ライフサイエンスコーパス: BMI

1 BMI at birth was inversely associated with HT; c-BMI fro

2 BMI over 25 kg/m(2), diabetes, past and current smoking,

3 BMI was classified according to clinical cutoffs.Data fr

4 BMI was inversely correlated with the extent of emphysem

5 l, 0.32-0.54] kg/m(2) per A-allele, P<0.001; BMI gene score: 1.05 [95% confidence interval, 0.90-1.20

6 tio, 1.07 [1.02-1.11] per A-allele, P=0.004; BMI gene score, hazard ratio, 1.11 [1.05-1.18] per 1-U i

7 79 (0.58) at 1 year, an improvement of -0.09 BMI z score units (95% CI, -0.13 to -0.05).

8 osure to p,p'-DDE and BMI z-score (beta=0.13 BMI z-score (95% CI: 0.01, 0.25) per log increase of p,p

9 ; nonalcoholic steatohepatitis etiology 24%; BMI 33.3 +/- 3.2 kg/m(2) ; Child A 92%; HVPG >/=10 mm Hg

10 Child weight loss after 6 months was -0.25 BMI z scores in both PBT and FBT.

11 dult BMI (beta = 0.64 (standard error, 0.26) BMI units).

12 1:1 ratio to 1 of 2 groups within each of 3 BMI percentiles: 50th to <70th, 70th to <85th, and 85th

13 bjects were healthy weight [5th through 70th BMI percentiles for age (percentile)], and 50% of subjec

14 score difference: 0.37; 95% CI: 0.04, 0.71; BMI z score difference: 0.35; 95% CI: 0, 0.69), with no

15 [0.42-0.50]; specificity, 0.91 [0.89-0.92]), BMI (performance, 0.22; sensitivity, 0.75 [0.73-0.77]; s

16 e, 46.9 [11.3] years; 16.6% male) achieved a BMI of less than 30 at 1 year after bariatric surgery.

17 To identify predictors for achieving a BMI of less than 30 after bariatric surgery.

18 eight-related morbidity and mortality with a BMI above this threshold.

19 hospital costs were lowest for women with a BMI of 20.0 kg/m(2) to less than 22.5 kg/m(2) ( pound567

20 ildhood SEP was associated with higher adult BMI in both genders, and differences were typically larg

21 was independently related to a higher adult BMI in daughters, particularly for the highest 90th quan

22 nd adulthood is associated with higher adult BMI, but how these associations have changed across time

23 ive policies to reduce inequalities in adult BMI that tackle inequality with respect to both childhoo

24 larly for the highest 90th quantile of adult BMI (beta = 0.64 (standard error, 0.26) BMI units).

25 ize, and childhood growth factors with adult BMI in daughters at midlife using quantile, linear, and

26 fasting insulin (0.00%, -0.06 to 0.07), and BMI (0.11 kg/m(2), -0.09 to 0.30).

27 risk of adult obesity increased with age and BMI, from 1.17 (95% UI, 1.09 to 1.29) for overweight 2-y

28 , previous use of long-term oxygen, age, and BMI.

29 Twelve adults with T2DM and 11 age- and BMI-matched control participants without diabetes underw

30 , healthy non-NAFLD controls (normal ALT and BMI), or indeterminate.

31 ple, we evaluated the association of BMI and BMI change at different ages with ALS risk using uncondi

32 child weight loss (body mass index [BMI] and BMI z score) at 6, 12, and 18 months post treatment.

33 correlations only between beta-carotene and BMI (-0.27), WC (-0.30), and HDL cholesterol (0.31) afte

34 dex (BMI), according to age, sex, cause, and BMI in 195 countries between 1990 and 2015.

35 in HbA1c, triglycerides, HDL cholesterol and BMI in a mixed effects longitudinal analysis model.

36 akly associated with waist circumference and BMI, mostly among women.

37 ationship between H. pylori colonization and BMI/obesity.

38 ssociations between exposure to p,p'-DDE and BMI z-score (beta=0.13 BMI z-score (95% CI: 0.01, 0.25)

39 Baseline HRQoL, depression and BMI should be systematically assessed before starting th

40 e health and suggest that race/ethnicity and BMI play an important role in pregnancy bone health.

41 Results indicate socioeconomic factors and BMI are strong predictors of serum PBDE levels among you

42 odified the relation between the BMI-GRS and BMI among men (EDEN: P-interaction = 0.0001; Fenland: P-

43 , physical and mental health, medication and BMI outcome measures.

44 y relevant association between H. pylori and BMI/obesity.

45 ion between H. pylori genetic risk score and BMI/obesity, nor between BMI or obesity genetic risk sco

46 , and a negative association between t50 and BMI was observed between BMI 12 and 25 kg/m(2) (p = 0.00

47 ely; P < 0.01) but gained more in weight and BMI through 7 mo of age (weight z score difference: 0.37

48 2.8 years), weight (2.8 to 14.5 years), and BMI (2.8 to 8.5 years) compared with the control arm.

49 at 10/11 y) and adulthood (42/43 years), and BMI repeatedly across adulthood, spanning 1966 to 2012.

50 y feeding did not result in more appropriate BMI than traditional spoon-feeding, although children we

51 es of mothers in BMI categories were 2.4% at BMI less than 18.5 (underweight), 61.8% at BMI of 18.5 t

52 BMI of 30 to 34.9 (obesity grade 1), 2.4% at BMI of 35 to 39.9 (obesity grade 2), and 0.8% at BMI 40

53 of 35 to 39.9 (obesity grade 2), and 0.8% at BMI 40 or greater (obesity grade 3).

54 t BMI less than 18.5 (underweight), 61.8% at BMI of 18.5 to 24.9 (normal weight), 24.8% at BMI of 25

55 MI of 18.5 to 24.9 (normal weight), 24.8% at BMI of 25 to 29.9 (overweight), 7.8% at BMI of 30 to 34.

56 % at BMI of 25 to 29.9 (overweight), 7.8% at BMI of 30 to 34.9 (obesity grade 1), 2.4% at BMI of 35 t

57 Average BMI at surgery was 13.83 (SD 1.49) and 14 (88%) of the 1

58 ll ages from 7 to 13 years, an above-average BMI z score was positively associated with early ischemi

59 Among children with above-average BMI z scores at age 7 years, a score increase of 0.5 fro

60 We found that high baseline BMI was associated with a significantly slower rate of f

61 sal hazard ratio for the association between BMI and AF.

62 to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and

63 Significant correlations between BMI and unsaturated fatty acids in intramyocellular lipi

64 etic risk score and BMI/obesity, nor between BMI or obesity genetic risk scores and H. pylori positiv

65 ion between t50 and BMI was observed between BMI 12 and 25 kg/m(2) (p = 0.007).

66 positive dose-response relationship between BMI and current asthma was observed (odds ratios were 0.

67 or excess weight (eg, body mass index [BMI]; BMI z score, measuring the number of standard deviations

68 ither positively or negatively influenced by BMI.

69 at birth was inversely associated with HT; c-BMI from school age to adulthood and c-height from birth

70 nical-community interventions improved child BMI z score and health-related quality of life, as well

71 childhood obesity and improvements in child BMI.

72 k characteristics and higher early childhood BMI.

73 The claimed BMI-defined overweight risk paradox may result in part f

74 ording to WHO recommendations, we classified BMI into categories of healthy (20.0-24.9 kg/m(2)), over

75 n at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with

76 the highest and lowest fifths were compared, BMI (HR = 1.35, 95%CI: 1.13-1.61; Ptrend < 0.0001), wais

77 s index (BMI) were based on SSB consumption, BMI from the Australian Health Survey 2011-12, and energ

78 obesity, defined as donor body mass index (D-BMI) of 30 kg/m or greater, has been associated with inc

79 ransplant centers establish a threshold of D-BMI of 30 kg/m to decline donor offers for pancreas tran

80 Associations of D-BMI with pancreas and kidney allograft failure were asse

81 Compared with D-BMI 20 to 25 kg/m, only D-BMI 35 to 50 kg/m was associated with significantly high

82 Compared with D-BMI 20 to 25 kg/m, only D-BMI 35 to 50 kg/m was associat

83 A decreasing BMI from early to middle age and a low BMI in middle age

84 howed increasing levels of FG and decreasing BMI (p < 0.001).

85 plasma from 259 Caucasian women at delivery (BMI 18-55 kg/m(2)).

86 did not modify the effect of post-diagnosis BMI or WHR on the outcomes.

87 association was observed for post-diagnosis BMI or WHR with late recurrence; a U-shaped association

88 creased as grip strength reduced within each BMI category.

89 he prevalence and disease burden of elevated BMI highlights the need for continued focus on surveilla

90 We sought to extend BMI lifetime by developing an algorithmic technique, imp

91 Among females, BMI development differed between children with and witho

92 erval (CI), 0.52-0.75] after controlling for BMI and other risk factors.

93 Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have

94 level of 0.05, 287 loci were identified for BMI and 75 loci for T2D, 23 of which for both traits.

95 The dose-response relationship for BMI with HFpEF risk was also more consistent than with H

96 ypic scores and polygenic profile scores for BMI, HDL cholesterol, low-density lipoprotein cholestero

97 enetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on dis

98 By extending functional BMI lifetime, this approach increases the clinical viabi

99 espectively, versus the normal-weight group (BMI 20.0-24.9)).

100 gnificantly greater than that of insulin --> BMI (beta = -0.023, p = 0.207) in childhood, with p < 0.

101 =1604; mean age, 61+/-12 years; 75% men) had BMI measured on admission, and 2-dimensional transthorac

102 nd web-response system, stratified by HbA1c, BMI, region, and estimated glomerular filtration rate.

103 Age, duration of diabetes, HbA1c, BMI, BCVA, and CST had no impact on the ability to achie

104 cases are attributable to diabetes and high BMI.

105 follow-up were also associated with a higher BMI at age 18 years.

106 py), lower RMR (beta = -31 kcal/day), higher BMI (beta = +0.6 kg/m(2)), and higher PFAT (beta = +0.9%

107 confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95%

108 oprotein cholesterol in men, and with higher BMI and white blood cell count in women (differences 0.0

109 cts on PD in a manner consistent with higher BMI leading to lower risk of PD.

110 that work stress was associated with higher BMI, waist circumference, waist-hip ratio, alanine trans

111 en with and without asthma, with the highest BMI being seen among females with persistent asthma.

112 .8% in general cognitive ability and 5.4% in BMI in an independent test set, predicting 1.1%, 1.1%, a

113 es to invoke clinically meaningful change in BMI among adult patients with diabetes.

114 18-21 years, BMI at baseline, and change in BMI differed according to genetic risk based on lifetime

115 The primary outcome measure was change in BMI over 5 years.

116 -0.7 to 1.6) at extension week 96; change in BMI was 0.69 (0.56 to 0.81) at extension week 72 and 0.9

117 Changes in BMI between baseline and 12 weeks follow-up were assesse

118 Every 2 kg/m(2) increase in BMI above 20 kg/m(2) was associated with a 7.4% (7.1-7.6

119 The percentages of mothers in BMI categories were 2.4% at BMI less than 18.5 (underwei

120 cant center-level heterogeneity was noted in BMI of accepted donors; the MOR varied from 1.10 for ove

121 t than with HFrEF risk, such that increasing BMI above the normal range (>/=25 kg/m(2)) was associate

122 ugh these studies have shown that increasing BMI is associated with larger increases in body fat cont

123 sults support the conclusion that increasing BMI is causally related to higher prevalence of asthma a

124 sitive effect on lifespan whereas increasing BMI negatively affects lifespan.

125 .4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m(2)).

126 predictive of having a high body mass index (BMI) and being obese.

127 associated with children's body mass index (BMI) and detailed measures of body composition.

128 sociations between maternal body mass index (BMI) and offspring systemic cardio-metabolic profile are

129 ubstances (PFAS) may affect body mass index (BMI) and other components of cardiometabolic (CM) risk d

130 ons between early pregnancy body mass index (BMI) and rates of cerebral palsy by gestational age and

131 obesity (GPRS-obesity) with body mass index (BMI) and waist circumference (WC) was modified by sleep

132 opometric indices including body mass index (BMI) and waist circumference (WC) were used to determine

133 nation Survey, we regressed body mass index (BMI) and waist-to-height ratios on urinary arsenic conce

134 Diabetes and high body-mass index (BMI) are associated with increased risk of several cance

135 activity (LTPA) and higher body mass index (BMI) are independently associated with risk of heart fai

136 Results were similar using body mass index (BMI) as an anthropometric indicator of nutritional statu

137 were identified as having a body mass index (BMI) at or above the 85th percentile and 2 or more risk

138 ch 31, 2011, in relation to body-mass index (BMI) at recruitment, overall and for categories of healt

139 may be associated with low body mass index (BMI) at the time of diagnosis.

140 Further adjustment for body mass index (BMI) attenuated these associations but remained signific

141 and CDKAL1) overestimated (body mass index (BMI) decreasing) and one (near MTNR1B) underestimated (B

142 in blood pressure (BP) and body mass index (BMI) during childhood and adolescence are sentinels for

143 e frequently and at a lower body mass index (BMI) in Asians than in European populations, the mechani

144 High body mass index (BMI) is an important contributor to the global burden of

145 Body mass index (BMI) is used to diagnose obesity in adolescents worldwid

146 1 (1.7) years and mean (SD) body mass index (BMI) of 30.2 (3.5) kg/m(2) in obese and 19.4 (2.2) kg/m(

147 nsplant in individuals with body mass index (BMI) of 40 kg/m or greater.

148 n increases with increasing body mass index (BMI) on recommended calcium intakes.

149 the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese.

150 The total mean body mass index (BMI) was 24.7 +/- 4.2 kg/m(2).

151 estionnaire, and children's body mass index (BMI) was measured.

152 Changes in body mass index (BMI) were based on SSB consumption, BMI from the Austral

153 n association analyses with body mass index (BMI) were evaluated in the 100 subjects and another inde

154 Paternal age or body mass index (BMI) were not associated with NAFLD in female offspring.

155 re strongly associated than body mass index (BMI) with childhood asthma.

156 examine the association of body mass index (BMI) with FPM/SPM emergence in a representative sample o

157 etermine the association of body mass index (BMI) with mortality and functional outcome in patients w

158 Lower body-mass index (BMI) z-score and household smoking were strong predictor

159 ip ratio (WHR) adjusted for body mass index (BMI), a measure of abdominal adiposity, with type 2 diab

160 of disease related to high body-mass index (BMI), according to age, sex, cause, and BMI in 195 count

161 d 6 months included weight, body mass index (BMI), body composition, muscle strength, cytokines, comp

162 ified between tiredness and body mass index (BMI), C-reactive protein, high-density lipoprotein (HDL)

163 , reported smoking history, body mass index (BMI), diabetes, HIV, and all other resistance mutations.

164 ve identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology.

165 The secondary outcomes were body-mass index (BMI), mood, anxiety, affective regulation, and anorexia

166 able fractions for smoking, body-mass index (BMI), physical activity, alcohol intake, type 2 diabetes

167 e statistical analyses were body mass index (BMI), waist circumference (WC), serum adipokines, cytoki

168 h hypertension, and between body mass index (BMI), waist circumference (WC), waist-to-height ratio (W

169 food craving and changes in body mass index (BMI).

170 ing by healthy lifestyle or body mass index (BMI).

171 g food insecurity to a high body mass index (BMI).

172 al homocysteine, and higher body mass index (BMI)] and greater odds of large-vessel cerebral vascular

173 Body mass index (BMI, calculated as weight in kilograms divided by height

174 Achieving a body mass index (BMI, calculated as weight in kilograms divided by height

175 re obesity was defined as a body-mass index (BMI, the weight in kilograms divided by the square of th

176 de association to show that body mass index (BMI; a key measure of adiposity) is associated with wide

177 2) for groups with baseline body mass index (BMI; in kg/m(2)) >/=30 and <30, respectively.These findi

178 analysis of variance.Three body mass index (BMI; in kg/m(2)) trajectory patterns were identified and

179 hemoglobin (HbA1c), weight, body mass index (BMI; in kg/m(2)), and LDL cholesterol.

180 lated to weight management [body mass index (BMI; in kg/m(2)), body weight, percentage of body fat, a

181 osity indicators, including body mass index (BMI; in kg/m(2)).

182 re thin at 1 wk postpartum [body mass index (BMI; in kg/m(2)): 22.9 +/- 2.9].

183 ean +/- SD age: 25 +/- 6 y; body mass index (BMI; in kg/m(2)): 23 +/- 2].

184 r groups, being overweight [body mass index (BMI; in kg/m(2)): 25 to <30] is reportedly associated wi

185 tions of breast cancer with body mass index (BMI; weight (kg)/height (m)2) at age 18-21 years, BMI at

186 ing" for height, weight, or body mass index (BMI; weight (kg)/height (m)2) measured concurrently with

187 borhood characteristics and body mass index (BMI; weight (kg)/height (m)2) were assessed from 2000 to

188 on of maternal prepregnancy body mass index (BMI; weight (kg)/height (m)2), gestational weight gain (

189 women or >/= 31 for men and body mass index [BMI] > 25 kg/m(2) ), healthy non-NAFLD controls (normal

190 sure was child weight loss (body mass index [BMI] and BMI z score) at 6, 12, and 18 months post treat

191 ith obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin).

192 ciations between body size (body mass index [BMI], height, waist circumference, and waist-to-hip rati

193 eight or excess weight (eg, body mass index [BMI]; BMI z score, measuring the number of standard devi

194 akes are associated with unfavorable infancy BMI peak characteristics and higher early childhood BMI.

195 R, we found that variants known to influence BMI had effects on PD in a manner consistent with higher

196 Subjects in North America had higher initial BMIs than those of subjects in Eastern Asia.

197 llow-up studies are warranted to investigate BMI changes over time.

198 Fixed-effects models with a 1-year-lagged BMI were estimated.

199 Secondary outcomes were parent weight loss (BMI), child and parent energy intake, child and parent p

200 asing BMI from early to middle age and a low BMI in middle age may be positively associated with ALS

201 The predictors of MAC-PP are low BMI, NB pattern, and high AFS grade; if these risk facto

202 altered in RRMS patients, especially in low-BMI patients, which may contribute to disease progressio

203 Lower BMI in preclinical MCs was significantly associated with

204 e in HbA1c, a 0.55 (95% CI: 0.02, 1.1) lower BMI, a 2.1-kg (95% CI: 1.2-, 2.9-kg) lower weight, and a

205 m those of type 2 diabetes: they had a lower BMI (27.4 kg/m(2) [95% CI 26.7-28.0] vs 32.4 kg/m(2) [32

206 d with smaller waist circumference and lower BMI and body fat percentage.

207 actor profile (higher HDL cholesterol, lower BMI, lower C-reactive protein, lower waist circumference

208 Older age, white race, lower BMI, IV drug use, lower baseline CD4, HCV coinfection, p

209 tic capacity to digest starch had the lowest BMI, potentially because larger amounts of undigested st

210 Associations between LTPA, BMI, and risk of overall HF, HFpEF (ejection fraction >/

211 ify dose-response associations between LTPA, BMI, and the risk of different HF subtypes.

212 ated 45% of the association between maternal BMI and rates of cerebral palsy in full-term children wa

213 5%CI -0.11-0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.

214 5% CI 0.19-0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant sco

215 In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/

216 Data on maternal BMI was collected at 15 weeks of gestation, and paternal

217 e association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blo

218 Our findings suggest that maternal BMI-offspring metabolome associations are likely to be l

219 The pattern of excess risk with a maximum BMI above normal weight was maintained across strata def

220 investigate the relationship between maximum BMI over 16 years and subsequent mortality.

221 hundred fifty children (mean BMI, 26.4; mean BMI z score, 2.0; mean age, 10.4 years; 66.4% girls) and

222 The subgroup of studies with a mean BMI >/=30 exhibited substantially greater lean mass (SMD

223 One hundred fifty children (mean BMI, 26.4; mean BMI z score, 2.0; mean age, 10.4 years;

224 The lowest mean BMI was observed in the group of participants with a low

225 4 years; 66.4% girls) and their parent (mean BMI, 31.9; mean age, 42.9 years; 87.3% women; and 31% Hi

226 Approximately, 67% were males with mean BMI 26.5 kg/m.

227 umber of standard deviations from the median BMI for age and sex), cardiometabolic outcomes, quality

228 lly reversed by overexpression of PcG member BMI-1, suggesting opposing roles for PEITC and PcG prote

229 crossover study, twelve normoglycaemic men (BMI 25-35 kg/m(2)) underwent four investigational days,

230 We developed a new BMI that allows arbitrarily fast control and feedback ra

231 little difference in the risk between normal BMI (HR: 3.25; 95% CI: 1.86, 5.65), overweight (HR: 2.50

232 Compared with the reference group (normal BMI and highest handgrip tertile), the risk of all-cause

233 10000 women, compared with women with normal BMI) were 28.8 (95% CI, 12.2-47.2) for underweight women

234 the meta-analyzed estimate between observed BMI and AF (age- and sex-adjusted hazard ratio 1.05 [1.0

235 understand the full genetic architecture of BMI.

236 this sample, we evaluated the association of BMI and BMI change at different ages with ALS risk using

237 years, the cross-lagged path coefficient of BMI --> insulin (beta = 0.326, p < 0.001) was significan

238 iable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y

239 We examined the causal effect of BMI on asthma, hay fever, allergic sensitization, serum

240 weight, without any comparable influence of BMI or BSA.

241 here were fairly similar trends in levels of BMI, waist circumference, and skinfold thicknesses in me

242 need for continued focus on surveillance of BMI and identification, implementation, and evaluation o

243 ime with baseline levels and trajectories of BMI and waist circumference over time using linear mixed

244 NT5A interaction may affect the variation of BMI in Han Chinese population.

245 approach increases the clinical viability of BMIs.

246 triglycerides can amplify the FTO impact on BMI.

247 etween AMY1 copy number and starch intake on BMI (P-interaction = 0.007) and body fat percentage (P-i

248 or >9 h daily, the effect of GPRS-obesity on BMI was stronger (beta: 0.60; 95% CI: 0.54, 0.65 and bet

249 and fasting triglycerides with rs9939609 on BMI (p = 0.0005 and p = 5 x 10(-7), respectively).

250 ditional adjustment for concurrent weight or BMI reversed (i.e., to positive) the SGA-adiposity assoc

251 adjustment for concurrent height, weight, or BMI.

252 Our BMI paradigm can dissect the contribution of different e

253 dy size which rapidly increases as their own BMI increases.

254 ected at 15 weeks of gestation, and paternal BMI was assessed when the child was 18 months old.

255 In contrast, higher paternal BMI (P < 0.001), maternal prepregnancy BMI (P < 0.001),

256 present for maternal compared with paternal BMI across these associations; however, there was no str

257 nal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 x 10-7) methylation variati

258 We found no association between prediagnosis BMI and survival.

259 y correlated with food craving and predicted BMI gains.

260 Early pregnancy BMI.

261 hibit excessive GWG, both high pre-pregnancy BMI and excessive GWG influence perinatal outcomes.

262 ested the associations between pre-pregnancy BMI or GWG and length of gestation, birthweight, length,

263 However, the role of premorbid BMI in the development of ALS and survival after diagnos

264 ernal BMI (P < 0.001), maternal prepregnancy BMI (P < 0.001), and lower family socioeconomic status (

265 evention of SSI in obese women (prepregnancy BMI >/=30) who had received standard intravenous preoper

266 diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rat

267 rend for prebiotic supplementation to reduce BMI z score to a greater extent than placebo (-3.4%; P =

268 increases transplant eligibility by reducing BMI in kidney transplant candidates, but the effect of s

269 We identified novel and previously reported BMI-related differential methylation at 83 CpGs that rep

270 ncy is positively associated with children's BMI during early childhood and particularly with higher

271 Children's BMI, WC, and WHtR were positively associated with their

272 plus coaching group, the adjusted mean (SD) BMI z score was 1.87 (0.56) at baseline and 1.79 (0.58)

273 dard deviation score in body mass index [SDS-BMI]).

274 .A total of 153 participants (means +/- SDs: BMI: 33.3 +/- 4.6; age: 63.8 +/- 6.3 y; 83% women) were

275 One-year changes in age- and sex-specific BMI z score, child health-related quality of life measur

276 atified analyses revealed that the strongest BMI signal originated predominantly from females (chr.

277 t correlate highly with sweat chloride test, BMI, and FEV1% predicted values.

278 olescents as overweight more accurately than BMI z scores and equally as well as updated BMI percenti

279 restraint modified the relation between the BMI-GRS and BMI among men (EDEN: P-interaction = 0.0001;

280 1.42), and 1.87 (95% CI: 1.60, 2.18) for the BMI groups <20.0, 25.0-29.9, and >/=30.0, respectively,

281 However, the BMI curves begun to diverge already at 17.8 years before

282 s system to concurrently learn operating the BMI while exploiting the possibility to adapt the availa

283 to a final model explaining FLI best through BMI, waist circumference, and the Lac:Man ratio.

284 % CI -0.1-0.48), but was unlikely related to BMI although the estimate lacked precision.

285 between arsenic concentration in relation to BMI and waist-to-height ratio.

286 ariants across eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL choleste

287 asing) and one (near MTNR1B) underestimated (BMI increasing) associations among 11 type 2 diabetes ri

288 Obesity and underweight BMI were associated with increased risk of composite adv

289 BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either b

290 risk of mortality than being normal weight (BMI: 18.5 to <25).

291 struments were significantly associated with BMI (FTO: 0.43 [95% confidence interval, 0.32-0.54] kg/m

292 s2072920 and rs11918967, was associated with BMI after multiple testing corrections (combined P = 2.2

293 roach to discover novel loci associated with BMI and T2D by incorporating the summary statistics from

294 gle-nucleotide polymorphisms associated with BMI from previous genome-wide association studies was co

295 e 2 diabetes alleles will be associated with BMI in sample sizes of >500 000 if the prevalence of tho

296 erfiltering patients and was associated with BMI, waist circumference, blood pressure, heart rate, Hb

297 replaced diabetes and total cholesterol with BMI.

298 also evaluated the association of SNPs with BMI related factors such as sleep duration and quality,

299 Participants were randomly assigned within BMI categories to receive an 18-mo dairy intervention (3

300 weight (kg)/height (m)2) at age 18-21 years, BMI at baseline, and change in BMI differed according to

301 (as a proxy for cognitive ability in youth), BMI, height, systolic blood pressure, coronary artery di