ライフサイエンスコーパス: BMI

1 BMI (52.18 vs. 40.11, p = 0.001), insulin (19.35 vs. 8.8

2 BMI was a poor diagnostic parameter.

3 BMI was assessed at baseline, after 3 and 6 months of di

4 BMI was increased in 60% of female patients.

5 oantibodies, age at diabetes onset, HbA(1c), BMI, and measures of insulin resistance and insulin secr

6 emales), with mean BMI 36.9 +/- 5.3 kg/m(2) (BMI SDS 3.33 +/- 0.79).

7 For >=25 BMI only, 10 mg/dL increase in HDL-C change was associat

8 t cohort (combined cohort, body weight 6.3%, BMI 3.6%).

9 eers (17 men and 10 women, age 35.1 +/- 7.3, BMI 32.3 +/- 8.0), who were healthy other than having im

10 nd WL in the previous 6 mo, and considered 4 BMI categories-underweight (BMI < 22.5), normal weight (

11 Hazard ratios per 5 BMI units, calculated using proportional hazards regress

12 A PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0

13 and data from 394 waist-to-hip ratio and 773 BMI-associated loci.

14 , male sex [P = 0.015, OR 1.77 (1.10-2.81)], BMI at diagnosis [P < 0.001, OR 1.10 (1.07-1.14)], and d

15 rolled in a weight-loss program to achieve a BMI <25, and were followed for 2 y.

16 rweight (including obesity) was defined as a BMI >=25.

17 osed with a cardiomyopathy was detected at a BMI of 21 kg/m(2), with a gradual increase in risk with

18 owest all-cause mortality was observed for a BMI of 22.5 kg/m(2) in all participants, and a WC of 78

19 stratified analyses, the HR for those with a BMI >= 25 was 1.12 per unit (95% CI:1.05-1.19) and those

20 per unit (95% CI:1.05-1.19) and those with a BMI < 25 was 1.04 per unit (95% CI:0.92-1.18).

21 270 adult participants (135 cases with a BMI <18.5 and 135 controls with a BMI between 18.5 and 2

22 ses with a BMI <18.5 and 135 controls with a BMI between 18.5 and 24.9) aged 18-45 y were enrolled be

23 associated with increased risk of SMM across BMI groups, except in women with class 3 obesity, for wh

24 After adjustment for history, adding BMI, waist-to-height ratio and total skinfolds (anthropo

25 n, parental transmitted GRSs, based on adult BMI, contribute to child overweight, but in overweight m

26 These associations were not modified by age, BMI, smoking, or red meat intake (All P(interaction) > 0

27 p = 0.005) after adjustment for gender, age, BMI and smoking.

28 fter adjustment for baseline C-peptide, age, BMI, and sex, baseline levels of miR-3187-3p, miR-4302,

29 tor for velum-CCC, controlling for sex, age, BMI, and TS grade.

30 In linear regression analysis, BMI was positively associated with serum levels of TC, L

31 ssover trial in adult subjects with ARDS and BMI >=35 kg/m(2) (n=21) was performed to explore the hem

32 s between circulating protein biomarkers and BMI at baseline, during a weight loss diet intervention,

33 ence for the role of smoking, vitamin D, and BMI in melanoma progression independent of a postcode-de

34 not sex when volume was controlled for, and BMI had only a small but significant association with sh

35 iations between grand-maternal lifestyle and BMI in grandchildren were mainly mediated by maternal pr

36 o greater than 3 times the normal limit, and BMI <= 28 kg/m.

37 years, CD4+ T-cell count 512 cells/muL, and BMI 26.4 kg/m2.

38 cut-offs for survival, according to sex and BMI (+/-25) were computed.

39 plore the association of height, weight, and BMI with refractive error and ocular biometric measures

40 er, as data on metabolic parameters (such as BMI and levels of glucose and insulin) in patients with

41 st identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes

42 ds regression, declined steadily with age at BMI assessment, from 1.25 (95% confidence interval: 1.18

43 The increase in the average BMI and prevalence of obesity was steeper among the gene

44 Baseline BMI (mean+/-SD) was similar between groups (36.8 +/- 2.6

45 was 45.8 years (SD 11.5), the mean baseline BMI was 29.5 kg/m2 (SD 5.1), and the mean weight loss pr

46 he results imply that the effect of baseline BMI, HAART initiation, baseline viral load, and the numb

47 Besides BMI and ALT, integrase inhibitor exposure was associated

48 iet quality modifies the association between BMI and all-cause mortality in women and men.

49 o study has reported the association between BMI and Hcy levels in schizophrenia.

50 19, there was a J-shaped association between BMI and risk for death, even after adjustment for obesit

51 ORs and 95% CIs for the associations between BMI and risk of CRC by major molecular pathological feat

52 uggesting additional interdependence between BMI and lung function.

53 ear, but not quadratic, relationship between BMI and model-based control.

54 al sample had an overall improvement in both BMI (-0.9+/-0.6) and fat mass (FM: -2.3+/-1.5), while le

55 Gestational lipid trajectories differed by BMI group and were differentially associated with birthw

56 th wrists, multiplied by age, and divided by BMI has been used as an index.

57 tive causal pathways to diabetes mediated by BMI for four genes.

58 -for-gestational age (LGA or SGA) neonate by BMI group.

59 lassroom NO(2) levels and asthma outcomes by BMI stratification.

60 of the tumour microenvironment that vary by BMI in the tumour and peritumoral adipose tissue, which

61 ents undergoing laparoscopic gastric bypass (BMI >35-50) from January 1, 2005 to December 31, 2013 we

62 Higher child BMI was associated with more energy from the "salt, umam

63 lities to be associated with increased child BMI.

64 Adiposity outcomes were child BMI and sum of skinfolds (SSF), and candidate eating beh

65 We created a variable combining BMI at cancer diagnosis and WL in the previous 6 mo, and

66 of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which cou

67 between serum 25-hydroxyvitamin D [25(OH)D], BMI, and 16 inflammatory biomarkers, and to assess the r

68 n between Adv36 seropositivity and different BMI categories, or glucose tolerance status.

69 king, chronic obstructive pulmonary disease, BMI, renin-angiotensin-aldosterone system inhibitor use,

70 UNa significantly elevated BMI-adjusted WHR in men [0.321 (0.094-0.548)], but not i

71 uted tomography from 83 subjects (49 M/34 F, BMI [Formula: see text]) was used to derive two statisti

72 their counterparts (24.0 to 26.9 kg/m(2) for BMI) (odds ratios [OR] and 95% confidence intervals: 4.1

73 Prediction accuracy improved by 28.7% for BMI and 10.2% for smoking over a LASSO model, with age-,

74 owed positive associations when adjusted for BMI (OR per 10 cm = 1.38 (0.98-1.94)).

75 and a third model additionally adjusted for BMI and estimated glomerular filtration rate (eGFR) were

76 Additional adjustment for BMI yielded similar results.

77 0.89-1.08, P = 0.69), after controlling for BMI.

78 HR (95% confidence interval [CI]) of EOS for BMI categories <18.5, 25.0-29.9, 30.0-34.9, 35.0-39.9, a

79 predisposed tenth, defined using the GPS for BMI.

80 aist circumference and body fat, and low for BMI.

81 l, lipid transport and sterol metabolism for BMI, and xenobiotic stimuli response for smoking, showed

82 nd a J-shaped association was suggestive for BMI.

83 +/- 4.07 kg/m with a postsleeve gastrectomy BMI of 34.07 +/- 3.73 kg/m, representing total body weig

84 There were no differences in gender, BMI, % body fat, visual acuity or contrast sensitivity b

85 t circumference threshold values for a given BMI category, to optimize obesity risk stratification ac

86 Other parameters, such as glucose, BMI, insulin, HOMA-IR and lipid profile, were also inves

87 tients in the DJBL group experienced greater BMI loss [mean adjusted difference (95% confidence inter

88 nt was common among middle-aged PWH; greater BMI and physical inactivity are important modifiable fac

89 volume was significantly related to height, BMI and age, and that there was an acceleration in muscl

90 High BMI was associated with elevated risk for Caucasians and

91 We studied whether a high BMI was associated with better survival, and whether the

92 to note that within each age category, high BMI individuals were predicted to be older on average th

93 < 0.05) were the influencing factors of high BMI.

94 Adult asthmatics with PTE were high BMI and heavy compared with those without PTE.

95 Among participants with normal or high BMIs, rates of cure, treatment failure, or death did not

96 to a low-steatosis graft placed into a high-BMI recipient.

97 4 cohorts: (1) high-steatosis graft in high-BMI recipient; (2) low-steatosis graft in high-BMI recip

98 I recipient; (2) low-steatosis graft in high-BMI recipient; (3) high-steatosis graft in normal-BMI re

99 Among women, a higher BMI was differentially and more strongly associated with

100 In adjusted analyses, higher BMI was associated with dialysis initiation and with ven

101 l mediator in the association between higher BMI and inflammation.

102 ic" group (37%-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH

103 DM, TB patients with diagnosed DM had higher BMI and HbA1c, less severe TB, and more frequent comorbi

104 each 5-kg/m(2) genetically-predicted higher BMI was associated with a 49% (1.49; 1.39 to 1.59) incre

105 Higher composite risk score predicted higher BMI z scores (B = 0.08; 95% CI: 0.04, 0.13) and larger S

106 PFNA and PFDA were associated with higher BMI SDS [adjusted beta = 0.26; 95% confidence interval (

107 ures was more strongly increased with higher BMI than risk of CRC with the traditional pathway featur

108 with a gradual increase in risk with higher BMI, particularly for dilated cardiomyopathy, where a ha

109 usting for sociodemographic/medical history, BMI (Odds Ratio [OR] = 1.62 [95%CI 1.32-1.99]), waist-to

110 46 years, average annual rates of change in BMI, FEV1, FVC, and FEV1:FVC ratio were 0.22 kg/m2/year,

111 The greater increase in BMI in genetically predisposed individuals over time was

112 eases of 2.1 kg in body weight, 0.8 kg/m2 in BMI, 1.4% in PBF, and 2.0, 1.9, 0.6, and 1.0 cm in waist

113 l (P = .04) in combined models that included BMI.

114 other unhealthy habits relating to increased BMI.

115 habits, which was associated with increased BMI (all p for trend < 0.001).

116 intake affects male body shape by increasing BMI-adjusted WHR, but showed no effects on female body s

117 ient obesity was defined as body mass index (BMI) >35 adjusted for ascites.

118 e compared by pre-pregnancy body mass index (BMI) <25 or >=25 kg/m(2); logistic regression models eva

119 l age (<35/>=35 years), and body mass index (BMI) (<30/>=30).

120 negatively associated with body mass index (BMI) (in kilograms per square meter) and positively corr

121 e age 62.4 years (SD 10.8), body mass index (BMI) 27.1 kg/m2 (SD 4.7).

122 l additionally adjusted for body mass index (BMI) and a third model additionally adjusted for BMI and

123 according to pre-pregnancy body mass index (BMI) and maternal age.

124 ly associated with parental body mass index (BMI) and overweight.

125 ia and its association with body mass index (BMI) and pubertal stage.

126 bumin <3.5 g/dL) as well as body mass index (BMI) as a marker of obesity (BMI > 30 kg/m(2)).

127 t moderate doses and with a body mass index (BMI) between 30.0 and 39.9 kg/m(2) were randomly assigne

128 ct on mortality of a higher body mass index (BMI) can be compensated for by adherence to a healthy di

129 of vascular disease across body mass index (BMI) categories.

130 a symptoms and morbidity by body mass index (BMI) category.

131 We hypothesized that body mass index (BMI) could help to explain the association between smoki

132 anning 17 mouse organs with body mass index (BMI) genome-wide association study (GWAS) data from >457

133 A body mass index (BMI) genome-wide polygenic score (BMIGPS) was generated

134 general population, higher body mass index (BMI) has been associated with increased incidence of and

135 th lung size, age, sex, and Body Mass Index (BMI) in healthy subjects across a seven-decade age span.

136 Body mass index (BMI) is a known risk factor associated with kidney trans

137 tly higher in subjects with body mass index (BMI) less than 25 kg/m(2) (n = 13) compared to those of

138 with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped i

139 D insufficiency, and excess body mass index (BMI) might share both peripheral blood and placental gen

140 metabolism in adults with a body mass index (BMI) of 19-27 kg/m(2).(10-18) Twelve healthy adults (age

141 The mean body mass index (BMI) of the participants was 20 kg/m2 and the mean systo

142 or participants with a high body-mass index (BMI) than those with a low BMI (1.31, 1.06-1.63; p=0.015

143 e of waist-to-hip ratio and body mass index (BMI) to CKD prevalence.

144 Pre-procedure body mass index (BMI) was 46.01 +/- 4.07 kg/m with a postsleeve gastrecto

145 ter adjusting for age, sex, body mass index (BMI), and tonsil size (TS), the grade IV individuals had

146 ns, lymphocyte counts, age, body mass index (BMI), complications, and mortality were analyzed.

147 ty, menopausal hormone use, Body Mass Index (BMI), diabetes, and other risk factors.

148 econdary endpoints included body mass index (BMI), glucose control, blood pressure, and lipids, asses

149 Body weight, body mass index (BMI), percentage body fat (PBF), and waist, hip, arm, an

150 ycated haemoglobin (HbA1c), body mass index (BMI), smoking status, comorbidities, consultations, medi

151 e obtained baseline data on body mass index (BMI), smoking, education, and previous disorders.

152 mmunity, adjusting for age, body mass index (BMI), specific gravity (SG), and, for the PCA, other fac

153 To detect obesity with body mass index (BMI), the meta-analyses rendered a sensitivity of 51.4%

154 ts, including education and body mass index (BMI).

155 eters included sex, age and body mass index (BMI).

156 l consumption and increased body mass index (BMI).

157 s also been associated with body mass index (BMI).

158 e conduction, strength, and body mass index (BMI).ResultsTwenty participants with DPN (mean age, 65 y

159 Body mass index (BMI, from measured height and weight) was used as an ind

160 Body mass index (BMI; calculated as weight in kilograms divided by height

161 = .004) and having a lower body mass index (BMI; P = .003), higher white blood cell count (P = .005)

162 ance and effect on obesity (body mass index [BMI] >= 30 kg/m2) in >450,000 individuals (age 40-69 yea

163 n HbA1c 7.4% +/- 1.7%; mean body mass index [BMI] 25.3 +/- 4.0 kg/m2) were followed prospectively in

164 ge [IQR]: age = 28 [25-32], body mass index [BMI] = 35.4 [28.2-41.5]).

165 )), as well as within most of the individual BMI categories (p = 8.1 x 10(-3)-1.4 x 10(-49)).

166 -up data (mean age of 51 years, mean initial BMI 47.2 kg/m2, and 64% female).

167 to baseline smoking status, alcohol intake, BMI, and diabetes status.

168 ry kilogram per meter squared interpregnancy BMI change was associated with a mean 8.3% increase in E

169 on (FMD), FGF-23, serum lipid, hsCRP levels, BMI and HOMA were assessed.

170 body-mass index (BMI) than those with a low BMI (1.31, 1.06-1.63; p=0.015).

171 In this South Indian cohort, a low BMI was significantly associated with an increased risk

172 munosuppression initiating ART, baseline low BMI and hemoglobin and high CRP and D-dimer levels may b

173 g globulin (SHBG) levels with relatively low BMI and insulin levels, and a "metabolic" group (37%-39%

174 Among participants with low BMIs, poorly controlled diabetes (glycohemoglobin [HbA1c

175 .01, 0.33; P for trend = 0.05) kg/m(2) lower BMI and 7% (95% CI 2%, 12%; P for trend = 0.001) lower r

176 In univariate analyses, lower BMI and oxidized LDL, and higher waist-hip ratio, hsCRP,

177 duals suggested that taller height and lower BMI increase educational attainment, these effects were

178 high prevalence of early onset T2D at lower BMI.

179 hods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure.

180 ae and Ruminococcaceae) was related to lower BMI z-scores and longer duration of breastfeeding (per m

181 s/d) was significantly associated with lower BMI (-1.88; 95% CI: -3.27, -0.48) and higher energy inta

182 ent smokers, nonaspirin users, and had lower BMIs, compared with controls (P < .05).

183 In normal weight women (18.5 <= BMI < 25), women with central obesity (WC > 88 cm) had a

184 rved basis (n = 130; M age = 45.8, SD = 8; M BMI = 34.48 kg/m2, SD = 4.87) and randomised by a blinde

185 ontrolled attenuation parameters < 296 dB/m, BMI < 25 kg/m(2) and normal waist circumference were inc

186 e relations between metabolites and maternal BMI and fat mass.

187 st important factors were increased maternal BMI and maternal height, improved maternal and newborn h

188 the GRS associations may depend on maternal BMI, being weaker among mothers with overweight.

189 Overall, maternal BMI, along with maternal socioeconomic status and lifest

190 Among 100 patients (76% female; mean BMI, 36.9 kg/m(2) [SD, 2.7]), 88% from the RYGB group an

191 ts (mean age, 61 years +/- 10; 55% men; mean BMI, 27 kg/m(2) +/- 5) were enrolled in this study.

192 DPN (mean age, 64 years +/- 9; 55% men; mean BMI, 30 kg/m(2) +/- 6), and 20 HC participants (mean age

193 rs +/- 9 [standard deviation]; 70% men; mean BMI, 34 kg/m(2) +/- 5), 20 participants without DPN (mea

194 ipants (14-18 years; 59% females), with mean BMI 36.9 +/- 5.3 kg/m(2) (BMI SDS 3.33 +/- 0.79).

195 ts (n=525; mean age 21.5 +/- 3.0 years; mean BMI of 20.7 +/- 2.7kg/m(2)).

196 ity, and of normal pre-pregnancy BMI (median BMI: 23.5 kg/m2).

197 ge was 70 with 89% white, 59% female, median BMI 35.1, and 48% with diabetes.

198 nducted with multiple imputation for missing BMI.

199 pared with infants of normal-weight mothers (BMI, 18.5-24.9), the adjusted HR (95% confidence interva

200 Neither BMI nor the Townsend deprivation score were predictive i

201 w mMED had a high mortality despite a normal BMI (HR 1.60; 95% CI 1.48-1.74).

202 years), which was not observed in the normal BMI group.

203 eing overweight or obese (relative to normal BMI) were significantly associated with decreased odds o

204 Compared with individuals with normal BMI, the multivariable adjusted odds of CAC >0 were incr

205 ed with a high-steatosis graft into a normal-BMI recipient is similar in magnitude to a low-steatosis

206 pient; and (4) low-steatosis graft in normal-BMI recipient.

207 ecipient; (3) high-steatosis graft in normal-BMI recipient; and (4) low-steatosis graft in normal-BMI

208 Thus, interventions aiming at normalizing BMI in girls with high values may be warranted to help p

209 Whether or not BMI is a modifier of this pathway needs to be investigat

210 This study was conducted in 33 obese (BMI > 38.3) healthy male subjects aged 25 to 50 years un

211 in Sub-Saharan Africa, and 12.6% were obese (BMI > = 30 kg/m(2)).

212 Obesity (BMI > 30 kg/m2) was more prevalent in the class Diet (41

213 Obesity (BMI > 30) was significantly associated with cortical and

214 9), overweight (BMI = 25-29.9), and obesity (BMI >= 30)-and 3 WL categories-<5% (minimal), 5% to <10%

215 ain Results: Subjects with ARDS and obesity (BMI=57+/-12 kg/m(2)), following LRM, required an increas

216 ody mass index (BMI) as a marker of obesity (BMI > 30 kg/m(2)).

217 (HRs) associated with postdiagnosis obesity (BMI >= 30 kg/m(2)) compared with healthy weight (BMI 18.

218 Seventy-one individuals with obesity (BMI: 34.6 +/- 3.4 kg/m2; age: 45.4 +/- 8.2 y; 33 men) en

219 The MR analyses showed causal association of BMI on these 3 inflammatory biomarkers.

220 0.05 for each), such that the association of BMI with death or mechanical ventilation was strongest i

221 For the association of BMI with MSI CRC, we observed effect modification by sex

222 aimed to evaluate the causal association of BMI with risk of and mortality from BSI.

223 We examined associations of BMI and other clinical and genetic factors with glycemic

224 l-cause mortality according to categories of BMI and CAC.

225 after adjusting for genetic determinants of BMI.

226 of vitamin D in mediating a causal effect of BMI on inflammatory biomarkers [soluble intercellular ad

227 We examined effects of BMI using survival models and tested interactions with r

228 progression was associated with extremes of BMI and high HbA1c.

229 ded to definitively understand the impact of BMI on epigenetic aging in sperm.

230 onclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables

231 red with control (CON) women, independent of BMI.

232 of 9,115 adults with paired measurements of BMI and lung function taken at >=3 visits were selected

233 The proportions of BMI-defined obesity in this cohort were underweight (13.

234 T2D cases and 485 controls (pair-matched on BMI, age, and race/ethnicity) to discover metabolites as

235 ion) for parity, but not for maternal age or BMI.

236 Residuals of WC over BMI showed positive associations when adjusted for BMI (

237 normal weight (BMI = 22.5-24.9), overweight (BMI = 25-29.9), and obesity (BMI >= 30)-and 3 WL categor

238 Maternal and paternal BMI (standard deviation (SD) units) had a strong associa

239 or gestational age and maternal and paternal BMIs.

240 Overweight/obese patients (BMI > 25) did not show a significant difference in (p =

241 ession model showed that non-obese patients (BMI < 30 kg/m(2)) were at significantly reduced risk for

242 er (beta: 0.22 E%; 95% CI: 0.06, 0.38 E% per BMI standard deviation score).

243 models were performed to estimate percentage BMI decrease depending on the dietary macronutrient comp

244 74958 methylation with metabolic phenotypes (BMI, triglyceride, glucose) and diseases in all 3 popula

245 icipants of different occupational position, BMI, physical activity level, and smoking habit, as well

246 Postdiagnosis BMI was obtained from the first survey completed 1 to <

247 PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0.057] per SD; P = 5.84 x 10-8)

248 race/ethnicity, and of normal pre-pregnancy BMI (median BMI: 23.5 kg/m2).

249 re mainly mediated by maternal pre-pregnancy BMI (mediation effect: 64%; P value = 0.001).

250 birth, but the risk varied by pre-pregnancy BMI and maternal age.

251 Mean preoperative BMI was 44.8 kg/m and 75.7% had noninsulin dependent dia

252 city, parity, education levels, prepregnancy BMI, previous history of preterm birth, marital status,

253 he association between maternal prepregnancy BMI and HMO composition was assessed.

254 mediate the impact of maternal prepregnancy BMI on childhood obesity, which warrants further investi

255 n a model adjusted for maternal prepregnancy BMI, mode of delivery, birthweight z score, sex, and tim

256 ecruited across the spectrum of prepregnancy BMI.

257 In the multiple logistic regressions, BMI >=27.0 kg/m(2) , WC >=90.0 cm and WHtR >=0.50 were a

258 tic regression models adjusted for age, sex, BMI, smoking status, and hypertension.

259 competing risks regression adjusted for sex, BMI, and MELDNa.

260 Significant BMI by age interactions were seen for all primary end po

261 e, sex, ethnicity, education level, smoking, BMI, and diabetes.

262 7.89) was found for severely obese subjects (BMI >=35 kg/m(2)), as compared with BMI 20 to <22.5.

263 enic score (BMIGPS) was generated by summing BMI-increasing risk alleles across the genome.

264 ined more of the variance in age at PHV than BMI in both the old cohort and the recent cohort (combin

265 associated with pancreatic cancer risk than BMI at older ages, and they underscore the importance of

266 Given that BMI measurements and urine analyses are non-invasive, ou

267 These results suggest that BMI before age 50 years is more strongly associated with

268 Obesity was classified by the BMI-for-age based on the WHO growth charts.

269 mated hazard ratios (HR) of EOS according to BMI using proportional hazard models, and identified pot

270 ferential response to docetaxel according to BMI, which calls for a body composition-based re-evaluat

271 r any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific.

272 t-to-height ratio (WHtR) but were similar to BMI and WC.

273 MI) and fat mass index (FMI) are superior to BMI and fat percentage in evaluating nutritional status.

274 er interaction was assessed among treatment, BMI, and estrogen receptor (ER) status.

275 and considered 4 BMI categories-underweight (BMI < 22.5), normal weight (BMI = 22.5-24.9), overweight

276 Adiposity was assessed using BMI z-score (zBMI).

277 >= 30 kg/m(2)) compared with healthy weight (BMI 18.5 to < 25.0 kg/m(2)) were 1.28 for PCSM (95% CI,

278 ies-underweight (BMI < 22.5), normal weight (BMI = 22.5-24.9), overweight (BMI = 25-29.9), and obesit

279 s in the mean changes in HbA1c, body weight, BMI, body composition or lipid parameters, or BP between

280 rimary outcomes were changes in body weight, BMI, waist circumference (WC), waist-to-height ratio (Wt

281 redict WCI in 5594 NHANES participants whose BMI was within the normal weight range.

282 increased risks were observed in women whose BMI normalized from childhood to adulthood: RR was 2.04

283 west 6(th) percentile of the population-wide BMI spectrum) in a uniquely phenotyped Estonian cohort.

284 ulation and is independently associated with BMI and diabetes.

285 children, VDD was positively associated with BMI-for-age Z >1 and maternal education.

286 mortality showed a J-shaped association with BMI, with the lowest mortality risks at 22.5 kg/m(2) for

287 ubjects (BMI >=35 kg/m(2)), as compared with BMI 20 to <22.5.

288 Leptin was positively correlated with BMI (Spearman's rho was 0.6 in women, 0.7 in men).

289 ned the associations of infancy 25(OH)D with BMI-for-age z-score (BMIZ) at ages 5, 10, and 16/17 y; w

290 ed healthy 609 adults (18-50 years old) with BMI 28-40 kg/m(2), to evaluate associations between circ

291 iated with healthy birthweight in women with BMI >=25.

292 n = 12) without diabetes, aged 18-60 y, with BMI 20.0-30.0 kg/m2 who were unrestrained eaters partici

293 using only the present data with and without BMI as a feature.

294 Forty-one overweight men and women (BMI: 27-35 kg/m2; aged 40-70 y) completed the study.

295 A total of 171 overweight women [BMI (kg/m2): 28.3 +/- 1.3; age: 35.2 +/- 6.3 y; 88 white

296 20 in study 2 (mean +/- SD age: 23 +/- 3 y; BMI: 23 +/- 2) participated in a 2 x 2 randomized trial.

297 nts in study 1 [mean +/- SD age: 24 +/- 4 y; BMI (in kg/m2): 22 +/- 2] and 20 in study 2 (mean +/- SD

298 Mean age was 57.2 +/- 12.6 years, BMI 33.7 +/- 11.4 kg/m, defect size 210.0 +/- 221.4 cm;

299 lve healthy adults (age: 26.3 +/- 3.4 years; BMI: 21.9 +/- 1.7 kg/m(2); 5 females) participated in a

300 for a four-person male crew (age: 40-years; BMI: 26.5-kg/m(2); resting VO(2) and VO(2max): 3.3- and