Abstract
Despite frequent reports of mental health needs among older women with cancer, depressive symptoms often go unrecognized and untreated, particularly in socially vulnerable survivors. Here, we examined associations of sociodemographic factors and social limitations with depressive symptoms from pre-diagnosis to post-diagnosis in older women diagnosed with breast or gynecological cancer. Using the Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey (SEER-MHOS) linked dataset, we used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between sociodemographic factors (race, ethnicity, marital status, rurality) and social limitations (i.e., health interfering with social activities) on depressive symptoms in women aged ≥65 years with breast or gynecologic cancer (n = 1,353). Most participants had breast cancer (82.0%), stage I-II cancer (85.8%), received surgery for their cancer (94.8%), and radiation treatment (50.6%). Prior to diagnosis, 11.8% reported depressive symptoms, which nearly doubled to 22.4% at follow-up. Participants were 2.7 times more likely of reporting depressive symptoms after cancer diagnosis compared with pre-cancer diagnosis (95%CI: 2.10–3.48). Race, ethnicity, rurality, marital status, and social interference were significantly associated with an increased risk of depressive symptoms after cancer diagnosis than before their cancer diagnosis (p < 0.05). In summary, depressive symptoms increased following a cancer diagnosis. Our results suggest potential avenues for intervention that could lead to reduced depressive symptoms among older female cancer survivors.
Introduction
In 2023, an estimated 67% of the 18+ million cancer survivors living in the United States were older adults (≥65 years) (Siegel et al., Citation2023). By 2040, the cancer survivor population will increase to 26.1 million, of which an estimated 73% will be older adults (Bluethmann et al., Citation2016; Smith et al., Citation2009). Additionally, there is a growing population of older breast and gynecologic cancer survivors, accounting for approximately 40% of new cancer diagnoses in U.S. women (Siegel et al., Citation2023).
Despite this increase, there continue to be unmet needs among older female cancer survivors, with a substantial need for attention to poor mental health (Burg et al., Citation2015). Prior findings indicate the prevalence of depressive symptoms in cancer survivors is 3- to 4-fold higher compared to the general population. Approximately 15–32% of older women receiving cancer treatment report depressive symptoms (Klapheke et al., Citation2020; Philip & Merluzzi, Citation2016), which can be long-lasting, with 14–16% of older cancer survivors reporting depressive symptoms 8–10 years post-diagnosis (Bernardo et al., Citation2022; Paek et al., Citation2021; Reyes-Gibby et al., Citation2012). Depressive symptoms, as well as major depressive disorder, can go undetected and untreated in older adults due to comorbidity, cognitive impairment, and difficulty in differentiating affective (guilt, sadness) and somatic complaints (fatigue, difficulties with memory) (Clark et al., Citation2016; Cohen, Citation2014; Parpa et al., Citation2015). Notably, the prevalence of depressive symptoms is higher among older women compared with older men (Cheruvu & Chiyaka, Citation2019; Kiely et al., Citation2019). Older female cancer survivors’ depressive symptoms are understudied yet warrant additional examination.
Previous cross-sectional studies have reported that demographic (age, sex, education, marital status, home ownership), social (social support, health interfering on social activity) and health factors (comorbidities, functional limitations) were associated with depressive symptoms among older cancer survivors (Buscariollo et al., Citation2019; Lee et al., Citation2023; Pamoukdjian et al., Citation2017). However, these findings are heterogeneous and often inconclusive (Bai et al., Citation2021; Paek et al., Citation2021). A limited number of longitudinal studies (Avis et al., Citation2013; Jones et al., Citation2015; Leach et al., Citation2017) have examined changes in depressive symptoms among older cancer survivors during treatment and/or life after cancer treatment. Leach et al. (Citation2017) found that cancer survivors endorsed at least one depressive symptom at the 2-year follow-up. However, demographic and social correlates of changes in risk from baseline to follow-up were not explored.
An unexplored topic among older female cancer survivors is how demographic factors and social limitations are associated with changes in depressive symptoms. Previous cross-sectional studies have noted differences in depressive symptoms among older female cancer survivors by race and ethnicity (Klapheke et al., Citation2020; Parajuli et al., Citation2021), rurality (Andrykowski & Burris, Citation2010; Burris & Andrykowski, Citation2010), and marital status (Lee et al., Citation2023; Parajuli et al., Citation2021), yet these were not examined longitudinally. Examining differences in the prevalence of depressive symptoms and correlating factors may help support clinical approaches to support psychosocial functioning, particularly among those at an increased risk of depressive symptoms. Thus, this study examined associations of sociodemographic factors and social limitations associated with changes in depressive symptoms from pre-diagnosis to post-diagnosis among older women diagnosed with a breast or gynecologic cancer.
Methods
Dataset and study population
Data were derived from the Surveillance, Epidemiology and End Results (SEER)-Medicare Health Outcomes Survey (MHOS) combined dataset (Ambs et al., Citation2008). Briefly, SEER-MHOS provides detailed cancer registry data (e.g., cancer type, stage, histology, and diagnosis date) from selected U.S. regions/states, as well as self-administered, longitudinal survey data assessing physical and mental functioning, smoking status, and chronic medical conditions. Medicare beneficiaries were included in this analysis if they met the following criteria: female, 65 years or older at the time of cancer diagnosis, had exactly one breast or gynecologic (i.e., ovarian, endometrial, cervical, vulvar, or vaginal) cancer, had at least one complete MHOS datapoint between 1998 and 2017 and within 5 years of their cancer diagnosis, and had at least one survey before diagnosis and one survey after diagnosis.
Outcome of interest: Depressive symptoms
Depression status was evaluated at pre-cancer and post-cancer diagnosis. A participant had pre-cancer depressive symptoms if their MHOS survey indicated depressive symptoms at least once before cancer diagnosis, and a participant had post-cancer depression if their MHOS survey indicated depressive symptoms at least once after cancer diagnosis. As demonstrated by Klapheke et al. (Citation2020), participants who met either of the two criteria were classified as having depressive symptoms: (1) any affirmative response (e.g., several days, more than half the days, or nearly every day) to either “little interest or pleasure in doing things” or “feeling down, depressed or hopeless,” or (2) an affirmative response (e.g., yes) to both “depression much of the time in past year” and “depression most of the time for two years,” as well as any affirmative response (e.g., some of the time, most of the time, or all of the time) to “downhearted and blue.” Participants who did not respond to the questions (1) “little interest or pleasure in doing things” and “feeling down, depressed or hopeless” and (2) “depression much of the time in past year,” “depression most of the time for two years”, and “downhearted and blue” were coded as missing depression status. Only participants with non-missing values for depression at pre- and post-cancer diagnosis were included in this study.
Variables of interest: Independent variables
This study had four main independent variables of interest: race and ethnicity, marital status, rurality, and social interference. Since marital status, rurality, and social interference did not have constant values throughout the study period, the first non-missing value after cancer diagnosis was assumed for these independent variables. Race and ethnicity were categorized as Asian/Pacific Islander, Black/African American, Hispanic, Non-Hispanic White, American Indian/Alaskan Native (AIAN), and other/multi-race. American Indian or Alaskan Native was collapsed into the other/multi-race category due to small cell sizes. Marital status included currently married, never married, widowed, separated, and divorced and was dichotomized as currently married vs. the remaining categories of marital status. To assess rurality, rural-urban continuum codes based on county of residence were utilized (United States Department of Agriculture, Citation2021). Three different levels of metropolitan areas (i.e., populations ≥1 million, 250,000–1 million, and <250,000) were analyzed, as well as areas classified as non-metropolitan. For social interference, participants were specifically asked how frequently physical health or emotional problems interfered with social activities with the following possible responses: “all of the time”; “most of the time”; “some of the time”; “a little of the time”; and “none of the time.” Other variables in this study included cancer treatment (e.g., radiation, surgery), cancer type, age at diagnosis, number of comorbidities, year of diagnosis, educational attainment, annual income, comorbidity burden, and American Joint Committee on Cancer (AJCC) stage. The first value for educational attainment and comorbidity burden after cancer diagnosis was used in analyses.
Statistical analysis
Descriptive statistics of patient demographic and clinical characteristics included the median and interquartile range (IQR) for continuous variables, frequencies, and percentages for categorical variables. Multivariable-adjusted logistic regression was used to assess odds ratios (ORs) and 95% confidence intervals (CIs) for the association of time (pre-cancer vs. post cancer) and depressive symptoms (no vs. yes) in the overall study population and stratified by race/ethnicity, marital status, social interference, and rurality. Significance was evaluated at the 0.05 level, and all analyses were performed using SAS 9.4. Per the SEER-MHOS data use agreement, variables with cell sizes less than 11 were collapsed in the descriptive tables, however, multivariable analyses included variables as previously described.
Results
A total of 1,353 women with breast or gynecologic cancer >65 years old were included in this study. Median age at diagnosis was 74 (IQR: 70–79) and the majority were non-Hispanic White (71.7%) and had a high school education or higher (77.3%). Most participants had breast cancer (82.0%), stage I-II cancer (85.8%), received surgery for their cancer (94.8%), and radiation treatment (50.6%). The median length of time between the last pre-cancer survey and cancer diagnosis was shorter in patients who reported depressive symptoms (median: 10, IQR: 5–19), and the median length of time from cancer diagnosis to the next post-cancer survey was slightly longer in subjects with depression (median: 13, IQR: 7–20) ().
Table 1. Sample demographic and clinical characteristics by depressive symptoms before and after cancer diagnosis.
Prior to the cancer diagnosis, 11.8% of the sample were classified as having depressive symptoms (). The majority of women who reported depressive symptoms before cancer diagnosis were non-Hispanic White (62.5%), not married or had unknown marital status (64.4%), had their health interfering on their social activities “most” or “some of the time” (54.4%), or lived in metropolitan areas with ≥1 million people (57.5%). Among participants who reported depressive symptoms before diagnosis (n = 160), 65% (n = 104) reported depressive symptoms post-diagnosis.
Table 2. Frequency distributions of primary independent variables according to depressive symptoms measure before cancer diagnosis.
After cancer diagnosis, 22.4% of the sample reported depressive symptoms (). Most individuals who reported depressive symptoms after cancer diagnosis were non-Hispanic White (63.7%), not married or had unknown marital status (66.3%), had their health interfering on their social activities “most” or “some of the time” (52.5%), or lived in metropolitan areas with ≥1 million people (55.4%).
Table 3. Frequency distributions of primary independent variables according to depressive symptoms measure after cancer diagnosis.
Overall, participants were 2.7 times more likely to report depressive symptoms after cancer diagnosis compared with pre-cancer diagnosis (95%CI: 2.10–3.48) (). While not statistically significant, the odds of depressive symptoms post- versus pre-cancer diagnosis was highest among participants who identified as other/multi-race (OR: 5.61, 95%CI: 0.80–39.21) and the second highest odds ratio was among Asian or Pacific Islanders (OR: 3.44, 95%CI: 1.54–7.66). Participants who identified as Black, non-Hispanic White, or Hispanic had similar odds ratios, ranging from 2.43 to 2.64. Those who were never married, divorced, separated, or widowed had 3 times higher odds of depression after cancer diagnosis (95%CI: 2.12–4.01), while those who were married had around 2.5 times higher odds of depression after cancer diagnosis (95%CI: 1.59–3.58). Odds ratios across levels of social interference ranged from 2.66 to 3.40, where the lowest odds ratio was among those who did not experience social interference (95%CI: 1.51–4.72) and the highest odds ratio was among those who experienced social interference most of the time (95%CI: 1.86–6.23). Lastly, rurality is an important factor regarding post-cancer depressive symptoms. Specifically, participants residing in metropolitan areas with populations greater than 1 million (OR: 2.62, 95%CI: 1.88–3.65) or between 250k − 1 million (OR: 2.47, 95%CI: 1.55–3.92) had similar odds of post- versus pre-cancer depressive symptoms. Among the smaller (<250k) metropolitan area and non-metropolitan areas, the odds ratios increased to 3.56 (95%CI: 1.59–7.99) and 4.02 (95%CI: 1.28–12.59), respectively. Online Supplemental Tables 1–3 demonstrate that controlling for time did not have a meaningful impact on the odds of depressive symptoms post- versus pre-cancer diagnosis.
Table 4. Adjusted ORs comparing the odds of depressive symptoms post- versus pre-cancer diagnosis in the overall study population and stratified by race/ethnicity, marital status, social interference, and rurality.
Discussion
This study examined how sociodemographic factors and social limitations were associated with changes in depressive symptoms from pre-diagnosis to post-diagnosis among older women diagnosed with a breast or gynecologic cancer. Prior to diagnosis, 11.8% of the sample reported depressive symptoms, which nearly doubled to 22.4% at follow-up. This prevalence falls within the broad range of reported depressive symptoms rates (7.3%–49% (Harrison et al., Citation2011; Brandenbarg et al., Citation2019; Hoffman et al., Citation2009; Frazzetto et al., Citation2012; Zhang et al., Citation2021) among older female cancer survivors. The observed increase in depressive symptoms, especially years after their diagnosis, demonstrates the importance of routine depression screening by oncology and primary care providers that treat older cancer survivors. This study identified several sociodemographic factors (e.g., race and ethnicity, social interference) associated with depressive symptoms that may help identify survivors at increased risk for depressive symptoms and facilitating supportive care.
Older women who identified themselves as Asian, Black, Hispanic, and non-Hispanic White had significantly higher odds of depressive symptoms after cancer diagnosis than before their cancer diagnosis. Differences in depressive symptoms by race and ethnicity have been found among older adults in the general population. Abrams and Mehta (Abrams & Mehta, Citation2019) found that older adults from minoritized racial and ethnic groups compared to non-Hispanic White older adults exhibited higher depressive symptoms, yet those differences greatly narrowed among their 76–90 year age group. The current study observed that older women who identified themselves as Asian or Pacific Islander had a significantly higher risk of depressive symptoms after cancer diagnosis than before their cancer diagnosis. A nationally representative study of U.S. older adults also found that older Asian women reported a higher prevalence of depressive symptoms compared to their non-Hispanic White peers (Hooker et al., Citation2018). Potential reasons include factors related to their immigration experiences as well as reported lower use of mental health services and lower use of prescription anti-depressants than their non-Hispanic White counterparts (Sorkin et al., Citation2011). In a cancer context, there is a paucity of literature on the role of race and ethnicity on depressive symptoms among older cancer survivors. Few studies found minority race and ethnicity as a correlate (Bevilacqua et al., Citation2018; Clark et al., Citation2016) of depressive symptoms among older cancer survivors, though few have examined the relationship (Cohen, Citation2014; Pamoukdjian et al., Citation2017, Lee et al., Citation2023, Jones et al., Citation2015, Cook et al., Citation2018, Alobaidi et al., Citation2020). In a longitudinal analysis of older cancer survivors, Leach et al. (Citation2017) found that non-Hispanic White survivors reported significantly higher cancer-related symptom management compared to members of minoritized racial and ethnic groups. However, the mean scores were on the lower end of the scale (1.2 and 1.4 out of 4), denoting some perceived cancer-related physical and psychological symptom management in both non-Hispanic White survivors and non-White survivors, respectively. The lack of significant results among older women who identified themselves as an other/multi-race may be due to the small sample size in this group. Future research would benefit from longitudinal exploration of the role of race and ethnicity on the mental health of cancer survivors by using large datasets that are representative of the diverse older cancer survivor population (e.g., All of Us dataset).
Participants who lived in rural settings had significantly higher odds of depressive symptoms after cancer diagnosis than before their cancer diagnosis. Many studies (Andrykowski et al., Citation2014; Kim et al., Citation2022; Moss et al., Citation2021; Naughton & Weaver, Citation2014; van der Kruk et al., Citation2022), but not all (Purtle et al., Citation2019; Sun et al., Citation2022), have found significantly poorer mental health among rural cancer survivors than among urban survivors. This finding suggests evidence of rural disparities in the mental health among older cancer survivors. Older adults living in rural areas have barriers to accessing mental health services, including access to affordable care, availability of mental health providers, transportation, long distances to mental health services, limited access to cancer survivor support groups, and difficulty navigating the health care system (Brenes et al., Citation2015). The current literature using the SEER-MHOS dataset to explore rurality, urbanicity, and depressive symptoms is limited. Paek et al. (Citation2021)studied the prevalence and correlates of depressive symptoms among older breast cancer survivors within the SEER-MHOS dataset yet did not examine how rurality is associated with depressive symptoms. Two studies using the SEER-MHOS dataset examined rural-urban differences in quality of life for older breast, colorectal, lung, and prostate cancer survivors. Moss et al. (Citation2021) found differences by rurality, with some differences pronounced in rural areas while Burrell and colleagues (Burrell et al., Citation2023) did not find significant rural–urban differences in quality of life among older colorectal cancer survivors. Overall, the results of this study indicate the continued need to provide supportive care to rural-dwelling older cancer survivors to improve their mental well-being. Examining potential differences by rurality in access to mental health services, coping strategies, and social support is warranted to target interventions and resources.
Risk of depressive symptoms after cancer diagnosis was higher before cancer diagnosis among women who are married and unmarried. However, the higher risk was more pronounced among those older women who were unmarried rather than married (2.9 and 2.4 times, respectively). This finding is supported in the literature that demonstrated unmarried older adults with cancer were predisposed to depressive symptoms compared to their married counterparts (Lee et al., Citation2023). However, the risk of depressive symptoms over time by marital status was not examined among older female cancer survivors. Undoubtedly, marital status and, more broadly, social support is essential to the health and well-being of older cancer survivors. Additional mixed methods approaches would benefit to delve into this finding and should consider quality of social support, changes in social networks, types of social support (e.g., informational, emotional) given by social network members, and sources for informal and formal social support (e.g., support groups, religion-based, medical center-based).
Health inference on social functioning was also associated with the risk of depressive symptoms after cancer diagnosis. However, all levels of social interference, including no interference, were associated with higher risk of depressive symptoms after cancer diagnosis. This inconclusive result should be further examined in the areas of physical functioning and the aforementioned elements of social support and networks. An older cancer survivor’s social functioning and social support has consistently been associated with physical and mental well-being, reduced frailty, and longevity (Kadambi et al., Citation2020; Koll et al., Citation2021; Pinquart & Duberstein, Citation2010; Utley et al., Citation2022). Given social functioning’s importance reported here and within the literature, clinicians and researchers could implement strategies including individual and group activities, animal assisted therapy, patient navigation, peer support, and social media groups to maintain older adults’ social health throughout survivorship (Leow et al., Citation2021).
Study limitations
The large sample size and relative representativeness of the population were strengths of the study. We acknowledge several study limitations that may impact the generalizability of the findings. First, survivor bias is inherent in the SEER-MHOS dataset, which may manifest in a healthier sample reporting lower depressive symptoms. Depressive symptoms were assessed by a two-item question, which is not a measure of clinical depression. Sample sizes of older women identifying themselves as AIAN and other/multi-race were small as were the sample sizes of rural and smaller urban populations, limiting generalizability. Future research should explore the associations of sociodemographic variables and depressive symptoms before and after cancer diagnosis with greater representation of members of vulnerable populations (e.g., low-income individuals, immigrants, and sexual and gender minorities).
Conclusions
This study found that race and ethnicity, marital status, social interference, and rurality are significant correlates of the change in risk of depressive symptoms among older women pre- and post-cancer diagnosis. Results indicated that prevalence of depressive symptoms increased over time within this population. These results suggest specific focus areas of intervention that could potentially lead to reduced depressive symptoms among older female cancer survivors.
Ethics statement
Individuals who participate in the MHOS survey have provided informed consent. SEER-MHOS linked data are a limited data set exempt from additional requirements of obtaining informed consent by the Health Insurance Portability and Accountability Act of 1996. As SEER-MHOS is considered a limited data set, requiring investigators to sign a data use agreement prior to use, this analysis did not require institutional review board approval (https://healthcaredelivery.cancer.gov/seer-mhos).
Informed consent
All participants provided informed consent.
Supplemental Tables 06DEC2023.docx
Download MS Word (18.7 KB)Acknowledgment
This study used data from the SEER-MHOS linked data resource. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute; the Centers for Medicare & Medicaid Services; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-MHOS database.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
This study used data from the SEER-MHOS linked data resource. Restrictions apply to the availability of these data, which were used under license for this study. Data are available with the permission of SEER-MHOS. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute; the Centers for Medicare & Medicaid Services; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-MHOS database.
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References
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