Sun Protective Behaviors Amongst Non-White US Adults from 2003-2023 

Sun Protective Behaviors Amongst Non-White US Adults from 2003-2023 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sun Protective Behaviors Amongst Non-White US Adults from 2003-2023 Christine Olagun-Samuel, Edwine Coulanges, Jamon Thomas, Kajal Gupta, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7263486/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Sun-protective behaviors play a significant role in preventing UV-related skin damage, photoaging, increased pigmentation in pigmentary disorders, and skin cancer. Understanding changes in sun protection practices over time can further elucidate the long-term impact of ongoing efforts to educate populations about the role of UV exposure in these pathologies. We assessed 20-year trends in sun-protective behaviors (sunscreen use, shade-seeking, and long-sleeve clothing) among U.S. adults according to race and ethnicity using nationally representative data from the National Health and Nutrition Examination Survey (NHANES) between 2003 and 2023. We analyzed responses from 28,765 U.S. adults using logistic regression models, adjusted for age, sex, education, income-to-poverty ratio, and occupation to assess behavioral trends across racial groups: Black, White, and Other (Hispanic, Asian, Multiracial). Our analysis indicated all racial groups had statistically significant increases in sunscreen use over time (White p = 0.0267, Black p = 0.0013, Other p < 0.0001). White participants consistently used sunscreen more than any group (from 28.7% in 2003-04, rising to 36.4% in 2021–23). Black participants reported the lowest usage compared to White and Other racial groups but demonstrated a steady increase over the course of this 20-year period, starting from 4.4% in 2003–04, peaking at 11.4% in 2021–23. Sunscreen use amongst Other races, showed steady increases from 17.2% to 29.1% over the course of this 20-year period. Compared to Black adults, the odds of sunscreen use were significantly higher among White (OR 8.01, 95% CI 5.15–12.47) and Other race participants (OR 5.91, 95% CI 3.86–9.04). In contrast, Black participants reported the highest rates of shade-seeking behavior, and Other races reported the highest use of long-sleeve protective clothing. Our findings highlight persistent disparities in sun-protective behaviors, particularly low sunscreen use among Black Americans despite improvement over time. Cultural norms, cosmetic acceptability (specifically white cast), and lack of inclusive public health messaging may play a role in these trends. Future education efforts, more tailored resources and inclusive messaging may help bridge this gap and advance skin health equity. UV protection disparities public health education Figures Figure 1 Figure 2 Introduction Chronic sun exposure contributes to various dermatologic conditions, including erythema, tanning, photoaging, and carcinogenesis. 1 – 4 Although individuals with darker skin tones may have some protection, they also experience these effects. Public health campaigns have worked to dispel misinformation surrounding sun protection in darker-skinned populations. 1 Though darker skin types are more resistant to photoaging due to the protective effects of melanin, they are more prone to pigmentary disorders, such as post-inflammatory hyperpigmentation (PIH). 5 Although the incidence of skin cancers like melanoma and keratinocyte carcinoma is lower in SOC populations, when they do occur, they tend to present more aggressively. 6 , 7 Delayed diagnoses due to atypical clinical presentations and socioeconomic factors often lead to worse outcomes for SOC individuals. 8 The disparities in sun protection behaviors and skin cancer outcomes reflect broader healthcare access issues, dermatologic education, and cultural perceptions of skin health in darker skin populations. Understanding changes in sun exposure behaviors and protective practices is essential for evaluating the long-term impact of these interventions. Few studies have examined how sun-protective behaviors have evolved across racial and ethnic groups over time, highlighting a need to evaluate the impact of current public health efforts in improving sun-protection. The National Health and Nutrition Examination Study (NHANES), a program conducted by the Center of Disease Control (CDC), collects data on the health and nutritional status in the United States. This study aims to analyze data from the NHANES databases to assess trends in sun-protective behaviors among the U.S. adult population over the last two decades. Methods Study Sample Data was collected from the National Health and Nutrition Examination Survey (NHANES), an annual, cross-sectional survey conducted by the US Census Bureau. Sample weights provided by the NHIS, National Health Interview Survey are used to yield estimates representative of the non-military, non-institutionalized US population. The NHANES examines a nationally representative sample of about 5,000 persons each year. These data are collected via face-to-face interviews in respondents’ homes. The earliest record of sun-protective behaviors was during the 2003 survey. We collected data from a series of NHANES databases up until 2023. This study was exempt from the New York University Institutional Review Board. Measures We pooled NHANES 2-year cycles 2003–2004, 2005–2006, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2021–2023, excluding 2007–2008 and 2017–2018. Participants missing any outcome or key covariate (age, sex, education, income-to-poverty ratio, hours worked, occupation) were dropped, yielding 28, 765 non-White adults. Each behavior was dichotomized (“Always”/“Most of the time” = 1; otherwise = 0). Race was categorized as Black (reference), Other (Hispanic, Asian, Multiracial), or White. We fit three logistic regression models for each behavior using R’s survey package (PSU = SDMVPSU; strata = SDMVSTRA; weight = WTMEC2YR): Model 1: Race + Year, Model 2: Model 1 + Age, Sex, Education, Income-to-Poverty, Hours Worked, Occupation, Model 3: Model 2 + Race × Year interaction. Results Demographic Data The NHANES survey, across the years 2003 and 2023, included survey results from 28, 765 US adults. Demographic data was weighted (See Table 1 ). A bivariate analysis across years accounted for race and each sun protective behavior. When analyzing data for demographic variables across all time periods, females had lower odds of seeking shade (OR 0.71 [0.62–0.82]) and long-sleeves use (0.71 [0.62–0.82]), but nearly three times higher odds of sunscreen use (2.99 [2.45–3.66]) (See Table 2 ). Participants aged 40–65 had slightly higher odds of shade seeking behavior and wearing long sleeves compared to a reference range of 18–39, (OR 1.03 [1.02–1.04]), and no effect on sunscreen use. Education measures, specifically schooling past the 9th grade, were associated with lower shade/sleeve odds, with college graduates having an OR 0.56 [0.41–0.77]. However, more advanced education levels were associated with higher odds of sunscreen usage (4.01 [3.01–5.34]). A higher income-to-Poverty index r ≥ 5 vs. <5 was associated with slightly lower shade/sleeve odds (0.94 [0.90–0.99]) and higher sunscreen odds (1.16 [1.10–1.22]). Sunscreen Use Trends The bivariate analysis indicated that all groups had statistically significant increases in sunscreen use over time (White p = 0.0267, Black p = 0.0013, Other p < 0.0001). White participants consistently used sunscreen more than any group (from 28.7% in 2003-04, rising to 36.4% in 2021–23). Black participants reported very low usage throughout, however demonstrated a steady increase over the course of this 20-year period, starting from (4.4% in 2003–04, and ultimately peaking at 11.4% in the years 2021–23 (Table 3 ). Sunscreen use amongst other races, non-Black and Non-White, showed steady increases from 17.2–29.1% over the course of this 20 year period (see Table 1 ). A fully adjusted odds ratio was created with Black participants as reference. Using the interaction model depicted in Table 2 , overall, white participants had eight times greater odds of using sunscreen (OR 8.01, 95% CI 5.15–12.47) compared to Black participants when adjusting for the year across this 20 year period. Whereas, other non-White races had a 5.91 [3.86–9.04], odds of sunscreen use, (both p < 0.01) compared to Black patients. Shade Protection Trends Black participants consistently reported the highest rates of staying in the shade (range: 38.3–48.7%).White participants had the lowest prevalence, increasing from 21.3% in 2005–06 to 32.4% in 2021–23. Other racial groups reported intermediate rates, mostly 35–41%. (White p = 0.0267, Black p = 0.0013, Other p < 0.0001). Model 3 provided a fully adjusted odds ratio with Black participants as reference and indicates that those of other non-White races had a higher odds of seeking shade with an OR 1.96 [1.43–2.69]. Whites also had a higher odds ratio of 1.75 [1.30–2.36] (both p < 0.05) compared to Black patients. Long Sleeve Use Trends Fully adjusted odds ratios (95% CI) in Model 3, using Black participants as the reference, found that other races engaged in wearing long sleeves at a higher OR, 1.96 [1.46–2.62] (p < 0.05). White participants engaged in using long sleeve sun protective clothing less than Black participants with an OR 0.76 [0.55–1.05], however this was not significantly different. Though there is a large amount of variability of long sleeve use across races, ultimately there is significant sun-protective clothing use amongst non-White and non-Black races (See Fig. 2 ). Discussion The findings from this study reveal important trends in sun-protective behaviors amongst non-White U.S. adults, and highlights the role of improved public health efforts, particularly in education and access. However, it maintains that compared to other non-White races, and their White counterparts, Black individuals had lowest sun-protective behaviors, albeit significant improvements over time. It is apparent that public health efforts over the course of the decade included in this study were effective in increasing sunscreen use, however, there remains significant opportunity for increased advocacy to address apparent disparities. Other sun-protective behaviors had variable utilization. These variations, particularly the higher use of shade-seeking and long-sleeve clothing among Black, Hispanic and Asian populations, may be attributed to both cultural and practical factors. Rooted in African heritage, Black communities have historically relied on physical barriers like shade, hats, turbans, and long-sleeved clothing for sun protection in regions with intense UV radiation. A study of informal workers in African markets, who spend entire days in the sun, found that portable shade was the most common form of photoprotection, used by 69.9% of participants. 9 In modern U.S. Black communities, these cultural practices persist, manifesting as increased use of hats, long sleeves, and shade-seeking and are often more effective at preventing sunburn than sunscreen alone. Similarly, in Asian cultures, where fairer skin is a prevailing beauty standard, parasols are commonly used to prevent tanning. 10 It is possible that practical barriers such as the cost of sunscreen and the undesirable “white cast” residue associated with physical sunscreens may drive greater reliance on these traditional, non-chemical photoprotective methods. There is a common belief that individuals with darker skin types are less susceptible to skin cancer due to higher melanin content, which provides some natural protection against ultraviolet (UV) radiation. 11 While skin cancer incidence is lower in these populations, they are not immune, and skin cancers often present at more advanced stages in people of color, leading to worse outcomes and higher mortality rates. 12 Additionally, minimizing photo exposure is the standard of care for addressing post-inflammatory hyperpigmentation, which more often occurs when skin darkens following inflammation or injury. UV exposure can exacerbate these pigmentation issues, so sun protection (e.g., using sunscreen and seeking shade) can help reduce the risk of worsening post-inflammatory hyperpigmentation from conditions like acne, eczema, and psoriasis and pigmentary conditions such as melasma. 12 Particularly, darker skin, though less susceptible to photodamage, is at higher risk of hyperpigmentation caused by visible light (VL) 1 UV-A1. 13 While darker skin provides more protection against the visible signs of aging, such as wrinkles, UV exposure can still contribute to photoaging, particularly in the form of uneven skin tone and dark spots. Regular sun protection can help prevent these signs of aging in all skin types. Particularly, tinted sunscreen can help in blocking high-energy visible light and help with hyperpigmentation, particularly in pigmentary disorders as PIH and melasma. 14 – 16 Photoprotection with broad-spectrum sunscreens (SPF 30+), especially those containing iron oxide to block visible light, is the cornerstone of treatment. 17 Chronic sun exposure, particularly UVA1 and HEVL, exacerbates these mechanisms, inducing oxidative stress, DNA damage, and pigmentation through the activation of melanocytes. 15 Unfortunately, dark-skinned individuals, who are more susceptible to melasma, often take fewer photoprotective measures. Many patients do not adhere to recommended sunscreen application practices, particularly reapplying sunscreen every two hours. Traditional sunscreens may leave a visible white cast on darker skin, which can be a barrier to regular use. 12 In a 2023 survey of 410 sunscreen products, only 1.7% of facial sunscreens contained iron oxides, essential for VL protection in the skin of color. None of the products for body use included iron oxides, and only 0.5% of non-lip products offered shade matching for varying skin tones. All tinted products were based on inorganic filters like zinc oxide and titanium dioxide, which can create a white cast on darker skin tones unless tinted. 18 Public health campaigns targeting sun protection have traditionally focused on light-skinned populations, potentially contributing to the lower engagement with sun-protective behaviors seen in non-White individuals. This highlights a need for more inclusive and culturally tailored interventions that address the unique risks individuals with darker skin tones face. Efforts to dispel the myth that darker skin is immune to sun damage should be prioritized in future health education programs, alongside encouragement of protective measures such as sunscreen use, shade-seeking behaviors, and protective clothing. Moreover, despite increasing awareness campaigns, the lack of significant increase in sunscreen use over the years suggests that barriers to sunscreen use remain unaddressed. Factors such as the lack of formulations suitable for darker skin concerns about visible residue, and the cost of high-quality sunscreens may all play a role in this persistent trend. Future research should focus on identifying and addressing these barriers to improve sunscreen adherence in non-White populations. This study is limited by its cross-sectional design, which prevents assessment of causality. Among the sun-protective behaviors examined, sunscreen use demonstrated the most substantial change over time. In contrast, the prevalence of long-sleeve clothing and shade-seeking behaviors remained relatively stable. Future studies could help elucidate the specific types of sun-protective behaviors emphasized by public health campaigns and physician-led education efforts. It is possible that sunscreen use has been inadequately promoted, despite its limitations—namely, the need for frequent reapplication and its reduced efficacy in certain settings. For example, outdoor workers such as those in construction may benefit more from consistent physical barriers like UV-protective clothing and wide-brimmed hats and the need for regular reapplication. A prior NHANES analysis (2003–2006) found that individuals who practiced shade-seeking and wore long sleeves had a 30% lower risk of sunburn compared to those who relied solely on sunscreen. 19 These findings highlight the effectiveness of sun-protective clothing as a strategy for UV protection. Additionally, sun protection education efforts should incorporate other aspects of sun protection and should not be limited to sunscreen use. Efforts to improve sun protection in more diverse groups should be part of broader strategies to address health inequities, including improving access to dermatologic care and increasing representation in skin health research. Table 1 Weighted Demographic Representation of NHANES Participants 2003–2023 2003–2004 2005–2006 2009–2010 2011–2012 2013–2014 2015–2016 2021–2023 Study Participants (N) 3140 3409 4145 3769 3928 3818 4305 Gender (%) (95% CI) Male 49.2 (47.8–50.5) 49.3 (47.9–50.7) 49.4 (48.1–50.8) 49 (46.8–51.2) 49.1 (47.8–50.4) 49.1 (47.6–50.7) 49.5 (47.7–51.4) Female 50.8 (49.5–52.2) 50.7 (49.3–52.1) 50.6 (49.2–51.9) 51 (48.8–53.2) 50.9 (49.6–52.2) 50.9 (49.3–52.4) 50.5 (48.6–52.3) Age (%) (95% CI) 18–39 50.2 (47.4–53.1) 49.3 (46.8–51.9) 49.2 (47.1–51.3) 48.9 (44–53.8) 49.5 (47.1–52) 50.2 (47.5–52.9) 51.4 (48.7–54) 40–65 49.8 (46.9–52.6) 50.7 (48.1–53.2) 50.8 (48.7–52.9) 51.1 (46.2–56) 50.5 (48–52.9) 49.8 (47.1–52.5) 48.6 (46–51.3) Education Level (%) (95% CI) College graduate 24.3 (21.2–27.4) 27.1 (22.6–31.6) 28.8 (26.1–31.6) 31.9 (26.7–37.1) 30.5 (26.3–34.8) 33.3 (27–39.7) 35.7 (29.1–42.2) Grade 9–11 11.3 (10–12.6) 10.4 (8–12.7) 12.4 (11.4–13.3) 10.9 (7.9–13.9) 10.8 (8.6–13) 8.6 (6.6–10.5) 5.9 (4.2–7.7) High school 26.4 (24.2–28.5) 23.7 (21.9–25.5) 22.4 (20–24.8) 19.5 (16.9–22.2) 21.6 (18.5–24.7) 19.7 (17.3–22) 25.2 (21.5–28.9) < 9th grade 4.6 (3.6–5.6) 5 (3.5–6.4) 5.3 (4–6.6) 4.5 (3.4–5.6) 3.8 (3–4.7) 5.5 (3.6–7.3) 3.2 (2.1–4.3) Some college 33.4 (30.8–36) 33.9 (31.7–36) 31.1 (29.5–32.6) 33.2 (29.9–36.5) 33.2 (30.9–35.6) 33 (29.7–36.2) 30 (26.6–33.4) Marital Status (%) (95% CI) Married/Living with partner 64.6 (61.8–67.5) 67.6 (64.3–70.8) 63 (61.1–65) 60.4 (55.9–65) 62.3 (59.5–65) 64.6 (61.4–67.8) 60.5 (58.3–62.8) Widowed/Divorced/Separated 35.4 (32.5–38.2) 32.4 (29.2–35.7) 37 (35–38.9) 39.6 (35–44.1) 37.7 (35–40.5) 35.4 (32.2–38.6) 39.5 (37.2–41.7) Nativity Status (%) (95% CI) Born in US 83.4 (79–87.8) 83.1 (78.4–87.8) 79.2 (74.3–84) 79.6 (75.3–84) 80.9 (77.4–84.4) 79.6 (75.5–83.6) 79 (75.7–82.3) Not born in US 16.6 (12.2–21) 16.9 (12.2–21.6) 20.8 (16–25.7) 20.4 (16–24.7) 19.1 (15.6–22.6) 20.4 (16.4–24.5) 21 (17.7–24.3) Employment Status (%) (95% CI) Looking for Work 2.8 (2–3.5) 2.1 (1.5–2.7) 3.9 (3.1–4.7) 4.9 (4–5.8) 3.1 (2.4–3.8) 3.9 (3–4.7) 5.5 (4.2–6.9) Not at Work 4.4 (3.1–5.6) 3.9 (2.7–5) 2.4 (1.4–3.5) 2.2 (1.5–2.8) 2 (1.3–2.6) 2.8 (2.1–3.4) 4 (3.3–4.8) Not Working 20.6 (18.5–22.7) 18.1 (15.7–20.5) 23.2 (21.4–25) 23.2 (20.1–26.4) 23 (20–26.1) 18.3 (16.1–20.5) 18.2 (16.3–20.2) Working 72.2 (70.4–74.1) 76 (73–78.9) 70.4 (67.8–73.1) 69.7 (66.9–72.5) 72 (69.1–74.8) 75 (72.5–77.4) 72.2 (69.6–74.8) Avg Work Hours (hours/week) 42.5 43.3 41.4 41.1 41.6 41.3 40.8 Table 2 Adjusted Odds Ratios (95% CI) for Sun−Protective Behaviors from Logistic Regression Models Seek Shade Long Sleeve Sunscreen Race (OR[(95% CI]) Black Reference Value Other 1.96 [1.43–2.69] 1.96 [1.46–2.62] 5.91 [3.86–9.04] White 1.75 [1.30–2.36] 0.76 [0.55–1.05] 8.01 [5.36–11.96] Gender (OR[(95% CI]) Male Reference Value Female 0.71 [0.62–0.82] 0.71 [0.62–0.82] 2.99 [2.45–3.66] Age (OR[(95% CI]) 18–39 Reference Value 40–65 1.03 [1.02–1.04] 1.03 [1.02–1.04] 1.00 [0.99–1.01] Gender (OR[(95% CI]) Less than 9th Reference Value 9–11th 0.55 [0.40–0.75] 0.55 [0.40–0.75] 1.12 [0.78–1.61] High school/GED 0.44 [0.31–0.63] 0.44 [0.31–0.63] 1.39 [1.06–1.83] Some college/AA 0.51 [0.37–0.69] 0.51 [0.37–0.69] 2.14 [1.63–2.81] College graduate or above 0.56 [0.41–0.77] 0.56 [0.41–0.77] 4.01 [3.01–5.34] Income to Poverty Ratio (OR[(95% CI]) 0 to 4.99 Reference Value 5 0.94 [0.90–0.99] 0.94 [0.90–0.99] 1.16 [1.10–1.22] Hours Worked Per Week (OR[(95% CI]) 1.01 [0.99–1.03] 1.01 [0.99–1.03] 0.99 [0.97–1.00] *OR in bold signifies statistically significant results (p < 0.05) . Table 3 Sun-Protective Behaviors by Race Sunscreen Use Shade Protection Long Sleeve Use Black (%) (95% CI) White (%) (95% CI) Other Race (%) (95% CI) Black (%) (95% CI) White (%) (95% CI) Other Race (%) (95% CI) Black (%) (95% CI) White (%) (95% CI) Other Race (%) (95% CI) 2003–2004 4.4 (3.3–5.4) 28.7 (24.2–33.3) 17.2 (14–20.3) 46.2 (42.4–50) 26.5 (23.8–29.1) 37.8 (32.4–43.3) 6.4 (4.5–8.4) 5.5 (4–7) 13.1 (8.8–17.3) 2005–2006 6.6 (4.4–8.8) 31.7 (28.8–34.6) 17.7 (15.1–20.3) 38.3 (35.4–41.3) 21.3 (19.6–22.9) 35.2 (31.9–38.6) 9.2 (7.2–11.1) 5.6 (3.8–7.4) 12.4 (9.8–14.9) 2009–2010 6.1 (4.8–7.4) 34.2 (32.2–36.2) 23.6 (20–27.2) 43.3 (39.2–47.5) 26.2 (23.1–29.3) 37.5 (35–40.1) 7.6 (5.3–10) 6.5 (4.9–8.2) 18.2 (14.4–21.9) 2011–2012 10.5 (8.1–12.8) 38.6 (33.8–43.4) 24.0 (20.7–27.4) 48.7 (44.7–52.7) 27.3 (23–31.7) 40.7 (35.9–45.5) 11.0 (9.2–12.8) 8.3 (6.4–10.3) 15.9 (12.7–19.1) 2013–2014 7.1 (5.6–8.7) 36.4 (31.2–41.6) 25.4 (22.4–28.5) 41.8 (38.5–45.2) 24.9 (22.4–27.5) 41.3 (36.1–46.6) 8.6 (7.5–9.8) 6.2 (5–7.4) 14.2 (12.2–16.3) 2015–2016 8.1 (5.4–10.8) 33.9 (29.7–38.1) 22.1 (19.1–25.2) 48.1 (45.5–50.7) 25.2 (22.1–28.3) 38.2 (35.2–41.2) 9.8 (6.8–12.8) 6.3 (4.7–7.9) 17.5 (13.5–21.6) 2021–2023 11.4 (7–15.8) 36.4 (32.2–40.7) 29.1 (24.8–33.4) 38.5 (30.3–46.6) 32.4 ​​(29.3–35.6) 35.0 (30.6–39.3) 8.3 (5.4–11.2) 8.2 (6.1–10.3) 18.5 (15–21.9) Declarations Conflicts of Interest: There are no potential conflicts of interest or competing interests to disclose. Funding: None IRB Study Number: Not applicable Patient Consent: Not applicable Author Contribution C.O. conceived the project, led the data analysis, and drafted the manuscript. E.C. and J.T. contributed to writing and editing the manuscript. K.G., H.Y., and X.P. assisted with statistical analysis and methodological design. C.O., K.G., H.Y., and X.P. developed the study methodology. P.A. provided project supervision and oversight. All authors contributed to the critical review and revision of the manuscript and approved the final version. References Pellacani G, Lim HW, Stockfleth E, Sibaud V, Brugués AO, Saint Aroman M (2024) Photoprotection: Current developments and controversies. Acad Dermatol Venereol 38(S5):12–20. 10.1111/jdv.19677 Matsumura Y, Ananthaswamy HN (2002) Short-term and long-term cellular and molecular events following UV irradiation of skin: implications for molecular medicine. 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Photochem Photobiol Sci 22(2):441–456. 10.1007/s43630-022-00314-z Shetty NP, Taylor SC, Lim HW (2023) Personalized photoprotection: Commentary on Adjusting best practices in the treatment of melasma with a focus on patients with skin of color. J Am Acad Dermatol 89(3):635–636. 10.1016/j.jaad.2023.05.038 Zhou C, Lee C, Salas J, Luke J (2023) Guide to tinted sunscreens in skin of color. Int J Dermatology Published online Dec 10. 10.1111/ijd.16954 Morgado-Carrasco D, Piquero‐Casals J, Granger C, Trullàs C, Passeron T (2022) Melasma: The need for tailored photoprotection to improve clinical outcomes. Photoderm Photoimm Photomed 38(6):515–521. 10.1111/phpp.12783 He M, Chen X, Jin S, Zhang C (2025) Visible Light Protection: An Updated Review of Tinted Sunscreens. Photoderm Photoimm Photomed 41(4). 10.1111/phpp.70033 Moolla S, Miller-Monthrope Y (2022) Dermatology: how to manage facial hyperpigmentation in skin of colour. Drugs Context 11:2021–2011. 10.7573/dic.2021-11-2 Cole Y, Ilyas AM, Ilyas EN Availability of Adequate Photoprotection for Skin of Color. Cureus 15(8):e42794. 10.7759/cureus.42794 Linos E, Keiser E, Fu T, Colditz G, Chen S, Tang JY (2011) Hat, shade, long sleeves, or sunscreen? Rethinking US sun protection messages based on their relative effectiveness. Cancer Causes Control 22(7):1067–1071. 10.1007/s10552-011-9780-1 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 29 Sep, 2025 Reviews received at journal 28 Sep, 2025 Reviews received at journal 23 Sep, 2025 Reviewers agreed at journal 21 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers invited by journal 15 Sep, 2025 Editor assigned by journal 01 Aug, 2025 Submission checks completed at journal 01 Aug, 2025 First submitted to journal 31 Jul, 2025 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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06:21:38","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94265,"visible":true,"origin":"","legend":"","description":"","filename":"a2cb6add05024103b73f7dae2e3fb80c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7263486/v1/ab1119a356359f52ad3a44b5.xml"},{"id":92053188,"identity":"9961d133-fe33-46bc-8e4a-31d843e280b6","added_by":"auto","created_at":"2025-09-24 06:21:38","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":106798,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7263486/v1/a42bd7d73ee2bbed36cd44ba.html"},{"id":92053178,"identity":"e942c4a7-b8e6-442a-b733-94c1215a81e4","added_by":"auto","created_at":"2025-09-24 06:21:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78621,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted Probability of Sunscreen Use by Race and Year\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7263486/v1/186f92070b8d8f84f38ba548.png"},{"id":92053179,"identity":"219881cd-3418-45c8-93e3-a2ff46ee5382","added_by":"auto","created_at":"2025-09-24 06:21:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted Probability of Wearing Long Sleeves by Race and Year\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7263486/v1/40794753d4568525ea609eeb.png"},{"id":92054382,"identity":"ab34da24-8ede-4756-90b7-1fb4b6298adf","added_by":"auto","created_at":"2025-09-24 06:37:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1306894,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7263486/v1/f3c382c6-6355-46db-ab1b-770fc14e0e6a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sun Protective Behaviors Amongst Non-White US Adults from 2003-2023 ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic sun exposure contributes to various dermatologic conditions, including erythema, tanning, photoaging, and carcinogenesis.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Although individuals with darker skin tones may have some protection, they also experience these effects. Public health campaigns have worked to dispel misinformation surrounding sun protection in darker-skinned populations.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Though darker skin types are more resistant to photoaging due to the protective effects of melanin, they are more prone to pigmentary disorders, such as post-inflammatory hyperpigmentation (PIH).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Although the incidence of skin cancers like melanoma and keratinocyte carcinoma is lower in SOC populations, when they do occur, they tend to present more aggressively.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Delayed diagnoses due to atypical clinical presentations and socioeconomic factors often lead to worse outcomes for SOC individuals.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The disparities in sun protection behaviors and skin cancer outcomes reflect broader healthcare access issues, dermatologic education, and cultural perceptions of skin health in darker skin populations. Understanding changes in sun exposure behaviors and protective practices is essential for evaluating the long-term impact of these interventions. Few studies have examined how sun-protective behaviors have evolved across racial and ethnic groups over time, highlighting a need to evaluate the impact of current public health efforts in improving sun-protection. The National Health and Nutrition Examination Study (NHANES), a program conducted by the Center of Disease Control (CDC), collects data on the health and nutritional status in the United States. This study aims to analyze data from the NHANES databases to assess trends in sun-protective behaviors among the U.S. adult population over the last two decades.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Sample\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData was collected from the National Health and Nutrition Examination Survey (NHANES), an annual, cross-sectional survey conducted by the US Census Bureau. Sample weights provided by the NHIS, National Health Interview Survey are used to yield estimates representative of the non-military, non-institutionalized US population. The NHANES examines a nationally representative sample of about 5,000 persons each year. These data are collected via face-to-face interviews in respondents’ homes. The earliest record of sun-protective behaviors was during the 2003 survey. We collected data from a series of NHANES databases up until 2023. This study was exempt from the New York University Institutional Review Board.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe pooled NHANES 2-year cycles 2003–2004, 2005–2006, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2021–2023, excluding 2007–2008 and 2017–2018. Participants missing any outcome or key covariate (age, sex, education, income-to-poverty ratio, hours worked, occupation) were dropped, yielding 28, 765 non-White adults. Each behavior was dichotomized (“Always”/“Most of the time” = 1; otherwise = 0). Race was categorized as Black (reference), Other (Hispanic, Asian, Multiracial), or White. We fit three logistic regression models for each behavior using R’s survey package (PSU = SDMVPSU; strata = SDMVSTRA; weight = WTMEC2YR): Model 1: Race + Year, Model 2: Model 1 + Age, Sex, Education, Income-to-Poverty, Hours Worked, Occupation, Model 3: Model 2 + Race × Year interaction.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eDemographic Data\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe NHANES survey, across the years 2003 and 2023, included survey results from 28, 765 US adults. Demographic data was weighted (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A bivariate analysis across years accounted for race and each sun protective behavior. When analyzing data for demographic variables across all time periods, females had lower odds of seeking shade (OR 0.71 [0.62\u0026ndash;0.82]) and long-sleeves use (0.71 [0.62\u0026ndash;0.82]), but nearly three times higher odds of sunscreen use (2.99 [2.45\u0026ndash;3.66]) (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Participants aged 40\u0026ndash;65 had slightly higher odds of shade seeking behavior and wearing long sleeves compared to a reference range of 18\u0026ndash;39, (OR 1.03 [1.02\u0026ndash;1.04]), and no effect on sunscreen use. Education measures, specifically schooling past the 9th grade, were associated with lower shade/sleeve odds, with college graduates having an OR 0.56 [0.41\u0026ndash;0.77]. However, more advanced education levels were associated with higher odds of sunscreen usage (4.01 [3.01\u0026ndash;5.34]). A higher income-to-Poverty index r\u0026thinsp;\u0026ge;\u0026thinsp;5 vs. \u0026lt;5 was associated with slightly lower shade/sleeve odds (0.94 [0.90\u0026ndash;0.99]) and higher sunscreen odds (1.16 [1.10\u0026ndash;1.22]).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSunscreen Use Trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe bivariate analysis indicated that all groups had statistically significant increases in sunscreen use over time (White p\u0026thinsp;=\u0026thinsp;0.0267, Black p\u0026thinsp;=\u0026thinsp;0.0013, Other p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). White participants consistently used sunscreen more than any group (from 28.7% in 2003-04, rising to 36.4% in 2021\u0026ndash;23). Black participants reported very low usage throughout, however demonstrated a steady increase over the course of this 20-year period, starting from (4.4% in 2003\u0026ndash;04, and ultimately peaking at 11.4% in the years 2021\u0026ndash;23 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Sunscreen use amongst other races, non-Black and Non-White, showed steady increases from 17.2\u0026ndash;29.1% over the course of this 20 year period (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A fully adjusted odds ratio was created with Black participants as reference. Using the interaction model depicted in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, overall, white participants had eight times greater odds of using sunscreen (OR 8.01, 95% CI 5.15\u0026ndash;12.47) compared to Black participants when adjusting for the year across this 20 year period. Whereas, other non-White races had a 5.91 [3.86\u0026ndash;9.04], odds of sunscreen use, (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to Black patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eShade Protection Trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBlack participants consistently reported the highest rates of staying in the shade (range: 38.3\u0026ndash;48.7%).White participants had the lowest prevalence, increasing from 21.3% in 2005\u0026ndash;06 to 32.4% in 2021\u0026ndash;23. Other racial groups reported intermediate rates, mostly 35\u0026ndash;41%. (White p\u0026thinsp;=\u0026thinsp;0.0267, Black p\u0026thinsp;=\u0026thinsp;0.0013, Other p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Model 3 provided a fully adjusted odds ratio with Black participants as reference and indicates that those of other non-White races had a higher odds of seeking shade with an OR 1.96 [1.43\u0026ndash;2.69]. Whites also had a higher odds ratio of 1.75 [1.30\u0026ndash;2.36] (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to Black patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLong Sleeve Use Trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFully adjusted odds ratios (95% CI) in Model 3, using Black participants as the reference, found that other races engaged in wearing long sleeves at a higher OR, 1.96 [1.46\u0026ndash;2.62] (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). White participants engaged in using long sleeve sun protective clothing less than Black participants with an OR 0.76 [0.55\u0026ndash;1.05], however this was not significantly different. Though there is a large amount of variability of long sleeve use across races, ultimately there is significant sun-protective clothing use amongst non-White and non-Black races (See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings from this study reveal important trends in sun-protective behaviors amongst non-White U.S. adults, and highlights the role of improved public health efforts, particularly in education and access. However, it maintains that compared to other non-White races, and their White counterparts, Black individuals had lowest sun-protective behaviors, albeit significant improvements over time. It is apparent that public health efforts over the course of the decade included in this study were effective in increasing sunscreen use, however, there remains significant opportunity for increased advocacy to address apparent disparities.\u003c/p\u003e\u003cp\u003eOther sun-protective behaviors had variable utilization. These variations, particularly the higher use of shade-seeking and long-sleeve clothing among Black, Hispanic and Asian populations, may be attributed to both cultural and practical factors. Rooted in African heritage, Black communities have historically relied on physical barriers like shade, hats, turbans, and long-sleeved clothing for sun protection in regions with intense UV radiation. A study of informal workers in African markets, who spend entire days in the sun, found that portable shade was the most common form of photoprotection, used by 69.9% of participants.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e In modern U.S. Black communities, these cultural practices persist, manifesting as increased use of hats, long sleeves, and shade-seeking and are often more effective at preventing sunburn than sunscreen alone. Similarly, in Asian cultures, where fairer skin is a prevailing beauty standard, parasols are commonly used to prevent tanning.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e It is possible that practical barriers such as the cost of sunscreen and the undesirable \u0026ldquo;white cast\u0026rdquo; residue associated with physical sunscreens may drive greater reliance on these traditional, non-chemical photoprotective methods.\u003c/p\u003e\u003cp\u003eThere is a common belief that individuals with darker skin types are less susceptible to skin cancer due to higher melanin content, which provides some natural protection against ultraviolet (UV) radiation.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e While skin cancer incidence is lower in these populations, they are not immune, and skin cancers often present at more advanced stages in people of color, leading to worse outcomes and higher mortality rates.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAdditionally, minimizing photo exposure is the standard of care for addressing post-inflammatory hyperpigmentation, which more often occurs when skin darkens following inflammation or injury. UV exposure can exacerbate these pigmentation issues, so sun protection (e.g., using sunscreen and seeking shade) can help reduce the risk of worsening post-inflammatory hyperpigmentation from conditions like acne, eczema, and psoriasis and pigmentary conditions such as melasma.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Particularly, darker skin, though less susceptible to photodamage, is at higher risk of hyperpigmentation caused by visible light (VL) 1 UV-A1.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e While darker skin provides more protection against the visible signs of aging, such as wrinkles, UV exposure can still contribute to photoaging, particularly in the form of uneven skin tone and dark spots. Regular sun protection can help prevent these signs of aging in all skin types. Particularly, tinted sunscreen can help in blocking high-energy visible light and help with hyperpigmentation, particularly in pigmentary disorders as PIH and melasma.\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePhotoprotection with broad-spectrum sunscreens (SPF 30+), especially those containing iron oxide to block visible light, is the cornerstone of treatment.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Chronic sun exposure, particularly UVA1 and HEVL, exacerbates these mechanisms, inducing oxidative stress, DNA damage, and pigmentation through the activation of melanocytes.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Unfortunately, dark-skinned individuals, who are more susceptible to melasma, often take fewer photoprotective measures. Many patients do not adhere to recommended sunscreen application practices, particularly reapplying sunscreen every two hours.\u003c/p\u003e\u003cp\u003eTraditional sunscreens may leave a visible white cast on darker skin, which can be a barrier to regular use.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In a 2023 survey of 410 sunscreen products, only 1.7% of facial sunscreens contained iron oxides, essential for VL protection in the skin of color. None of the products for body use included iron oxides, and only 0.5% of non-lip products offered shade matching for varying skin tones. All tinted products were based on inorganic filters like zinc oxide and titanium dioxide, which can create a white cast on darker skin tones unless tinted.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePublic health campaigns targeting sun protection have traditionally focused on light-skinned populations, potentially contributing to the lower engagement with sun-protective behaviors seen in non-White individuals. This highlights a need for more inclusive and culturally tailored interventions that address the unique risks individuals with darker skin tones face.\u003c/p\u003e\u003cp\u003eEfforts to dispel the myth that darker skin is immune to sun damage should be prioritized in future health education programs, alongside encouragement of protective measures such as sunscreen use, shade-seeking behaviors, and protective clothing. Moreover, despite increasing awareness campaigns, the lack of significant increase in sunscreen use over the years suggests that barriers to sunscreen use remain unaddressed. Factors such as the lack of formulations suitable for darker skin concerns about visible residue, and the cost of high-quality sunscreens may all play a role in this persistent trend. Future research should focus on identifying and addressing these barriers to improve sunscreen adherence in non-White populations.\u003c/p\u003e\u003cp\u003eThis study is limited by its cross-sectional design, which prevents assessment of causality. Among the sun-protective behaviors examined, sunscreen use demonstrated the most substantial change over time. In contrast, the prevalence of long-sleeve clothing and shade-seeking behaviors remained relatively stable. Future studies could help elucidate the specific types of sun-protective behaviors emphasized by public health campaigns and physician-led education efforts. It is possible that sunscreen use has been inadequately promoted, despite its limitations\u0026mdash;namely, the need for frequent reapplication and its reduced efficacy in certain settings. For example, outdoor workers such as those in construction may benefit more from consistent physical barriers like UV-protective clothing and wide-brimmed hats and the need for regular reapplication. A prior NHANES analysis (2003\u0026ndash;2006) found that individuals who practiced shade-seeking and wore long sleeves had a 30% lower risk of sunburn compared to those who relied solely on sunscreen.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e These findings highlight the effectiveness of sun-protective clothing as a strategy for UV protection. Additionally, sun protection education efforts should incorporate other aspects of sun protection and should not be limited to sunscreen use. Efforts to improve sun protection in more diverse groups should be part of broader strategies to address health inequities, including improving access to dermatologic care and increasing representation in skin health research.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWeighted Demographic Representation of NHANES Participants 2003\u0026ndash;2023\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2003\u0026ndash;2004\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2005\u0026ndash;2006\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2021\u0026ndash;2023\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStudy Participants (N)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3769\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3928\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4305\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.2 (47.8\u0026ndash;50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49.3 (47.9\u0026ndash;50.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.4 (48.1\u0026ndash;50.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49 (46.8\u0026ndash;51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e49.1 (47.8\u0026ndash;50.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49.1 (47.6\u0026ndash;50.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e49.5 (47.7\u0026ndash;51.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.8 (49.5\u0026ndash;52.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.7 (49.3\u0026ndash;52.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.6 (49.2\u0026ndash;51.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51 (48.8\u0026ndash;53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e50.9 (49.6\u0026ndash;52.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50.9 (49.3\u0026ndash;52.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e50.5 (48.6\u0026ndash;52.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003e18\u0026ndash;39\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.2 (47.4\u0026ndash;53.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49.3 (46.8\u0026ndash;51.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.2 (47.1\u0026ndash;51.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48.9 (44\u0026ndash;53.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e49.5 (47.1\u0026ndash;52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50.2 (47.5\u0026ndash;52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51.4 (48.7\u0026ndash;54)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003e40\u0026ndash;65\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.8 (46.9\u0026ndash;52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.7 (48.1\u0026ndash;53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.8 (48.7\u0026ndash;52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51.1 (46.2\u0026ndash;56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e50.5 (48\u0026ndash;52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49.8 (47.1\u0026ndash;52.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e48.6 (46\u0026ndash;51.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCollege graduate\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.3 (21.2\u0026ndash;27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.1 (22.6\u0026ndash;31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.8 (26.1\u0026ndash;31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.9 (26.7\u0026ndash;37.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.5 (26.3\u0026ndash;34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33.3 (27\u0026ndash;39.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e35.7 (29.1\u0026ndash;42.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGrade 9\u0026ndash;11\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.3 (10\u0026ndash;12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.4 (8\u0026ndash;12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.4 (11.4\u0026ndash;13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.9 (7.9\u0026ndash;13.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.8 (8.6\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.6 (6.6\u0026ndash;10.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.9 (4.2\u0026ndash;7.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHigh school\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.4 (24.2\u0026ndash;28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.7 (21.9\u0026ndash;25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.4 (20\u0026ndash;24.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.5 (16.9\u0026ndash;22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.6 (18.5\u0026ndash;24.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.7 (17.3\u0026ndash;22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25.2 (21.5\u0026ndash;28.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;9th grade\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.6 (3.6\u0026ndash;5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3.5\u0026ndash;6.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.3 (4\u0026ndash;6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.5 (3.4\u0026ndash;5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.8 (3\u0026ndash;4.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.5 (3.6\u0026ndash;7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.2 (2.1\u0026ndash;4.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSome college\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.4 (30.8\u0026ndash;36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.9 (31.7\u0026ndash;36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.1 (29.5\u0026ndash;32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.2 (29.9\u0026ndash;36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33.2 (30.9\u0026ndash;35.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33 (29.7\u0026ndash;36.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e30 (26.6\u0026ndash;33.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMarried/Living with partner\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.6 (61.8\u0026ndash;67.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67.6 (64.3\u0026ndash;70.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63 (61.1\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.4 (55.9\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e62.3 (59.5\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e64.6 (61.4\u0026ndash;67.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60.5 (58.3\u0026ndash;62.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eWidowed/Divorced/Separated\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.4 (32.5\u0026ndash;38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.4 (29.2\u0026ndash;35.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (35\u0026ndash;38.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39.6 (35\u0026ndash;44.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e37.7 (35\u0026ndash;40.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35.4 (32.2\u0026ndash;38.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39.5 (37.2\u0026ndash;41.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNativity Status\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBorn in US\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.4 (79\u0026ndash;87.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.1 (78.4\u0026ndash;87.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79.2 (74.3\u0026ndash;84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79.6 (75.3\u0026ndash;84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.9 (77.4\u0026ndash;84.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e79.6 (75.5\u0026ndash;83.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e79 (75.7\u0026ndash;82.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot born in US\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.6 (12.2\u0026ndash;21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.9 (12.2\u0026ndash;21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.8 (16\u0026ndash;25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.4 (16\u0026ndash;24.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.1 (15.6\u0026ndash;22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.4 (16.4\u0026ndash;24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e21 (17.7\u0026ndash;24.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLooking for Work\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.8 (2\u0026ndash;3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.1 (1.5\u0026ndash;2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.9 (3.1\u0026ndash;4.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.9 (4\u0026ndash;5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.1 (2.4\u0026ndash;3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.9 (3\u0026ndash;4.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.5 (4.2\u0026ndash;6.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot at Work\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.4 (3.1\u0026ndash;5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.9 (2.7\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4 (1.4\u0026ndash;3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.2 (1.5\u0026ndash;2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (1.3\u0026ndash;2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.8 (2.1\u0026ndash;3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4 (3.3\u0026ndash;4.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Working\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.6 (18.5\u0026ndash;22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.1 (15.7\u0026ndash;20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.2 (21.4\u0026ndash;25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.2 (20.1\u0026ndash;26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23 (20\u0026ndash;26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.3 (16.1\u0026ndash;20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e18.2 (16.3\u0026ndash;20.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eWorking\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.2 (70.4\u0026ndash;74.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (73\u0026ndash;78.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70.4 (67.8\u0026ndash;73.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e69.7 (66.9\u0026ndash;72.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72 (69.1\u0026ndash;74.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e75 (72.5\u0026ndash;77.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e72.2 (69.6\u0026ndash;74.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAvg Work Hours\u003c/b\u003e (hours/week)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003csup\u003eAdjusted Odds Ratios (95% CI) for Sun\u0026minus;Protective Behaviors from Logistic Regression Models\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003eSeek Shade\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003eLong Sleeve\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003eSunscreen\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRace\u003c/b\u003e (OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eBlack\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003eReference Value\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e1.96 [1.43\u0026ndash;2.69]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.96 [1.46\u0026ndash;2.62]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e5.91 [3.86\u0026ndash;9.04]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eWhite\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.75 [1.30\u0026ndash;2.36]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e0.76 [0.55\u0026ndash;1.05]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e8.01 [5.36\u0026ndash;11.96]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e (OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003eReference Value\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.71 [0.62\u0026ndash;0.82]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.71 [0.62\u0026ndash;0.82]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e2.99 [2.45\u0026ndash;3.66]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e (OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e18\u0026ndash;39\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003eReference Value\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e40\u0026ndash;65\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.03 [1.02\u0026ndash;1.04]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.03 [1.02\u0026ndash;1.04]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e1.00 [0.99\u0026ndash;1.01]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e (OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eLess than 9th\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003eReference Value\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e9\u0026ndash;11th\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.55 [0.40\u0026ndash;0.75]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.55 [0.40\u0026ndash;0.75]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e1.12 [0.78\u0026ndash;1.61]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eHigh school/GED\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.44 [0.31\u0026ndash;0.63]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.44 [0.31\u0026ndash;0.63]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.39 [1.06\u0026ndash;1.83]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eSome college/AA\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.51 [0.37\u0026ndash;0.69]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.51 [0.37\u0026ndash;0.69]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e2.14 [1.63\u0026ndash;2.81]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003eCollege graduate or above\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.56 [0.41\u0026ndash;0.77]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.56 [0.41\u0026ndash;0.77]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e4.01 [3.01\u0026ndash;5.34]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIncome to Poverty Ratio\u003c/b\u003e (OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e0 to 4.99\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003eReference Value\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.94 [0.90\u0026ndash;0.99]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.94 [0.90\u0026ndash;0.99]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e1.16 [1.10\u0026ndash;1.22]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHours Worked Per Week\u003c/b\u003e(OR[(95% CI])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003csup\u003e1.01 [0.99\u0026ndash;1.03]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e1.01 [0.99\u0026ndash;1.03]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003e0.99 [0.97\u0026ndash;1.00]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e*OR in bold signifies statistically significant results (p \u0026lt; 0.05)\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSun-Protective Behaviors by Race\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eSunscreen Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eShade Protection\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eLong Sleeve Use\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eBlack\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eWhite\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eOther Race\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eBlack\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eWhite\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eOther Race\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003eBlack\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eWhite\u003c/b\u003e (%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003eOther Race\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(%) (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2003\u0026ndash;2004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e4.4\u003c/b\u003e (3.3\u0026ndash;5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e28.7\u003c/b\u003e (24.2\u0026ndash;33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e17.2\u003c/b\u003e (14\u0026ndash;20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e46.2\u003c/b\u003e (42.4\u0026ndash;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e26.5\u003c/b\u003e (23.8\u0026ndash;29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e37.8\u003c/b\u003e (32.4\u0026ndash;43.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e6.4\u003c/b\u003e (4.5\u0026ndash;8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e5.5\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(4\u0026ndash;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e13.1\u003c/b\u003e (8.8\u0026ndash;17.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2005\u0026ndash;2006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e6.6\u003c/b\u003e (4.4\u0026ndash;8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e31.7\u003c/b\u003e (28.8\u0026ndash;34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e17.7\u003c/b\u003e (15.1\u0026ndash;20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e38.3\u003c/b\u003e (35.4\u0026ndash;41.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e21.3\u003c/b\u003e (19.6\u0026ndash;22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e35.2\u003c/b\u003e (31.9\u0026ndash;38.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e9.2\u003c/b\u003e (7.2\u0026ndash;11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e5.6\u003c/b\u003e (3.8\u0026ndash;7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e12.4\u003c/b\u003e (9.8\u0026ndash;14.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2009\u0026ndash;2010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e6.1\u003c/b\u003e (4.8\u0026ndash;7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e34.2\u003c/b\u003e (32.2\u0026ndash;36.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e23.6\u003c/b\u003e (20\u0026ndash;27.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e43.3\u003c/b\u003e (39.2\u0026ndash;47.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e26.2\u003c/b\u003e (23.1\u0026ndash;29.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e37.5\u003c/b\u003e (35\u0026ndash;40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e7.6\u003c/b\u003e (5.3\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e6.5\u003c/b\u003e (4.9\u0026ndash;8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e18.2\u003c/b\u003e (14.4\u0026ndash;21.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2011\u0026ndash;2012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e10.5\u003c/b\u003e (8.1\u0026ndash;12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e38.6\u003c/b\u003e (33.8\u0026ndash;43.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e24.0\u003c/b\u003e (20.7\u0026ndash;27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e48.7\u003c/b\u003e (44.7\u0026ndash;52.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e27.3\u003c/b\u003e (23\u0026ndash;31.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e40.7\u003c/b\u003e (35.9\u0026ndash;45.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e11.0\u003c/b\u003e (9.2\u0026ndash;12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e8.3\u003c/b\u003e (6.4\u0026ndash;10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e15.9 (12.7\u0026ndash;19.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2013\u0026ndash;2014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e7.1\u003c/b\u003e (5.6\u0026ndash;8.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e36.4\u003c/b\u003e (31.2\u0026ndash;41.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e25.4\u003c/b\u003e (22.4\u0026ndash;28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e41.8\u003c/b\u003e (38.5\u0026ndash;45.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e24.9\u003c/b\u003e (22.4\u0026ndash;27.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e41.3\u003c/b\u003e (36.1\u0026ndash;46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e8.6\u003c/b\u003e (7.5\u0026ndash;9.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e6.2\u003c/b\u003e (5\u0026ndash;7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e14.2\u003c/b\u003e (12.2\u0026ndash;16.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2015\u0026ndash;2016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e8.1\u003c/b\u003e (5.4\u0026ndash;10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e33.9\u003c/b\u003e (29.7\u0026ndash;38.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e22.1\u003c/b\u003e (19.1\u0026ndash;25.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e48.1\u003c/b\u003e (45.5\u0026ndash;50.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e25.2\u003c/b\u003e (22.1\u0026ndash;28.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e38.2\u003c/b\u003e (35.2\u0026ndash;41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e9.8\u003c/b\u003e (6.8\u0026ndash;12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e6.3\u003c/b\u003e (4.7\u0026ndash;7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e17.5\u003c/b\u003e (13.5\u0026ndash;21.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2021\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e11.4\u003c/b\u003e (7\u0026ndash;15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e36.4\u003c/b\u003e (32.2\u0026ndash;40.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e29.1\u003c/b\u003e (24.8\u0026ndash;33.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e38.5\u003c/b\u003e (30.3\u0026ndash;46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e32.4\u003c/b\u003e ​​(29.3\u0026ndash;35.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e35.0\u003c/b\u003e (30.6\u0026ndash;39.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e8.3\u003c/b\u003e (5.4\u0026ndash;11.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e8.2\u003c/b\u003e (6.1\u0026ndash;10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e18.5\u003c/b\u003e (15\u0026ndash;21.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e There are no potential conflicts of interest or competing interests to disclose. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e None \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRB Study Number:\u003c/strong\u003e Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent:\u003c/strong\u003e Not applicable\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.O. conceived the project, led the data analysis, and drafted the manuscript. E.C. and J.T. contributed to writing and editing the manuscript. K.G., H.Y., and X.P. assisted with statistical analysis and methodological design. C.O., K.G., H.Y., and X.P. developed the study methodology. P.A. provided project supervision and oversight. All authors contributed to the critical review and revision of the manuscript and approved the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePellacani G, Lim HW, Stockfleth E, Sibaud V, Brugu\u0026eacute;s AO, Saint Aroman M (2024) Photoprotection: Current developments and controversies. 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Cancer Causes Control 22(7):1067\u0026ndash;1071. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10552-011-9780-1\u003c/span\u003e\u003cspan address=\"10.1007/s10552-011-9780-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"UV protection, disparities, public health, education ","lastPublishedDoi":"10.21203/rs.3.rs-7263486/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7263486/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSun-protective behaviors play a significant role in preventing UV-related skin damage, photoaging, increased pigmentation in pigmentary disorders, and skin cancer. Understanding changes in sun protection practices over time can further elucidate the long-term impact of ongoing efforts to educate populations about the role of UV exposure in these pathologies. We assessed 20-year trends in sun-protective behaviors (sunscreen use, shade-seeking, and long-sleeve clothing) among U.S. adults according to race and ethnicity using nationally representative data from the National Health and Nutrition Examination Survey (NHANES) between 2003 and 2023.\u003c/p\u003e\n\u003cp\u003eWe analyzed responses from 28,765 U.S. adults using logistic regression models, adjusted for age, sex, education, income-to-poverty ratio, and occupation to assess behavioral trends across racial groups: Black, White, and Other (Hispanic, Asian, Multiracial).\u003c/p\u003e\n\u003cp\u003eOur analysis indicated all racial groups had statistically significant increases in sunscreen use over time (White p = 0.0267, Black p = 0.0013, Other p \u0026lt; 0.0001). White participants consistently used sunscreen more than any group (from 28.7% in 2003-04, rising to 36.4% in 2021–23). Black participants reported the lowest usage compared to White and Other racial groups but demonstrated a steady increase over the course of this 20-year period, starting from 4.4% in 2003–04, peaking at 11.4% in 2021–23. Sunscreen use amongst Other races, showed steady increases from 17.2% to 29.1% over the course of this 20-year period. Compared to Black adults, the odds of sunscreen use were significantly higher among White (OR 8.01, 95% CI 5.15–12.47) and Other race participants (OR 5.91, 95% CI 3.86–9.04). In contrast, Black participants reported the highest rates of shade-seeking behavior, and Other races reported the highest use of long-sleeve protective clothing.\u003c/p\u003e\n\u003cp\u003eOur findings highlight persistent disparities in sun-protective behaviors, particularly low sunscreen use among Black Americans despite improvement over time. Cultural norms, cosmetic acceptability (specifically white cast), and lack of inclusive public health messaging may play a role in these trends. Future education efforts, more tailored resources and inclusive messaging may help bridge this gap and advance skin health equity.\u003c/p\u003e","manuscriptTitle":"Sun Protective Behaviors Amongst Non-White US Adults from 2003-2023 ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-24 06:21:34","doi":"10.21203/rs.3.rs-7263486/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-29T20:22:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-28T12:45:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-24T01:15:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321542039053178282386867026523436889350","date":"2025-09-21T05:28:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15950773739518674010015973916833587225","date":"2025-09-16T13:46:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T23:48:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-01T10:59:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-01T10:59:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Dermatological Research","date":"2025-07-31T14:41:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2ec0bf25-3bb0-4d3c-ab4f-1465d41007b0","owner":[],"postedDate":"September 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-11T20:38:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-24 06:21:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7263486","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7263486","identity":"rs-7263486","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}