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1. Smoking during pregnancy is associated with child overweight independent of maternal pre-pregnancy BMI and genetic predisposition to adiposity.

Author: Schnurr TM, Ängquist L, Nøhr EA, Hansen T, Sørensen TIA, and Morgen CS
Subjects: Adolescent, Adult, Child, Child, Preschool, Female, Follow-Up Studies, Genome-Wide Association Study, Humans, Infant, Infant, Newborn, Male, Pregnancy, Retrospective Studies, Body Mass Index, Genetic Predisposition to Disease, Overweight genetics, Prenatal Exposure Delayed Effects genetics, Smoking adverse effects, Smoking genetics
Abstract: High maternal body mass index (BMI) and smoking during pregnancy are risk factors for child overweight. Maternal smoking tends to reduce her BMI and the association of smoking with child overweight may be confounded by or interacting with maternal genetic predisposition to adiposity. In the Danish National Birth Cohort, we investigated whether smoking during pregnancy is associated with child BMI/overweight independent of pre-pregnancy BMI and maternal genetic predisposition to adiposity estimated as total, transmitted and non-transmitted genetic risk scores (GRSs) based on 941 common genetic variants associated with BMI. Smoking during pregnancy was associated with higher child BMI and higher odds of child overweight in a dose-response relationship. The odds ratio (95% CI) for smoking 11 + cigarettes in third trimester versus no smoking was 2.42 (1.30; 4.50), irrespective of maternal BMI and maternal GRSs (total, transmitted or non-transmitted). There were no statistically significant interactions between maternal GRSs and smoking (all p-values for interactions > 0.05). In conclusion, in this study, smoking during pregnancy exhibits a dose-response association with increased child BMI/overweight, independent of maternal pre-pregnancy BMI, maternal transmitted, and non-transmitted genetic predisposition to adiposity. Avoidance of smoking during pregnancy may help prevent childhood obesity irrespective of the mother-child genetic predisposition., (© 2022. The Author(s).)
Published: 2022
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2. Instrumental variable analysis using offspring BMI in childhood as an indicator of parental BMI in relation to mortality.

Author: Blond K, Carslake D, Gjærde LK, Vistisen D, Sørensen TIA, Smith GD, and Baker JL
Subjects: Adolescent, Adult, Aged, Body Height, Cardiovascular Diseases pathology, Child, Female, Follow-Up Studies, Humans, Infant, Newborn, Male, Middle Aged, Neoplasms pathology, Prognosis, Risk Factors, Survival Rate, Body Mass Index, Cardiovascular Diseases mortality, Mortality trends, Neoplasms mortality, Parents
Abstract: Childhood BMI shows associations with adult mortality, but these may be influenced by effects of ill health in childhood on BMI and later mortality. To avoid this, we used offspring childhood BMI as an instrumental variable (IV) for own BMI in relation to mortality and compared it with conventional associations of own childhood BMI and own mortality. We included 36,097 parent-offspring pairs with measured heights and weights from the Copenhagen School Health Records Register and register-based information on death. Hazard ratios (HR) were estimated using adjusted Cox regression models. For all-cause mortality, per zBMI at age 7 the conventional HR = 1.07 (95%CI: 1.04-1.09) in women and 1.02 (95%CI: 0.92-1.14) in men, whereas the IV HR = 1.23 (95%CI: 1.15-1.32) in women and 1.05 (95%CI: 0.94-1.17) in men. Per zBMI at age 13, the conventional HR = 1.11 (95%CI: 1.08-1.15) in women and 1.03 (95%CI: 0.99-1.06) in men, whereas the IV HR = 1.30 (95%CI: 1.19-1.42) in women and 1.15 (95%CI: 1.04-1.29) in men. Only conventional models showed indications of J-shaped associations. Our IV analyses suggest that there is a causal relationship between BMI and mortality that is positive at both high and low BMI values., (© 2021. The Author(s).)
Published: 2021
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3. Two genetic analyses to elucidate causality between body mass index and personality.

Author: Arumäe K, Briley D, Colodro-Conde L, Mortensen EL, Jang K, Ando J, Kandler C, Sørensen TIA, Dagher A, Mõttus R, and Vainik U
Subjects: Biological Specimen Banks statistics & numerical data, Causality, Correlation of Data, Estonia, Genetic Testing instrumentation, Genetic Testing methods, Genetic Testing statistics & numerical data, Humans, Mendelian Randomization Analysis, Personality Tests statistics & numerical data, Body Mass Index, Personality classification
Abstract: Background/objectives: Many personality traits correlate with BMI, but the existence and direction of causal links between them are unclear. If personality influences BMI, knowing this causal direction could inform weight management strategies. Knowing that BMI instead influences personality would contribute to a better understanding of the mechanisms of personality development and the possible psychological effects of weight change. We tested the existence and direction of causal links between BMI and personality., Subjects/methods: We employed two genetically informed methods. In Mendelian randomization, allele scores were calculated to summarize genetic propensity for the personality traits neuroticism, worry, and depressive affect and used to predict BMI in an independent sample (N = 3 541). Similarly, an allele score for BMI was used to predict eating-specific and domain-general phenotypic personality scores (PPSs; aggregate scores of personality traits weighted by BMI). In a direction of causation (DoC) analysis, twin data from five countries (N = 5424) were used to assess the fit of four alternative models: PPSs influencing BMI, BMI influencing PPSs, reciprocal causation, and no causation., Results: In Mendelian randomization, the allele score for BMI predicted domain-general (β = 0.05; 95% CI: 0.02, 0.08; P = 0.003) and eating-specific PPS (β = 0.06; 95% CI: 0.03, 0.09; P < 0.001). The allele score for worry also predicted BMI (β = -0.05; 95% CI: -0.08, -0.02; P < 0.001), while those for neuroticism and depressive affect did not (P ≥ 0.459). In DoC, BMI similarly predicted domain-general (β = 0.21; 95% CI:, 0.18, 0.24; P < 0.001) and eating-specific personality traits (β = 0.19; 95% CI:, 0.16, 0.22; P < 0.001), suggesting causality from BMI to personality traits. In exploratory analyses, links between BMI and domain-general personality traits appeared reciprocal for higher-weight individuals (BMI > ~25)., Conclusions: Although both genetic analyses suggested an influence of BMI on personality traits, it is not yet known if weight management interventions could influence personality. Personality traits may influence BMI in turn, but effects in this direction appeared weaker., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2021
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4. Body mass index and height in young adult men in relation to subsequent risk of mood disorder.

Author: Okholm GT, Jørgensen TSH, Rozing MP, Wium-Andersen MK, Wium-Andersen IK, Jørgensen MB, Sørensen TIA, and Osler M
Subjects: Adolescent, Adult, Bipolar Disorder psychology, Body Weight, Cohort Studies, Denmark epidemiology, Depression psychology, Humans, Male, Risk Factors, Young Adult, Bipolar Disorder epidemiology, Body Height, Body Mass Index, Depression epidemiology
Abstract: Adolescence represents an important period in brain and mental development, which raises the question of whether measures of body size at entry into adult life influence the risk of developing mood disorders. We examined the association of BMI and height in a cohort of young men with risk of mood disorders throughout life. The study included 630,807 Danish men born 1939-1959 and 1983-1997 with measures of height and weight at conscription board examinations. Psychiatrist's diagnosis of mood disorders was obtained from national patient registries from 1969 to 2016. The associations of BMI and height with mood disorders were estimated by Cox proportional hazard regression analyses adjusting for education, cognitive ability, migration status drug and alcohol misuse. During a mean follow-up of 26.3 years, 2,608 (0.6%) and 19,690 (3.1%) men were diagnosed with bipolar disorder and depression, respectively. We found an inverse linear association of BMI with risk of bipolar disorder, whereas the association of BMI with depression was curve-linear with a decline in risk until BMI around 25 kg/m 2 , and an almost constant risk across the BMI range above 25 kg/m 2 . Height was not associated with bipolar disorder or depression. Comparison of brothers, assumed to share family factors of possible influence on the risk of mood disorders, showed similar results although with wider confidence intervals. BMI in the lower range at men's entry into adulthood is inversely associated with risk of bipolar disorder and depression throughout adult life, whereas height is not related., (© 2021. Springer Nature B.V.)
Published: 2021
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5. Do genetic risk scores for childhood adiposity operate independent of BMI of their mothers?

Author: Huang LO, Morgen CS, Ängquist L, Nohr EA, Kilpeläinen TO, Hansen T, Sørensen TIA, and Schnurr TM
Subjects: Adult, Child, Cohort Studies, Correlation of Data, Denmark epidemiology, Female, Follow-Up Studies, Genetic Predisposition to Disease epidemiology, Humans, Logistic Models, Male, Mothers statistics & numerical data, Pediatric Obesity epidemiology, Pediatric Obesity physiopathology, Body Mass Index, Mothers classification, Pediatric Obesity diagnosis, Risk Factors
Abstract: Objectives: Genetic predisposition and maternal body mass index (BMI) are risk factors for childhood adiposity, defined by either BMI or overweight. We aimed to investigate whether childhood-specific genetic risk scores (GRSs) for adiposity-related traits are associated with childhood adiposity independent of maternal BMI, or whether the associations are modified by maternal BMI., Methods: We constructed a weighted 26-SNP child BMI-GRS and a weighted 17-SNP child obesity-GRS in overall 1674 genotyped children within the Danish National Birth Cohort. We applied a case-cohort (N = 1261) and exposure-based cohort (N = 912) sampling design. Using logistic regression models we estimated associations of the GRSs and child overweight at age 7 years and examined if the GRSs influence child adiposity independent of maternal BMI (per standard deviation units)., Results: In the case-cohort design analysis, maternal BMI and the child GRSs were associated with increased odds for childhood overweight [OR for maternal BMI: 2.01 (95% CI: 1.86; 2.17), OR for child BMI-GRS: 1.56 (95% CI: 1.47; 1.66), and OR for child obesity-GRS 1.46 (95% CI: 1.37; 1.54)]. Adjustment for maternal BMI did not change the results, and there were no significant interactions between the GRSs and maternal BMI. However, in the exposure-based cohort design analysis, significant interactions between the child GRSs and maternal BMI on child overweight were observed, suggesting 0.85-0.87-fold attenuation on ORs of child overweight at higher values of maternal BMI and child GRS., Conclusion: GRSs for childhood adiposity are strongly associated with childhood adiposity even when adjusted for maternal BMI, suggesting that the child-specific GRSs and maternal BMI contribute to childhood overweight independent of each other. However, high maternal BMI may attenuate the effects of child GRSs in children., (© 2021. The Author(s).)
Published: 2021
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6. Body mass index and height in relation to type 2 diabetes by levels of intelligence and education in a large cohort of Danish men.

Author: Bjerregaard LG, Damborg ML, Osler M, Sørensen TIA, and Baker JL
Subjects: Adolescent, Adult, Aged, Cognition, Cohort Studies, Denmark epidemiology, Diabetes Mellitus, Type 2 epidemiology, Humans, Incidence, Intelligence Tests statistics & numerical data, Male, Middle Aged, Social Class, Young Adult, Body Height, Body Mass Index, Diabetes Mellitus, Type 2 etiology, Educational Status, Intelligence
Abstract: Socioeconomic status (SES) is inversely associated with risks of type 2 diabetes (T2D). We investigated if young men's cognitive function, measured by intelligence test scores and educational level, as determinants of SES modified associations between body mass index (BMI) and height with the risk of T2D. 369 989 young men from the Danish Conscription Database born between 1939 and 1959 with information on measured height, weight, intelligence test scores, and education were linked to the Danish National Patient Register. During follow-up from 1977 through 2015, T2D was recorded in 32 188 men. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated by Cox regressions. BMIs below-average (z-scores ≤ 0) were not related to risks of T2D. For BMIs above-average (z-scores > 0), positive associations between BMI and T2D were slightly stronger among men with higher intelligence test scores or longer educations than among men with lower levels of these factors (p interaction -values < 0.004). Irrespective of BMI, incidence rates of T2D were higher among men with low levels of intelligence test score and education. Height was inversely associated with T2D (per z-score, HR = 0.96 (95% CI 0.95-0.97) and the association did not vary by intelligence test scores or education (all p interaction -values > 0.59). While below-average BMI was not associated with T2D risk, above-average BMIs were and these association were stronger among men with high cognitive function. Nevertheless, T2D risk was higher at lower levels of cognitive function throughout the range of BMI. Height was inversely associated with T2D and it was not modified by cognitive function.
Published: 2020
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7. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies.

Author: Vehmeijer FOL, Küpers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan FI, Melton PE, Nohr E, Escaramís G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergström A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Håberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries JP, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Räikkönen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S, Ullemar V, Verduci E, Vonk JM, Xu CJ, Yang IV, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton CV, Lahti J, Almqvist C, Jarvelin MR, Koletzko B, Vrijheid M, Sørensen TIA, Huang RC, Arshad SH, Nystad W, Melén E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert MF, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, and Felix JF
Subjects: Adolescent, Child, Child, Preschool, CpG Islands, Cross-Sectional Studies, Epigenome, Female, Fetal Blood, Humans, Male, Pediatric Obesity genetics, Pregnancy, Body Mass Index, DNA Methylation, Epigenesis, Genetic, Obesity genetics, Parturition
Abstract: Background: DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits., Methods: We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment., Results: DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10 -7 , with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth P enrichment = 1; childhood P enrichment = 2.00 × 10 -4 ; adolescence P enrichment = 2.10 × 10 -7 )., Conclusions: There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.
Published: 2020
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8. Levels and changes in body mass index decomposed into fat and fat-free mass index: relation to long-term all-cause mortality in the general population.

Author: Sørensen TIA, Frederiksen P, and Heitmann BL
Subjects: Adult, Aged, Body Composition, Denmark, Female, Health Behavior, Humans, Longitudinal Studies, Male, Middle Aged, Proportional Hazards Models, Body Mass Index, Mortality
Abstract: Background: In the general population, body mass index (BMI = weight (kg)/(height (m)) 2 ) shows a U-shaped relation to mortality, which is attributable to a combination of an inverse association with fat-free mass index (FFMI) and a direct association with fat mass index (FMI). However, preceding changes in body composition related to diseases, health behaviors, or social conditions that are also influencing later mortality may confound these associations., Objective: To examine associations of FFMI and FMI, adjusted for preceding changes in FFMI and FMI over a 6 years period, with all-cause mortality in a healthy general population., Methods: The study population was a random subset of adult Danes, participating in the Danish MONICA project; 989 men and 962 women, born 1922, 1932, 1942, and 1952, and examined in 1987-88 and 1993-94. They had no known major co-morbidities until start of follow-up in 1993-94, and were followed up for 18 years. Measures included height, weight, and bio-impedance, from which BMI, FFMI, and FMI were calculated, and information on educational level, smoking, alcohol drinking, leisure-time physical activity, which were obtained by questionnaires. We analyzed the relation between body composition and all-cause mortality by Cox proportional hazards model with splines, stratified by birth cohorts, and with adjustment for preceding changes in body composition and for the covariates including gender. We estimated hazard ratios (HR) with 95% confidence intervals (CI) relative to HR = 1.00 at the median values of BMI, FMI, and FFMI., Results: During 18 years of follow-up, 286 men and 200 women died. BMI showed the well-known U-shaped association with mortality, and FMI was directly and FFMI inversely associated with mortality. Associations were not significantly modified by gender. Preceding changes in BMI, FMI, and FFMI were only weakly and not significantly associated with mortality. Associations for FMI and FFMI were monotonic, but curve-linear with a higher mortality above and below the respective median values of FMI and FFMI: at the 5th percentiles of FMI and FFMI, HRs were 0.80 (CI 0.57-1.13) and 2.01 (1.24-3.27), and at the 95th percentiles, HRs were 2.16 (1.38-3.38) and 0.81 (0.52-1.27), respectively., Conclusions: In an apparently healthy general population, a large fat mass and a small fat-free mass are associated with greater risk of early mortality, also after adjusting for preceding changes in body composition, health behaviors, and educational level.
Published: 2020
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9. Body mass index in young adulthood and risk of subsequent dementia at different levels of intelligence and education in Danish men.

Author: Osler M, Okholm GT, Sørensen TIA, and Jørgensen TSH
Subjects: Adolescent, Adult, Aged, Data Interpretation, Statistical, Denmark epidemiology, Educational Status, Humans, Incidence, Intelligence Tests, Male, Middle Aged, Registries, Risk Factors, Young Adult, Body Mass Index, Body Weight, Dementia epidemiology, Intelligence
Abstract: The risk of dementia seems to be established already early in life, which leads to the question if overweight early in life is an important risk factor for dementia as it appears to be later in life. We examined the association between body mass index (BMI) at entry to adult life and subsequent risk of dementia in men and assessed whether the relationship differed by levels of intelligence and education. The study population consisted of 377,598 Danish men born 1939-1959 with measures of height, weight, intelligence test score (ITS), and educational level (EL) at conscript board examinations around the age of 19 years. Dementia outcomes were obtained from National Patient and Prescription Registries between 1969 and 2016. The association between BMI and dementia was analysed using Cox proportional hazard regression including interactions between BMI and ITS and EL, respectively. During the follow-up through age 77 years, 6144 (1.6%) developed dementia. The frequency was highest in men with lowest BMI, lowest ITS and lowest EL. Young adult BMI below the mean of 21.8 kg/m 2 was inversely associated with subsequent dementia, whereas there was no association with higher levels of BMI. Adjustment for young adult ITS and EL attenuated the risk estimates slightly, and interaction analyses showed that the shape of the association between BMI and dementia was unaffected by the levels of ITS and EL. Regardless of levels of ITS and EL, young adult BMI below the mean is inversely associated with subsequent dementia, whereas there is no association with higher levels of BMI.
Published: 2020
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10. The influence of transmitted and non-transmitted parental BMI-associated alleles on the risk of overweight in childhood.

Author: Schnurr TM, Morgen CS, Borisevich D, Beaumont RN, Engelbrechtsen L, Ängquist L, Have CT, Freathy RM, Smith GD, Nohr EA, Hansen T, and Sørensen TIA
Subjects: Adiposity genetics, Child, Cohort Studies, Female, Gene-Environment Interaction, Humans, Male, Pediatric Obesity etiology, Risk, Alleles, Body Mass Index, Genetic Association Studies, Parents, Pediatric Obesity genetics
Abstract: Overweight in children is strongly associated with parental body mass index (BMI) and overweight. We assessed parental transmitted and non-transmitted genetic contributions to overweight in children from the Danish National Birth Cohort by constructing genetic risk scores (GRSs) from 941 common genetic variants associated with adult BMI and estimating associations of transmitted maternal/paternal and non-transmitted maternal GRS with child overweight. Maternal and paternal BMI (standard deviation (SD) units) had a strong association with childhood overweight [Odds ratio (OR): 2.01 (95% confidence interval (CI) 1.74; 2.34) and 1.64 (95% CI 1.43; 1.89)]. Maternal and paternal transmitted GRSs (SD-units) increased odds for child overweight equally [OR: 1.30 (95% CI 1.16; 1.46) and 1.30 (95% CI 1.16; 1.47)]. However, both the parental phenotypic and the GRS associations may depend on maternal BMI, being weaker among mothers with overweight. Maternal non-transmitted GRS was not associated with child overweight [OR 0.98 (95% CI 0.88; 1.10)] suggesting no specific influence of maternal adiposity as such. In conclusion, parental transmitted GRSs, based on adult BMI, contribute to child overweight, but in overweight mothers other genetic and environmental factors may play a greater role.
Published: 2020
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11. Exposure to traffic noise and gestational weight gain and postpartum weight retention: a cohort study.

Author: Sørensen M, Sørensen TIA, Ketzel M, and Raaschou-Nielsen O
Subjects: Adiposity, Adult, Cohort Studies, Female, Humans, Motor Vehicles, Overweight etiology, Pregnancy, Pregnancy Complications, Pregnancy Trimesters, Railroads, Risk Factors, Weight Loss, Body Mass Index, Environmental Exposure adverse effects, Gestational Weight Gain, Noise, Transportation adverse effects, Obesity etiology, Postpartum Period
Abstract: Objectives: Transportation noise has been associated with markers of obesity. We aimed to investigate whether road traffic and railway noise were associated with weight gain during and after pregnancy., Methods: Among the women participating in the Danish National Birth Cohort, 74 065 reported on weight before and during the pregnancy (gestational week 30) and 52 661 reported on weight before and 18 months after pregnancy. Residential address history from conception to 18 months after pregnancy was obtained in national registers, and road traffic and railway noise were modelled for all addresses. Associations between noise and gestational weight gain (GWG) and postpartum weight retention (PPWR) were analysed using the linear and log-binomial regression., Results: A 10 dB(A) higher road traffic noise was associated with an increase in GWG of 3.8 g/week (95% CI 2.3 to 5.3) and PPWR of 0.09 kg (95% CI 0.02 to 0.16). For PPWR, this association seemed confined to women who were overweight (0.17 kg, 95% CI 0.02 to 0.32) or obese (0.49 kg, 95% CI 0.26 to 0.73) before pregnancy. Further adjustment by nitrogen dioxide reduced GWG risk estimates and slightly increased PPWR risk estimates. Railway noise ≥65 dB(A) was associated with an increase in GWG of 4.5 g/week (95% CI -2.7 to 11.6) and PPWR of 0.26 kg (95% CI -0.09 to 0.60) compared with levels <55 dB(A)., Conclusions: Our findings suggest that road traffic noise is associated with weight gain during and after the pregnancy, which adds to the literature linking transportation noise to adiposity., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2020
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12. The CODATwins Project: The Current Status and Recent Findings of COllaborative Project of Development of Anthropometrical Measures in Twins.

Author: Silventoinen K, Jelenkovic A, Yokoyama Y, Sund R, Sugawara M, Tanaka M, Matsumoto S, Bogl LH, Freitas DL, Maia JA, Hjelmborg JVB, Aaltonen S, Piirtola M, Latvala A, Calais-Ferreira L, Oliveira VC, Ferreira PH, Ji F, Ning F, Pang Z, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Burt SA, Klump KL, Martin NG, Medland SE, Montgomery GW, Kandler C, McAdams TA, Eley TC, Gregory AM, Saudino KJ, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Tarnoki AD, Tarnoki DL, Haworth CMA, Plomin R, Öncel SY, Aliev F, Medda E, Nisticò L, Toccaceli V, Craig JM, Saffery R, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Jeong HU, Spector T, Mangino M, Lachance G, Gatz M, Butler DA, Gao W, Yu C, Li L, Bayasgalan G, Narandalai D, Harden KP, Tucker-Drob EM, Christensen K, Skytthe A, Kyvik KO, Derom CA, Vlietinck RF, Loos RJF, Cozen W, Hwang AE, Mack TM, He M, Ding X, Silberg JL, Maes HH, Cutler TL, Hopper JL, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Baker LA, Tuvblad C, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Ullemar V, Almqvist C, Tan Q, Zhang D, Swan GE, Krasnow R, Jang KL, Knafo-Noam A, Mankuta D, Abramson L, Lichtenstein P, Krueger RF, McGue M, Pahlen S, Tynelius P, Rasmussen F, Duncan GE, Buchwald D, Corley RP, Huibregtse BM, Nelson TL, Whitfield KE, Franz CE, Kremen WS, Lyons MJ, Ooki S, Brandt I, Nilsen TS, Harris JR, Sung J, Park HA, Lee J, Lee SJ, Willemsen G, Bartels M, van Beijsterveldt CEM, Llewellyn CH, Fisher A, Rebato E, Busjahn A, Tomizawa R, Inui F, Watanabe M, Honda C, Sakai N, Hur YM, Sørensen TIA, Boomsma DI, and Kaprio J
Subjects: Adolescent, Adult, Aged, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Socioeconomic Factors, Aging genetics, Body Height genetics, Body Mass Index, Databases, Factual, Gene-Environment Interaction, Twins, Dizygotic genetics
Abstract: The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural-geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
Published: 2019
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13. Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta-analysis of European, North American and Australian cohorts.

Author: Santos S, Voerman E, Amiano P, Barros H, Beilin LJ, Bergström A, Charles MA, Chatzi L, Chevrier C, Chrousos GP, Corpeleijn E, Costa O, Costet N, Crozier S, Devereux G, Doyon M, Eggesbø M, Fantini MP, Farchi S, Forastiere F, Georgiu V, Godfrey KM, Gori D, Grote V, Hanke W, Hertz-Picciotto I, Heude B, Hivert MF, Hryhorczuk D, Huang RC, Inskip H, Karvonen AM, Kenny LC, Koletzko B, Küpers LK, Lagström H, Lehmann I, Magnus P, Majewska R, Mäkelä J, Manios Y, McAuliffe FM, McDonald SW, Mehegan J, Melén E, Mommers M, Morgen CS, Moschonis G, Murray D, Ní Chaoimh C, Nohr EA, Nybo Andersen AM, Oken E, Oostvogels A, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Roeleveld N, Ronfani L, Santos AC, Standl M, Stigum H, Stoltenberg C, Thiering E, Thijs C, Torrent M, Tough SC, Trnovec T, Turner S, van Gelder M, van Rossem L, von Berg A, Vrijheid M, Vrijkotte T, West J, Wijga AH, Wright J, Zvinchuk O, Sørensen T, Lawlor DA, Gaillard R, and Jaddoe V
Subjects: Adult, Australia epidemiology, Birth Weight, Cohort Studies, Europe epidemiology, Female, Gestational Age, Humans, Infant, Newborn, North America epidemiology, Odds Ratio, Pregnancy, Pregnancy Complications epidemiology, Risk Factors, Body Mass Index, Gestational Weight Gain physiology, Overweight complications, Pregnancy Complications etiology
Abstract: Objective: To assess the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact., Design: Individual participant data meta-analysis of 39 cohorts., Setting: Europe, North America, and Oceania., Population: 265 270 births., Methods: Information on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used., Main Outcome Measures: Gestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth., Results: Higher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes, and large for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared with normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (odds ratio 2.51, 95% CI 2.31- 2.74). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large for gestational age infants was attributable to excessive gestational weight gain., Conclusions: Maternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity., Tweetable Abstract: Promoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications., (© 2019 Royal College of Obstetricians and Gynaecologists.)
Published: 2019
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14. Association of Gestational Weight Gain With Adverse Maternal and Infant Outcomes.

Author: Voerman E, Santos S, Inskip H, Amiano P, Barros H, Charles MA, Chatzi L, Chrousos GP, Corpeleijn E, Crozier S, Doyon M, Eggesbø M, Fantini MP, Farchi S, Forastiere F, Georgiu V, Gori D, Hanke W, Hertz-Picciotto I, Heude B, Hivert MF, Hryhorczuk D, Iñiguez C, Karvonen AM, Küpers LK, Lagström H, Lawlor DA, Lehmann I, Magnus P, Majewska R, Mäkelä J, Manios Y, Mommers M, Morgen CS, Moschonis G, Nohr EA, Nybo Andersen AM, Oken E, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Roeleveld N, Ronfani L, Santos AC, Standl M, Stigum H, Stoltenberg C, Thiering E, Thijs C, Torrent M, Trnovec T, van Gelder MMHJ, van Rossem L, von Berg A, Vrijheid M, Wijga A, Zvinchuk O, Sørensen TIA, Godfrey K, Jaddoe VWV, and Gaillard R
Subjects: Adult, Birth Weight, Cesarean Section statistics & numerical data, Diabetes, Gestational, Female, Humans, Hypertension, Pregnancy-Induced, Infant, Newborn, Obesity, Pregnancy, Premature Birth, Body Mass Index, Gestational Weight Gain, Pregnancy Complications, Pregnancy Outcome
Abstract: Importance: Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges., Objectives: To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories., Design, Setting, and Participants: Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015., Exposures: Gestational weight gain., Main Outcomes and Measures: The main outcome termed any adverse outcome was defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth., Results: Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI <18.5); 133 788 (68.0%), normal weight (BMI, 18.5-24.9); 38 828 (19.7%), overweight (BMI, 25.0-29.9); 11 992 (6.1%), obesity grade 1 (BMI, 30.0-34.9); 3284 (1.7%), obesity grade 2 (BMI, 35.0-39.9); and 969 (0.5%), obesity grade 3 (BMI, ≥40.0). Overall, any adverse outcome occurred in 37.2% (n = 73 161) of women, ranging from 34.7% (2706 of 7809) among women categorized as underweight to 61.1% (592 of 969) among women categorized as obesity grade 3. Optimal gestational weight gain ranges were 14.0 kg to less than 16.0 kg for women categorized as underweight; 10.0 kg to less than 18.0 kg for normal weight; 2.0 kg to less than 16.0 kg for overweight; 2.0 kg to less than 6.0 kg for obesity grade 1; weight loss or gain of 0 kg to less than 4.0 kg for obesity grade 2; and weight gain of 0 kg to less than 6.0 kg for obesity grade 3. These gestational weight gain ranges were associated with low to moderate discrimination between those with and those without adverse outcomes (range for area under the receiver operating characteristic curve, 0.55-0.76). Results for discriminative performance in the validation sample were similar to the corresponding results in the main study sample (range for area under the receiver operating characteristic curve, 0.51-0.79)., Conclusions and Relevance: In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights. The estimates of optimal gestational weight gain may inform prenatal counseling; however, the optimal gestational weight gain ranges had limited predictive value for the outcomes assessed.
Published: 2019
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15. Parental Education and Genetics of BMI from Infancy to Old Age: A Pooled Analysis of 29 Twin Cohorts.

Author: Silventoinen K, Jelenkovic A, Latvala A, Yokoyama Y, Sund R, Sugawara M, Tanaka M, Matsumoto S, Aaltonen S, Piirtola M, Freitas DL, Maia JA, Öncel SY, Aliev F, Ji F, Ning F, Pang Z, Rebato E, Saudino KJ, Cutler TL, Hopper JL, Ullemar V, Almqvist C, Magnusson PKE, Cozen W, Hwang AE, Mack TM, Willemsen G, Bartels M, van Beijsterveldt CEM, Nelson TL, Whitfield KE, Sung J, Kim J, Lee J, Lee S, Llewellyn CH, Fisher A, Medda E, Nisticò L, Toccaceli V, Baker LA, Tuvblad C, Corley RP, Huibregtse BM, Derom CA, Vlietinck RF, Loos RJF, Knafo-Noam A, Mankuta D, Abramson L, Burt SA, Klump KL, Silberg JL, Maes HH, Krueger RF, McGue M, Pahlen S, Gatz M, Butler DA, Harris JR, Nilsen TS, Harden KP, Tucker-Drob EM, Franz CE, Kremen WS, Lyons MJ, Lichtenstein P, Jeong HU, Hur YM, Boomsma DI, Sørensen TIA, and Kaprio J
Subjects: Adolescent, Adult, Aged, Child, Child, Preschool, Cohort Studies, Female, Humans, Infant, Male, Middle Aged, Twins, Young Adult, Body Mass Index, Gene-Environment Interaction, Parents education
Abstract: Objective: The objective of this study was to analyze how parental education modifies the genetic and environmental variances of BMI from infancy to old age in three geographic-cultural regions., Methods: A pooled sample of 29 cohorts including 143,499 twin individuals with information on parental education and BMI from age 1 to 79 years (299,201 BMI measures) was analyzed by genetic twin modeling., Results: Until 4 years of age, parental education was not consistently associated with BMI. Thereafter, higher parental education level was associated with lower BMI in males and females. Total and additive genetic variances of BMI were smaller in the offspring of highly educated parents than in those whose parents had low education levels. Especially in North American and Australian children, environmental factors shared by co-twins also contributed to the higher BMI variation in the low education level category. In Europe and East Asia, the associations of parental education with mean BMI and BMI variance were weaker than in North America and Australia., Conclusions: Lower parental education level is associated with higher mean BMI and larger genetic variance of BMI after early childhood, especially in the obesogenic macro-environment. The interplay among genetic predisposition, childhood social environment, and macro-social context is important for socioeconomic differences in BMI., (© 2019 The Obesity Society.)
Published: 2019
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16. Body mass index in young men and risk of inflammatory bowel disease through adult life: A population-based Danish cohort study.

Author: Mendall MA, Jensen CB, Sørensen TIA, Ängquist LH, and Jess T
Subjects: Adult, Cohort Studies, Colitis, Ulcerative epidemiology, Confidence Intervals, Crohn Disease epidemiology, Denmark epidemiology, Humans, Male, Risk Factors, Young Adult, Body Mass Index, Inflammatory Bowel Diseases epidemiology
Abstract: Body mass index (BMI) is associated with increased future risk of inflammatory bowel disease(IBD) particularly Crohn's disease(CD), where associations with high and low BMI have been observed. Most studies are based on adult women. We aimed to explore the impact of BMI in men entering adult life on their long-term risk of developing IBD. A total of 377,957 men born during 1939-1959, with BMI measured at draft boards at mean age 19, were followed from 1977, or time of examination, to end of 2015. Risk of IBD was assessed using Cox regression. During 13 million person-years of follow-up, 1,523 developed CD and 3,323 UC. Using normal weight as reference, for CD the following HRs were observed: BMI < 18.5, 1.35; 95% CI, 1.12-1.62, BMI 25-29.9; 0.83; 95% CI, 0.68-1.02. and BMI > 30 1.20; 95% CI, 0.75-1.90). The increased risk of CD in underweight was maintained up until age 60 not explained by known effects of smoking. For UC, minor inverse associations were observed. Restricted cubic splines revealed a U-shape association between BMI and CD, but not UC. Low BMI of men entering adult life is associated with an increased incidence of CD and UC up to 40 years later.
Published: 2019
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17. Levels of and Changes in Childhood Body Mass Index in Relation to Risk of Atrial Fibrillation and Atrial Flutter in Adulthood.

Author: Adelborg K, Ängquist L, Ording A, Gjærde LK, Bjerregaard LG, Sørensen HT, Sørensen TIA, and Baker JL
Subjects: Adolescent, Adult, Atrial Fibrillation epidemiology, Atrial Flutter epidemiology, Child, Denmark epidemiology, Female, Humans, Male, Pediatric Obesity physiopathology, Risk Factors, Young Adult, Atrial Fibrillation etiology, Atrial Flutter etiology, Body Mass Index, Pediatric Obesity complications
Abstract: Children with obesity have a cardiometabolic risk profile that may predispose them to cardiovascular diseases. We examined the associations of childhood body mass index (BMI) and changes in BMI with the risk of atrial fibrillation and flutter (AFF) in adulthood. We conducted a population-based cohort study of Danish schoolchildren aged 7-13 years born from 1930 to 1989. Among 314,140 children, 17,594 were diagnosed with AFF as adults (1977-2014). In both men and women, above-average BMIs in childhood were associated with increased risks of AFF. Children who were persistently heavy at ages 7 and 13 years and children whose BMIs increased from the internal 25.0th-75.0th percentiles or from the internal 75.1th-90.0th percentiles between ages 7 and 13 years had higher risks of AFF in adulthood than children whose BMIs remained in the internal 25.0th-75.0th percentiles at both ages. A decrease in BMI percentile categories between 7 and 13 years of age reduced risks of AFF in adulthood, with risks of AFF reverting to levels similar to those in the reference group for women but not for men. In conclusion, risks of AFF in adulthood increased with higher childhood BMIs. Remission from overweight by age 13 years reduced AFF risks, especially in women., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Published: 2019
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18. Changes in Childhood Body-Mass Index and Risk of Venous Thromboembolism in Adulthood.

Author: Sundbøll J, Ängquist L, Adelborg K, Gjærde LK, Ording A, Sørensen TIA, Baker JL, and Sørensen HT
Subjects: Adolescent, Child, Denmark epidemiology, Disease Progression, Female, Humans, Incidence, Male, Prognosis, Risk Factors, Venous Thromboembolism etiology, Body Mass Index, Obesity complications, Overweight complications, Registries, Risk Assessment methods, Venous Thromboembolism epidemiology
Abstract: Background Childhood weight trajectories may influence cardiometabolic traits and thereby the risk of venous thromboembolism ( VTE ) later in life. We examined whether overweight and changes in weight status during childhood were associated with risk of VTE in adulthood. Methods and Results We used Danish medical registries to conduct a population-based cohort study of Danish schoolchildren aged 7 to 13 years and born during 1930-1989. We calculated body-mass index ( BMI ) z-scores based on weight and height measurements. We estimated hazard ratios using Cox regressions to examine associations between changes in BMI z-scores from 7 to 13 years of age and the subsequent risk of VTE . Among 313 998 children, 5007 girls and 5397 boys were diagnosed with VTE as adults. Compared with children with a normal BMI (25th to 75th percentile category) at both ages, children with a BMI persistently above the 75th percentile had a 1.30- to 1.50-fold increased risk of VTE in adulthood. Children who experienced a BMI increase from the 25th to 75th or >75th to 90th percentile to a higher percentile category had a 1.35- to 1.70-fold increased risk of adulthood VTE . Children whose BMI percentile category decreased between 7 and 13 years of age had a VTE risk similar to that of children with a persistently normal BMI . Conclusions Risk of VTE in adulthood was higher in children with a persistently above-average BMI . Whereas weight gain from 7 to 13 years of age additionally increased VTE risk, remission from overweight by 13 years of age completely reverted the risk.
Published: 2019
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19. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis.

Author: Voerman E, Santos S, Patro Golab B, Amiano P, Ballester F, Barros H, Bergström A, Charles MA, Chatzi L, Chevrier C, Chrousos GP, Corpeleijn E, Costet N, Crozier S, Devereux G, Eggesbø M, Ekström S, Fantini MP, Farchi S, Forastiere F, Georgiu V, Godfrey KM, Gori D, Grote V, Hanke W, Hertz-Picciotto I, Heude B, Hryhorczuk D, Huang RC, Inskip H, Iszatt N, Karvonen AM, Kenny LC, Koletzko B, Küpers LK, Lagström H, Lehmann I, Magnus P, Majewska R, Mäkelä J, Manios Y, McAuliffe FM, McDonald SW, Mehegan J, Mommers M, Morgen CS, Mori TA, Moschonis G, Murray D, Chaoimh CN, Nohr EA, Nybo Andersen AM, Oken E, Oostvogels AJJM, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Ronfani L, Santos AC, Standl M, Stoltenberg C, Thiering E, Thijs C, Torrent M, Tough SC, Trnovec T, Turner S, van Rossem L, von Berg A, Vrijheid M, Vrijkotte TGM, West J, Wijga A, Wright J, Zvinchuk O, Sørensen TIA, Lawlor DA, Gaillard R, and Jaddoe VWV
Subjects: Australia epidemiology, Cohort Studies, Europe epidemiology, Female, Humans, North America epidemiology, Overweight diagnosis, Overweight epidemiology, Pediatric Obesity diagnosis, Pregnancy, Risk Factors, Body Mass Index, Data Analysis, Gestational Weight Gain physiology, Pediatric Obesity epidemiology
Abstract: Background: Maternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact., Methods and Findings: We conducted an individual participant data meta-analysis of data from 162,129 mothers and their children from 37 pregnancy and birth cohort studies from Europe, North America, and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges, with the risks of overweight/obesity in early (2.0-5.0 years), mid (5.0-10.0 years) and late childhood (10.0-18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal sociodemographic and lifestyle-related characteristics. We observed that higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (odds ratios [ORs] for overweight/obesity in early, mid, and late childhood, respectively: OR 1.66 [95% CI: 1.56, 1.78], OR 1.91 [95% CI: 1.85, 1.98], and OR 2.28 [95% CI: 2.08, 2.50] for maternal overweight; OR 2.43 [95% CI: 2.24, 2.64], OR 3.12 [95% CI: 2.98, 3.27], and OR 4.47 [95% CI: 3.99, 5.23] for maternal obesity; and OR 1.39 [95% CI: 1.30, 1.49], OR 1.55 [95% CI: 1.49, 1.60], and OR 1.72 [95% CI: 1.56, 1.91] for excessive gestational weight gain). The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal obesity, and excessive gestational weight gain ranged from 10.2% to 21.6%. Relative to the effect of maternal BMI, excessive gestational weight gain only slightly increased the risk of childhood overweight/obesity within each clinical BMI category (p-values for interactions of maternal BMI with gestational weight gain: p = 0.038, p < 0.001, and p = 0.637 in early, mid, and late childhood, respectively). Limitations of this study include the self-report of maternal BMI and gestational weight gain for some of the cohorts, and the potential of residual confounding. Also, as this study only included participants from Europe, North America, and Australia, results need to be interpreted with caution with respect to other populations., Conclusions: In this study, higher maternal pre-pregnancy BMI and gestational weight gain were associated with an increased risk of childhood overweight/obesity, with the strongest effects at later ages. The additional effect of gestational weight gain in women who are overweight or obese before pregnancy is small. Given the large population impact, future intervention trials aiming to reduce the prevalence of childhood overweight and obesity should focus on maternal weight status before pregnancy, in addition to weight gain during pregnancy., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: KMG has received reimbursement for speaking at conferences sponsored by companies selling nutritional products, and is part of an academic consortium that has received research funding from Abbott Nutrition, Nestec and Danone. HL has participated as an advisory board member, consultant and speaker for Nestlé Nutrition Institute and Nestlé Finland. DAL has received support from several National and International Government and Charity Funders and from Roche Diagnostics and Medtronic for research unrelated to that presented here. All support had been administered via DAL's institution; not directly to her. The other authors have declared that no competing interests exist.
Published: 2019
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20. Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania.

Author: Santos S, Eekhout I, Voerman E, Gaillard R, Barros H, Charles MA, Chatzi L, Chevrier C, Chrousos GP, Corpeleijn E, Costet N, Crozier S, Doyon M, Eggesbø M, Fantini MP, Farchi S, Forastiere F, Gagliardi L, Georgiu V, Godfrey KM, Gori D, Grote V, Hanke W, Hertz-Picciotto I, Heude B, Hivert MF, Hryhorczuk D, Huang RC, Inskip H, Jusko TA, Karvonen AM, Koletzko B, Küpers LK, Lagström H, Lawlor DA, Lehmann I, Lopez-Espinosa MJ, Magnus P, Majewska R, Mäkelä J, Manios Y, McDonald SW, Mommers M, Morgen CS, Moschonis G, Murínová Ľ, Newnham J, Nohr EA, Andersen AN, Oken E, Oostvogels AJJM, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Roeleveld N, Santa-Marina L, Santos AC, Smit HA, Sørensen TIA, Standl M, Stanislawski M, Stoltenberg C, Thiering E, Thijs C, Torrent M, Tough SC, Trnovec T, van Gelder MMHJ, van Rossem L, von Berg A, Vrijheid M, Vrijkotte TGM, Zvinchuk O, van Buuren S, and Jaddoe VWV
Subjects: Adult, Europe, Female, Humans, North America, Oceania, Pregnancy, Pregnancy Complications, Pregnancy Outcome, Risk Factors, Body Mass Index, Gestational Weight Gain physiology
Abstract: Background: Gestational weight gain differs according to pre-pregnancy body mass index and is related to the risks of adverse maternal and child health outcomes. Gestational weight gain charts for women in different pre-pregnancy body mass index groups enable identification of women and offspring at risk for adverse health outcomes. We aimed to construct gestational weight gain reference charts for underweight, normal weight, overweight, and grades 1, 2 and 3 obese women and to compare these charts with those obtained in women with uncomplicated term pregnancies., Methods: We used individual participant data from 218,216 pregnant women participating in 33 cohorts from Europe, North America, and Oceania. Of these women, 9065 (4.2%), 148,697 (68.1%), 42,678 (19.6%), 13,084 (6.0%), 3597 (1.6%), and 1095 (0.5%) were underweight, normal weight, overweight, and grades 1, 2, and 3 obese women, respectively. A total of 138, 517 women from 26 cohorts had pregnancies with no hypertensive or diabetic disorders and with term deliveries of appropriate for gestational age at birth infants. Gestational weight gain charts for underweight, normal weight, overweight, and grade 1, 2, and 3 obese women were derived by the Box-Cox t method using the generalized additive model for location, scale, and shape., Results: We observed that gestational weight gain strongly differed per maternal pre-pregnancy body mass index group. The median (interquartile range) gestational weight gain at 40 weeks was 14.2 kg (11.4-17.4) for underweight women, 14.5 kg (11.5-17.7) for normal weight women, 13.9 kg (10.1-17.9) for overweight women, and 11.2 kg (7.0-15.7), 8.7 kg (4.3-13.4) and 6.3 kg (1.9-11.1) for grades 1, 2, and 3 obese women, respectively. The rate of weight gain was lower in the first half than in the second half of pregnancy. No differences in the patterns of weight gain were observed between cohorts or countries. Similar weight gain patterns were observed in mothers without pregnancy complications., Conclusions: Gestational weight gain patterns are strongly related to pre-pregnancy body mass index. The derived charts can be used to assess gestational weight gain in etiological research and as a monitoring tool for weight gain during pregnancy in clinical practice.
Published: 2018
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21. Association of current and former smoking with body mass index: A study of smoking discordant twin pairs from 21 twin cohorts.

Author: Piirtola M, Jelenkovic A, Latvala A, Sund R, Honda C, Inui F, Watanabe M, Tomizawa R, Iwatani Y, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Tarnoki AD, Tarnoki DL, Martin NG, Montgomery GW, Medland SE, Rasmussen F, Tynelius P, Tan Q, Zhang D, Pang Z, Rebato E, Stazi MA, Fagnani C, Brescianini S, Busjahn A, Harris JR, Brandt I, Nilsen TS, Cutler TL, Hopper JL, Corley RP, Huibregtse BM, Sung J, Kim J, Lee J, Lee S, Gatz M, Butler DA, Franz CE, Kremen WS, Lyons MJ, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Öncel SY, Aliev F, Derom CA, Vlietinck RF, Loos RJF, Silberg JL, Maes HH, Boomsma DI, Sørensen TIA, Korhonen T, Kaprio J, and Silventoinen K
Subjects: Adolescent, Adult, Aged, Cohort Studies, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Smoking genetics, Smoking Cessation, Young Adult, Body Mass Index, Smoking adverse effects, Smoking pathology, Twins, Dizygotic, Twins, Monozygotic
Abstract: Background: Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background., Methods and Findings: The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18-69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m2 lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m2 lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m2 higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m2 higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m2, 95% CI 0.04, 0.23 among men; -0.04 kg/m2, 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade., Conclusions: Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m2., Competing Interests: TK reports personal consultation fees from Pfizer Finland, during the conduct of the study but outside of this study. JK reports grants from the Academy of Finland and the Sigrid Juselius Foundation, during the conduct of the study, and personal fees from Pfizer Inc., outside the submitted study. AB reports working in the HealthTwiSt GmbH but the company did not have any impact on this study. FI reports grants from JSPS KAKENHI JP (23593419,16K15978), during the conduct of the study. MG reports grants from the National Institutes of Health, during the conduct of the study, and other grants from National Institutes of Health, outside the submitted work period. All other authors have nothing to declare. None of the funders played a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials. None of the commercial affiliations affects our adherence to PLOS ONE policies on sharing data and materials. The specific roles of authors with commercial affiliations (AB, JK, TK) are articulated in the 'author contributions' section. The corresponding author had full access to all of the data in the study and had final responsibility for the decision to submit the paper for publication.
Published: 2018
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22. Childhood body mass index and risk of inflammatory bowel disease in adulthood: a population-based cohort study.

Author: Jensen CB, Ängquist LH, Mendall MA, Sørensen TIA, Baker JL, and Jess T
Subjects: Adult, Age Factors, Age of Onset, Child, Denmark epidemiology, Female, Follow-Up Studies, Humans, Incidence, Male, Middle Aged, Registries statistics & numerical data, Risk Factors, Body Mass Index, Colitis, Ulcerative epidemiology, Crohn Disease epidemiology, Obesity epidemiology, Thinness epidemiology
Abstract: Background: The increasing incidence of inflammatory bowel disease (IBD) in western countries has led to the hypothesis that obesity-related inflammation could play a role in the etiology of IBD. However, this hypothesis lacks confirmation in studies of individuals prior to the typical onset of IBD in young adulthood., Methods: In a cohort of 316,799 individuals from the Copenhagen School Health Records Register (CSHRR), we examined whether BMI at ages 7 through 13 years was associated with later IBD. Linking the CSHRR to the Danish National Patient Register, we identified cases of Crohn's disease (CD) and ulcerative colitis (UC) diagnosed during follow-up. Cox regression was used to estimate the hazard ratios (HR) with 95% confidence intervals., Results: During 10 million person-years of follow-up, 1500 individuals were diagnosed with CD and 2732 with UC. At all examined ages, a 1 unit increase in BMI z-score was associated with a significantly decreased risk of UC (HRs = 0.9) and with a significantly increased risk of CD when diagnosed before age 30 (HRs = 1.2). We observed no associations between changes in BMI z-score between 7 and 13 years and later risk of CD or UC., Conclusion: We found a direct association between childhood BMI and CD diagnosed before 30 years of age, and an inverse association between childhood BMI and UC irrespective of age. Our results support the previous hypotheses of obesity being a risk factor for CD, and suggest that childhood underweight might be a risk factor for UC.
Published: 2018
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23. Childcare before age 6 and body mass index at age 7 years in a cohort of Danish children.

Author: Benjamin Neelon SE, Schmidt Morgen C, Kamper-Jørgensen M, Oken E, Gillman MW, Gallis JA, and Sørensen TIA
Subjects: Child, Child, Preschool, Databases, Factual, Denmark epidemiology, Female, Humans, Infant, Male, Overweight epidemiology, Overweight etiology, Pediatric Obesity epidemiology, Body Mass Index, Child Care statistics & numerical data, Pediatric Obesity etiology
Abstract: Background: Previous studies show inconsistent associations between childcare and obesity., Aims: Our prior work demonstrated that childcare in infancy was associated with higher weight in a cohort of Danish children. Here, we extend this work and examine childcare through 6 years and body mass index (BMI) at age 7 years., Materials and Methods: We examined 24 714 children in the Danish National Birth Cohort who were also in the Childcare Database. We conducted multivariable linear regressions examining children prior to age 6, overall and by type (daycare, crèche, age-integrated and kindergarten), and BMI z-score at 7 years, stratifying on maternal socio-occupational status., Results: A total of 19 760 (80.0%) children attended childcare before age 6. Childcare prior to age 6 was associated with BMI z-score at 7 years (0.004 units per each additional 6 months of care; 95% CI: 0.001, 0.008; p = 0.01). Childcare in a kindergarten was the only type of care associated with BMI (0.009 units; 95% CI: 0.003, 0.02; p = 0.01). For children of higher socio-occupational status mothers, childcare was associated with a 0.008 unit increase in BMI (95% CI: 0.004, 0.01; p > 0.001)., Conclusions: Childcare was weakly associated with later BMI. This relationship was more pronounced in children from higher socio-occupational status mothers and children in kindergarten care., (© 2017 World Obesity Federation.)
Published: 2018
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24. Prenatal risk factors influencing childhood BMI and overweight independent of birth weight and infancy BMI: a path analysis within the Danish National Birth Cohort.

Author: Morgen CS, Ängquist L, Baker JL, Andersen AMN, Michaelsen KF, and Sørensen TIA
Subjects: Adult, Birth Weight, Body Size, Child, Cohort Studies, Denmark epidemiology, Educational Status, Female, Humans, Male, Risk Factors, Smoking, Body Mass Index, Pediatric Obesity epidemiology
Abstract: Background and Objectives: Prenatal risk factors for childhood overweight may operate indirectly through development in body size in early life and/or directly independent hereof. We quantified the effects of maternal and paternal body mass index (BMI), maternal age, socioeconomic position (SEP), parity, gestational weight gain, maternal smoking during pregnancy, caesarean section, birth weight, and BMI at 5 and 12 months on BMI and overweight at 7 and 11 years., Methods: Family triads with information on maternal, paternal and child BMI at ages 7 (n=29 374) and 11 years (n=18 044) were selected from the Danish National Birth Cohort. Information originated from maternal interviews and medical health examinations. Path analysis was used to estimate the direct and indirect effects of prenatal risk factors on childhood BMI z-scores (BMIz per unit score of the risk factor). Logistic regression was used to examine associations with overweight., Results: The strongest direct effects on BMIz at age 7 were found for maternal and paternal BMI (0.19 BMIz and 0.14 BMIz per parental BMIz), low SEP (0.08 BMIz), maternal smoking (0.12 BMIz) and higher BMIz at 5 and 12 months (up to 0.19 BMIz per infant BMIz). For BMIz at age 11 with BMIz at age 7 included in the model, similar effects were found, but the direct effects of BMIz at age 5 and 12 months were mediated through BMI at age 7 (0.62 BMIz per BMIz). Same results were found for overweight. The sum of the direct effects can be translated to approximate absolute measures: 2.4 kg at 7 years, 5.7 kg at 11 years, in a child with average height and BMI., Conclusions: Parental BMI, low SEP and smoking during pregnancy have persisting, strong and direct effects on child BMI and overweight independent of birth weight and infancy BMI.
Published: 2018
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25. Breastfeeding and complementary feeding in relation to body mass index and overweight at ages 7 and 11 y: a path analysis within the Danish National Birth Cohort.

Author: Morgen CS, Ängquist L, Baker JL, Andersen AN, Sørensen TIA, and Michaelsen KF
Subjects: Child, Cohort Studies, Dairy Products, Denmark epidemiology, Diet Surveys, Dietary Proteins administration & dosage, Female, Fish Proteins, Dietary administration & dosage, Follow-Up Studies, Humans, Infant, Lost to Follow-Up, Male, Meat Proteins administration & dosage, Time Factors, Body Mass Index, Breast Feeding, Infant Nutritional Physiological Phenomena, Overweight epidemiology, Pediatric Obesity epidemiology
Abstract: Background: Infant feeding may play an important role in the development of childhood overweight and obesity., Objective: The objective of this study was to examine whether duration of breastfeeding (BF), timing of introduction of complementary food, and protein intake at age 18 mo are associated with body mass index [BMI (measured in kg/m2)] and overweight at ages 7 and 11 y, independent of BMI during infancy., Design: Children participating in the Danish National Birth Cohort were followed up at ages 7 and 11 y. Information on infant feeding, protein intake at age 18 mo, Ponderal Index at birth, child BMI (at ages 5 mo, 12 mo, 7 y, and 11 y), and several parental factors was available. Path analysis was used to assess the direct and indirect effects of infant feeding on BMI z scores (BMIz) at ages 7 (n = 36,481) and 11 y (n = 22,047). Logistic regression analyses were used to examine associations with overweight., Results: Duration of BF was not associated with childhood BMIz at ages 7 and 11 y. Earlier introduction of complementary food (<4 mo old) was not associated with BMIz at age 7 y, but with a 0.069 (95% CI: 0.021, 0.117, P = 0.005) higher BMIz at age 11 y and increased risk of overweight at age 11 y (OR 1.44; 95% CI: 1.04, 2.00; P = 0.03). Protein intake from dairy products (per 5 g/d) was associated with higher BMIz only at age 7 y (OR: 0.012; 95% CI: 0.003, 0.021; P = 0.007). Protein intake from meat and fish (per 2 g/d) was associated with a 0.010 (95% CI: 0.004, 0.017; P = 0.003) higher BMIz at age 7 y, a 0.013 (95% CI: 0.005, 0.020; P = 0.002) higher BMIz at age 11 y and increased odds of overweight at age 7 y (OR: 1.07; 95% CI: 1.03, 1.10; P < 0.001), but not at age 11 y., Conclusions: Intake of protein from meat and fish at age 18 mo was associated with higher BMIz and risk of overweight in childhood. However, the effect sizes were small. Early introduction of complementary food may be associated with child BMIz and child overweight. This study was registered at www.clinicaltrials.gov as NCT03334760.
Published: 2018
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26. Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.

Author: Smith CE, Follis JL, Dashti HS, Tanaka T, Graff M, Fretts AM, Kilpeläinen TO, Wojczynski MK, Richardson K, Nalls MA, Schulz CA, Liu Y, Frazier-Wood AC, van Eekelen E, Wang C, de Vries PS, Mikkilä V, Rohde R, Psaty BM, Hansen T, Feitosa MF, Lai CQ, Houston DK, Ferruci L, Ericson U, Wang Z, de Mutsert R, Oddy WH, de Jonge EAL, Seppälä I, Justice AE, Lemaitre RN, Sørensen TIA, Province MA, Parnell LD, Garcia ME, Bandinelli S, Orho-Melander M, Rich SS, Rosendaal FR, Pennell CE, Kiefte-de Jong JC, Kähönen M, Young KL, Pedersen O, Aslibekyan S, Rotter JI, Mook-Kanamori DO, Zillikens MC, Raitakari OT, North KE, Overvad K, Arnett DK, Hofman A, Lehtimäki T, Tjønneland A, Uitterlinden AG, Rivadeneira F, Franco OH, German JB, Siscovick DS, Cupples LA, and Ordovás JM
Subjects: Actins genetics, Adult, Aged, Cohort Studies, Cross-Sectional Studies, Female, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Myosin-Light-Chain Phosphatase genetics, White People genetics, Body Mass Index, Dairy Products, Polymorphism, Single Nucleotide
Abstract: Scope: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption., Methods and Results: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10 -7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10 -8) such that each serving of low-fat dairy was associated with 0.225 kg m -2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure., Conclusion: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)
Published: 2018
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27. Childhood body mass index and height in relation to site-specific risks of colorectal cancers in adult life.

Author: Jensen BW, Gamborg M, Gögenur I, Renehan AG, Sørensen TIA, and Baker JL
Subjects: Adenocarcinoma epidemiology, Adult, Child, Cohort Studies, Colonic Neoplasms epidemiology, Denmark epidemiology, Female, Humans, Incidence, Male, Proportional Hazards Models, Rectal Neoplasms epidemiology, Registries, Risk Factors, Weight Gain, Adenocarcinoma diagnosis, Body Height, Body Mass Index, Colonic Neoplasms diagnosis, Rectal Neoplasms diagnosis
Abstract: As colorectal cancers have a long latency period, their origins may lie early in life. Therefore childhood body mass index (BMI; kg/m 2 ) and height may be associated with adult colorectal cancer. Using a cohort design, 257,623 children from The Copenhagen School Health Records Register born from 1930 to 1972 with measured heights and weights at ages 7 to 13 years were followed for adult colon and rectal adenocarcinomas by linkage to the Danish Cancer Registry. Hazard ratios (HRs) with 95% confidence intervals (CI) were estimated by Cox proportional hazard regressions. During follow-up, 2676 colon and 1681 rectal adenocarcinomas were diagnosed. No sex differences were observed in the associations between child BMI or height and adult colon or rectal cancers. Childhood BMI and height were positively associated with colon cancer; at age 13 years the HRs were 1.09 (95% CI 1.04-1.14) and 1.14 (95% CI 1.09-1.19) per z-score, respectively. Children who were persistently taller or heavier than average, had increased risk of colon cancer. Similarly, growing taller or gaining more weight than average was positively associated with colon cancer. No associations were observed between BMI or height and rectal cancer. Childhood BMI and height, along with above average change during childhood are significantly and positively associated with adult colon cancers, but not with rectal cancer, suggesting different etiologies.
Published: 2017
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28. Association of Childhood Body Mass Index and Change in Body Mass Index With First Adult Ischemic Stroke.

Author: Gjærde LK, Gamborg M, Ängquist L, Truelsen TC, Sørensen TIA, and Baker JL
Subjects: Adolescent, Adult, Brain Ischemia etiology, Child, Cohort Studies, Denmark epidemiology, Female, Humans, Male, Middle Aged, Stroke etiology, Body Mass Index, Brain Ischemia epidemiology, Pediatric Obesity epidemiology, Registries statistics & numerical data, Stroke epidemiology
Abstract: Importance: The incidence of ischemic stroke among young adults is rising and is potentially due to an increase in stroke risk factors occurring at younger ages, such as obesity., Objectives: To investigate whether childhood body mass index (BMI) and change in BMI are associated with adult ischemic stroke and to assess whether the associations are age dependent or influenced by birth weight., Design, Setting, and Participants: This investigation was a population-based cohort study of schoolchildren born from 1930 to 1987, with follow-up through national health registers from 1977 to 2012 in Denmark. Participants were 307 677 individuals (8899 ischemic stroke cases) with measured weight and height at ages 7 to 13 years. The dates of the analysis were September 1, 2015, to May 27, 2016., Main Outcomes and Measures: Childhood BMI, change in BMI, and birth weight. Ischemic stroke events were divided into early (≤55 years) or late (>55 years) age at diagnosis., Results: The study cohort comprised 307 677 participants (approximately 49% female and 51% male). During the study period, 3529 women and 5370 men experienced an ischemic stroke. At all ages from 7 to 13 years, an above-average BMI z score was positively associated with early ischemic stroke. At age 13 years, a BMI z score of 1 was associated with hazard ratios (HRs) of 1.26 (95% CI, 1.11-1.43) in women and 1.21 (95% CI, 1.10-1.33) in men. No significant associations were found for below-average BMI z scores. Among children with above-average BMI z scores at age 7 years, a score increase of 0.5 from ages 7 to 13 years was positively associated with early ischemic stroke in women (HR, 1.10; 95% CI, 1.01-1.20) and in men (HR, 1.08; 95% CI, 1.00-1.16). Similarly, among children with below-average BMI z scores at age 7 years, a score increase of 0.5 from ages 7 to 13 years was positively associated with early ischemic stroke in women (HR, 1.14; 95% CI, 1.06-1.23) and in men (HR, 1.10; 95% CI, 1.04-1.18). Adjusting for birth weight minimally affected the associations., Conclusions and Relevance: Independent of birth weight, above-average childhood BMI and increases in BMI during childhood are positively associated with early adult ischemic stroke. To avoid the occurrence of early ischemic stroke associated with childhood overweight and obesity, these results suggest that all children should be helped to attain and maintain healthy weights.
Published: 2017
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29. Association between birthweight and later body mass index: an individual-based pooled analysis of 27 twin cohorts participating in the CODATwins project.

Author: Jelenkovic A, Yokoyama Y, Sund R, Pietiläinen KH, Hur YM, Willemsen G, Bartels M, van Beijsterveldt TCEM, Ooki S, Saudino KJ, Stazi MA, Fagnani C, D'Ippolito C, Nelson TL, Whitfield KE, Knafo-Noam A, Mankuta D, Abramson L, Heikkilä K, Cutler TL, Hopper JL, Wardle J, Llewellyn CH, Fisher A, Corley RP, Huibregtse BM, Derom CA, Vlietinck RF, Loos RJF, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Tarnoki AD, Tarnoki DL, Burt SA, Klump KL, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Harris JR, Brandt I, Nilsen TS, Craig JM, Saffery R, Rasmussen F, Tynelius P, Bayasgalan G, Narandalai D, Haworth CMA, Plomin R, Ji F, Ning F, Pang Z, Rebato E, Krueger RF, McGue M, Pahlen S, Boomsma DI, Sørensen TIA, Kaprio J, and Silventoinen K
Subjects: Adolescent, Adult, Child, Child, Preschool, Female, Humans, Infant, Internationality, Linear Models, Male, Middle Aged, Twins, Dizygotic, Twins, Monozygotic, Young Adult, Birth Weight genetics, Body Mass Index
Abstract: Background: There is evidence that birthweight is positively associated with body mass index (BMI) in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. We analysed the association between birthweight and BMI from infancy to adulthood within twin pairs, which provides insights into the role of genetic and environmental individual-specific factors., Methods: This study is based on the data from 27 twin cohorts in 17 countries. The pooled data included 78 642 twin individuals (20 635 monozygotic and 18 686 same-sex dizygotic twin pairs) with information on birthweight and a total of 214 930 BMI measurements at ages ranging from 1 to 49 years. The association between birthweight and BMI was analysed at both the individual and within-pair levels using linear regression analyses., Results: At the individual level, a 1-kg increase in birthweight was linearly associated with up to 0.9 kg/m2 higher BMI (P < 0.001). Within twin pairs, regression coefficients were generally greater (up to 1.2 kg/m2 per kg birthweight, P < 0.001) than those from the individual-level analyses. Intra-pair associations between birthweight and later BMI were similar in both zygosity groups and sexes and were lower in adulthood., Conclusions: These findings indicate that environmental factors unique to each individual have an important role in the positive association between birthweight and later BMI, at least until young adulthood., (© The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association)
Published: 2017
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30. Childhood body mass index and development of type 2 diabetes throughout adult life-A large-scale danish cohort study.

Author: Zimmermann E, Bjerregaard LG, Gamborg M, Vaag AA, Sørensen TIA, and Baker JL
Subjects: Adolescent, Adult, Child, Cohort Studies, Diabetes Mellitus, Type 2 pathology, Female, Humans, Male, Middle Aged, Risk Factors, Sweden, Young Adult, Body Mass Index, Diabetes Mellitus, Type 2 etiology
Abstract: Objective: This study investigated how a wide spectrum of body mass index (BMI) values at ages 7 to 13 years are associated with type 2 diabetes throughout adulthood, including potential modifying effects of sex and birth weight., Methods: From the Copenhagen School Health Records Register, 292,827 individuals, born between 1930 and 1989, were followed in national registers for type 2 diabetes (women, n = 7,472; men, n = 11,548). Heights and weights were measured at ages 7 to 13 years., Results: Below-average BMIs, with few exceptions, were not associated with type 2 diabetes. Above-average BMIs had positive associations that were stronger in women than men, stronger in younger birth cohorts, and weaker with older age at diagnosis. Women born 1930-1947, 1948-1965, and 1966-1983 with above-average BMIs at 13 years (≥18.2 kg/m 2 ) had hazard ratios (95% confidence intervals) ranging from 2.12 (1.91-2.36) to 2.84 (2.31-3.49) per z score when diagnosed at 30 to 47 years. Birth weight did not modify these associations., Conclusions: Childhood BMIs below average are not associated with type 2 diabetes, whereas childhood BMIs above average are strongly associated with type 2 diabetes in adulthood, corresponding to excess risks even at levels below international definitions of overweight. The associations are stronger in women than men but are not affected by birth weight., (© 2017 The Obesity Society.)
Published: 2017
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31. Does the sex of one's co-twin affect height and BMI in adulthood? A study of dizygotic adult twins from 31 cohorts.

Author: Bogl LH, Jelenkovic A, Vuoksimaa E, Ahrenfeldt L, Pietiläinen KH, Stazi MA, Fagnani C, D'Ippolito C, Hur YM, Jeong HU, Silberg JL, Eaves LJ, Maes HH, Bayasgalan G, Narandalai D, Cutler TL, Kandler C, Jang KL, Christensen K, Skytthe A, Kyvik KO, Cozen W, Hwang AE, Mack TM, Derom CA, Vlietinck RF, Nelson TL, Whitfield KE, Corley RP, Huibregtse BM, McAdams TA, Eley TC, Gregory AM, Krueger RF, McGue M, Pahlen S, Willemsen G, Bartels M, van Beijsterveldt TCEM, Pang Z, Tan Q, Zhang D, Martin NG, Medland SE, Montgomery GW, Hjelmborg JVB, Rebato E, Swan GE, Krasnow R, Busjahn A, Lichtenstein P, Öncel SY, Aliev F, Baker LA, Tuvblad C, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Magnusson PKE, Pedersen NL, Aslan AKD, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Duncan GE, Buchwald D, Tarnoki AD, Tarnoki DL, Yokoyama Y, Hopper JL, Loos RJF, Boomsma DI, Sørensen TIA, Silventoinen K, and Kaprio J
Subjects: Adult, Aged, Aged, 80 and over, Cohort Studies, Female, Humans, Male, Middle Aged, Young Adult, Body Height, Body Mass Index, Twins, Dizygotic
Abstract: Background: The comparison of traits in twins from opposite-sex (OS) and same-sex (SS) dizygotic twin pairs is considered a proxy measure of prenatal hormone exposure. To examine possible prenatal hormonal influences on anthropometric traits, we compared mean height, body mass index (BMI), and the prevalence of being overweight or obese between men and women from OS and SS dizygotic twin pairs., Methods: The data were derived from the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) database, and included 68,494 SS and 53,808 OS dizygotic twin individuals above the age of 20 years from 31 twin cohorts representing 19 countries. Zygosity was determined by questionnaires or DNA genotyping depending on the study. Multiple regression and logistic regression models adjusted for cohort, age, and birth year with the twin type as a predictor were carried out to compare height and BMI in twins from OS pairs with those from SS pairs and to calculate the adjusted odds ratios and 95% confidence intervals for being overweight or obese., Results: OS females were, on average, 0.31 cm (95% confidence interval (CI) 0.20, 0.41) taller than SS females. OS males were also, on average, taller than SS males, but this difference was only 0.14 cm (95% CI 0.02, 0.27). Mean BMI and the prevalence of overweight or obesity did not differ between males and females from SS and OS twin pairs. The statistically significant differences between OS and SS twins for height were small and appeared to reflect our large sample size rather than meaningful differences of public health relevance., Conclusions: We found no evidence to support the hypothesis that prenatal hormonal exposure or postnatal socialization (i.e., having grown up with a twin of the opposite sex) has a major impact on height and BMI in adulthood.
Published: 2017
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32. Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) study.

Author: Silventoinen K, Jelenkovic A, Sund R, Hur YM, Yokoyama Y, Honda C, Hjelmborg Jv, Möller S, Ooki S, Aaltonen S, Ji F, Ning F, Pang Z, Rebato E, Busjahn A, Kandler C, Saudino KJ, Jang KL, Cozen W, Hwang AE, Mack TM, Gao W, Yu C, Li L, Corley RP, Huibregtse BM, Christensen K, Skytthe A, Kyvik KO, Derom CA, Vlietinck RF, Loos RJ, Heikkilä K, Wardle J, Llewellyn CH, Fisher A, McAdams TA, Eley TC, Gregory AM, He M, Ding X, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Tarnoki AD, Tarnoki DL, Stazi MA, Fagnani C, D'Ippolito C, Knafo-Noam A, Mankuta D, Abramson L, Burt SA, Klump KL, Silberg JL, Eaves LJ, Maes HH, Krueger RF, McGue M, Pahlen S, Gatz M, Butler DA, Bartels M, van Beijsterveldt TC, Craig JM, Saffery R, Freitas DL, Maia JA, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Martin NG, Medland SE, Montgomery GW, Chong Y, Swan GE, Krasnow R, Magnusson PK, Pedersen NL, Tynelius P, Lichtenstein P, Haworth CM, Plomin R, Bayasgalan G, Narandalai D, Harden KP, Tucker-Drob EM, Öncel SY, Aliev F, Spector T, Mangino M, Lachance G, Baker LA, Tuvblad C, Duncan GE, Buchwald D, Willemsen G, Rasmussen F, Goldberg JH, Sørensen TIa, Boomsma DI, and Kaprio J
Subjects: Adolescent, Adult, Age Factors, Australia, Child, Child, Preschool, Europe, Asia, Eastern, Female, Humans, Infant, Male, North America, Obesity ethnology, Obesity genetics, Sex Factors, Young Adult, Body Mass Index, Environment, Gene-Environment Interaction, Genetic Variation, Obesity etiology, Twins, Dizygotic genetics, Twins, Monozygotic genetics
Abstract: Background: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking., Objectives: We analyzed the genetic and environmental contributions to BMI variation from infancy to early adulthood and the ways they differ by sex and geographic regions representing high (North America and Australia), moderate (Europe), and low levels (East Asia) of obesogenic environments., Design: Data were available for 87,782 complete twin pairs from 0.5 to 19.5 y of age from 45 cohorts. Analyses were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling., Results: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive genetic factors was lowest at 4 y of age in boys (a(2) = 0.42) and girls (a(2) = 0.41) and then generally increased to 0.75 in both sexes at 19 y of age. This was because of a stronger influence of environmental factors shared by co-twins in midchildhood. After 15 y of age, the effect of shared environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained roughly similar across different regions., Conclusions: Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a major role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity., (© 2016 American Society for Nutrition.)
Published: 2016
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33. Comparison of associations of maternal peri-pregnancy and paternal anthropometrics with child anthropometrics from birth through age 7 y assessed in the Danish National Birth Cohort.

Author: Sørensen TIa, Ajslev TA, Ängquist L, Morgen CS, Ciuchi IG, and Davey Smith G
Subjects: Adult, Age Factors, Anthropometry, Birth Weight, Child, Child, Preschool, Cohort Studies, Denmark, Female, Humans, Infant, Infant, Newborn, Male, Odds Ratio, Overweight, Pediatric Obesity etiology, Pregnancy, Body Mass Index, Fathers, Mothers, Obesity complications
Abstract: Background: Maternal prepregnancy adiposity may influence child adiposity beyond the transmitted genetic effects, which, if true, may accelerate the obesity epidemic, but the evidence for this mechanism is inconsistent., Objective: The aim was to assess whether the associations of maternal body mass index (BMI) with child anthropometric measurements from birth through infancy and at 7 y of age exceed those of paternal associations., Design: In the Danish National Birth Cohort, information on parental and child anthropometric measures is available for 30,655 trio families from maternal interviews during pregnancy and the postpartum period and from a 7-y follow-up. By using multiple linear and logistic regression models of child SD (z) scores of weight and BMI at birth, 5 mo, 12 mo, and 7 y of age, and of child overweight at age 7 y, we compared associations with maternal prepregnancy and postpartum BMI z scores and with paternal BMI z scores., Results: When comparing maternal-child and paternal-child BMI z score associations, the strongest associations were observed with mothers' BMI at birth [maternal and paternal BMI z scores: 0.143 (95% CI: 0.130, 0.155) and 0.017 (95% CI: 0.005, 0.029), respectively] and throughout infancy, but the relative difference in the associations declined by child age [for BMI z score at child age 7 y per maternal and paternal BMI z scores: 0.208 (95% CI: 0.196, 0.220) and 0.154 (95% CI: 0.143, 0.166), respectively]. At 7 y of age, ORs of child overweight were 2.30 (95% CI: 1.99, 2.67) by maternal overweight and 1.96 (95% CI: 1.74, 2.21) by paternal overweight. There were no differences between the results based on maternal BMI before and after pregnancy or on child's weight adjusted for length or height., Conclusions: The associations of child weight and BMI with maternal BMI were stronger than with paternal BMI. The differences between the associations were strong at birth but declined with child aging., (© 2016 American Society for Nutrition.)
Published: 2016
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34. Childhood body mass index and risk of schizophrenia in relation to childhood age, sex and age of first contact with schizophrenia.

Author: Sørensen HJ, Gamborg M, Sørensen TIA, Baker JL, and Mortensen EL
Subjects: Adolescent, Aged, Child, Cohort Studies, Denmark epidemiology, Female, Humans, Male, Middle Aged, Proportional Hazards Models, Registries statistics & numerical data, Risk Assessment statistics & numerical data, Birth Weight, Body Mass Index, Schizophrenia epidemiology
Abstract: Unlabelled: Childhood leanness is associated with an increased risk of schizophrenia, but the effects of gender, age at anthropometric measurements and age at first diagnosis on this relationship are unclear. The present study aimed at elucidating these associations., Methods: Population-based cohort study with childhood anthropometric measures obtained annually from the age of 7 to 13 years in 253,353 Danes born 1930-1976 and followed to 31 December 2010. During this period, 4936 were registered with schizophrenia. The associations of childhood BMI with risk of schizophrenia were estimated with Cox regression models., Results: Childhood BMI was significantly inversely associated with risk of schizophrenia, however with different patterns among boys and girls. In boys, childhood BMI had an inverse non-linear association with schizophrenia risk dependent on age at diagnosis; in particular, a surprisingly strong association was found between leanness and later onset of schizophrenia. In girls, the risk of schizophrenia decreased linearly with increasing BMI z-score (HR: 0.93; 95% CI: 0.88-0.98). In both boys and girls, birth weight was inversely associated with later risk. In girls, but not in boys, birth weight appeared to significantly modify the associations; there was a somewhat stronger inverse association in the lowest birth weight category., Conclusion: Birth weight as well as childhood BMI at ages 7 through 13 years is associated with risk of schizophrenia in both genders, but with a particular high risk of late-onset in lean boys irrespective of birth weight, and in lean girls with low birth weight. If replicated, these observations may inform preventive efforts build on schizophrenia trajectories rooted in early life., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)
Published: 2016
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35. Road Traffic and Railway Noise Exposures and Adiposity in Adults: A Cross-Sectional Analysis of the Danish Diet, Cancer, and Health Cohort.

Author: Christensen JS, Raaschou-Nielsen O, Tjønneland A, Overvad K, Nordsborg RB, Ketzel M, Sørensen TIa, and Sørensen M
Subjects: Cohort Studies, Cross-Sectional Studies, Denmark epidemiology, Diet, Electric Impedance, Environmental Exposure adverse effects, Female, Housing, Humans, Male, Middle Aged, Obesity epidemiology, Obesity etiology, Adiposity, Body Mass Index, Noise, Transportation adverse effects, Waist Circumference
Abstract: Background: Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight., Objectives: We aimed to investigate the relationship between residential traffic and railway noise and adiposity., Methods: In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993-1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors., Results: Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure-response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0-20 dB)., Conclusions: The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity.
Published: 2016
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36. C-reactive protein levels in relation to various features of non-alcoholic fatty liver disease among obese patients.

Author: Zimmermann E, Anty R, Tordjman J, Verrijken A, Gual P, Tran A, Iannelli A, Gugenheim J, Bedossa P, Francque S, Le Marchand-Brustel Y, Clement K, Van Gaal L, Sørensen TIA, and Jess T
Subjects: Adiposity, Adolescent, Adult, Aged, Biomarkers metabolism, Fatty Liver complications, Female, Humans, Linear Models, Male, Middle Aged, Non-alcoholic Fatty Liver Disease, Obesity complications, Severity of Illness Index, Young Adult, Body Mass Index, C-Reactive Protein metabolism, Fatty Liver metabolism, Fatty Liver pathology, Obesity metabolism
Abstract: Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a major hepatic consequence of obesity. It has been suggested that the high sensitivity C-reactive protein (hs-CRP) is an obesity-independent surrogate marker of severity of NAFLD, especially development of non-alcoholic steato-hepatitis (NASH), but this remains controversial. We aimed to investigate whether associations between various features of NAFLD and hs-CRP are independent of body mass index (BMI) in its broad range among obese patients., Methods: A total of 627 obese adults (80% females), representing three cohorts from France and Belgium, had information on liver histology obtained from liver biopsies and measures of hs-CRP and BMI. We investigated whether the different features of NAFLD and BMI were associated with hs-CRP, with and without mutual adjustments using linear regression., Results: BMI and hs-CRP were strongly associated. Per every 10% increase in BMI the hs-CRP level increased by 19-20% (p<0.001), and adjustment for NAFLD-stage (including no-NAFLD) did not influence the association. We found no BMI-independent association between NASH and hs-CRP. However, a positive association between degree of steatosis and hs-CRP was observed (p<0.05) and this effect remained significant after adjusting for BMI, lobular inflammation, hepatocyte ballooning, and fibrosis. We found no significant associations between the other features of NAFLD and hs-CRP., Conclusions: This study indicates that it is the accumulation of fat -both in the adipose tissue and in liver steatosis- that leads to increased hs-CRP levels among obese patients. Thus, hs-CRP may be a marker of steatosis, but not of severity of NAFLD, in obese patients., (Copyright © 2011 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)
Published: 2011
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37. Combined associations of prepregnancy body mass index and gestational weight gain with the outcome of pregnancy.

Author: Nohr EA, Vaeth M, Baker JL, Sørensen TIa, Olsen J, and Rasmussen KM
Subjects: Adult, Cohort Studies, Denmark, Female, Humans, Interviews as Topic, Obesity physiopathology, Overweight physiopathology, Parity, Pregnancy Trimester, Second, Pregnancy Trimester, Third, Body Mass Index, Pregnancy physiology, Pregnancy Outcome, Weight Gain
Abstract: Background: Although both maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) may affect birth weight, their separate and joint associations with complications of pregnancy and delivery and with postpartum weight retention are unclear., Objectives: We aimed to investigate the combined associations of prepregnancy BMI and GWG with pregnancy outcomes and to evaluate the trade-offs between mother and infant for different weight gains., Design: Data for 60892 term pregnancies in the Danish National Birth Cohort were linked to birth and hospital discharge registers. Self-reported total GWG was categorized as low (<10 kg), medium (10-15 kg), high (16-19 kg), or very high (>or=20 kg). Adjusted associations of prepregnancy BMI and GWG with outcomes of interest were estimated by logistic regression analyses., Results: High and very high GWG added to the associations of high prepregnancy BMI with cesarean delivery and were strongly associated with high postpartum weight retention. Moreover, greater weight gains and high maternal BMI decreased the risk of growth restriction and increased the risk of the infant's being born large-for-gestational-age or with a low Apgar score. Generally, low GWG was advantageous for the mother, but it increased the risk of having a small baby, particularly for underweight women., Conclusions: Heavier women may benefit from avoiding high and very high GWG, which brings only a slight increase in the risk of growth restriction for the infant. High weight gain in underweight women does not appear to have deleterious consequences for them or their infants, but they may want to avoid low GWG to prevent having a small baby.
Published: 2008
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38. Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta‐analysis of European, North American and Australian cohorts

Author: Santos, S, Voerman, E, Amiano, P, Barros, H, Beilin, LJ, Bergström, A, Charles, M‐A, Chatzi, L, Chevrier, C, Chrousos, GP, Corpeleijn, E, Costa, O, Costet, N, Crozier, S, Devereux, G, Doyon, M, Eggesbø, M, Fantini, MP, Farchi, S, Forastiere, F, Georgiu, V, Godfrey, KM, Gori, D, Grote, V, Hanke, W, Hertz‐Picciotto, I, Heude, B, Hivert, M‐F, Hryhorczuk, D, Huang, R‐C, Inskip, H, Karvonen, AM, Kenny, LC, Koletzko, B, Küpers, LK, Lagström, H, Lehmann, I, Magnus, P, Majewska, R, Mäkelä, J, Manios, Y, McAuliffe, FM, McDonald, SW, Mehegan, J, Melén, E, Mommers, M, Morgen, CS, Moschonis, G, Murray, D, Chaoimh, C Ní, Nohr, EA, Andersen, A‐M Nybo, Oken, E, Oostvogels, AJJM, Pac, A, Papadopoulou, E, Pekkanen, J, Pizzi, C, Polanska, K, Porta, D, Richiardi, L, Rifas‐Shiman, SL, Roeleveld, N, Ronfani, L, Santos, AC, Standl, M, Stigum, H, Stoltenberg, C, Thiering, E, Thijs, C, Torrent, M, Tough, SC, Trnovec, T, Turner, S, Gelder, MMHJ, Rossem, L, Berg, A, Vrijheid, M, Vrijkotte, TGM, West, J, Wijga, AH, Wright, J, Zvinchuk, O, Sørensen, TIA, Lawlor, DA, Gaillard, R, and Jaddoe, VWV
Subjects: Obesity, Contraception/Reproduction, Diabetes, Preterm, Low Birth Weight and Health of the Newborn, Infant Mortality, Cardiovascular, Clinical Research, Perinatal Period - Conditions Originating in Perinatal Period, Prevention, Nutrition, Pediatric, Aetiology, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, 2.1 Biological and endogenous factors, Prevention of disease and conditions, and promotion of well-being, Metabolic and endocrine, Reproductive health and childbirth, Good Health and Well Being, Adult, Australia, Birth Weight, Body Mass Index, Cohort Studies, Europe, Female, Gestational Age, Gestational Weight Gain, Humans, Infant, Newborn, North America, Odds Ratio, Overweight, Pregnancy, Pregnancy Complications, Risk Factors, Birthweight, body mass index, pregnancy complications, preterm birth, weight gain, Medical and Health Sciences, Obstetrics & Reproductive Medicine
Abstract: ObjectiveTo assess the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact.DesignIndividual participant data meta-analysis of 39 cohorts.SettingEurope, North America, and Oceania.Population265 270 births.MethodsInformation on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used.Main outcome measuresGestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth.ResultsHigher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes, and large for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared with normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (odds ratio 2.51, 95% CI 2.31- 2.74). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large for gestational age infants was attributable to excessive gestational weight gain.ConclusionsMaternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity.Tweetable abstractPromoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications.
Published: 2019

39. Body mass index trajectories from 2 to 18 years - exploring differences between European cohorts

Author: Graversen, L, Howe, LD, Sørensen, TIA, Sovio, U, Hohwü, L, Tilling, K, Laitinen, J, Taanila, A, Pouta, A, Järvelin, M-R, and Obel, C
Subjects: Male, Parents, child, Pediatric Obesity, Adolescent, ALSPAC, Scandinavian and Nordic Countries, United Kingdom, White People, Body Mass Index, BMI, cohort studies, Pregnancy, Child, Preschool, Ethnicity, Prevalence, Humans, Female, Longitudinal Studies
Abstract: BACKGROUND: In recent decades, there has been an increase in the prevalence of childhood overweight in most high-income countries. Within northern Europe, prevalence tends to be higher in the UK compared with the Scandinavian countries. We aimed to study differences in body mass index (BMI) trajectories between large cohorts of children from UK and Scandinavian populations. METHODS: We compared BMI trajectories in participants from the English Avon Longitudinal Study of Parents and Children born in 1991-1993 (ALSPAC) (N = 6517), the Northern Finland Birth Cohorts born in 1966 (NFBC1966) (N = 3321) and 1986 (NFBC1986) (N = 4764), and the Danish Aarhus Birth Cohort born in 1990-1992 (ABC) (N = 1920). We used multilevel models to estimate BMI trajectories from 2 to 18 years. We explored whether cohort differences were explained by maternal BMI, height, education or smoking during pregnancy and whether differences were attributable to changes in the degree of skew in the BMI distribution. RESULTS: Differences in mean BMI between the cohorts were small but emerged early and persisted in most cases across childhood. Girls in ALSPAC had a higher BMI than all other cohorts throughout childhood, e.g. compared with the NFBC1986 BMI was 2.2-3.5% higher. For boys, the difference emerging over time (comparing the two NFBC's) exceeded the differences across populations (comparing NFBC1986, ABC and ALSPAC). BMI distribution demonstrated increasing right skew with age. CONCLUSION: Population-level differences between cohorts were small, tended to emerge very early, persisted across childhood, and demonstrated an increase in the right-hand tail of the BMI distribution.
Published: 2020
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40. Body mass index trajectories from 2 to 18 years - exploring differences between European cohorts

Author: Graversen, L, Howe, LD, Sørensen, TIA, Sovio, U, Hohwü, L, Tilling, K, Laitinen, J, Taanila, A, Pouta, A, Järvelin, M-R, Obel, C, Sovio, Ulla [0000-0002-0799-1105], and Apollo - University of Cambridge Repository
Subjects: Male, Parents, child, Pediatric Obesity, Adolescent, ALSPAC, Scandinavian and Nordic Countries, United Kingdom, White People, Body Mass Index, BMI, cohort studies, Pregnancy, Child, Preschool, Ethnicity, Prevalence, Humans, Female, Longitudinal Studies
Abstract: BACKGROUND: In recent decades, there has been an increase in the prevalence of childhood overweight in most high-income countries. Within northern Europe, prevalence tends to be higher in the UK compared with the Scandinavian countries. We aimed to study differences in body mass index (BMI) trajectories between large cohorts of children from UK and Scandinavian populations. METHODS: We compared BMI trajectories in participants from the English Avon Longitudinal Study of Parents and Children born in 1991-1993 (ALSPAC) (N = 6517), the Northern Finland Birth Cohorts born in 1966 (NFBC1966) (N = 3321) and 1986 (NFBC1986) (N = 4764), and the Danish Aarhus Birth Cohort born in 1990-1992 (ABC) (N = 1920). We used multilevel models to estimate BMI trajectories from 2 to 18 years. We explored whether cohort differences were explained by maternal BMI, height, education or smoking during pregnancy and whether differences were attributable to changes in the degree of skew in the BMI distribution. RESULTS: Differences in mean BMI between the cohorts were small but emerged early and persisted in most cases across childhood. Girls in ALSPAC had a higher BMI than all other cohorts throughout childhood, e.g. compared with the NFBC1986 BMI was 2.2-3.5% higher. For boys, the difference emerging over time (comparing the two NFBC's) exceeded the differences across populations (comparing NFBC1986, ABC and ALSPAC). BMI distribution demonstrated increasing right skew with age. CONCLUSION: Population-level differences between cohorts were small, tended to emerge very early, persisted across childhood, and demonstrated an increase in the right-hand tail of the BMI distribution.
Published: 2017

41. The relation between drinking pattern and body mass index and waist and hip circumference.

Author: Tolstrup, JS, Heitmann, BL, Tjønneland, AM, Overvad, OK, Sørensen, TIA, and Grønbæk, MN
Subjects: OBESITY, NUTRITION disorders, ALCOHOL drinking, METABOLIC disorders, OVERWEIGHT persons, BODY weight
Abstract: OBJECTIVES:: To study the association between alcohol drinking pattern and obesity. DESIGN:: Cross-sectional population study with assessment of quantity and frequency of alcohol intake, waist and hip circumference, height, weight, and lifestyle factors including diet. SUBJECTS:: In all, 25?325 men and 24?552 women aged 50-65?y from the Diet, Cancer and Health Study, Denmark, 1993-1997 participated in the study. MEASUREMENTS:: Drinking frequency, total alcohol intake, body mass index (BMI), and waist and hip circumference. RESULTS:: Among men, total alcohol intake was positively associated with high BMI (=30?kg/m2), large waist circumference (=102?cm) and inversely associated with small hip circumference (<100?cm). Among women, the total alcohol was associated with high BMI, large waist (=88?cm), and small hips only for the highest intake (28+drinks/week). The most frequent drinkers had the lowest odds ratios (OR) for being obese. Among men, OR for having a high BMI were 1.39 (95%confidence interval: 1.36-1.64), 1.17 (1.02-1.34), 1.00 (reference), 0.87 (0.77-0.98), and 0.73 (0.65-0.82) for drinking 1-3 days/month, 1 day/week, 2-4 days/week, 5-6 days/week, and 7 days/week, respectively. Similar estimates were found for waist circumference. Corresponding results were found for women. CONCLUSION:: For a given level of total alcohol intake, obesity was inversely associated with drinking frequency, whereas the amount of alcohol intake was positively associated with obesity. These results indicate that frequent drinking of small amounts of alcohol is the optimal drinking pattern in this relation.International Journal of Obesity (2005) 29, 490-497. doi:10.1038/sj.ijo.0802874 Published online 11 January 2005 [ABSTRACT FROM AUTHOR]
Published: 2005
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42. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author: Justice, AE, Winkler, TW, Feitosa, MF, Graff, M, Fisher, VA, Young, K, Barata, L, Deng, X, Czajkowski, J, Hadley, D, Ngwa, JS, Ahluwalia, TS, Chu, AY, Heard-Costa, NL, Lim, E, Perez, J, Eicher, JD, Kutalik, Z, Xue, L, Mahajan, A, Renström, F, Wu, J, Qi, Q, Ahmad, S, Alfred, T, Amin, N, Bielak, LF, Bonnefond, A, Bragg, J, Cadby, G, Chittani, M, Coggeshall, S, Corre, T, Direk, N, Eriksson, J, Fischer, K, Gorski, M, Neergaard Harder, M, Horikoshi, M, Huang, T, Huffman, JE, Jackson, AU, Justesen, JM, Kanoni, S, Kinnunen, L, Kleber, ME, Komulainen, P, Kumari, M, Lim, U, Luan, J, Lyytikäinen, L-P, Mangino, M, Manichaikul, A, Marten, J, Middelberg, RPS, Müller-Nurasyid, M, Navarro, P, Pérusse, L, Pervjakova, N, Sarti, C, Smith, AV, Smith, JA, Stančáková, A, Strawbridge, RJ, Stringham, HM, Sung, YJ, Tanaka, T, Teumer, A, Trompet, S, Van Der Laan, SW, Van Der Most, PJ, Van Vliet-Ostaptchouk, JV, Vedantam, SL, Verweij, N, Vink, JM, Vitart, V, Wu, Y, Yengo, L, Zhang, W, Hua Zhao, J, Zimmermann, ME, Zubair, N, Abecasis, GR, Adair, LS, Afaq, S, Afzal, U, Bakker, SJL, Bartz, TM, Beilby, J, Bergman, RN, Bergmann, S, Biffar, R, Blangero, J, Boerwinkle, E, Bonnycastle, LL, Bottinger, E, Braga, D, Buckley, BM, Buyske, S, Campbell, H, Chambers, JC, Collins, FS, Curran, JE, De Borst, GJ, De Craen, AJM, De Geus, EJC, Dedoussis, G, Delgado, GE, Den Ruijter, HM, Eiriksdottir, G, Eriksson, AL, Esko, T, Faul, JD, Ford, I, Forrester, T, Gertow, K, Gigante, B, Glorioso, N, Gong, J, Grallert, H, Grammer, TB, Grarup, N, Haitjema, S, Hallmans, G, Hamsten, A, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, ND, Heath, AC, Hernandez, D, Hindorff, L, Hocking, LJ, Hollensted, M, Holmen, OL, Homuth, G, Jan Hottenga, J, Huang, J, Hung, J, Hutri-Kähönen, N, Ingelsson, E, James, AL, Jansson, J-O, Jarvelin, M-R, Jhun, MA, Jørgensen, ME, Juonala, M, Kähönen, M, Karlsson, M, Koistinen, HA, Kolcic, I, Kolovou, G, Kooperberg, C, Krämer, BK, Kuusisto, J, Kvaløy, K, Lakka, TA, Langenberg, C, Launer, LJ, Leander, K, Lee, NR, Lind, L, Lindgren, CM, Linneberg, A, Lobbens, S, Loh, M, Lorentzon, M, Luben, R, Lubke, G, Ludolph-Donislawski, A, Lupoli, S, Madden, PAF, Männikkö, R, Marques-Vidal, P, Martin, NG, McKenzie, CA, McKnight, B, Mellström, D, Menni, C, Montgomery, GW, Musk, AB, Narisu, N, Nauck, M, Nolte, IM, Oldehinkel, AJ, Olden, M, Ong, KK, Padmanabhan, S, Peyser, PA, Pisinger, C, Porteous, DJ, Raitakari, OT, Rankinen, T, Rao, DC, Rasmussen-Torvik, LJ, Rawal, R, Rice, T, Ridker, PM, Rose, LM, Bien, SA, Rudan, I, Sanna, S, Sarzynski, MA, Sattar, N, Savonen, K, Schlessinger, D, Scholtens, S, Schurmann, C, Scott, RA, Sennblad, B, Siemelink, MA, Silbernagel, G, Slagboom, PE, Snieder, H, Staessen, JA, Stott, DJ, Swertz, MA, Swift, AJ, Taylor, KD, Tayo, BO, Thorand, B, Thuillier, D, Tuomilehto, J, Uitterlinden, AG, Vandenput, L, Vohl, M-C, Völzke, H, Vonk, JM, Waeber, G, Waldenberger, M, Westendorp, RGJ, Wild, S, Willemsen, G, Wolffenbuttel, BHR, Wong, A, Wright, AF, Zhao, W, Zillikens, MC, Baldassarre, D, Balkau, B, Bandinelli, S, Böger, CA, Boomsma, DI, Bouchard, C, Bruinenberg, M, Chasman, DI, Chen, Y-D, Chines, PS, Cooper, RS, Cucca, F, Cusi, D, Faire, UD, Ferrucci, L, Franks, PW, Froguel, P, Gordon-Larsen, P, Grabe, H-J, Gudnason, V, Haiman, CA, Hayward, C, Hveem, K, Johnson, AD, Wouter Jukema, J, Kardia, SLR, Kivimaki, M, Kooner, JS, Kuh, D, Laakso, M, Lehtimäki, T, Marchand, LL, März, W, McCarthy, MI, Metspalu, A, Morris, AP, Ohlsson, C, Palmer, LJ, Pasterkamp, G, Pedersen, O, Peters, A, Peters, U, Polasek, O, Psaty, BM, Qi, L, Rauramaa, R, Smith, BH, Sørensen, TIA, Strauch, K, Tiemeier, H, Tremoli, E, Van Der Harst, P, Vestergaard, H, Vollenweider, P, Wareham, NJ, Weir, DR, Whitfield, JB, Wilson, JF, Tyrrell, J, Frayling, TM, Barroso, I, Boehnke, M, Deloukas, P, Fox, CS, Hirschhorn, JN, Hunter, DJ, Spector, TD, Strachan, DP, Van Duijn, CM, Heid, IM, Mohlke, KL, Marchini, J, Loos, RJF, Kilpeläinen, TO, Liu, C-T, Borecki, IB, North, KE, and Cupples, LA
Subjects: Adult, Waist-Hip Ratio, Quantitative Trait Loci, Smoking, Epistasis, Genetic, Polymorphism, Single Nucleotide, 3. Good health, Body Mass Index, Phenotype, Body Fat Distribution, Humans, Genetic Predisposition to Disease, Obesity, Waist Circumference, Adiposity, Genome-Wide Association Study
Abstract: Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

43. Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Author: Bixby, Honor, Bentham, James, Zhou, Bin, Di Cesare, Mariachiara, Paciorek, Christopher J., Bennett, James E., Taddei, Cristina, Stevens, Gretchen A., Rodriguez-Martinez, Andrea, Carrillo-Larco, Rodrigo M., Khang, Young-Ho, Soric, Maroje, Gregg, Edward W., Miranda, J. Jaime, Bhutta, Zulfiqar A., Savin, Stefan, Sophiea, Marisa K., Iurilli, Maria L. C., Solomon, Bethlehem D., Cowan, Melanie J., Riley, Leanne M., Danaei, Goodarz, Bovet, Pascal, Chirita-Emandi, Adela, Hambleton, Ian R., Hayes, Alison J., Ikeda, Nayu, Kengne, Andre P., Laxmaiah, Avula, Li, Yanping, McGarvey, Stephen T., Mostafa, Aya, Neovius, Martin, Starc, Gregor, Zainuddin, Ahmad A., Abarca-Gomez, Leandra, Abdeen, Ziad A., Abdrakhmanova, Shynar, Ghaffar, Suhaila Abdul, Hamid, Zargar Abdul, Garba, Jamila Abubakar, Abu-Rmeileh, Niveen M., Acosta-Cazares, Benjamin, Adams, Robert J., Aekplakorn, Wichai, Afsana, Kaosar, Agdeppa, Imelda A., Aguilar-Salinas, Carlos A., Agyemang, Charles, Ahmad, Mohamad Hasnan, Ahmad, Noor Ani, Ahmadi, Naser, Ahmadvand, Alireza, Ahrens, Wolfgang, Ajlouni, Kamel, AlBuhairan, Fadia, AlDhukair, Shahla, Al-Hazzaa, Hazzaa M., Ali, Mohamed M., Ali, Osman, Alkerwi, Ala'a, Al-Othman, Amani Rashed, Al-Raddadi, Rajaa, Alvarez-Pedrerol, Mar, Aly, Eman, Amarapurkar, Deepak N., Amouyel, Philippe, Amuzu, Antoinette, Bo, Lars, Anderssen, Sigmund A., Angquist, Lars H., Anjana, Ranjit Mohan, Ansari-Moghaddam, Alireza, Aounallah-Skhiri, Hajer, Araujo, Joana, Ariansen, Inger, Aris, Tahir, Arku, Raphael E., Arlappa, Nimmathota, Aryal, Krishna K., Aspelund, Thor, Assah, Felix K., Assuncao, Maria Cecilia F., Aung, May Soe, Auvinen, Juha, Avdicova, Maria, Azevedo, Ana, Azizi, Fereidoun, Azmin, Mehrdad, Babu, Bontha V., Baharudin, Azli, Bahijri, Suhad, Baker, Jennifer L., Balakrishna, Nagalla, Bamoshmoosh, Mohamed, Banach, Maciej, Bandosz, Piotr, Banegas, Jose R., Barbagallo, Carlo M., Barcelo, Alberto, Barkat, Amina, Barros, Aluisio J. D., Barros, Mauro V. G., Bata, Iqbal, Batieha, Anwar M., Batista, Rosangela L., Battakova, Zhamilya, Batyrbek, Assembekov, Baur, Louise A., Beaglehole, Robert, Bel-Serrat, Silvia, Ben Romdhane, Habiba, Benedics, Judith, Benet, Mikhail, Berkinbayev, Salim, Bernabe-Ortiz, Antonio, Bernotiene, Gailute, Bettiol, Heloisa, Bhagyalaxmi, Aroor, Bharadwaj, Sumit, Bhargava, Santosh K., Bi, Hongsheng, Bi, Yufang, Biehl, Anna, Lele, Elysee Claude Bika, Bikbov, Mukharram, Bista, Bihungum, Bjelica, Dusko J., Bjerregaard, Peter, Bjertness, Espen, Bjertness, Marius B., Bjorkelund, Cecilia, Blokstra, Anneke, Bo, Simona, Bobak, Martin, Boddy, Lynne M., Boehm, Bernhard O., Boeing, Heiner, Boggia, Jose G., Boissonnet, Carlos P., Bonaccio, Marialaura, Bongard, Vanina, Bopp, Matthias, Borchini, Rossana, Borghs, Herman, Braeckevelt, Lien, Braeckman, Lutgart, Bragt, Marjolijn C. E., Brajkovich, Imperia, Branca, Francesco, Breckenkamp, Juergen, Breda, Joao, Brenner, Hermann, Brewster, Lizzy M., Brian, Garry R., Brinduse, Lacramioara, Bruno, Graziella, Bueno-de-Mesquita, H. Bas, Bugge, Anna, Buoncristiano, Marta, Burazeri, Genc, Burns, Con, Cabrera de Leon, Antonio, Cacciottolo, Joseph, Cai, Hui, Cama, Tilema, Cameron, Christine, Camolas, Jose, Can, Gamze, Can, Gunay, Candido, Ana Paula C., Canete, Felicia, Capanzana, Mario V., Capuano, Eduardo, Capuano, Vincenzo, Cardoso, Viviane C., Carlsson, Axel C., Carmuega, Esteban, Carvalho, Maria J., Casanueva, Felipe F., Casas, Juan-Pablo, Caserta, Carmelo A., Celikcan, Ertugrul, Censi, Laura, Cesar, Juraci A., Chamukuttan, Snehalatha, Chan, Angelique W., Chan, Queenie, Chaturvedi, Himanshu K., Chaturvedi, Nishi, Rahim, Norsyamlina Che Abdul, Chen, Chien-Jen, Chen, Fangfang, Chen, Huashuai, Chen, Shuohua, Chen, Zhengming, Cheng, Ching-Yu, Cheng, Yiling J., Chetrit, Angela, Chikova-Iscener, Ekaterina, Chiolero, Arnaud, Chiou, Shu-Ti, Chirlaque, Maria-Dolores, Cho, Belong, Cho, Yumi, Christensen, Kaare, Christofaro, Diego G., Chudek, Jerzy, Cifkova, Renata, Cilia, Michelle, Cinteza, Eliza, Claessens, Frank, Clarke, Janine, Clays, Els, Concin, Hans, Confortin, Susana C., Cooper, Cyrus, Coppinger, Tara C., Costanzo, Simona, Cottel, Dominique, Cowell, Chris, Craig, Cora L., Crampin, Amelia C., Crujeiras, Ana B., Cruz, Juan J., Cucu, Alexandra, Cui, Liufu, Dallongeville, Jean, Damasceno, Albertino, Damsgaard, Camilla T., Dankner, Rachel, Dantoft, Thomas M., D'Arrigo, Graziella, Dasgupta, Parasmani, Dastgiri, Saeed, Dauchet, Luc, Davletov, Kairat, De Backer, Guy, De Bacquer, Dirk, De Curtis, Amalia, de Gaetano, Giovanni, De Henauw, Stefaan, de Oliveira, Paula Duarte, De Ridder, Karin, de Rooij, Susanne R., De Smedt, Delphine, Deepa, Mohan, Deev, Alexander D., Dehghan, Abbas, Delisle, Helene, Delpeuch, Francis, Dennison, Elaine, Deschamps, Valerie, Dhana, Klodian, Dhimal, Meghnath, Di Castelnuovo, Augusto F., Dias-da-Costa, Juvenal Soares, Diaz, Alejandro, Dika, Zivka, Djalalinia, Shirin, Do, Ha T. P., Dobson, Annette J., Donati, Maria Benedetta, Donfrancesco, Chiara, Donoso, Silvana P., Doering, Angela, Dorobantu, Maria, Dorosty, Ahmad Reza, d'Orsi, Eleonora, Doua, Kouamelan, Drygas, Wojciech, Duan, Jia Li, Duante, Charmaine A., Duda, Rosemary B., Duleva, Vesselka, Dulskiene, Virginija, Dumith, Samuel C., Dzerve, Vilnis, Dziankowska-Zaborszczyk, Elzbieta, Eddie, Ricky, Egbagbe, Eruke E., Eggertsen, Robert, Eiben, Gabriele, Ekelund, Ulf, El Ati, Jalila, Eldemire-Shearer, Denise, Eliasen, Marie, Elliott, Paul, Engle-Stone, Reina, Erasmus, Rajiv T., Erem, Cihangir, Eriksen, Louise, Eriksson, Johan G., Escobedo-de la Pena, Jorge, Evans, Alun, Faeh, David, Fall, Caroline H., Sant'Angelo, Victoria Farrugia, Farzadfar, Farshad, Fattahi, Mohammad R., Felix-Redondo, Francisco J., Ferguson, Trevor S., Fernandes, Romulo A., Fernandez-Berges, Daniel, Ferrante, Daniel, Ferrari, Marika, Ferreccio, Catterina, Ferrer, Eldridge, Ferrieres, Jean, Fijalkowska, Anna, Fink, Gunther, Fischer, Krista, Flores, Eric Monterubio, Foeger, Bernhard, Foo, Leng Huat, Forslund, Ann-Sofie, Forsner, Maria, Fouad, Heba M., Francis, Damian K., Franco, Maria do Carmo, Franco, Oscar H., Frontera-Juan, Guillem, Fuchs, Flavio D., Fuchs, Sandra C., Fujita, Yuki, Furusawa, Takuro, Gaciong, Zbigniew, Gafencu, Mihai, Galeone, Daniela, Galvano, Fabio, Gao, Jingli, Garcia-de-la-Hera, Manoli, Gareta, Dickman, Garnett, Sarah P., Gaspoz, Jean-Michel, Gasull, Magda, Gates, Louise, Gazzinelli, Andrea, Geiger, Harald, Geleijnse, Johanna M., Ghanbari, Ali, Ghasemi, Erfan, Ghasemian, Anoosheh, Gheorghe-Fronea, Oana-Florentina, Giampaoli, Simona, Gianfagna, Francesco, Gill, Tiffany K., Giovannelli, Jonathan, Gironella, Glen, Giwercman, Aleksander, Godos, Justyna, Gogen, Sibel, Goldsmith, Rebecca A., Goltzman, David, Goncalves, Helen, Gonzalez, Angel R., Gonzalez-Chica, David A., Gonzalez-Gross, Marcela, Gonzalez-Leon, Margot, Gonzalez-Rivas, Juan P., Gonzalez-Villalpando, Maria-Elena, Gottrand, Frederic, Graca, Antonio Pedro, Graff-Iversen, Sidsel, Grafnetter, Dusan, Grajda, Aneta, Grammatikopoulou, Maria G., Gregor, Ronald D., Grodzicki, Tomasz, Grontved, Anders, Grosso, Giuseppe, Gruden, Gabriella, Gu, Dongfeng, Gualdi-Russo, Emanuela, Gudmundsson, Elias F., Gudnason, Vilmundur, Guerrero, Ramiro, Guessous, Idris, Guimaraes, Andre L., Gulliford, Martin C., Gunnlaugsdottir, Johanna, Gunter, Marc, Guo, Xiuhua, Guo, Yin, Gupta, Prakash C., Gupta, Rajeev, Gureje, Oye, Gurzkowska, Beata, Gutierrez, Laura, Gutzwiller, Felix, Hadaegh, Farzad, Hadjigeorgiou, Charalambos A., Haghshenas, Rosa, Halkjaer, Jytte, Hardy, Rebecca, Kumar, Rachakulla Hari, Hassapidou, Maria, Hata, Jun, Haugsgjerd, Teresa, He, Jiang, He, Yuna, Heidinger-Felso, Regina, Heinen, Mirjam, Hejgaard, Tatjana, Hendriks, Marleen Elisabeth, Henriques, Ana, Hernandez Cadena, Leticia, Herrala, Sauli, Herrera, Victor M., Herter-Aeberli, Isabelle, Heshmat, Ramin, Hill, Allan G., Ho, Sai Yin, Ho, Suzanne C., Hobbs, Michael, Hofman, Albert, Hopman, Wilma M., Horimoto, Andrea R. V. R., Hormiga, Claudia M., Horta, Bernardo L., Houti, Leila, Howitt, Christina, Htay, Thein Thein, Htet, Aung Soe, Htike, Maung Maung Than, Hu, Yonghua, Huerta, Jose Maria, Huhtaniemi, Ilpo Tapani, Petrescu, Constanta Huidumac, Huisman, Martijn, Husseini, Abdullatif, Chinh Nguyen Huu, Huybrechts, Inge, Hwalla, Nahla, Hyska, Jolanda, Iacoviello, Licia, Ibarluzea, Jesus M., Ibrahim, Mohsen M., Wong, Norazizah Ibrahim, Ikram, M. Arfan, Irazola, Vilma E., Ishida, Takafumi, Islam, Muhammad, Ismail, Aziz al-Safi, Ivkovic, Vanja, Iwasaki, Masanori, Jaaskelainen, Tuija, Jackson, Rod T., Jacobs, Jeremy M., Jaddou, Hashem, Jafar, Tazeen, James, Kenneth, Jamil, Kazi M., Jamrozik, Konrad, Janszky, Imre, Janus, Edward, Jarani, Juel, Jarvelin, Marjo-Riitta, Jasienska, Grazyna, Jelakovic, Ana, Jelakovic, Bojan, Jennings, Garry, Jeong, Seung-Lyeal, Jiang, Chao Qiang, Jimenez, Ramon O., Joffres, Michel, Johansson, Mattias, Jokelainen, Jari J., Jonas, Jost B., Jorgensen, Torben, Joshi, Pradeep, Jovic, Dragana P., Jozwiak, Jacek, Juolevi, Anne, Jurak, Gregor, Juresa, Vesna, Kaaks, Rudolf, Kafatos, Anthony, Kajantie, Eero O., Kalter-Leibovici, Ofra, Kamaruddin, Nor Azmi, Kameli, Yves, Kapantais, Efthymios, Karki, Khem B., Kasaeian, Amir, Katibeh, Marzieh, Katz, Joanne, Katzmarzyk, Peter T., Kauhanen, Jussi, Kaur, Prabhdeep, Kavousi, Maryam, Kazakbaeva, Gyulli, Keil, Ulrich, Keinan-Boker, Lital, Keinanen-Kiukaanniemi, Sirkka, Kelishadi, Roya, Kelleher, Cecily, Kemper, Han C. G., Kerimkulova, Alina, Kersting, Mathilde, Key, Timothy, Khader, Yousef Saleh, Khalili, Davood, Khateeb, Mohammad, Khaw, Kay-Tee, Kheiri, Bahareh, Khosravi, Alireza, Khouw, Ilse M. S. L., Kiechl, Stefan, Kiechl-Kohlendorfer, Ursula, Killewo, Japhet, Kim, Jeongseon, Kim, Yeon-Yong, Klimont, Jeannette, Klumbiene, Jurate, Knoflach, Michael, Koirala, Bhawesh, Kolle, Elin, Kolsteren, Patrick, Koenig, Jurgen, Korpelainen, Raija, Korrovits, Paul, Korzycka, Magdalena, Koskinen, Seppo, Kouda, Katsuyasu, Kovacs, Viktoria A., Kowlessur, Sudhir, Koziel, Slawomir, Kratzer, Wolfgang, Kriemler, Susi, Kristensen, Peter Lund, Krokstad, Steinar, Kromhout, Daan, Kruger, Herculina S., Kubinova, Ruzena, Kuciene, Renata, Kuh, Diana, Kujala, Urho M., Kujundzic, Enisa, Kulaga, Zbigniew, Kumar, R. Krishna, Kunesova, Marie, Kurjata, Pawel, Kusuma, Yadlapalli S., Kuulasmaa, Kari, Kyobutungi, Catherine, Quang Ngoc La, Laamiri, Fatima Zahra, Laatikainen, Tiina, Lachat, Carl, Laid, Youcef, Tai Hing Lam, Morovic, Maja Lang, Lanska, Vera, Lappas, Georg, Larijani, Bagher, Latt, Tint Swe, Laugsand, Lars E., Lauria, Laura, Lazo-Porras, Maria, Khanh Le Nguyen Bao, Le Port, Agnes, Le, Tuyen D., Lee, Jeannette, Lee, Jeonghee, Lee, Paul H., Lehtimaki, Terho, Lemogoum, Daniel, Levitt, Naomi S., Lilly, Christa L., Lim, Wei-Yen, Lima-Costa, M. Fernanda, Lin, Hsien-Ho, Lin, Xu, Lind, Lars, Linneberg, Allan, Lissner, Lauren, Litwin, Mieczyslaw, Liu, Jing, Loit, Helle-Mai, Lopes, Luis, Lopez, Tania, Lopez-Garcia, Esther, Lorbeer, Roberto, Lotufo, Paulo A., Lozano, Jose Eugenio, Luksiene, Dalia, Lundqvist, Annamari, Lundqvist, Robert, Lunet, Nuno, Lytsy, Per, Ma, Guansheng, Ma, Jun, Machado-Coelho, George L. L., Machado-Rodrigues, Aristides M., Machi, Suka, Maggi, Stefania, Magliano, Dianna J., Magriplis, Emmanuella, Maire, Bernard, Majer, Marjeta, Makdisse, Marcia, Malekzadeh, Fatemeh, Malekzadeh, Reza, Malhotra, Rahul, Malyutina, Sofia, Maniego, Lynell V., Manios, Yannis, Mann, Jim I., Manzato, Enzo, Margozzini, Paula, Markaki, Anastasia, Markey, Oonagh, Ioannidou, Eliza Markidou, Marques, Larissa Pruner, Marques-Vidal, Pedro, Marrugat, Jaume, Martin, Rosemarie, Martin-Prevel, Yves, Martorell, Reynaldo, Martos, Eva, Marventano, Stefano, Masoodi, Shariq R., Mathiesen, Ellisiv B., Mathur, Prashant, Matijasevich, Alicia, Matsha, Tandi E., Mazur, Artur, Mbanya, Jean Claude N., McFarlane, Shelly R., Mckee, Martin, McLachlan, Stela, McLean, Rachael M., McLean, Scott B., McNulty, Breige A., Yusof, Safiah Md, Mediene-Benchekor, Sounnia, Medzioniene, Jurate, Mehdipour, Parinaz, Meirhaeghe, Aline, Meisfjord, Jorgen, Meisinger, Christa, Menezes, Ana Maria B., Menon, Geetha R., Mensink, Gert B. M., Mereke, Alibek, Meshram, Indrapal I., Metspalu, Andres, Meyer, Haakon E., Mi, Jie, Michaelsen, Kim F., Michels, Nathalie, Mikkel, Kairit, Miller, Jody C., Minderico, Claudia S., Francisco Miquel, Juan, Mirkopoulou, Daphne, Mirrakhimov, Erkin, Misigoj-Durakovic, Marjeta, Mistretta, Antonio, Mocanu, Veronica, Modesti, Pietro A., Moghaddam, Sahar Saeeidi, Mohajer, Bahram, Mohamed, Mostafa K., Mohammad, Kazem, Mohammadifard, Noushin, Mohan, Viswanathan, Mohanna, Salim, Yusoff, Muhammad Fadhli Mohd, Mohebi, Farnam, Moitry, Marie, Molbo, Drude, Mollehave, Line T., Moller, Niels C., Molnar, Denes, Momenan, Amirabbas, Mondo, Charles K., Monterrubio, Eric A., Monyeki, Kotsedi Daniel K., Moon, Jin Soo, Moreira, Leila B., Morejon, Alain, Moreno, Luis A., Morgan, Karen, Morin, Suzanne, Mortensen, Erik Lykke, Moschonis, George, Mossakowska, Malgorzata, Mota, Jorge, Mota-Pinto, Anabela, Motlagh, Mohammad Esmaeel, Motta, Jorge, Msyamboza, Kelias P., Mu, Thet Thet, Muc, Magdalena, Mugosa, Boban, Muiesan, Maria Lorenza, Mukhtorova, Parvina, Mueller-Nurasyid, Martina, Murphy, Neil, Mursu, Jaakko, Murtagh, Elaine M., Milanovic, Sanja Music, Musil, Vera, Nabipour, Iraj, Naderimagham, Shohreh, Nagel, Gabriele, Naidu, Balkish M., Nakamura, Harunobu, Namesna, Jana, Nang, Ei Ei K., Nangia, Vinay B., Nankap, Martin, Narake, Sameer, Nardone, Paola, Nauck, Matthias, Navarrete-Munoz, Eva Maria, Neal, William A., Nelis, Keiu, Nelis, Liis, Nenko, Ilona, Nervi, Flavio, Nguyen, Chung T., Nguyen, Nguyen D., Quang Ngoc Nguyen, Nieto-Martinez, Ramfis E., Ning, Guang, Ninomiya, Toshiharu, Nishtar, Sania, Noale, Marianna, Noboa, Oscar A., Norat, Teresa, Norie, Sawada, Noto, Davide, Al Nsour, Mohannad, Nurk, Eha, Nyirenda, Moffat, Obreja, Galina, Ochoa-Aviles, Angelica M., Oda, Eiji, Oh, Kyungwon, Ohara, Kumiko, Ohtsuka, Ryutaro, Olafsson, Orn, Anselmo Olinto, Maria Teresa, Oliveira, Isabel O., Oltarzewski, Maciej, Omar, Mohd Azahadi, Onat, Altan, O'Neill, Terence W., Ong, Sok King, Ono, Lariane M., Ordunez, Pedro, O'Reilly, Dermot, Ornelas, Rui, Ortiz, Ana P., Ortiz, Pedro J., Osler, Merete, Osmond, Clive, Ostojic, Sergej M., Ostovar, Afshin, Otero, Johanna A., Overvad, Kim, Owusu-Dabo, Ellis, Paccaud, Fred Michel, Padez, Cristina, Pagkalos, Ioannis, Pahomova, Elena, Pajak, Andrzej, Palli, Domenico, Palloni, Alberto, Palmieri, Luigi, Pan, Wen-Harn, Panda-Jonas, Songhomitra, Pandey, Arvind, Panza, Francesco, Papandreou, Dimitrios, Park, Soon-Woo, Parnell, Winsome R., Parsaeian, Mahboubeh, Pascanu, Ionela M., Patel, Nikhil D., Pecin, Ivan, Pednekar, Mangesh S., Peer, Nasheeta, Peixoto, Sergio Viana, Peltonen, Markku, Pereira, Alexandre C., Perez, Cynthia M., Perez-Farinos, Napoleon, Peters, Annette, Petersmann, Astrid, Petkeviciene, Janina, Petrauskiene, Ausra, Peykari, Niloofar, Son Thai Pham, Pierannunzio, Daniela, Pigeot, Iris, Pikhart, Hynek, Pilav, Aida, Pilotto, Lorenza, Pistelli, Francesco, Pitakaka, Freda, Piwonska, Aleksandra, Plans-Rubio, Pedro, Poh, Bee Koon, Pohlabeln, Hermann, Pop, Raluca M., Popovic, Stevo R., Porta, Miquel, Portegies, Marileen L. P., Posch, Georg, Poulimeneas, Dimitrios, Pouraram, Hamed, Pourshams, Akram, Poustchi, Hossein, Pradeepa, Rajendra, Price, Alison J., Price, Jacqueline F., Puder, Jardena J., Pudule, Iveta, Puhakka, Soile E., Puiu, Maria, Punab, Margus, Qasrawi, Radwan F., Qorbani, Mostafa, Tran Quoc Bao, Radhika, Madhari S., Radic, Ivana, Radisauskas, Ricardas, Rahman, Mahfuzar, Rahman, Mahmudur, Raitakari, Olli, Raj, Manu, Rajkumar, Hemalatha, Rakhmatulloev, Sherali, Rao, Sudha Ramachandra, Ramachandran, Ambady, Ramke, Jacqueline, Ramos, Elisabete, Ramos, Rafel, Rampal, Lekhraj, Rampal, Sanjay, Rao, Kodavanti Mallikharjuna, Rascon-Pacheco, Ramon A., Rasmussen, Mette, Redon, Josep, Reganit, Paul Ferdinand M., Regecova, Valeria, Revilla, Luis, Ribas-Barba, Lourdes, Ribeiro, Robespierre, Riboli, Elio, Rigo, Fernando, Rinaldo, Natascia, de Wit, Tobias F. Rinke, Rito, Ana, Ritti-Dias, Raphael M., Rivera, Juan A., Robitaille, Cynthia, Rodrigues, Daniela, Rodriguez-Artalejo, Fernando, del Cristo Rodriguez-Perez, Maria, Rodriguez-Villamizar, Laura A., Rojas-Martinez, Rosalba, Rojroongwasinkul, Nipa, Romaguera, Dora, Rosengren, Annika, Rouse, Ian, Roy, Joel G. R., Rubinstein, Adolfo, Ruhli, Frank J., Ruidavets, Jean-Bernard, Ruiz Moreno, Emma, Sandra Ruiz-Betancourt, Blanca, Russo, Paola, Rust, Petra, Rutkowski, Marcin, Sabanayagam, Charumathi, Sachdev, Harshpal S., Safiri, Saeid, Saidi, Olfa, Salanave, Benoit, Salazar-Martinez, Eduardo, Salmeron, Diego, Salomaa, Veikko, Salonen, Jukka T., Salvetti, Massimo, Sanchez-Abanto, Jose, Sandjaja, Sans, Susana, Santa-Marina, Loreto, Santos, Diana A., Santos, Ina S., Santos, Osvaldo, Santos, Rute, Santos Sanz, Sara, Saramies, Jouko L., Sardinha, Luis B., Sarrafzadegan, Nizal, Saum, Kai-Uwe, Savva, Savvas, Savy, Mathilde, Scazufca, Marcia, Rosario, Angelika Schaffrath, Schargrodsky, Herman, Schienkiewitz, Anja, Schindler, Karin, Schipf, Sabine, Schmidt, Carsten O., Schmidt, Ida Maria, Schoettker, Ben, Schultsz, Constance, Schutte, Aletta E., Sebert, Sylvain, Sein, Aye Aye, Selamat, Rusidah, Sember, Vedrana, Sen, Abhijit, Senbanjo, Idowu O., Sepanlou, Sadaf G., Sequera, Victor, Serra-Majem, Luis, Servais, Jennifer, Shalnova, Svetlana A., Sharma, Sanjib K., Shaw, Jonathan E., Shengelia, Lela, Shibuya, Kenji, Shimizu-Furusawa, Hana, Shin, Dong Wook, Shin, Youchan, Siani, Alfonso, Siantar, Rosalynn, Sibai, Abla M., Silva, Antonio M., Santos Silva, Diego Augusto, Simon, Mary, Simons, Judith, Simons, Leon A., Si-Ramlee, Khairil, Sjoberg, Agneta, Sjostrom, Michael, Slowikowska-Hilczer, Jolanta, Slusarczyk, Przemyslaw, Smeeth, Liam, Snijder, Marieke B., So, Hung-Kwan, Sobngwi, Eugene, Soderberg, Stefan, Soekatri, Moesijanti Y. E., Soemantri, Agustinus, Solfrizzi, Vincenzo, Sonestedt, Emily, Song, Yi, Sorensen, Thorkild I. A., Jerome, Charles Sossa, Soumare, Aicha, Spinelli, Angela, Spiroski, Igor, Staessen, Jan A., Stamm, Hanspeter, Stathopoulou, Maria G., Staub, Kaspar, Stavreski, Bill, Steene-Johannessen, Jostein, Stehle, Peter, Stein, Aryeh D., Stergiou, George S., Stessman, Jochanan, Stoeckl, Doris, Stocks, Tanja, Stokwiszewski, Jakub, Stratton, Gareth, Stronks, Karien, Strufaldi, Maria Wany, Sturua, Lela, Suarez-Medina, Ramon, Sun, Chien-An, Sundstrom, Johan, Sung, Yn-Tz, Sunyer, Jordi, Suriyawongpaisal, Paibul, Swinburn, Boyd A., Sy, Rody G., Sylva, Rene Charles, Szponar, Lucjan, Tai, E. 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H, Zapata ME, Zaw KK, Zdrojewski T, Zeljkovic Vrkic T, Zeng Y, Zhao D, Zhao W, Zheng W, Zheng Y, Zholdin B, Zhou M, Zhu D, Zhussupov B, Zimmermann E, Zuñiga Cisneros J, Ezzati M, Yiallouros, Panayiotis K. [0000-0002-8339-9285], APH - Societal Participation & Health, APH - Aging & Later Life, Epidemiology and Data Science, Public and occupational health, APH - Health Behaviors & Chronic Diseases, and APH - Personalized Medicine
Subjects: Male, Rural Population, obesity, Obesity, body mass index, Settore MED/09 - Medicina Interna, Letter, Urban Population, Epidemiology, [SDV]Life Sciences [q-bio], humanos, body-mass index, adolescente, Geographic Mapping, Sex Factor, países desarrollados, Rural Health, purl.org/pe-repo/ocde/ford#3.03.09 [https], systematic analysis, Body Mass Index, países en desarrollo, 80 and over, risk factors, Age Factor, physical-activity, mediana edad, mapeo geográfico, Aged, 80 and over, anciano, purl.org/pe-repo/ocde/ford#3.02.18 [https], dieta, Age Factors, health, adulto, Middle Aged, Multidisciplinary Sciences, adulto joven, [SDV] Life Sciences [q-bio], estado nutricional, nutrition, Science & Technology - Other Topics, NUTRITION, Female, HEALTH, pooled analysis, Diet, Healthy, worldwide trends, Human, Developed Countrie, Adult, Adolescent, purl.org/pe-repo/ocde/ford#3.03.04 [https], FOOD SYSTEM, Socio-culturale, Nutritional Status, URBAN, Aged, Developed Countries, Developing Countries, Humans, Obesity, Sex Factors, Urban Health, Young Adult, POOLED ANALYSIS, Developing Countrie, MIDDLE-INCOME COUNTRIES, SYSTEMATIC ANALYSIS, Urban rural Obesity Body-Mass-Index, obesidad, Middle-income countries, food system, urban, weight, Healthy, Science & Technology, índice de masa corporal, Diet, PHYSICAL-ACTIVITY, WORLDWIDE TRENDS, Risk factors, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, WEIGHT
Abstract: Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories., This study was funded by the Wellcome Trust. H.B. was supported by a Medical Research Council Doctoral Training Partnership Studentship, J.B. by a Royal Society Research Grant, and M.D.C. by an Academy of Medical Sciences Springboard Award. We thank L. Jaacks, B. Popkin, S. Sundberg and W. Willett for recommendations of relevant citations. The authors are responsible for the views expressed in this Letter and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.
Published: 2019

44. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants

Author: Cesare, Mariachiara Di, Bentham, James, Stevens, Gretchen A., Zhou, Bin, Danaei, Goodarz, Lu, Yuan, Bixby, Honor, Cowan, Melanie J., Riley, Leanne M., Hajifathalian, Kaveh, Fortunato, Lea, Taddei, C., Bennett, James E., Ikeda, Nayu, Khang, Young-Ho, Kyobutungi, Catherine, Laxmaiah, Avula, Li, Yanping, Lin, Hsien-Ho, Miranda, J. Jaime, Mostafa, Aya, Turley, Maria L., Paciorek, Christopher J., Gunter, Marc, Ezzati, Majid, Abdeen, Ziad A., Hamid, Zargar Abdul, Abu-Rmeileh, Niveen M., Acosta-Cazares, Benjamin, Adams, Robert, Aekplakorn, Wichai, Aguilar-Salinas, Carlos A., Agyemang, Charles, Ahrens, Wolfgang, Ali, Farhan, Alkerwi, Ala'a, Alvarez-Pedrerol, Mar, Aly, Eman, Amouyel, Philippe, Amuzu, Antoinette, Andersen, Lars Bo, Anderssen, Sigmund A., Andrade, Dolores S., Anjana, Ranjit Mohan, Aounallah-Skhiri, Hajer, Ariansen, Inger, Aris, Tahir, Arlappa, Nimmathota, Arveiler, Dominique, Assah, Felix K., Avdicova, Maria, Azizi, Fereidoun, Babu, Bontha V., Balakrishna, Nagalla, Bandosz, Piotr, Banegas, Jose R., Barbagallo, Carlo M., Barcelo, Alberto, Barkat, Amina, Barros, Mauro V., Bata, Iqbal, Batieha, Anwar M., Batista, Rosangela L., Baur, Louise A., Beaglehole, Robert, Romdhane, H. B., Benet, Mikhail, Bernabe-Ortiz, Antonio, Bernotine, Gailute, Bettiol, Heloisa, Bhagyalaxmi, Aroor, Bharadwaj, Sumit, Bhargava, Santosh K., Bhatti, Zaid, Bhutta, Zulfiqar A., Bi, HongSheng, Bi, Yufang, Bjerregaard, Peter, Bjertness, Espen, Bjertness, Marius B., Bjorkelund, Cecilia, Blake, Margaret, Blokstra, Anneke, Bo, Simona, Bobak, Martin, Boddy, Lynne M., Boehm, Bernhard O., Boeing, Heiner, Boissonnet, Carlos P., Bongard, Vanina, Bovet, Pascal, Bradbury, Mark, Bragt, Marjolijn C. E., Brajkovich, Imperia, Branca, Francesco, Breckenkamp, Juergen, Brenner, Hermann, Brewster, Lizzy M., Brian, Garry R., Bruno, Graziella, Bueno-de-Mesquita, H. B., Bugge, Anna, Burns, C., Leon, Antonio Cabrera de, Cacciottolo, Joseph, Cama, Tilema, Cameron, Christine, Camolas, Jose, Can, Gunay, Candido, Ana Paula C., Capuano, Vincenzo, Cardoso, Viviane C., Carvalho, Maria J., Casanueva, Felipe F., Casas, Juan-Pablo, Caserta, Carmelo A., Castetbon, Katia, Chamukuttan, Snehalatha, Chan, Angelique W., Chan, Queenie, Chaturvedi, Himanshu K., Chaturvedi, Nishi, Chen, Chien-Jen, Chen, Fangfang, Chen, Shuohua, Chen, Y. Z., Cheng, Ching-Yu, Chetrit, Angela, Chiolero, Arnaud, Chiou, Shu-Ti, Chirita-Emandi, Adela, Cho, Yumi, Christensen, Kaare, Chudek, Jerzy, Cifkova, Renata, Claessens, Frank, Clays, Els, Concin, Hans, Cooper, Cyrus, Cooper, Rachel, Coppinger, Tara C., Costanzo, Simona, Cottel, Dominique, Cowell, Chris, Craig, Cora L., Crujeiras, Ana B., D'Arrigo, Graziella, d'Orsi, Eleonora, Dallongeville, Jean, Damasceno, Albertino, Damsgaard, Camilla T., Dankner, Rachel, Dauchet, Luc, Backer, Guy De, Bacquer, Dirk De, Gaetano, Giovanni de, Hanauw, Stefaan De, Smedt, Delphine De, Deepa, Mohan, Deev, Alexander D., Dehghan, Abbas, Delisle, Helene, Delpeuch, Francis, Dhana, Klodian, Castelnuovo, Augusto F. Di, Dias-da-Costa, Juvenal Soares, Diaz, Alejandro, Djalalinia, Shirin, Do, Ha T. 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Kasaeian, A., Katz, J., Kaur, P., Kavousi, M., Keil, U., Keinan Boker, L., Kelishadi, R., Kemper, H., Kengne, A.P., Kersting, M., Key, T., Khader, Y.S., Khalili, D., Khaw, K.T., Khouw, I.M., Kiechl, S., Killewo, J., Kim, J., Kiyohara, Y., Klimont, J., Kolle, E., Kolsteren, P., Korrovits, P., Koskinen, S., Kouda, K., Koziel, S., Kratzer, W., Krokstad, S., Kromhout, D., Kruger, H.S., Kula, K., Kulaga, Z., Kumar, R.K., Kusuma, Y.S., Kuulasmaa, K., Laamiri, F.Z., Laatikainen, T., Lachat, C., Laid, Y., Lam, T.H., Landrove, O., Lanska, V., Lappas, G., Laugsand, L.E., Le Nguyen Bao, K., Le, T.D., Leclercq, C., Lee, J., Lehtimäki, T., Lekhraj, R., León-Muñoz, L.M., Lim, W.Y., Lima-Costa, M.F., Lin, X., Linneberg, A., Lissner, L., Litwin, M., Liu, J., Lorbeer, R., Lotufo, P.A., Lozano, J.E., Luksiene, D., Lundqvist, A., Lunet, N., Lytsy, P., Ma, G., Machi, S., Maggi, S., Magliano, D.J., Makdisse, M., Malekzadeh, R., Malhotra, R., Mallikharjuna Rao, K., Manios, Y., Mann, J., Manzato, E., Margozzini, P., Markey, O., Marques-Vidal, P., Marrugat, J., Martin-Prevel, Y., Martorell, R., Masoodi, S.R., Matsha, T.E., Mazur, A., Mbanya, J.C., McFarlane, S.R., McGarvey, S.T., McKee, M., McLachlan, S., McLean, R.M., McNulty, B.A., Md Yusof, S., Mediene-Benchekor, S., Meirhaeghe, A., Meisinger, C., Mendes, L.L., Menezes, A.M., Mensink, G.B., Meshram, I.I., Metspalu, A., Mi, J., Michaelsen, K.F., Mikkel, K., Miller, J.C., Miquel, J.F., Mišigoj-Duraković, M., Mohamed, M.K., Mohammad, K., Mohammadifard, N., Mohan, V., Mohd Yusoff, M.F., Molbo, D., Møller, N.C., Molnár, D., Mondo, C.K., Monterrubio, E.A., Monyeki, K.D., Moreira, L.B., Morejon, A., Moreno, L.A., Morgan, K., Mortensen, E.L., Moschonis, G., Mossakowska, M., Mota, J., Motlagh, M.E., Motta, J., Mu, T.T., Muiesan, M.L., Müller-Nurasyid, M., Murphy, N., Mursu, J., Murtagh, E.M., Musa, K.I., Musil, V., Nagel, G., Nakamura, H., Námešná, J., Nang, E.E., Nangia, V.B., Nankap, M., Narake, S., Navarrete-Muñoz, E.M., Nenko, I., Neovius, M., Nervi, F., Neuhauser, H.K., Nguyen, N.D., Nguyen, Q.N., Nieto-Martínez, R.E., Ning, G., Ninomiya, T., Nishtar, S., Noale, M., Norat, T., Noto, D., Nsour, M.A., O'Reilly, D., Ochoa-Avilés, A.M., Oh, K., Olayan, I.H., Olinto, M.T., Oltarzewski, M., Omar, M., Onat, A., Ordunez, P., Ortiz, A.P., Osler, M., Osmond, C., Ostojic, S.M., Otero, J.A., Overvad, K., Paccaud, F.M., Padez, C., Pajak, A., Palli, D., Palloni, A., Palmieri, L., Panda-Jonas, S., Panza, F., Parnell, W.R., Parsaeian, M., Pednekar, M.S., Peeters, P.H., Peixoto, S.V., Pereira, A.C., Pérez, C.M., Peters, A., Peykari, N., Pham, S.T., Pigeot, I., Pikhart, H., Pilav, A., Pilotto, L., Pistelli, F., Pitakaka, F., Piwonska, A., Piwonski, J., Plans-Rubió, P., Poh, B.K., Porta, M., Portegies, M.L., Poulimeneas, D., Pradeepa, R., Prashant, M., Price, J.F., Puiu, M., Punab, M., Qasrawi, R.F., Qorbani, M., Quoc Bao, T., Radic, I., Radisauskas, R., Rahman, M., Raitakari, O., Raj, M., Ramachandra Rao, S., Ramachandran, A., Ramke, J., Ramos, R., Rampal, S., Rasmussen, F., Redon, J., Reganit, P.F., Ribeiro, R., Riboli, E., Rigo, F., Rinke de Wit, T.F., Ritti-Dias, R.M., Rivera, J.A., Robinson, S.M., Robitaille, C., Rodríguez-Artalejo, F., Rodriguez-Perez, M.del C., Rodríguez-Villamizar, L.A., Rojas-Martinez, R., Rojroongwasinkul, N., Romaguera, D., Ronkainen, K., Rosengren, A., Rouse, I., Rubinstein, A., Rühli, F.J., Rui, O., Ruiz-Betancourt, B.S., Russo Horimoto, A.R., Rutkowski, M., Sabanayagam, C., Sachdev, H.S., Saidi, O., Salanave, B., Salazar Martinez, E., Salomaa, V., Salonen, J.T., Salvetti, M., Sánchez-Abanto, J., Sandjaja, X., Sans, S., Santos, D.A., Santos, O., dos Santos, R.N., Santos, R., Sardinha, L.B., Sarrafzadegan, N., Saum, K.U., Savva, S.C., Scazufca, M., Schaffrath Rosario, A., Schargrodsky, H., Schienkiewitz, A., Schmidt, I.M., Schneider, I.J., Schultsz, C., Schutte, A.E., Sein, A.A., Senbanjo, I.O., Sepanlou, S.G., Shalnova, S.A., Shaw, J.E., Shibuya, K., Shin, Y., Shiri, R., Siantar, R., Sibai, A.M., Silva, A.M., Silva, D.A., Simon, M., Simons, J., Simons, L.A., Sjostrom, M., Slowikowska-Hilczer, J., Slusarczyk, P., Smeeth, L., Smith, M.C., Snijder, M.B., So, H.K., Sobngwi, E., Söderberg, S., Soekatri, M.Y., Solfrizzi, V., Sonestedt, E., Sørensen, T.I., Sorić, M., Sossa Jérome, C., Soumare, A., Staessen, J.A., Starc, G., Stathopoulou, M.G., Staub, K., Stavreski, B., Steene-Johannessen, J., Stehle, P., Stein, A.D., Stergiou, G.S., Stessman, J., Stieber, J., Stöckl, D., Stocks, T., Stokwiszewski, J., Stratton, G., Strufaldi, M.W., Sun, C.A., Sundström, J., Sung, Y.T., Sunyer, J., Suriyawongpaisal, P., Swinburn, B., Sy, R.G., Szponar, L., Tai, E.S., Tammesoo, M.L., Tamosiunas, A., Tang, L., Tang, X., Tanser, F., Tao, Y., Tarawneh, M., Tarp, J., Tarqui-Mamani, C.B., Taylor, A., Tchibindat, F., Thijs, L., Thuesen, B.H., Tjonneland, A., Tolonen, H.K., Tolstrup, J.S., Topbas, M., Topór-Madry, R., Torrent, M., Traissac, P., Trichopoulou, A., Trichopoulos, D., Trinh, O.T., Trivedi, A., Tshepo, L., Tulloch-Reid, M.K., Tuomainen, T.P., Tuomilehto, J., Tynelius, P., Tzotzas, T., Tzourio, C., Ueda, P., Ukoli, F.A., Ulmer, H., Unal, B., Valdivia, G., Vale, S., Valvi, D., van der Schouw, Y.T., Van Herck, K., Van Minh, H., van Valkengoed, I.G., Vanderschueren, D., Vanuzzo, D., Vatten, L., Vega, T., Velasquez-Melendez, G., Veronesi, G., Verschuren, W.M., Viegi, G., Viet, L., Viikari-Juntura, E., Vineis, P., Vioque, J., Virtanen, J.K., Visvikis-Siest, S., Viswanathan, B., Vollenweider, P., Voutilainen, S., Vrijheid, M., Wade, A.N., Wagner, A., Walton, J., Wan, N., Wan, M., Wang, M.D., Wang, Q., Wang, Y.X., Wannamethee, S.G., Wareham, N., Weerasekera, D., Whincup, P.H., Widhalm, K., Widyahening, I., Wiecek, A., Wilks, R.J., Willeit, J., Wojtyniak, B., Wong, J.E., Wong, T.Y., Woo, J., Woodward, M., Wu, F.C., Wu, J., Wu, S.L., Xu, H., Xu, L., Yamborisut, U., Yan, W., Yang, X., Yardim, N., Ye, X., Yiallouros, P.K., Yoshihara, A., You, Q.S., Younger-Coleman, N.O., Yusoff, A.F., Zainuddin, A., Zambon, S., Zdrojewski, T., Zeng, Y., Zhao, D., Zhao, W., Zheng, Y., Zhou, M., Zhu, D., Zimmermann, E., Zuñiga Cisneros, J., Erasmus MC other, Epidemiology, Medical Oncology, Cardiology, Repositório Científico do Instituto Politécnico do Porto, University Medical Center Utrecht, Imperial College Trust, Yiallouros, Panayiotis K. [0000-0002-8339-9285], NCD Risk Factor Collaboration (ukupan broj autora: 754), Repositório da Universidade de Lisboa, Di Cesare M, Bentham J, Stevens GA, Zhou B, Danaei G, Lu Y, Bixby H, Cowan MJ, Riley LM, Hajifathalian K, Fortunato L, Taddei C, Bennett JE, Ikeda N, Khang Y-O, Kyobutungi C, Laxmaiah A, Li Y, Lin H-O, Miranda JJ, Mostafa A, Turley ML, Gunter M, Ezzati M, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Adams R, Aekplakorn W, Aguilar-Salinas CA, Ahmadvand A, Ahrens W, Ali MM, Ala'a Alkerwi A, Alvarez-Pedrerol M, Aly E, Amouyel P, Antoinette Amuzu A, Andersen LB, Anderssen SA, Andrade DS, Anjana RM, Aounallah-Skhiri H, Ariansen I, Aris T, Arlappa N, Arveiler D, Assah FK, Avdicová M, Azizi F, Babu BV, Balakrishna N, Bandosz P, Banegas. JR, Barbagallo CM, Barceló A, Barkat A, Barros MV, Bata I, Batieha AM, Batista RL, Baur LA, Beaglehole R, Romdhane HB, Benet M, Bernabe-Ortiz A, Bernotiene G, Bettiol H, Bhagyalaxmi A, Bharadwaj S, Bhargava SH, Bhatti Z, Bhutta ZA, Bi HS, Bi Y, Bjerregaard P, Bjertness E, Bjertness MB, Björkelund C, Blake M, Blokstra A, Bo S, Bobak M, Boddy LM, Boehm BO, Boeing H, Boissonnet CP, Bongard V, Bovet P, Braeckman L, Bragt MCE, Brajkovich I, Branca F, Breckenkamp J, Brenner H, Brewster LM, Brian GR, Bruno G, Bueno-de-Mesquita HB, Bugge A, Burns C, de León CA, Cacciottolo J, Cama T, Cameron C, Camolas J, Can G, Cândido APC, Capuano V, Cardoso VC, Carvalho MJ, Casanueva FF, Casas J-P, Caserta CA, Castetbon K, Chamukuttan S, Chan AW, Chan Q, Chaturvedi HK, Nishi Chaturvedi N, Chen C-J, Chen F, Chen H, Chen S, Chen Z, Cheng C-Y, Chetrit A, Chiolero A, Chiou S-T, Chirita-Emandi A, Cho Y, Kaare Christensen K, Chudek J, Renata Cifkova R, Claessens F, Clays E, Concin H, Cooper C, Cooper R, Coppinger TC, Costanzo C, Cottel D, Cowell C, Craig CL, Crujeiras AB, D'Arrigo G, d'Orsi E, Dallongeville J, Damasceno A, Damsgaard CT, Dankner R, Luc Dauchet L, De Backer G, De Bacquer D, de Gaetano G, De Henauw S, De Smedt D, Deepa M, Deev AD, Dehghan A, Delisle H, Delpeuch F, Dhana K, Di Castelnuovo AF, Dias-da-Costa JS, Diaz A, Djalalinia S, Do HTP, Dobson AJ, Donfrancesco C, Döring A, Doua K, Drygas W, Egbagbe EE, Eggertsen R, Ekelund U, El Ati J, Elliott P, Engle-Stone R, Erasmus RT, Erem C, Eriksen L, Escobedo-de la Peña J, Evans A, Faeh D, Fall CH, Farshad Farzadfar F, Felix-Redondo FJ, Ferguson TS, Fernández-Bergés D, Ferrante D, Ferrari M, Ferreccio C, Ferrieres J, Finn JD, Fischer K, Monterubio Flores E, Föger B, Foo LH, Forslund A-S, Fortmann SP, Fouad HM, Francis DK, Franco MdC, Franco OH, Guillermo Frontera G, Fuchs FH, Fuchs SC, Fujita Y, Furusawa T, Gaciong Z, Gafencu M, Gareta D, Garnett SP, Gaspoz J-M, GasulL M, Gates L, Geleijnse JM, Ghasemian A, Giampaoli S, GianfagnA F, Giovannelli J, Giwercman A, Goldsmith RA, Gonzalez Gross M, González Rivas JP, Gorbea MB, Gottrand F, Graff-Iversen S, Grafnetter D, Grajda A, Grammatikopoulou MG, Gregor RD, Grodzicki T, Grøntved A, Gruden G, Grujic V, Gu D, Guan OP, Gudnason V, Guerrero R, Guessous I, Guimaraes AL, Gulliford MC, Gunnlaugsdottir J, Guo XK, Guo Y, Gupta PC, Gureje O, Gurzkowska B, Gutierrez L, Gutzwiller F, Halkjær J, Hardy R, Kumar RH, Hayes AJ, He J, Hendriks ME, Hernandez Cadena L, Heshmat R, Hihtaniemi IP, Sai SY, Ho SC, Hobbs M, Hofman A, Hormiga CM, Horta BH, Houti L, Htay TT, Htet AS, Htike MMT, Hu Y, Hussieni HS, Huu CN, Huybrechts I, Hwalla N, Iacoviello L, Iannone AG, Ibrahim MM, Ikram MA, Irazola VE, Islam M, Iwasaki M, Jackson RT, Jacobs JM, Tazeen Jafar T, Jamil KM, Jamrozi K, Jasienska G, Jiang CQ, Joffres M, Johansson M, Jonas JB, Jørgensen T, Joshi P, Juolevi A, Jurak G, Vesna Jureša V, Kaaks R, Kafatos A, Kalter-Leibovici O, Kapantais E, Kasaeian A, Katz J, Kaur P, Kavousi M, Keil U, Keinan Boker L, Kelishadi R, Kemper HHCG, Kengne AP, Kersting M, Key T, Khader YS, Khalili D, Khang Y-H, Kay-Tee H Khaw K-TH, Khouw LMSL, Kiechl S, Killewo J, Kim J, Kiyohara Y, Klimont J, Kolle E, Kolsteren P, Korrovits P, Koskinen S, Kouda K, Koziel S, Kratzer W, Krokstad S, Kromhout D, Kruger HS, Kula K, Kulaga Z, Kumar RK, Kusuma YS, Kuulasmaa K, Laamiri FZ, Laatikainen T, Lachat C, Laid Y, Lam TH, Landrove O, Lanska V, Lappas G, Laugsand LE, Nguyen Bao KL, Le TD, Leclercq C, Lee J, Jeonghee Lee J, Lehtimäki T, Lekhraj R, León-Muñoz LM, Lim W-Y, M Fernanda Lima-Costa MF, Lin H-H, Lin X, Linneberg A, Lissner L, Litwin M, Liu J, Lorbeer R, Lotufo PA, Lozano JE, Luksiene D, Lundqvist A, Lunet N, Lytsy P, Ma G, Machi S, Maggi S, Magliano DJ, Makdisse M, Malekzadeh R, Malhotra R, Mallikharjuna Rao K, Manios Y, Mann JI, Manzato E, Margozzini P, Markey O, Marques-Vidal P, Marrugat P, Martin-Prevel Y, Martorell R, Masoodi SR, Matsha TE, Mazur A, Mbanya JCN, McFarlane SR, McGarvey ST, McKee M, McLachlan S, McLean RM, McNulty BA, Md Yusof S, Mediene-Benchekor S, Meirhaeghe A, Meisinger A, Mendes LL, Menezes AMB, Mensink GBM, Meshram II, Metspalu A, Mi JM, Michaelsen KF, Miller JC, Miquel JF, Mišigoj-Duraković M, Mohamed MK, Mohammad K, Mohammadifard N, Mohan V, Mohd Yusoff MF, Molbo D, Møller NC, Molnár D, Mondo CK, Monterrubio EA, Monyeki KDK, Leila B Moreira LB, Morejon A, Moreno LA, Morgan K, Mortensen EL, Moschonis G, Mossakowska M, Mota J, Motlagh ME, Motta J, Mu TT, Muiesan ML, Müller-Nurasyid M, Murphy N, Mursu J, Murtagh EM, Musa KI, Musil V, Nagel G, Nakamura H, Námešná J, Nang EEK, Nangia VB, Nankap M, Narake S, Navarrete-Muñoz EM, Nenko I, Neovius M, Nervi F, Neuhauser HK, Nguyen ND, Ngoc Nguyen Q, Nieto-Martínez RE, Ning G, Ninomiya T, Nishtar S, Noale M, Norat T, Noto D, Al Nsour M, O'Reilly D, Ochoa-Avilés AM, Oh K, Olayan IH, Olinto MTA, Oltarzewski M, Omar MA, Onat A, Ordunez P, Ortiz AP, Osler M, Osmond C, Ostojic AM, Otero JA, Overvad K, Paccaud F, Padez C, Pajak A, Palli D, Palloni A, Palmieri L, Panda-Jonas S, Panza F, Parnell WR, Parsaeian M, Pednekar MS, Peeters PH, Peixoto SV, Pereira AC, Pérez CM, Peters A, Peykari N, Pham ST, Pigeot I, Pikhart H, Pilav A, Pilotto L, Pistelli F, Pitakaka F, Piwonska A, Piwonski J, Pedro Plans-Rubió P, Poh BK, Porta M, Portegies MLP, Poulimeneas D, Pradeepa R, Prashant M, Price JF, Puiu M, Punab M, Qasrawi RF, Qorbani M, Quoc Bao T, Radic I, Ricardas Radisauskas R, Rahman M, Raitakari O, Raj M, Ramachandra Rao S, Ramachandran A, Ramke J, Ramos R, Rampal S, Rasmussen F, Redon J, Reganit PFM, Robespierre Ribeiro R, Riboli E, Rigo F, Rinke de Wit TF, Ritti-Dias RM, Juan A Rivera JA, Robinson SM, Robitaille C, Rodríguez-Artalejo F, Rodriguez-Perez MdC, Rodríguez-Villamizar LA, Rojas-Martinez R, Rojroongwasinkul N, Romaguera D, Ronkainen K, Rosengren A, Rouse I, Rubinstein A, Rühli FJ, Rui O, Ruiz-Betancourt BS, Russo Horimoto ARV, Rutkowski M, Sabanayagam C, Sachdev HS, Saidi O, Salanave B, Salazar Martinez E, Salomaa V, Salonen JT, Salvetti M, Sánchez-Abanto J, Sandjaja A, Sans S, Santos DA, Santos O, dos Santos RN, Santos R, Sardinha LB, Sarrafzadegan N, Saum K-U, Savva SC, Scazufca M, Schaffrath Rosario A, Schargrodsky H, Schienkiewitz A, Schmidt IM, Schneider IJ, Schultsz C, Schutte AE, Sein AA, Sen A, Senbanjo IO, Sepanlou SG, Shalnova SA, Shaw JE, Shibuya K, Shin Y, Shiri R, Siantar R, Sibai AM, Silva AM, Simon M, Simons J, Simons LA, Sjostrom M, Slowikowska-Hilczer J, Slusarczyk P, Smeeth L, Smith MC, Snijder MB, So H-K, Sobngwi E, Söderberg S, Soekatri MYE, Solfrizzi V, Sonestedt E, Sørensen TIA, Sorić M, Sossa Jérome C, Soumare A, Staessen JA, Starc G, Stathopoulou MG, Staub K, Stavreski B, Steene-Johannessen J, Stehle P, Stein AD, Stergiou GS, Stessman J, Stieber J, Stöckl D, Stocks T, Stokwiszewski J, Stratton G, Strufaldi MW, Chien-An Sun C-A, Sundström J, Sung Y-T, Sunyer J, Suriyawongpaisal P, Swinburn BA, Sy RG, Szponar L, E Shyong Tai E, Tammesoo M-L, Tamosiunas A, Tang L, Tang X, Tanser F, Tao Y, Tarawneh M, Jakob Tarp J, Tarqui-Mamani CB, Taylor A, Félicité Tchibindat F, Thijs L, Thuesen BH, Tjonneland A, Tolonen HK, Janne S Tolstrup JS, Topbas M, Topór-Madry R, Torrent M, Traissac P, Trichopoulos D, Trinh OTH, Trivedi A, Tshepo L, Tulloch-Reid MK, Tuomainen T-P, Tuomilehto J, Tynelius P, Tzotzas T, Tzourio C, Ueda P, Ukoli FAM, Ulmer H, Unal B, Valdivia G, Susana Va S, Valvi D, van der Schouw YT, Van Herck K, Van Minh H, van Valkengoed IGM, Vanderschueren D, Vanuzzo D, Vatten L, Vega T, Velasquez-Melendez G, Veronesi G, Verschuren WMM, Viegi G, Viet L, Viikari-Juntura E, Vineis P, Vioque P, Virtanen JK, Visvikis-Siest S, Viswanathan B, Vollenweider P, Voutilainen S, Vrijheid M, Wade AN, Wagner A, Walton J, Wan Mohamud WN, Wang M-D, Wang Q, Wang YX, Wannamethee SG, Wareham N, Deepa Weerasekera D, Whincup PH, Widhalm K, Widyahening IS, Wiecek A, Wilks RJ, Willeit J, Wojtyniak B, Wong, Wong TY, Woo J, Woodward M, Wu FC, JianFeng Wu JF, Wu SL, Xu H, Xu L, Yamborisut U, Yan W, Yang X, Yardim N, Ye X, Yiallouros PK, Yoshihara A, Qi Sheng You QS, Younger-Coleman NO, Yusoff AF, Ahmad A Zainuddin AA, Zambon S, Zdrojewski T, Zeng Y, Zhao D, Zhao W, Zheng Y, Zhou M, Zhu D, Zimmermann E, Zuñiga Cisneros J, General Internal Medicine, AII - Amsterdam institute for Infection and Immunity, Public and occupational health, Global Health, and APH - Amsterdam Public Health
Subjects: Male, Obesidad, CHILDREN, Salud, Review, países desarrollados, Global Health, Body Mass Index, Body mass index, population study, 0302 clinical medicine, Models, Factores de riesgo cardiovascular, Medicine, body mass index, underweight, overweight, obesity, Young adult, Human Nutrition & Health, education.field_of_study, Humane Voeding & Gezondheid, General Medicine, ASSOCIATION, 11 Medical And Health Sciences, adulto, predicción, adulto joven, CARDIOVASCULAR-DISEASE, thinness/epidemiology, NONCOMMUNICABLE DISEASES, NCD Risk Factor Collaboration (NCD-RisC), Enfermedades cardiovasculares, Developed country, teorema de Bayes, Medical sciences, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Thinness, Humans, education, Developing Countries, obesidad, VLAG, Science & Technology, Models, Statistical, CAUSE-SPECIFIC MORTALITY, Bayes Theorem, medicine.disease, QP, Obesity, adult body-mass, Indice de masa corporal (IMC), RISK-FACTORS, Adolescent, Adult, Developed Countries, Female, Forecasting, Obesity/epidemiology, Prevalence, Thinness/epidemiology, Young Adult, RA, Body mass index, Demography, Meta-Analysis, Gerontology, Settore MED/09 - Medicina Interna, Nutrition and Disease, humanos, adolescente, Overweight, países en desarrollo, Voeding en Ziekte, Medicine and Health Sciences, Global health, 030212 general & internal medicine, Non-U.S. Gov't, Medicine (all), Research Support, Non-U.S. Gov't, prevalencia, Public Health, Global Health, Social Medicine and Epidemiology, Statistical, Underweight, medicine.symptom, pooled analysis, Life Sciences & Biomedicine, obesity/*epidemiology, Population, 030209 endocrinology & metabolism, Research Support, Medicine, General & Internal, EPIDEMIC, General & Internal Medicine, Journal Article, Life Science, ddc:610, Obesidad morbida, OBESITY PREVENTION, OVERWEIGHT, business.industry, índice de masa corporal, COHORTS, purl.org/pe-repo/ocde/ford#3.02.00 [https], Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Ciencias socio biomédicas, business, delgadez
Abstract: Copyright © NCD Risk Factor Collaboration. Open Access article distributed under the terms of CC BY., Background: Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods: We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (, Wellcome Trust, Grand Challenges Canada
Published: 2016

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