ライフサイエンスコーパス: ethnicity

1 icity) and in combination (ICE-income + race/ethnicity).

2 ified strata (age, sex, region, and race and ethnicity).

3 d by year, 10-year age groups, sex, and race/ethnicity.

4 black ethnic groups than in people of white ethnicity.

5 rements, including variation by age and race/ethnicity.

6 sity risk stratification across age, sex and ethnicity.

7 n from the United Kingdom of comparable race/ethnicity.

8 V (cases) to 15 controls matched for age and ethnicity.

9 re-Washington, DC area by self-reported race/ethnicity.

10 ciated with major changes in urbanization or ethnicity.

11 ch sleep characteristic, overall and by race/ethnicity.

12 models for girls were created for each race/ethnicity.

13 m different European populations of the same ethnicity.

14 uld influence transplant eligibility by race/ethnicity.

15 .94% male vs. 45.45% female, P = 0.669), and ethnicity.

16 sease risk may differ by vascular domain and ethnicity.

17 26.9) postmenopausal women paired by age and ethnicity.

18 The majority (96.2%) were white ethnicity.

19 HIV infection was associated with age and ethnicity.

20 high prevalence in younger women of African ethnicity.

21 disease should be evoked whatever patients' ethnicity.

22 rs and determine differences by sex and race/ethnicity.

23 ationship with age, gender, axial length, or ethnicity.

24 morbidity and in-hospital mortality by race/ethnicity.

25 ge-related RNFL thinning differs by race and ethnicity.

26 h recipient age, diagnosis, gender, and race/ethnicity.

27 increasing age and in children of non-white ethnicity.

28 se were matched to controls based on age and ethnicity.

29 on week of birth and region and adjusted for ethnicity.

30 ntal exposures have differential risk across ethnicity.

31 ositive family history, parity and Caucasian ethnicity.

32 ratified by sex, care setting, age, and race/ethnicity.

33 cally on socioeconomic status (SES) and race/ethnicity.

34 ciation between mRALE scores and race and/or ethnicity.

35 ure during pregnancy among primiparas of Han ethnicity.

36 arities in HF outcomes persist based on race/ethnicity.

37 , 48.1% were male, and 90.9% were of Chinese ethnicity.

38 micropore lifetime than self-identified race/ethnicity.

39 ates and survival vary by neighborhood-level ethnicity.

40 cluded older age, female gender, and race or ethnicity.

41 cases where outcomes did not differ by race/ethnicity.

42 difference in the proportion with AF by race/ethnicity.

43 opulations to other populations of different ethnicities.

44 se visual acuity compared to all other races/ethnicities.

45 d developed nations, particularly in certain ethnicities.

46 ealth care (including intensive care) across ethnicities.

47 men, and little difference was found between ethnicities.

48 trongly associated with SLE risk in multiple ethnicities.

49 and 74 healthy controls, of three different ethnicities.

50 sterior microphthalmia (MCOP) from different ethnicities.

51 en reported in patients from a wide range of ethnicities.

52 report NO(2) disparities separately by race ethnicity (11-32%) and poverty status (15-28%).

53 n [48%], 1 Asian [2%], and 1 of unknown race/ethnicity [2%]), 44 (92%) completed the trial.

54 omparison site) and/or of Hispanic or Latino ethnicity (26% in the intervention site, 33% in the comp

55 ETHODSWe treated 14 healthy women of diverse ethnicities (27.5 +/- 1.1 years of age, BMI of 25.4 +/-

56 %, p = 0.04) and lower proportion with white ethnicity (74.7% versus 86.9%, p = 0.003); was more freq

57 %, p < 0.001), and lower proportion of white ethnicity (75.5% versus 82.5%, p < 0.001).

58 for 39.5% of the cohort, of those with known ethnicity, 75.3% were White.

59 .9%, p < 0.001), greater proportion of Asian ethnicity (8.3% versus 4.0%, p < 0.001), and lower propo

60 rding COVID-19 that varied by physician race/ethnicity, acknowledgment of racism/inequality, and comm

61 SAFELY study with mortality rates by age and ethnicity across US states.

62 ic information, including age, gender, race, ethnicity, affected eye, subtype, stalk origin, complica

63 Preoperative VA, the distribution of race/ethnicity, age, gender, lens status, macula status, and

64 uation regression models, adjusting for race/ethnicity, age, HIV load, and hepatitis C virus infectio

65 ortality, after separate adjustment for sex, ethnicity, age, hospital acquisition of COVID-19 (defini

66 tudy participant metadata (including race or ethnicity, age, sex and blood pressure) or the combinati

67 ng for confounding variables, including race/ethnicity, age, sex, and burn size, the GG homozygotes d

68 xamined in our clinical cohort included race/ethnicity, age, time to return of spontaneous circulatio

69 te (W) race, Black (B) race, or Hispanic (H) ethnicity aged 18 years and older with diabetic macular

70 redictors included age, sex, education, race/ethnicity, alcohol drinking intensity, cigarette smoking

71 d that adjusting for age, race, and Hispanic ethnicity altered the evaluation: 8 OPOs changed their p

72 sence of incidental findings and sex or race/ethnicity among either cohort, and no correlation with C

73 awareness decline was observed in all races/ethnicities and ages except women >=65 years of age.

74 of living with arthritis pain across diverse ethnicities and cultures.

75 se with and without OSAS, as well as between ethnicities and disease states.

76 d to 373 HCC patients of different races and ethnicities and diverse etiologies.

77 potent topical corticosteroids in non-white ethnicities and people of lower socioeconomic status.

78 sts differences in ACARs are associated with ethnicity and age.

79 Hispanic ethnicity and an infected sibling close contact are asso

80 (PAH).Objectives: Determine effects of race/ethnicity and ancestry on mortality and disease outcomes

81 d to determine the relationship between race/ethnicity and annual costs of care, all-cause hospitaliz

82 Adjustments for ethnicity and body mass index changed odds ratios for au

83 ression analysis alongside age, gender, race/ethnicity and body mass index, the area under the curve

84 ugh this relationship was consistent by race/ethnicity and by serotype, it was not present in 5 FoodN

85 setts, there was no association between race/ethnicity and clinically relevant hospitalization outcom

86 Non-White ethnicity and comorbidities such as obesity, diabetes, a

87 survival analysis to estimate the effects of ethnicity and comorbidity at an individual level in the

88 , 38.31); a test of interaction between race/ethnicity and cord UMFA concentrations was significant (

89 -treated eyes by visual acuity (VA) and race/ethnicity and correlations between volumes.

90 Although 70% of the effect between ethnicity and DCGF was mediated by BPAR, no similar asso

91 rmed to assess the relationship between race/ethnicity and each outcome adjusting for differences in

92 partly mediate the association between race/ethnicity and fetal growth restriction.

93 d inclusion across several domains including ethnicity and gender.

94 significantly associated with age, and race/ethnicity and income with masking.

95 association between non-Hispanic Black race/ethnicity and IUGR, 12% of the association in Hispanic w

96 led that the association between race and/or ethnicity and mRALE scores was mediated by limited Engli

97 treatment escalation in people of non-white ethnicity and of more-deprived backgrounds.

98 er BPAR mediated the adverse effects between ethnicity and outcomes.

99 ng, and treatment protocols based on patient ethnicity and race may be necessary.

100 We evaluated associations between race/ethnicity and receipt of COVID-19 testing, a positive te

101 raction using the 12-lead ECG varies by race/ethnicity and to (2) determine whether its performance i

102 -specific COVID-19 mortality rates by racial/ethnicity and to calculate the impact of this mortality

103 isadvantage separately (ICE-income, ICE-race/ethnicity) and in combination (ICE-income + race/ethnici

104 d participants (PWID and those of indigenous ethnicity) and those disengaged from care were more like

105 size issues, demographics (age, gender, and ethnicity), and whether such studies should not be perfo

106 ere also calculated, stratified by age, sex, ethnicity, and aetiological classification (Trial of Org

107 als rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study particip

108 eath, and rates and proportions by sex, race/ethnicity, and birth year.

109 expression was most pronounced by sex, race/ethnicity, and body mass index (BMI), but transcriptome

110 d to control patients according to age, sex, ethnicity, and body mass index.

111 djusting for BMT type, age at BMT, sex, race/ethnicity, and cognitive reserve, SNPs in the blood-brai

112 t the importance of geography, urbanization, ethnicity, and diet on the shape of the adult gut DNA vi

113 th HIV were more likely to be male, of Black ethnicity, and from a more deprived geographical area th

114 ed studies did not report participants' race/ethnicity, and half of the remaining study samples were

115 (being older, being male, being of nonwhite ethnicity, and having comorbidities) were associated wit

116 adjusting for calendar year, age, sex, race/ethnicity, and HIV transmission risk factor, estimated r

117 June 2020) vs 2019, overall and by age, race/ethnicity, and insurance status.

118 publicize data on grantees by gender, race, ethnicity, and location from neuroscience funding agenci

119 7%) were female, 1,681 (98.5%) were of white ethnicity, and mean (+/-SD) eGFR was 53.5 +/- 11.9 mL/mi

120 ellowship, state median wage, practice type, ethnicity, and number of workdays.

121 hT (P < .001), after adjusting for age, sex, ethnicity, and ocular measures.

122 3 years), of white (60%) or black (20%) race/ethnicity, and of normal pre-pregnancy BMI (median BMI:

123 ir evaluations irrespective of their gender, ethnicity, and primary cause of liver disease.

124 with covariates including age, gender, race/ethnicity, and primary insurance.

125 nsistent across all institutions and by sex, ethnicity, and race.

126 005 and 2015 were matched by age, sex, race, ethnicity, and residency to 788 controls with hyperlipid

127 sments and were similar concerning age, sex, ethnicity, and SES.

128 ve identified disparities according to race, ethnicity, and SES.

129 8 to 9 in a control population of age, race/ethnicity, and sex-matched normal-weight and obese indiv

130 e annual CHD mortality by age at death, race/ethnicity, and sex.

131 ributable to and related to CHD by age, race/ethnicity, and sex.

132 ment for year of colonoscopy, age, sex, race/ethnicity, and smoking history.

133 stment for index of multiple deprivation and ethnicity, and then for a broad range of comorbidities.

134 Older patients, those of minority race/ethnicity, and those with uncontrolled HIV experienced h

135 overty level, after accounting for age, race/ethnicity, and year.

136 adolescents (PHIV+) compared to age-, sex-, ethnicity- and socioeconomic status (SES)-matched HIV-ne

137 % CI 1.05-1.52) vs. White race, and Hispanic ethnicity (aOR 1.52, 95% CI 1.40-1.65).

138 eated eyes, with increasing age, and between ethnicities are highlighted.

139 ident hemodialysis patients how sex and race/ethnicity are associated with time on a central venous c

140 rvations of hospitalization outcomes by race/ethnicity are limited.

141 according to sex, socioeconomic status, and ethnicity are unknown.

142 ation with trait serum triglyceride and used ethnicity as a covariate.

143 men, Hispanic women, and women of other race/ethnicity as compared with White women was partly mediat

144 c characteristics such as age, sex, and race/ethnicity, as well as by social factors including socioe

145 S levels in association with a mother's race/ethnicity, as well as potential effects on pregnancy and

146 Adjustment for ICE-income + race/ethnicity at both time periods yielded the greatest decl

147 ts completed the study: 68% women, 95% white ethnicity, average age 62.4 years (SD 10.8), body mass i

148 ower in the cohort with NAFLD, with sex- and ethnicity-based differences.

149 rge decisive attention to and action against ethnicity-based inequities that undermine cardiovascular

150 -effects models adjusting for age, sex, race/ethnicity, baseline BMI, nadir and current CD4+ T-cell c

151 Minority ethnicity, being married, and having better mental and p

152 s were associated with older age, other race/ethnicity, birthplace outside the United States, four or

153 01), 30-day mortality did not differ by race/ethnicity (Black versus White: OR 0.97, 95% CI 0.80-1.17

154 Compared with people of white ethnicity, Black and South Asian people were at higher r

155 Covariates included age, gender, ethnicity, blood pressure, body mass index, and spherica

156 ccording to categories of baseline age, race/ethnicity, body mass index, physical activity, physical

157 We collected data on age, sex, race/ethnicity, body weight, body mass index (BMI), diabetes,

158 tiple confounding factors (age, sex, race or ethnicity, body-mass index, underlying cardiovascular di

159 The associations between ethnicity, BPAR, DCGF, and DWFG were examined using adju

160 number of donors did not change across race/ethnicity but increased by 38% and 29% for Hispanic and

161 ity; that authors consider not just race and ethnicity but many social determinants of health, includ

162 redictor after accounting for recipient sex, ethnicity, cause of liver disease, donor age, cold ische

163 sessed and compared by patient-reported race/ethnicity, classified as White, Black, Latinx, Asian, or

164 For Black participants, messages from race/ethnicity-concordant physicians increased information-se

165 of B-CPR and survival by neighborhood-level ethnicity controlling for site and patient-level confoun

166 hether rejection mediates the effect between ethnicity, death-censored graft failure (DCGF), and deat

167 On adjusting for sociodemographic (sex, age, ethnicity, deprivation) and maternity (maternal age, mat

168 ed; that dietary pattern descriptions inform ethnicity descriptions; and that depersonalizating langu

169 on model adjusted for recipient age, gender, ethnicity, diagnosis, and bridging status.

170 strated that despite statistical adjustment, ethnicity differences remained a significant source of s

171 opulation had similar age, sex, and race and ethnicity distribution to the US dialysis population, wi

172 ificantly by HIV status by age, sex, or race/ethnicity due to the matching algorithm.

173 in the United States by birthplace and race/ethnicity during 1999-2016.

174 quantile regression, adjusting for age, sex, ethnicity, education level, smoking, BMI, and diabetes.

175 terventions" vs "full treatment"), age, race/ethnicity, education, days from POLST completion to admi

176 Controlling for age, race/ethnicity, education, income, smoking, alcohol, menopaus

177 classifications adjusting for age; sex; race/ethnicity; education; diet; smoking status; body mass in

178 The ethnicity effect might be related to differences in susc

179 ect) and in the Pardo and Black populations (ethnicity effect).

180 Prevalence of African American ethnicity, end-stage renal disease, diabetes, fair/poor

181 Results were compared to 644 age- and ethnicity-equivalent women from the Framingham Heart Stu

182 e of baseline risk over time across race and ethnicity, even though the distribution of risk within t

183 Age, sex, ethnicity, follow-up time, AAK stage, noncorneal abnorma

184 ata on US COVID-19 deaths with reported race/ethnicity, for the time period February 1, 2020, to July

185 tion status assessment in children over race/ethnicity-generic references.

186 egression models adjusted for age, sex, race/ethnicity, geographic region, and health status.

187 h age, and the effects of diet, medications, ethnicity, geography, and lifestyle.

188 ces in incidence and prevalence of eczema by ethnicity, geography, sex, and socio-economic status, wh

189 xpanded to include the intersections of race/ethnicity, geography, sexual orientation and gender iden

190 2-isoprostane controlling for sex, age, race/ethnicity, glomerular status, birth weight, premature bi

191 revalence by city and according to sex, age, ethnicity group, and socioeconomic status, and compare s

192 that supragingival microbiota differed among ethnicity groups in children.

193 sults were similar across sex, age, and race/ethnicity groups.

194 rhinitis subjects were more likely of Indian ethnicity, had siblings, reported childcare attendance,

195 The disorder affects people of all ages and ethnicities, has a substantial psychosocial impact on pa

196 lidity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear.

197 compared sex, age group, birth cohort, race/ethnicity, health insurance coverage, and hepatitis A im

198 Factors examined were age, sex, ethnicity, height, body mass index (BMI), smoking status

199 ons that controlled for age, gender, race or ethnicity, hemoglobin A1c, duration of diabetes, high-de

200 On MVA: younger age, female gender, black ethnicity, higher KPS, obtaining a gross total resection

201 e (CVD) affects individuals of all races and ethnicities; however, its prevalence is highest in non-H

202 emale sex (HR = 1.5; 95% CI 1.3-1.74), white ethnicity (HR = 1.71, 95% CI 1.06-2.77), and low hospita

203 association was larger among people of Black ethnicity: HR 4.31 (95% CI 2.42-7.65) versus 1.84 (1.03-

204 er studies specially conducted among various ethnicities in different geographic locations, are requi

205 e in specific anatomic sites among races and ethnicities in individuals 50 years or older.

206 hypothesis of differential detection by race/ethnicity in the clinical recognition of AF, which may h

207 All analyses were stratified by race/ethnicity in the main analysis, and further by sex.

208 ased on patient characteristics such as race/ethnicity, income, insurance type, geographical region,

209 strated that neither Black race nor Hispanic ethnicity increased the chance of metastatic disease at

210 ver 70 confounders (e.g., maternal age, race/ethnicity, indications for gabapentin, other pain condit

211 spiratory syndrome coronavirus 2 and who had ethnicity information in the dataset.

212 e cohort was from London (24.4%), and whilst ethnicity information was missing for 39.5% of the cohor

213 We wanted to determine whether ethnicity, insurance, and documentation status served as

214 ectively stratify cardiovascular risk across ethnicities irrespective of age, sex, and risk factor bu

215 Race/ethnicity is associated with intrauterine growth restric

216 Accurate reporting of race/ethnicity is encouraged to address race-specific risk fa

217 adjustment for significant covariates (race/ethnicity, malignant disease, graft, and graft-versus-ho

218 lleles from the same original cohort and 320 ethnicity-match non-epilepsy control alleles.

219 available data, living epilepsy controls and ethnicity-match non-epilepsy controls, to identify poten

220 rve to refute suggestions that certain races/ethnicities may be biologically predisposed to poorer CO

221 riates related to demographics (ie, race and ethnicity), medical comorbidities (eg, obesity), access

222 o were black, Hispanic, or of another racial/ethnicity minority spent significantly more days on a CV

223 .45 to 0.26]; P = 2.3x10(-14)), and nonwhite ethnicity (most significant for mRNFL comparing blacks w

224 ion, household social class, parity, child's ethnicity, mother's age, mother's marital status, mother

225 e 62.7 years, 55.2% male); 93% were of white ethnicity (n = 150,754), 5% were South Asian (n = 8,139)

226 adjusting for maternal age, smoking, parity, ethnicity, neonate sex, and predicted cell-type composit

227 Ethnicity (non-exclusive) was 27 (57%) white, 10 (21%) b

228 including experienced racism; that race and ethnicity not be conflated; that dietary pattern descrip

229 Race and ethnicity, obesity status, cancer type, type of anticanc

230 ried independently by illness severity, race/ethnicity, obesity, and immunosuppressive drug therapy.

231 l as the sex, population of origin, and race/ethnicity of an individual.

232 types differ by geographic location and the ethnicity of the human host, which may have implications

233 suicide include Asian/Pacific Islander race/ethnicity, older age, history of mental disorder, alcoho

234 d ethnic groups, and the effects of race and ethnicity on access to care, use of resources, and disea

235 rranted to understand the effect of race and ethnicity on anti-VEGF efficacy to ensure optimal treatm

236 provided birth histories and information on ethnicity or a proxy variable.

237 as found in primary outcomes across race and ethnicity or those with a history of tobacco use, asthma

238 ave cirrhosis or advanced fibrosis; Hispanic ethnicity (OR = 12.34, 95% CI 2.59-58.82) and high BMI (

239 1.09; 95% CI, 1.07-1.11; P < 0.001), Russian ethnicity (OR, 1.50; 95% CI, 2.09-1.11;P = 0.02), higher

240 fference did not significantly vary by race, ethnicity, or age group.

241 nfidence interval [CI], 1.20-3.54), Hispanic ethnicity (P = 0.011; OR, 6.01; 95% CI, 1.51-23.9), meta

242 y patient sexual behavior (p&0.001) and race/ethnicity (p&0.001).

243 iation of myopia with age, sex, grade level, ethnicity, parental history of myopia and severity.

244 s consumed, adjusting for maternal age, race/ethnicity, parity, education levels, prepregnancy BMI, p

245 Structural determinants included race/ethnicity, poverty, insurance status, education, populat

246 risk factors for lead exposure include race/ethnicity, poverty, Medicaid enrollment, housing built b

247 mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the clo

248 ictors/protectors were identified, including ethnicity, prenatal tobacco smoke exposure, history of a

249 le diverse cohorts to generate ancestry- and ethnicity PRSs.

250 ignificant association between diagnosis and ethnicity/race (P < 0.001), with PCG more frequent in no

251 ecial attention to differences in geography, ethnicity/race and sex, as well as traditional and novel

252 reater prevalence when compared to all other ethnicities, regardless of sex.

253 uals that had cancer, based on age, sex, and ethnicity serving as a comparison group.

254 udies (altered glucose homeostasis, obesity, ethnicity, sex, etc.), the limited availability of repre

255 stered by subject and adjusted for age, race/ethnicity, sex, income, environmental tobacco smoke, con

256 ined high, after adjustment for deprivation, ethnicity, smoking and obesity: adjusted HR 2.59 (95% CI

257 tific community (i.e., those of gender, race/ethnicity, socioeconomic background, sexual orientation,

258 tions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but p

259 ed on sex and common classifications of race/ethnicity, socioeconomic status and geographical region.

260 hmC in AD pathogenesis and highlighting both ethnicity-specific and overlapping changes of brain hydr

261 We conducted ethnicity-specific and trans-ethnic epigenome-wide assoc

262 of additive, dominance, epistasis, and their ethnicity-specific effects.

263 Overall, sex- and race/ethnicity-specific PAFs and 95% CIs were estimated.

264 Race/ethnicity-specific references for FFMI and FMI will incr

265 s) in rates were estimated by age, sex, race/ethnicity, state, and region.

266 m CHD significantly declined among all races/ethnicities studied, although disparities in mortality p

267 ions of both HDL-C and HDL-P for MI by Black ethnicity suggest that atherosclerotic cardiovascular di

268 ad rely on a more comprehensive framework of ethnicity; that authors consider not just race and ethni

269 When stratified by race/ethnicity, the association was limited to 311 (45 ASD) B

270 We used multivariable analyses of U5MR by ethnicity to adjust for household wealth, maternal educa

271 etheless, there have been calls for race and ethnicity to be included as risk-adjusted variables in t

272 controls (pair-matched on BMI, age, and race/ethnicity) to discover metabolites associated with new o

273 Age, sex, race/ethnicity, tobacco use, chronic conditions, influenza va

274 Ethnicity trend differences were insignificant, but Sout

275 Sex, age, and race/ethnicity varied across preventability categories (P < 0

276 Matching individuals on age, sex, ethnicity, visit timing, and recent antibiotic receipt,

277 panic black (versus non-Hispanic white) race/ethnicity was associated with higher risk for cardiovasc

278 Hispanic ethnicity was associated with less linkage-to-care, and

279 For example, ICE-income + race/ethnicity was associated with preterm delivery in both e

280 Recipient ethnicity was associated with pretransplant opioid use.

281 Maternal race/ethnicity was associated with significant differences in

282 omorbidity Index, and insurance status, race/ethnicity was still independently associated with poor o

283 Pardo ethnicity was the second most important risk factor (aft

284 some comorbidities may be underreported and ethnicity was unknown for 24% of participants.

285 E) groups, 38% (235) white and for 22% (135) ethnicity was unknown.

286 ange) age was 61 years (48-74); 73% men; and ethnicity was White in 34%.

287 to transition to a fistula, and other races/ethnicities were significantly more likely to transition

288 tions by age, sex, socioeconomic status, and ethnicity were described from 2009 to 2018 inclusive.

289 fferences by social deprivation, region, and ethnicity were examined using Poisson regression, taking

290 admission, or mechanical ventilation by race/ethnicity were found.

291 /CARD15 polymorphisms, perianal disease, and ethnicity were risk factors for penetrating (B3) and/or

292 patients with previous history; diabetes and ethnicity were the only independent predictors of HCC re

293 n = 723, 71% women, median age 34; 85% white-ethnicity) were either following (n = 170, 24%) or had t

294 overty level, overall and stratified by race/ethnicity, were used to calculate adjusted prevalence ra

295 e unadjusted odds of death did not differ by ethnicity, when adjusting for age, sex and comorbidities

296 es of Caucasian, Turkish and French-Canadian ethnicities with seven affected children that showed fea

297 nd 58% were male; 83% were of European/other ethnicity, with the rest Maori, Polynesian, or South Asi

298 e patients as well as patients of mixed race/ethnicity within a New York City health system.

299 ed to predict life expectancy, adjusting for ethnicity, working status, deprivation, body mass index,

300 female sex, Hispanic and non-Hispanic black ethnicity, worse glycemic control, and elevated heart ra