“…Between 1996 and 2013, 9 US states—including California, Texas, and Michigan—banned race-based affirmative action in college admissions. …”
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“…RESULTS: Among the 3392 nonblack resident physician respondents, 1693 (49.9%) were male, 1964 (57.9%) were younger than 30 years, and 2362 (69.6%) self-identified as belonging to the white race. In this cohort, 1529 of 3380 resident physicians (45.2%) had symptoms of burnout and 1394 of 3377 resident physicians (41.3%) had depression. …”
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“…Among those with a history of hypertension exclusively, basic mobile phone, smartphone, and tablet ownership were associated with age and education, but not race or sex. Older adults were more likely to report having a basic mobile phone only, whereas those with higher education were more likely to report owning a tablet or smartphone. …”
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“…Multivariable analyses showed that for all 3 age groups, educational attainment, ability to use the internet without help, and having 1 or more chronic condition were significant predictors of patient portal and Web-based HIA use after controlling for gender, race/ethnicity, and internet use. CONCLUSIONS: Internet use, and especially use without help, significantly declines with age, even within a middle-aged group. …”
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“…Control variables will include demographics (eg, age, race, ethnicity, marital status, educational level) and OB history (eg, history of preterm labor, history of fetal or infant death). …”
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“…In our sample, there was no difference in the favorable ratings as determined by race/ethnicity. In conclusion, the findings of this study inform the community with regard to how the research participants rate their experiences, and thus motivate others to participate in clinical research. …”
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“…The association between core agents and incident T2DM was estimated with multivariate Cox proportional hazards regression adjusted for age, sex, race, HCV co-infection and BMI at baseline. Median (IQR) absolute BMI change from baseline was evaluated at 6, 12, 18, and 24 months in those who developed incident T2DM and those who did not. …”
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“…METHODS: Thirty-two Tx recipients who were prospectively enrolled in the Blood Stream Infection Biorepository (BSIB) were matched 1:1 with Non-Tx patients on age, race, gender and bacteria using a perfect matching algorithm (Tx-SAB n = 16, Non-Tx SAB n = 16; Tx GNB n = 16, Non-Tx GNB n = 16). …”
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“…Adjusted, self-reported, prior-year weight was calculated using correction equations that considered age, sex, race/ethnicity, and quartile of self-reported prior-year weight. …”
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“…Study limitations include possible residual confounding by factors at the individual/household level, and lack of disaggregation of gun homicide data by gender and race/ethnicity. CONCLUSIONS: This study finds that the rich–poor gap, level of citizens’ trust in institutions, economic opportunity, and public welfare spending are all related to firearm homicide rates in the US. …”
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“…Results: On weighted analysis, after removing missing data of age, gender and race, from years 2013 to 2014, of the total 983,065 (1.74%) migraine patients were identified. …”
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“…DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included statewide, all-payer, longitudinally linked ED patient records and mortality data from all California residents who presented to a California-licensed ED at least 1 time from January 1, 2009, to December 31, 2011, with deliberate self-harm, suicidal ideation but not self-harm, or neither (a 5% random sample). Age-, sex-, and race/ethnicity-adjusted standardized mortality ratios (SMRs) for suicide and other manners or causes of death were determined for each patient group using statewide mortality data. …”
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“…Key social determinants of health such as race/ethnicity, socioeconomic status, and type of insurance were associated with receiving treatment at ACCPs and INCPs.…”
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“…However, in the SHIFT trial 8% of the ivabradine study group were from Asia, with 3% from other races and Caucasians making up the majority of the sample (89%)(3). …”
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“…In survival analysis, patients with older ages (11–20 years: HR = 1.549, 95%CI 1.144–2.099, p = 0.005; 21–30 years: HR = 1.808, 95%CI 1.278–2.556, p = 0.001; 31–49 years: HR = 3.481, 95%CI 2.379–5.094, p < 0.001; ≥ 50 years: HR = 4.307, 95%CI 2.648–7.006, p < 0.001) , larger tumor size (5–8 cm: HR = 1.386, 95%CI 1.005–1.991, p = 0.046; > 8 cm: HR = 1.877, 95%CI 1.376–2.561, p < 0.001), black race (HR = 2.104, 95%CI 1.296–3.416, p = 0.003), and wider extension (regional: HR = 1.373, 95%CI 1.033–1.823, p = 0.029; metastatic: HR = 3.259, 95%CI 2.425–4.379, p < 0.001) were associated with worse prognosis. …”
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“…After adjusting for age, sex, race/ethnicity, education, income, age at type 1 diabetes diagnosis, and hemoglobin A(1c) level, mean flourishing scores increased from the lowest (201.0; 95% CI, 195.0-207.0) to medium (225.2; 95% CI, 219.4-231.0) to highest (240.4; 95% CI, 234.4-246.4) tertiles of family connection; compared with those in the lowest tertile of family connection, the flourishing scores were 1.04 (95% CI, 0.81-1.27) SD units higher among those in the highest tertile and 0.64 (95% CI, 0.42-0.86) SD units higher among those in the middle tertile. …”
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“…Veterans with HIV were matched with controls without HIV by age, race, sex, and site of care. Data were analyzed from January 2019 to December 2019. …”
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“…METHODS: A total of 18 volunteers (mean age 71 years, SD 4.5; 12 women) completed a three-session study to evaluate different genres of games in increasing order of difficulty (S(1)-BrainGame, S(2)-CarRace, and S(3)-Exergame). Each session included an identical sequence of activities (t(1)-Baseline, t(2)-Picture encode, t(3)-Play, t(4)-Stroop test, t(5)-Play, and t(6)-Picture recall), a repeated sampling of salivary cortisol, and time-tagged ambulatory data from a wrist-worn device. …”
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“…Limitations of this study include missing information on prescription claims of patients not included in the database, and for those included, some patients were missing information on patient diagnosis, race/ethnicity, educational attainment, and income (34%–36%). …”
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“…The three primary predictors of interest—language preference, smartphone ownership, and type of clinic for usual care—were adjusted for age, gender, race or ethnicity, limited English proficiency, educational attainment, health literacy, and health status. …”
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