Poor mental health days and depressive disorders by informal cancer patient caregiver status: BRFSS 2022-23

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Ward, John R. Blosnich, Victoria Champion This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9181837/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Purpose: Informal caregivers (i.e., caregivers) of cancer patients are increasing, significantly influencing patient outcomes. Caregivers face mental health issues such as depression and anxiety and factors related to caregiver burden. This study sought to elucidate whether the mental health of cancer caregivers differs from that of the general population. Methods: Data from 2022 and 2023 Behavioral Risk Factor Surveillance Surveys (BRFSS) for 24 states including the optional caregiving module were analyzed to investigate factors associated with mental health and depression, comparing cancer caregivers (n=3,078) to the general population (n=196,586). Logistic regressions identified factors associated with frequent mental distress days (FMD; > 6 days of poor mental health in the last 30 days) or a lifetime depression diagnosis. Predictors included cancer caregiver status, reporting > 14 poor physical health days monthly, exercise in the previous month, age, sex, marital status, education, employment status, rural/urban status, U.S. region, and year. Results: In unadjusted comparisons, caregivers were significantly more likely than the general population to be female, older, married/partnered, have attended college, unemployed, live rurally, and report FMD or a depression diagnosis. After adjusting for sociodemographics, year, U.S. region, physical health, and exercise, caregivers were significantly more likely than the general population to have FMD (aOR=1.69, 95%CI=1.42-2.02) or a lifetime depression diagnosis (aOR=1.22, 95%CI=1.03-1.46). Conclusion: Future research should address risk factors associated with mental health, identifying the most at-risk caregivers for targeted interventions. These findings support mental health screening of caregivers in oncology and primary care settings, especially during high-burden periods such as treatment initiation. Mental health caregiving cancer care health promotion public health BRFSS Introduction Informal caregivers (i.e., caregivers) consist of family members, friends, or other individuals who support patients’ complex needs outside the formal healthcare system, [1,2] and they play a critical role in supporting cancer patients. There are approximately 2.8 million caregivers of cancer patients [3], and that number is expected to grow alongside the more than two million new cancer diagnoses in 2026 [4,5]. Caregivers substantially contribute to cancer patients’ outcomes, including improving patients’ mental health and coping with the adverse effects of treatment [1,6]. However, many of the caregivers’ psychological needs are unmet, resulting in poor mental health [7,8]. Emerging data show that caregivers of cancer patients have mental health needs that exceed those of the general population [9,10], but population-level comparisons remain limited. Additionally, more recent estimates are needed, especially after the height of the COVID-19 pandemic. Multiple factors affect mental health outcomes, including physical activity, exercise, emotional support, employment status, and other socio-demographic characteristics, such as age, sex, income, education level, and marital status [11]. Many caregivers report feeling emotional distress due to their grief as well as changes in the cancer patient’s trajectory [10]. Other studies about cancer caregivers cite unmet needs for financial, psychosocial, community, or religious support [12,13], which can also contribute to mental distress. In turn, frequent mental distress (FMD), defined as having more than six poor mental health days in the last 30 days [14–17], is associated with multiple adverse health behaviors, increased healthcare utilization, mental health disorders, and chronic disease [17]. Other studies of cancer caregivers’ mental health have not compared their outcomes to those of the general population [8,18,19]. Despite the importance of these other outcomes, it remains unclear how the mental health of cancer caregivers differs from that of the general population, and what salient factors are related to self-disclosed mental distress and depression diagnoses. These group comparisons are important for public health benchmarking to detect potential disparities and identify areas of intervention. The health and well-being of cancer patient caregivers are commonly conceptualized through multiple outcomes, including depression and emotional distress [20]. The Cancer Family Caregiving experience model provides a conceptual framework to understand cancer patient caregivers' stressors and well-being outcomes (mental health days or depression) [20]. In this framework, contextual factors (socio-demographics) and primary and secondary stressors culminate in caregivers' cognitive and behavioral responses within the stress process. Primary stressors include increased cancer caregiving demands, such as psychomotor tasks and driving to more appointments as patient acuity increases, and secondary stressors include spillover onto employment and finances. This process occurs over the trajectory of the cancer patient’s illness process, affecting the health and well-being of the caregiver, including their mental health. While this theoretical underpinning is important, population-level exploration remains limited to operationalizing these factors and testing their association with outcomes. The purpose of this study is to understand the factors associated with reporting frequent mental distress or a depressive disorder diagnosis and whether these differ between cancer caregivers and the general population, utilizing a national dataset. We hypothesized that caregivers of cancer patients would have higher odds of poor mental health outcomes than the general population. This information will provide oncology and mental health providers with data on factors most strongly associated with poor mental health outcomes of caregivers. This analysis will also inform the development of screenings and interventions for cancer caregivers. Methods Design and Sample The Behavioral Risk Factor Surveillance Survey (BRFSS) is an annual health behavior survey administered by states through coordination by the Centers for Disease Control and Prevention (CDC). The survey instrument consists of core items that states must administer, and states can elect to use optional modules. In 2022 and 2023, 24 states or territories collected information using the CDC’s optional caregiving module. Arizona, Louisiana, Ohio, and Oregon administered the caregiving module in both years. In 2022, the following states used the module: Georgia, Mississippi, New Hampshire, Oklahoma, Pennsylvania, Puerto Rico, Utah, Virginia, Washington, and Wisconsin. In 2023, the following states used the module: Arkansas, Hawaii, Idaho, Iowa, Maine, Maryland, New York, Tennessee, and Texas. Individuals from states administering survey versions with the caregiving modules and who described their caregiving status (n = 199,664) met the inclusion criteria for this study. The combined response rates for the 24 states across both years ranged from a low of 31% in Tennessee in 2023 to a high of 58.5% in Puerto Rico in 2022. Further details about the BRFSS methodology are available from the CDC [21]. Independent Variables Demographic variables for all analyses included age, sex, race/ethnicity, marital status, educational level, income level, and urban/rural status. Age categories were 18–24 years, 25–34 years, 35–44 years, 45–54 years, 55–64 years, and 65 years or older. Race included categories of non-Hispanic White, non-Hispanic Black, non-Hispanic American Indian/Alaska Native, Hispanic, non-Hispanic Multiracial or Other, and non-Hispanic Asian/Pacific Islander/Native Hawaiian. Marital status was categorized as married or partnered, divorced or separated, widowed, or never married. Education level was defined as less than high school, high school graduate, some college, or a college or technical school graduate. Employment status was recoded as employed (including self-employed), unemployed, or out of the workforce (i.e., homemakers, students, retirees, and individuals unable to work). Geography was defined as urban or rural, using the National Center for Health Statistics (NCHS) Urban-Rural Classification, considering large central, large fringe, medium, and small metropolitan areas in addition to micropolitan areas as urban, and noncore non-metropolitan areas as rural [22]. To account for regional differences in caregiving support, states were coded into the following regions: West (Arizona, Utah, Colorado, Texas, Oregon, Washington, Hawaii, and Idaho), Midwest (Ohio, Wisconsin, Oklahoma, and Iowa), South (Louisiana, Georgia, Mississippi, Virginia, Arkansas, Maryland, Tennessee, and Puerto Rico), and Northeast (New Hampshire, Pennsylvania, Maine, and New York). Year was separated into survey years of 2022 and 2023. Independent variables also included selected social and health behaviors. Exercise in the previous month was assessed with the following yes/no question: “During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?” The BRFSS questionnaire defined poor physical health as physical illness or injury, asking respondents: “Now thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?” Poor physical health days were dichotomized into reporting 14 or more poor physical health days per month or less than 14 poor physical health days per month [23]. The main independent variable was caregiving status, which was assessed with a yes/no question: “During the past 30 days, did you provide regular care or assistance to a friend or family member who has a health problem or disability?” Individuals who answered “Yes” proceeded with the caregiving module of the BRFSS. Only versions of the BRFSS surveys used by states assessing the caregiver status question were included in the analysis, listed in Supplementary Table 1. The caregiving module asked caregivers to select one response to the following question: “What is the main health problem, long-term illness, or disability that the person you care for has?” Caregivers could select from 14 options: arthritis or rheumatism, asthma, cancer, chronic respiratory conditions (e.g., emphysema, chronic obstructive pulmonary disorder), cognitive disorders (e.g., Alzheimer’s disease, dementia), developmental disabilities (e.g., autism, Down’s syndrome, spina bifida), diabetes, vascular issues (heart disease, hypertension, and stroke), Human Immunodeficiency Virus (HIV), mental illnesses (anxiety, depression, and schizophrenia), organ failure or diseases, substance abuse or addiction disorders, injuries, and old age or infirmity. Dependent Variables The BRFSS assessed mental health with the following question: “Now, thinking about your mental health, which includes stress, depression, and problems and emotions, for how many days during the past 30 days was your mental health not good?” Poor mental health days were then operationalized as six or more days of poor mental health per month, indicating frequent mental distress (FMD6) or fewer than six days of poor mental health per month. The FMD6 indicator has been validated against standards of mental distress (i.e., the Kessler 6 scale of mental distress) and effectively used with multiple populations [15,16,24]. The second dependent variable was whether an individual had a lifetime depression diagnosis (yes/no), assessed by the BRFSS with the following question: “(Ever told) (you had) a depressive disorder (including depression, major depression, dysthymia, or minor depression)? Data analysis The datasets from the BRFSS were downloaded and combined into one file, reflecting the appropriate weights for each survey version. Arizona and Ohio utilized more than one survey version, so a working data set was created following the BRFSS complex sampling recommendations for their weights [25]. Missing data were retained by being recoded into other/unknown categories for each variable. Pearson’s chi-squared tests were used to compare cancer caregivers with the general population on the prevalence of each socio-demographic variable, exercise, emotional support, physical health indicator, and mental health outcomes (i.e., FMD6 and depression). Logistic regression was used to determine the odds of FMD6 or lifetime depression diagnosis by caregiver status, adjusting all models for socio-demographic covariates, physical health indicators, exercise, and emotional support. Adjusted odds ratios (aOR) and 95% confidence intervals are reported. Stata version 18 was used for all data cleaning, coding, and analysis. Statistical significance was set at p < .05. Because this study used a publicly available dataset, the IRB of [institution name masked] deemed the project as not human subjects research. Results After identifying states using the caregiving modules, 199,664 individuals were included in unadjusted analyses, including 3,078 cancer caregivers and 196,586 other individuals representing the general population (i.e., people without caregiving responsibilities and people who were caregivers for non-cancer conditions). For adjusted analyses, the sample sizes were 186,767 and 188,345 (FMD and depression, respectively). The cancer caregivers’ total numbers from each state (Supplementary Table 1) were checked for accuracy against original year datasets and available BRFSS data from individual states, including Arizona [26,27], New York [28], Washington (Crawbuck, G., personal communication, June 16, 2025), and Wisconsin [29]. Unadjusted analyses identified differences between cancer caregivers and the general population in the prevalence of each variable. In unadjusted models, cancer caregivers were significantly more likely than the general population to be 45 years or older ( p < .001), female ( p < .001), married or partnered ( p = .01), have attended or graduated from college or technical school ( p = .01), be unemployed ( p = .001), live in a rural area ( p =.04), and report FMD6 ( p < .001) or a lifetime depression diagnosis ( p = .01) (Table 1 ). Table 1 Prevalence in socio-demographics, frequent mental distress, and a lifetime depression diagnosis, general population versus cancer informal caregivers (ICs), BRFSS 2022–2023 Socio-demographics Full population N = 199,664 General population N = 196,586 Cancer ICs N = 3,078 n (%) n (%) n (%) P Gender < .001 Men 92,515 (48.4) 91,393 (48.6) 1,122 (39.0) Women 107,149 (51.6) 105,193 (51.4) 1,956 (61.0) Race/ethnicity .01 White (non-Hispanic) 146,260 (60.1) 143,888 (60.0) 2,372 (64.5) Black (non-Hispanic) 13,670 (11.5) 13,432 (11.5) 238 (14.1) AI/AN (non-Hispanic) 2,352 (1.2) 2,317 (1.2) 35 (0.6) Asian (non-Hispanic) 6,520 (4.8) 6,468 (4.8) 52 (2.9) Multiracial/Other (non-Hispanic) 5,830 (3.5) 5,718 (3.5) 112 (4.5) Hispanic 20,246 (16.7) 20,039 (16.8) 207 (11.4) Unknown 4,786 (2.3) 4,724 (2.3) 62 (1.9) Age group < .001 18–24 years 11,085 (11.6) 10,971 (11.7) 114 (7.0) 25–34 years 20,132 (16.1) 19,933 (16.2) 199 (9.9) 35–44 years 25,812 (16.3) 25,446 (16.3) 366 (14.4) 45–54 years 29,679 (15.3) 29,187 (15.3) 492 (16.9) 55–64 years 36,746 (16.4) 36,084 (16.4) 662 (20.8) 65 + years 76,210 (24.3) 74,965 (24.2) 1,245 (31.0) Marital status .01 Married/partnered 111,610 (55.2) 109,718 (55.2) 1,892 (59.6) Divorced/separated 30,469 (12.9) 29,996 (12.9) 473 (14.9) Widowed Never married 22,475 33,480 (7.3) (23.6) 22,165 33,099 (7.3) (23.7) 310 381 (6.9) (17.9) Unknown 1,630 (0.9) 1,608 (0.9) 22 (0.7) Education level (highest) .01 < High school 11,215 (11.0) 11,076 (11.1) 139 (7.9) High school graduate 49,426 (27.9) 48,691 (27.9) 735 (25.5) Some college/tech school 56,056 (30.4) 55,162 (30.4) 894 (33.5) Graduate coll./tech school 82,230 (30.2) 80,928 (30.2) 1,302 (33.0) Unknown 737 (0.4) 729 (0.4) 8 (0.1) Employment status .001 Employed 97,954 (56.2) 96,528 (56.5) 1,426 (49.1) Unemployed 7,376 (5.0) 7,264 (5.0) 112 (6.2) Out of workforce 92,668 (37.6) 91,143 (37.5) 1,525 (44.2) Unknown 1,666 (1.2) 1,651 (1.2) 15 (0.5) Exercise in previous month .39 Yes 150,639 (75.1) 148,231 (75.1) 2,408 (77.1) No 48,588 (24.6) 47,923 (24.7) 665 (22.7) Unknown 437 (0.2) 432 (0.2) 5 (0.2) Poor physical health days .06 Less than 14/month 166,589 (86.7) 164,037 (86.8) 2,552 (84.3) 14 or more/month 28,129 (13.3) 27,653 (13.2) 476 (15.7) Geography .04 Urban 174,079 (93.4) 171,415 (93.5) 2,664 (91.2) Rural 20,228 (6.6) 19,865 (6.5) 363 (8.8) Year of survey .36 2022 116,291 (48.24) 114,530 (44.9) 1,761 (43.2) 2023 83,373 (41.76) 82,056 (55.1) 1,317 (56.8) Region of U.S. West 83,946 (35.6) 82,732 (35.7) 1,214 (34.5) .09 Midwest 48,827 (19.6) 48,095 (19.7) 732 (16.5) South 47,063 (25.7) 46,249 (25.6) 814 (29.3) Northeast 19,828 (19.1) 19,510 (19.1) 318 (19.6) Frequent Mental Distress < .001 Less than 6/month 154,035 (76.1) 151,919 (76.2) 2,116 (68.8) 6 or more/month 41,703 (23.9) 40,806 (23.8) 897 (31.2) Lifetime Depression Diagnosis .01 Yes 44,054 (22.1) 43,210 (22.0) 844 (26.0) No 154,448 (77.9) 152,234 (78.0) 2,214 (74.0) Notes: Combined population includes non-cancer caregivers and non-caregivers. AI/AN=American Indian & Alaska Native. West U.S. = AZ, UT, CO, TX, OR, WA, HI, and ID; Midwest U.S. = OH, WI, OK, IA; South U.S. = LA, GA, MS, VA, AK, MD, TN, PR; Northeast U.S. = NH, PA, ME, NY Results of regression analysis identified the association between caregiver status with mental health-dependent variables while controlling for physical health, exercise, and socio-demographics. The full models were statistically significant ( p < .001), indicating that they could distinguish between reporting FMD and not reporting it, and between reporting a lifetime depression diagnosis and not reporting it. Table 2 shows the significant predictors in the logistic models for the FMD and lifetime depression diagnosis outcome variables. Cancer caregivers were significantly more likely than non-cancer caregivers to have FMD and a lifetime depression diagnosis, having approximately 69% and 22% greater odds, respectively. Table 2 Association of caregiver status with FMD and lifetime depression diagnosis FMD6 Diagnosed with depression (n = 186,767) (n = 188,345) aOR (95%CI) aOR (95%CI) Status General population Ref Ref Cancer patient caregivers 1.69 (1.42–2.02)* 1.22 (1.03–1.46)* Age group 18–24 years Ref Ref 25–34 years 0.87 (0.79–0.96)* 1.11 (0.90–1.13)* 35–44 years 0.60 (0.55–0.67)* 0.88 (0.73–0.91)* 45–54 years 0.41 (0.37–0.46)* 0.68 (0.58–0.74)* 55–64 years 0.28 (0.25–0.31)* 0.53 (0.44–0.56)* 65 + years 0.15 (0.14–0.17)* 0.29 (0.22–0.29)* Sex Male Ref Ref Female 1.64 (1.56–1.73)* 2.09 (1.99–2.20)* Race White (Non-Hispanic) Ref Ref Black (Non-Hispanic) 0.81 (0.74–0.88)* 0.49 (0.45–0.54)* AI/AN (Non-Hispanic) 1.02 (0.84–1.23) 0.85 (0.70–1.03) Asian (Non-Hispanic) 0.65 (0.56–0.74)* 0.35 (0.30–0.41)* Multiracial/Other (Non-Hispanic) 1.17 (1.03–1.33)* 1.06 (0.94–1.19) Hispanic 0.73 (0.66–0.80)* 0.57 (0.51–0.63)* Unknown 0.99 (0.84–1.18) 0.66 (0.56–0.78)* Marital status Married/partnered Ref Ref Divorced/separated 1.66 (1.55–1.78)* 1.83 (1.71–1.96)* Widowed 1.33 (1.20–1.48)* 1.26 (1.14–1.40)* Never married 1.55 (1.45–1.66)* 1.40 (1.31–1.50)* Unknown 1.21 (0.94–1.58) 1.14 (0.87–1.51) Education level < High school Ref Ref High school graduate 0.94 (0.84–1.06) 0.89 (0.79-1.00) Some college/tech. school 1.06 (0.94–1.18) 1.06 (0.95–1.20) Graduate college/tech. school 0.84 (0.75–0.95)* 0.91 (0.81–1.03) Unknown 1.07 (0.66–1.76) 0.48 (0.32–0.72)* Employment status Employed Ref Ref Unemployed 1.61 (1.45–1.79)* 1.79 (1.60-2.00)* Out of workforce 1.22 (1.15–1.30)* 1.49 (1.40–1.59)* Unknown 0.78 (0.62–0.99)* 0.76 (0.55–1.05) Geography Urban Ref Ref Rural 0.84 (0.77–0.91)* 0.87 (0.80–0.95)* Exercise in previous month Yes Ref Ref No 1.23 (1.16–1.31)* 1.28 (1.20–1.36)* Unknown 1.03 (0.61–1.73) 1.20 (0.77–1.89) Poor physical health days Less than 14 days/month Ref Ref 14 or more days/month 4.73 (4.42–5.07)* 2.75 (2.57–2.94)* U.S. Region West Ref Ref Midwest 0.98 (0.93–1.04) 1.06 (1.00-1.12) South 1.01 (0.95–1.07) 1.03 (0.98–1.10) Northeast 0.84 (0.77–0.91)* 0.83 (0.76–0.90)* Year 2022 Ref Ref 2023 0.97 (0.93–1.02) 0.95 (0.91-1.00)* Notes: AI/AN=American Indian & Alaska Native. West U.S. = AZ, UT, CO, TX, OR, WA, HI, and ID; Midwest U.S. = OH, WI, OK, IA; South U.S. = LA, GA, MS, VA, AK, MD, TN, PR; Northeast U.S. = NH, PA, ME, NY Other significant correlates included lack of exercise in the last month being associated with higher odds of FMD (aOR = 1.23; 95%CI = 1.16–1.31) and lifetime depression diagnosis (aOR = 1.28; 95%CI = 1.20–1.36), and 14 or more poor physical health days in the last 30 days being significantly positively associated with both FMD (aOR = 4.73; 95%CI = 4.42–5.07) and a lifetime depression diagnosis (aOR = 2.75; 95%CI = 2.57–2.94). Individuals from rural areas had significantly lower odds of FMD (aOR = 0.84; 95%CI = 0.77–0.91) and a lifetime depression diagnosis (aOR = 0.87; 95%CI = 0.80–0.95) than individuals from urban areas. Additionally, individuals from the Northeast region of the U.S. had significantly lower odds of FMD (aOR = 0.84; 95%CI = 0.77–0.91) and a lifetime depression diagnosis (aOR = 0.83; 95%CI = 0.76–0.90) than those from the Western region. Women had significantly higher odds of FMD (aOR = 1.64; 95%CI = 1.56–1.73) or a lifetime depression diagnosis (aOR = 2.09; 95%CI = 1.99–2.20). Discussion This population-based analysis of BRFSS data from 24 states examined whether cancer caregivers have poorer mental health outcomes than the general population, after adjusting for covariates. Cancer caregivers had several significant unadjusted differences with the general population, and they had significantly higher odds of FMD and a lifetime depression diagnosis than the general population in the adjusted models, underscoring the persistent burden associated with cancer caregiving. The stronger association observed for cancer caregivers having higher odds of FMD versus lifetime depression diagnosis is notable, especially given that FMD reflects distress in the last 30 days, and lifetime depression diagnosis captures a historical clinical diagnosis. This may reflect ongoing situational stress related to caregiving burden rather than pre-existing depression, or it could reflect underdiagnosis of depression among caregivers or barriers to accessing mental healthcare. The results here align with the Cancer Family Caregiving Experience Model, which conceptualizes caregiving as a dynamic stress process leading to psychological outcomes [20]. This study found that cancer caregivers have a higher unadjusted prevalence of poor mental health and higher odds of poor mental health days than the general populations, which echoed other studies’ findings [30–32]. Other research studies contrasting caregivers and non-caregivers [33–35] have similarly identified that caregivers have elevated rates of poor mental health outcomes. Yet, other studies comparing caregivers with non-caregivers have found more modest differences or have suggested that caregiving does not necessarily lead to poorer mental health outcomes, although these studies often used different outcome measures, such as life satisfaction [36–38]. Heterogeneity in caregiving experiences also likely explains these differences. For instance, caregivers caring for patients with aggressive cancers such as pancreatic cancer often report worse psychological outcomes compared to caregivers caring for patients with other types of cancer, such as breast [39–41]. Additionally, a recent analysis of BRFSS data from 2015–2016 to 2021–2022 identified an increase in FMD among both caregivers and the population as a whole [42], a broader trend that may partially explain some differences in our findings [43]. Nonetheless, the persistence of disparities after adjusting for covariates suggests that caregiving contributes to psychological strain. These mixed findings also suggest that future caregiver studies should account for differences in patient acuity and prognosis. Similarly, cancer caregivers in this study had higher odds of reporting a lifetime depression diagnosis, consistent with prior literature demonstrating elevated rates of depressive disorders among cancer caregivers [44,45]. However, findings across studies have not been consistent, with some demonstrating smaller differences between caregivers and non-caregivers or no clear association between caregiving and depression diagnosis [36,38]. This variability in findings reflects differences in measurement (e.g., lifetime diagnosis versus current depressive symptoms) or in access to mental healthcare across samples. Lifetime depression captures a historical clinical diagnosis rather than current distress, and it may be less sensitive to the evolving stressors of caregiving. These findings highlight the need to account for patient acuity, prognosis, caregiver burden, and caregiving intensity in future studies. Implications Altogether, these results indicate that cancer caregivers require interventions to improve their physical and psychological health. Such interventions should include bolstering components of the stress process of caregivers, including addressing primary stressors such as care demands and patient factors, an appraisal of needs, and cognitive-behavioral responses such as coping and self-care to lower the level of burden and distress on the caregiver, and addressing secondary stressors such as schedule, financial challenges, and fatigue. The findings here echo those of other studies showing lower mental and physical well-being in cancer caregivers, especially at the end of a cancer patient’s life [9,10]. Further, the emotional needs of cancer caregivers may change over the trajectory of the patient’s illness, especially if treatment is ineffective or a prognosis worsens [10], suggesting that oncology and other teams vary approaches with caregivers throughout these changes and ensure that caregivers are kept informed and involved in decision making for the patient’s care, including anticipatory guidance [2,9] and attention to their mental health needs . Limitations Despite the strengths of this analysis, there are limitations. BRFSS data utilize self-reported information, which introduces recall bias and bias due to social desirability, and the measures of mental distress are not caregiving-specific. Additionally, the BRFSS depression question assesses any lifetime depressive diagnosis and does not distinguish between minor and major depressive conditions. Also, comorbid conditions of individuals receiving informal caregiving support could not be assessed in the single-item measure of the BRFSS, nor could the mental and physical health of the caregiver before becoming a caregiver. Conclusion This study fills an important gap in the literature with data supporting that poor mental health outcomes are pervasive among U.S. cancer caregivers, identifying associated factors with mental health outcomes. The results of this study can inform the public health approach to health promotion by determining further research and interventions to identify relevant issues and ultimately address cancer caregivers’ mental health. Future studies should assess caregiving intensity, cancer type, trajectories of stress over time, the interaction of multiple patient comorbidities, in order to develop tailored interventions. Declarations Competing interests The authors have no relevant financial or non-financial interests to disclose. Funding The National Cancer Institute of the National Institutes of Health supported this work (T32CA117865; Champion/Mosher). Support for this work also came from a research award from the National Institute of Mental Health (DP2MH129967; PI Blosnich) Author Contribution All authors contributed to the study conception and design. Data collection and analysis were performed by Jeanne Ward under the oversight of John Blosnich. The first draft of the manuscript was written by Jeanne Ward, and all authors commented on previous versions. All authors read and approved the final manuscript. Data Availability Data used are publicly available at https://www.cdc.gov/brfss/index.html References Molassiotis A, Wang M. Understanding and supporting informal cancer caregivers. Curr Treat Options Oncol. 2022;23(4):494–513. Northouse L, Williams A-l, Given B, et al. Psychosocial care for family caregivers of patients with cancer. J Clin Oncol. 2012;30(11):1227–1234. National Alliance for Caregiving. Cancer caregiving in the U.S. 2016 [Feb. 27, 2025]. Available from: https://www.caregiving.org/wp-content/uploads/2022/11/CancerCaregivingReport_FINAL_June-17-2016.pdf American Cancer Society. Cancer Facts & Figs. 2025 2025 [Feb. 27, 2025]. Available from: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2025/2025-cancer-facts-and-figures-acs.pdf Siegel RL, Kratzer TB, Wagle NS, et al. Cancer statistics, 2026. Ca Cancer J Clin. 2026;76(1):e70043. Litzelman K, Blanch-Hartigan D, Lin CC, et al. Correlates of the positive psychological byproducts of cancer: Role of family caregivers and informational support. Palliat Support Care. 2017;15(6):693–703. van der Kruk SR, Butow P, Mesters I, et al. Psychosocial well-being and supportive care needs of cancer patients and survivors living in rural or regional areas: A systematic review from 2010 to 2021. Support Care Cancer. 2022;30(2):1021–1064. Qian Y, Kent EE. Gender differences in the association between unmet support service needs and mental health among American cancer caregivers. Support Care Cancer. 2022;30(6):5469–5480. Butow PN, Price MA, Bell ML, et al. Caring for women with ovarian cancer in the last year of life: A longitudinal study of caregiver quality of life, distress and unmet needs. Gynecol Oncol. 2014;132(3):690–697. Rodenbach RA, Norton SA, Wittink MN, et al. When chemotherapy fails: Emotionally charged experiences faced by family caregivers of patients with advanced cancer. Patient Educ Couns. 2019;102(5):909–915. McGuire LC, Strine TW, Vachirasudlekha S, et al. Modifiable characteristics of a healthy lifestyle and chronic health conditions in older adults with or without serious psychological distress, 2007 Behavioral Risk Factor Surveillance System. Int J Public Health. 2009;54 Suppl 1:84–93. Biddell CB, Spees LP, Petermann V, et al. Financial assistance processes and mechanisms in rural and nonrural oncology care settings. JCO Oncology Practice. 2022;29. Ratnapradipa KL, Ranta J, Napit K, et al. Qualitative analysis of cancer care experiences among rural cancer survivors and caregivers. The Journal of Rural Health. 2022;38(4):876–885. Cree RA. Frequent mental distress among adults, by disability status, disability type, and selected characteristics—United States, 2018. MMWR Morbidity and mortality weekly report. 2020;69. National Academies of Sciences E, Medicine, Health, et al. Leading health indicators 2030: advancing health, equity, and well-being. Leading health indicators 2030: advancing health, equity, and well-being. Washington (DC): National Academies Press (US); 2020. Bossarte RM, He H, Claassen CA, et al. Development and validation of a 6-day standard for the identification of frequent mental distress. Soc Psychiatry Psychiatr Epidemiol. 2011;46(5):403 − 11. Cree RA, Okoro CA, Zack MM, et al. Frequent mental distress among adults, by disability status, disability type, and selected characteristics —United States, 2018. MMWR Morbidity and Mortality Weekly Report. 2020;69(36):1238–1243. Monahan Z, Shores D, Mack A, et al. Prevalence of depression among caregivers based on the condition and relationship of care recipient. J Affect Disord. 2023;340:442–447. Longacre ML, Brewer B, Hubbard A, et al. Caregiver health by context: Moderating effects of mental health and health behaviors. West J Nurs Res. 2020;43(7):622–630. Fletcher BS, Miaskowski C, Given B, et al. The cancer family caregiving experience: An updated and expanded conceptual model. Eur J Oncol Nurs. 2012;16(4):387–398. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System 2024 [December 13, 2024]. Available from: Behavioral Risk Factor Surveillance System, Centers for Disease Control and Prevention. NCHS Urban-Rural Classification Scheme for Counties 2024 [February 3, 2025]. Available from: https://www.cdc.gov/nchs/data-analysis-tools/urban-rural.html Dwyer-Lindgren L, Mackenbach JP, van Lenthe FJ, et al. Self-reported general health, physical distress, mental distress, and activity limitation by US county, 1995–2012. Population Health Metrics. 2017;15(1):16. New Mexico Department of Health. Adult frequent mental distress by year, New Mexico and U.S., 2004 to 2021 2023. Available from: https://ibis.doh.nm.gov/indicator/view/MentHlthAdult.Year.NM_US.html? Centers for Disease Control and Prevention. Complex sampling weights and preparing 2022 BRFSS module data for analysis 2023 [June 9, 2025]. Available from: https://www.cdc.gov/brfss/annual_data/2022/pdf/Complex-Sampling-Weights-and-Preparing-Module-Data-for-Analysis-2022-508.pdf Arizona Department of Health Services. Arizona 2022 Codebook Report Version 1 Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.azdhs.gov/documents/preparedness/public-health-statistics/behavioral-risk-factor-surveillance/code-book/az22code-llcp-v1.pdf Arizona Department of Health Services. Arizona 2022 Codebook Reprot Version 2 Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.azdhs.gov/documents/preparedness/public-health-statistics/behavioral-risk-factor-surveillance/code-book/az22code-llcp-v2.pdf New York State Department of Health. New York State Behavioral Risk Ractor Surveillance Survey: 2023 2025 [June 26, 2025]. Available from: https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-Survey-2023/tk4g-wdfe/about_data Wisconsin Department of Health Services. Wisconsin 2022 Codebook Report Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.dhs.wisconsin.gov/stats/2022-wi-brfss-codebook.pdf Chakraborty R, Jana A, Vibhute VM. Caregiving: A risk factor of poor health and depression among informal caregivers in India- a comparative analysis. BMC Public Health. 2023;23(1):42. Mosher CE, Bakas T, Champion VL. Physical health, mental health, and life changes among family caregivers of patients with lung cancer. Oncology Nursing Forum. 2013;40(1):53–61. Pan YC, Lin YS. Systematic Review and Meta-Analysis of Prevalence of Depression Among Caregivers of Cancer Patients. Front Psychiatry. 2022;13:817936. Janson P, Willeke K, Zaibert L, et al. Mortality, morbidity and health-related outcomes in informal caregivers compared to non-caregivers: A systematic review. Int J Environ Res Public Health. 2022;19(10):5864. Berglund E, Lytsy P, Westerling R. Health and wellbeing in informal caregivers and non-caregivers: A comparative cross-sectional study of the Swedish general population. Health and Quality of Life Outcomes. 2015;13(1):109. Anderson LA, Edwards VJ, Pearson WS, et al. Adult caregivers in the United States: characteristics and differences in well-being, by caregiver age and caregiving status. Prev Chronic Dis. 2013;10:E135. Roth DL, Fredman L, Haley WE. Informal caregiving and its impact on health: A reappraisal from population-based studies. Gerontologist. 2015;55(2):309–319. de Camargos MG, Paiva BSR, de Oliveira MA, et al. An explorative analysis of the differences in levels of happiness between cancer patients, informal caregivers and the general population. BMC Palliat Care. 2020;19(1):106. Pinquart M, Sörensen S. Differences between caregivers and noncaregivers in psychological health and physical health: A meta-analysis. Psychol Aging. 2003;18(2):250. Anderson T, Mitchell G, Prue G, et al. The psychosocial impact of pancreatic cancer on caregivers: a scoping review. BMC Cancer. 2025;25(1):511. Chong E, Crowe L, Mentor K, et al. Systematic review of caregiver burden, unmet needs and quality-of-life among informal caregivers of patients with pancreatic cancer. Support Care Cancer. 2022;31(1):74. Özönder Ünal I, Ordu C. Decoding Caregiver Burden in Cancer: Role of Emotional Health, Rumination, and Coping Mechanisms. Healthcare (Basel). 2023;11(19). Kilmer G. Changes in health indicators among caregivers—United States, 2015–2016 to 2021–2022. MMWR Morbidity and Mortality Weekly Report. 2024;73. Udupa NS, Twenge JM, McAllister C, et al. Increases in poor mental health, mental distress, and depression symptoms among U.S. adults, 1993–2020. J Mood Anxiety Disord. 2023;2:100013. Trevino KM, Prigerson HG, Maciejewski PK. Advanced cancer caregiving as a risk for major depressive episodes and generalized anxiety disorder. Psycho-Oncology. 2018;27(1):243–249. Pan Y-C, Lin Ya-S. Systematic Review and Meta-Analysis of Prevalence of Depression Among Caregivers of Cancer Patients [Systematic Review]. Front Psychiatry. 2022;Volume 13–2022. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 05 May, 2026 Editor assigned by journal 05 May, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 20 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9181837","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":636338153,"identity":"31a3901a-ce55-48a2-bc55-caa5f7254472","order_by":0,"name":"Jeanne M. 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Blosnich","email":"","orcid":"","institution":"University of Southern California","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"R.","lastName":"Blosnich","suffix":""},{"id":636338164,"identity":"d0b8dec7-3bf8-43d7-9ee2-2d696a4d173e","order_by":2,"name":"Victoria Champion","email":"","orcid":"","institution":"1=Indiana University School of Nursing","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Champion","suffix":""}],"badges":[],"createdAt":"2026-03-20 20:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9181837/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9181837/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109152317,"identity":"410aafbe-5018-4161-a7e3-60e96c6174ce","added_by":"auto","created_at":"2026-05-13 05:59:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":627615,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9181837/v1/a212d74e-dd9b-4020-ac7d-fa61e30745c9.pdf"},{"id":109152256,"identity":"841bff03-39f3-4a71-a02b-592122d87763","added_by":"auto","created_at":"2026-05-13 05:58:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15790,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9181837/v1/70c256cdf3785666566955dd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Poor mental health days and depressive disorders by informal cancer patient caregiver status: BRFSS 2022-23","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInformal caregivers (i.e., caregivers) consist of family members, friends, or other individuals who support patients\u0026rsquo; complex needs outside the formal healthcare system, [1,2] and they play a critical role in supporting cancer patients. There are approximately 2.8\u0026nbsp;million caregivers of cancer patients [3], and that number is expected to grow alongside the more than two million new cancer diagnoses in 2026 [4,5]. Caregivers substantially contribute to cancer patients\u0026rsquo; outcomes, including improving patients\u0026rsquo; mental health and coping with the adverse effects of treatment [1,6]. However, many of the caregivers\u0026rsquo; psychological needs are unmet, resulting in poor mental health [7,8]. Emerging data show that caregivers of cancer patients have mental health needs that exceed those of the general population [9,10], but population-level comparisons remain limited. Additionally, more recent estimates are needed, especially after the height of the COVID-19 pandemic.\u003c/p\u003e \u003cp\u003eMultiple factors affect mental health outcomes, including physical activity, exercise, emotional support, employment status, and other socio-demographic characteristics, such as age, sex, income, education level, and marital status [11]. Many caregivers report feeling emotional distress due to their grief as well as changes in the cancer patient\u0026rsquo;s trajectory [10]. Other studies about cancer caregivers cite unmet needs for financial, psychosocial, community, or religious support [12,13], which can also contribute to mental distress. In turn, frequent mental distress (FMD), defined as having more than six poor mental health days in the last 30 days [14\u0026ndash;17], is associated with multiple adverse health behaviors, increased healthcare utilization, mental health disorders, and chronic disease [17]. Other studies of cancer caregivers\u0026rsquo; mental health have not compared their outcomes to those of the general population [8,18,19]. Despite the importance of these other outcomes, it remains unclear how the mental health of cancer caregivers differs from that of the general population, and what salient factors are related to self-disclosed mental distress and depression diagnoses. These group comparisons are important for public health benchmarking to detect potential disparities and identify areas of intervention.\u003c/p\u003e \u003cp\u003eThe health and well-being of cancer patient caregivers are commonly conceptualized through multiple outcomes, including depression and emotional distress [20]. The Cancer Family Caregiving experience model provides a conceptual framework to understand cancer patient caregivers' stressors and well-being outcomes (mental health days or depression) [20]. In this framework, contextual factors (socio-demographics) and primary and secondary stressors culminate in caregivers' cognitive and behavioral responses within the stress process. Primary stressors include increased cancer caregiving demands, such as psychomotor tasks and driving to more appointments as patient acuity increases, and secondary stressors include spillover onto employment and finances. This process occurs over the trajectory of the cancer patient\u0026rsquo;s illness process, affecting the health and well-being of the caregiver, including their mental health. While this theoretical underpinning is important, population-level exploration remains limited to operationalizing these factors and testing their association with outcomes.\u003c/p\u003e \u003cp\u003eThe purpose of this study is to understand the factors associated with reporting frequent mental distress or a depressive disorder diagnosis and whether these differ between cancer caregivers and the general population, utilizing a national dataset. We hypothesized that caregivers of cancer patients would have higher odds of poor mental health outcomes than the general population. This information will provide oncology and mental health providers with data on factors most strongly associated with poor mental health outcomes of caregivers. This analysis will also inform the development of screenings and interventions for cancer caregivers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign and Sample\u003c/h2\u003e \u003cp\u003eThe Behavioral Risk Factor Surveillance Survey (BRFSS) is an annual health behavior survey administered by states through coordination by the Centers for Disease Control and Prevention (CDC). The survey instrument consists of core items that states must administer, and states can elect to use optional modules. In 2022 and 2023, 24 states or territories collected information using the CDC\u0026rsquo;s optional caregiving module. Arizona, Louisiana, Ohio, and Oregon administered the caregiving module in both years. In 2022, the following states used the module: Georgia, Mississippi, New Hampshire, Oklahoma, Pennsylvania, Puerto Rico, Utah, Virginia, Washington, and Wisconsin. In 2023, the following states used the module: Arkansas, Hawaii, Idaho, Iowa, Maine, Maryland, New York, Tennessee, and Texas. Individuals from states administering survey versions with the caregiving modules and who described their caregiving status (n\u0026thinsp;=\u0026thinsp;199,664) met the inclusion criteria for this study. The combined response rates for the 24 states across both years ranged from a low of 31% in Tennessee in 2023 to a high of 58.5% in Puerto Rico in 2022. Further details about the BRFSS methodology are available from the CDC [21].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIndependent Variables\u003c/h3\u003e\n\u003cp\u003eDemographic variables for all analyses included age, sex, race/ethnicity, marital status, educational level, income level, and urban/rural status. Age categories were 18\u0026ndash;24 years, 25\u0026ndash;34 years, 35\u0026ndash;44 years, 45\u0026ndash;54 years, 55\u0026ndash;64 years, and 65 years or older. Race included categories of non-Hispanic White, non-Hispanic Black, non-Hispanic American Indian/Alaska Native, Hispanic, non-Hispanic Multiracial or Other, and non-Hispanic Asian/Pacific Islander/Native Hawaiian. Marital status was categorized as married or partnered, divorced or separated, widowed, or never married. Education level was defined as less than high school, high school graduate, some college, or a college or technical school graduate. Employment status was recoded as employed (including self-employed), unemployed, or out of the workforce (i.e., homemakers, students, retirees, and individuals unable to work). Geography was defined as urban or rural, using the National Center for Health Statistics (NCHS) Urban-Rural Classification, considering large central, large fringe, medium, and small metropolitan areas in addition to micropolitan areas as urban, and noncore non-metropolitan areas as rural [22]. To account for regional differences in caregiving support, states were coded into the following regions: West (Arizona, Utah, Colorado, Texas, Oregon, Washington, Hawaii, and Idaho), Midwest (Ohio, Wisconsin, Oklahoma, and Iowa), South (Louisiana, Georgia, Mississippi, Virginia, Arkansas, Maryland, Tennessee, and Puerto Rico), and Northeast (New Hampshire, Pennsylvania, Maine, and New York). Year was separated into survey years of 2022 and 2023.\u003c/p\u003e \u003cp\u003eIndependent variables also included selected social and health behaviors. Exercise in the previous month was assessed with the following yes/no question: \u0026ldquo;During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?\u0026rdquo; The BRFSS questionnaire defined poor physical health as physical illness or injury, asking respondents: \u0026ldquo;Now thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?\u0026rdquo; Poor physical health days were dichotomized into reporting 14 or more poor physical health days per month or less than 14 poor physical health days per month [23].\u003c/p\u003e \u003cp\u003eThe main independent variable was caregiving status, which was assessed with a yes/no question: \u0026ldquo;During the past 30 days, did you provide regular care or assistance to a friend or family member who has a health problem or disability?\u0026rdquo; Individuals who answered \u0026ldquo;Yes\u0026rdquo; proceeded with the caregiving module of the BRFSS. Only versions of the BRFSS surveys used by states assessing the caregiver status question were included in the analysis, listed in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eThe caregiving module asked caregivers to select one response to the following question: \u0026ldquo;What is the main health problem, long-term illness, or disability that the person you care for has?\u0026rdquo; Caregivers could select from 14 options: arthritis or rheumatism, asthma, cancer, chronic respiratory conditions (e.g., emphysema, chronic obstructive pulmonary disorder), cognitive disorders (e.g., Alzheimer\u0026rsquo;s disease, dementia), developmental disabilities (e.g., autism, Down\u0026rsquo;s syndrome, spina bifida), diabetes, vascular issues (heart disease, hypertension, and stroke), Human Immunodeficiency Virus (HIV), mental illnesses (anxiety, depression, and schizophrenia), organ failure or diseases, substance abuse or addiction disorders, injuries, and old age or infirmity.\u003c/p\u003e\n\u003ch3\u003eDependent Variables\u003c/h3\u003e\n\u003cp\u003eThe BRFSS assessed mental health with the following question: \u0026ldquo;Now, thinking about your mental health, which includes stress, depression, and problems and emotions, for how many days during the past 30 days was your mental health not good?\u0026rdquo; Poor mental health days were then operationalized as six or more days of poor mental health per month, indicating frequent mental distress (FMD6) or fewer than six days of poor mental health per month. The FMD6 indicator has been validated against standards of mental distress (i.e., the Kessler 6 scale of mental distress) and effectively used with multiple populations [15,16,24]. The second dependent variable was whether an individual had a lifetime depression diagnosis (yes/no), assessed by the BRFSS with the following question: \u0026ldquo;(Ever told) (you had) a depressive disorder (including depression, major depression, dysthymia, or minor depression)?\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe datasets from the BRFSS were downloaded and combined into one file, reflecting the appropriate weights for each survey version. Arizona and Ohio utilized more than one survey version, so a working data set was created following the BRFSS complex sampling recommendations for their weights [25]. Missing data were retained by being recoded into other/unknown categories for each variable. Pearson\u0026rsquo;s chi-squared tests were used to compare cancer caregivers with the general population on the prevalence of each socio-demographic variable, exercise, emotional support, physical health indicator, and mental health outcomes (i.e., FMD6 and depression). Logistic regression was used to determine the odds of FMD6 or lifetime depression diagnosis by caregiver status, adjusting all models for socio-demographic covariates, physical health indicators, exercise, and emotional support. Adjusted odds ratios (aOR) and 95% confidence intervals are reported.\u003c/p\u003e \u003cp\u003eStata version 18 was used for all data cleaning, coding, and analysis. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e \u0026lt;\u0026thinsp;.05. Because this study used a publicly available dataset, the IRB of [institution name masked] deemed the project as not human subjects research.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAfter identifying states using the caregiving modules, 199,664 individuals were included in unadjusted analyses, including 3,078 cancer caregivers and 196,586 other individuals representing the general population (i.e., people without caregiving responsibilities and people who were caregivers for non-cancer conditions). For adjusted analyses, the sample sizes were 186,767 and 188,345 (FMD and depression, respectively). The cancer caregivers\u0026rsquo; total numbers from each state (Supplementary Table\u0026nbsp;1) were checked for accuracy against original year datasets and available BRFSS data from individual states, including Arizona [26,27], New York [28], Washington (Crawbuck, G., personal communication, June 16, 2025), and Wisconsin [29]. Unadjusted analyses identified differences between cancer caregivers and the general population in the prevalence of each variable. In unadjusted models, cancer caregivers were significantly more likely than the general population to be 45 years or older (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), female (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), married or partnered (\u003cem\u003ep\u003c/em\u003e =\u0026thinsp;.01), have attended or graduated from college or technical school (\u003cem\u003ep\u003c/em\u003e = .01), be unemployed (\u003cem\u003ep\u003c/em\u003e = .001), live in a rural area (\u003cem\u003ep\u003c/em\u003e=.04), and report FMD6 (\u003cem\u003ep\u003c/em\u003e \u0026lt;\u0026thinsp;.001) or a lifetime depression diagnosis (\u003cem\u003ep\u003c/em\u003e = .01) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence in socio-demographics, frequent mental distress, and a lifetime depression diagnosis, general population versus cancer informal caregivers (ICs), BRFSS 2022\u0026ndash;2023\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eSocio-demographics\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eFull population\u003c/span\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;199,664\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eGeneral population\u003c/span\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;196,586\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCancer ICs\u003c/span\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;3,078\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92,515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91,393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107,149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105,193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite (non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146,260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e143,888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack (non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI/AN (non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian (non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiracial/Other (non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20,246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20,132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19,933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25,812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25,446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29,187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36,746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76,210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried/partnered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111,610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(55.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109,718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(55.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30,469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29,996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,475\u003c/p\u003e \u003cp\u003e33,480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(7.3)\u003c/p\u003e \u003cp\u003e(23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22,165\u003c/p\u003e \u003cp\u003e33,099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(7.3)\u003c/p\u003e \u003cp\u003e(23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e310\u003c/p\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(6.9)\u003c/p\u003e \u003cp\u003e(17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49,426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48,691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college/tech school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55,162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate coll./tech school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80,928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96,528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut of workforce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92,668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91,143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise in previous month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150,639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(75.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e148,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(75.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(77.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48,588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47,923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor physical health days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 14/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e166,589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e164,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(86.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14 or more/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28,129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27,653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e174,079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(93.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e171,415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(91.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20,228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19,865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116,291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(48.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114,530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83,373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(41.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion of U.S.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83,946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82,732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48,827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48,095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47,063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19,510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequent Mental Distress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 6/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154,035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(76.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e151,919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(76.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 or more/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41,703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40,806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLifetime Depression Diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44,054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43,210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154,448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(77.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e152,234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e(78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: Combined population includes non-cancer caregivers and non-caregivers. AI/AN=American Indian \u0026amp; Alaska Native. West U.S. = AZ, UT, CO, TX, OR, WA, HI, and ID; Midwest U.S. = OH, WI, OK, IA; South U.S. = LA, GA, MS, VA, AK, MD, TN, PR; Northeast U.S. = NH, PA, ME, NY\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResults of regression analysis identified the association between caregiver status with mental health-dependent variables while controlling for physical health, exercise, and socio-demographics. The full models were statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), indicating that they could distinguish between reporting FMD and not reporting it, and between reporting a lifetime depression diagnosis and not reporting it. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the significant predictors in the logistic models for the FMD and lifetime depression diagnosis outcome variables. Cancer caregivers were significantly more likely than non-cancer caregivers to have FMD and a lifetime depression diagnosis, having approximately 69% and 22% greater odds, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of caregiver status with FMD and lifetime depression diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFMD6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDiagnosed with depression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;186,767)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;188,345)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eaOR\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eaOR\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer patient caregivers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.42\u0026ndash;2.02)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.03\u0026ndash;1.46)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.79\u0026ndash;0.96)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.90\u0026ndash;1.13)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.55\u0026ndash;0.67)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.73\u0026ndash;0.91)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.37\u0026ndash;0.46)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.58\u0026ndash;0.74)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.25\u0026ndash;0.31)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.44\u0026ndash;0.56)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.14\u0026ndash;0.17)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.22\u0026ndash;0.29)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.56\u0026ndash;1.73)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.99\u0026ndash;2.20)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite (Non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack (Non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.74\u0026ndash;0.88)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.45\u0026ndash;0.54)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI/AN (Non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.84\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.70\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian (Non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.56\u0026ndash;0.74)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.30\u0026ndash;0.41)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiracial/Other (Non-Hispanic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.03\u0026ndash;1.33)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.94\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.66\u0026ndash;0.80)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.51\u0026ndash;0.63)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.84\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.56\u0026ndash;0.78)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried/partnered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.55\u0026ndash;1.78)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.71\u0026ndash;1.96)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.20\u0026ndash;1.48)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.14\u0026ndash;1.40)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.45\u0026ndash;1.66)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.31\u0026ndash;1.50)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.94\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.87\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.84\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.79-1.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college/tech. school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.94\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.95\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate college/tech. school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.75\u0026ndash;0.95)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.81\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.66\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.32\u0026ndash;0.72)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.45\u0026ndash;1.79)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.60-2.00)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut of workforce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.15\u0026ndash;1.30)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.40\u0026ndash;1.59)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.62\u0026ndash;0.99)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.55\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.77\u0026ndash;0.91)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.80\u0026ndash;0.95)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise in previous month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.16\u0026ndash;1.31)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.20\u0026ndash;1.36)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.61\u0026ndash;1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.77\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor physical health days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 14 days/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14 or more days/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.42\u0026ndash;5.07)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.57\u0026ndash;2.94)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eU.S. Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.93\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.00-1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.95\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.98\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.77\u0026ndash;0.91)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.76\u0026ndash;0.90)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.93\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.91-1.00)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: AI/AN=American Indian \u0026amp; Alaska Native. West U.S. = AZ, UT, CO, TX, OR, WA, HI, and ID; Midwest U.S. = OH, WI, OK, IA; South U.S. = LA, GA, MS, VA, AK, MD, TN, PR; Northeast U.S. = NH, PA, ME, NY\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOther significant correlates included lack of exercise in the last month being associated with higher odds of FMD (aOR\u0026thinsp;=\u0026thinsp;1.23; 95%CI\u0026thinsp;=\u0026thinsp;1.16\u0026ndash;1.31) and lifetime depression diagnosis (aOR\u0026thinsp;=\u0026thinsp;1.28; 95%CI\u0026thinsp;=\u0026thinsp;1.20\u0026ndash;1.36), and 14 or more poor physical health days in the last 30 days being significantly positively associated with both FMD (aOR\u0026thinsp;=\u0026thinsp;4.73; 95%CI\u0026thinsp;=\u0026thinsp;4.42\u0026ndash;5.07) and a lifetime depression diagnosis (aOR\u0026thinsp;=\u0026thinsp;2.75; 95%CI\u0026thinsp;=\u0026thinsp;2.57\u0026ndash;2.94). Individuals from rural areas had significantly lower odds of FMD (aOR\u0026thinsp;=\u0026thinsp;0.84; 95%CI\u0026thinsp;=\u0026thinsp;0.77\u0026ndash;0.91) and a lifetime depression diagnosis (aOR\u0026thinsp;=\u0026thinsp;0.87; 95%CI\u0026thinsp;=\u0026thinsp;0.80\u0026ndash;0.95) than individuals from urban areas. Additionally, individuals from the Northeast region of the U.S. had significantly lower odds of FMD (aOR\u0026thinsp;=\u0026thinsp;0.84; 95%CI\u0026thinsp;=\u0026thinsp;0.77\u0026ndash;0.91) and a lifetime depression diagnosis (aOR\u0026thinsp;=\u0026thinsp;0.83; 95%CI\u0026thinsp;=\u0026thinsp;0.76\u0026ndash;0.90) than those from the Western region. Women had significantly higher odds of FMD (aOR\u0026thinsp;=\u0026thinsp;1.64; 95%CI\u0026thinsp;=\u0026thinsp;1.56\u0026ndash;1.73) or a lifetime depression diagnosis (aOR\u0026thinsp;=\u0026thinsp;2.09; 95%CI\u0026thinsp;=\u0026thinsp;1.99\u0026ndash;2.20).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis population-based analysis of BRFSS data from 24 states examined whether cancer caregivers have poorer mental health outcomes than the general population, after adjusting for covariates. Cancer caregivers had several significant unadjusted differences with the general population, and they had significantly higher odds of FMD and a lifetime depression diagnosis than the general population in the adjusted models, underscoring the persistent burden associated with cancer caregiving.\u003c/p\u003e \u003cp\u003eThe stronger association observed for cancer caregivers having higher odds of FMD versus lifetime depression diagnosis is notable, especially given that FMD reflects distress in the last 30 days, and lifetime depression diagnosis captures a historical clinical diagnosis. This may reflect ongoing situational stress related to caregiving burden rather than pre-existing depression, or it could reflect underdiagnosis of depression among caregivers or barriers to accessing mental healthcare. The results here align with the Cancer Family Caregiving Experience Model, which conceptualizes caregiving as a dynamic stress process leading to psychological outcomes [20].\u003c/p\u003e \u003cp\u003eThis study found that cancer caregivers have a higher unadjusted prevalence of poor mental health and higher odds of poor mental health days than the general populations, which echoed other studies\u0026rsquo; findings [30\u0026ndash;32]. Other research studies contrasting caregivers and non-caregivers [33\u0026ndash;35] have similarly identified that caregivers have elevated rates of poor mental health outcomes. Yet, other studies comparing caregivers with non-caregivers have found more modest differences or have suggested that caregiving does not necessarily lead to poorer mental health outcomes, although these studies often used different outcome measures, such as life satisfaction [36\u0026ndash;38]. Heterogeneity in caregiving experiences also likely explains these differences. For instance, caregivers caring for patients with aggressive cancers such as pancreatic cancer often report worse psychological outcomes compared to caregivers caring for patients with other types of cancer, such as breast [39\u0026ndash;41]. Additionally, a recent analysis of BRFSS data from 2015\u0026ndash;2016 to 2021\u0026ndash;2022 identified an increase in FMD among both caregivers and the population as a whole [42], a broader trend that may partially explain some differences in our findings [43]. Nonetheless, the persistence of disparities after adjusting for covariates suggests that caregiving contributes to psychological strain. These mixed findings also suggest that future caregiver studies should account for differences in patient acuity and prognosis.\u003c/p\u003e \u003cp\u003eSimilarly, cancer caregivers in this study had higher odds of reporting a lifetime depression diagnosis, consistent with prior literature demonstrating elevated rates of depressive disorders among cancer caregivers [44,45]. However, findings across studies have not been consistent, with some demonstrating smaller differences between caregivers and non-caregivers or no clear association between caregiving and depression diagnosis [36,38]. This variability in findings reflects differences in measurement (e.g., lifetime diagnosis versus current depressive symptoms) or in access to mental healthcare across samples. Lifetime depression captures a historical clinical diagnosis rather than current distress, and it may be less sensitive to the evolving stressors of caregiving. These findings highlight the need to account for patient acuity, prognosis, caregiver burden, and caregiving intensity in future studies.\u003c/p\u003e\n\u003ch3\u003eImplications\u003c/h3\u003e\n\u003cp\u003eAltogether, these results indicate that cancer caregivers require interventions to improve their physical and psychological health. Such interventions should include bolstering components of the stress process of caregivers, including addressing primary stressors such as care demands and patient factors, an appraisal of needs, and cognitive-behavioral responses such as coping and self-care to lower the level of burden and distress on the caregiver, and addressing secondary stressors such as schedule, financial challenges, and fatigue. The findings here echo those of other studies showing lower mental and physical well-being in cancer caregivers, especially at the end of a cancer patient\u0026rsquo;s life [9,10]. Further, the emotional needs of cancer caregivers may change over the trajectory of the patient\u0026rsquo;s illness, especially if treatment is ineffective or a prognosis worsens [10], suggesting that oncology and other teams vary approaches with caregivers throughout these changes and ensure that caregivers are kept informed and involved in decision making for the patient\u0026rsquo;s care, including anticipatory guidance [2,9] and attention to their mental health needs .\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eDespite the strengths of this analysis, there are limitations. BRFSS data utilize self-reported information, which introduces recall bias and bias due to social desirability, and the measures of mental distress are not caregiving-specific. Additionally, the BRFSS depression question assesses any lifetime depressive diagnosis and does not distinguish between minor and major depressive conditions. Also, comorbid conditions of individuals receiving informal caregiving support could not be assessed in the single-item measure of the BRFSS, nor could the mental and physical health of the caregiver before becoming a caregiver.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study fills an important gap in the literature with data supporting that poor mental health outcomes are pervasive among U.S. cancer caregivers, identifying associated factors with mental health outcomes. The results of this study can inform the public health approach to health promotion by determining further research and interventions to identify relevant issues and ultimately address cancer caregivers\u0026rsquo; mental health. Future studies should assess caregiving intensity, cancer type, trajectories of stress over time, the interaction of multiple patient comorbidities, in order to develop tailored interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe National Cancer Institute of the National Institutes of Health supported this work (T32CA117865; Champion/Mosher). Support for this work also came from a research award from the National Institute of Mental Health (DP2MH129967; PI Blosnich)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Data collection and analysis were performed by Jeanne Ward under the oversight of John Blosnich. The first draft of the manuscript was written by Jeanne Ward, and all authors commented on previous versions. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData used are publicly available at https://www.cdc.gov/brfss/index.html\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMolassiotis A, Wang M. Understanding and supporting informal cancer caregivers. Curr Treat Options Oncol. 2022;23(4):494\u0026ndash;513.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorthouse L, Williams A-l, Given B, et al. Psychosocial care for family caregivers of patients with cancer. J Clin Oncol. 2012;30(11):1227\u0026ndash;1234.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Alliance for Caregiving. Cancer caregiving in the U.S. 2016 [Feb. 27, 2025]. Available from: https://www.caregiving.org/wp-content/uploads/2022/11/CancerCaregivingReport_FINAL_June-17-2016.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmerican Cancer Society. Cancer Facts \u0026amp; Figs.\u0026nbsp;2025 2025 [Feb. 27, 2025]. Available from: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2025/2025-cancer-facts-and-figures-acs.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiegel RL, Kratzer TB, Wagle NS, et al. Cancer statistics, 2026. Ca Cancer J Clin. 2026;76(1):e70043.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLitzelman K, Blanch-Hartigan D, Lin CC, et al. Correlates of the positive psychological byproducts of cancer: Role of family caregivers and informational support. Palliat Support Care. 2017;15(6):693\u0026ndash;703.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Kruk SR, Butow P, Mesters I, et al. Psychosocial well-being and supportive care needs of cancer patients and survivors living in rural or regional areas: A systematic review from 2010 to 2021. Support Care Cancer. 2022;30(2):1021\u0026ndash;1064.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian Y, Kent EE. Gender differences in the association between unmet support service needs and mental health among American cancer caregivers. Support Care Cancer. 2022;30(6):5469\u0026ndash;5480.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButow PN, Price MA, Bell ML, et al. Caring for women with ovarian cancer in the last year of life: A longitudinal study of caregiver quality of life, distress and unmet needs. Gynecol Oncol. 2014;132(3):690\u0026ndash;697.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodenbach RA, Norton SA, Wittink MN, et al. When chemotherapy fails: Emotionally charged experiences faced by family caregivers of patients with advanced cancer. Patient Educ Couns. 2019;102(5):909\u0026ndash;915.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGuire LC, Strine TW, Vachirasudlekha S, et al. Modifiable characteristics of a healthy lifestyle and chronic health conditions in older adults with or without serious psychological distress, 2007 Behavioral Risk Factor Surveillance System. Int J Public Health. 2009;54 Suppl 1:84\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiddell CB, Spees LP, Petermann V, et al. Financial assistance processes and mechanisms in rural and nonrural oncology care settings. JCO Oncology Practice. 2022;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRatnapradipa KL, Ranta J, Napit K, et al. Qualitative analysis of cancer care experiences among rural cancer survivors and caregivers. The Journal of Rural Health. 2022;38(4):876\u0026ndash;885.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCree RA. Frequent mental distress among adults, by disability status, disability type, and selected characteristics\u0026mdash;United States, 2018. MMWR Morbidity and mortality weekly report. 2020;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Academies of Sciences E, Medicine, Health, et al. Leading health indicators 2030: advancing health, equity, and well-being. Leading health indicators 2030: advancing health, equity, and well-being. Washington (DC): National Academies Press (US); 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBossarte RM, He H, Claassen CA, et al. Development and validation of a 6-day standard for the identification of frequent mental distress. Soc Psychiatry Psychiatr Epidemiol. 2011;46(5):403\u0026thinsp;\u0026minus;\u0026thinsp;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCree RA, Okoro CA, Zack MM, et al. Frequent mental distress among adults, by disability status, disability type, and selected characteristics \u0026mdash;United States, 2018. MMWR Morbidity and Mortality Weekly Report. 2020;69(36):1238\u0026ndash;1243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMonahan Z, Shores D, Mack A, et al. Prevalence of depression among caregivers based on the condition and relationship of care recipient. J Affect Disord. 2023;340:442\u0026ndash;447.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLongacre ML, Brewer B, Hubbard A, et al. Caregiver health by context: Moderating effects of mental health and health behaviors. West J Nurs Res. 2020;43(7):622\u0026ndash;630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFletcher BS, Miaskowski C, Given B, et al. The cancer family caregiving experience: An updated and expanded conceptual model. Eur J Oncol Nurs. 2012;16(4):387\u0026ndash;398.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Behavioral Risk Factor Surveillance System 2024 [December 13, 2024]. Available from: Behavioral Risk Factor Surveillance System,\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. NCHS Urban-Rural Classification Scheme for Counties 2024 [February 3, 2025]. Available from: https://www.cdc.gov/nchs/data-analysis-tools/urban-rural.html\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDwyer-Lindgren L, Mackenbach JP, van Lenthe FJ, et al. Self-reported general health, physical distress, mental distress, and activity limitation by US county, 1995\u0026ndash;2012. Population Health Metrics. 2017;15(1):16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNew Mexico Department of Health. Adult frequent mental distress by year, New Mexico and U.S., 2004 to 2021 2023. Available from: https://ibis.doh.nm.gov/indicator/view/MentHlthAdult.Year.NM_US.html?\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Complex sampling weights and preparing 2022 BRFSS module data for analysis 2023 [June 9, 2025]. Available from: https://www.cdc.gov/brfss/annual_data/2022/pdf/Complex-Sampling-Weights-and-Preparing-Module-Data-for-Analysis-2022-508.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArizona Department of Health Services. Arizona 2022 Codebook Report Version 1 Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.azdhs.gov/documents/preparedness/public-health-statistics/behavioral-risk-factor-surveillance/code-book/az22code-llcp-v1.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArizona Department of Health Services. Arizona 2022 Codebook Reprot Version 2 Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.azdhs.gov/documents/preparedness/public-health-statistics/behavioral-risk-factor-surveillance/code-book/az22code-llcp-v2.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNew York State Department of Health. New York State Behavioral Risk Ractor Surveillance Survey: 2023 2025 [June 26, 2025]. Available from: https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-Survey-2023/tk4g-wdfe/about_data\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWisconsin Department of Health Services. Wisconsin 2022 Codebook Report Behavioral Risk Factor Surveillance System 2023 [June 26, 2025]. Available from: https://www.dhs.wisconsin.gov/stats/2022-wi-brfss-codebook.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakraborty R, Jana A, Vibhute VM. Caregiving: A risk factor of poor health and depression among informal caregivers in India- a comparative analysis. BMC Public Health. 2023;23(1):42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMosher CE, Bakas T, Champion VL. Physical health, mental health, and life changes among family caregivers of patients with lung cancer. Oncology Nursing Forum. 2013;40(1):53\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan YC, Lin YS. Systematic Review and Meta-Analysis of Prevalence of Depression Among Caregivers of Cancer Patients. Front Psychiatry. 2022;13:817936.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanson P, Willeke K, Zaibert L, et al. Mortality, morbidity and health-related outcomes in informal caregivers compared to non-caregivers: A systematic review. Int J Environ Res Public Health. 2022;19(10):5864.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerglund E, Lytsy P, Westerling R. Health and wellbeing in informal caregivers and non-caregivers: A comparative cross-sectional study of the Swedish general population. Health and Quality of Life Outcomes. 2015;13(1):109.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson LA, Edwards VJ, Pearson WS, et al. Adult caregivers in the United States: characteristics and differences in well-being, by caregiver age and caregiving status. Prev Chronic Dis. 2013;10:E135.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoth DL, Fredman L, Haley WE. Informal caregiving and its impact on health: A reappraisal from population-based studies. Gerontologist. 2015;55(2):309\u0026ndash;319.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Camargos MG, Paiva BSR, de Oliveira MA, et al. An explorative analysis of the differences in levels of happiness between cancer patients, informal caregivers and the general population. BMC Palliat Care. 2020;19(1):106.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinquart M, S\u0026ouml;rensen S. Differences between caregivers and noncaregivers in psychological health and physical health: A meta-analysis. Psychol Aging. 2003;18(2):250.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson T, Mitchell G, Prue G, et al. The psychosocial impact of pancreatic cancer on caregivers: a scoping review. BMC Cancer. 2025;25(1):511.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChong E, Crowe L, Mentor K, et al. Systematic review of caregiver burden, unmet needs and quality-of-life among informal caregivers of patients with pancreatic cancer. Support Care Cancer. 2022;31(1):74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;z\u0026ouml;nder \u0026Uuml;nal I, Ordu C. Decoding Caregiver Burden in Cancer: Role of Emotional Health, Rumination, and Coping Mechanisms. Healthcare (Basel). 2023;11(19).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKilmer G. Changes in health indicators among caregivers\u0026mdash;United States, 2015\u0026ndash;2016 to 2021\u0026ndash;2022. MMWR Morbidity and Mortality Weekly Report. 2024;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUdupa NS, Twenge JM, McAllister C, et al. Increases in poor mental health, mental distress, and depression symptoms among U.S. adults, 1993\u0026ndash;2020. J Mood Anxiety Disord. 2023;2:100013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrevino KM, Prigerson HG, Maciejewski PK. Advanced cancer caregiving as a risk for major depressive episodes and generalized anxiety disorder. Psycho-Oncology. 2018;27(1):243\u0026ndash;249.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y-C, Lin Ya-S. Systematic Review and Meta-Analysis of Prevalence of Depression Among Caregivers of Cancer Patients [Systematic Review]. Front Psychiatry. 2022;Volume 13\u0026ndash;2022.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Mental health, caregiving, cancer care, health promotion, public health, BRFSS","lastPublishedDoi":"10.21203/rs.3.rs-9181837/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9181837/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose: Informal caregivers (i.e., caregivers) of cancer patients are increasing, significantly influencing patient outcomes. Caregivers face mental health issues such as depression and anxiety and factors related to caregiver burden. This study sought to elucidate whether the mental health of cancer caregivers differs from that of the general population.\u003c/p\u003e\n\u003cp\u003eMethods: Data from 2022 and 2023 Behavioral Risk Factor Surveillance Surveys (BRFSS) for 24 states including the optional caregiving module were analyzed to investigate factors associated with mental health and depression, comparing cancer caregivers (n=3,078) to the general population (n=196,586). Logistic regressions identified factors associated with frequent mental distress days (FMD; \u003cu\u003e\u0026gt;\u003c/u\u003e6 days of poor mental health in the last 30 days) or a lifetime depression diagnosis. Predictors included cancer caregiver status, reporting \u003cu\u003e\u0026gt;\u003c/u\u003e14 poor physical health days monthly, exercise in the previous month, age, sex, marital status, education, employment status, rural/urban status, U.S. region, and year.\u003c/p\u003e\n\u003cp\u003eResults: In unadjusted comparisons, caregivers were significantly more likely than the general population to be female, older, married/partnered, have attended college, unemployed, live rurally, and report FMD or a depression diagnosis. After adjusting for sociodemographics, year, U.S. region, physical health, and exercise, caregivers were significantly more likely than the general population to have FMD (aOR=1.69, 95%CI=1.42-2.02) or a lifetime depression diagnosis (aOR=1.22, 95%CI=1.03-1.46).\u003c/p\u003e\n\u003cp\u003eConclusion: Future research should address risk factors associated with mental health, identifying the most at-risk caregivers for targeted interventions. These findings support mental health screening of caregivers in oncology and primary care settings, especially during high-burden periods such as treatment initiation.\u003c/p\u003e","manuscriptTitle":"Poor mental health days and depressive disorders by informal cancer patient caregiver status: BRFSS 2022-23","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 05:57:24","doi":"10.21203/rs.3.rs-9181837/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-05T15:08:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T15:06:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-02T05:17:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2026-03-20T20:18:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1458f99e-6a6f-4e93-9c3a-f284d2065869","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"5","date":"2026-05-05T15:08:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T15:06:24+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T05:57:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 05:57:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9181837","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9181837","identity":"rs-9181837","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}