We investigate global differences in psychosocial well-being between older adult age groups.
Methods
Using multinomial logistic regression, we analyzed 2018 data (n = 93,663) from 9 countries/regions in the Health and Retirement Study international family of studies to compare age group differences in depression, loneliness, and happiness.
Results
Compared to the young old, the old-old reported more depression in Southern Europe, while the oldest old had higher risk in India and Southern Europe but lower risk in the United States. The old-old reported less loneliness in the United States but more in Southern Europe, while the oldest old had greater risk in Southern Europe. The old-old reported less happiness in Korea, while the oldest old had lower reports in Korea but higher reports in the United States.
Discussion
The psychosocial well-being of the oldest old is exceptionally good in the United States but exceptionally poor in Southern Europe.
Introduction
The Oldest Old
An increasing number of people are living to old ages (He et al., 2016). The global “oldest old” population, typically defined as individuals ages 85+ (Brittain et al., 2017; S. B. Lee et al., 2018), is projected to increase more than threefold between 2020 (65.5 million) and 2050 (238 million) (United States Census Bureau, 2022). The oldest old are more prevalent in high-income countries (HICs) with advanced health and long-term care systems, though their rates are also increasing in middle-income countries (MICs) (He et al., 2016; Sadana et al., 2013). Characteristics of the oldest old, such as gender, marital status, and education, can vary greatly by country (Solé-Auró & Crimmins, 2013), thus making this demographic uniquely diverse. Although some research indicates that the oldest old tend to have smaller social networks (Ailshire & Crimmins, 2011) and poorer health (Yu et al., 2012) than their younger older adult counterparts. In addition, older adults across the world, including the oldest old, face varied levels of ageism (Bratt et al., 2018; Chande & González, 2008; Jia et al., 2022) and opportunities for social integration (Carr, 2019). Previous research has paid much attention to the physical and cognitive health of the oldest old but less to their psychosocial well-being.
Psychosocial well-being is integral to health and functioning (Na & Streim, 2017; Zhang et al., 2022) and predictive of quality of life in older adults (León et al., 2020; Rondón García & Ramírez Navarrro, 2018). Compared to their younger older adult counterparts, the oldest old tend to report higher rates of depression (Cohen-Mansfield et al., 2013; S.-W. Lee et al., 2020; Yu et al., 2012) and loneliness (Ailshire & Crimmins, 2011; Beam & Kim, 2020; Cohen-Mansfield et al., 2013). However, happiness tends to have a u-shaped pattern across the lifespan, with the lowest rates in mid-life (Becker & Trautmann, 2022) and higher rates among the oldest old (Blanchflower & Oswald, 2008). Adjacent to this research is the literature that highlights a “well-being paradox” among older adults where, despite poor health outcomes, subjective well-being does not decline (Hansen & Blekesaune, 2022; Van Loon et al., 2023). Most previous research highlighting older adult age group differences in psychosocial well-being has focused on single countries or regions, with some cross-national research from Europe. This relationship, however, may vary by country or region. Thus, our study explores the relationship between age group and psychosocial well-being while accounting for economic, social, and health indicators.
Psychosocial Well-Being
Psychosocial well-being refers to levels of functioning that involve one’s relationship with others and self-referred attitudes (Burns, 2017). Commonly used measures of psychosocial well-being are depression, loneliness, and happiness.
Depression
Globally, the oldest old tend have lower rates of depressive disorder than other older adults (World Health Organization, 2017). One study investigating older adult depression in various HICs showed substantial age group differences throughout Europe, with the oldest respondents (ages 75+) having generally the highest rates (Richardson et al., 2020). Research also indicates prevalence rates of depression are heterogenous across MICs and HICs (Rai et al., 2013; Scorza et al., 2018). Relatedly, other research has found that rates of depression are higher among older populations in low-and-middle-income countries (LMICs) (Guerra et al., 2016) but higher among younger individuals in HICs (Bromet et al., 2011); despite these age group differences across the world, marital status was a notable indicator of depression. Also, across cultures worldwide, research has found that education consistently plays a key role in rates of depression (Kessler & Bromet, 2013).
Loneliness
In contrast, cross-national research on older adult loneliness is more established, although it largely focuses on European countries. This research consistently finds that the highest rates of older adult loneliness are in Eastern Europe (Hansen & Slagsvold, 2016; Rapolienė & Aartsen, 2022; Surkalim et al., 2022; Yang & Victor, 2011) which has been attributed to the rapid economic and social changes of the 1990s that transformed intergenerational relationships, social integration, and perception of social ties (De Jong Gierveld & Tesch-Römer, 2012). One study observed the highest rates of older adults loneliness in Southern and Central Europe, but this study did not include Eastern Europe (Fokkema et al., 2012). Also, one study found that England had lower rates of older adult loneliness than the United States, despite the prior having more risk factor prevalence (Hawkley et al., 2020). While this area of research is largely informed by European countries, living alone and marital status are known to be key indicators of older adult loneliness across the world (Newmyer et al., 2021).
Happiness
Cross-national rates of happiness are evaluated annually in the World Happiness Report. Recent data shows that the happiest countries in the world were (1) Finland, (2) Denmark, and (3) Iceland, while the happiest regions, on average, were (1) North America, Australia, and New Zealand, (2) Western Europe, and (3) Latin America and Caribbean (Helliwell et al., 2023); however, these rates of happiness were not self-reports, rather they were calculated with various population-based indicators (e.g., gross domestic product per capita; healthy life expectancy) and thus exclude age-specific analyses that capture cohort effects. Though some research has found a u-shaped pattern of happiness across the lifespan that sees high-points among young adults and older adults (Becker & Trautmann, 2022; Blanchflower & Oswald, 2008). While some literature argues that the concept of happiness is culturally relative (Oishi & Gilbert, 2016; Stavrova, 2019; Uchida & Oishi, 2016), other research indicates that happiness is generally associated with health (Jorm & Ryan, 2014), marital status (K. S. Lee & Ono, 2012; Stavrova et al., 2012), and social support (Diener et al., 2013) across countries.
Research suggests that older adults, especially those in retirement, are subject to aging into a “roleless role” (Riley & Riley, 1986). In one instance, being void of social roles can be perceived as an escape from workforce obligations and possibly a segue to new roles that relate to personal interests. On the other hand, a “roleless role” can lack stimulation to maintain one’s status and thus lead to declining health. As such, researchers have long called for greater integration of older adults into mainstream society (Riley & Riley, 1994; Steinkamp & Kelly, 1987). This phenomenon is particularly salient to the mental health of older adults where social status, role occupancy, and work can explain age-graded patterns of depression (Clarke et al., 2011). Additionally, different configurations of social roles can contribute to older adult loneliness (Warner et al., 2019) and happiness (Vidovićová et al., 2015).
Although life course implications can play an important role in one’s level of optimism which can ultimately influence psychosocial well-being (Purol & Chopik, 2021). Research from the United States has found cohort-based distinctions in levels of optimism; specifically, those who attended high school after the Supreme Court’s Brown versus Board of Education (1954) decision, which ended race-based segregation in public schools, report more optimism than those who attended high school before this ruling (Magee et al., 2022). Research from Central and Eastern Europe has found that younger cohorts are more optimistic than older cohorts, as the prior have benefited more from the post-Soviet transition to a market-based economy (Horvat & Evans, 2011). Adjacent to these cohort differences in optimism are the changing attitudes about mental health, particularly less stigma related to depression (Pescosolido et al., 2021). As a result, cohort differences in life course conditions and attitudes may result in differential outcomes of psychosocial well-being.
The Current Study
What remains unclear is whether psychosocial age group differences among older adults are universal or vary by country/region. Living conditions for older populations are generally worse in MICs than in HICs due to unfavorable economic and health environments (Kämpfen et al., 2018). MICs continue to experience a relatively high prevalence of communicable diseases, coupled by the growth of non-communicable diseases related to rapid aging. These developments require MICs to strengthen the strategies and governance of their health care systems (Balabanova et al., 2013). Meanwhile, formal long-term care systems for older adults are common in many HICs. The burden of such care in MICs regularly falls on younger family members (Bloom et al., 2015), even as globalization and urbanization undermine traditional family dynamics (Jesmin et al., 2011). Many individuals in MICs work in the informal economy which does not contribute to a social safety net later in life (Bloom et al., 2015).
To systematically explore how psychosocial well-being varies among older age groups by country/region, we use nationally representative data on the young old (ages 65–74), old-old (75–84), and oldest old (ages 85+). Like previous studies (Ailshire & Crimmins, 2011; Cho et al., 2015; Jivraj et al., 2014), we use economic, social, and health indicators to elucidate differences in psychosocial well-being by age group. Unlike prior research—and the unique contribution of this study—we incorporate reports from a diverse sample of countries and regions: India, China, Mexico, Korea, the United States, Northern Europe, Southern Europe, Eastern Europe, and Western Europe. This study seeks to determine psychosocial well-being differences between the young old, old-old, and oldest old, with particular attention to variation by country/region. We expect to find that the oldest old generally report higher rates of depression and loneliness, but also greater rates of happiness, than their younger older adult counterparts.
Methods
Data
To provide consistency across datasets, we used 2018 data from seven nationally representative surveys of older adults, as this was the most recent survey year that all the datasets had in common. These were the Longitudinal Aging Study in India (LASI), China Health and Retirement Longitudinal Study (CHARLS), Mexican Health and Aging Study (MHAS), Korean Longitudinal Study of Aging (KLoSA), United States Health and Retirement Study (HRS), English Longitudinal Study of Ageing (ELSA), and Survey of Health, Ageing and Retirement in Europe (SHARE). We used data from ELSA and SHARE to analyze four regions of Europe. We restricted our sample to those ages 65+ (n = 100,410). We also excluded respondents who were missing reports of pension income (n = 3535), living siblings (n = 2100), ADL disability (n = 1585) education (n = 552), person-level survey weight (n = 406), marital status (n = 66), and gender (n = 1). This left an analytical sample of 93,663 adults ages 65 and older.
Dependent Variables
Due to the availability and harmonization of variables between these seven datasets, we examined three psychosocial outcomes: depression, loneliness, and happiness. We coded these measures dichotomously to indicate whether respondents felt depressed, lonely, or happy much of the past week. CHARLS, KLoSA, and LASI asked respondents to use a four-point Likert scale to assess “how often” they felt depressed, lonely, or happy during the past week. We recoded those who said they were “mostly” or “almost always” depressed, lonely, or happy as “yes” on these variables and those who responded otherwise as “no”. HRS and ELSA asked respondents if “much of the time over/during the past week” they felt depressed, lonely, or happy, with a “yes” or “no” response option. MHAS asked respondents if they had such feelings a “majority of the time during the week prior.” For SHARE, the harmonized depression measure asked, “In the last month, have you been sad or depressed?” with “yes” and “no” response options. The harmonized version of SHARE did not provide a loneliness measure, though we self-harmonized a loneliness measure from the traditional SHARE data which asks, “How much of the time do you feel lonely?” with the three following response options: “often,” “some of the time,” and “hardly ever or never”. To better align with the other surveys, we recoded this measure so that those who responded “some of the time” and “hardly ever or never” were a “no” and those who responded “often” were a “yes”. SHARE did not include a self-reported happiness measure, so our happiness analyses did not include any data from SHARE; however, since ELSA provided a happiness measure, England is part of Northern Europe in our depression and loneliness analyses but is represented individually in the happiness analysis.
Independent Variable
Age Group is categorized as the young old (65–74, reference), old-old (75–84), and oldest old (ages 85+).
Country/Region
We include the following countries/regions in our study: India, China, Mexico, Korea, United States, Northern Europe, Southern Europe, Eastern Europe, and Western Europe. Our four European regions reflect the United Nations geoscheme categorization (United Nations Department of Social and Economic Affairs, 2022) as well as differences in GNI per capita as measured by purchasing power parity (PPP) (World Bank, 2022). For this analysis, Northern Europe comprises Denmark, England, and Sweden; Southern Europe comprises Greece, Italy, and Spain; Eastern Europe comprises the Czech Republic and Poland; and Western Europe comprises Austria, Belgium, France, Germany, and Switzerland.
Covariates
We categorize Gender as men (reference) and women. We categorize Education as low (less than upper secondary, reference), moderate (upper secondary or vocational training), or high (tertiary). Marital Status indicates whether an individual is married or partnered (“Yes”) or not (“No,” reference). Household Size is a count variable that ranges from 1–35. Living Siblings is a count variable that ranges from 0–24. ADL Disability, which indicates physical disability, is a dichotomous variable measuring whether a respondent had difficulty with any of the following activities: bathing, bed transferring, dressing, eating, or toileting. Those no difficulty with all five activities were coded “No” (reference), while those who reported at least one difficulty were coded as “Yes”. Pension, a common source of income later in life (Lu & Shelley, 2021), measures if the respondent receives a public or private pension (“Yes”) or not (“No”, reference).
Missingness Analysis
Pension
SHARE represented 88.5% of respondents who were missing the pension variable. Thus, within each of the four regions of Europe, we compared descriptive statistics between those who did and did not answer the pension question. Due to similarity in frequencies between groups, we decided to keep pension as a covariate for this study.
Living Siblings
Mexico represented 47.6% of respondents missing the living siblings variable. Thus, we compared descriptive statistics between MHAS respondents who did and did not answer the living siblings question. While the covariate frequencies between the two groups were similar, those who answered the living siblings question, and were sequentially included in this study, had a greater prevalence of depression (+12.5%) and happiness (+7.0%) but lower prevalence of loneliness (−9.7%). However, if we were to drop the living siblings variable, it would only allow us to gain 200 respondents since this variable and ADL disability both have a high number of missing responses from MHAS’s non-random proxy respondent skip pattern.
ADL Disability
Mexico represented 55.1% of the respondents missing the ADL disability variable. Thus, we compared descriptive statistics between Mexican respondents who did and did not answer the ADL disability question. While the covariate frequencies between the two groups were similar, those who answered the living siblings question, and were sequentially included in this study, had a lower prevalence of depression (-27.9%) and loneliness (-14.9%) but higher prevalence of happiness (+25.8%). Despite these findings, we included ADL disability in our study due to its known association with older adult psychosocial well-being (Barry et al., 2013; Cohen-Mansfield et al., 2013; Na & Streim, 2017).
Statistical Analysis
We first examined sample characteristics of the young old, old-old, and oldest old across country/region. Second, we examined age group differences in prevalence rates of each psychosocial well-being outcome by country/region. Finally, we used multinomial logistic regression models for each country/region to examine age group differences in the relative risk ratio of (RRR) of reporting depression, loneliness, and happiness. These models fully adjust for gender, education, marital status, household size, living siblings, ADL disability, and pension income. We conducted all analyses in Stata, release 18, using sample weights as appropriate.
Results
Sample Characteristics
Table 1 presents characteristics of the sample by country/region and age group. Women represented a majority of the sample, especially among the oldest old. Women were most prevalent among the oldest old in Korea (66.9%), United States (65.0%), Northern Europe (62.6%), and Western Europe (61.8%). The oldest old reported lower educational levels and rates of marriage than the young old and old. The oldest old reported higher rates of ADL disability than the young old and old-old, especially in Korea, Southern Europe, and Western Europe. The oldest old generally lived in smaller households than the young old and old-old, except in India and Mexico. The oldest had a lower average of living siblings than the young old and old-old. The oldest old had lower rates of pension income than the young old and/or old-old across various countries, though rates were similar within each of the four regions of Europe.
Table 1. Prevalence of Sample Characteristics by Country/Region and Age Group (N = 93,663).
India
China
Mexico
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Women
50.6%
51.2%
54.6%
51.4%
51.5%
54.8%
56.4%
53.7%
54.7%
Low education
77.1%
83.5%
89.7%
94.3%
91.7%
96.1%
87.1%
92.0%
94.2%
Moderate education
18.7%
12.9%
8.7%
4.7%
5.7%
1.8%
3.0%
1.5%
1.1%
High education
4.2%
3.6%
1.6%
1.0%
2.6%
2.1%
9.9%
6.4%
4.7%
Married
64.7%
47.7%
28.1%
81.5%
59.8%
33.3%
68.0%
51.4%
31.8%
ADL disability
19.9%
30.2%
44.6%
23.9%
34.5%
50.0%
15.9%
26.2%
41.4%
Household size†
4.9
4.9
5.2
2.6
2.3
2.3
2.3
2.3
2.3
Living siblings†
2.9
2.3
1.7
3.4
2.6
2.2
4.9
3.5
2.1
Has pension
43.1%
50.4%
47.1%
87.5%
84.6%
77.1%
31.7%
34.6%
31.8%
n = 21,343
n = 7394
n = 7873
Korea
United States
Northern Europe
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Women
55.3%
59.0%
66.9%
58.2%
57.8%
65.0%
55.3%
58.3%
62.6%
Low education
61.2%
77.2%
88.1%
15.4%
20.0%
22.3%
23.5%
38.8%
51.6%
Moderate education
29.8%
15.9%
8.1%
57.7%
57.9%
55.9%
47.6%
38.6%
31.4%
High education
8.9%
6.9%
3.9%
26.9%
22.1%
21.7%
28.9%
22.6%
16.9%
Married
81.1%
62.0%
36.4%
64.9%
54.5%
30.9%
72.4%
58.2%
36.7%
ADL disability
2.2%
7.2%
24.3%
14.8%
21.1%
38.4%
11.0%
20.3%
36.9%
Household size†
3.0
2.6
2.8
2.2
2.0
1.8
1.9
1.7
1.5
Living siblings†
3.4
2.4
1.3
3.4
2.8
2.1
1.8
1.4
0.9
Has pension
49.6%
36.9%
18.6%
28.9%
36.7%
35.9%
95.1%
95.9%
92.2%
n = 4353
n = 9016
n = 15,854
Southern Europe
Eastern Europe
Western Europe
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Young old
Old-old
Oldest old
Women
49.8%
52.0%
57.1%
56.1%
59.0%
58.2%
51.8%
53.7%
61.8%
Low education
58.4%
74.0%
83.2%
32.9%
50.7%
63.6%
24.9%
35.0%
52.4%
Moderate education
27.3%
17.5%
10.9%
54.8%
37.0%
25.6%
45.2%
40.5%
30.9%
High education
14.3%
8.6%
5.8%
12.3%
12.4%
10.8%
29.9%
24.5%
16.7%
Married
78.7%
64.4%
43.5%
72.0%
54.8%
37.2%
73.8%
62.4%
37.2%
ADL disability
7.1%
17.2%
41.1%
12.2%
24.7%
43.6%
8.5%
18.0%
38.8%
Household size†
2.2
2.0
1.8
2.2
2.0
2.0
1.8
1.7
1.4
Living siblings†
2.3
1.9
1.3
1.7
1.2
0.8
2.1
1.7
1.0
Has pension
90.7%
94.6%
96.2%
99.0%
99.6%
99.7%
98.3%
98.6%
98.4%
n = 14,000
n = 9074
n = 11,503
Note. Figures shown use person-level survey weights; ADL = Activities of Daily Living; † = count mean.
Bivariate Analyses
Figure 1 presents prevalence rates of depression by country/region and age group, while significance levels indicate comparison to the young old. A list of all prevalence rates of depression, loneliness, and happiness by country/region and age group can be found in Supplemental Table 1. In India, the prevalence of depression was significantly higher among the old-old (p = .001) and oldest old (p = .000). In Mexico, the prevalence of depression was significantly higher among the old-old (p = .003) and oldest old (p = .000). In Korea, the prevalence of depression was significantly higher among the oldest old (p = .000). In Northern Europe, the prevalence of depression was significantly higher among the old-old (p = .000) and oldest old (p = .000). In Southern Europe, the prevalence of depression was significantly higher among the old-old (p = .000) and oldest old (p = .000). In Eastern Europe, the prevalence of depression was significantly higher among the old-old (p = .032). In Western Europe, the prevalence of depression was significantly higher among the oldest old (p = .001). There were no significant age group differences in depression in China and the United States. Figure 2 presents prevalence rates of loneliness by country/region and age group, while significance levels indicate comparison to the young old. In India, the prevalence of loneliness was significantly higher among the old-old (p = .000) and oldest old (p = .000). In China, the prevalence of loneliness was significantly higher among the old-old (p = .000). In Mexico, the prevalence of loneliness was significantly higher among the old-old (p = .008) and oldest old (p = .000). In Korea, the prevalence of loneliness was significantly higher among the oldest old (p = .000). In the United States, the prevalence of loneliness was significantly among the oldest old (p = .000). In Northern Europe, the prevalence of loneliness was significantly higher among the old-old (p = .000) and oldest old (p = .000). In Southern Europe, the prevalence of loneliness was significantly higher among the old-old (p = .000) and oldest old (p = .000). In Eastern Europe, the prevalence of loneliness was significantly higher among the old-old (p = .000) and oldest old (p = .000). In Western Europe, the prevalence of depression was significantly higher among the oldest old (p = .000). Figure 3 presents prevalence rates of happiness by country/region and age group, while significance levels indicate comparison to the young old. In India, the prevalence of happiness was significantly lower among the oldest old (p = .030). In Mexico, the prevalence of happiness was significantly lower among the oldest old (p = .027). In Korea, the prevalence of happiness was significantly lower among the old-old (p = .000) and oldest old (p = .000). In England, the prevalence of happiness was significantly lower among the oldest old (p = .001). There were no significant age group differences in happiness in China and the United States.
Figure 1. Depression prevalence by country/region and age group. Note. Compared to young old=*p < .05, **p < .01, ***p < .001.
Figure 2. Loneliness prevalence by country/region and age group. Note. Compared to young old=*p < .05, **p < .01, ***p < .001.
Figure 3. Happiness prevalence by country/region and age group. Note. Compared to young old=*p < .05, **p < .01, ***p < .001.
Multivariate Analyses
Table 2 presents RRRs of reporting depression among the old-old and oldest old, when compared to the young old, while fully adjusting for gender, education, marital status, household size, living siblings, ADL disability, and pension income. Full models with RRRs of depression among all covariates for each country/region can be found in Supplemental Tables 2–10. In India, the oldest old reported a higher risk of depression than the young old (RRR = 1.39; p = .017; 95% CI = 1.06, 1.83). In the United States, the oldest old reported a lower risk of depression than the young old (RRR = 0.78; p = .030; 95% CI = 0.62, 0.98). In Southern Europe, a higher risk of depression was reported among both the old-old (RRR = 1.34; p = .000; 95% CI = 1.14, 1.57) and oldest old (RRR = 1.37; p = .016; 95% CI = 1.06, 1.77).
Table 2. Adjusted Multinomial Logistic Regression of Age Group Differences in Depression by Country/Region.
Table 3 presents RRRs of reporting loneliness among the old-old and oldest old, when compared to the young old, while fully adjusting for gender, education, marital status, household size, living siblings, ADL disability, and pension income. Full models with RRRs of loneliness among all covariates for each country/region can be found in Supplemental Tables 11–19. In the United States, the old-old reported a lower risk of loneliness than the young old (RRR = 0.87; p = .045; 95% CI = 0.75, 1.00). In Southern Europe, a higher risk of loneliness was reported among both the old-old (RRR = 1.66; p = .000; 95% CI = 1.30, 2.12) and oldest old (RRR = 1.83; p = .000; 95% CI = 1.31, 2.57).
Table 3. Adjusted Multinomial Logistic Regression of Age Group Differences in Loneliness by Country/Region.
Table 4 presents RRRs of reporting happiness among the old-old and oldest old, when compared to the young old, while fully adjusting for gender, education, marital status, household size, living siblings, ADL disability, and pension income. Full models with RRRs of happiness among all covariates for each country/region can be found in Supplemental Tables 20–25. In Korea, lower reports of happiness were found among both the old-old (RRR = 0.81; p = .007; 95% CI = 0.70, 0.94) and oldest old (RRR = 0.73; p = .022; 95% CI = 0.56, 0.96). In the United States, the oldest old had higher reports of happiness (RRR = 1.62; p = .000; 95% CI = 1.29, 2.03).
Table 4. Adjusted Multinomial Logistic Regression of Age Group Differences in Happiness by Country/Region.
A comprehensive table of all adjusted age group differences by country/region and psychosocial well-being outcome can be found in Supplemental Table 26.
Discussion
The purpose of this study was to determine if worse psychosocial well-being, as measured by higher levels of depression and loneliness, but also greater levels of happiness, among the oldest old is universal or varies by country/region. This investigation is important due the rapidly growing number of the oldest old across the world (United States Census Bureau, 2022) who face varied levels of ageism (Bratt et al., 2018; Chande & González, 2008; Jia et al., 2022) and opportunities for social integration (Carr, 2019). Informed by life course theory, our analysis included a diverse group of five countries and four regions while accounting for economic, social, and health indicators of psychosocial well-being. We found that the oldest old had higher depression and loneliness in Southern Europe but less loneliness and more happiness in the United States; also, the oldest old were more depressed in India and less happy in Korea.
Depression
Rates of depression are typically higher at the oldest ages (Cohen-Mansfield et al., 2013; S.-W. Lee et al., 2020; Yu et al., 2012). Although we initially found no depression differences by age group in China and the United States; this age group parity in depression would be expected in the United States because rates are notably low among older adults in this country, while our findings from China are unique because rates of depression there are known to increase in advanced ages (Wang et al., 2023). Also, finding no oldest old disadvantage in Eastern Europe is likely in part to this region having notably high rates of depression when compared to other regions in Europe (Hansen & Slagsvold, 2017). Although older adult depression in Eastern Europe has been attributed to low levels of social cohesion (Bertossi Urzua et al., 2019). Our other European findings were not surprising given prior research on depression among all age groups (World Health Organization, 2017) and the investment in mental health care that many of these countries have made in response to similar concerns (World Health Organization, 2021). Also, the notably low rates of depression in India and Korea do not reflect the rates in their respective regions (World Health Organization, 2017) and thus warrant further analysis.
After model adjustment, the oldest old maintained high odds in Southern Europe and India but lower odds surfaced in the United States. Our findings from Southern Europe align with existing research that shows the oldest respondents (ages 75+) in Southern European countries (i.e., Greece; Italy; Spain) report higher rates of depression than their younger older adult counterparts (ages 55–65). The oldest old depression disadvantage in India is a notable finding because this is a seemingly new observation about this demographic. Existing research indicates that life satisfaction, particularly with one’s living arrangement (Paul et al., 2023), and quality of family relationships (Vishwakarma et al., 2023) are related to depression among older adults in India. The oldest old’s lower rates of depression in the United States were interesting because it counters the other country/region findings in our sample. ADL disability, education, and marital status were all strongly associated with depression among older adults in the United States (see Supplemental Table 6), as found in prior research (Zivin et al., 2010, 2013). Although ADL disability had a particularly strong association, suggesting that depression among older adults in the United States largely hinges on their ability to provide self-care. Also, it is claimed that underdiagnosis of older adult depression is informed by poor cognition and societal stigma (Morichi et al., 2015). One study found that older adults in the United States had better cognition than those from England and attributed this to lower rates of depression in the prior (Langa et al., 2009). Therefore, future research would benefit by exploring country/region variations in cognition among the oldest old, particularly as it relates to depression.
Loneliness
Age group rates of loneliness were significant across all countries/region, except the oldest old in China; this matched earlier findings indicating loneliness typically increases with age (Ailshire & Crimmins, 2011; Beam & Kim, 2020; Cohen-Mansfield et al., 2013). After considering covariates, only the low odds among the old-old in the United States and high odds among the old-old and oldest old in Southern Europe remained. Only observing a loneliness advantage among the old-old in the United States is contrary to existing research that highlights high rates of loneliness among the oldest old (Ailshire & Crimmins, 2011; Beam & Kim, 2020). Despite our contrary findings, we found that the old-old loneliness advantage was associated with ADL disability, education, and marital status (see Supplemental Table 15) which resonates with prior research (Ailshire & Crimmins, 2011). ADL disability had a particularly strong association with loneliness in the United States, thus reasserting the integral role self-care has on psychosocial well-being among the oldest old in this country. This age group difference in the United States is possibly due to those from the Silent Generation exhibiting the resilience and coping mechanisms they developed while growing up during the Great Depression and War II (Twenge, 2023). The loneliness disadvantage among Southern Europe’s old-old and oldest old was less surprising since this region reports notably high rates of loneliness (Yang & Victor, 2011); such high rates of loneliness could be due to Southern Europe having communal societies with high expectations for social contact (Van Tilburg et al., 1998).
Happiness
Age group prevalence rates of happiness were significant in Mexico and England as well as Korea and India where rates were much lower. These cross-country variations provide some support to the “Easterlin paradox,” which states that happiness varies by country income (Easterlin, 1974), although our rates from China and Mexico counter this theory. Also, our findings challenge the research that finds happiness is generally u-shaped across the lifespan (Becker & Trautmann, 2022; Blanchflower & Oswald, 2008), as we found that the oldest old generally report lower rates of happiness. Younger cohorts of older adults, particularly in Korea and England, have benefited from social protections earlier in their retirement than the oldest old (Ginn & MacIntyre, 2013; S. Lee et al., 2019); although some research argues that such reforms do not contribute to rates of happiness (Pak, 2020).
Adjusted models showed high rates of happiness among the oldest old in the United States but also low rates among the old-old and oldest old in Korea. Existing literature from the United States shows a u-shaped direction between age group and happiness, suggesting young adults and older adults have the highest rates (Blanchflower & Oswald, 2008). We advance this research by comparing reports of happiness between older age groups and find that the oldest old in the United States are exceptionally happy. Happiness in the United States was linked to ADL disability and marital status (see Supplemental Table 24) which supports existing research (Freedman et al., 2017; Mhaske, 2017). Once again, ADL disability played an important role in the exceptional psychosocial well-being of the oldest old in the United States. Research suggests that Baby Boomers, which are represented in our study as the young old, experienced reduced rates of happiness in part to the Great Recession (Bardo et al., 2017), a time when many of those from this generation were nearing retirement. Therefore, it is possible that the timing of the Great Recession in the United States facilitated cohort differences in older adult happiness. In contrast, the old-old and the oldest old in Korea reported notably lower rates of happiness which counters research from Western countries (Blanchflower & Oswald, 2008). Research from Korea has tested the u-shaped age group relationship with happiness and found that happiness did not increase in older adulthood (Kim et al., 2023); researchers contributed this to respondents with low agreeableness and neuroticism. Regardless of its explanation, the low rates of happiness that we observed among Korea’s older age groups are source of societal concern that needs further examination.
(Dis)parities in Psychosocial Well-Being
Our findings give some credence to “well-being paradox” that suggests subjective older adults well-being does not decline, despite their poor health (Hansen & Blekesaune, 2022; Van Loon et al., 2023). However, our findings from the United States do not align with existing research that indicates older generations are less optimistic than younger generations (Horvat & Evans, 2011; Magee et al., 2022). Although we have established that ADL disability is essential to the oldest old psychosocial advantage in the United States. Future research would benefit from investigating why this association is not afforded to other aging countries/regions. In contrast, the oldest old in Southern Europe reported notably high rates of depression and loneliness, despite this region of the world being known for its strong family ties (Litwin, 2010). These findings are consequential to the social integration of older adults (Carr, 2019), particularly the oldest old, who are a rapidly growing demographic in aging societies (United States Census Bureau, 2022). Many countries in Southern Europe have modest investment in long-term care (LTC) services (Nagode & Lebar, 2019). Research from China shows that LTC services contribute to less depression and more happiness among older adults (Chen & Zhao, 2023; Tang et al., 2022). Therefore, investment in LTC services in Southern Europe has potential to hamper the high rates of depression, and perhaps loneliness, among its oldest old population. Although since LTC needs in Southern Europe are heterogeneous, it is recommended that LTC policy interventions in the region should be country-specific (Albuquerque, 2022).
There were no adjusted age group differences in psychosocial well-being throughout China, Mexico, Northern Europe, Eastern Europe, or Western Europe. Research shows that ageism is associated with poorer psychosocial well-being outcomes among older adults (Kang & Kim, 2022). Coincidentally, older adults face profound discrimination in China (Jia et al., 2022) and Mexico (Chande & González, 2008). Moreover, age discrimination is higher among older adults than younger age groups in Eastern European countries, although the opposite is true throughout many countries in Northern Europe and Western Europe (Bratt et al., 2018). Therefore, it is possible that we observed no older adult age group differences in psychosocial well-being in these countries/regions because notably high/low levels of old age discrimination contribute to similar psychosocial well-being outcomes across older age groups. Research indicates there are effective interventions aimed at reducing ageism toward older adults such as aging education and positive intergenerational contact (Apriceno & Levy, 2023). Also, future research in this area would benefit from studying how participation in certain social roles, or even the “roleless role” (Riley & Riley, 1986), might influence psychosocial well-being outcomes among the oldest old in these countries/regions.
Limitations
Our research has some limitations. First, while we used representative samples for 9 countries/regions, survey questions regarding depression, loneliness, and happiness varied. These questions were dichotomous (yes/no) in the HRS, ELSA, and MHAS but were based on a 4-point Likert-type scale in the CHARLS, LASI, and KLoSA. Also, in SHARE, the depression measure was dichotomous (yes/no), while the loneliness measure derived from a 3-point Likert-type item. We recoded the Likert-type questions to approximate dichotomous variables, but there may be some limitations to this approach since some of the response options were different across surveys. Second, SHARE does not ask questions about self-reported happiness, so Europe was excluded from our happiness analyses (aside from England), thus limiting our cross-national examination of this psychosocial outcome. Third, due to the comparably small sample sizes in the SHARE countries, we recoded them into four regions of Europe. While these regions are relatively homogenous in geography and income, they may obscure country variations in psychosocial well-being. Finally, response rates in all the surveys were different and thus might contribute to biased results. Specifically, a high number of Mexico respondents were excluded due to a non-random proxy respondent skipping pattern on the ADL disability question. As such, study might have influenced partially bias psychosocial results for Mexico.
Conclusion
While existing research indicates that the oldest old generally have higher rates of depression and loneliness, but also greater rates of happiness, we observed this in only few countries/regions as well as some findings to the contrary. Specifically, we found that the oldest old had higher depression and loneliness in Southern Europe but less loneliness and more happiness in the United States; also, the oldest old were more depressed in India and less happy in Korea. Thus, the psychosocial well-being of the oldest old is exceptionally good in the United States but exceptionally poor in Southern Europe. Our study contributes to the growing literature on the oldest old by cross-nationally comparing the psychosocial profile of this growing demographic. Future research in this area would benefit from incorporating a wider range of countries/regions and psychosocial well-being measures as well as comparing the cognition of the world’s oldest old.
Acknowledgements
We thank Philippa J. Clarke for her assistance with this study.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this manuscript was provided to SDB by the University of Southern California Leonard Davis School of Gerontology and Training in the Demography and Economics of Aging (Grant No: T32AG000221) at the University of Michigan Population Studies Center.
Ailshire J. A., Crimmins E. M. (2011). Psychosocial factors associated with longevity in the United States: Age differences between the old and oldest-old in the health and retirement study. Journal of Aging Research, 2011(1), Article e530534. https://doi.org/10.4061/2011/530534
Albuquerque P. C. (2022). Met or unmet need for long-term care: Formal and informal care in southern Europe. The Journal of the Economics of Ageing, 23(October), Article 100409. https://doi.org/10.1016/j.jeoa.2022.100409
Apriceno M., Levy S. R. (2023). Systematic review and meta-analyses of effective programs for reducing ageism toward older adults. Journal of Applied Gerontology, 42(6), 1356–1375. https://doi.org/10.1177/07334648231165266
Balabanova D., Mills A., Conteh L., Akkazieva B., Banteyerga H., Dash U., Gilson L., Harmer A., Ibraimova A., Islam Z., Kidanu A., Koehlmoos T. P., Limwattananon S., Muraleedharan V., Murzalieva G., Palafox B., Panichkriangkrai W., Patcharanarumol W., Penn-Kekana L., McKee M. (2013). Good health at low cost 25 years on: Lessons for the future of health systems strengthening. The Lancet, 381(9883), 2118–2133. https://doi.org/10.1016/S0140-6736(12)62000-5
Bardo A. R., Lynch S. M., Land K. C. (2017). The importance of the baby boom cohort and the great recession in understanding age, period, and cohort patterns in happiness. Social Psychological and Personality Science, 8(3), 341–350. https://doi.org/10.1177/1948550616673874
Barry L. C., Soulos P. R., Murphy T. E., Kasl S. V., Gill T. M. (2013). Association between indicators of disability burden and subsequent depression among older persons. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 68(3), 286–292. https://doi.org/10.1093/gerona/gls179
Beam C. R., Kim A. J. (2020). Psychological sequelae of social isolation and loneliness might be a larger problem in young adults than older adults. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1), S58–S60. https://doi.org/10.1037/tra0000774
Becker C. K., Trautmann S. T. (2022). Does happiness increase in old age? Longitudinal evidence from 20 European countries. Journal of Happiness Studies, 23(7), 3625–3654. https://doi.org/10.1007/s10902-022-00569-4
Bertossi Urzua C., Ruiz M. A., Pajak A., Kozela M., Kubinova R., Malyutina S., Peasey A., Pikhart H., Marmot M., Bobak M. (2019). The prospective relationship between social cohesion and depressive symptoms among older adults from Central and Eastern Europe. Journal of Epidemiology and Community Health, 73(2), 117–122. https://doi.org/10.1136/jech-2018-211063
Bloom D. E., Chatterji S., Kowal P., Lloyd-Sherlock P., McKee M., Rechel B., Rosenberg L., Smith J. P. (2015). Macroeconomic implications of population ageing and selected policy responses. The Lancet, 385(9968), 649–657. https://doi.org/10.1016/S0140-6736(14)61464-1
Bratt C., Abrams D., Swift H. J., Vauclair C.-M., Marques S. (2018). Perceived age discrimination across age in Europe: From an ageing society to a society for all ages. Developmental Psychology, 54(1), 167–180. https://doi.org/10.1037/dev0000398
Brittain K., Kingston A., Davies K., Collerton J., Robinson L. A., Kirkwood T. B. L., Bond J., Jagger C. (2017). An investigation into the patterns of loneliness and loss in the oldest old – Newcastle 85+ Study. Ageing and Society, 37(1), 39–62. https://doi.org/10.1017/S0144686X15001142
Bromet E., Andrade L. H., Hwang I., Sampson N. A., Alonso J., De Girolamo G., De Graaf R., Demyttenaere K., Hu C., Iwata N., Karam A. N., Kaur J., Kostyuchenko S., Lépine J.-P., Levinson D., Matschinger H., Mora M. E. M., Browne M. O., Posada-Villa J., Kessler R. C. (2011). Cross-national epidemiology of DSM-IV major depressive episode. BMC Medicine, 9(1), 90. https://doi.org/10.1186/1741-7015-9-90
Carr D. (2019). Aging alone? International perspectives on social integration and isolation. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 74(8), 1391–1393. https://doi.org/10.1093/geronb/gbz095
Chen Y., Zhao H. (2023). Long-term care insurance, mental health of the elderly and its spillovers. Frontiers in Public Health, 11(March), Article 982656. https://doi.org/10.3389/fpubh.2023.982656
Cheng G., Yan Y. (2021). Sociodemographic, health-related, and social predictors of subjective well-being among Chinese oldest-old: A national community-based cohort study. BMC Geriatrics, 21(1), 124. https://doi.org/10.1186/s12877-021-02071-7
Cho J., Martin P., Poon L. W., Georgia Centenarian Study. (2015). Successful aging and subjective well-being among oldest-old adults. The Gerontologist, 55(1), 132–143. https://doi.org/10.1093/geront/gnu074
Clarke P., Marshall V., House J., Lantz P. (2011). The social structuring of mental health over the adult life course: Advancing theory in the sociology of aging. Social Forces, 89(4), 1287–1313. https://doi.org/10.1353/sof.2011.0036
Cohen-Mansfield J., Shmotkin D., Blumstein Z., Shorek A., Eyal N., Hazan H., CALAS Team. (2013). The old, old-old, and the oldest old: Continuation or distinct categories? An examination of the relationship between age and changes in health, function, and wellbeing. The International Journal of Aging and Human Development, 77(1), 37–57. https://doi.org/10.2190/AG.77.1.c
De Jong Gierveld J., Tesch-Römer C. (2012). Loneliness in old age in Eastern and Western European societies: Theoretical perspectives. European Journal of Ageing, 9(4), 285–295. https://doi.org/10.1007/s10433-012-0248-2
Diener E., Oishi S., Ryan K. L. (2013). Universals and cultural differences in the causes and structure of happiness: A multilevel review. In Keyes C. L. M. (Ed.), Mental well-being (pp. 153–176). Springer. https://doi.org/10.1007/978-94-007-5195-8_8
Easterlin R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. In Nations and households in economic growth (pp. 89–125). Elsevier. https://doi.org/10.1016/B978-0-12-205050-3.50008-7
Elder G. H., Johnson M. K., Crosnoe R. (2003). The emergence and development of life course theory. In Mortimer J. T., Shanahan M. J. (Eds.), Handbook of the life course (pp. 3–19). Springer US. https://doi.org/10.1007/978-0-306-48247-2_1
Fokkema T., De Jong Gierveld J., Dykstra P. A. (2012). Cross-national differences in older adult loneliness. The Journal of Psychology, 146(1–2), 201–228. https://doi.org/10.1080/00223980.2011.631612
Freedman V. A., Carr D., Cornman J. C., Lucas R. E. (2017). Impairment severity and evaluative and experienced well-being among older adults: Assessing the role of daily activities. Innovation in Aging, 1(1), Article igx010. https://doi.org/10.1093/geroni/igx010
Guerra M., Prina A. M., Ferri C. P., Acosta D., Gallardo S., Huang Y., Jacob K. S., Jimenez-Velazquez I. Z., Llibre Rodriguez J. J., Liu Z., Salas A., Sosa A. L., Williams J. D., Uwakwe R., Prince M. (2016). A comparative cross-cultural study of the prevalence of late life depression in low and middle income countries. Journal of Affective Disorders, 190(January), 362–368. https://doi.org/10.1016/j.jad.2015.09.004
Hansen T., Blekesaune M. (2022). The age and well-being “paradox”: A longitudinal and multidimensional reconsideration. European Journal of Ageing, 19(4), 1277–1286. https://doi.org/10.1007/s10433-022-00709-y
Hansen T., Slagsvold B. (2016). Late-life loneliness in 11 European countries: Results from the generations and gender survey. Social Indicators Research, 129(1), 445–464. https://doi.org/10.1007/s11205-015-1111-6
Hansen T., Slagsvold B. (2017). The East–West divide in late-life depression in Europe: Results from the generations and gender survey. Scandinavian Psychologist, 4(1), 1–18. https://doi.org/10.15714/scandpsychol.4.e4
Hawkley L. C., Steptoe A., Schumm L. P., Wroblewski K. (2020). Comparing loneliness in England and the United States, 2014–2016: Differential item functioning and risk factor prevalence and impact. Social Science & Medicine, 265(November), Article 113467. https://doi.org/10.1016/j.socscimed.2020.113467
Horvat P., Evans G. (2011). Age, inequality, and reactions to marketization in post-communist Central and Eastern Europe. European Sociological Review, 27(6), 708–727. https://doi.org/10.1093/esr/jcq033
House J. S., Lepkowski J. M., Kinney A. M., Mero R. P., Kessler R. C., Herzog A. R. (1994). The social stratification of aging and health. Journal of Health and Social Behavior, 35(3), 213–234. https://doi.org/10.2307/2137277
Jesmin S. S., Amin I., Ingman S. (2011). Sustainability of seniors in low- and middle-income societies. Educational Gerontology, 37(6), 548–557. https://doi.org/10.1080/03601277.2011.570220
Jia J., Ning Y., Chen M., Wang S., Li Y., Yang H. (2022). Ending age discrimination and stigma to promote healthy ageing in China. The Lancet, 400(10367), 1907–1909. https://doi.org/10.1016/S0140-6736(22)02362-5
Jivraj S., Nazroo J. (2014). Determinants of socioeconomic inequalities in subjective well-being in later life: A cross-country comparison in England and the USA. Quality of Life Research, 23(9), 2545–2558. https://doi.org/10.1007/s11136-014-0694-8
Jivraj S., Nazroo J., Vanhoutte B., Chandola T. (2014). Aging and subjective well-being in later life. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 69(6), 930–941. https://doi.org/10.1093/geronb/gbu006
Jorm A. F., Ryan S. M. (2014). Cross-national and historical differences in subjective well-being. International Journal of Epidemiology, 43(2), 330–340. https://doi.org/10.1093/ije/dyt188
Kämpfen F., Wijemunige N., Evangelista B. (2018). Aging, non-communicable diseases, and old-age disability in low- and middle-income countries: A challenge for global health. International Journal of Public Health, 63(9), 1011–1012. https://doi.org/10.1007/s00038-018-1137-z
Kang H., Kim H. (2022). Ageism and psychological well-being among older adults: A systematic review. Gerontology and Geriatric Medicine, 8(April), Article 23337214221087023. https://doi.org/10.1177/23337214221087023
Kim J. H., Choi E., Kim N., Choi I. (2023). Older people are not always happier than younger people: The moderating role of personality. Applied Psychology: Health and Well-Being, 15(1), 275–292. https://doi.org/10.1111/aphw.12377
Langa K. M., Llewellyn D. J., Lang I. A., Weir D. R., Wallace R. B., Kabeto M. U., Huppert F. A. (2009). Cognitive health among older adults in the United States and in England. BMC Geriatrics, 9(1), 23. https://doi.org/10.1186/1471-2318-9-23
Lee J., Meijer E., Phillips D., Hu P. (2021). Disability incidence rates for men and women in 23 countries: Evidence on health effects of gender inequality. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 76(2), 328–338. https://doi.org/10.1093/gerona/glaa288
Lee K. S., Ono H. (2012). Marriage, cohabitation, and happiness: A cross‐national analysis of 27 countries. Journal of Marriage and Family, 74(5), 953–972. https://doi.org/10.1111/j.1741-3737.2012.01001.x
Lee S., Ku I., Shon B. (2019). The effects of old-age public transfer on the well-being of older adults: The case of social pension in South Korea. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 74(3), 506–515. https://doi.org/10.1093/geronb/gbx104
Lee S. B., Oh J. H., Park J. H., Choi S. P., Wee J. H. (2018). Differences in youngest-old, middle-old, and oldest-old patients who visit the emergency department. Clinical and Experimental Emergency Medicine, 5(4), 249–255. https://doi.org/10.15441/ceem.17.261
Lee S.-W., Choi J.-S., Lee M. (2020). Life satisfaction and depression in the oldest old: A longitudinal study. The International Journal of Aging and Human Development, 91(1), 37–59. https://doi.org/10.1177/0091415019843448
León L. P. D., Mangin J. P. L., Ballesteros S. (2020). Psychosocial determinants of quality of life and active aging. A structural equation model. International Journal of Environmental Research and Public Health, 17(17), 6023. https://doi.org/10.3390/ijerph17176023
Litwin H. (2010). Social networks and well-being: A comparison of older people in mediterranean and non-mediterranean countries. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65(5), 599–608. https://doi.org/10.1093/geronb/gbp104
Lu P., Shelley M. (2021). Retirement, pensions, and depressive symptoms among older adults in China, England, Mexico, and the United States. The International Journal of Aging and Human Development, 92(1), 40–64. https://doi.org/10.1177/0091415019868227
Magee W., Elliott M. R., Sinkewicz M., Finlay J., Clarke P. (2022). Who looks on the bright side? Optimistic and pessimistic perceptual-response reflexes over American adulthood. Advances in Life Course Research, 51(1), Article 100452. https://doi.org/10.1016/j.alcr.2021.100452
McLeod J. D. (2013). Social stratification and inequality. In Aneshensel C. S., Phelan J. C., Bierman A. (Eds.), Handbook of the sociology of mental health (pp. 229–253). Springer. https://doi.org/10.1007/978-94-007-4276-5_12
Morichi V., Dell’Aquila G., Trotta F., Belluigi A., Lattanzio F., Cherubini A. (2015). Diagnosing and treating depression in older and oldest old. Current Pharmaceutical Design, 21(13), 1690–1698. https://doi.org/10.2174/1381612821666150130124354
Na L., Streim J. E. (2017). Psychosocial well-being associated with activity of daily living stages among community-dwelling older adults. Gerontology & geriatric medicine, 3(March), Article 2333721417700011. https://doi.org/10.1177/2333721417700011
Nagode M., Lebar L. (2019). Trends and challenges in long-term care in Europe. Revija za Socijalnu Politiku, 26(2), 255–262. https://doi.org/10.3935/rsp.v26i2.1655
Newmyer L., Verdery A. M., Margolis R., Pessin L. (2021). Measuring older adult loneliness across countries. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 76(7), 1408–1414. https://doi.org/10.1093/geronb/gbaa109
Oishi S., Gilbert E. A. (2016). Current and future directions in culture and happiness research. Current Opinion in Psychology, 8(April), 54–58. https://doi.org/10.1016/j.copsyc.2015.10.005
O’Rand A. M. (2003). The future of the life course. In Mortimer J. T., Shanahan M. J. (Eds.), Handbook of the life course (pp. 693–701). Springer US. https://doi.org/10.1007/978-0-306-48247-2_33
Pak T.-Y. (2020). Social protection for happiness? The impact of social pension reform on subjective well-being of the Korean elderly. Journal of Policy Modeling, 42(2), 349–366. https://doi.org/10.1016/j.jpolmod.2019.12.001
Paúl C., Ayis S., Ebrahim S. (2007). Disability and psychosocial outcomes in old age. Journal of Aging and Health, 19(5), 723–741. https://doi.org/10.1177/0898264307304301
Paul R., Muhammad T., Rashmi R., Sharma P., Srivastava S., Zanwar P. P. (2023). Depression by gender and associated factors among older adults in India: Implications for age-friendly policies. Scientific Reports, 13(1), Article 17651. https://doi.org/10.1038/s41598-023-44762-8
Pescosolido B. A., Halpern-Manners A., Luo L., Perry B. (2021). Trends in public stigma of mental illness in the US, 1996-2018. JAMA Network Open, 4(12), Article e2140202. https://doi.org/10.1001/jamanetworkopen.2021.40202
Purol M. F., Chopik W. J. (2021). Optimism: Enduring resource or miscalibrated perception? Social and Personality Psychology Compass, 15(5), Article e12593. https://doi.org/10.1111/spc3.12593
Rai D., Zitko P., Jones K., Lynch J., Araya R. (2013). Country- and individual-level socioeconomic determinants of depression: Multilevel cross-national comparison. British Journal of Psychiatry, 202(3), 195–203. https://doi.org/10.1192/bjp.bp.112.112482
Rapolienė G., Aartsen M. (2022). Lonely societies: Low trust societies? Further explanations for national variations in loneliness among older Europeans. European Journal of Ageing, 19(3), 485–494. https://doi.org/10.1007/s10433-021-00649-z
Read S., Grundy E., Foverskov E. (2016). Socio-economic position and subjective health and well-being among older people in Europe: A systematic narrative review. Aging & Mental Health, 20(5), 529–542. https://doi.org/10.1080/13607863.2015.1023766
Richardson R. A., Keyes K. M., Medina J. T., Calvo E. (2020). Sociodemographic inequalities in depression among older adults: Cross-sectional evidence from 18 countries. The Lancet. Psychiatry, 7(8), 673–681. https://doi.org/10.1016/S2215-0366(20)30151-6
Rondón García L. M., Ramírez Navarrro J. M. (2018). The impact of quality of life on the health of older people from a multidimensional perspective. Journal of Aging Research, 2018(May), Article 4086294. https://doi.org/10.1155/2018/4086294
Sadana R., Foebel A. D., Williams A. N., Beard J. R. (2013). Population aging, longevity, and the diverse contexts of the oldest old. Public Policy & Aging Report, 23(2), 18–25. https://doi.org/10.1093/ppar/23.2.18
Scorza P., Masyn K., Salomon J. A., Betancourt T. S. (2018). The impact of measurement differences on cross-country depression prevalence estimates: A latent transition analysis. PLoS One, 13(6), Article e0198429. https://doi.org/10.1371/journal.pone.0198429
Stavrova O. (2019). How much do sources of happiness vary across countries? A review of the empirical literature. KZfSS Kölner Zeitschrift Für Soziologie Und Sozialpsychologie, 71(S1), 429–464. https://doi.org/10.1007/s11577-019-00612-y
Stavrova O., Fetchenhauer D., Schlösser T. (2012). Cohabitation, gender, and happiness: A cross-cultural study in thirty countries. Journal of Cross-Cultural Psychology, 43(7), 1063–1081. https://doi.org/10.1177/0022022111419030
Steinkamp M. W., Kelly J. R. (1987). Social integration, leisure activity, and life satisfaction in older adults: Activity theory revisited. International Journal of Aging & Human Development, 25(4), 293–307. https://doi.org/10.2190/V813-QA3G-6AQC-MWYM
Surkalim D. L., Luo M., Eres R., Gebel K., van Buskirk J., Bauman A., Ding D. (2022). The prevalence of loneliness across 113 countries: Systematic review and meta-analysis. BMJ, 376(February), Article e067068. https://doi.org/10.1136/bmj-2021-067068
Tang Y., Chen T., Zhao Y., Taghizadeh-Hesary F. (2022). The impact of the long-term care insurance on the medical expenses and health status in China. Frontiers in Public Health, 10(May), Article 847822. https://doi.org/10.3389/fpubh.2022.847822
Twenge J. M. (2023). Generations: The real differences between Gen Z, millennials, Gen X, boomers, and silents—and what they mean for America’s future. Simon & Schuster.
Uchida Y., Oishi S. (2016). The happiness of individuals and the collective. Japanese Psychological Research, 58(1), 125–141. https://doi.org/10.1111/jpr.12103
Van Loon A. M., Depla M. F. I. A., Hertogh C. M. P. M., Huisman M., Kok A. A. L. (2023). The disability paradox? Trajectories of well-being in older adults with functional decline. Journal of Aging and Health, 35(1–2), 125–137. https://doi.org/10.1177/08982643221108660
Van Tilburg T., De Jong Gierveld J., Lecchini L., Marsiglia D. (1998). Social integration and loneliness: A comparative study among older adults in The Netherlands and Tuscany, Italy. Journal of Social and Personal Relationships, 15(6), 740–754. https://doi.org/10.1177/0265407598156002
Vidovićová L., Galčanová L., Petrová Kafková M. (2015). The meaning and performance of the grandparenting role among young old Czechs. Czech Sociological Review, 51(5), 761–782. https://doi.org/10.13060/00380288.2015.51.5.213
Vishwakarma D., Gaidhane A., Bhoi S. R. (2023). Depression and its associated factors among the elderly population in India: A review. Cureus, 15(6), Article e41013. https://doi.org/10.7759/cureus.41013
Wang S., Lu T., Sun J., Huang L., Li R., Wang T., Yu C. (2023). Long-term trends in the incidence of depressive disorders in China, the United States, India and globally: A comparative study from 1990 to 2019. Frontiers in Psychology, 13(January), Article 1066706. https://doi.org/10.3389/fpsyg.2022.1066706
Warner D. F., Adams S. A., Anderson R. K. (2019). The good, the bad, and the indifferent: Physical disability, social role configurations, and changes in loneliness among married and unmarried older adults. Journal of Aging and Health, 31(8), 1423–1453. https://doi.org/10.1177/0898264318781129
Yu J., Li J., Cuijpers P., Wu S., Wu Z. (2012). Prevalence and correlates of depressive symptoms in Chinese older adults: A population-based study. International Journal of Geriatric Psychiatry, 27(3), 305–312. https://doi.org/10.1002/gps.2721
Zhang J., Li L. W., McLaughlin S. J. (2022). Psychological well-being and cognitive function among older adults in China: A population-based longitudinal study. Journal of Aging and Health, 34(2), 173–183. https://doi.org/10.1177/08982643211036226
Zivin K., Llewellyn D. J., Lang I. A., Vijan S., Kabeto M. U., Miller E. M., Langa K. M. (2010). Depression among older adults in the United States and England. American Journal of Geriatric Psychiatry: Official Journal of the American Association for Geriatric Psychiatry, 18(11), 1036–1044. https://doi.org/10.1097/JGP.0b013e3181dba6d2
Zivin K., Pirraglia P. A., McCammon R. J., Langa K. M., Vijan S. (2013). Trends in depressive symptom burden among older adults in the United States from 1998 to 2008. Journal of General Internal Medicine, 28(12), 1611–1619. https://doi.org/10.1007/s11606-013-2533-y
Create a link to share a read only version of this article with your colleagues and friends. For more information view the Sage Journals article sharing
page.
Please read and accept the terms and conditions and check the box to generate a sharing link.
Shane D. Burns, PhD, MPH, Population Studies Center, University of Michigan, 426 Thompson St., Room 2098, Ann Arbor, Michigan 48109, USA. Email: [email protected]
Metrics and citations
Metrics
Journals metrics
This article was published in Journal of Aging and Health.
I can access personal subscriptions, purchases, paired institutional access and free tools such as favourite journals, email alerts and saved searches.
