed the regional differences in depressive symptoms to urbanization, wherein urbanization increased the risk of mental health problems. Several studies have reported that urbanization is associated with the prevalence of depressive symptoms (45, 49). Urban residents are more likely to have lower social support (49), and be exposed to stressors related to urban environments, including artificial light at night, neighborhood crime, traffic congestion, and noise (48). In addition to environmental pollution, rapid urbanization has increased other public health issues, such as chronic and mental health diseases and changes in people’s living and working habits, all of which have resulted in adverse health effects (50).

Globally, with increasing urbanization, more than 55% of the world’s population lived in urban areas in 2018, and by 2050, the urbanized population is expected to rise to two-thirds of the overall population (51). Korea is one of the few countries that has rapidly progressed from a low-income to a high-income country and has thereby experienced rapid economic development and urbanization. At the baseline of this study, 78.2% of the cohort lived in urban areas. In 1970, the urbanization rate in Korea was 50.2% (52), rising to 90.7% in 2008 and 91.3% in 2021 (53). Therefore, the sample of this study, KLoSA, is reasonable and not biased. In Korea, many previous studies have compared levels of depressive symptoms between urban and rural areas. Some studies reported that rural populations in Korea are more likely to display higher levels of depressive symptoms than urban populations (14, 44). However, many of the studies are cross-sectional or do not use national-wide samples. Park et al. (54) reported that older adults in urban areas had a mean score of 10.07 for depression, compared to a mean score of 5.82 of their rural peers. Further, in the nationwide Korean Community Health Survey, Jeong et al. (45) reported that the prevalence of depressive symptoms was 3.33% in urban areas and 2.59% in rural areas. Therefore, the findings of this study represent the health disparities between urban and rural areas.

In this study, less frequent contact with neighbors (< 1/week) or children was associated with increased depressive symptoms. We found that urban residents who had less contact with their neighbors had higher depressive symptoms than their rural counterparts. In addition, inactive labor force participation increased depressive symptoms in both urban and rural areas, consistent with previous reports that participation in social activities alleviates depressive symptoms (20, 48). Health behaviors, such as physical activity, alcohol consumption, and regular diet, are known to affect depression regardless residence areas. In the present study, urban residents who lacked regular exercise had higher rates of depressive symptoms than rural residents. Exercise is known to play a critical role in preventing depression and reducing depressive symptoms (54). Physical status may contribute to depressive symptoms (48). According to previous studies, the relationship between depression and BMI is U-shaped (55, 56), indicating that both underweight and overweight individuals had a higher incidence of depression, and we observed a higher incidence of depressive symptoms among underweight adults; however, no participant was classified as overweight (BMI ≥25 kg/m²) in this study. Regarding alcohol consumption, the non-drinking group had a higher incidence of depressive symptoms. Similarly, Jung (57), who analyzed the relationship between depression and drinking using KLoSA, reported that drinking lowered the depressive symptoms of older adults. In this study, we considered the current drinking status and did not investigate the drinking patterns and frequency. Thus, further studies are needed to explore the relationship between depressive symptoms and drinking patterns and frequency.

In 2020, the WHO and United Nations declared a 10-year global action plan – UN Decade of Healthy Aging (2021–2030) (58) – and established healthy aging as a global agenda. However, healthy aging is a multidimensional and highly heterogeneous concept, and there are no reliable tools or survey protocols to measure it. Recently, studies on the development of a healthy aging index have been reported (58). Therefore, we compared the incidence of healthy aging through the research results of successful aging, a similar concept that has been used more frequently (37). In the present study, the prevalence of healthy aging at baseline was 39.4%, which was slightly higher than the 32–35% reported in a previous KLoSA survey among adults over 45 years old (20). Another study comprising 2,157 participants aged 70 years and older from five European countries reported that 41.8% were healthy agers (59). Further, among 2,565 older adults aged 65 years and above in Singapore, 25.4% showed healthy aging (60). In contrast, 3,100 veterans aged over 60 years in the United States reported a self-rated healthy aging of 79% (61). These differences can be explained by the varied definitions of healthy aging and population characteristics among the above-mentioned studies. Therefore, healthy aging should be monitored using standardized healthy aging tools that consider cultural differences in various countries.

Among the five indicators of healthy aging, ADLs (unadjusted HR = 5.05) and IADLs (unadjusted HR = 3.72) demonstrated a higher risk ratio for depressive symptoms than the remaining factors. ADLs and IADLs are crucial for healthy aging because the ability to perform these activities is essential for maintaining independence and autonomy. In previous studies, ADLs and IADLs were strongly associated with depressive symptoms, even after adjusting for demographic and socioeconomic conditions (62, 63). The present study findings support that healthy aging intervention programs should include improvement of physical function as a main component (64–66). Among the indicators of healthy aging, life satisfaction constituted the second highest risk ratio for depressive symptoms (unadjusted HR = 4.27). A systematic review of healthy aging across 13 countries revealed that a positive attitude, such as satisfaction with life, was crucial for healthy aging (67). These factors should be considered in developing healthy aging interventions.

A strength of this study is that it compares the incidence of depressive symptoms over time. To achieve this, we applied the Anderson-Gill model, which considers depressive symptoms as repeated events, and not as censored data, and thereby increased the completeness of the results. Therefore, our findings may lead to a deeper understanding of the characteristics of depressive symptoms that are associated with a high risk of recurrence and suggest possible risk factors. However, although we analyzed longitudinal data, causality in the relationship between healthy aging and depressive symptoms could not be ascertained. Since exploring factors on depression using various study design, many studies have investigated determinants focusing on individual factors, including sex, income, chronic disease, and health behaviors (10, 11, 14, 23). In the present study, more urban than rural residents had healthy aging. However, we did not analyze environmental factors, such as service facilities and social capital, that could contribute to these differences. This is because the KloSA data do not include these environmental variables.

This study has some limitations. First, due to the limited data sources and the fact that this was a secondary data analysis, the analysis did not include physical environmental factors, such as housing, neighborhood facilities, and social capital that influence depressive symptoms. Physical environmental factors decrease the risk of depressive symptoms (68). Therefore, future studies should consider these factors and their effect on regional differences in the prevalence of depressive symptoms. Second, there is no clear consensus on healthy aging. A systematic review of healthy aging identified 65 models that define healthy aging in the literature, and the subcomponents vary greatly, ranging from two to nine. Moreover, some frameworks include depression as a component of healthy aging (37). In this study, healthy aging was operationalized based on successful aging, which is widely utilized as the closest concept to healthy aging and has been employed in the KLoSA study. Third, depressive symptoms were self-reported and were not ascertained through diagnostic tests. However, the CES-D is a reliable and validated screening instrument for depressive symptoms. A systematic review and meta-analysis (69) confirmed that the CES-D has acceptable screening accuracy for depression in the general population or in primary care. Nonetheless, these results should be interpreted with caution because an objective diagnostic measure of depression was not utilized. Fourth, this study lacks information on the underlying factors responsible for these differences and the mechanisms that cause these inequalities. Further research is needed to investigate the effects of various neighborhood-level factors on depressive symptoms and their interaction at the community level. Finally, the variables included in this study could also change over time. Therefore, future research should employ appropriate analysis methods to investigate how the changes in healthy aging and other variables affect the occurrence of depressive symptoms.

The present study findings provide insight into potential approaches to reducing depressive symptoms in urban and rural areas. Given that healthy aging is a crucial factor for depressive symptoms, it should be improved starting from middle age. In addition, healthy aging is related to urbanization, necessitating the need to reduce regional disparities in factors that affect healthy aging.

As urbanization accelerates, urban residents have a higher risk of depressive symptoms than rural residents. Healthy aging is an essential factor in reducing depressive symptoms. To achieve healthy aging, appropriate interventions and policies that target the middle-aged adults and gradually extend to older adults should be developed with reference to the various factors that cause regional and individual differences in healthy aging.

Publicly available datasets were analyzed in this study. This data can be found at: Korean Longitudinal Study of Aging (KLoSA) https://survey.keis.or.kr/eng/klosa/klosa01.jsp.

SK: Conceptualization, Funding acquisition, Writing – review & editing. JH: Formal analysis, Methodology, Supervision, Writing – review & editing. DK: Formal analysis, Methodology, Writing – review & editing. BK: Conceptualization, Writing – original draft, Writing – review & editing.