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Choi E, Levy C. Relationship between employment status and reported depressive disorders among older adults in the United States. HPHR. 2023;78. https://doi.org/10.54111/0001/ZZZ2
In response to major demographic shifts around the world, many specialists in a variety of professions have begun to investigate the implications. Some countries have raised their legal retirement age. This article investigated the relationship between depression and retirement of older adults (65 and older) in the United States.
A chi-square test and logistic regression were performed using the data from the Substance Abuse and Mental Health Data Archive.
Results suggested a significant association between employment status and the prevalence of depression among older adults. Compared to unemployed or employed part-time groups, those who were employed full time were more likely to report having depressive disorders (p-Value < 0.05). Additionally, among those who were not in the workforce, students and those in non-competitive employment were less likely to have depressive disorders (p-Value < 0.05).
Depressive disorders were the major mental health concerns for the older adult population. In the age group of 65 and older, those who are in the workforce reported a higher prevalence of depression compared to the unemployed group, including retirees. However, among the unemployed group, retirees were more likely to report having depression compared to students and individuals participating in non-competitive employment. However, this study faced many limitations, including non-inclusive data and unspecified variables. Thus, future studies are needed.
As the legal retirement age increases, communities and institutions should continue to study its potential impact on the well-being of older adults and seek ways to promote healthy aging and elder-friendly communities.
The global demography has been aging rapidly.1 In the United States, the population age 65 or older has been rising since 1920.2 There was a sharp uptake from 2010 to 2020 when baby boomers (people born between 1946 and 1964) started turning 65.2 The most recognized contributing factors to the increased proportion of adults who are 65 or older were declining fertility rates, increasing life expectancy, and aging population cohorts.1 The imbalance in the demography continues; as fertility rates keep declining, fewer people will grow up to join the youth cohort.1 As this pattern keeps up, the U.S. Census Bureau3 has projected that the older adult population cohort will outnumber the younger population cohort by 2034.
With this significant demographic shift, experts have begun to investigate its impact on the workforce and pension system.4 Population aging indicates the shrinking labor force as more workers exit the labor market than enter.1,4 This decline in workforce participation is expected to put stress on economic growth and social security systems due to the imbalance between future tax payers and tax recipients.1,4 In response to these potential challenges, some countries, such as Greece, France, the United Kingdom, and the United States have raised the legal retirement age.1,5,6 According to the United States Social Security Administration,6 an individual can start receiving their Social Security retirement benefits at 62. However, this is not their full benefit retirement age. 6 To be eligible for the full benefit, individuals need to reach their full retirement age, which depends on the year they were born. 6 For instance, for those who were born in 1958, the full retirement age is 66 years and 6 months, and for those who were born in 1960 or later, it would be 67 years.6
Retirement can bring significant changes to multiple aspects of individuals’ lives such as changes to daily routines, social interactions, income, and both mental and physical health.7 Thus, understanding retirement’s impact on health would be crucial to promote healthy aging as multiple countries are on trend of increasing their legal retirement age.1,5,6
This present paper will focus on depression among older adults to further investigate previous studies on the relationship between retirement and depression. Li et al8 found a longitudinal association between retirement and higher risk of depression by performing the meta-analysis on 25 longitudinal studies. Further, another meta-analysis involving 9 articles (n=360) from mainly the United States showed a 28% rate of depression among retirees, suggesting a significant part of the retired population may have depression.9
While there were studies suggesting the negative impact of retirement on mental health,8,9 other studies suggested positive impacts. Handley et al10 studied the impact of retirement on participants’ self-reported physical health, daily functioning, mental health, and satisfaction with life in a rural part of Australia. While the results suggested no significant difference in physical health or everyday functioning between employed and retired participants, the retired participants reported significantly higher scores for mental health and satisfaction with life.10 From Japan, Oshio and Kan11 compared 9283 individuals’ health indicators and behaviors 5 years before and after retirement. They discovered a pattern of increase in leisure-time physical activity and a decrease in psychological distress after the retirement in both male and female participants.11
In response to the increased legal retirement age, its impact on healthy aging should be further investigated. However, there have been few such studies done in the United States. Thus, this paper investigated the potential relationship between retirement and its impact on mental health. The focused area of mental health was depression to further the previous studies indicating the increased risk of depression among retirees.8,9 As part of this study, the mental health diagnosis among older adults in the United States was also explored, in addition to comparing the prevalence of depression among older adults in the United States based on their employment status.
Retirement can bring significant changes to multiple aspects of individuals’ lives such as changes to daily routines, social interactions, income, and both mental and physical health.7 Thus, understanding retirement’s impact on health would be crucial to promote healthy aging as multiple countries are on trend of increasing their legal retirement age.1,5,6
This present paper will focus on depression among older adults to further investigate previous studies on the relationship between retirement and depression. Li et al8 found a longitudinal association between retirement and higher risk of depression by performing the meta-analysis on 25 longitudinal studies. Further, another meta-analysis involving 9 articles (n=360) from mainly the United States showed a 28% rate of depression among retirees, suggesting a significant part of the retired population may have depression.9
While there were studies suggesting the negative impact of retirement on mental health,8,9 other studies suggested positive impacts. Handley et al10 studied the impact of retirement on participants’ self-reported physical health, daily functioning, mental health, and satisfaction with life in a rural part of Australia. While the results suggested no significant difference in physical health or everyday functioning between employed and retired participants, the retired participants reported significantly higher scores for mental health and satisfaction with life.10 From Japan, Oshio and Kan11 compared 9283 individuals’ health indicators and behaviors 5 years before and after retirement. They discovered a pattern of increase in leisure-time physical activity and a decrease in psychological distress after the retirement in both male and female participants.11
In response to the increased legal retirement age, its impact on healthy aging should be further investigated. However, there have been few such studies done in the United States. Thus, this paper investigated the potential relationship between retirement and its impact on mental health. The focused area of mental health was depression to further the previous studies indicating the increased risk of depression among retirees.8,9 As part of this study, the mental health diagnosis among older adults in the United States was also explored, in addition to comparing the prevalence of depression among older adults in the United States based on their employment status.
Peer-reviewed journal articles were retrieved from the Massachusetts College of Pharmacy and Health Sciences’ databases using key terms such as global aging, retirement, physical activity, and mental health among older adults. Studies published before 2014 were excluded from the literature review.
The data used in this research was obtained from the Mental Health Client-Level Data (MH-CLD) 2021. This annual report was generated by the Substance Abuse and Mental Health Services Administration (SAMHSA) and the State Mental Health Agencies (SMHAs). The report contained data such as the number of clients who received publicly funded mental health treatments in 2021 in the United States.12 The data from following states were excluded by SAMHSA due to insufficient data: American Samoa, Federated States of Micronesia, Florida, Guam, Maine, Marshall Islands, Ohio, South Dakota, U.S. Virgin Islands.12
For this research, only limited data collected by SAMHSA were used: age, gender, employment status, reports on depressive disorder and more. (Table 1) These selected data were analyzed by the statistical software, Stata, 18.0 BE-Basic Edition. Among the total participants in SAMHSA, 5.80% (377,581) were 65 years of age and older (146,297 males, 228,965 females, and 2,319 unknowns). (Table 2) A Pearson’s chi-squared test and logistic regression were performed to compare prevalence of depressive disorders among the two groups, retired vs. non-retired, among the population 65 years of age and older. Any missing and invalid data were excluded from the data analyzing process.
Table 1. Demographics
Sex | Frequencies (Percent) |
Male | 146,297 (38.99) |
Female | 228,965 (61.01) |
Total | 375,262 (100.00) |
Race | Frequencies (Percent) |
American Indian/ Alaska Native Asian | 4,790 (1.43) |
Asian | 8,595 (2.56) |
Black or African American | 61,032 (18.19) |
Native Hawaiian or Other Pacific Island White | 682 (0.20) |
White | 238,959 (71.23) |
Some other race along/ two or more races | 21,410 (6.38) |
Total | 335,468 (100.00) |
Marital status | Frequencies (Percent) |
Never married | 80,305 (33.60) |
Now married | 56,405 (23.60) |
Separated | 14,914 (6.24) |
Divorced, windowed | 87,350 (36.55) |
Total | 238,974 (100.00) |
Education | Frequencies (Percent) |
Special education | 2,108 (1.04) |
0 to 8 | 26,601 (13.12) |
9 to 11 | 26,303 (12.97) |
12 (GED) | 91,377 (45.05) |
More than 12 | 56,438 (27.83) |
Total | 202,827 (100.00) |
Number of mental health diagnoses reported | Frequencies (Percent) |
0 | 58,948 (15.61) |
1 | 204,754 (54.23) |
2 | 97,274 (25.76) |
3 | 16,605 (4.40) |
Total | 377,581 (100.00) |
Mental health diagnosis | Frequencies |
Trauma- and stressor-related disorders | 27,781 (8.72) |
Anxiety disorders | 32,521(10.21) |
Attention deficit/ hyperactivity disorder | 976(0.31) |
Conduct disorders | 399(0.13) |
Delirium, dementia | 9,877(3.10) |
Bipolar disorders | 34,326(10.77) |
Depressive disorders | 101,753(31.93) |
Oppositional defiant disorders | 84(0.03) |
Pervasive developmental disorders | 274(0.09) |
Personality disorders | 2,897(0.91) |
Schizophrenia or other psychotic disorder | 73,298(23.00) |
Alcohol or substance use disorders | 10,056(3.16) |
Other disorders/ conditions | 24,391(7.65) |
Total | 318,633(100.00) |
Employment status | Frequencies |
Full-time | 4,140 (2.85) |
Part-time | 4,305(2.96) |
In working force (full-time and part-time was not recorded) | 2,386(1.64) |
Unemployed (actively looking for jobs) | 18,292(12.60) |
Not in labor force (had not been looking for jobs in the past 30 days) | 116,077(79. 94) |
Total | 145,200 (100.00) |
Employment Reasons | Frequencies |
Retired, disabled | 85,895 (74.00) |
Student | 417 (0.36) |
Homemaker | 1,614 (1.39) |
Shelter/non-competitive employment | 692 (0.60) |
Other | 27,459 (23.66) |
Total | 116,077 (100.00) |
Depressive disorder | Frequencies |
Not reported | 257,194 (68.12) |
Reported | 120,387 (31.88) |
Total | 377,581 (100.00) |
Adapted from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112
This table includes data on gender, race, marital status, educational attainment, number of mental health diagnoses, current first mental diagnosis during the reporting year, employment status, reasons for not being in labor force, and total number of reported depressive disorders, including the first, second, or third mental health diagnosis distribution among 65 years or older, excluding missing Missing/unknown/not collected/ invalid data.
Table 2. Reported age groups from Mental Health Client-Level Data (MH-CLD), 2021.
Age groups | Frequencies | Percent |
0-11 years | 810,055 | 12.45 |
12-14 years | 466,637 | 7.17 |
15-17 years | 476,192 | 7.32 |
18-20 years | 318,318 | 4.89 |
21-24 years | 383,151 | 5.89 |
25-29 years | 576,483 | 8.86 |
30-34 years | 587,924 | 9.03 |
35-39 years | 524,808 | 8.06 |
40-44 years | 446,163 | 6.85 |
45-49 years | 388,432 | 8.86 |
50-54 years | 406,019 | 6.24 |
55-59 years | 413,454 | 6.35 |
60-64 years | 327,152 | 5.03 |
65 years and older | 377,581 | 5.80 |
Missing/unknown/ invalid | 6,656 | 0.10 |
Total | 6,509,025 | 100.00 |
Adapted from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112
Table 3. Pearson’s chi-squared test: reported depressive disorder vs. Gender, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older.
Depressive disorder reported | Sex | Total | |
Male | Female | ||
Disorder not reported | 107,625 643.4 | 147,905 411.1 | 255,530 1054.5 |
Disorder Reported | 38,672 1373.1 | 81,060 877.3 | 119,732 2250.5 |
Total | 146,297 2016.5 | 228,965 1288.4 | 375,262 3304.9 |
Pearson chi2(1) = 3.3e+03 | Pr = 0.000v | ||
Derived from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112, using Stata, 18.0 BE-Basic Edition
Table 4. Pearson’s chi-squared test: reported depressive disorder vs. Race, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older.
Depressive disorder reported | Race | Total | ||||||
American | Asian | Black or African American | Native Hawaiian | White | Some other | |||
Disorder not reported | 3,263 0.0 | 5,483 23.2 | 44,703 239.6 | 410 6.3 | 160,379 32.4 | 14,135 13.3 | 228,373 314.7 | |
Disorder Reported | 1,527 0.0 | 3,112 49.4 | 16,329 510.8 | 272 13.5 | 78,580 69.0 | 7,275 28.3 | 107,095 671.1 | |
Total | 4,790 0.0 | 8,595 72.6 | 61,032 750.4 | 682 19.9 | 238,959 101.4 | 21,410 41.6 | 335,468 985.8 | |
Pearson chi2 (5) = 985.8475 | Pr = 0.000 | |||||||
Derived from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112, using Stata, 18.0 BE-Basic Edition
Table 5. Pearson’s chi-squared test: reported depressive disorder vs. Employment status, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older.
Depressive disorder reported | Competitive employment status (aged 16 years and older) | Total | ||||
Full-time | Part-time | Employed (full-time or part-time) | Unemployed | Not in labor force | ||
Disorder not reported | 2,324 | 2,656 | 1,614 | 11,939 | 71,646
| 90,179 |
Disorder Reported | 1,816 | 1,649 | 772 | 6,353 | 44,431
| 55,021 |
Total | 4,140 | 4,305 | 2,386 | 18,292 | 116,077
| 145,200 |
Pearson chi2 (4) = 179.1220 | Pr=0.000 | |||||
Derived from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112, using Stata, 18.0 BE-Basic Edition
Table 6. Binary logistic regression test with a baseline = full-time: reported depressive disorder vs. Employment status, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older
| Number of obs = 145,200 | |||||
LR chi2 (4) = 179.61 | ||||||
Prob > chi2 = 0.0000 | ||||||
Log likelihood = -96256.076 | Pseudo R2 = 0.0009 | |||||
Depressive disorder reported | Odds ratio | Std. err. | Z | P > | z | | [95% conf. | interval] |
Employment status |
| |||||
Part-time | 0.7945347 | 0.0352104 | -5.19 | 0.000 | 0.7284357 | 0.8666316 |
Employed (full-time or part-time) | 0.6121164 | 0.03294 | -9.12 | 0.000 | 0.5508433 | 0.6802053 |
Unemployed | 0.680975 | 0.0238061 | -10.99 | 0.000 | 0.6358786 | 0.7292697 |
Not in labor force | 0.7936233 | 0.0253142 | -7.25 | 0.000 | 0.7455275 | 0.8448219 |
_cons | 0.7814114 | 0.0244739 | -7.88 | 0.000 | 0.7348859 | 0.8308823 |
Baseline = full-time | ||||||
Derived from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112, using Stata, 18.0 BE-Basic Edition
Table 7. Pearson’s chi-squared test: reported depressive disorder vs. detailed Not in work force status, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older
Depressive disorder reported | Competitive employment status (aged 16 years and older) | Total | ||||
Retired | Student | Homemaker | Sheltered | Other | ||
Disorder not reported | 52,244 | 317 | 881 | 551 | 17,653 | 71,646 |
Disorder Reported | 33,651 | 100 | 733 | 141 | 9,806 | 44,431 |
Total | 85,895 | 417 | 1,614 | 692 | 27,459 | 116,077 |
Pearson chi2 (4) = 270.6875 | Pr = 0.000 | |||||
Derived from Substance Abuse and Mental Health Services Administration. Mental Health Client-Level Data (MH-CLD) 202112, using Stata, 18.0 BE-Basic Edition
Table 8. Binary logistic regression test with a baseline = Retired/disabled: reported depressive disorder vs. Detailed Not in work force status, excluding missing Missing/unknown/not collected/ invalid data. – Among 65 years or older
| Number of obs = 145,200 | |||||
LR chi2 (4) = 179.6 | ||||||
Prob > chi2 = 0.0000 | ||||||
Log likelihood = -77097.148 | Pseudo R2 = 0.0018 | |||||
Depressive disorder reported | Odds ratio | Std. err. | Z | P > | z | | [95% conf. | interval] |
Detailed ‘not in labor force’ category |
|
|
|
|
|
|
Student | 0.4897555 | 0.0562759 | -6.21 | 0.000 | 0.3909949 | 0.613462 |
Homemaker | 1.291714 | 0.0652052 | 5.07 | 0.000 | 1.170033 | 1.42605 |
Non-competitive employment | 0.3972908 | 0.0375979 | -9.75 | 0.000 | 0.3300308 | 0.4782583 |
Other | 0.8624061 | 0.0124224 | -10.28 | 0.000 | 0.8383992 | 0.8871004 |
_cons (estimates baseline odds) | 0.6441122 | 0.0045022 | -62.93 | 0.000 | 0.6353482 | 0.6529972 |
Baseline = Retired | ||||||
Among 377,581 subjects who were 65 or older, 31.9% (120,387) reported having a depressive disorder. 15.6% (58,948) reported not having any mental health diagnoses while 54.2% (204,754) reported having 1 mental health diagnosis and 25.8% (97,274) reported having 2 mental health diagnoses. Depressive disorders made up the highest percentage of the client’s first mental diagnosis, at 31.9%, (101,753), followed by Schizophrenia or other psychotic disorders, at 23.0% (73,298). (Table 1)
Excluding missing or invalid data, 145,200 subjects’ employment status was studied. The percentages for full-time and part-time were 2.85% (4,140) and 3.96% (4,305), respectively. 12.6% (18,292) were unemployed while actively looking for jobs. (Table 1) The majority, 79.9% (116,077), were not in the labor force, indicating that they have not been actively looking for jobs in the past 30 days. (Table 1)
For those who were not in the labor force, 74.0% (85,895) was retired or disabled and 23.7% (27,459) of “other”. The rest were 1.39% (1,614) of homemaker, 0.60% (692) of shelter/non-competitive employment, and 036% (417) of student. (Table 1)
The Pearson’s chi-squared test was performed to test relationships between reported depressive disorder and subjects’ gender and race. The results showed a p-value of less than 0.05. (Table 3,4) The Pearson’s chi-squared test was performed to test a potential relationship between employment status and reported depressive disorder. The results yielded a p-value less than 0.05, suggesting a statistically significant relationship between employment status and reported depressive disorders. (Table 5) Further, a binary logistic regression test was performed to investigate the direction of the relationship between employment status and reported depressive disorder. The odds ratio for full-time (a constant), part-time, employment type not differentiated, unemployed, and not in the labor force were 0.78, 0.79, 0.61, 0.68, and 0.79 in the order given. For all variables, the p-values were less than 0.05. (Table 6)
The Pearson’s chi-square test was done to study a potential relationship between detailed not-in-the-work force status and reported depressive disorder. The results showed a p-value less than 0.05, indicating a statistically significant relationship between detailed not in the labor force status and reported depressive disorder. (Table 7) A binary logistic regression test was performed to investigate the direction of the relationships. The odds ratio for constant, retired/disabled, was 0.64 with a p-value less than 0.05. The odds ratios for other variables were student (0.49), homemaker (1.29), shelter/non-competitive employment (0.40), and other (0.86). The P-values for all variables were less than 0.05. (Table 8)
Results suggested that depressive disorders are major mental health concerns among the older adult population and indicated that most clients who were 65 or older were not in the work force, and the primary reason was retirement and disability. When the impact of employment status on mental health of 65 or older clients studied, a significant relationship was observed. Those who held full-time jobs were significantly more likely to have depressive disorders when compared to those who were part-time, unspecified employed (full/part time), unemployed, and not in the labor force. Further, there was a significant association between reported depressive disorders and detailed not-in-the-workforce status. Compared to the retired/disabled group, subjects in groups of students, sheltered/non-competitive employment, and “others” were less likely to report having depressive disorders. However, the homemaker group was more likely to report having depressive disorders.
Unlike the previous study suggesting a higher risk of depression among retirees,8,9 the results of this study yielded the opposite conclusion. Those who retired were less likely to report having depressive disorders. These findings may agree with studies done by Handley et al10 and Oshio and Kan11 reporting higher scores for mental health and a decrease in psychological distress after their retirement.
According to the significant relationship between the impact of employment status and mental health observed in this study, the countries attempt to increase the legal retirement age may not be effective methods to prepare for challenges related to aging demographics. Older adults 65 or older who held full-time jobs were more likely to report having depressive disorders than other forms of employment or unemployment. Thus, raising the legal retirement age may relieve the financial aspect of the aging demographic, but it would not be an ideal approach when the goal is to promote healthier aging along with a lively economy. A significant difference within the not-in-the-workforce status highlighted the importance of establishing socially engaging communities for elders. Those who were not actively looking for jobs showed a significantly less likelihood of reporting depressive disorders compared to those with full-time employment. However, looking closely at the subgroups of not-in-the-workforce, those who showed regular social and cognitive engagement, such as student or shelter/non-competitive employment, were significantly less likely to report having depressive disorders. Therefore, this may suggest that building more engaging communities for elders could potentially play an important role in keeping the older adult demographic healthier.
The data was retrieved from the Mental Health Client-Level Data (MH-CLD) 2021. The subjects of MH-CLD were those who had received mental health treatment services that were affiliated with state mental health agencies (SMHAs). Thus, the data used for this study did not include those who sought private mental health resources. Additionally, the data set did not contain populations who were 65 or older and had not needed any mental health treatments.
A variable such as “other” had not been specified but showed statistical significance when studying the relationship between detailed-not-in-the-workforce and reported depressive disorders. Further, as the data set did not contain other factors such as income level, chronic conditions, and social isolation, potential confounding variables had not been considered.
Future research should be conducted to further investigate the relationship between the employment status, race, and gender of older adults and their mental health. Significant relationships were detected between depressive disorders and race and gender. However, the directionality had not been studied. The new research should include a data set of the overall older adults’ population in the United States, including both state-run and privately funded mental health facilities and those who have not yet needed any mental health resources. Future research should investigate other cofounding variables that may influence the mental health of the targeted population, such as their income and education level, overall health, conditions of their workplaces, and social connections.
Additionally, the data set categorized homemakers as not in the labor force. Although the homemakers may not be financially compensated for their work, it could be essential to investigate their role and its impact on their mental health by further studying it in relation to their work hours, expected physical and mental demands, and social life.
This paper does not discuss a potential relationship between depression and increased risk of chronic illness. Future research should investigate the potential relationship and how this relationship would impact the nation’s health care spending.
The world has been experiencing a significant shift in demography.1 To prepare for potential challenges from this phenomenon, countries began to raise the legal retirement age 1,5 Yet, there seemed to be insufficient data available on how this change may affect the well-being of the older adult population. Delaying retirement could potentially put older adults in a vulnerable position, forcing them to prioritize work over their overall health. Thus, this paper investigated the potential relationship between employment status and the mental well-being of older adults. The findings from this study suggested that increasing the legal retirement age may not be the optimal solution to combat the economic challenges while simultaneously promoting healthier communities. According to this study, those who were 65 or older with full-time jobs were more likely to report having depressive disorders than those who had part-time jobs or were not in employment. Furthermore, among those who were not in the workforce, people who had other commitments, such as being a student or involved in a non-competitive work force, were less likely to report having depressive disorders, except for the homemakers. Future research is necessary, but these findings propose that the establishment of an elder-friendly community, where society fosters social interaction and ongoing education for elders, could be beneficial. For this reason, a continuous collaborative effort should be made to assure health equity among the growing older adult population.
The author(s) have no relevant financial disclosures or conflicts of interest.
Eunji Choi obtained a Master of Public Health from the Massachusetts College of Pharmacy and Health Sciences in May 2024. Her academic interests include population aging and substance use disorders.
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