Patterns of Dietary Quality, Physical Activity, and Sleep Duration among Cancer Survivors and Caregivers

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Badger, Thaddeus WW Pace, Michael A. Grandner, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4271736/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Health behaviors such as fruit and vegetable intake (FVI), moderate-to-vigorous physical activity (MVPA), and sleep duration are associated with cancer-related and general health outcomes. This analysis examined to what degree FVI, MVPA, and sleep co-occur among cancer survivors and informal cancer caregivers and identified sociodemographic and clinical correlates of health behavior engagement. Using data from the Health Information National Trends Survey (HINTS), an exploratory latent profile analysis (LPA) was conducted among a nationally representative sample of those self-reporting a history of cancer or identifying as a cancer caregiver. The LPA model was fit with continuous variables for daily self-reported FVI (servings/d), MPVA (minutes/d) and sleep duration (hours/d). Multinomial logistic regression models were used to predict profile membership based on current age, education, relationship status, income, rurality, body mass index (BMI), other health behaviors, and role (survivor or caregiver). Four health behavior profiles were identified (Least Engaged–Sedentary, Least Engaged–Inactive, Moderately Engaged, and Highly Engaged). The largest profile membership was Least-Engaged Sedentary, capturing 37% of the sample. Profiles were most distinguished by MVPA with the lowest variance in sleep duration. Health behavior profile membership was significantly associated with current age, relationship status, education, income, rurality, alcohol use, self-efficacy, psychological distress, BMI, and cancer type. This study identified that, in a nationally representative sample, cancer survivors and cancer caregivers who reported more FVI also often reported greater MVPA and longer sleep duration. Health behavior profiles and sociodemographic correlates can help identify for whom health behavior interventions may be of greatest benefit. health-related behaviors cancer survivorship cancer caregiving HINTS latent profile analysis Figures Figure 1 Introduction The more than 22 million cancer survivors living in the United States by 2032 (Office of Cancer Survivorship, 2022 ) are at high risk for late effects, such as cancer recurrence, secondary cancers, chronic comorbidities, and mortality (Leach et al., 2015 ; Sogaard et al., 2013 ). Cancer survivors include everyone with a history of cancer from the time of diagnosis through end of life. Engaging in healthful lifestyle behaviors such as eating a high-quality diet, being physically active, and getting sufficient sleep have been independently associated with reduced all-cause and disease-specific mortality (del Pozo Cruz et al., 2020 ; Xiao et al., 2014 ). The American Cancer Society (ACS) has published nutrition and physical activity recommendations for adult survivors of cancer to promote overall health (Rock et al., 2022 ). These include consuming a plant-based high-fiber diet with a variety of colorful fruits and vegetables and engaging in regular moderate-to-vigorous physical activity. Although cancer-specific sleep recommendations have not been released, the American Academy of Sleep Medicine and Sleep Research Society recommend that adults sleep seven to nine hours per night for optimal health (Watson et al., 2015 ). Importantly, these health behaviors appear to be interrelated. Insufficient sleep is associated with decreased leptin and elevated ghrelin levels, which can cue increased food intake (Spiegel et al., 2004 ). Decreased sleep is also associated with greater intake of processed foods and high-sugar refined foods (Godos et al., 2021 ) and less physical activity (Mead et al., 2019 ; Semplonius & Willoughby, 2018 ). Level of physical activity can influence sleep quality (Wang & Boros, 2021 ) and dietary quality (Gillman et al., 2001 ). Similarly, dietary quality impacts the energy available for physical activity, which in turn can affect sleep (Dolezal et al., 2017 ). This interrelationship has been theorized to be due to spillover effects, wherein engagement in one behavior influences engagement in others, although the evidence supporting this is mixed (Pan et al., 2022 ; Sarma et al., 2019 ). Thus, the degree to which these spillover effects occur in the cancer population remains unclear. Increasing attention has been paid to the relationships among multiple co-occurring health behaviors in cancer survivors and their collective impact on health outcomes. Glasgow and colleagues (Glasgow et al., 2022 ) categorized a sample of 856 survivors participating in a national survey as either adherent or non-adherent to six health behavior recommendations (i.e., aerobic physical activity, strength training, fruit and vegetable consumption, sleep duration and quality, and sedentary time). When assessed individually and as a composite score, individuals categorized as adherent reported better psychological health. This work identified which behaviors are relevant to psychological health in a nationally representative sample. However, an important limitation was the analytic approach, which precluded identification of patterns of health behavior engagement. To address this gap, research focused on multiple health behaviors is moving toward person-centered analytic approaches such as latest class analysis (LCA). Olson and colleagues (Olson et al., 2023 ) evaluated lifestyle behaviors of 591 cancer survivors and identified three patterns based on physical activity, diet, smoking, and sleep. By utilizing LCA, they were able to identify naturally occurring patterns of behaviors and evaluate their relationships with health outcomes. However, prior to conducting the LCA the authors dichotomized each behavior, much like Glasgow and colleagues (Glasgow et al., 2022 ). This approach can result in a loss of information that interferes with identification of more nuanced patterns of engagement. Similarly, Fong and colleagues (Fong et al., 2023 ) conducted an LCA to identify patterns based on a combination of categorical (i.e., BMI, physical activity, smoking status, alcohol consumption, time since last physician visit) and continuous (i.e., dietary intake, sun safety) behaviors among 661 participants with cancer. Notably, sleep was absent. A gap remains in generalizability to a broader population of cancer survivors and how dietary quality, physical activity, and sleep may co-occur along a continuum. Although health behavior patterns have been explored among cancer survivors, informal cancer caregivers (e.g., family members, friends) have generally been excluded. Informal caregivers provide a significant amount of unpaid cancer care and experience documented adverse health outcomes (Perkins et al., 2013 ; Pinquart & Sörensen, 2003 ; van Ryn et al., 2011 ; Yun et al., 2005 ). Although evidence regarding the impact of cancer caregiving on health behaviors is mixed (Litzelman et al., 2018 ; Ross et al., 2013 ; Secinti et al., 2022 ), the health behaviors of cancer survivors and their caregivers are interrelated (Badr et al., 2019 ; Kiecolt-Glaser & Wilson, 2017 ). It is possible that by considering both survivors and caregivers, additional information could emerge regarding the prevalence, composition, and impact of health behavior patterns in the cancer context. The present study had two aims. The first was to explore how dietary quality, physical activity, and sleep co-occur among a nationally representative sample of cancer survivors and informal cancer caregivers. To achieve this, we used a person-centered analytic approach to identify naturally occurring patterns of health behavior engagement. The second aim was to determine the association of sociodemographic and clinical variables to health behavior patterns to facilitate identification of individuals who may particularly benefit from health promotion intervention. Given the exploratory nature of this work, there were no a priori hypotheses. Methods Study Sample Data were derived from the National Cancer Institute (NCI) Health Information National Trends Survey (HINTS) database. HINTS is a nationally representative, cross-sectional survey of the US non-institutionalized adult population. Data are collected annually via mail and telephone (Finney Rutten et al., 2020 ; Nelson et al., 2004 ). Datasets and methodological documentation are publicly available for download (U.S. Department of Health and Human Services, 2020 ). Participants who completed the HINTS 5 Cycle 3 survey (2019; response rate: 30.3%) in English or Spanish were included in the present analysis. Although more recent data have been fielded for HINTS, the 2019 survey is the most recent survey that included all three targeted health behaviors in a singular dataset. The analytical sample was limited to individuals with a self-reported history of cancer (“ Have you ever been diagnosed with having cancer? ”; n = 856) or those who reported providing unpaid care to an individual with cancer (“ Are you currently caring for or making health care decisions for someone with a medical, behavioral, disability, or other condition?” Caregiving condition: Cancer ; n = 75). Fifteen respondents reported both having a history of cancer and being a current informal caregiver and were categorized as “Dual Role” (weighted N = 711,464). Those who reported a history of cancer with no informal caregiving responsibilities were categorized as “Cancer Survivor Role” (n = 841, weighted N = 22,754,490) and those who reported current informal cancer caregiving without a cancer diagnosis were categorized as “Caregiver Role” (n = 60, weighted N = 2,895,557). This study did not require Institutional Review Board approval because it used publicly available deidentified data. Health Behaviors Fruit and Vegetable Intake. Fruit and vegetable intake (FVI) were assessed using the following questions: “ About how many cups of fruit (including 100% pure fruit juice) do you eat or drink each day? ” and “ About how many cups of vegetables (including 100% pure vegetable juice) do you eat or drink each day? ” Survey respondents were provided with approximate serving sizes and could select “None”, “1/2 cup or less”, “1/2 cup to 1 cup”, “1 to 2 cups”, “2 to 3 cups”, “3 to 4 cups”, or “4 or more cups”. FYI was recoded as the maximum possible within each response category (e.g., “1/2 cup to 1 cup” was coded as 1 cup), summed, and analyzed continuously as a conservative estimate of total daily servings of fruit and vegetables. Physical Activity. Weekly minutes of moderate-to-vigorous physical activity (MVPA) was calculated from responses to two questions: “In a typical week, how many days do you do any physical activity or exercise of at least moderate intensity, such as brisk walking, bicycling at a regular pace, and swimming at a regular pace (do not include weightlifting)?” and “On the days that you do any physical activity or exercise of at least moderate intensity, how long do you typically do these activities?”. Daily minutes of physical activity were calculated by dividing the weekly minutes by seven, and the resulting values were log transformed for normality prior to analysis. Sleep Duration. Average nightly hours of sleep over the previous week were self-reported in response to the question “ During the past 7 days, how many hours of sleep did you get on average per night? ”. Sociodemographic and Clinical Covariates Sociodemographic and clinical information was self-reported. Sociodemographic characteristics included age, sex, race/ethnicity, geographic area (rural vs. urban designation), annual household income, household size, relationship status, and educational attainment. Cancer history included age at diagnosis, years since diagnosis (calculated from age at survey completion and age at diagnosis), family history of cancer, and cancer type. Other health characteristics included perceived general health (excellent to poor), health insurance coverage, comorbid conditions (diabetes, high blood pressure, heart disease, lung disease, or depression), body mass index (BMI; calculated as weight (kg)/height (m 2 ), and BMI category (normal weight- 18.5–24.9 kg/m 2 , overweight- 25.0-29.9 kg/m 2 , and obese ≥ 30.0 kg/m 2 ) (Weir & Jan, 2020 ). Smoking status (current, former, never) and alcohol use (none, moderate, heavy) (Rock et al., 2020 ) were also included. Self-efficacy and psychological distress, behavioral covariates in HINTS previously associated with health behaviors (Glasgow et al., 2022 ; Skiba et al., 2021 ), were also included. Self-efficacy was dichotomized into low and high, consistent with previous analyses (Fleary et al., 2019 ; Niederdeppe & Levy, 2007 ; Skiba et al., 2021 ), from the response to the question: “Overall, how confident are you about your ability to take good care of your health?” while Patient Health Questionnaire-4 (PHQ-4) scores were used to categorize psychological distress as: No Distress (0–2), Mild (3–5), Moderate (6–8) and Severe (9–12), consistent with previous analyses (Glasgow et al., 2022 ; Kroenke et al., 2009 ). Statistical Analysis Data were managed according to NCI guidance (Moser et al., 2013 ). Survey weights provided by HINTS were applied using the Taylor linearization replication method to provide population level estimates. Differences in sociodemographic characteristics, cancer history, and health characteristics stratified to compare cancer survivors and caregivers were assessed using Chi-square tests for categorical variables and t -tests for continuous variables. We conducted an exploratory latent profile analysis (LPA) to identify groups of individuals with similar co-occurring health behavior patterns. We fit an LPA model with one categorical latent variable and three observed continuous variables (FVI, MVPA, and sleep) following best practices for model assumptions, estimation, selection, and interpretation (Masyn, 2013 ). Profiles were added iteratively to determine the best model fit. The optimal number of profiles was determined by interpretation of Akaike’s information criterion (AIC), Bayesian information criterion (BIC), global entropy, and clinical relevance (Nylund et al., 2007 ). Profiles were further evaluated for interpretability and sample size, and those containing < 5% of the sample were deemed spurious. Profile membership was assigned based on highest probability of belonging. LPA models were not stratified based on role (survivor/caregiver), which was instead evaluated as a predictor of profile membership. Standardized profile means ( z -scores) of the indicators were calculated to visualize differences among profiles. Final profiles were used as a categorical outcome variable in subsequent multinomial logistic regression analyses to predict profile membership based on sociodemographic and health characteristics. Current age, age at diagnosis, years since diagnosis, and number of comorbid conditions were categorized prior to analysis to facilitate interpretation. Analytical samples were restricted to complete cases, and individuals with missing responses for any covariate were excluded. An alpha level of 5% was considered statistically significant. All analyses were completed in STATA 18.0 (StataCorp LLC, College Station, TX, USA). Sensitivity Analysis. A sensitivity analysis was conducted to facilitate interpretation in comparison to prior research (Fong et al., 2023 ; Glasgow et al., 2022 ; Olson et al., 2023 ). To determine the proportion of respondents in each profile meeting established health behavior recommendations, responses were dichotomized as meeting or not meeting recommendations according to the following cut-points: 1) FVI: ≥ 2 cups of fruit and ≥ 3 cups of vegetables per day (Rock et al., 2020 ); 2) MVPA: ≥150 minutes per week (Rock et al., 2020 ); and 3) Sleep: ≥7 hours per night (Hirshkowitz et al., 2015 ). Adherence to established guidelines by profile were compared using Pearson’s chi-squared tests of independence with Bonferroni adjustment for multiple comparisons. Results Descriptive Statistics Sample sociodemographic and clinical characteristics are summarized in Table 1 . All responses included in the present analysis were completed using the English HINTS survey, as no respondents endorsing a history of cancer or cancer caregiving completed the survey in Spanish. Cancer survivors were on average older than cancer caregivers (63.5 ± 15.9 and 56.2 ± 12.8 years, respectively). The most common cancer diagnosis was cutaneous (29%). Most cancer caregivers reported providing care to either a parent (37.9%) or partner (18.2%). Most respondents identified as non-Hispanic (84%) and resided in urban areas (83%). About half reported never smoking (54%) and no current alcohol use (46%), while 71% were either overweight or obese and reported one or more chronic comorbid health conditions. Identified Health Behavior Profiles Four health behavior profiles were identified (Fig. 1): Least Engaged–Sedentary , Least Engaged–Inactive , Moderately Engaged , and Highly Engaged . The Least Engaged–Sedentary profile was characterized by low engagement overall and no reported MVPA. Comparatively, the Least Engaged–Inactive profile was characterized by low engagement overall but minimal reported MVPA and lower FVI. The Moderately Engaged profile was characterized by moderate MVPA and FVI, and lower average sleep duration. The Highly Engaged profile was characterized by elevated engagement across health behaviors. Profiles were most distinguished by mean MVPA ( Table 2 ). The largest profile group was Least Engaged–Sedentary with 37% of the sample. Associations of Profile Membership and Sociodemographic and Health Characteristics Profile membership was significantly associated with sociodemographic and health characteristics ( Table 3 ). All models used the Least Engaged–Sedentary profile as the reference group. Respondents in the Least Engaged–Inactive profile were significantly more likely to be a caregiver but less likely to be aged ≥ 65 years, identify as Hispanic, and have greater than a high school education. Respondents in the Moderately Engaged profile were significantly more likely to have higher annual household income, moderately use alcohol, and have high health self-efficacy. They were also significantly less likely to report an “other” cancer diagnosis, be partnered, have greater than a high school education, live in a rural setting, report fair-to-poor general health, be obese, and report mild psychological distress. Respondents in the Highly Engaged profile were significantly more likely to be a caregiver, moderately use alcohol, and have high health self-efficacy. They were also significantly less likely to be aged ≥ 65 years, report a gynecologic cancer diagnosis, and have greater than a high school education. No other sociodemographic or health characteristics were significantly associated with profile membership. Sensitivity Analysis - Profile Adherence to Recommendations Information about adherence to recommendations can be found in Supplemental Materials . Across profiles, the least adhered to behavior was FVI followed by MVPA, while sleep had the greatest observed levels of adherence. Post-hoc analyses indicated that percent adherence to FVI and MVPA recommendations were significantly different across profiles. Discussion We observed four distinct patterns of health behavior co-occurrence among a nationally representative sample of cancer survivors and informal cancer caregivers. In general, respondents who reported greater FVI also reported greater MVPA and sleep duration. Likewise, participants reporting lower FVI had lower MVPA and sleep duration. Approximately 20% of the sample was in the Highly Engaged profile, indicating that more than 80% warrant some degree of intervention to support dietary quality, physical activity, and/or sleep behaviors. We also identified that role, cancer type, self-efficacy, age, alcohol use, and educational attainment were associated with profile membership. This information could help identify which individuals may require more or less intensive health behavior intervention for maximum benefit. Our results were similar to Olson and colleagues’ (Olson et al., 2023 ) finding that most survivors had problems with physical activity and diet, with or without sleep difficulties, and that those with these challenges were less likely to report high health-related quality of life. Our results are also consistent with their finding that the most engaged were younger and had a lower BMI. However, unlike these authors, we found that MVPA had the greatest variance across profiles while they identified sleep as the key differentiating behavior. This difference may be due to their categorization of variables prior to analysis, or because their profiles were also indicated by smoking status. Although Olson and colleagues did not evaluate ethnicity or rurality, we found that rural-dwelling respondents were least likely to be in the Moderately Engaged profile. This is consistent with the broader cancer survivorship literature, suggesting that greater efforts may be required to promote health behavior engagement among rural-dwelling cancer survivors (Werts et al., 2023 ). Regarding inclusion of informal cancer caregivers, qualitative evidence has suggested that including an informal caregiver in interventions may help survivors engage in healthful behaviors (Skiba et al., 2022 ). However, dyadic health behavior interventions developed specifically with the well-being of both the cancer survivor and the informal caregiver in mind remain limited (Bisht et al., 2023 ). To date, most of this work has focused on physical activity (Song et al., 2023 ), diet (Xu et al., 2023 ), weight-loss (Demark-Wahnefried et al., 2023 ), or symptom management (Crane et al., 2021 ), or has excluded non-spousal caregivers (Carmack et al., 2021 ; Kim et al., 2023 ; Winters-Stone KM, 2016). Given the demonstrated interrelationship between survivor-caregiver health behaviors (Badr et al., 2019 ; Kiecolt-Glaser & Wilson, 2017 ), more interventional research is warranted that includes diverse cancer survivor-caregiving relationship dynamics and targets multiple health behaviors. Previous studies have identified patterns and correlates of health behaviors respective to current recommendations (Fong et al., 2023 ; Glasgow et al., 2022 ; Olson et al., 2023 ). Such an approach is important, as higher adherence to health behavior guidelines is associated with lower cancer incidence and mortality (Kohler et al., 2016 ). However, simply categorizing behaviors as adherent or non-adherent runs the risk of missing individuals who are close to the cut-off but may need just a little more support to cross the threshold into adherence. Our use of a person-centered analysis that considered three behaviors on a continuous scale allowed for the inclusion of this information. For example, we found that those in the Moderately Engaged profile were, on average, consuming one less serving of fruits and vegetables and engaging in eight fewer minutes of MVPA per day than guidelines recommend. Although these individuals may benefit from health behavior intervention, they are likely to need much less intensive intervention than the participants in either of the Least Engaged profiles. Had we categorized behaviors as adherent and non-adherent prior to analysis, we would not have identified this pattern, and in turn our conclusions may have encouraged inefficient application of health behavior support. Although we included three health behaviors as indicators of profile membership in our analysis, cancer-specific guidelines were available for only two. This is likely because, historically, sleep has been underrepresented in cancer survivorship research relative to dietary quality and physical activity. Interestingly, we also found that sleep had the lowest variance across profiles. However, even this low variance corresponded to a 33 minute per night difference in sleep duration between the profile with the lowest average sleep ( Moderately Engaged ) compared to highest ( Highly Engaged ). The clinical relevance of this difference is substantial, as just a few minutes of additional sleep per night is related to improvements in population-level resting heart rate and decreased cardiometabolic risk (Rezaei & Grandner, 2021 ). Adult survivors of cancer have significantly heightened risk for cardiovascular disease relative to those with no history of cancer (Florido et al., 2022 ), and findings from the National Health Interview Survey have shown that survivors have lower odds of obtaining adequate sleep compared to cancer-free controls (Boyd et al., 2020 ). Therefore, despite the lack of cancer-specific sleep recommendations, our results highlight the criticality of including sleep when developing multiple health behavior interventions for cancer survivors. An important consideration when looking at co-occurrence of multiple health behaviors is that these behaviors are mutually time exclusive. An individual typically is not physically active or eating while sleeping. Instead, dietary intake, physical activity, and sleep may happen sequentially and in a rhythm throughout each 24-hour period. This phenomenon has been documented outside of cancer populations. For the average American in 2022, during each 24-hour period an estimated 1.23 hours were spent eating or drinking with another 0.65 hours spent on food preparation and clean up, 0.29 hours were spent participating in recreational physical activity, and 9.02 hours were spent sleeping (U.S. Bureau of Labor Statistics, 2023 ). In recognition of this relationship, reducing the emphasis on guideline adherence and focusing instead on balancing multiple health behaviors may promote greater behavior change. Strengths and Limitations This study provides early evidence of the co-occurrence of multiple synergistic cancer preventive health behaviors in a sample of cancer survivors and informal cancer caregivers. Unique to this analysis, we pooled together cancer survivors and informal cancer caregivers and found they had similar health behavior profiles. Data were evaluated on a continuous scale, providing greater granularity. The utilization of HINTS data provided a nationally representative sample, increasing the generalizability of our findings to cancer survivors and informal cancer caregivers across the United States. Moreover, the methodology employed by HINTS reduced the risk of sampling bias through random sampling and nonresponse bias through applying weights (Maitland et al., 2017 ). There is a potential for recall bias, as HINTS data are self-reported health behaviors and the selected behaviors come from singular survey items. There may also be measurement error in reporting or potential overestimation of FVI due to the response scale on which the original data were collected and our subsequent recoding to enable evaluation on a continuum. The evaluation of sleep duration as a continuous variable did not account for the documented curvilinear relationship between sleep and health (Hoogland et al., 2019 ), with both short and long sleep linked to poor outcomes. Weighted ranges in our sample demonstrated that most long-sleepers (i.e., ≥9 hours per night) were in the Least Engaged–Sedentary profile, further supporting the potential utility of health behavior intervention for this group. Data included in this analysis were collected prior to the COVID-19 pandemic, which may have changed population engagement in health behaviors, although this remains unclear (Cole et al., 2023 ; Donzella et al., 2021 ; Ye & Ren, 2022 ). Finally, the temporality of the relationships examined and changes over time cannot be determined in this cross-sectional study. Implications and Future Research In 2021, HINTS fielded a cancer survivor specific survey that did not capture sleep (Blake et al., 2023 ). Given the co-occurrence of behaviors we observed in the present analysis and the clinical relevance of sleep for cancer outcomes, it is important that future surveys measuring health behaviors include assessment of sleep. Developing interventions that focus on promoting multiple health behaviors, rather than a singular behavior, remains a priority to address the deleterious effects cancer treatment and cancer caregiving can have on health outcomes (Carroll et al., 2022 ; Guida et al., 2021 ). Multiple studies promote diet and physical activity together and sleep separately in cancer survivors (Fox et al., 2022 ; Rodrigues et al., 2023 ; Squires et al., 2022 ; Thomson et al., 2023 ), but little work has championed all three simultaneously. Theoretically informed behavior change interventions can support strategic selection of techniques (Abraham & Michie, 2008 ). Additionally, due to the concordant tendencies of behaviors within survivor-caregiver dyads, future research should consider dyadic dynamics in the design, assessment, and interpretation of health behavior promotion interventions (Badr et al., 2019 ). Conclusions This analysis of a nationally representative sample of cancer survivors and cancer caregivers found that dietary quality, physical activity, and sleep duration generally co-occurred. Profiles were most distinguishable by MVPA relative to FVI and sleep duration. Profiles also differed by numerous sociodemographic and clinical variables, including survivor/caregiver role, current age, relationship status, education, income, rurality, alcohol use, self-efficacy, psychological distress, BMI, and cancer type. These characteristics, combined with profile membership, may identify cancer survivors and informal cancer caregivers who are most likely to engage in multiple health behaviors, thus not needing intervention, and those for whom health behavior intervention may be warranted. References Abraham, C., & Michie, S. (2008). A taxonomy of behavior change techniques used in interventions. 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Oncology , 68 (2-3), 107-114. https://doi.org/10.1159/000085703 Tables Table 1. Weighted Sample Characteristics of Cancer Survivors and Informal Cancer Caregivers Participating in HINTS 5 Cycle 3, 2019 Cancer Survivor Role (n = 841) Cancer Caregiver Role (n = 60) Dual Role (n = 15) Total (n = 916) Weighted N 22,754,490 2,895,557 711,464 26,382,979 Mean (SD) or n(%) p-value Current Age, years 63.5 (15.9) 55.5 (11.3) 59.0 (17.9) 62.5 (15.7) <0.001 Age at Diagnosis, years a 53.3 (16.1) -- 43.7 (15.8) 53.0 (16.2) 0.003 Time Since Diagnosis, years a 0.67 11 357 (45.0%) -- 14 (50.8%) 370 (45.2%) Family Cancer History 0.15 Yes 645 (83.1%) 88 (88.9%) 25 (100.0%) 757 (84.2%) No 69 (8.9%) 11 (10.6%) 0 (0.0%) 80 (8.8%) Not sure 63 (8.0%) 1 (0.6%) 0 (0.0%) 63 (7.0%) Primary Cancer Type a 0.84 Cutaneous 239 (29.0%) -- 3 (10.7%) 241 (28.5%) Breast 98 (11.9%) -- 9 (32.8%) 106 (12.5%) Gynecological 67 (8.1%) -- 2 (6.0%) 69 (8.1%) Colorectal 33 (4.0%) -- 0 (0.0%) 33 (3.9%) Prostate 57 (6.9%) -- 1 (1.8%) 58 (6.7%) Hematologic 32 (3.9%) -- 3 (10.9%) 35 (4.1%) ≥1 reported 154 (18.7%) -- 4 (14.1%) 157 (18.5%) Other 144 (17.5%) -- 7 (23.7%) 150 (17.7%) Sex 0.10 Male 347 (44.4%) 46 (45.5%) 6 (24.3%) 399 (43.9%) Female 436 (55.6%) 55 (54.5%) 19 (75.7%) 509 (56.1%) Ethnicity 0.40 Non-Hispanic 658 (83.3%) 95 (93.5%) 13 (49.1%) 765 (83.5%) Hispanic 63 (7.9%) 4 (3.8%) 8 (32.0%) 74 (8.1%) Decline to answer 71 (8.9%) 3 (2.7%) 5 (18.9%) 78 (8.5%) Racial Identity 0.15 Non-Hispanic White 542 (77.3%) 77 (79.7%) 8 (40.2%) 626 (76.7%) Non-Hispanic Black 67 (9.5%) 13 (12.5%) 1 (1.0%) 79 (9.7%) Hispanic 61 (8.7%) 4 (3.9%) 8 (39.5%) 73 (8.9%) Non-Hispanic Asian 18 (2.5%) 3 (2.4%) 0 (0.0%) 20 (2.4%) Non-Hispanic Other 15 (2.1%) 2 (1.5%) 4 (19.4%) 20 (2.4%) Relationship Status <0.001 Married / Partnered 437 (55.6%) 86 (85.4%) 21 (83.7%) 544 (59.7%) Divorced 94 (11.9%) 8 (7.3%) 1 (0.8%) 101 (11.1%) Widowed 113 (14.3%) 1 (0.9%) 0 (0.0%) 114 (12.5%) Separated 11 (1.3%) 2 (1.6%) 4 (15.5%) 16 (1.7%) Single, never been married 133 (16.9%) 5 (4.7%) 0 (0.0%) 138 (15.1%) Educational Attainment 0.58 < High School 78 (9.9%) 1 (0.4%) 0 (0.0%) 79 (8.6%) High School or Equivalent 193 (24.5%) 16 (15.7%) 9 (34.1%) 217 (23.8%) Some College / Vocational 306 (38.9%) 55 (54.3%) 12 (47.9%) 372 (40.8%) ≥ College Graduate 210 (26.7%) 30 (29.6%) 5 (18.0%) 244 (26.8%) Annual Household Income (USD) 0.86 < $20,000 102 (15.0%) 24 (24.4%) 4 (16.5%) 129 (16.1%) $20,000 to < $35,000 126 (18.4%) 8 (7.9%) 4 (14.9%) 137 (17.1%) $35,000 to < $50,000 135 (19.9%) 3 (2.3%) 9 (36.8%) 146 (18.2%) $50,000 to < $75,000 101 (14.7%) 19 (19.0%) 2 (5.7%) 120 (15.0%) ≥ $75,000 218 (32.0%) 45 (46.3%) 7 (26.1%) 269 (33.6%) Household Size <0.001 1 196 (24.7%) 5 (4.8%) 2 (4.4%) 202 (22.0%) 2 356 (45.0%) 41 (39.5%) 10 (38.0%) 405 (44.2%) 3 100 (12.6%) 9 (8.6%) 1 (3.3%) 110 (11.9%) 4 51 (6.4%) 7 (6.2%) 2 (6.5%) 59 (6.4%) ≥ 5 90 (11.4%) 42 (40.9%) 12 (47.8%) 144 (15.6%) Geographic Designation 0.70 Urban 665 (84.2%) 78 (76.4%) 19 (73.3%) 761 (83.0%) Rural 126 (15.8%) 24 (23.6%) 7 (26.7%) 156 (17.0%) Health Insurance Status 0.01 Uninsured 759 (97.3%) 84 (84.6%) 22 (87.8%) 864 (95.7%) Insured 21 (2.7%) 16 (15.4%) 4 (12.2%) 40 (4.3%) Perceived General Health 0.40 Excellent 84 (10.9%) 7 (6.4%) 2 (6.7%) 92 (10.3%) Very Good 205 (26.6%) 51 (50.0%) 9 (33.0%) 264 (29.4%) Good 300 (38.9%) 32 (31.6%) 7 (24.5%) 338 (37.7%) Fair 162 (21.0%) 12 (11.5%) 5 (20.0%) 178 (19.9%) Poor 21 (2.7%) 1 (0.4%) 4 (15.7%) 25 (2.8%) BMI Category 0.44 Normal 243 (30.7%) 17 (16.5%) 10 (39.2%) 269 (29.3%) Overweight 291 (36.8%) 42 (41.3%) 9 (33.9%) 341 (37.2%) Obese 258 (32.6%) 43 (42.3%) 7 (26.9%) 307 (33.5%) Smoking Status 0.04 Current 96 (12.2%) 9 (8.6%) 8 (31.3%) 113 (12.3%) Former 280 (35.6%) 24 (23.2%) 4 (15.7%) 307 (33.7%) Never 410 (52.2%) 69 (68.2%) 14 (53.1%) 492 (54.0%) Current Alcohol Use 0.56 None 361 (45.6%) 48 (47.3%) 11 (42.5%) 420 (45.7%) Moderate 239 (30.2%) 25 (24.6%) 2 (8.1%) 266 (29.0%) Heavy 191 (24.2%) 29 (28.1%) 13 (49.4%) 232 (25.3%) Number of Comorbid Conditions 0.29 0 217 (27.4%) 37 (36.2%) 11 (43.3%) 264 (28.8%) 1 248 (31.3%) 38 (37.4%) 3 (10.9%) 288 (31.4%) 2 190 (24.0%) 13 (12.7%) 4 (12.7%) 206 (22.5%) 3 117 (14.7%) 14 (13.5%) 4 (15.5%) 134 (14.6%) 4 19 (2.3%) 1 (0.3%) 5 (17.6%) 23 (2.5%) 5 3 (0.3%) 0 (0.0%) 0 (0.0%) 3 (0.2%) Health Self-Efficacy 0.62 Low 242 (31.2%) 32 (31.5%) 6 (24.3%) 280 (31.1%) High 532 (68.8%) 70 (68.5%) 19 (75.7%) 620 (68.9%) Psychological Distress 0.10 None 517 (66.0%) 51 (51.9%) 11 (42.3%) 578 (63.8%) Mild 159 (20.3%) 20 (19.7%) 2 (6.7%) 180 (19.8%) Moderate 52 (6.5%) 13 (12.5%) 4 (12.2%) 67 (7.3%) Severe 57 (7.2%) 16 (16.0%) 10 (38.9%) 82 (9.0%) a Excluding cancer caregiver role. Table 2. Weighted Summaries of Health Behaviors by Health Behavior Profile in HINTS 5 Cycle 3, 2019 Least Engaged–Sedentary Least Engaged– Inactive Moderately Engaged Highly Engaged Total Proportion 37.1% 12.2% 31.5% 19.2% 100% Weighted N 8,935,368 2,968,261 7,981,537 4,790,915 24,676,081 Mean (SD) p-value FVI, servings/day 4.30 (8.27) 3.04 (2.63) 4.18 (4.88) 7.66 (11.04) 4.77 (7.72) 0.007 MVPA, minutes/day 0 (0.02) 6.49 (2.36) 22.21 (8.45) 83.46 (34.44) 23.83 (34.38) <0.001 Sleep Duration, hours/night 6.72 (1.69) 6.55 (1.58) 6.91 (1.28) 7.10 (1.20) 6.83 (1.48) <0.001 Note. FVI = Fruit and Vegetable Intake; MVPA = Moderate to Vigorous Physical Activity Table 3 . Sociodemographic and Clinical Characteristics Associations with Health Behavior Profile Membership Health Behavior Profile RRR (95% CI) Reference: Least Engaged–Sedentary Least Engaged – Inactive Moderately Engaged Highly Engaged Characteristic Role Cancer Survivor Reference Reference Reference Cancer Caregiver 3.87 (1.05, 14.19) * 1.27 (0.48, 3.41) 3.26 (1.04, 10.19) * Dual -- b 4.03 (0.68, 23.86) 1.60 (0.17, 14.90) Sex Female Reference Reference Reference Male 0.60 (0.28, 1.27) 0.87 (0.50, 1.51) 1.06 (0.51, 2.22) Current Age <65 years Reference Reference Reference ≥65 years 0.44 (0.22, 0.88) * 0.88 (0.53, 1.44) 0.52 (0.28, 0.98) * Age at Diagnosis a ≥40 years Reference Reference Reference ≤39 years 1.53 (0.68, 3.49) 0.93 (0.48, 1.81) 0.59 (0.16, 2.12) Years Since Diagnosis a ≤10 Reference Reference Reference ≥11 1.03 (0.56, 1.89) 1.08 (0.66, 1.76) 0.86 (0.43, 1.73) Family Cancer History No Reference Reference Reference Yes 1.34 (0.42, 4.31) 1.64 (0.85, 3.18) 1.10 (0.50, 2.42) Cancer Type a Cutaneous Reference Reference Reference Breast 1.13 (0.40, 3.24) 1.18 (0.55, 2.55) 0.86 (0.34, 2.15) Gynecological 0.89 (0.30, 2.68) 0.53 (0.24, 1.21) 0.10 (0.03, 0.36) *** Colorectal 0.57 (0.10, 3.22) 0.85 (0.24, 3.00) 1.08 (0.25, 4.64) Prostate 2.05 (0.61, 6.85) 1.41 (0.55, 3.61) 1.65 (0.60, 4.53) Hematologic 0.76 (0.18, 3.19) 0.27 (0.06, 1.23) 0.68 (0.18, 2.50) ≥1 reported 0.70 (0.28, 1.74) 0.45 (0.24, 1.74) 0.62 (0.25, 1.52) Other 0.46 (0.12, 1.76) 0.33 (0.13, 0.81) * 0.62 (0.14, 2.81) Ethnicity Non-Hispanic Reference Reference Reference Hispanic 0.31 (0.11, 0.88)* 0.53 (0.20, 1.37) 0.95 (0.16, 5.66) Relationship Status Partnered Reference Reference Reference Unpartnered 0.57 (0.29, 1.10) 0.50 (0.30, 0.84) ** 0.52 (0.27, 1.01) Education <High School Reference Reference Reference ≥High School 0.23 (0.11, 0.50) *** 0.34 (0.19, 0.63) *** 0.34 (0.18, 0.84) * Household Income <$50,000 USD Reference Reference Reference ≥$50,000 USD 2.39 (0.87, 6.62) 2.33 (1.01, 5.38)* 2.44 (0.79, 7.54) Household Size 1 Reference Reference Reference 2 0.56 (0.26, 1.19) 1.04 (0.59, 1.85) 0.70 (0.34, 1.45) ≥3 1.23 (0.57, 2.66) 1.06 (0.61, 1.83) 0.94 (0.40, 2.19) Geographic Designation Urban Reference Reference Reference Rural 0.71 (0.31, 1.63) 0.36 (0.17, 0.74) ** 0.51 (0.23, 1.15) Health Insurance Status Uninsured Reference Reference Reference Insured 0.49 (0.06, 3.77) 2.29 (0.47, 11.23) 1.33 (0.22, 8.11) Perceived General Health Excellent - Good Reference Reference Reference Fair - Poor 0.41 (0.13, 1.25) 0.15 (0.06, 0.39) *** 0.36 (0.10, 1.34) Body Mass Index Normal Reference Reference Reference Overweight 1.76 (0.67, 4.64) 0.77 (0.39, 1.55) 0.88 (0.39, 1.99) Obese 1.08 (0.49, 2.38) 0.39 (0.23, 0.66) *** 0.49 (0.24, 1.02) Alcohol Use None Reference Reference Reference Moderate 1.48 (0.67, 3.19) 2.90 (1.74, 4.83) *** 2.42 (1.09, 5.36) * Heavy 0.58 (0.18, 1.85) 1.79 (0.74, 4.36) 2.57 (0.94, 7.05) Smoking Status Never Reference Reference Reference Current 1.26 (0.48, 3.29) 0.61 (0.26, 1.44) 0.60 (0.22, 1.66) Former 1.18 (0.52, 2.64) 0.68 (0.38, 1.21) 1.06 (0.50, 2.21) Comorbid Conditions None Reference Reference Reference 1 or more 1.27 (0.51, 3.21) 1.68 (0.75, 3.77) 1.57 (0.61, 4.00) Health Self-Efficacy Low Reference Reference Reference High 1.56 (0.74, 3.27) 1.98 (1.17, 3.36) * 4.07 (1.82, 9.07) *** Psychological Distress None Reference Reference Reference Mild 0.70 (0.31, 1.58) 0.36 (0.17, 0.77) ** 0.40 (1.3, 1.22) Moderate 1.64 (0.48, 5.58) 0.45 (0.18, 1.11) 0.42 (0.12, 1.47) Severe 1.25 (0.24, 6.55) 0.69 (0.26, 1.78) 0.60 (0.18, 0.31) Note. Multinomial logistic regression models using Taylor linearization and survey weights. Missing data ≤10%. a Excluding cancer caregiver role. b Indicates a small cell size, <0.5% of sample. * p<0.05 ** p<0.01 *** p<0.001 Supplementary Materials Supplemental Materials file is not available with this version. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-4271736","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291567447,"identity":"1beb187f-2c32-4fea-891e-852ddc3874f2","order_by":0,"name":"Meghan Skiba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYDACCQZmhsQGBjkGBsYGqFACcVqMSdQCVJzYgBAioEV3dvtjg4c77NL7Zx9u/vBxhx0DP3uOAV4tZnfOGCcknknOnXEuscFw5plkBsmeNwS03MhhPpDYxpzbcIaxIZm3jZnB4AYhW26kPwZqqU+XB2o5zNtWz2BPWEsC0GFthxMMzjA2NvO2HWYwkCDCLwaJZ44bbjzD2Mw4s+04j8SZZwX4tdxufyz5c0e1vNwZ9scfPrZVy/G3J2/AqwUD8JCmfBSMglEwCkYBVgAAYvRLCiwZwtEAAAAASUVORK5CYII=","orcid":"","institution":"University of Arizona","correspondingAuthor":true,"prefix":"","firstName":"Meghan","middleName":"","lastName":"Skiba","suffix":""},{"id":291567448,"identity":"89979d4a-9068-42d5-a601-8b563c8da45f","order_by":1,"name":"Terry A. Badger","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Terry","middleName":"A.","lastName":"Badger","suffix":""},{"id":291567449,"identity":"38b63c15-b610-4094-8c99-d13c6c4e571c","order_by":2,"name":"Thaddeus WW Pace","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Thaddeus","middleName":"WW","lastName":"Pace","suffix":""},{"id":291567450,"identity":"fff736fc-fe80-4589-8613-a57923c0f78e","order_by":3,"name":"Michael A. Grandner","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"A.","lastName":"Grandner","suffix":""},{"id":291567451,"identity":"19eccb9c-808f-410b-b7f0-ef88517ba21f","order_by":4,"name":"Patricia L. Haynes","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"L.","lastName":"Haynes","suffix":""},{"id":291567452,"identity":"182c531c-0aa8-4e4a-87bd-9aa35464fad8","order_by":5,"name":"Chris Segrin","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Chris","middleName":"","lastName":"Segrin","suffix":""},{"id":291567453,"identity":"379def35-7f5f-4eec-bc28-ef7ce91c0e70","order_by":6,"name":"Rina S. Fox","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Rina","middleName":"S.","lastName":"Fox","suffix":""}],"badges":[],"createdAt":"2024-04-15 20:13:48","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4271736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4271736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54786265,"identity":"2bdbe5a8-85bc-4849-9b21-ce663432e401","added_by":"auto","created_at":"2024-04-16 18:34:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":341594,"visible":true,"origin":"","legend":"\u003cp\u003eStandardized Means (z-score) in the Indicators of Health Behaviors Among Four Health Behavior Profiles\u003c/p\u003e","description":"","filename":"HINTSLPAFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4271736/v1/7d4f5436b7fe010ce3bf3d95.png"},{"id":54786663,"identity":"4696426e-722c-44dc-9049-01638cbeb39e","added_by":"auto","created_at":"2024-04-16 18:42:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":509522,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4271736/v1/399fab05-faee-4533-a744-41576a00c37b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003ePatterns of Dietary Quality, Physical Activity, and Sleep Duration among Cancer Survivors and Caregivers\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe more than 22\u0026nbsp;million cancer survivors living in the United States by 2032 (Office of Cancer Survivorship, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) are at high risk for late effects, such as cancer recurrence, secondary cancers, chronic comorbidities, and mortality (Leach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sogaard et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Cancer survivors include everyone with a history of cancer from the time of diagnosis through end of life. Engaging in healthful lifestyle behaviors such as eating a high-quality diet, being physically active, and getting sufficient sleep have been independently associated with reduced all-cause and disease-specific mortality (del Pozo Cruz et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xiao et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The American Cancer Society (ACS) has published nutrition and physical activity recommendations for adult survivors of cancer to promote overall health (Rock et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These include consuming a plant-based high-fiber diet with a variety of colorful fruits and vegetables and engaging in regular moderate-to-vigorous physical activity. Although cancer-specific sleep recommendations have not been released, the American Academy of Sleep Medicine and Sleep Research Society recommend that adults sleep seven to nine hours per night for optimal health (Watson et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, these health behaviors appear to be interrelated. Insufficient sleep is associated with decreased leptin and elevated ghrelin levels, which can cue increased food intake (Spiegel et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Decreased sleep is also associated with greater intake of processed foods and high-sugar refined foods (Godos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and less physical activity (Mead et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Semplonius \u0026amp; Willoughby, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Level of physical activity can influence sleep quality (Wang \u0026amp; Boros, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and dietary quality (Gillman et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Similarly, dietary quality impacts the energy available for physical activity, which in turn can affect sleep (Dolezal et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This interrelationship has been theorized to be due to spillover effects, wherein engagement in one behavior influences engagement in others, although the evidence supporting this is mixed (Pan et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sarma et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, the degree to which these spillover effects occur in the cancer population remains unclear.\u003c/p\u003e \u003cp\u003eIncreasing attention has been paid to the relationships among multiple co-occurring health behaviors in cancer survivors and their collective impact on health outcomes. Glasgow and colleagues (Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) categorized a sample of 856 survivors participating in a national survey as either adherent or non-adherent to six health behavior recommendations (i.e., aerobic physical activity, strength training, fruit and vegetable consumption, sleep duration and quality, and sedentary time). When assessed individually and as a composite score, individuals categorized as adherent reported better psychological health. This work identified which behaviors are relevant to psychological health in a nationally representative sample. However, an important limitation was the analytic approach, which precluded identification of patterns of health behavior engagement.\u003c/p\u003e \u003cp\u003eTo address this gap, research focused on multiple health behaviors is moving toward person-centered analytic approaches such as latest class analysis (LCA). Olson and colleagues (Olson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) evaluated lifestyle behaviors of 591 cancer survivors and identified three patterns based on physical activity, diet, smoking, and sleep. By utilizing LCA, they were able to identify naturally occurring patterns of behaviors and evaluate their relationships with health outcomes. However, prior to conducting the LCA the authors dichotomized each behavior, much like Glasgow and colleagues (Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This approach can result in a loss of information that interferes with identification of more nuanced patterns of engagement. Similarly, Fong and colleagues (Fong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) conducted an LCA to identify patterns based on a combination of categorical (i.e., BMI, physical activity, smoking status, alcohol consumption, time since last physician visit) and continuous (i.e., dietary intake, sun safety) behaviors among 661 participants with cancer. Notably, sleep was absent. A gap remains in generalizability to a broader population of cancer survivors and how dietary quality, physical activity, and sleep may co-occur along a continuum.\u003c/p\u003e \u003cp\u003eAlthough health behavior patterns have been explored among cancer survivors, informal cancer caregivers (e.g., family members, friends) have generally been excluded. Informal caregivers provide a significant amount of unpaid cancer care and experience documented adverse health outcomes (Perkins et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Pinquart \u0026amp; S\u0026ouml;rensen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; van Ryn et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yun et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Although evidence regarding the impact of cancer caregiving on health behaviors is mixed (Litzelman et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ross et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Secinti et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the health behaviors of cancer survivors and their caregivers are interrelated (Badr et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kiecolt-Glaser \u0026amp; Wilson, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It is possible that by considering both survivors and caregivers, additional information could emerge regarding the prevalence, composition, and impact of health behavior patterns in the cancer context.\u003c/p\u003e \u003cp\u003eThe present study had two aims. The first was to explore how dietary quality, physical activity, and sleep co-occur among a nationally representative sample of cancer survivors and informal cancer caregivers. To achieve this, we used a person-centered analytic approach to identify naturally occurring patterns of health behavior engagement. The second aim was to determine the association of sociodemographic and clinical variables to health behavior patterns to facilitate identification of individuals who may particularly benefit from health promotion intervention. Given the exploratory nature of this work, there were no \u003cem\u003ea priori\u003c/em\u003e hypotheses.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Sample\u003c/h2\u003e \u003cp\u003eData were derived from the National Cancer Institute (NCI) Health Information National Trends Survey (HINTS) database. HINTS is a nationally representative, cross-sectional survey of the US non-institutionalized adult population. Data are collected annually via mail and telephone (Finney Rutten et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Nelson et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Datasets and methodological documentation are publicly available for download (U.S. Department of Health and Human Services, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Participants who completed the HINTS 5 Cycle 3 survey (2019; response rate: 30.3%) in English or Spanish were included in the present analysis. Although more recent data have been fielded for HINTS, the 2019 survey is the most recent survey that included all three targeted health behaviors in a singular dataset. The analytical sample was limited to individuals with a self-reported history of cancer (\u0026ldquo;\u003cem\u003eHave you ever been diagnosed with having cancer?\u003c/em\u003e\u0026rdquo;; n\u0026thinsp;=\u0026thinsp;856) or those who reported providing unpaid care to an individual with cancer (\u0026ldquo;\u003cem\u003eAre you currently caring for or making health care decisions for someone with a medical, behavioral, disability, or other condition?\u0026rdquo; Caregiving condition: Cancer\u003c/em\u003e; n\u0026thinsp;=\u0026thinsp;75). Fifteen respondents reported both having a history of cancer and being a current informal caregiver and were categorized as \u0026ldquo;Dual Role\u0026rdquo; (weighted N\u0026thinsp;=\u0026thinsp;711,464). Those who reported a history of cancer with no informal caregiving responsibilities were categorized as \u0026ldquo;Cancer Survivor Role\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;841, weighted N\u0026thinsp;=\u0026thinsp;22,754,490) and those who reported current informal cancer caregiving without a cancer diagnosis were categorized as \u0026ldquo;Caregiver Role\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;60, weighted N\u0026thinsp;=\u0026thinsp;2,895,557). This study did not require Institutional Review Board approval because it used publicly available deidentified data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eHealth Behaviors\u003c/h2\u003e \u003cp\u003e \u003cb\u003eFruit and Vegetable Intake.\u003c/b\u003e Fruit and vegetable intake (FVI) were assessed using the following questions: \u0026ldquo;\u003cem\u003eAbout how many cups of fruit (including 100% pure fruit juice) do you eat or drink each day?\u003c/em\u003e\u0026rdquo; and \u0026ldquo;\u003cem\u003eAbout how many cups of vegetables (including 100% pure vegetable juice) do you eat or drink each day?\u003c/em\u003e\u0026rdquo; Survey respondents were provided with approximate serving sizes and could select \u0026ldquo;None\u0026rdquo;, \u0026ldquo;1/2 cup or less\u0026rdquo;, \u0026ldquo;1/2 cup to 1 cup\u0026rdquo;, \u0026ldquo;1 to 2 cups\u0026rdquo;, \u0026ldquo;2 to 3 cups\u0026rdquo;, \u0026ldquo;3 to 4 cups\u0026rdquo;, or \u0026ldquo;4 or more cups\u0026rdquo;. FYI was recoded as the maximum possible within each response category (e.g., \u0026ldquo;1/2 cup to 1 cup\u0026rdquo; was coded as 1 cup), summed, and analyzed continuously as a conservative estimate of total daily servings of fruit and vegetables.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePhysical Activity.\u003c/b\u003e Weekly minutes of moderate-to-vigorous physical activity (MVPA) was calculated from responses to two questions: \u003cem\u003e\u0026ldquo;In a typical week, how many days do you do any physical activity or exercise of at least moderate intensity, such as brisk walking, bicycling at a regular pace, and swimming at a regular pace (do not include weightlifting)?\u0026rdquo;\u003c/em\u003e and \u003cem\u003e\u0026ldquo;On the days that you do any physical activity or exercise of at least moderate intensity, how long do you typically do these activities?\u0026rdquo;.\u003c/em\u003e Daily minutes of physical activity were calculated by dividing the weekly minutes by seven, and the resulting values were log transformed for normality prior to analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSleep Duration.\u003c/b\u003e Average nightly hours of sleep over the previous week were self-reported in response to the question \u0026ldquo;\u003cem\u003eDuring the past 7 days, how many hours of sleep did you get on average per night?\u003c/em\u003e\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic and Clinical Covariates\u003c/h2\u003e \u003cp\u003eSociodemographic and clinical information was self-reported. Sociodemographic characteristics included age, sex, race/ethnicity, geographic area (rural vs. urban designation), annual household income, household size, relationship status, and educational attainment. Cancer history included age at diagnosis, years since diagnosis (calculated from age at survey completion and age at diagnosis), family history of cancer, and cancer type. Other health characteristics included perceived general health (excellent to poor), health insurance coverage, comorbid conditions (diabetes, high blood pressure, heart disease, lung disease, or depression), body mass index (BMI; calculated as weight (kg)/height (m\u003csup\u003e2\u003c/sup\u003e), and BMI category (normal weight- 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e, overweight- 25.0-29.9 kg/m\u003csup\u003e2\u003c/sup\u003e, and obese\u0026thinsp;\u0026ge;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e) (Weir \u0026amp; Jan, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Smoking status (current, former, never) and alcohol use (none, moderate, heavy) (Rock et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) were also included. Self-efficacy and psychological distress, behavioral covariates in HINTS previously associated with health behaviors (Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Skiba et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), were also included. Self-efficacy was dichotomized into low and high, consistent with previous analyses (Fleary et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Niederdeppe \u0026amp; Levy, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Skiba et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), from the response to the question: \u003cem\u003e\u0026ldquo;Overall, how confident are you about your ability to take good care of your health?\u0026rdquo;\u003c/em\u003e while Patient Health Questionnaire-4 (PHQ-4) scores were used to categorize psychological distress as: No Distress (0\u0026ndash;2), Mild (3\u0026ndash;5), Moderate (6\u0026ndash;8) and Severe (9\u0026ndash;12), consistent with previous analyses (Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kroenke et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were managed according to NCI guidance (Moser et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Survey weights provided by HINTS were applied using the Taylor linearization replication method to provide population level estimates. Differences in sociodemographic characteristics, cancer history, and health characteristics stratified to compare cancer survivors and caregivers were assessed using Chi-square tests for categorical variables and \u003cem\u003et\u003c/em\u003e-tests for continuous variables.\u003c/p\u003e \u003cp\u003eWe conducted an exploratory latent profile analysis (LPA) to identify groups of individuals with similar co-occurring health behavior patterns. We fit an LPA model with one categorical latent variable and three observed continuous variables (FVI, MVPA, and sleep) following best practices for model assumptions, estimation, selection, and interpretation (Masyn, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Profiles were added iteratively to determine the best model fit. The optimal number of profiles was determined by interpretation of Akaike\u0026rsquo;s information criterion (AIC), Bayesian information criterion (BIC), global entropy, and clinical relevance (Nylund et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Profiles were further evaluated for interpretability and sample size, and those containing\u0026thinsp;\u0026lt;\u0026thinsp;5% of the sample were deemed spurious. Profile membership was assigned based on highest probability of belonging. LPA models were not stratified based on role (survivor/caregiver), which was instead evaluated as a predictor of profile membership. Standardized profile means (\u003cem\u003ez\u003c/em\u003e-scores) of the indicators were calculated to visualize differences among profiles.\u003c/p\u003e \u003cp\u003eFinal profiles were used as a categorical outcome variable in subsequent multinomial logistic regression analyses to predict profile membership based on sociodemographic and health characteristics. Current age, age at diagnosis, years since diagnosis, and number of comorbid conditions were categorized prior to analysis to facilitate interpretation. Analytical samples were restricted to complete cases, and individuals with missing responses for any covariate were excluded. An alpha level of 5% was considered statistically significant. All analyses were completed in STATA 18.0 (StataCorp LLC, College Station, TX, USA).\u003c/p\u003e \u003cp\u003e\u003cb\u003eSensitivity Analysis.\u003c/b\u003e A sensitivity analysis was conducted to facilitate interpretation in comparison to prior research (Fong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Olson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To determine the proportion of respondents in each profile meeting established health behavior recommendations, responses were dichotomized as meeting or not meeting recommendations according to the following cut-points: 1) FVI: \u0026ge; 2 cups of fruit and \u0026ge;\u0026thinsp;3 cups of vegetables per day (Rock et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); 2) MVPA: \u0026ge;150 minutes per week (Rock et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); and 3) Sleep: \u0026ge;7 hours per night (Hirshkowitz et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Adherence to established guidelines by profile were compared using Pearson\u0026rsquo;s chi-squared tests of independence with Bonferroni adjustment for multiple comparisons.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eDescriptive Statistics\u003c/h2\u003e\n \u003cp\u003eSample sociodemographic and clinical characteristics are summarized in \u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e. All responses included in the present analysis were completed using the English HINTS survey, as no respondents endorsing a history of cancer or cancer caregiving completed the survey in Spanish. Cancer survivors were on average older than cancer caregivers (63.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9 and 56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 years, respectively). The most common cancer diagnosis was cutaneous (29%). Most cancer caregivers reported providing care to either a parent (37.9%) or partner (18.2%). Most respondents identified as non-Hispanic (84%) and resided in urban areas (83%). About half reported never smoking (54%) and no current alcohol use (46%), while 71% were either overweight or obese and reported one or more chronic comorbid health conditions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eIdentified Health Behavior Profiles\u003c/h2\u003e\n \u003cp\u003eFour health behavior profiles were identified (Fig.\u0026nbsp;1): \u003cem\u003eLeast Engaged\u0026ndash;Sedentary\u003c/em\u003e, \u003cem\u003eLeast Engaged\u0026ndash;Inactive\u003c/em\u003e, \u003cem\u003eModerately Engaged\u003c/em\u003e, and \u003cem\u003eHighly Engaged\u003c/em\u003e. The \u003cem\u003eLeast Engaged\u0026ndash;Sedentary\u003c/em\u003e profile was characterized by low engagement overall and no reported MVPA. Comparatively, the \u003cem\u003eLeast Engaged\u0026ndash;Inactive\u003c/em\u003e profile was characterized by low engagement overall but minimal reported MVPA and lower FVI. The \u003cem\u003eModerately Engaged\u003c/em\u003e profile was characterized by moderate MVPA and FVI, and lower average sleep duration. The \u003cem\u003eHighly Engaged\u003c/em\u003e profile was characterized by elevated engagement across health behaviors. Profiles were most distinguished by mean MVPA (\u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e). The largest profile group \u003cem\u003ewas Least Engaged\u0026ndash;Sedentary\u003c/em\u003e with 37% of the sample.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eAssociations of Profile Membership and Sociodemographic and Health Characteristics\u003c/h2\u003e\n \u003cp\u003eProfile membership was significantly associated with sociodemographic and health characteristics (\u003cstrong\u003eTable\u0026nbsp;3\u003c/strong\u003e). All models used the \u003cem\u003eLeast Engaged\u0026ndash;Sedentary\u003c/em\u003e profile as the reference group. Respondents in the \u003cem\u003eLeast Engaged\u0026ndash;Inactive\u003c/em\u003e profile were significantly more likely to be a caregiver but less likely to be aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years, identify as Hispanic, and have greater than a high school education. Respondents in the \u003cem\u003eModerately Engaged\u003c/em\u003e profile were significantly more likely to have higher annual household income, moderately use alcohol, and have high health self-efficacy. They were also significantly less likely to report an \u0026ldquo;other\u0026rdquo; cancer diagnosis, be partnered, have greater than a high school education, live in a rural setting, report fair-to-poor general health, be obese, and report mild psychological distress. Respondents in the \u003cem\u003eHighly Engaged\u003c/em\u003e profile were significantly more likely to be a caregiver, moderately use alcohol, and have high health self-efficacy. They were also significantly less likely to be aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years, report a gynecologic cancer diagnosis, and have greater than a high school education. No other sociodemographic or health characteristics were significantly associated with profile membership.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eSensitivity Analysis - Profile Adherence to Recommendations\u003c/h2\u003e\n \u003cp\u003eInformation about adherence to recommendations can be found in \u003cstrong\u003eSupplemental Materials\u003c/strong\u003e. Across profiles, the least adhered to behavior was FVI followed by MVPA, while sleep had the greatest observed levels of adherence. Post-hoc analyses indicated that percent adherence to FVI and MVPA recommendations were significantly different across profiles.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe observed four distinct patterns of health behavior co-occurrence among a nationally representative sample of cancer survivors and informal cancer caregivers. In general, respondents who reported greater FVI also reported greater MVPA and sleep duration. Likewise, participants reporting lower FVI had lower MVPA and sleep duration. Approximately 20% of the sample was in the \u003cem\u003eHighly Engaged\u003c/em\u003e profile, indicating that more than 80% warrant some degree of intervention to support dietary quality, physical activity, and/or sleep behaviors. We also identified that role, cancer type, self-efficacy, age, alcohol use, and educational attainment were associated with profile membership. This information could help identify which individuals may require more or less intensive health behavior intervention for maximum benefit.\u003c/p\u003e \u003cp\u003eOur results were similar to Olson and colleagues\u0026rsquo; (Olson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) finding that most survivors had problems with physical activity and diet, with or without sleep difficulties, and that those with these challenges were less likely to report high health-related quality of life. Our results are also consistent with their finding that the most engaged were younger and had a lower BMI. However, unlike these authors, we found that MVPA had the greatest variance across profiles while they identified sleep as the key differentiating behavior. This difference may be due to their categorization of variables prior to analysis, or because their profiles were also indicated by smoking status. Although Olson and colleagues did not evaluate ethnicity or rurality, we found that rural-dwelling respondents were least likely to be in the \u003cem\u003eModerately Engaged\u003c/em\u003e profile. This is consistent with the broader cancer survivorship literature, suggesting that greater efforts may be required to promote health behavior engagement among rural-dwelling cancer survivors (Werts et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding inclusion of informal cancer caregivers, qualitative evidence has suggested that including an informal caregiver in interventions may help survivors engage in healthful behaviors (Skiba et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, dyadic health behavior interventions developed specifically with the well-being of both the cancer survivor and the informal caregiver in mind remain limited (Bisht et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To date, most of this work has focused on physical activity (Song et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), diet (Xu et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), weight-loss (Demark-Wahnefried et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), or symptom management (Crane et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), or has excluded non-spousal caregivers (Carmack et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Winters-Stone KM, 2016). Given the demonstrated interrelationship between survivor-caregiver health behaviors (Badr et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kiecolt-Glaser \u0026amp; Wilson, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), more interventional research is warranted that includes diverse cancer survivor-caregiving relationship dynamics and targets multiple health behaviors.\u003c/p\u003e \u003cp\u003ePrevious studies have identified patterns and correlates of health behaviors respective to current recommendations (Fong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Glasgow et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Olson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Such an approach is important, as higher adherence to health behavior guidelines is associated with lower cancer incidence and mortality (Kohler et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, simply categorizing behaviors as adherent or non-adherent runs the risk of missing individuals who are close to the cut-off but may need just a little more support to cross the threshold into adherence. Our use of a person-centered analysis that considered three behaviors on a continuous scale allowed for the inclusion of this information. For example, we found that those in the \u003cem\u003eModerately Engaged\u003c/em\u003e profile were, on average, consuming one less serving of fruits and vegetables and engaging in eight fewer minutes of MVPA per day than guidelines recommend. Although these individuals may benefit from health behavior intervention, they are likely to need much less intensive intervention than the participants in either of the \u003cem\u003eLeast Engaged\u003c/em\u003e profiles. Had we categorized behaviors as adherent and non-adherent prior to analysis, we would not have identified this pattern, and in turn our conclusions may have encouraged inefficient application of health behavior support.\u003c/p\u003e \u003cp\u003e Although we included three health behaviors as indicators of profile membership in our analysis, cancer-specific guidelines were available for only two. This is likely because, historically, sleep has been underrepresented in cancer survivorship research relative to dietary quality and physical activity. Interestingly, we also found that sleep had the lowest variance across profiles. However, even this low variance corresponded to a 33 minute per night difference in sleep duration between the profile with the lowest average sleep (\u003cem\u003eModerately Engaged\u003c/em\u003e) compared to highest (\u003cem\u003eHighly Engaged\u003c/em\u003e). The clinical relevance of this difference is substantial, as just a few minutes of additional sleep per night is related to improvements in population-level resting heart rate and decreased cardiometabolic risk (Rezaei \u0026amp; Grandner, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adult survivors of cancer have significantly heightened risk for cardiovascular disease relative to those with no history of cancer (Florido et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and findings from the National Health Interview Survey have shown that survivors have lower odds of obtaining adequate sleep compared to cancer-free controls (Boyd et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, despite the lack of cancer-specific sleep recommendations, our results highlight the criticality of including sleep when developing multiple health behavior interventions for cancer survivors.\u003c/p\u003e \u003cp\u003eAn important consideration when looking at co-occurrence of multiple health behaviors is that these behaviors are mutually time exclusive. An individual typically is not physically active or eating while sleeping. Instead, dietary intake, physical activity, and sleep may happen sequentially and in a rhythm throughout each 24-hour period. This phenomenon has been documented outside of cancer populations. For the average American in 2022, during each 24-hour period an estimated 1.23 hours were spent eating or drinking with another 0.65 hours spent on food preparation and clean up, 0.29 hours were spent participating in recreational physical activity, and 9.02 hours were spent sleeping (U.S. Bureau of Labor Statistics, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In recognition of this relationship, reducing the emphasis on guideline adherence and focusing instead on balancing multiple health behaviors may promote greater behavior change.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study provides early evidence of the co-occurrence of multiple synergistic cancer preventive health behaviors in a sample of cancer survivors and informal cancer caregivers. Unique to this analysis, we pooled together cancer survivors and informal cancer caregivers and found they had similar health behavior profiles. Data were evaluated on a continuous scale, providing greater granularity. The utilization of HINTS data provided a nationally representative sample, increasing the generalizability of our findings to cancer survivors and informal cancer caregivers across the United States. Moreover, the methodology employed by HINTS reduced the risk of sampling bias through random sampling and nonresponse bias through applying weights (Maitland et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is a potential for recall bias, as HINTS data are self-reported health behaviors and the selected behaviors come from singular survey items. There may also be measurement error in reporting or potential overestimation of FVI due to the response scale on which the original data were collected and our subsequent recoding to enable evaluation on a continuum. The evaluation of sleep duration as a continuous variable did not account for the documented curvilinear relationship between sleep and health (Hoogland et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), with both short and long sleep linked to poor outcomes. Weighted ranges in our sample demonstrated that most long-sleepers (i.e., \u0026ge;9 hours per night) were in the \u003cem\u003eLeast Engaged\u0026ndash;Sedentary\u003c/em\u003e profile, further supporting the potential utility of health behavior intervention for this group. Data included in this analysis were collected prior to the COVID-19 pandemic, which may have changed population engagement in health behaviors, although this remains unclear (Cole et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Donzella et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ye \u0026amp; Ren, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Finally, the temporality of the relationships examined and changes over time cannot be determined in this cross-sectional study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImplications and Future Research\u003c/h2\u003e \u003cp\u003eIn 2021, HINTS fielded a cancer survivor specific survey that did not capture sleep (Blake et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Given the co-occurrence of behaviors we observed in the present analysis and the clinical relevance of sleep for cancer outcomes, it is important that future surveys measuring health behaviors include assessment of sleep. Developing interventions that focus on promoting multiple health behaviors, rather than a singular behavior, remains a priority to address the deleterious effects cancer treatment and cancer caregiving can have on health outcomes (Carroll et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Guida et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Multiple studies promote diet and physical activity together and sleep separately in cancer survivors (Fox et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rodrigues et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Squires et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thomson et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but little work has championed all three simultaneously. Theoretically informed behavior change interventions can support strategic selection of techniques (Abraham \u0026amp; Michie, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Additionally, due to the concordant tendencies of behaviors within survivor-caregiver dyads, future research should consider dyadic dynamics in the design, assessment, and interpretation of health behavior promotion interventions (Badr et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis analysis of a nationally representative sample of cancer survivors and cancer caregivers found that dietary quality, physical activity, and sleep duration generally co-occurred. Profiles were most distinguishable by MVPA relative to FVI and sleep duration. Profiles also differed by numerous sociodemographic and clinical variables, including survivor/caregiver role, current age, relationship status, education, income, rurality, alcohol use, self-efficacy, psychological distress, BMI, and cancer type. These characteristics, combined with profile membership, may identify cancer survivors and informal cancer caregivers who are most likely to engage in multiple health behaviors, thus not needing intervention, and those for whom health behavior intervention may be warranted.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbraham, C., \u0026amp; Michie, S. (2008). A taxonomy of behavior change techniques used in interventions. \u003cem\u003eHealth Psychol\u003c/em\u003e,\u003cem\u003e 27\u003c/em\u003e(3), 379-387. https://doi.org/10.1037/0278-6133.27.3.379 \u003c/li\u003e\n\u003cli\u003eBadr, H., Bakhshaie, J., \u0026amp; Chhabria, K. (2019). 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Economic burdens and quality of life of family caregivers of cancer patients. \u003cem\u003eOncology\u003c/em\u003e,\u003cem\u003e 68\u003c/em\u003e(2-3), 107-114. https://doi.org/10.1159/000085703 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eWeighted Sample Characteristics of Cancer Survivors and Informal Cancer Caregivers Participating in HINTS 5 Cycle 3, 2019\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"621\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Survivor Role\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 841)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Caregiver Role\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 60)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDual Role\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 916)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u003cem\u003eWeighted N\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cem\u003e22,754,490\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cem\u003e2,895,557\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u003cem\u003e711,464\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cem\u003e26,382,979\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"top\"\u003e\n \u003cp\u003eMean (SD) or n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eCurrent Age, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e63.5 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e55.5 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e59.0 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e62.5 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eAge at Diagnosis, years\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e53.3 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e43.7 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e53.0 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eTime Since Diagnosis, years\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026lt;1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e125 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e126 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e2-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e182 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e11 (40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e193 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e6-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e131 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e131 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026gt;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e357 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e14 (50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e370 (45.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eFamily Cancer History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e645 (83.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e88 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e25 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e757 (84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e69 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e11 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e80 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNot sure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e63 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e63 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003ePrimary Cancer Type\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eCutaneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e239 (29.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e241 (28.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e98 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e9 (32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e106 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eGynecological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e67 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e69 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e33 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e33 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e57 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e58 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHematologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e32 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e35 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026ge;1 reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e154 (18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e157 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e144 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e150 (17.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e347 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e46 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e6 (24.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e399 (43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e436 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e55 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e19 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e509 (56.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNon-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e658 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e95 (93.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e13 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e765 (83.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e63 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e4 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e8 (32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e74 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eDecline to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e71 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e3 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e78 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eRacial Identity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e542 (77.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e77 (79.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e8 (40.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e626 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e67 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e13 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e79 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e61 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e4 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e8 (39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e73 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNon-Hispanic Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e18 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e3 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e20 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNon-Hispanic Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e20 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eRelationship Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eMarried / Partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e437 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e86 (85.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e21 (83.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e544 (59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e94 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e8 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e101 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e113 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e114 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e11 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e2 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e16 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSingle, never been married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e133 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e138 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eEducational Attainment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026lt; High School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e78 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e79 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHigh School or Equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e193 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e16 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e9 (34.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e217 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSome College / Vocational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e306 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e55 (54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e12 (47.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e372 (40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026ge; College Graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e210 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e30 (29.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5 (18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e244 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eAnnual Household Income \u0026nbsp;(USD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026lt; $20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e102 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e24 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (16.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e129 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e$20,000 to \u0026lt; $35,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e126 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e8 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e137 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e$35,000 to \u0026lt; $50,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e135 (19.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e3 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e9 (36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e146 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e$50,000 to \u0026lt; $75,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e101 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e19 (19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e120 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026ge; $75,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e218 (32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e45 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7 (26.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e269 (33.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHousehold Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e196 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e5 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e202 (22.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e356 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e41 (39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e10 (38.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e405 (44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e100 (12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e9 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e110 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e51 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e59 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026ge; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e90 (11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e42 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e12 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e144 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eGeographic Designation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e665 (84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e78 (76.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e19 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e761 (83.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e126 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e24 (23.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e156 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHealth Insurance Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eUninsured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e759 (97.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e84 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e22 (87.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e864 (95.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eInsured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e21 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e16 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e40 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003ePerceived General Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e84 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e7 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e92 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eVery Good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e205 (26.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e51 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e9 (33.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e264 (29.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e300 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e32 (31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e338 (37.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e162 (21.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e12 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e178 (19.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e21 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e25 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eBMI Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e243 (30.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e17 (16.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e10 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e269 (29.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e291 (36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e42 (41.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e9 (33.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e341 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e258 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e43 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e307 (33.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSmoking Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e96 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e9 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e8 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e113 (12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e280 (35.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e24 (23.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e307 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e410 (52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e69 (68.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e14 (53.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e492 (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eCurrent Alcohol Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e361 (45.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e48 (47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e11 (42.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e420 (45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e239 (30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e266 (29.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e191 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e29 (28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e13 (49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e232 (25.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNumber of Comorbid Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e217 (27.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e37 (36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e11 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e264 (28.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e248 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e38 (37.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e288 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e190 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e13 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e206 (22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e117 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e134 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e19 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e23 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e3 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e3 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHealth Self-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e242 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e32 (31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e6 (24.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e280 (31.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e532 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e70 (68.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e19 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e620 (68.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003ePsychological Distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e517 (66.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e51 (51.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e11 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e578 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e159 (20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e20 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e180 (19.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e52 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e13 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e67 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e57 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e16 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e10 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e82 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eExcluding cancer caregiver role.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eWeighted Summaries of Health Behaviors by Health Behavior Profile in HINTS 5 Cycle 3, 2019\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeast Engaged\u0026ndash;Sedentary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeast Engaged\u0026ndash; Inactive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerately Engaged\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighly Engaged\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003eProportion\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e37.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e12.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e19.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003eWeighted N\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e8,935,368\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e2,968,261\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e7,981,537\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e4,790,915\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e24,676,081\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFVI, servings/day\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e4.30 (8.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e3.04 (2.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e4.18 (4.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e7.66 (11.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e4.77 (7.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMVPA, minutes/day\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0 (0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e6.49 (2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e22.21 (8.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e83.46 (34.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e23.83 (34.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep Duration, hours/night\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e6.72 (1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e6.55 (1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e6.91 (1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e7.10 (1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e6.83 (1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e FVI = Fruit and Vegetable Intake; MVPA = Moderate to Vigorous Physical Activity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Sociodemographic and Clinical Characteristics Associations with Health Behavior Profile Membership\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.292929292929294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.70707070707071%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth Behavior Profile\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.292929292929294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.70707070707071%\" colspan=\"3\"\u003e\n \u003cp\u003eRRR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.292929292929294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.70707070707071%\" colspan=\"3\"\u003e\n \u003cp\u003eReference: \u003cem\u003eLeast Engaged\u0026ndash;Sedentary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLeast Engaged\u003c/em\u003e\u003c/strong\u003e\u0026ndash;\u003cstrong\u003e\u003cem\u003eInactive\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eModerately Engaged\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHighly Engaged\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eRole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCancer Survivor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCancer Caregiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e3.87 (1.05, 14.19)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.27 (0.48, 3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e3.26 (1.04, 10.19)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eDual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e--\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e4.03 (0.68, 23.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.60 (0.17, 14.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.60 (0.28, 1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.87 (0.50, 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.06 (0.51, 2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCurrent Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026lt;65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.44 (0.22, 0.88)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.88 (0.53, 1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.52 (0.28, 0.98)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eAge at Diagnosis\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;40 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026le;39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.53 (0.68, 3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.93 (0.48, 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.59 (0.16, 2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eYears Since Diagnosis\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026le;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.03 (0.56, 1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.08 (0.66, 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.86 (0.43, 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eFamily Cancer History\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.34 (0.42, 4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.64 (0.85, 3.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.10 (0.50, 2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCancer Type\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Cutaneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.13 (0.40, 3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.18 (0.55, 2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.86 (0.34, 2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eGynecological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.89 (0.30, 2.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.53 (0.24, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.10 (0.03, 0.36)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.57 (0.10, 3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.85 (0.24, 3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.08 (0.25, 4.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e2.05 (0.61, 6.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.41 (0.55, 3.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.65 (0.60, 4.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHematologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.76 (0.18, 3.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.27 (0.06, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.68 (0.18, 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;1 reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.70 (0.28, 1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.45 (0.24, 1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.62 (0.25, 1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.46 (0.12, 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.33 (0.13, 0.81)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.62 (0.14, 2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNon-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.31 (0.11, 0.88)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.53 (0.20, 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.95 (0.16, 5.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eRelationship Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003ePartnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eUnpartnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.57 (0.29, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.50 (0.30, 0.84)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.52 (0.27, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026lt;High School\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;High School\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.23 (0.11, 0.50)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.34 (0.19, 0.63)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.34 (0.18, 0.84)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHousehold Income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026lt;$50,000 USD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;$50,000 USD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e2.39 (0.87, 6.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e2.33 (1.01, 5.38)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e2.44 (0.79, 7.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHousehold Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.56 (0.26, 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.04 (0.59, 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.70 (0.34, 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.23 (0.57, 2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.06 (0.61, 1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.94 (0.40, 2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eGeographic Designation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.71 (0.31, 1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.36 (0.17, 0.74)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.51 (0.23, 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHealth Insurance Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eUninsured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eInsured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.49 (0.06, 3.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e2.29 (0.47, 11.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.33 (0.22, 8.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003ePerceived General Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eExcellent - Good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eFair - Poor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.41 (0.13, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.15 (0.06, 0.39)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.36 (0.10, 1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eBody Mass Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.76 (0.67, 4.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.77 (0.39, 1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.88 (0.39, 1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.08 (0.49, 2.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.39 (0.23, 0.66)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.49 (0.24, 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eAlcohol Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.48 (0.67, 3.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e2.90 (1.74, 4.83)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e2.42 (1.09, 5.36)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.58 (0.18, 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.79 (0.74, 4.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e2.57 (0.94, 7.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eSmoking Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.26 (0.48, 3.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.61 (0.26, 1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.60 (0.22, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.18 (0.52, 2.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.68 (0.38, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.06 (0.50, 2.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eComorbid Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e1 or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.27 (0.51, 3.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.68 (0.75, 3.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e1.57 (0.61, 4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHealth Self-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.56 (0.74, 3.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e1.98 (1.17, 3.36)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e4.07 (1.82, 9.07)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003ePsychological Distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e0.70 (0.31, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.36 (0.17, 0.77)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.40 (1.3, 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.64 (0.48, 5.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.45 (0.18, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.42 (0.12, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\"\u003e\n \u003cp\u003e1.25 (0.24, 6.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\"\u003e\n \u003cp\u003e0.69 (0.26, 1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.60 (0.18, 0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eMultinomial logistic regression models using Taylor linearization and survey weights. Missing data \u0026le;10%.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eExcluding cancer caregiver role. \u003csup\u003eb\u0026nbsp;\u003c/sup\u003eIndicates a small cell size, \u0026lt;0.5% of sample.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e p\u0026lt;0.05 \u003csup\u003e**\u0026nbsp;\u003c/sup\u003ep\u0026lt;0.01 \u003csup\u003e***\u003c/sup\u003e p\u0026lt;0.001\u003c/p\u003e"},{"header":"Supplementary Materials","content":"\u003cp\u003eSupplemental Materials file is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"health-related behaviors, cancer survivorship, cancer caregiving, HINTS, latent profile analysis","lastPublishedDoi":"10.21203/rs.3.rs-4271736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4271736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHealth behaviors such as fruit and vegetable intake (FVI), moderate-to-vigorous physical activity (MVPA), and sleep duration are associated with cancer-related and general health outcomes. This analysis examined to what degree FVI, MVPA, and sleep co-occur among cancer survivors and informal cancer caregivers and identified sociodemographic and clinical correlates of health behavior engagement. Using data from the Health Information National Trends Survey (HINTS), an exploratory latent profile analysis (LPA) was conducted among a nationally representative sample of those self-reporting a history of cancer or identifying as a cancer caregiver. The LPA model was fit with continuous variables for daily self-reported FVI (servings/d), MPVA (minutes/d) and sleep duration (hours/d). Multinomial logistic regression models were used to predict profile membership based on current age, education, relationship status, income, rurality, body mass index (BMI), other health behaviors, and role (survivor or caregiver). Four health behavior profiles were identified (Least Engaged–Sedentary, Least Engaged–Inactive, Moderately Engaged, and Highly Engaged). The largest profile membership was Least-Engaged Sedentary, capturing 37% of the sample. Profiles were most distinguished by MVPA with the lowest variance in sleep duration. Health behavior profile membership was significantly associated with current age, relationship status, education, income, rurality, alcohol use, self-efficacy, psychological distress, BMI, and cancer type. This study identified that, in a nationally representative sample, cancer survivors and cancer caregivers who reported more FVI also often reported greater MVPA and longer sleep duration. Health behavior profiles and sociodemographic correlates can help identify for whom health behavior interventions may be of greatest benefit.\u003c/p\u003e","manuscriptTitle":"Patterns of Dietary Quality, Physical Activity, and Sleep Duration among Cancer Survivors and Caregivers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-16 18:34:44","doi":"10.21203/rs.3.rs-4271736/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"40679f97-cb36-446c-b4ad-0f88935f47dc","owner":[],"postedDate":"April 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-16T18:34:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-16 18:34:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4271736","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4271736","identity":"rs-4271736","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}