ライフサイエンスコーパス: anthropometric

1 variables in the domains of demographics and anthropometrics (7), prehospital (11), emergency departm

2 Demographic, anthropometric, admission, illness severity, laboratory,

3 An anthropometric analysis confirmed the prediction of heal

4 All 232 individuals underwent anthropometric and biochemical investigations and genoty

5 Surveys that include anthropometric and biochemical measurements at the famil

6 Anthropometric and biochemical parameters were recorded.

7 fter adjustments for age, smoking, drinking, anthropometric and biochemical variables, or menopausal

8 Anthropometric and bioelectrical impedance measures were

9 Childhood anthropometric and bioelectrical impedance outcomes incl

10 frequency questionnaires and fasting blood, anthropometric and blood pressure measurements were obta

11 ine and every 4 wk, blood, urine, feces, and anthropometric and body composition measures were collec

12 which biological and environmental samples, anthropometric and clinical measurements, and additional

13 r-metabolic, neuropsychiatric, physiological-anthropometric and cognitive traits in the participants

14 By using anthropometric and demographic variables, the equation w

15 Bone scans and anthropometric and dietary assessments were conducted.

16 6 in mid-childhood (median, 7.7 years) using anthropometric and dual X-ray absorptiometry (DXA) measu

17 ly lower" trajectory, accounting for age and anthropometric and lifestyle factors.Within both sexes,

18 obank, and its joint measurement of genetic, anthropometric and lifestyle variables, offers an unprec

19 Adding anthropometric and medical history variables to the mode

20 lated soluble fiber supplementation improves anthropometric and metabolic outcomes in overweight and

21 In multiple regression, including anthropometric and metabolic parameters, steatosis remai

22 ic diet with an LGI and low glycemic load on anthropometric and metabolic variables, ghrelin and lept

23 Participants had anthropometric and nutritional assessments and seven sch

24 examined relations between HMO and maternal anthropometric and reproductive indexes and indirectly e

25 Anthropometric and spirometric assessments were undertak

26 We studied body anthropometrics and arterial morphology and physiology i

27 Anthropometrics and biomarkers of glucose metabolism wer

28 We measured infants' anthropometrics and used dual-energy X-ray absorptiometr

29 Multivariable models included demographic, anthropometric, and clinical variables in addition to es

30 Clinical, anthropometric, and demographic variables were collected

31 Demographic, anthropometric, and diagnostic information were collecte

32 the geographic, demographic, socioeconomic, anthropometric, and environmental status of the MAL-ED c

33 yslipidemia in excess of measured lifestyle, anthropometric, and inherited genetic factors.

34 At recruitment (1992-1998), dietary, anthropometric, and lifestyle information was collected.

35 Clinical, anthropometric, and survival differences were small amon

36 Information on satiety responsiveness, anthropometrics, and genotype was available for 2258 chi

37 ONTROL; matched for dose with LOW), on child anthropometrics, and to explore putative mediators of we

38 Among older adults, the optimal anthropometric approach to risk stratification of AF rem

39 Nutritional status was assessed by anthropometric assessment, bioimpedance, handgrip streng

40 m circumference (MUAC) has long been used in anthropometric assessments of nutritional status in fiel

41 length-for-age z scores (LAZs) obtained from anthropometric assessments that incorporated covariate p

42 Cardiopulmonary, demographic, and anthropometric assessments were conducted before and aft

43 Baseline interviews and anthropometric assessments were conducted, followed by b

44 Anthropometrics, BMC, and body composition via dual-ener

45 Anthropometric, body composition, and behavioral data we

46 Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and ex

47 urther explore physiological processes at an anthropometric, cellular, and molecular level.

48 There were no differences in anthropometric changes between groups; however, weight,

49 The NDS was not associated with anthropometric changes during follow-up.

50 Child anthropometric characteristics and family income were as

51 Subjects were matched for other anthropometric characteristics and were studied using a

52 II, increased with an increase in all of the anthropometric characteristics examined.

53 Growth measures were linked with age-5-years anthropometric characteristics using linear regression.

54 with respect to phenotypic traits related to anthropometric characteristics, dietary habits, social s

55 owth and adult cardiometabolic risk factors (anthropometric characteristics, lipids, insulin sensitiv

56 st associations of metabolomic profiles with anthropometric, clinical and biochemical parameters.

57 This analysis examined preoperative anthropometrics, comorbid conditions, and major and mino

58 Anthropometric data (height, weight, BMI, and waist circ

59 Studies with large samples of anthropometric data (n > 1,000) were reviewed to track w

60 Socio-demographic and anthropometric data [anthropometric measurements, blood

61 scores were calculated from parent-reported anthropometric data for each child.

62 esity in mid-life using objectively measured anthropometric data from UK Biobank.

63 We collected anthropometric data including weight, height, and body m

64 Anthropometric data of the children were collected repea

65 Anthropometric data were collected in 146 participants w

66 Clinical and anthropometric data were collected, and biochemical and

67 Anthropometric data were complete at the 24-month visit

68 Dual-energy x-ray absorptiometry and anthropometric data were used to determine changes in bo

69 Anthropometric data, biochemical measurements, and infor

70 Participants' anthropometric data, blood values and objective PA were

71 This finding was also independent of anthropometric data.

72 lings and also after adjustment for maternal anthropometric data.

73 en aged <10 years had complete genotypic and anthropometric data; 796 were followed up over a median

74 We collected anthropometric data; plasma samples; and SAT, VAT, and l

75 All degrees of anthropometric deficits are associated with increased ri

76 In cause-specific analyses, all degrees of anthropometric deficits increased the hazards of dying f

77 <-1), moderate (-3</=Z<-2), or severe (Z<-3) anthropometric deficits with the reference category (Z>/

78 was elevated among children with 1, 2, and 3 anthropometric deficits.

79 the mortality risk associated with multiple anthropometric deficits.

80 with dual-energy x-ray absorptiometry (DXA), anthropometric, demographic, and prescription medication

81 the present study were therefore to compare anthropometric dimensions, blood values, psychological f

82 gitudinal Study from whom DNA and dental and anthropometric endpoints were collected during multiple

83 evaluation, including collection of history, anthropometric examination, and biochemical tests.

84 Periodontal and anthropometric examinations were performed.

85 ls explained minimal additional variation in anthropometric factors (null coefficients; adjusted R(2)

86 (EF) vary significantly with demographic and anthropometric factors and are associated with poor prog

87 Socio-demographic, clinical, and anthropometric factors, along with access to toilets and

88 family relatedness and offspring lifestyle, anthropometric factors, and inherited genetic variants (

89 II) and single components of MetS, including anthropometric factors, blood pressure, lipids, triglyce

90 of bloodspot adiponectin by demographic and anthropometric factors, fasting insulin and glucose.

91 le nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive fa

92 1.89), independent of potential demographic, anthropometric, family history, reproductive, and lifest

93 The geographical, anthropometrics, FEV1, dyspnea, comorbidities, and healt

94 indings suggest that differences in maternal anthropometrics, gestational weight gain, and preterm bi

95 ral palsy, hearing or visual impairment, and anthropometric growth parameters.

96 hand grip, and respiratory muscle strength; anthropometrics (height, weight, mid-arm circumference,

97 investigated the association between these 2 anthropometric indexes and body composition to help unde

98 e widespread use of weight- and length-based anthropometric indexes as proxies for adiposity, little

99 .The aim was to determine the association of anthropometric indexes with risks of inpatient and postd

100 Anthropometric indexes, blood pressure, and heart rate w

101 not reduce the risk of death associated with anthropometric indexes.U6M infants at the highest risk o

102 re similar using body mass index (BMI) as an anthropometric indicator of nutritional status.

103 sociation between anemia and any other child anthropometric indicator was detected.

104 Body fat distribution was assessed based on anthropometric indicators alone.

105 We aimed to analyse anthropometric indicators for childhood and maternal nut

106 le requirements, favorably shifted metabolic/anthropometric indicators of dysregulation in a healthy

107 d explored the use of visceral adiposity and anthropometric indicators to identify men and women with

108 Anthropometric indicators were estimated for all age gro

109 Anthropometric indices including body mass index (BMI) a

110 Caucasians whose 35 clinical blood test and anthropometric indices matched the medical norm, we prov

111 Age and anthropometric indices were higher in the GDM than non-G

112 ,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control,

113 is study has limitations because some of the anthropometric information was obtained from retrospecti

114 Anthropometric, lipid, inflammatory, and IR markers were

115 in 2000-2010 in the Dortmund Nutritional and Anthropometric Longitudinally Designed Study were analyz

116 Diarrhea during the 30 days prior to anthropometric measurement was consistently associated w

117 for antibiotic use, infection diagnosis, and anthropometric measurements (and thus BMI and obesity st

118 Anthropometric measurements (i.e., BMI, waist/hip circum

119 Anthropometric measurements and %L through urine were co

120 Anthropometric measurements and activity history data we

121 ormed a clinical examination and nurses took anthropometric measurements and assessed self-reported s

122 No effect of dietary interventions on anthropometric measurements and body composition was fou

123 at 1 year of age, determined from objective anthropometric measurements and defined according to Wor

124 Both groups showed a significant decrease in anthropometric measurements and significant improvements

125 A significant reduction in anthropometric measurements and significant improvements

126 A statistically significant reduction in anthropometric measurements and significant improvements

127 A statistically significant reduction in anthropometric measurements and statistically significan

128 cal records, hematological, biochemical, and anthropometric measurements and telomere lengths were co

129 etermined from regression equations based on anthropometric measurements derived from relatively smal

130 an National Nutrition Survey, which included anthropometric measurements for 33 638 children younger

131 Anthropometric measurements for every age-eligible respo

132 of maternal body mass index (BMI) with child anthropometric measurements from birth through infancy a

133 We used repeated cross-sectional anthropometric measurements from fitness testing of Amer

134 etween exposure to PBDEs via breast milk and anthropometric measurements in early childhood.

135 Anthropometric measurements of the village children aged

136 There were no differences in anthropometric measurements or energy intakes between gr

137 arly-life PBDE exposures via breast milk and anthropometric measurements overall; however, our result

138 We used ultrasound to take fetal anthropometric measurements prospectively from 14 weeks

139 esity outcomes were determined directly from anthropometric measurements using National Health and Nu

140 equency consumption, 24-h dietary recall and anthropometric measurements was applied to 241 children

141 Forty-eight percent of the anthropometric measurements were classified as overweigh

142 Anthropometric measurements were converted into age- and

143 Lifestyle, diet, and anthropometric measurements were obtained at baseline an

144 can in the first trimester, and infant birth anthropometric measurements were obtained from hospital

145 o significant differences in weight loss and anthropometric measurements were seen between groups aft

146 Anthropometric measurements were similar in the LP and b

147 Anthropometric measurements were taken at all study visi

148 Anthropometric measurements were taken at baseline and 5

149 Anthropometric measurements were taken at birth and at 1

150 Infant anthropometric measurements were taken every month for 6

151 Anthropometric measurements were taken from 108 patients

152 Anthropometric measurements were taken weekly for 4 wk t

153 cy and general health status questionnaires, anthropometric measurements were taken, and a fasting bl

154 Anthropometric measurements were taken, and growth index

155 ociations of body mass index (BMI) and other anthropometric measurements with lung cancer were examin

156 study visits (n = 246 children with > 1,400 anthropometric measurements).

157 Self-reported anthropometric measurements, adjustment for intermediary

158 obtained clinical and epidemiological data, anthropometric measurements, and a faecal sample to iden

159 Survey, anthropometric measurements, and laboratory data were co

160 djusted for age, sex, socioeconomic factors, anthropometric measurements, and lifestyle.

161 The periodontal parameters, anthropometric measurements, and serum levels of triglyc

162 Data on demographic characteristics, anthropometric measurements, biomarkers of nutrient stat

163 Socio-demographic and anthropometric data [anthropometric measurements, blood pressure and total bo

164 Anthropometric measurements, blood samples, and lifestyl

165 Anthropometric measurements, demographic characteristics

166 Follow-up Study, which included standardised anthropometric measurements, feeding practices based on

167 Anthropometric measurements, inflammatory markers (IL-6,

168 l ethers and its relation to early childhood anthropometric measurements.

169 sampling methodology, survey questions, and anthropometric measurements.

170 ral risk factors, other dietary factors, and anthropometric measurements.

171 re forms of malnutrition and correlates with anthropometric measurements.

172 ild-days of diarrhea surveillance and 15,629 anthropometric measurements.

173 significant, positive associations for all 9 anthropometric measures (HRs ranging from 1.08 [95% conf

174 ortcomings were observed in items related to anthropometric measures (the main variable of interest),

175 artum contribute equally to adverse maternal anthropometric measures 7 y after delivery.

176 dinal association between NIS inhibitors and anthropometric measures [height, waist circumference, an

177 s observed for either of the obesity-related anthropometric measures after adjustment for lean body m

178 rotein intake during pregnancy and offspring anthropometric measures and biomarkers of adiposity and

179 ps was compared between tools and related to anthropometric measures and clinical variables [e.g., le

180 Anthropometric measures and diet records were collected

181 11) for a follow-up assessment that included anthropometric measures and DNA collection.

182 composition variables were assessed by using anthropometric measures and dual-energy X-ray absorptiom

183 The primary endpoints were anthropometric measures and gut integrity [assessed by u

184 al questionnaires; a research nurse recorded anthropometric measures and insurance status.

185 Anthropometric measures and menopausal status contribute

186 Anthropometric measures and self-reported life-style inf

187 Rs for postdischarge mortality for different anthropometric measures and thresholds.

188 tudies with long-term follow-up and repeated anthropometric measures are typically subject to missing

189 To explore the latter anthropometric measures as causal mediators, we also use

190 c risks were determined by serum markers and anthropometric measures at pre- and post-intervention.

191 All patents had fasting blood tests and anthropometric measures at the time of liver biopsy.

192 as the obvious correlations between various anthropometric measures hamper identification of the cha

193 aPBDEs during pregnancy were associated with anthropometric measures in children aged 1-8 years.

194 ome (OSAS) risk with periodontal disease and anthropometric measures in Class III obese patients.

195 ast milk were not associated with early-life anthropometric measures in the PIN Babies cohort.

196 Anthropometric measures included height, weight, body ma

197 th Cohort, information on parental and child anthropometric measures is available for 30,655 trio fam

198 ollowed from birth through 24 mo of age with anthropometric measures obtained every 3 mo.

199 45 men and 1110 women in 15 centres and also anthropometric measures of fatness including body mass i

200 Anthropometric measures remained stable for both cohorts

201 Iron, vitamin A, anemia, malaria, and anthropometric measures were assessed at baseline and at

202 Birth anthropometric measures were made at home.

203 siderable portion of children with subnormal anthropometric measures were not identified with all of

204 Newborn anthropometric measures were obtained within 12 h of bir

205 In addition, anthropometric measures were taken and risk factors were

206 y until 36 wk of gestation (P36), and infant anthropometric measures were taken at 2, 13, and 52 wk p

207 BP and anthropometric measures were taken at P20 and then 4 wee

208 The combination of anthropometric measures with metabolic parameters, such

209 Socioeconomic data, anthropometric measures, and blood samples were collecte

210 available on glycemic indices, lipid traits, anthropometric measures, blood pressure, coronary artery

211 on included socioeconomic and clinical data, anthropometric measures, blood pressure, human immunodef

212 RONGKIDS)] compared with and were related to anthropometric measures, body composition, and clinical

213 10 follow-up study collected data on current anthropometric measures, bone mineral density (BMD) meas

214 mass index and secondary outcomes including anthropometric measures, cardiometabolic risk factors, p

215 renia and a range of other human phenotypes (anthropometric measures, cardiovascular disease risk fac

216 obesity and IR with complete data, including anthropometric measures, FFAs, IR measured by euglycemic

217 macro- and microcirculation, blood pressure, anthropometric measures, glucose metabolism, and biomark

218 Various anthropometric measures, including height, have been ass

219 ntration <70 g/L) and individual-level (age, anthropometric measures, micronutrient deficiencies, mal

220 Other outcomes were adverse events, anthropometric measures, mood, and pain.

221 range: 5.7 y, 6.8 y), we measured childhood anthropometric measures, total fat mass and the android:

222 cidence of gestational diabetes and neonatal anthropometric measures.

223 g dual-energy X-ray absorptiometry (DXA) and anthropometric measures.

224 comes comprised recovery rate and additional anthropometric measures.

225 ssociations between maternal PBDEs and child anthropometric measures.

226 BMD), BMC, and bone area at the 4% tibia and anthropometric measures.No significant differences in th

227 conditions; schooling; child care behavior; anthropometric measures; and cognitive function were col

228 Anthropometric, metabolic, and periodontal parameters we

229 indicators (functional capacity (VO(2peak)), anthropometrics) of CR post-HT compared to post-coronary

230 ct in men was not influenced by demographic, anthropometric, or metabolic factors; by the development

231 oncentrations were not associated with child anthropometric outcomes (all p-values > 0.05).

232 s related maternal component scores to child anthropometric outcomes at ages 5 (n = 326) and 7 (n = 3

233 ively followed for mortality, morbidity, and anthropometric outcomes at monthly visits (median follow

234 No significant associations with anthropometric outcomes were seen in girls (for BMI z-sc

235 ith respect to demographics (except age) and anthropometric parameters as well as comorbidities.

236 5 years of age were not associated with any anthropometric parameters at 5 or 9 years, but BPA conce

237 s (SNPs) were associated with functional and anthropometric parameters in a cohort of old community-d

238 we investigated how chemical properties and anthropometric parameters interact to influence the bioa

239 nical scans is a valuable source to identify anthropometric parameters that influence BAT mass and ac

240 Periodontal parameters, anthropometric parameters, and serum levels of high-sens

241 standard polysomnography was performed, and anthropometric, pathologic, clinical, and pharmacologica

242 s are associated with multiple metabolic and anthropometric phenotypes and have large effect sizes fo

243 aim of the study was to derive and validate anthropometric prediction equations to quantify whole-bo

244 locate the HJC were developed using various anthropometrics predictors.

245 5% confidence intervals (CIs), adjusting for anthropometric, reproductive, lifestyle, and socioeconom

246 Lean body mass was the predominant anthropometric risk factor for AF, whereas no associatio

247 We studied the role of anthropometric risk factors for differentiated thyroid c

248 for the ability of REG1B to forecast future anthropometric shortfalls, independent of known predicto

249 ssion models were adjusted for demographics, anthropometrics, smoking status, cardiac risk factors, a

250 d function after adjusting for demographics, anthropometrics, smoking status, diabetes mellitus, and

251 After adjustment for anthropometric, sociodemographic, and lifestyle factors,

252 for routine clinical practice, international anthropometric standards to assess newborn size that are

253 and AGP in WRA.Recent morbidity and abnormal anthropometric status are consistently associated with i

254 ween maternal malaria infection and maternal anthropometric status on the risk of LBW using pooled da

255 such as demographics, reported illness, and anthropometric status, in preschool children (PSC) (age

256 Blinded assessments of patients' arm anthropometrics, strength, pulmonary function, 6-minute-

257 within 12 h of birth by identically trained anthropometric teams using the same equipment at all sit

258 In the entire cohort, adjusted for anthropometrics, trabeculation was higher in African Ame

259 We included an anthropometric trait, body mass index, for comparison.

260 previously reported signals for a different anthropometric trait.

261 p11.2 and 22q11.21, implicating at least one anthropometric trait.

262 We tested for association with newborn anthropometric traits (birth length, head circumference,

263 981) study, and the Genetic Investigation of ANthropometric Traits (body mass index in 152,893 men an

264 Cs) representing body shape derived from six anthropometric traits (body mass index, height, weight,

265 5), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19

266 statistics from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the Interna

267 rticipants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an

268 The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 l

269 mary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare an

270 GG) Consortium, the Genetic Investigation of Anthropometric Traits (GIANT) Consortium, the Tobacco an

271 e 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium.

272 Consistent with the Genetic Investigation of ANthropometric Traits (GIANT) dataset results, we didn't

273 Consortium (GLGC), Genetic Investigation of Anthropometric Traits (GIANT), and Meta-Analysis of Gluc

274 verlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis

275 using data from the Genetic Investigation of Anthropometric Traits and Psychiatric Genomics consortia

276 amine the broader allelic architecture of 12 anthropometric traits associated with height, body mass,

277 ic simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well

278 large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples fro

279 d rare variants affecting body size and that anthropometric traits share genetic loci with developmen

280 well-powered GWASs of cognitive, medical and anthropometric traits to predict three core developmenta

281 led hundreds of genetic loci associated with anthropometric traits, one trait at a time.

282 orders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remain

283 type that is represented by a combination of anthropometric traits.

284 s between specific gene KOs and quantitative anthropometric traits.

285 sted associations between gene KOs and three anthropometric traits: body mass index (BMI), height and

286 Neonatal anthropometric values were measured at birth, and abdomi

287 ndent variable for multiple regressions) and anthropometric variables (independent variables).

288 owing for each patient: nutritional indices, anthropometric variables and handgrip strength.

289 ociated with MetS even after controlling for anthropometric variables and lipid profiles.

290 Anthropometric variables and PLIN1 genotypes were analyz

291 Results did not change after controlling for anthropometric variables and potential confounders.

292 erence equations should account for not only anthropometric variables but also spirometer type.

293 Anthropometric variables including body composition were

294 ns, length of hospital stay, biochemical and anthropometric variables, and costs of hospitalization w

295 ociated with PCOS even after controlling for anthropometric variables, blood pressure, lipid profile

296 Measurements included anthropometric variables, breastfeeding, hemoglobin, pla

297 Secondary endpoints were changes in anthropometric variables, including knee-heel length.

298 between both measures of SES and illnesses, anthropometric variables, psychiatric disorders, and cog

299 ortion of children younger than 5 years with anthropometric wasting.

300 e, 6-month exercise stress test results, and anthropometrics were examined retrospectively among cons

301 tricted cubic splines for the mean change in anthropometric z scores were fit for each group.