Introduction COVID-19 disrupted traditional research infrastructures and processes most notably in-person community recruitment, especially in underrepresented populations like racial ethnic minorities. To find creative and effective strategies, our group implemented and tested the efficacy of a culturally tailored community outreach plan (COP) developed during the US COVID-19 pandemic. Methods In February 2021, we developed an 11 step culturally-tailored community outreach program to support the implementation of three NIH funded community-based sleep studies. The following steps include: (1) description of the situation statement, 2) definition of goals, 3) engagement of audience/stakeholders, 4) tailoring message, 5) defining incentives, 6) choice of outreach methods, 7) identification of spokesperson, 8) choice of tools to assess progress, 9) identification of media outlets, 10) creation of study timeline, and 11) implementation of the plan. The studies leveraged several recruitment channels: 1) community settings (Place of worship, “community recruiter”, health fairs, word of mouth, & healthcare providers/doctors’ clinics), 2) online platforms (Facebook, Twitter, LinkedIn and Research Match), and 3) preexisting datasets in NYC. Results All three studies successfully met recruitment goals. ESSENTIAL [n= 224, 69% females, mean age= 36], MOSAIC [n=109, 61% females; mean age= 64] and Latinx/Hispanics: DORMIR[n=260, 61.3% of female; 32.4]. Among the three NYC cohorts, the most common recruitment channels were: preexisting datasets (74%), community settings (19%), & online platform (7%) for ESSENTIAL; preexisting datasets (85%) & community settings (15%) for MOSAIC, and (71.7%) online platform for DORMIR. However, the Miami cohorts came mostly from community settings 90% for Essential and 97% for MOSAIC. Conclusion Overall, the TSCS community outreach plan seems to be an effective tool to engage minoritized populations in greater NY and Miami. Our current field experience indicates that recruitment channels must be adapted to age, and community resources. Limited access to technology, particularly among older Blacks seem to be a major barrier for field staff to successfully engage the disenfranchised communities. Support (If Any) NIH R01HL142066-04; R01HL152453-01 R01HL142066, R01HL095799, RO1MD004113
Introduction One in three American adults are sleep deprived in the United States (US). Racial/ethnic minorities are more likely to experience shorter sleep duration than are whites. Light exposure is associated with sleep duration. However, whether this association is independent of individuals’ race/ethnicity has not been studied in a nationally representative sample of the US adult population. We examined associations between ambient light exposure and sleep duration and between race/ethnicity and sleep duration. We also assessed whether associations between light exposure and sleep duration are independent of participants’ race/ethnicity. Methods We used data from the National Health and Nutrition Examination Survey (n=4,277 adults; 2013-2014). Participants (≥ 18 years old) wore an actigraph that collected 24-hour sleep/wake and light data for 7 consecutive days. Objective measurements in our analyses included sleep duration (valid minutes) and light exposure (lux). To determine the associations between light exposure and sleep duration, a weighted mixed-effects linear model was estimated controlling for age, sex, family income to poverty ratio, education, employment, marital status, homeownership status, birthplace, household size, vitamin D, smoking, physical activity, sedentary lifestyle, health status, body mass index, depression, chronic conditions, and time in days. A product term between lux and race/ethnicity was included in a second regression model. Results Participants had a mean sleep duration of 468.2 minutes. On average, White adults had the longest sleep duration (mean=478.8), followed by other/multiple races (mean=458.6), Asians (mean=449.1); Blacks (mean=445.0), and Hispanics (mean=444.7). Overall, light exposure was negatively associated with sleep duration (= -0.08 lux; p<0.001). Black slept significantly less than did Whites (= -37.1 p<0.001) followed by Asians ( = -26.5; p<0.01) and Hispanics (= -24.6; p<0.01). The association between light exposure and sleep duration did not significantly differ across all race/ethnic groupings, except for Blacks (= -0.05; p<0.01). Conclusion To our knowledge, this is the first study that used national data to assess racial/ethnic disparities in objectively measured light exposure. Future research is needed to shed more light on racial/ethnic disparities in the light-exposure-sleep-duration link. Support (If Any) R01HL142066, R01HL095799, RO1MD004113, R01HL152453, R25HL105444
Introduction The prevalence of vitamin D deficiency (VitD) in the United States is 41 percent, with the highest rate among Blacks 82 percent. Vitamin D deficiency has been linked to chronic diseases. The extent to which the association between light exposure and vitamin D serum levels can vary by individual’s race/ethnicity of which has not been studied at a national level. We aim to explore the associations of ambient light exposure between race/ethnicity and vitamin D. Methods The study used data from the National Health and Nutrition Examination Survey (2013-14). For detection of 25-hydroxyvitamin D3 and 25-hydroxyvitamin D2 nmol/L, ultra-high-performance liquid chromatography-tandem mass spectrometry was performed based on serum samples from adults aged ≥ 18 years. Light levels (lux) data were gathered using 24-hour actigraphic monitoring over /a 7day period. Weighted generalized linear models were fitted examining association between light exposure and VitD adjusting for age, sex, family income/poverty ratio, education, employment, house tenure, marital status, birthplace, number of people in household, smoking, physical activity, and sedentarity. To compare this association across race/ethnicity, a product term between lux and race/ethnicity was included in adjusted models. Results Among 4,251 participants, White adults had the highest levels of VitD (mean=76.0; se=1.3), then other/multiple races (mean=65.1; se=2.2), Asians (mean=62.5; se=1.4); Hispanics (mean=57.4 nmol/L; se=1.6), and Blacks (mean=50.1; se=1.4). Regression analysis revealed estimated mean VitD of 64.9 nmol/L and positive association between light exposure and VitD ( 0.020). Blacks had significantly lower VitD levels ( -19.3) followed by Asians (-12.1) and Hispanics (-12.6) (all p-values <0.001). The association between light exposure and VitD depended on participant’s race/ethnicity Conclusion To our knowledge, this is the first study showing associations between objectively measured light exposure and VitD serum levels using a large representative sample of the US population. Although the study revealed racial/ethnic disparities in VitD levels, light exposure was associated with VitD even when race/ethnicity was adjusted for in the model. Further research on racial/ethnic differences in VitD is warranted. Support (If Any) R01HL142066, R01HL095799, RO1MD004113, R01HL152453, R25HL105444
Introduction Cancer survivors experience an increased stress burden. Twenty-five percent (25%) of cancer survivors experience persistent depressive and anxiety symptoms and 40% are afflicted with chronic sleep problems. Analysis of this relationship between survivors’ mental health and sleep may elucidate components of stress burden in a particularly vulnerable population. This study examined the relationship between anxious and depressive symptoms and frequency predicting sleep patterns, comparing individuals with a cancer history versus those without. Methods Data emanated from the 2020 National Health Interview Survey dataset (n=31,568). Six percent (n=1936) of respondents reported a cancer history. The primary outcome was sleep duration, based on the average hours of sleep per night an individual reported over the past month, which was coded into “healthy” (7-8 hrs.) vs “unhealthy” (< 7 hrs. or > 9 hrs.) sleep. Level of anxiety and depression as well as frequency of reported symptoms were included in the models as predictors. Binary logistic regression models were performed to determine the discrete impact of depression and anxiety on sleep duration among individuals with and without a cancer history. Adjusted models included the demographic covariates of age, sex, education, household income, and race. Results In adjusted models, frequency of anxious feelings (OR = 1.19, p<.01,), frequency of depressive feelings (OR =1.29, p<.01,), level of anxious feelings (OR = 1.38, p<.01,), and level of depressive feelings (OR=1.15, p<.01) significantly predicted unhealthy sleep in the full sample. However, among individuals with a cancer history, frequency of anxious feelings (OR =1.16, p<.01,), level of anxious feelings (OR = 1.28, p<.01,) and frequency of depressive feelings (OR = 1.23, p<.01,) significantly predicted unhealthy sleep duration, but level of depressive feelings did not (OR = 1.08, p=.13,). Conclusion Mental health and sleep are closely and bidirectionally connected in the general population, but among individuals with a history of cancer the link between level of depression and healthy sleep were not significant. Further research is needed to understand the complex relationship between mental health and sleep among people with a cancer history. Support (if any) K01HL135452, K07AG052685, R01AG072644, R01HL152453, R01MD007716, R01HL142066, R01AG067523, R01AG056031, and R01AG075007.
Introduction Blacks have a high burden of poor sleep health outcomes. Environmental determinants, such as green space or open environments, represent an underexplored contributor to sleep burden among Blacks. The extent these environmental factors affect sleep health outcomes within this population has not been adequately explored. To fill this gap in the literature, we investigated associations between environmental factors and sleep outcomes among Blacks in a large urban city. Objectives included (1) examine if zip-code derived open spaces (defined as proportion of open space in residential area,) green spaces (defined as open tree coverage of the ground) and blue spaces (proportion of water space) sleep apnea risk, and insomnia symptoms; (2) Examine if open, blue, and green spaces predict sleep outcomes independent of sex, age, and education level. Methods Our study used data from the Metabolic Syndrome Cohort Study (2009-2014), a studythat examined behavioral intervention methods to improve sleep apnea outcomes among Blacks. Sleep Apnea was assessed with the ARES (apnea risk) scale and insomnia status was collected through self-report (“Do you have difficulty staying/falling asleep or waking up?”) in a subset of 344 participants. Logistic regression analyses were performed to predict the effect green, blue, and open spaces had on sleep outcomes. To account for within zip-code correlation, mixed effects models (unadjusted and adjusted) account for sex, age, and education were considered. Results We found that none of the green, blue, or open space variables predicted sleep outcomes in the unadjusted model. In adjusted models, green space predicted sleep apnea risk scores, (OR=1.03, P<.05), but not insomnia. Conclusion Our study examined the extent which green, blue, and open spaces predicted insomnia and sleep apnea in urban blacks. We found that only green spaces were associated with sleep apnea, and none of our environmental variables predicted insomnia. Given the large amount of literature detailing a complex and multifactorial process on how environment affects sleep outcomes, our findings suggest that the link between urban environments, green spaces, and sleep outcomes may not be as definitive as they seem. Further research should explore the differential effect environment has on diverse populations’ sleep outcomes. Support (If Any) NIH R01HL142066, R01HL095799, RO1MD004113, R01HL152453
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