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Skowronski AA, Leibel RL, LeDuc CA. Neurodevelopmental Programming of Adiposity: Contributions to Obesity Risk. Endocr Rev 2024; 45:253-280. [PMID: 37971140 PMCID: PMC10911958 DOI: 10.1210/endrev/bnad031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 09/29/2023] [Accepted: 10/19/2023] [Indexed: 11/19/2023]
Abstract
This review analyzes the published evidence regarding maternal factors that influence the developmental programming of long-term adiposity in humans and animals via the central nervous system (CNS). We describe the physiological outcomes of perinatal underfeeding and overfeeding and explore potential mechanisms that may mediate the impact of such exposures on the development of feeding circuits within the CNS-including the influences of metabolic hormones and epigenetic changes. The perinatal environment, reflective of maternal nutritional status, contributes to the programming of offspring adiposity. The in utero and early postnatal periods represent critically sensitive developmental windows during which the hormonal and metabolic milieu affects the maturation of the hypothalamus. Maternal hyperglycemia is associated with increased transfer of glucose to the fetus driving fetal hyperinsulinemia. Elevated fetal insulin causes increased adiposity and consequently higher fetal circulating leptin concentration. Mechanistic studies in animal models indicate important roles of leptin and insulin in central and peripheral programming of adiposity, and suggest that optimal concentrations of these hormones are critical during early life. Additionally, the environmental milieu during development may be conveyed to progeny through epigenetic marks and these can potentially be vertically transmitted to subsequent generations. Thus, nutritional and metabolic/endocrine signals during perinatal development can have lifelong (and possibly multigenerational) impacts on offspring body weight regulation.
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Affiliation(s)
- Alicja A Skowronski
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Rudolph L Leibel
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Charles A LeDuc
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
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Lin Y, Xiu X, Lin J, Chen Z, Zheng CX, Pan X, Lin L, Yan J. Application of Team-Based Flipped Classroom and Traditional Learning on the Antenatal Education Center Course. ADVANCES IN MEDICAL EDUCATION AND PRACTICE 2023; 14:1379-1390. [PMID: 38106922 PMCID: PMC10725629 DOI: 10.2147/amep.s429806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/28/2023] [Indexed: 12/19/2023]
Abstract
Background The goal is to evaluate the effects of a flipped class strategy on knowledge, self-directed learning ability, learning satisfaction and pregnancy outcomes in primiparas undergoing antenatal education. Methods A random sampling method was adopted. A total of 600 primiparas who were diagnosed with early pregnancy in a first-class hospital in southeast China and received continuous prenatal health education from May to July 2020 were selected as the research subjects. In order to make the baseline of the two groups of primipara comparable, we divided the two groups in the antenatal education centre according to the odd-even number of the lesson card number. The odd-numbered group was the experimental group, who used the prenatal health education model based on blended learning; the even-numbered group was the control group, who used the traditional mode of prenatal health education. The two groups were compared on the following outcomes: knowledge, self-directed learning ability, learning satisfaction and pregnancy outcomes. Results Compared with traditional learning, the blended learning approach can effectively controlled the gestational weight gain (GWG), alleviated the anxiety and depression during pregnancy, improved the natural delivery rate of the primipara, shortened the delivery process and reduced the risk of gestational diabetes mellitus (GDM), the difference was statistically significant (all P<0.05). Conclusion Blended learning may be an effective strategy because of its validity and practicality in antenatal education.
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Affiliation(s)
- Yingying Lin
- Department of Healthcare, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Xiaoyan Xiu
- Department of Health Education, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Juan Lin
- Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Zhiwei Chen
- Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Cui Xian Zheng
- Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Xuehong Pan
- Department of Health Education, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Lihua Lin
- Department of Healthcare, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Jianying Yan
- Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
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Li Y, Gao D, Liu J, Yang Z, Wen B, Chen L, Chen M, Ma Y, Ma T, Dong B, Song Y, Huang S, Dong Y, Ma J. Prepubertal BMI, pubertal growth patterns, and long-term BMI: Results from a longitudinal analysis in Chinese children and adolescents from 2005 to 2016. Eur J Clin Nutr 2022; 76:1432-1439. [PMID: 35523866 DOI: 10.1038/s41430-022-01133-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 03/20/2022] [Accepted: 03/24/2022] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To assess the effects of prepubertal BMI on pubertal growth patterns, and the influence of prepubertal BMI and pubertal growth patterns on long-term BMI among Chinese children and adolescents. METHODS A total of 9606 individuals aged between 7 and 18 years from longitudinal surveys in Zhongshan city of China from 2005 to 2016 were enrolled. Age at peak height velocity (APHV) and peak height velocity (PHV) were estimated using Super-Imposition by Translation and Rotation (SITAR) model. Associations between prepubertal BMI, APHV, PHV, and long-term overweight and obesity were assessed by linear regression and multinominal logistic regression. Scatter plots were elaborated to show the associations between prepubertal BMI and pubertal growth patterns according to prepubertal BMI categories. RESULTS Prepubertal BMI Z-Score was positively correlated with long-term BMI Z-Score, and negatively correlated with APHV in both sexes. In addition, there was a negative association between prepubertal BMI Z-Score and PHV in boys. With 1-year decrease in APHV, risk of long-term underweight decreased by 92%, while overweight increased by 33% in boys. Corresponding risk of long-term underweight and overweight for girls decreased by 42% and increased by 20%, respectively. CONCLUSION High prepubertal BMI levels were associated with earlier APHV and lower PHV, and the early onset of pubertal development could increase the risks of long-term overweight and obesity at 17-18 years of age both in boys and girls. Such evidence emphasized the importance of reducing prepubertal obesity risks combined with appropriate pubertal development timing, including later APHV and higher PHV, so as to prevent the obesity and related cardiovascular diseases in adulthood.
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Affiliation(s)
- Yanhui Li
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Di Gao
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Jieyu Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Zhaogeng Yang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Bo Wen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Manman Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Ying Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Tao Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Bin Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Yi Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China
| | - Sizhe Huang
- Zhongshan Health Care Centers for Primary and Secondary School, 528403, Zhongshan, China
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China.
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China.
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, 100191, Beijing, China.
- National Health Commission Key Laboratory of Reproductive Health, 100191, Beijing, China.
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Von Holle A, North KE, Gahagan S, Blanco E, Burrows R, Lozoff B, Howard AG, Justice AE, Graff M, Voruganti S. Infant Growth Trajectories and Lipid Levels in Adolescence: Evidence From a Chilean Infancy Cohort. Am J Epidemiol 2022; 191:1700-1709. [PMID: 35467716 PMCID: PMC9989340 DOI: 10.1093/aje/kwac057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 02/14/2022] [Accepted: 03/22/2022] [Indexed: 01/29/2023] Open
Abstract
Growth in early infancy is hypothesized to affect chronic disease risk factors later in life. To date, most reports draw on European-ancestry cohorts with few repeated observations in early infancy. We investigated the association between infant growth before 6 months and lipid levels in adolescents in a Hispanic/Latino cohort. We characterized infant growth from birth to 5 months in male (n = 311) and female (n = 285) infants from the Santiago Longitudinal Study (1991-1996) using 3 metrics: weight (kg), length (cm), and weight-for-length (g/cm). Superimposition by translation and rotation (SITAR) and latent growth mixture models (LGMMs) were used to estimate the association between infant growth characteristics and lipid levels at age 17 years. We found a positive relationship between the SITAR length velocity parameter before 6 months of age and high-density lipoprotein cholesterol levels in adolescence (11.5, 95% confidence interval; 3.4, 19.5), indicating higher high-density lipoprotein cholesterol levels occurring with faster length growth. The strongest associations from the LGMMs were between higher low-density lipoprotein cholesterol and slower weight-for-length growth, following a pattern of associations between slower growth and adverse lipid profiles. Further research in this window of time can confirm the association between early infant growth as an exposure and adolescent cardiovascular disease risk factors.
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Affiliation(s)
- Ann Von Holle
- Correspondence to Dr. Ann Von Holle, P.O. Box 12233, Durham, NC 27709 (e-mail: )
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Oleszczuk-Modzelewska L, Malinowska-Polubiec A, Romejko-Wolniewicz E, Zawiejska A, Czajkowski K. What is the "cost" of reducing adverse pregnancy outcomes in patients with gestational diabetes mellitus - risk factors for perinatal complications in a retrospective cohort of pregnant women with GDM. BMC Pregnancy Childbirth 2022; 22:654. [PMID: 35986350 PMCID: PMC9392248 DOI: 10.1186/s12884-022-04980-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 06/07/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) is a frequent pregnancy complication, affecting the maternal and neonatal health. The new diagnostic strategy for GDM, proposed by the International Association of Diabetes and Pregnancy Study Groups in 2010 and World Health Organization in 2013, raised hope to reduce perinatal complications. The purpose of the study was to compare risk factors influencing maternal and foetal outcomes in a group of pregnant women diagnosed with GDM, and in a group of pregnant women without GDM, regardless of the adopted diagnostic criteria. Also, the aim of the study was to evaluate the impact of risk factors on perinatal results and the "cost" of reducing adverse pregnancy outcomes in patients with GDM. METHODS It was a retrospective study based on the analysis of births given after 37 weeks of pregnancy at the 2nd Department of Obstetrics and Gynaecology, Warsaw Medical University during the years 2013 to 2015. All pregnant women had a 75 g OGTT between the 24th and 28th weeks of pregnancy. The study compared risk factors for perinatal complications in 285 GDM patients and in 202 randomly selected women without GDM. The impact of selected risk factors on perinatal outcomes was analysed. RESULTS Both the diagnosis of GDM and maternal BMI prior to pregnancy, significantly modified the risk of excessive and insufficient weight gain during pregnancy. The parameters significantly influencing the risk of the composite adverse maternal outcome were the maternal abdominal circumference [OR: 1.08 (1.04; 1.11)] and multiparity, which reduced the risk by almost half [OR: 0.47 (0.30; 0.75)]. The maternal abdominal circumference before the delivery was a strong factor correlating with the occurrence of perinatal complications in both the mother and the foetus in the entire cohort. A circumference over 100 cm increased the risk of at least one maternal complication (increased blood loss, soft tissue injury, pre-eclampsia) by almost 40% (OR 1.38, p < 0.001). CONCLUSIONS No differences were found in maternal and foetal outcomes in GDM and non-GDM women except gestational weight gain below Institute of Medicine recommendations. The only "cost" of reducing adverse pregnancy outcomes in GDM patients seems to be lowering gestational weight gain, the future impact of which on GDM pregnant population should be assessed. The maternal abdominal circumference measured before delivery not the severity of carbohydrate intolerance, remained the main predictor for significant perinatal complications.
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Affiliation(s)
- Luiza Oleszczuk-Modzelewska
- 2nd Department of Obstetrics and Gynaecology, Medical University of Warsaw, 2 Karowa St, 00-315, Warsaw, Poland
| | - Aneta Malinowska-Polubiec
- 2nd Department of Obstetrics and Gynaecology, Medical University of Warsaw, 2 Karowa St, 00-315, Warsaw, Poland.
| | - Ewa Romejko-Wolniewicz
- 2nd Department of Obstetrics and Gynaecology, Medical University of Warsaw, 2 Karowa St, 00-315, Warsaw, Poland
| | - Agnieszka Zawiejska
- Department of Medical Simulation, Chair of Medical Education, Poznan University of Medical Sciences, 41 Jackowskiego St, 60-512, Poznan, Poland
| | - Krzysztof Czajkowski
- 2nd Department of Obstetrics and Gynaecology, Medical University of Warsaw, 2 Karowa St, 00-315, Warsaw, Poland
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Gonçalves R, Wiertsema CJ, Silva CCV, Monasso GS, Gaillard R, Steegers EAP, Santos S, Jaddoe VWV. Associations of Fetal and Infant Growth Patterns With Early Markers of Arterial Health in School-Aged Children. JAMA Netw Open 2022; 5:e2219225. [PMID: 35767260 PMCID: PMC9244605 DOI: 10.1001/jamanetworkopen.2022.19225] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE Fetal life and infancy might be critical periods for predisposing individuals to develop cardiovascular disease in adulthood. OBJECTIVE To examine the associations of fetal and infant weight growth patterns with early markers of arterial health. DESIGN, SETTING, AND PARTICIPANTS This population-based prospective cohort study was conducted from early fetal life onward among 4484 offspring of women in Rotterdam, the Netherlands, delivering between April 1, 2002, and January 31, 2006. Statistical analysis was performed between January 1 and August 31, 2021. EXPOSURES Estimated fetal weight was measured in the second and third trimester. Data on weight and gestational age at birth were collected from midwives. Infant weight was measured at 6, 12, and 24 months. MAIN OUTCOMES AND MEASURES The common carotid intima-media thickness (cIMT) and carotid distensibility were measured as early markers of arterial health. RESULTS Follow-up measurements were available for 4484 children (2260 girls [50.4%]; median age, 9.7 years [95% range, 9.3-10.5 years]; and 2578 [57.5%] of Dutch ethnicity). Gestational age at birth was not associated with markers of arterial health. A 500-g-higher birth weight was associated with increased cIMT (standard deviation score [SDS], 0.08 mm [95% CI, 0.05-0.10 mm]) and a lower carotid distensibility (SDS, -0.05 × 10-3 kPa-1; [95% CI, -0.08 to -0.03 × 10-3 kPa-1]). Compared with children with a birth weight of 2500 to 4500 g, those weighing more than 4500 g had the lowest carotid distensibility (difference in SDS, -0.22 × 10-3 kPa-1 [95% CI, -0.42 to -0.02 × 10-3 kPa-1]). Conditional regression analyses showed that higher third-trimester fetal weight and birth weight were associated with increased cIMT (difference in SDS: third-trimester fetal weight, 0.08 mm [95% CI, 0.04-0.12 mm]; birth weight, 0.05 mm [95% CI, 0.01-0.09 mm]) and that higher weight at 6, 12, and 24 months was associated with increased cIMT (difference in SDS: 6 months, 0.05 mm [95% CI, 0.01-0.10 mm]; 12 months, 0.06 mm [95% CI, 0.02-0.10 mm]; and 24 months, 0.07 mm [95% CI, 0.03-0.11 mm]) and lower carotid distensibility (difference in SDS: 6 months, -0.04 × 10-3 kPa-1 [95% CI, -0.09 to -0.001 × 10-3 kPa-1]; 12 months, -0.05 × 10-3 kPa-1 [95% CI, -0.09 to -0.01 × 10-3 kPa-1]; and 24 months, -0.10 × 10-3 kPa-1 [95% CI, -0.15 to -0.06 × 10-3 kPa-1]). Compared with children with normal fetal and infant growth, children with normal fetal growth that was followed by accelerated infant growth had the highest cIMT (SDS, 0.19 mm [95% CI, 0.07-0.31 mm]) and lowest carotid distensibility (SDS, -0.16 × 10-3 kPa-1 [95% CI, -0.28 to -0.03 × 10-3 kPa-1]). The observed associations were largely explained by childhood body mass index. CONCLUSIONS AND RELEVANCE In this cohort study of 4484 children aged approximately 10 years, higher fetal and infant weight growth patterns were associated with early markers of impaired arterial health. Childhood body mass index seemed to be involved in the underlying pathways of the observed associations.
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Affiliation(s)
- Romy Gonçalves
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Clarissa J. Wiertsema
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Carolina C. V. Silva
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Giulietta S. Monasso
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Romy Gaillard
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Eric A. P. Steegers
- Department of Obstetrics and Gynaecology, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Susana Santos
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
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Monasso GS, Silva CCV, Santos S, Goncalvez R, Gaillard R, Felix JF, Jaddoe VWV. Infant weight growth patterns, childhood BMI, and arterial health at age 10 years. Obesity (Silver Spring) 2022; 30:770-778. [PMID: 35142077 PMCID: PMC9302666 DOI: 10.1002/oby.23376] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/26/2021] [Accepted: 12/14/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Associations of obesity with cardiovascular disease may originate in childhood. This study examined critical periods for BMI in relation to arterial health at school age. METHODS Among 4,731 children from a prospective cohort study, associations of infant peak weight velocity, both age and BMI at adiposity peak, and BMI trajectories with carotid artery intima-media thickness and carotid artery distensibility at 10 years were examined. RESULTS A 1-standard deviation score (SDS) higher peak weight velocity and BMI at adiposity peak were associated with higher intima-media thickness (0.10 SDS; 95% CI: 0.06 to 0.13 and 0.08 SDS; 95% CI: 0.05 to 0.12) and lower distensibility (-0.07 SDS; 95% CI: -0.10 to -0.03 and -0.07 SDS; 95% CI: -0.11 to -0.03) at 10 years. For distensibility, current BMI explained these associations. Children within the highest BMI tertile at ages 2 and 10 years had the lowest distensibility (p < 0.05), but similar intima-media thickness, compared with children constantly within the middle tertile. CONCLUSIONS Infant weight growth patterns and childhood BMI are associated with subtle differences in carotid intima-media thickness and carotid distensibility at school age. For distensibility, current BMI seems critical. Follow-up is needed to determine whether these associations lead to adult cardiovascular disease.
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Affiliation(s)
- Giulietta S. Monasso
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
| | - Carolina C. V. Silva
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
| | - Susana Santos
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
| | - Romy Goncalvez
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of Obstetrics and GynaecologyErasmus University Medical CenterRotterdamthe Netherlands
| | - Romy Gaillard
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
| | - Janine F. Felix
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
| | - Vincent W. V. Jaddoe
- The Generation R Study GroupErasmus University Medical CenterRotterdamthe Netherlands
- Department of PediatricsErasmus University Medical CenterRotterdamthe Netherlands
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Growth from birth to 6 months of infants with and without intrauterine preeclampsia exposure. J Dev Orig Health Dis 2021; 13:151-155. [PMID: 33977898 DOI: 10.1017/s2040174421000167] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Intrauterine preeclampsia exposure affects the lifelong cardiometabolic health of the child. Our study aimed to compare the growth (from birth to 6 months) of infants exposed to either a normotensive pregnancy or preeclampsia and explore the influence of being born small for gestational age (SGA). Participants were children of women participating in the Post-partum, Physiology, Psychology and Paediatric follow-up cohort study. Birth and 6-month weight and length z-scores were calculated for term and preterm (<37 weeks) babies, and change in weight z-score, rapid weight gain (≥0.67 increase in weight z-score) and conditional weight gain z-score were calculated. Compared with normotensive exposed infants (n = 298), preeclampsia exposed infants (n = 84) were more likely to be born SGA (7% versus 23%; P < 0.001), but weight gain from birth to 6 months, by any measure, did not differ between groups. Infants born SGA, irrespective of pregnancy exposure, were more likely to have rapid weight gain and had greater increases in weight z-score compared with those not born SGA. Preeclampsia exposed infants born SGA may benefit from interventions designed to prevent future cardiometabolic disease.
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Huvinen E, Tuomaala AK, Bergman PH, Meinilä J, Tammelin T, Kulmala J, Engberg E, Koivusalo SB. Ascending Growth is Associated with Offspring Adiposity in Pregnancies Complicated with Obesity or Gestational Diabetes. J Clin Endocrinol Metab 2021; 106:e1993-e2004. [PMID: 33524144 DOI: 10.1210/clinem/dgaa979] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Indexed: 11/19/2022]
Abstract
CONTEXT Early growth is associated with childhood adiposity, but the influence of lifestyle remains unknown. OBJECTIVE This work aimed to investigate the association of growth profiles from high-risk pregnancies with adiposity at age 5 years, taking into account lifestyle and several antenatal/postnatal exposures. METHODS This prospective cohort study. INCLUDED 609 children born during the Finnish Gestational Diabetes Prevention Study (RADIEL), recruiting women with body mass index (BMI) greater than or equal to 30 and/or prior gestational diabetes mellitus (GDM) (2008-2013). Altogether 332 children attended the 5-year follow-up (2014-2017). Main outcome measures included growth profiles based on ponderal index (PI = weight/height3), investigated using latent class mixed models. Adiposity was assessed with anthropometrics and body composition (InBody720). RESULTS We identified 3 growth profiles: ascending (n = 82), intermediate (n = 351), and descending (n = 149). Children with ascending growth had a higher body fat percentage, ISO-BMI, and waist circumference (P < .05) at age 5 years. Ascending (β 4.09; CI, 1.60-6.58) and intermediate (β 2.27; CI, 0.50-4.03) profiles were associated with higher fat percentage, even after adjustment for age, sex, gestational age, diet, physical activity, education, and prepregnancy BMI. Similar associations existed with ISO-BMI. After adjusting for age and education, ascending growth was associated with prepregnancy BMI (odds ratio [OR] 1.06; CI, 1.01-1.12), primiparity (OR 3.07; CI, 1.68-5.62), cesarean delivery (OR 2.23; CI, 1.18-4.21), and lifestyle intervention (OR 2.56; CI, 1.44-4.57). However, meeting the intervention goals and exclusive breastfeeding for 3 months or more were associated with lower odds of ascending growth. CONCLUSION Accelerated early growth was associated with higher adiposity in 5-year-old children from high-risk pregnancies, even when adjusted for lifestyle. Reducing cesarean deliveries and promoting breastfeeding may be beneficial for postnatal growth.
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Affiliation(s)
- Emilia Huvinen
- Teratology Information Service, Emergency Medicine, Department of Prehospital Emergency Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Anna-Kaisa Tuomaala
- Department of Pediatrics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Paula H Bergman
- Biostatistics Consulting, Department of Public Health, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jelena Meinilä
- Department of Food and Nutrition, University of Helsinki, Helsinki, Finland
| | - Tuija Tammelin
- LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland
| | - Janne Kulmala
- LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland
| | - Elina Engberg
- Folkhälsan Research Center, Helsinki, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Saila B Koivusalo
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Maternal and infant prediction of the child BMI trajectories; studies across two generations of Northern Finland birth cohorts. Int J Obes (Lond) 2020; 45:404-414. [PMID: 33041325 DOI: 10.1038/s41366-020-00695-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 08/05/2020] [Accepted: 09/26/2020] [Indexed: 11/08/2022]
Abstract
BACKGROUND/OBJECTIVE Children BMI is a longitudinal phenotype, developing through interplays between genetic and environmental factors. Whilst childhood obesity is escalating, we require a better understanding of its early origins and variation across generations to prevent it. SUBJECTS/METHODS We designed a cross-cohort study including 12,040 Finnish children from the Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986) born before or at the start of the obesity epidemic. We used group-based trajectory modelling to identify BMI trajectories from 2 to 20 years. We subsequently tested their associations with early determinants (mother and child) and the possible difference between generations, adjusted for relevant biological and socioeconomic confounders. RESULTS We identified four BMI trajectories, 'stable-low' (34.8%), 'normal' (44.0%), 'stable-high' (17.5%) and 'early-increase' (3.7%). The 'early-increase' trajectory represented the highest risk for obesity. We analysed a dose-response association of maternal pre-pregnancy BMI and smoking with BMI trajectories. The directions of effect were consistent across generations and the effect sizes tended to increase from earlier generation to later. Respectively for NFBC1966 and NFBC1986, the adjusted risk ratios of being in the early-increase group were 1.08 (1.06-1.10) and 1.12 (1.09-1.15) per unit of pre-pregnancy BMI and 1.44 (1.05-1.96) and 1.48 (1.17-1.87) in offspring of smoking mothers compared to non-smokers. We observed similar relations with infant factors including birthweight for gestational age and peak weight velocity. In contrast, the age at adiposity peak in infancy was associated with the BMI trajectories in NFBC1966 but did not replicate in NFBC1986. CONCLUSIONS Exposures to adverse maternal predictors were associated with a higher risk obesity trajectory and were consistent across generations. However, we found a discordant association for the timing of adiposity peak over a 20-year period. This suggests the role of residual environmental factors, such as nutrition, and warrants additional research to understand the underlying gene-environment interplay.
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12
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Couto Alves A, De Silva NMG, Karhunen V, Sovio U, Das S, Taal HR, Warrington NM, Lewin AM, Kaakinen M, Cousminer DL, Thiering E, Timpson NJ, Bond TA, Lowry E, Brown CD, Estivill X, Lindi V, Bradfield JP, Geller F, Speed D, Coin LJM, Loh M, Barton SJ, Beilin LJ, Bisgaard H, Bønnelykke K, Alili R, Hatoum IJ, Schramm K, Cartwright R, Charles MA, Salerno V, Clément K, Claringbould AAJ, van Duijn CM, Moltchanova E, Eriksson JG, Elks C, Feenstra B, Flexeder C, Franks S, Frayling TM, Freathy RM, Elliott P, Widén E, Hakonarson H, Hattersley AT, Rodriguez A, Banterle M, Heinrich J, Heude B, Holloway JW, Hofman A, Hyppönen E, Inskip H, Kaplan LM, Hedman AK, Läärä E, Prokisch H, Grallert H, Lakka TA, Lawlor DA, Melbye M, Ahluwalia TS, Marinelli M, Millwood IY, Palmer LJ, Pennell CE, Perry JR, Ring SM, Savolainen MJ, Rivadeneira F, Standl M, Sunyer J, Tiesler CMT, Uitterlinden AG, Schierding W, O’Sullivan JM, Prokopenko I, Herzig KH, Smith GD, O'Reilly P, Felix JF, Buxton JL, Blakemore AIF, Ong KK, Jaddoe VWV, Grant SFA, Sebert S, McCarthy MI, Järvelin MR. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. SCIENCE ADVANCES 2019; 5:eaaw3095. [PMID: 31840077 PMCID: PMC6904961 DOI: 10.1126/sciadv.aaw3095] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 08/06/2019] [Indexed: 05/29/2023]
Abstract
Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
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Affiliation(s)
- Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | - N. Maneka G. De Silva
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Ulla Sovio
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Shikta Das
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - H. Rob Taal
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
| | - Nicole M. Warrington
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
| | - Alexandra M. Lewin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Marika Kaakinen
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
| | - Diana L. Cousminer
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Elisabeth Thiering
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom A. Bond
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Estelle Lowry
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Christopher D. Brown
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xavier Estivill
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Virpi Lindi
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
| | - Jonathan P. Bradfield
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Doug Speed
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
| | - Lachlan J. M. Coin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Marie Loh
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
| | - Sheila J. Barton
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Lawrence J. Beilin
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
| | - Hans Bisgaard
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Klaus Bønnelykke
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rohia Alili
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
| | - Ida J. Hatoum
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Katharina Schramm
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
| | - Rufus Cartwright
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Marie-Aline Charles
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - Vincenzo Salerno
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Karine Clément
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - Annique A. J. Claringbould
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
| | - BIOS Consortium
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Sidra Medical and Research Center, Doha, Qatar
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Elena Moltchanova
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Cathy Elks
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Claudia Flexeder
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Stephen Franks
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Timothy M. Frayling
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Rachel M. Freathy
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Hakon Hakonarson
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew T. Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Alina Rodriguez
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
| | - Marco Banterle
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Barbara Heude
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - John W. Holloway
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Albert Hofman
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Elina Hyppönen
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
| | - Hazel Inskip
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Lee M. Kaplan
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Asa K. Hedman
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Esa Läärä
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Timo A. Lakka
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Debbie A. Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
| | - Tarunveer S. Ahluwalia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcella Marinelli
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
| | - Iona Y. Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
| | - Lyle J. Palmer
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
| | - Craig E. Pennell
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - John R. Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Susan M. Ring
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Markku J. Savolainen
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Jordi Sunyer
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
| | - Carla M. T. Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Andre G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - Justin M. O’Sullivan
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
| | - Inga Prokopenko
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
| | - Karl-Heinz Herzig
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Paul O'Reilly
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jessica L. Buxton
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
| | - Alexandra I. F. Blakemore
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
| | - Ken K. Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Struan F. A. Grant
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sylvain Sebert
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Early Growth Genetics (EGG) Consortium
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Sidra Medical and Research Center, Doha, Qatar
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
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13
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Vogelezang S, Santos S, Toemen L, Oei EHG, Felix JF, Jaddoe VWV. Associations of Fetal and Infant Weight Change With General, Visceral, and Organ Adiposity at School Age. JAMA Netw Open 2019; 2:e192843. [PMID: 31026028 PMCID: PMC6487630 DOI: 10.1001/jamanetworkopen.2019.2843] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
IMPORTANCE Both fetal and infant growth influence obesity later in life. The association of longitudinal fetal and infant growth patterns with organ fat is unknown. OBJECTIVE To examine the associations of fetal and infant weight change with general, visceral, and organ adiposity at school age. DESIGN, SETTING, AND PARTICIPANTS This cohort study was embedded in the Generation R Study, a population-based prospective cohort study in Rotterdam, the Netherlands. Pregnant women with a delivery date between April 2002 and January 2006 were eligible to participate. Follow-up measurements were performed for 3205 children. Data analysis of this population was performed from July 26, 2018, to February 7, 2019. EXPOSURES Fetal weight was estimated in the second and third trimester of pregnancy. Infant weight was measured at 6, 12, and 24 months. Fetal and infant weight acceleration or deceleration were defined as a change in standard deviation scores greater than 0.67 between 2 ages. MAIN OUTCOMES AND MEASURES Visceral fat index, pericardial fat index, and liver fat fraction were measured by magnetic resonance imaging. RESULTS The sample consisted of 3205 children (1632 girls [50.9%]; mean [SD] age, 9.8 [0.3] years). Children born small for gestational age had the lowest median body mass index compared with children born appropriate for gestational age and large for gestational age (16.4 [90% range, 14.1-23.6] vs 16.9 [90% range, 14.4-22.8] vs 17.4 [90% range, 14.9-22.7]). Compared with children with normal fetal and infant growth (533 of 2370 [22.5%]), those with fetal weight deceleration followed by infant weight acceleration (263 of 2370 [11.1%]) had the highest visceral fat index (standard deviation scores, 0.18; 95% CI, 0.03-0.33; P = .02) and liver fat fraction (standard deviation scores, 0.34; 95% CI, 0.20-0.48; P < .001). CONCLUSIONS AND RELEVANCE Fetal and infant weight change patterns were both associated with childhood body fat, but weight change patterns in infancy tended to have larger effects. Fetal growth restriction followed by infant growth acceleration was associated with increased visceral and liver fat.
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Affiliation(s)
- Suzanne Vogelezang
- The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Paediatrics, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Susana Santos
- The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Paediatrics, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Liza Toemen
- The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Paediatrics, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Edwin H. G. Oei
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Janine F. Felix
- The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Paediatrics, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Paediatrics, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
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14
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Abstract
Blood pressure (BP) tracks from childhood to adulthood, and early BP trajectories predict cardiovascular disease risk later in life. Excess postnatal weight gain is associated with vascular changes early in life. However, to what extent it is associated with children's BP is largely unknown. In 853 healthy 5-year-old children of the Wheezing-Illnesses-Study-Leidsche-Rijn (WHISTLER) birth cohort, systolic (SBP) and diastolic BP (DBP) were measured, and z scores of individual weight gain rates adjusted for length gain rates were calculated using at least two weight and length measurements from birth until 3 months of age. Linear regression analyses were conducted to investigate the association between weight gain rates adjusted for length gain rates and BP adjusted for sex and ethnicity. Each standard deviation increase in weight gain rates adjusted for length gain rates was associated with 0.9 mmHg (95% CI 0.3, 1.5) higher sitting SBP after adjustment for confounders. Particularly in children in the lowest birth size decile, high excess weight gain was associated with higher sitting SBP values compared to children with low weight gain rates adjusted for length gain rates. BMI and visceral adipose tissue partly explained the association between excess weight gain and sitting SBP (β 0.5 mmHg, 95% CI -0.3, 1.3). Weight gain rates adjusted for length gain rates were not associated with supine SBP or DBP. Children with excess weight gain, properly adjusted for length gain, in the first three months of life, particularly those with a small birth size, showed higher sitting systolic BP at the age of 5 years.
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15
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Abrantes MA, Valencia AM, Bany-Mohammed F, Aranda JV, Beharry KD. Dose response effects of postnatal hydrocortisone on growth and growth factors in the neonatal rat. Steroids 2018; 140:1-10. [PMID: 30142369 DOI: 10.1016/j.steroids.2018.08.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 08/08/2018] [Accepted: 08/13/2018] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE Hydrocortisone (HC), at different dosages, is used in critically ill newborns for lung stability, blood pressure support, and prevention of chronic lung disease (CLD). Its long-term effects on postnatal growth are not well studied. We hypothesized that early exposure to high doses of HC adversely affects growth, growth factors, metabolic hormones, and neurological outcomes, persisting in adulthood. EXPERIMENTAL DESIGN Rat pups received a single daily intramuscular dose of HC (1 mg/kg/day, 5 mg/kg/day, or 10 mg/kg/day on days 3, 4 & 5 postnatal age (P3, P4, P5). Age-matched controls received equivalent volume saline. Body weight, linear growth, and neurological outcomes were monitored. Animals were sacrificed at P21, P45, and P70 for blood glucose, insulin, IGF-I, GH, leptin, and corticosterone levels. Liver mRNA expression of IGFs and IGFBPs were determined at P21 and P70. Memory and learning abilities were tested using the Morris water maze test at P70. RESULTS HC suppressed body weight and length at P12, P21 and P45, but by P70 there was catchup overgrowth in the 5 and 10 mg/kg/day groups. At P70 blood insulin, IGF-I, GH, and leptin levels were low, whereas blood glucose, and liver IGFs and IGFBPs were high in the high dose groups. High HC also caused delayed memory and learning abilities at P70. CONCLUSIONS These data demonstrate that while higher doses of HC may be required for hemodynamic stability and prevention of CLD, these doses may result in growth deficits, as well as neurological and metabolic sequelae in adulthood.
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Affiliation(s)
- Maria A Abrantes
- Department of Pediatrics, Division of Neonatal-Perinatal Medicine, Long Beach Memorial Medical Center, Long Beach, CA 90806, USA; Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of California, Irvine Medical Center, Orange, CA 92868, USA; Department of Pediatrics, Division of Neonatal-Perinatal Medicine, Kaiser Permanente, Anaheim, CA 92806, USA
| | - Arwin M Valencia
- Department of Pediatrics, Division of Neonatal-Perinatal Medicine, Long Beach Memorial Medical Center, Long Beach, CA 90806, USA; Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of California, Irvine Medical Center, Orange, CA 92868, USA; Department of Pediatrics, Division of Neonatal-Perinatal Medicine, Saddleback Memorial Medical Center, Laguna Hills, CA 92653, USA
| | - Fayez Bany-Mohammed
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of California, Irvine Medical Center, Orange, CA 92868, USA.
| | - Jacob V Aranda
- Department of Pediatrics, Division of Neonatal-Perinatal Medicine, State University of New York, Downstate Medical Center, Brooklyn, NY 11203, USA; Department of Ophthalmology, Division of Neonatal-Perinatal Medicine, State University of New York, Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - Kay D Beharry
- Department of Pediatrics, Division of Neonatal-Perinatal Medicine, Long Beach Memorial Medical Center, Long Beach, CA 90806, USA; Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of California, Irvine Medical Center, Orange, CA 92868, USA; Department of Pediatrics, Division of Neonatal-Perinatal Medicine, State University of New York, Downstate Medical Center, Brooklyn, NY 11203, USA; Department of Ophthalmology, Division of Neonatal-Perinatal Medicine, State University of New York, Downstate Medical Center, Brooklyn, NY 11203, USA.
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16
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Nedelec R, Jokelainen J, Miettunen J, Ruokonen A, Herzig KH, Männikkö M, Järvelin MR, Sebert S. Early determinants of metabolically healthy obesity in young adults: study of the Northern Finland Birth Cohort 1966. Int J Obes (Lond) 2018; 42:1704-1714. [PMID: 29795454 DOI: 10.1038/s41366-018-0115-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 04/06/2018] [Accepted: 04/17/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND A body of literature suggests a metabolically healthy phenotype in individuals with obesity. Despite important clinical implications, the early origins of metabolically healthy obesity (MHO) have received little attention. OBJECTIVE To assess the prevalence of MHO among the Northern Finland Birth Cohort 1966 (NFBC1966) at 31 years of age, examine its determinants in early life taking into account the sex specificity. METHODS We studied 3205 term-born cohort participants with data available for cardio-metabolic health outcomes at 31 years, and longitudinal height and weight data. After stratifying the population by sex, adult BMI and a strict definition of metabolic health (i.e., no risk factors meaning metabolic health), we obtained six groups. Repeated childhood height and weight measures were used to model early growth and early adiposity phenotypes. We employed marginal means adjusted for mother and child covariates including socio-economic status, birth weight and gestational-age, to compare differences between the groups. RESULTS The prevalence of adult MHO was 6% in men and 13.5% in women. Differences in adult metabolic status were linked to alterations in BMI and age at adiposity peak in infancy (p < 0.0003 in men and p = 0.027 in women), and BMI and age at adiposity rebound (AR) (p < 0.0001 irrespective of sex). Compared to MHO, metabolically unhealthy obese (MUO) women were five and a half months younger at AR (p = 0.007) with a higher BMI while MUO men were four months older (p = 0.036) with no difference in BMI at AR. CONCLUSION At the time of AR, MHO women appeared to be older than their MUO counterparts while MHO men were younger. These original results support potential risk factors at the time of adiposity rebound linked to metabolic health in adulthood. These variations by sex warrant independent replication.
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Affiliation(s)
- Rozenn Nedelec
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jari Jokelainen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University, Oulu, Finland
| | - Aimo Ruokonen
- NordLab Oulu, Department of Clinical Chemistry, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Karl-Heinz Herzig
- Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University, Oulu, Finland.,Research Unit of Biomedicine, Department of Physiology, University of Oulu, Oulu, Finland.,Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Minna Männikkö
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland. .,Biocenter Oulu, University of Oulu, Oulu, Finland. .,Unit of Primary Care, Oulu University Hospital, Oulu, Finland. .,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK. .,MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK. .,Department of Life Sciences, College of Health and Life Sciences, Brunel University, London, UK.
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Genomics of Complex Diseases, School of Public Health, Imperial College, London, UK
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17
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Lei X, Zhao D, Huang L, Luo Z, Zhang J, Yu X, Zhang Y. Childhood Health Outcomes in Term, Large-for-Gestational-Age Babies With Different Postnatal Growth Patterns. Am J Epidemiol 2018; 187:507-514. [PMID: 28992219 DOI: 10.1093/aje/kwx271] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 06/28/2017] [Indexed: 01/03/2023] Open
Abstract
Large-for-gestational-age (LGA) babies have a higher risk of metabolic disease later in life, and their postnatal growth in early childhood may be associated with long-term adverse outcomes. This study aimed to determine childhood health outcomes of term LGA babies with different growth patterns. Data were obtained from the US Collaborative Perinatal Project for the years between 1959 and 1976. The growth trajectories of 3,316 term LGA babies were identified and odds ratios of obesity, growth restriction, low intelligence quotient (IQ), and high blood pressure (HBP) were calculated by logistic regression. Compared with term appropriate-for-gestational-age infants, term LGA babies without catch-down growth had increased risks of obesity (adjusted odds ratio (aOR) = 6.37, 95% confidence interval (CI): 5.24, 7.73) and HBP (aOR = 1.67, 95% CI: 1.37, 2.03). Those with high catch-down growth had higher risks of growth restriction (aOR = 2.21, 95% CI: 1.66, 2.95) and low IQ (aOR = 1.61, 95% CI: 1.04, 2.49). Nevertheless, infants with small catch-down growth had lower risks of obesity (aOR = 0.78, 95% CI: 0.63, 0.95), growth restriction (aOR = 0.28, 95% CI: 0.17, 0.46), low IQ (aOR = 0.66, 95% CI: 0.41, 1.06), and HBP (aOR = 0.89, 95% CI: 0.77, 1.04). According to our data, term LGA infants with small catch-down growth had no increased risks of adverse outcomes.
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Affiliation(s)
- Xiaoping Lei
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
- Department of Neonatology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of China
| | - Dongying Zhao
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Lisu Huang
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Zhongcheng Luo
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
- MOE-Shanghai Key Laboratory of Children’s Environmental Health, Shanghai, People’s Republic of China
| | - Jun Zhang
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
- MOE-Shanghai Key Laboratory of Children’s Environmental Health, Shanghai, People’s Republic of China
| | - Xiaodan Yu
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
- MOE-Shanghai Key Laboratory of Children’s Environmental Health, Shanghai, People’s Republic of China
| | - Yongjun Zhang
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
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18
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Neonatal corticosteroid therapy affects growth patterns in early infancy. PLoS One 2018; 13:e0192162. [PMID: 29432424 PMCID: PMC5809117 DOI: 10.1371/journal.pone.0192162] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 01/17/2018] [Indexed: 12/15/2022] Open
Abstract
Objective Although postnatal corticosteroid (CS) therapy has well established beneficial effects on pulmonary function, it may also result in growth restriction during treatment. The course of early childhood growth is believed to predict cardiovascular and metabolic diseases in adulthood. Therefore, we determined the effects of postnatal dexamethasone (DEX) or hydrocortisone (HC) treatment on patterns of postnatal growth until approximately four years of age. Study design In an observational cohort study of children born prematurely (<32 weeks of gestation), we compared growth patterns for body weight, height, and head circumference from birth to age four years, of children who received DEX (boys: N = 30, girls: N = 14), HC (boys: N = 33, girls: N = 28) to a reference group that had not received postnatal CSs (boys: N = 52, girls: N = 53) using linear mixed-effects modeling. Results Growth velocity curves of CS-treated neonates showed a shift to the right, representing a delay in time. They had decreased absolute growth velocities during and shortly after treatment, followed by an increase in growth velocity thereafter. A shift to the right was also seen for the age at which maximal growth velocity of weight/height was reached in boys and girls. Fractional growth rates of weight, height, and head circumference were generally reduced in the CS-treated groups during the first two months of age, with catch-up growth in the following months. In DEX-treated infants these changes were more pronounced than in HC-treated infants. Conclusion These data suggest that postnatal growth patterns of preterm born infants are affected by CS-treatment, more by DEX than by HC. Effects were observed mainly on growth velocities. This observation may have impact on health in later life for those individuals treated with CSs in the neonatal period. A definitive conclusion would require a randomized trial of these therapies.
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19
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Ng DVY, Unger S, Asbury M, Kiss A, Bishara R, Bando N, Tomlinson C, Gibbins S, O'Connor DL. Neonatal Morbidity Count Is Associated With a Reduced Likelihood of Achieving Recommendations for Protein, Lipid, and Energy in Very Low Birth Weight Infants: A Prospective Cohort Study. JPEN J Parenter Enteral Nutr 2017; 42:623-632. [PMID: 28537798 DOI: 10.1177/0148607117710441] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2016] [Accepted: 04/27/2017] [Indexed: 01/02/2023]
Abstract
BACKGROUND Serious morbidity may elevate nutrient requirements and affect adherence to feeding guidelines for very low birth weight (VLBW) infants. An understanding of factors affecting nutrient intakes of VLBW infants will facilitate development of strategies to improve nutrient provision. Our aim was to examine the impact of neonatal morbidity count on achieving recommended nutrient intakes in VLBW infants. METHODS VLBW infants enrolled in the Donor Milk for Improved Neurodevelopmental Outcomes trial (ISRCTN35317141, n = 363) were included. Serious morbidities and daily parenteral and enteral intakes were collected prospectively. RESULTS Median intakes of infants with and without ≥1 morbidity met protein recommendations (3.5-4.5 g/kg/d) by week 2, although not maintained after week 4. Infants with ≥1 morbidity (vs without) were 2 weeks slower in achieving lipid (4.8-6.6 g/kg/d; week 4 vs 2) and energy (110-130 kcal/kg/d; week 5 vs 3) and 1 week slower in achieving carbohydrate recommendations (11.6-13.2 g/kg/d; week 4 vs 3). Adjusted hazard ratios of first achieving recommendations on any given day in infants with any 1 or 2 morbidities were 0.6 (95% confidence interval [CI], 0.5-0.9) and 0.6 (0.4-0.9), respectively, for protein; 0.5 (0.4-0.7) and 0.3 (0.2-0.5) for lipid; and 0.5 (0.4-0.7) and 0.3 (0.2-0.4) for energy. CONCLUSION Morbidity is associated with a decreased likelihood of achieving lipid and consequently energy recommendations. This and the decline in protein intakes after the early neonatal period require further investigation to ensure optimal nutrition in this vulnerable population.
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Affiliation(s)
- Dawn V Y Ng
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.,SickKids Research Institute, Toronto, Ontario, Canada
| | - Sharon Unger
- SickKids Research Institute, Toronto, Ontario, Canada.,Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.,Department of Pediatrics, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Michelle Asbury
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.,SickKids Research Institute, Toronto, Ontario, Canada
| | - Alex Kiss
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.,Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Rosine Bishara
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Nicole Bando
- SickKids Research Institute, Toronto, Ontario, Canada
| | - Chris Tomlinson
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.,SickKids Research Institute, Toronto, Ontario, Canada.,Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada
| | | | - Deborah L O'Connor
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.,SickKids Research Institute, Toronto, Ontario, Canada.,Department of Pediatrics, Mount Sinai Hospital, Toronto, Ontario, Canada
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20
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Matinolli HM, Hovi P, Levälahti E, Kaseva N, Silveira PP, Hemiö K, Järvenpää AL, Eriksson JG, Andersson S, Lindström J, Männistö S, Kajantie E. Neonatal Nutrition Predicts Energy Balance in Young Adults Born Preterm at Very Low Birth Weight. Nutrients 2017; 9:nu9121282. [PMID: 29186804 PMCID: PMC5748733 DOI: 10.3390/nu9121282] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 11/20/2017] [Accepted: 11/21/2017] [Indexed: 12/17/2022] Open
Abstract
Epidemiological studies and animal models suggest that early postnatal nutrition and growth can influence adult health. However, few human studies have objective recordings of early nutrient intake. We studied whether nutrient intake and growth during the first 9 weeks after preterm birth with very low birth weight (VLBW, <1500 g) predict total energy intake, resting energy expenditure (REE), physical activity and food preferences in young adulthood. We collected daily nutritional intakes and weights during the initial hospital stay from hospital records for 127 unimpaired VLBW participants. At an average age 22.5 years, they completed a three-day food record and a physical activity questionnaire and underwent measurements of body composition (dual X-ray absorptiometry; n = 115 with adequate data) and REE (n = 92 with adequate data). We used linear regression and path analysis to investigate associations between neonatal nutrient intake and adult outcomes. Higher energy, protein and fat intakes during the first three weeks of life predicted lower relative (=per unit lean body mass) energy intake and relative REE in adulthood, independent of other pre- and neonatal factors. In path analysis, total effects of early nutrition and growth on relative energy intake were mostly explained by direct effects of early life nutrition. A path mediated by early growth reached statistical significance only for protein intake. There were no associations of neonatal intakes with physical activity or food preferences in adulthood. As a conclusion, higher intake of energy and nutrients during first three weeks of life of VLBW infants predicts energy balance after 20 years. This association is partly mediated through postnatal growth.
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Affiliation(s)
- Hanna-Maria Matinolli
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
- Institute for Health Sciences, University of Oulu, FI-90014 Oulu, Finland
- Correspondence: ; Tel.: +358-29-524-6000
| | - Petteri Hovi
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
- Children’s Hospital, University of Helsinki and Helsinki University Hospital, FI-00290 Helsinki, Finland; (A.-L.J.); (S.A.)
| | - Esko Levälahti
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
| | - Nina Kaseva
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
| | - Patricia P. Silveira
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC H3T 1E2, Canada;
| | - Katri Hemiö
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
| | - Anna-Liisa Järvenpää
- Children’s Hospital, University of Helsinki and Helsinki University Hospital, FI-00290 Helsinki, Finland; (A.-L.J.); (S.A.)
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, FI-00014 Helsinki, Finland;
- Folkhälsan Research Center, FI-00280 Helsinki, Finland
| | - Sture Andersson
- Children’s Hospital, University of Helsinki and Helsinki University Hospital, FI-00290 Helsinki, Finland; (A.-L.J.); (S.A.)
| | - Jaana Lindström
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
| | - Satu Männistö
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
| | - Eero Kajantie
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271 Helsinki, Finland; (P.H.); (E.L.); (N.K.); (K.H.); (J.L.); (S.M.); (E.K.)
- Children’s Hospital, University of Helsinki and Helsinki University Hospital, FI-00290 Helsinki, Finland; (A.-L.J.); (S.A.)
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, FI-90014 Oulu, Finland
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21
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Ajala O, Mold F, Boughton C, Cooke D, Whyte M. Childhood predictors of cardiovascular disease in adulthood. A systematic review and meta-analysis. Obes Rev 2017; 18:1061-1070. [PMID: 28545166 DOI: 10.1111/obr.12561] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Revised: 04/01/2017] [Accepted: 04/04/2017] [Indexed: 11/27/2022]
Abstract
Childhood obesity predicts the risk of adult adiposity, which is associated with the earlier onset of cardiovascular disease [adult atherosclerotic cardiovascular disease, ACVD: hypertension, increased carotid intima media thickness (CIMT) stroke, ischemic heart disease (IHD)] and dysglycaemia. Because it is not known whether childhood obesity contributes to these diseases, we conducted a systematic review of studies that examine the ability of measures of obesity in childhood to predict dysglycaemia and ACVD. Data sources were Web of Science, MEDLINE, PubMed, CINAHL, Cochrane, SCOPUS, ProQuest and reference lists. Studies measuring body mass index (BMI), skin fold thickness and waist circumference were selected; of 1,954 studies, 18 met study criteria. Childhood BMI predicted CIMT: odds ratio (OR), 3.39 (95% confidence interval (CI), 2.02 to 5.67, P < 0.001) and risk of impaired glucose tolerance in adulthood, but its ability to predict ACVD events (stroke, IHD; OR, 1.04; 95% CI, 1.02 to 1.07; P < 0.001) and hypertension (OR, 1.17, 95% CI 1.06 to 1.27, P = 0.003) was weak-moderate. Body mass index was not predictive of systolic BP (r -0.57, P = 0.08) and weakly predicted diastolic BP (r 0.21, P = 0.002). Skin fold thickness in childhood weakly predicted CIMT in female adults only (rs 0.09, P < 0.05). Childhood BMI predicts the risk of dysglycaemia and abnormal CIMT in adulthood, but its ability to predict hypertension and ACVD events was weak and moderate, respectively. Skin fold thickness was a weak predictor of CIMT in female adults.
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Affiliation(s)
- O Ajala
- Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | - F Mold
- Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | - C Boughton
- Department Diabetes, King's College Hospital NHS Foundation Trust, London, UK
| | - D Cooke
- Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | - M Whyte
- Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK.,Department Diabetes, King's College Hospital NHS Foundation Trust, London, UK
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22
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Marinkovic T, Toemen L, Kruithof CJ, Reiss I, van Osch-Gevers L, Hofman A, Franco OH, Jaddoe VWV. Early Infant Growth Velocity Patterns and Cardiovascular and Metabolic Outcomes in Childhood. J Pediatr 2017; 186:57-63.e4. [PMID: 28256212 PMCID: PMC5489080 DOI: 10.1016/j.jpeds.2017.02.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 01/05/2017] [Accepted: 02/01/2017] [Indexed: 01/20/2023]
Abstract
OBJECTIVE To evaluate the impact of infant growth on childhood health by examining the associations of detailed longitudinal infant weight velocity patterns with childhood cardiovascular and metabolic outcomes. STUDY DESIGN In a population-based prospective cohort study of 4649 children, we used repeated growth measurements at age 0-3 years to derive peak weight velocity (PWV), age at adiposity peak (AGEAP), and body mass index at adiposity peak (BMIAP). At age 6 years, we measured blood pressure, left ventricular mass, and cholesterol, triglyceride, and insulin concentrations and defined children with clusters of risk factors. We assessed associations using 2 multivariable linear regression models. RESULTS A 1-SDS-higher infant PWV was associated with higher diastolic blood pressure (0.05 SDS; 95% CI, 0.02-0.09) and lower left ventricular mass (-0.05 SDS; 95% CI, -0.09 to -0.01), independent of body size. A 1-SDS-higher BMIAP was associated with higher systolic (0.12; 95% CI, 0.09-0.16) and diastolic (0.05; 95% CI, 0.01-0.08) blood pressure, but these associations were explained by childhood BMI. We did not observe any associations of PWV, BMIAP, and AGEAP with cholesterol and insulin concentrations. Higher PWV and AGEAP were associated with elevated risk of clustering of cardiovascular risk factors in childhood (P < .05). CONCLUSION Infant weight velocity patterns are associated with cardiovascular outcomes. Further studies are needed to explore the associations with metabolic outcomes and long-term consequences.
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Affiliation(s)
- Tamara Marinkovic
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Liza Toemen
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Claudia J Kruithof
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Irwin Reiss
- Department of Pediatrics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Lennie van Osch-Gevers
- Department of Pediatrics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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23
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Kim J, Lee I, Lim S. Overweight or obesity in children aged 0 to 6 and the risk of adult metabolic syndrome: A systematic review and meta-analysis. J Clin Nurs 2017; 26:3869-3880. [DOI: 10.1111/jocn.13802] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/04/2017] [Indexed: 11/28/2022]
Affiliation(s)
- Jieun Kim
- College of Nursing; Chungcheong University; Cheongju Korea
| | - Insook Lee
- College of Nursing; Chungcheong University; Cheongju Korea
- Research of Institute of Nursing Science; College of Nursing; Seoul National University; Seoul Korea
| | - Sungwon Lim
- Research of Institute of Nursing Science; College of Nursing; Seoul National University; Seoul Korea
- Research Institute of Health Sciences; Korea University; Seoul Korea
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24
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Casas M, den Dekker HT, Kruithof CJ, Reiss IK, Vrijheid M, de Jongste JC, Jaddoe VWV, Duijts L. Early childhood growth patterns and school-age respiratory resistance, fractional exhaled nitric oxide and asthma. Pediatr Allergy Immunol 2016; 27:854-860. [PMID: 27591561 DOI: 10.1111/pai.12645] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/01/2016] [Indexed: 10/21/2022]
Abstract
BACKGROUND Greater infant weight gain is associated with lower lung function and increased risk of childhood asthma. The role of early childhood peak growth patterns is unclear. We assessed the associations of individually derived early childhood peak growth patterns with respiratory resistance, fractional exhaled nitric oxide, wheezing patterns, and asthma until school-age. METHODS We performed a population-based prospective cohort study among 5364 children. Repeated growth measurements between 0 and 3 years of age were used to derive standard deviation scores (s.d.s) of peak height and weight velocities (PHV and PWV, respectively), and body mass index (BMI) and age at adiposity peak. Respiratory resistance and fractional exhaled nitric oxide were measured at 6 years of age. Wheezing patterns and asthma were prospectively assessed by annual questionnaires. We also assessed whether any association was explained by childhood weight status. RESULTS Greater PHV was associated with lower respiratory resistance [Z-score (95% CI): -0.03 (-0.04, -0.01) per s.d.s increase] (n = 3382). Greater PWV and BMI at adiposity peak were associated with increased risks of early wheezing [relative risk ratio (95% CI): 1.11 (1.06, 1.16), 1.26 (1.11, 1.43), respectively] and persistent wheezing [relative risk ratio (95% CI): 1.09 (1.03, 1.16), 1.37 (1.17, 1.60), respectively] (n = 3189 and n = 3005, respectively). Childhood weight status partly explained these associations. No other associations were observed. CONCLUSIONS PWV and BMI at adiposity peak are critical for lung developmental and risk of school-age wheezing. Follow-up studies at older ages are needed to elucidate whether these effects persist at later ages.
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Affiliation(s)
- Maribel Casas
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Division of Respiratory Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Herman T den Dekker
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Division of Respiratory Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Claudia J Kruithof
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Irwin K Reiss
- Department of Pediatrics, Division of Neonatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martine Vrijheid
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Johan C de Jongste
- Department of Pediatrics, Division of Respiratory Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Liesbeth Duijts
- Department of Pediatrics, Division of Respiratory Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Division of Neonatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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25
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Giapros V, Vavva E, Siomou E, Kolios G, Tsabouri S, Cholevas V, Bairaktari E, Tzoufi M, Challa A. Low-birth-weight, but not catch-up growth, correlates with insulin resistance and resistin level in SGA infants at 12 months. J Matern Fetal Neonatal Med 2016; 30:1771-1776. [PMID: 27609490 DOI: 10.1080/14767058.2016.1224838] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVE To investigate the insulin resistance status in SGA infants at 12 months and its relationship with auxological and metabolic parameters. METHODS One group of 45 SGA and one of 50 appropriate for gestational age infants were followed from birth to the end of the first year of life. At 12 months, skinfold thickness, waist circumference, and blood levels of glucose, insulin, adiponectin, leptin, resistin, visfatin, retinol-binding protein 4, IGFs, lipids profile were determined, and the HOMA-IR index was calculated. RESULTS The SGAs had increased insulin (5.2 ± 2.7 versus 2.9 ± 2.4 μIU/ml, p = 0.012) and HOMA-IR (1.09 ± 0.9 versus 0.59 ± 0.55, p = 0.016). In multiple regression, insulin resistance indices were independently correlated with low-birth-weight (β = -2.92, p = 0.015 for insulin, β = -2.98, p = 0.011 for HOMA-IR) but not with catch-up growth in either height or weight or any other metabolic parameter. Resistin was higher in the SGAs (5.1 ± 2.1 versus 3.9 ± 2.1 ng/ml, p = 0.03) and independently correlated with low-birth-weight but not insulin resistance. Resistin was negatively correlated with total cholesterol (R = -0.33, p = 0.007) and positively with lipoprotein(a) (R = 0.49, p = 0.001). CONCLUSION Low-birth-weight, but not catch-up growth or adiposity tissue hormones, was correlated with insulin resistance at 12 months in non-obese SGA infants. The higher resistin in SGA infants and its correlation with total cholesterol and lipoprotein(a) need further clarification.
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Affiliation(s)
| | | | | | | | | | - Vasileios Cholevas
- c Pediatric Research Laboratory , University of Ioannina , Ioannina , Greece
| | | | - Meropi Tzoufi
- a Neonatal Intensive Care Unit, Child Health Department
| | - Anna Challa
- c Pediatric Research Laboratory , University of Ioannina , Ioannina , Greece
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26
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Monnereau C, Vogelezang S, Kruithof CJ, Jaddoe VWV, Felix JF. Associations of genetic risk scores based on adult adiposity pathways with childhood growth and adiposity measures. BMC Genet 2016; 17:120. [PMID: 27538985 PMCID: PMC4991119 DOI: 10.1186/s12863-016-0425-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 08/11/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures. METHODS We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models. RESULTS A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area. CONCLUSIONS A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards.
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Affiliation(s)
- Claire Monnereau
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands
| | - Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands
| | - Claudia J Kruithof
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands. .,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands. .,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000, CA, Rotterdam, The Netherlands.
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Grillo LP, Gigante DP, Horta BL, de Barros FCF. Childhood stunting and the metabolic syndrome components in young adults from a Brazilian birth cohort study. Eur J Clin Nutr 2016; 70:548-53. [PMID: 26733042 PMCID: PMC4858756 DOI: 10.1038/ejcn.2015.220] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2015] [Revised: 11/02/2015] [Accepted: 11/18/2015] [Indexed: 12/20/2022]
Abstract
BACKGROUND/OBJECTIVES The aim of this study was to investigate the association between stunting in the second year of life and metabolic syndrome components in early adulthood among subjects who have been prospectively followed-up since birth, in a city in Southern Brazil. SUBJECTS/METHODS In 1984, we attempted to follow-up the entire cohort; the subjects were examined and their mothers interviewed. Stunting was defined by a length-for-age Z-score 2 s.d. or more below the mean, in accordance with the World Health Organization reference. Between 2004 and 2005, we again tried to follow the entire cohort; during this period the subjects were evaluated for the following metabolic syndrome components: high-density lipoprotein (HDL) cholesterol, triglycerides, random blood glucose, waist circumference and systolic and diastolic blood pressure. Family income at the time of the baby's birth, asset index, mother's education, mother's smoking during pregnancy and duration of breastfeeding were considered possible confounders. Linear regression was used in the unadjusted and adjusted analyses. RESULTS Among men, stunting was inversely associated with triglycerides (β=-11.90, confidence interval (CI)=-22.33 to -1.48) and waist circumference (β=-4.29, CI=-5.62 to -2.97), whereas for women stunting was negatively related to HDL-cholesterol (β=-4.50, CI=-6.47 to -2.52), triglycerides (β=-9.61, CI=-17.66 to -1.56) and waist circumference (β=-1.14, CI=-4.22 to -1.02). However, after controlling for confounding variables, these associations vanished. CONCLUSIONS The findings suggest that stunting in childhood is not associated with metabolic syndrome components in young adults.
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Affiliation(s)
- L P Grillo
- Departament of Nutrition, Vale of Itajaí University, Itajaí, Santa Catarina, Brazil
- Epidemiological Research Center, Epidemiology Postgraduate Program, Federal University of Pelotas, Rio Grande do Sul, Brazil
| | - D P Gigante
- Epidemiological Research Center, Epidemiology Postgraduate Program, Federal University of Pelotas, Rio Grande do Sul, Brazil
- Departament of Nutrition, Federal University of Pelotas, Rio Grande do Sul, Brazil
| | - B L Horta
- Epidemiological Research Center, Epidemiology Postgraduate Program, Federal University of Pelotas, Rio Grande do Sul, Brazil
| | - F C F de Barros
- Epidemiological Research Center, Epidemiology Postgraduate Program, Federal University of Pelotas, Rio Grande do Sul, Brazil
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Infant weight growth velocity patterns and general and abdominal adiposity in school-age children. The Generation R Study. Eur J Clin Nutr 2016; 70:1144-1150. [PMID: 27071509 DOI: 10.1038/ejcn.2016.60] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Revised: 01/05/2016] [Accepted: 01/11/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND/OBJECTIVES The objective of this study was to examine the association of individually derived infant weight growth velocity patterns with general and abdominal adiposity measures in childhood. SUBJECTS/METHODS In a population-based prospective cohort study among 5126 children, we used repeated growth measurements between 0 and 3 years of age to derive peak weight velocity (PWV), age at adiposity peak (AGEAP) and body mass index at adiposity peak (BMIAP). At the median age of 6.0 years (95% range 5.7, 6.8), we estimated body mass index (BMI), body fat percentage, android/gynoid fat mass ratio and pre-peritoneal abdominal fat area by using dual-energy X-ray absorptiometry and abdominal ultrasound. RESULTS Higher infant PWV and BMIAP were associated with higher childhood BMI, body fat percentage, android/gynoid fat mass ratio and pre-peritoneal abdominal fat area (all P-values<0.05), with the strongest effect estimates for BMI (differences in BMI: 0.37 standard deviation (s.d.), 95% confidence interval (CI): 0.34, 0.39 and 0.45 s.d. (95% CI: 0.43, 0.48) per 1-s.d. increase in infant PWV and BMIAP, respectively). Infant AGEAP in the highest tertile (>0.75 years) was associated with higher general and abdominal adiposity among girls at the age of 6 years (all P-values<0.05). Similarly, a 1-s.d. higher infant PWV and BMIAP were associated with increased risks of childhood overweight (odds ratios (95% CI): 2.1 (1.9, 2.3) and 2.5 (2.2, 2.8), respectively). These associations were independent of gestational age and size at birth and tended to be stronger among girls. CONCLUSIONS Higher infant PWV and BMIAP are associated with adverse general and abdominal fat distribution profiles and increased risks of overweight at school age. Whether infant growth patterns add to the prediction of later overweight should be further studied.
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Claudia F, Thiering E, von Berg A, Berdel D, Hoffmann B, Koletzko S, Bauer CP, Koletzko B, Heinrich J, Schulz H. Peak weight velocity in infancy is negatively associated with lung function in adolescence. Pediatr Pulmonol 2016; 51:147-56. [PMID: 26073174 DOI: 10.1002/ppul.23216] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Revised: 04/14/2015] [Accepted: 04/19/2015] [Indexed: 01/30/2023]
Abstract
BACKGROUND Rapid weight gain during infancy increases childhood asthma risk, which might be related to impaired lung function. This study investigated associations between peak weight velocity (PWV) during the first two years of life and spirometric lung function indices at 15 years of age. METHODS Data from 1842 children participating in the GINIplus German birth cohort who underwent spirometry at age 15 were analysed. PWV was calculated from weight measurements obtained between birth and two years of age. Generalised additive models were fitted after adjustment for potential confounding factors (birth weight, height, and age at lung function testing). Results are presented per interquartile range increase (3.5 kg/year) in PWV. RESULTS PWV was negatively associated with pre-bronchodilation flow rates after extensive adjustment for potential confounders including asthma: forced expiratory flow at 50% of forced vital capacity (FEF50 ) decreased by 141 ml/s (95%CI = [-225;-57]), FEF75 by 84 ml/s [-144;-24] and FEF25-75 by 118 ml/s [-192;-44]. FEV1 /FVC was also negatively associated with PWV (-0.750% [-1.273;-0.226]) whereas forced expiratory volume in 1s (FEV1 ) and forced vital capacity (FVC) were not. Similar results were found for measurements post-bronchodilation. CONCLUSION Early life weight gain was negatively associated with flow indices in adolescence, suggesting structural changes in peripheral lungs.
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Affiliation(s)
- Flexeder Claudia
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Elisabeth Thiering
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Dr von Hauner Children's Hospital, Ludwig Maximilians University of Munich, Munich, Germany
| | - Andrea von Berg
- Department of Pediatrics, Marien-Hospital Wesel, Wesel, Germany
| | - Dietrich Berdel
- Department of Pediatrics, Marien-Hospital Wesel, Wesel, Germany
| | - Barbara Hoffmann
- IUF Leibniz Research Institute for Environmental Medicine and Medical Faculty, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Sibylle Koletzko
- Dr von Hauner Children's Hospital, Ludwig Maximilians University of Munich, Munich, Germany
| | - Carl-Peter Bauer
- Department of Pediatrics, Technical University of Munich, Munich, Germany
| | - Berthold Koletzko
- Dr von Hauner Children's Hospital, Ludwig Maximilians University of Munich, Munich, Germany
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research, Munich, Germany
| | - Holger Schulz
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
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VEJRAZKOVA D, LUKASOVA P, VANKOVA M, BRADNOVA O, VACINOVA G, VCELAK J, CIRMANOVA V, ANDELOVA K, KREJCI H, BENDLOVA B. Gestational Diabetes – Metabolic Risks of Adult Women With Respect to Birth Weight. Physiol Res 2015; 64:S135-45. [DOI: 10.33549/physiolres.933089] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Metabolic disorders such as obesity, insulin resistance and other components of metabolic syndrome (MetS) are connected with birth weight. Low and high birth weight is associated with a higher risk of developing type 2 diabetes mellitus, the mechanism is not clear. In this study, we evaluated the association between birth weight and anthropometric as well as biochemical components of MetS in women with a history of gestational diabetes mellitus (GDM) in comparison with control women. In part of the GDM group, we re-evaluated metabolic changes over 5-8 years. Anthropometry, blood pressure, glucose metabolism during the 3-h oGTT, lipid profile, uric acid, thyroid hormones, and liver enzymes were assessed. From the analyzed components of MetS in adult women we proved the association of low birth weight (birth weight <25th percentile) with glucose processing, in particular among women with a history of GDM. Low birth weight GDM women revealed significantly higher postchallenge insulin secretion and lower peripheral insulin sensitivity. Re-examinations indicate this association persists long after delivery.
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Affiliation(s)
- D. VEJRAZKOVA
- Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czech Republic
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Dearden L, Ozanne SE. Early life origins of metabolic disease: Developmental programming of hypothalamic pathways controlling energy homeostasis. Front Neuroendocrinol 2015; 39:3-16. [PMID: 26296796 DOI: 10.1016/j.yfrne.2015.08.001] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2015] [Revised: 08/07/2015] [Accepted: 08/17/2015] [Indexed: 12/30/2022]
Abstract
A wealth of animal and human studies demonstrate that perinatal exposure to adverse metabolic conditions - be it maternal obesity, diabetes or under-nutrition - results in predisposition of offspring to develop obesity later in life. This mechanism is a contributing factor to the exponential rise in obesity rates. Increased weight gain in offspring exposed to maternal obesity is usually associated with hyperphagia, implicating altered central regulation of energy homeostasis as an underlying cause. Perinatal development of the hypothalamus (a brain region key to metabolic regulation) is plastic and sensitive to metabolic signals during this critical time window. Recent research in non-human primate and rodent models has demonstrated that exposure to adverse maternal environments impairs the development of hypothalamic structure and consequently function, potentially underpinning metabolic phenotypes in later life. This review summarizes our current knowledge of how adverse perinatal environments program hypothalamic development and explores the mechanisms that could mediate these effects.
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Affiliation(s)
- Laura Dearden
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, United Kingdom
| | - Susan E Ozanne
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, United Kingdom.
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Early life obesity and chronic kidney disease in later life. Pediatr Nephrol 2015; 30:1255-63. [PMID: 25145270 DOI: 10.1007/s00467-014-2922-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Revised: 04/23/2014] [Accepted: 07/17/2014] [Indexed: 12/16/2022]
Abstract
The prevalence of chronic kidney disease (CKD) has increased considerably with a parallel rise in the prevalence of obesity. It is now recognized that early life nutrition has life-long effects on the susceptibility of an individual to develop obesity, diabetes, cardiovascular disease and CKD. The kidney can be programmed by a number of intrauterine and neonatal insults. Low birth weight (LBW) is one of the most identifiable markers of a suboptimal prenatal environment, and the important intrarenal factors sensitive to programming events include decreased nephron number and altered control of the renin-angiotensin system (RAS). LBW complicated by accelerated catch-up growth is associated with an increased risk of obesity, hypertension and CKD in later life. High birth weight and exposure to maternal diabetes or obesity can enhance the risk for developing CKD in later life. Rapid postnatal growth per se may also contribute to the subsequent development of obesity and CKD regardless of birth weight and prenatal nutrition. Although the mechanisms of renal risks due to early life nutritional programming remain largely unknown, experimental and clinical studies suggest the burdening role of early life obesity in longstanding cardiovascular and renal diseases.
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Li L, Hardy R, Kuh D, Power C. Life-course body mass index trajectories and blood pressure in mid life in two British birth cohorts: stronger associations in the later-born generation. Int J Epidemiol 2015; 44:1018-26. [PMID: 26078389 PMCID: PMC4521132 DOI: 10.1093/ije/dyv106] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2015] [Indexed: 11/12/2022] Open
Abstract
Background: Little is known about the impact of recent increases in obesity and more rapid gains in body mass index (BMI) on cardiovascular risk factors. We investigated life-course BMI trajectories associations with adult blood pressure (BP) across two generations. Methods: We used the the 1946 and 1958 British birth cohorts. Joint multivariate response models were fitted to longitudinal BMI measures [7, 11, 16, 20, 26, 36, 43 and 50 y (years): 1946 cohort, n = 4787; 7, 11, 16, 23, 33 and 45 y: 1958 cohort, n = 16 820] and mid-adult BP. We adopted linear spline models with random coefficients to characterize childhood and adult BMI slopes. Results: Mean systolic BP (SBP) decreased from the earlier- to later-born cohort by 2.8 mmHg in females, not males; mean diastolic BP (DBP) decreased by 3.2-3.3 mmHg (both sexes). Adult BMI was higher in the later- than the earlier-born cohort by 1.3-1.8 kg/m2, slopes of BMI trajectory were steeper from early adulthood and associations with adult BP were stronger. Associations between adult BMI and SBP were stronger in the later-born cohort. For males, childhood BMI slope was associated with SBP only in the later-born cohort; the association for adult BMI slope was stronger in the later-born cohort: correlation coefficient r = 0.28 [95% confidence interval (CI): 0.25,0.33] versus 0.13 (0.06,0.20). For females, childhood slope was associated with SBP in both cohorts; adult slope was associated with SBP only in the 1958 cohort [r = 0.34 (0.31,0.37)]. Patterns of child-to-adult BMI associations were similar in relation to DBP. Conclusions: BP did not increase between two generations born 12 y apart despite higher BMI levels. A stronger association between BMI trajectory and BP in the later-born cohort suggests that BMI-related effects may have been offset by improvements in other factors linked to BP, such as diet and smoking.
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Affiliation(s)
- Leah Li
- Centre for Paediatric Epidemiology & Biostatistics and
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing, University College London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, University College London, UK
| | - Chris Power
- Centre for Paediatric Epidemiology & Biostatistics and
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Adult adiposity susceptibility loci, early growth and general and abdominal fatness in childhood: the Generation R Study. Int J Obes (Lond) 2015; 39:1001-9. [PMID: 25640768 DOI: 10.1038/ijo.2015.12] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Revised: 01/06/2015] [Accepted: 01/17/2015] [Indexed: 11/09/2022]
Abstract
BACKGROUND Genome-wide association studies in adults have identified genetic loci associated with adiposity measures. Little is known about the effects of these loci on growth and body fat distribution from early childhood onwards. METHODS In a population-based prospective cohort study among 4144 children, we examined the associations of weighted risk scores combining 29 known genetic markers of adult body mass index (BMI) and 14 known genetic markers of adult waist-hip ratio (WHR) with peak weight velocity, peak height velocity, age at adiposity peak and BMI at adiposity peak in early infancy and additionally with BMI, total fat mass, android/gynoid fat ratio and preperitoneal fat area at the median age of 6.0 years (95% range 5.7, 7.8). RESULTS A higher adult BMI genetic risk score was associated with a higher age at adiposity peak in infancy and a higher BMI, total fat mass, android/gynoid fat ratio and preperitoneal fat area in childhood (P=0.05, 1.5 × 10(-24), 3.6 × 10(-18), 4.0 × 10(-11) and 1.3 × 10(-5), respectively), with the strongest association for childhood BMI with a 0.04 higher s.d. score BMI (95% confidence interval 0.03, 0.05) per additional risk allele. A higher adult WHR genetic risk score was not associated with infant growth measures or childhood BMI and total fat mass, but was associated with childhood android/gynoid fat ratio and preperitoneal fat area (P<0.05). CONCLUSION Genetic variants associated with BMI and WHR in adults influence growth patterns and general and abdominal fat development from early childhood onwards.
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Bouret S, Levin BE, Ozanne SE. Gene-environment interactions controlling energy and glucose homeostasis and the developmental origins of obesity. Physiol Rev 2015; 95:47-82. [PMID: 25540138 PMCID: PMC4281588 DOI: 10.1152/physrev.00007.2014] [Citation(s) in RCA: 97] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Obesity and type 2 diabetes mellitus (T2DM) often occur together and affect a growing number of individuals in both the developed and developing worlds. Both are associated with a number of other serious illnesses that lead to increased rates of mortality. There is likely a polygenic mode of inheritance underlying both disorders, but it has become increasingly clear that the pre- and postnatal environments play critical roles in pushing predisposed individuals over the edge into a disease state. This review focuses on the many genetic and environmental variables that interact to cause predisposed individuals to become obese and diabetic. The brain and its interactions with the external and internal environment are a major focus given the prominent role these interactions play in the regulation of energy and glucose homeostasis in health and disease.
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Affiliation(s)
- Sebastien Bouret
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
| | - Barry E Levin
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
| | - Susan E Ozanne
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
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36
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Johnson W. Analytical strategies in human growth research. Am J Hum Biol 2015; 27:69-83. [PMID: 25070272 PMCID: PMC4309180 DOI: 10.1002/ajhb.22589] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Revised: 05/15/2014] [Accepted: 07/13/2014] [Indexed: 12/20/2022] Open
Abstract
Human growth research requires knowledge of longitudinal statistical methods that can be analytically challenging. Even the assessment of growth between two ages is not as simple as subtracting the first measurement from the second, for example. This article provides an overview of the key analytical strategies available to human biologists in increasing order of complexity, starting with a review on how to express cross-sectional measurements of size, before covering growth (conditional regression models, regression with conditional growth measures), growth curves (individual growth curves, mixed effects growth curves, latent growth curves), and patterns of growth (growth mixture modeling). The article is not a statistical treatise and has been written by a human biologist for human biologists; as such, it should be accessible to anyone with training in at least basic statistics. A summary table linking each analytical strategy to its applications is provided to help investigators match their hypotheses and measurement schedules to an analysis plan. In addition, worked examples using data on non-Hispanic white participants in the Fels Longitudinal Study are used to illustrate how the analytical strategies might be applied to gain novel insight into human growth and its determinants and consequences. All too often, serial measurements are treated as cross-sectional in analyses that do not harness the power of longitudinal data. The broad goal of this article is to encourage the rigorous application of longitudinal statistical methods to human growth research.
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Affiliation(s)
- William Johnson
- MRC Unit for Lifelong Health and Ageing at UCLLondon, WC1B 5JU, United Kingdom
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37
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Beyerlein A, Thiering E, Pflueger M, Bidlingmaier M, Stock J, Knopff A, Winkler C, Heinrich J, Ziegler AG. Early infant growth is associated with the risk of islet autoimmunity in genetically susceptible children. Pediatr Diabetes 2014; 15:534-42. [PMID: 24785566 DOI: 10.1111/pedi.12118] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2013] [Accepted: 12/20/2013] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Islet autoimmunity commonly develops early in infancy. We assessed whether specific parameters of early growth (including weight gain) were associated with the development of islet autoimmunity in children of type 1 diabetes patients, taking individual developmental patterns into account. METHODS Growth parameters were estimated in n = 1011 children followed from birth in the prospective BABYDIAB and BABYDIET studies using longitudinal models. Cox proportional hazard models, adjusted for study, sex, gestational age, birth weight percentile, and maternal type 1 diabetes status, were calculated to assess hazard ratios (HR) for islet autoimmunity with corresponding 95% confidence intervals (95% CI) by 2 SD increases in growth parameters. In a subset of n = 170 infants, we investigated whether the growth hormones insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein-3 (IGFBP-3) were in the causal pathway. RESULTS We found an early age at infant body mass index (BMI) peak to be associated with the development of islet autoimmunity [HR 0.60 (95% CI 0.41-0.87), per 2 SD increase in age]. Islet autoimmunity was also associated with BMI difference between infant BMI peak and childhood BMI rebound [HR 1.52 (95% CI 1.04-2.22)], but not after adjustment for age at infant BMI peak, and not with other parameters such as peak height and weight velocity during infancy. Serum concentrations of IGF-1 and IGFBP-3 at birth, 9 months, and 2 yr, respectively, were not significantly different between children with and without later islet autoimmunity. CONCLUSIONS Variations in early growth rate have subtle effects on the risk of islet autoimmunity with growth hormones unlikely to be in the causal pathway.
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Affiliation(s)
- Andreas Beyerlein
- Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Neuherberg, Germany
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Jeve YB, Konje JC, Doshani A. Placental dysfunction in obese women and antenatal surveillance strategies. Best Pract Res Clin Obstet Gynaecol 2014; 29:350-64. [PMID: 25457859 DOI: 10.1016/j.bpobgyn.2014.09.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Accepted: 09/04/2014] [Indexed: 10/24/2022]
Abstract
This review is aimed at discussing placental dysfunction in obesity and its clinical implication in pregnancy as well as an antenatal surveillance strategy for these women. Maternal obesity is associated with adverse perinatal outcome. Obesity is an independent risk factor for fetal hyperinsulinaemia, birthweight and newborn adiposity. Maternal obesity is associated with childhood obesity and obesity in adult life. Obesity induces a low-grade inflammatory response in placenta, which results in short- and long-term programming of obesity in fetal life. Preconception and antenatal counselling on obstetrics risk in pregnancy, on diet and lifestyle in pregnancy and on gestational weight gain is associated with a better outcome. Fetal growth velocity is closely associated with maternal weight and gestational weight gain. Careful monitoring of gestational weight gain and fetal growth, and screening and management of obstetrical complications such as gestational diabetes and pre-eclampsia, improves perinatal outcome. The use of metformin in non-diabetic obese women is under investigation; further evidence is required before recommending it.
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Associations between infant feeding and the size, tempo and velocity of infant weight gain: SITAR analysis of the Gemini twin birth cohort. Int J Obes (Lond) 2014; 38:980-7. [PMID: 24722545 PMCID: PMC4088337 DOI: 10.1038/ijo.2014.61] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Revised: 03/27/2014] [Accepted: 04/06/2014] [Indexed: 12/30/2022]
Abstract
Objective: Infant growth trajectories, in terms of size, tempo and velocity, may programme lifelong obesity risk. Timing of breastfeeding cessation and weaning are both implicated in rapid infant growth; we examined the association of both simultaneously with a range of growth parameters. Design: Longitudinal population-based twin birth cohort. Subjects: The Gemini cohort provided data on 4680 UK infants with a median of 10 (interquartile range=8–15) weight measurements between birth and a median of 6.5 months. Age at breastfeeding cessation and weaning were reported by parents at mean age 8.2 months (s.d.=2.2, range=4–20). Growth trajectories were modelled using SuperImposition by Translation And Rotation (SITAR) to generate three descriptors of individual growth relative to the average trajectory: size (grams), tempo (weeks, indicating the timing of the peak growth rate) and velocity (% difference from average, reflecting mean growth rate). Complex-samples general linear models adjusting for family clustering and confounders examined associations between infant feeding and SITAR parameters. Results: Longer breastfeeding (>4 months vs never) was independently associated with lower growth velocity by 6.8% (s.e.=1.3%) and delayed growth tempo by 1.0 (s.e.=0.2 weeks), but not with smaller size. Later weaning (⩾6 months vs <4 months) was independently associated with lower growth velocity by 4.9% (s.e.=1.1%) and smaller size by 102 g (s.e.=25 g). Conclusions: Infants breastfed for longer grew slower for longer after birth (later peak growth rate) but were no different in size, while infants weaned later grew slower overall and were smaller but the timing of peak growth did not differ. Slower trajectories with a delayed peak in growth may have beneficial implications for programming later obesity risk. Replication in cohorts with longer follow-up, alternative confounding structures or randomised controlled trials are required to confirm the long-term effects and directionality, and to rule out residual confounding.
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Graversen L, Sørensen TIA, Petersen L, Sovio U, Kaakinen M, Sandbaek A, Laitinen J, Taanila A, Pouta A, Järvelin MR, Obel C. Preschool weight and body mass index in relation to central obesity and metabolic syndrome in adulthood. PLoS One 2014; 9:e89986. [PMID: 24595022 PMCID: PMC3940896 DOI: 10.1371/journal.pone.0089986] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 01/25/2014] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND If preschool measures of body size routinely collected at preventive health examinations are associated with adult central obesity and metabolic syndrome, a focused use of these data for the identification of high risk children is possible. The aim of this study was to test the associations between preschool weight and body mass index (BMI) and adult BMI, central obesity and metabolic alterations. METHODS The Northern Finland Birth Cohort 1966 (NFBC1966) (N = 4111) is a population-based cohort. Preschool weight (age 5 months and 1 year) and BMI (age 2-5 years) were studied in relation to metabolic syndrome as well as BMI, waist circumference, lipoproteins, blood pressure, and fasting glucose at the age of 31 years. Linear regression models and generalized linear regression models with log link were used. RESULTS Throughout preschool ages, weight and BMI were significantly linearly associated with adult BMI and waist circumference. Preschool BMI was inversely associated with high-density lipoprotein levels from the age of 3 years. Compared with children in the lower half of the BMI range, the group of children with the 5% highest BMI at the age of 5 years had a relative risk of adult obesity of 6.2(95% CI:4.2-9.3), of adult central obesity of 2.4(95% CI:2.0-2.9), and of early onset adult metabolic syndrome of 2.5(95% CI:1.7-3.8). CONCLUSIONS High preschool BMI is consistently associated with adult obesity, central obesity and early onset metabolic syndrome. Routinely collected measures of body size in preschool ages can help to identify children in need of focused prevention due to their increased risk of adverse metabolic alterations in adulthood.
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Affiliation(s)
- Lise Graversen
- Section for General Medical Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
- * E-mail: (LG); (MRJ)
| | - Thorkild I. A. Sørensen
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg University Hospital, The Capital Region, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liselotte Petersen
- National Centre for Register-Based Research, Faculty of Social Sciences, Aarhus University, Aarhus, Denmark
| | - Ulla Sovio
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, United Kingdom
- Department of Epidemiology and Biostatistics, Imperial College, London, United Kingdom
| | - Marika Kaakinen
- Department of Epidemiology and Biostatistics, Imperial College, London, United Kingdom
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Annelli Sandbaek
- Section for General Medical Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
| | | | - Anja Taanila
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Primary Health Care Unit, University Hospital of Oulu, Oulu, Finland
| | - Anneli Pouta
- National Institute of Health and Welfare, Oulu, Finland
- Department of Obstetrics and Gynecology, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, Imperial College, London, United Kingdom
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Primary Health Care Unit, University Hospital of Oulu, Oulu, Finland
- National Institute of Health and Welfare, Oulu, Finland
- * E-mail: (LG); (MRJ)
| | - Carsten Obel
- Section for General Medical Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
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Wohlfahrt-Veje C, Audouze K, Brunak S, Antignac JP, le Bizec B, Juul A, Skakkebæk NE, Main KM. Polychlorinated dibenzo-p-dioxins, furans, and biphenyls (PCDDs/PCDFs and PCBs) in breast milk and early childhood growth and IGF1. Reproduction 2014; 147:391-9. [PMID: 24586095 DOI: 10.1530/rep-13-0422] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Experimental studies have shown that dioxin-like chemicals may interfere with aspects of the endocrine system including growth. However, human background population studies are, however, scarce. We aimed to investigate whether early exposure of healthy infants to dioxin-like chemicals was associated with changes in early childhood growth and serum IGF1. In 418 maternal breast milk samples of Danish children (born 1997-2001) from a longitudinal cohort, we measured polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and polychlorinated biphenyls (pg or ng/g lipid) and calculated total toxic equivalent (total TEQ). SDS and SDS changes over time (ΔSDS) were calculated for height, weight, BMI, and skinfold fat percentage at 0, 3, 18, and 36 months of age. Serum IGF1 was measured at 3 months. We adjusted for confounders using multivariate regression analysis. Estimates (in parentheses) correspond to a fivefold increase in total TEQ. TEQ levels in breast milk increased significantly with maternal age and fish consumption and decreased with maternal birth year, parity, and smoking. Total TEQ was associated with lower fat percentage (-0.45 s.d., CI: -0.89; -0.04), non-significantly with lower weight and length at 0 months, accelerated early height growth (increased ΔSDS) (ΔSDS 0-18 months: +0.77 s.d., CI: 0.34; 1.19) and early weight increase (ΔSDS 0-18: +0.52 s.d., CI: 0.03; 1.00), and increased IGF1 serum levels at 3 months (+13.9 ng/ml, CI: 2.3; 25.5). Environmental exposure to dioxin-like chemicals was associated with being skinny at birth and with higher infant levels of circulating IGF1 as well as accelerated early childhood growth (rapid catch-up growth).
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Affiliation(s)
- Christine Wohlfahrt-Veje
- Department of Growth and Reproduction, The Faculty of Medical and Health Sciences, University Hospital of Copenhagen, Rigshospitalet, University of Copenhagen, 5064, Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
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Pizzi C, Cole TJ, Richiardi L, dos-Santos-Silva I, Corvalan C, De Stavola B. Prenatal influences on size, velocity and tempo of infant growth: findings from three contemporary cohorts. PLoS One 2014; 9:e90291. [PMID: 24587314 PMCID: PMC3937389 DOI: 10.1371/journal.pone.0090291] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2013] [Accepted: 02/01/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Studying prenatal influences of early life growth is relevant to life-course epidemiology as some of its features have been linked to the onset of later diseases. METHODS We studied the association between prenatal maternal characteristics (height, age, parity, education, pre-pregnancy body mass index (BMI), smoking, gestational diabetes and hypertension) and offspring weight trajectories in infancy using SuperImposition by Translation And Rotation (SITAR) models, which parameterize growth in terms of three biologically interpretable parameters: size, velocity and tempo. We used data from three contemporary cohorts based in Portugal (GXXI, n=738), Italy (NINFEA, n=2,925), and Chile (GOCS, n=959). RESULTS Estimates were generally consistent across the cohorts for maternal height, age, parity and pre-pregnancy overweight/obesity. Some exposures only affected one growth parameter (e.g. maternal height (per cm): 0.4% increase in size (95% confidence interval (CI):0.3; 0.5)), others were either found to affect size and velocity (e.g. pre-pregnancy underweight vs normal weight: smaller size (-4.9%, 95% CI:-6.5; -3.3), greater velocity (5.9%, 95% CI:1.9;10.0)), or to additionally influence tempo (e.g. pre-pregnancy overweight/obesity vs normal weight: increased size (7.9%, 95% CI:4.9;10.8), delayed tempo (0.26 months, 95% CI:0.11;0.41), decreased velocity (-4.9%, 95% CI: -10.8;0.9)). CONCLUSIONS By disentangling the growth parameters of size, velocity and tempo, we found that prenatal maternal characteristics, especially maternal smoking, pre-pregnancy overweight and underweight, parity and gestational hypertension, are associated with different aspects of infant weight growth. These results may offer insights into the mechanisms governing infant growth.
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Affiliation(s)
- Costanza Pizzi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
- Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Tim J. Cole
- Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, United Kingdom
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Isabel dos-Santos-Silva
- Non-Communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Camila Corvalan
- Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile
| | - Bianca De Stavola
- Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Weitz CA, Friedlaender FY, Friedlaender JS. Adult lipids associated with early life growth in traditional Melanesian societies undergoing rapid modernization: a longitudinal study of the mid-20th century. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2013; 153:551-8. [PMID: 24382639 DOI: 10.1002/ajpa.22453] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Accepted: 12/08/2013] [Indexed: 01/09/2023]
Abstract
Both poor fetal development and accelerated post-natal growth have been linked to adult dyslipidemias in many studies conducted in developed societies. It is not known, however, whether these relationships only characterize populations with typical Western diets or if they also may develop in groups at the early stages of a dietary transition. Our longitudinal study of traditional rural populations in the Southwest Pacific during a period of extremely rapid modernization in diet and life-styles shows a nascent association between child growth retardation, subsequent growth acceleration, and adult lipid values in spite of a continuing prevalence of very low lipid levels. However, our results do not entirely conform to results from populations with "modern" diets. Outcome (i.e., young adult) cholesterol and triglyceride levels are more consistently related to initial measures of body fat and growth in body fat measures than with stature, while outcome apo A-1 is more consistently related to initial stature or stature growth than to measures of body fat. We suggest this may reflect a pattern characteristic of the initial stages of "modernization" associated with dietary change, with stronger and more pervasive relationships emerging only later as populations complete the dietary transition.
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Affiliation(s)
- Charles A Weitz
- Anthropology Department, Temple University, Philadelphia, PA, 19122
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Flexeder C, Thiering E, Kratzsch J, Klümper C, Koletzko B, Müller MJ, Koletzko S, Heinrich J. Is a child's growth pattern early in life related to serum adipokines at the age of 10 years? Eur J Clin Nutr 2013; 68:25-31. [PMID: 24169460 DOI: 10.1038/ejcn.2013.213] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2013] [Revised: 08/01/2013] [Accepted: 09/09/2013] [Indexed: 12/19/2022]
Abstract
BACKGROUND/OBJECTIVES Growth parameters during infancy and early childhood might predict adipokine levels later in life. This study investigates the association between peak growth velocities, body mass index (BMI) and age at adiposity rebound (AR), with leptin and adiponectin levels at age 10 years. SUBJECTS/METHODS Peak height (PHV) and weight (PWV) velocities were calculated from height and weight measurements obtained between birth and age 2 years from 2880 children participating in the GINIplus (German Infant Nutritional Intervention plus environmental and genetic influences on allergy development) and LISAplus (Influences of Lifestyle-Related Factors on the Immune System and the Development of Allergies in Childhood plus Air Pollution and Genetics) birth cohorts. BMI and age at AR were calculated using BMI measurements between age 1.5 and 12 years. Blood samples were collected during a physical examination at age 10. Adiponectin and leptin levels were measured by radioimmunoassay. Linear regression models were fitted after adjustment for potential confounding factors and results are presented per interquartile range increase in the exposure. RESULTS Age at AR was negatively associated with leptin in males and females (percent difference β*: -41.71%; 95% confidence interval: (-44.34;-38.96) and β*: -43.22%; (-45.59; -40.75), respectively). For both males and females PWV (β*: 14.23%; (7.60; 21.26) and β*: 18.54%; (10.76; 26.87), respectively) and BMI at AR (β*: 63.08%; (55.04; 71.53) and β*: 67.02%; (59.30; 75.10), respectively) were positively associated with leptin levels. PHV showed a positive effect on leptin in females only (β*: 10.75%; (3.73; 18.25)). Growth parameters were not significantly associated with adiponectin except for age at AR among females (β: 0.75 ng/ml; (0.42; 1.09)) and PWV among males (β: 0.45 ng/ml; (0.11; 0.79)). CONCLUSION Growth patterns in early life may be associated with leptin levels at age 10 years.
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Affiliation(s)
- C Flexeder
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg, Germany
| | - E Thiering
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg, Germany
| | - J Kratzsch
- University Hospital Leipzig, Faculty of Medicine, Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, Leipzig, Germany
| | - C Klümper
- IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - B Koletzko
- Dr von Hauner Children's Hospital, Ludwig Maximilians University of Munich, Munich, Germany
| | - M J Müller
- Institute of Human Nutrition and Food Science, Christian-Albrechts University, Kiel, Germany
| | - S Koletzko
- Dr von Hauner Children's Hospital, Ludwig Maximilians University of Munich, Munich, Germany
| | - J Heinrich
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg, Germany
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Touwslager RNH, Gielen M, Mulder ALM, Gerver WJM, Zimmermann LJ, Dagnelie PC, Houben AJHM, Stehouwer CDA, Derom C, Vlietinck R, Loos RJF, Zeegers MP. Genetic and environmental factors in associations between infant growth and adult cardiometabolic risk profile in twins. Am J Clin Nutr 2013; 98:994-1001. [PMID: 23985811 DOI: 10.3945/ajcn.112.039131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Accelerated infant growth is associated with an altered, mostly adverse adult cardiometabolic risk profile. The importance of genetic and environmental factors to these associations is unclear. OBJECTIVE The objective was to examine the importance of genetic and environmental factors in the associations between infant growth and adult cardiometabolic risk factors (anthropometric characteristics, lipids, insulin sensitivity, leptin, blood pressure, and fibrinogen) in twins. DESIGN Cardiometabolic risk factors were assessed in 240 twin pairs (aged 18-34 y) from the East Flanders Prospective Twin Survey. Infant growth was defined as change in weight z score. We regressed intrapair differences in growth during 4 growth windows (0-1, 1-6, 6-12, and 12-24 mo) against intrapair differences in the risk factors in monozygotic and dizygotic twins separately. RESULTS Within monozygotic twin pairs only, associations between infant growth and most adult lipids, glucose, leptin, and blood pressure (eg, systolic blood pressure: b = 5.95 mm Hg per change in z score, P = 0.01 in monozygotic twins; b = -1.64, P = 0.82 in dizygotic twins from 12 to 24 mo) were found. Within dizygotic twin pairs only, associations between growth and triglycerides and fibrinogen (eg, fibrinogen: b = 0.07 ln mg/dL per change in z score, P = 0.31 in monozygotic twins; b = 0.79, P = 0.01 in dizygotic twins from 0 to 1 mo) were identified. Most associations showed a detrimental effect of accelerated growth, but beneficial associations were also identified (eg, total-to-high-density-lipoprotein cholesterol ratio: b = -0.22 per change in z score from 1 to 6 mo, P = 0.008 in monozygotic twins). CONCLUSION Our data showed that environmental factors play a role in the associations between infant growth and most adult lipids, glucose, leptin, and blood pressure, whereas genetic factors are involved regarding triglycerides and fibrinogen.
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Affiliation(s)
- Robbert N H Touwslager
- Departments of Pediatrics, NUTRIM, Maastricht University Medical Centre, Maastricht, Netherlands; GROW, Maastricht School for Oncology and Developmental Biology, Maastricht, Netherlands
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Bahari H, Caruso V, Morris MJ. Late-onset exercise in female rat offspring ameliorates the detrimental metabolic impact of maternal obesity. Endocrinology 2013; 154:3610-21. [PMID: 23928377 DOI: 10.1210/en.2013-1059] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Rising rates of maternal obesity/overweight bring the need for effective interventions in offspring. We observed beneficial effects of postweaning exercise, but the question of whether late-onset exercise might benefit offspring exposed to maternal obesity is unanswered. Thus we examined effects of voluntary exercise implemented in adulthood on adiposity, hormone profiles, and genes involved in regulating appetite and metabolism in female offspring. Female Sprague Dawley rats were fed either normal chow or high-fat diet (HFD) ad libitum for 5 weeks before mating and throughout gestation/lactation. At weaning, female littermates received either chow or HFD and, after 7 weeks, half were exercised (running wheels) for 5 weeks. Tissues were collected at 15 weeks. Maternal obesity was associated with increased hypothalamic inflammatory markers, including suppressor of cytokine signaling 3, TNF-α, IL-1β, and IL-6 expression in the arcuate nucleus. In the paraventricular nucleus (PVN), Y1 receptor, melanocortin 4 receptor, and TNF-α mRNA were elevated. In the hippocampus, maternal obesity was associated with up-regulated fat mass and obesity-associated gene and TNF-α mRNA. We observed significant hypophagia across all exercise groups. In female offspring of lean dams, the reduction in food intake by exercise could be related to altered signaling at the PVN melanocortin 4 receptor whereas in offspring of obese dams, this may be related to up-regulated TNF-α. Late-onset exercise ameliorated the effects of maternal obesity and postweaning HFD in reducing body weight, adiposity, plasma leptin, insulin, triglycerides, and glucose intolerance, with greater beneficial effects in offspring of obese dams. Overall, hypothalamic inflammation was increased by maternal obesity or current HFD, and the effect of exercise was dependent on maternal diet. In conclusion, even after a significant sedentary period, many of the negative impacts of maternal obesity could be improved by voluntary exercise and healthy diet.
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Affiliation(s)
- Hasnah Bahari
- Department of Pharmacology, School of Medical Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia.
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Sovio U, Kaakinen M, Tzoulaki I, Das S, Ruokonen A, Pouta A, Hartikainen AL, Molitor J, Järvelin MR. How do changes in body mass index in infancy and childhood associate with cardiometabolic profile in adulthood? Findings from the Northern Finland Birth Cohort 1966 Study. Int J Obes (Lond) 2013; 38:53-9. [PMID: 24080793 DOI: 10.1038/ijo.2013.165] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Revised: 08/09/2013] [Accepted: 08/27/2013] [Indexed: 01/03/2023]
Abstract
BACKGROUND/OBJECTIVE Postnatal growth patterns leading to obesity may have adverse influences on future cardiometabolic health. This study evaluated age and body mass index (BMI) at infant BMI peak (BMIP) and childhood BMI rebound (BMIR) in relation to adult cardiometabolic outcomes in the Northern Finland Birth Cohort 1966. METHODS BMI at various ages was calculated from frequent height and weight measurements obtained from child health and welfare clinical records. Age and BMI at BMIP and BMIR were derived from random effect models fitted at >0-1.5 years (N=3 265) and >1.5-13 years (N=4 121). Cardiometabolic outcomes were obtained from a clinical examination at age 31 years. Multiple regression models were used to analyse associations between the derived growth parameters and cardiometabolic outcomes. RESULTS Age and BMI at BMIP were positively associated with adult BMI and waist circumference (WC), independently of birth weight and infant height growth (P<0.05). Later BMIR was associated with a better cardiometabolic profile: adult BMI and insulin were 14% lower, WC and triglycerides were 10% lower and the odds of metabolic syndrome (MetS) were 74% lower per 2 s.d. (1.86 years) higher age at BMIR (P<0.0001). BMI at rebound had generally weaker associations with cardiometabolic outcomes, which attenuated after adjustment for age at BMIR. CONCLUSIONS Age and BMI at infant BMIP were associated with adult adiposity but not with other cardiometabolic outcomes. Earlier timing of BMIR was a risk factor of an adverse cardiometabolic profile, independently of early growth or BMI at rebound. Identifying growth patterns harmful to cardiovascular health will give opportunities for early interventions.
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Affiliation(s)
- U Sovio
- 1] Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK [2] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - M Kaakinen
- 1] Institute of Health Sciences, University of Oulu, Oulu, Finland [2] Biocenter Oulu, University of Oulu, Oulu, Finland
| | - I Tzoulaki
- 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] Department of Hygiene and Epidemiology, Medical School University of Ioannina, Ioannina, Greece
| | - S Das
- Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - A Ruokonen
- Institute of Diagnostics, Clinical Chemistry, University of Oulu, Oulu, Finland
| | - A Pouta
- 1] Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland [2] Department of Clinical Sciences/Obstetrics and Gynecology, University of Oulu, Oulu, Finland
| | - A-L Hartikainen
- Department of Clinical Sciences/Obstetrics and Gynecology, University of Oulu, Oulu, Finland
| | - J Molitor
- 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] College of Public Health & Human Sciences, Oregon State University, Corvallis, OR, USA
| | - M-R Järvelin
- 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] Institute of Health Sciences, University of Oulu, Oulu, Finland [3] Biocenter Oulu, University of Oulu, Oulu, Finland [4] Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland
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Prodam F, Ricotti R, Genoni G, Parlamento S, Petri A, Balossini C, Savastio S, Bona G, Bellone S. Comparison of two classifications of metabolic syndrome in the pediatric population and the impact of cholesterol. J Endocrinol Invest 2013; 36:466-73. [PMID: 23211535 DOI: 10.3275/8768] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND To establish the rate of agreement in predicting metabolic syndrome (MS) in different pediatric classifications using percentiles or fixed cut-offs, as well as exploring the influence of cholesterol. SUBJECTS AND METHODS Cross-sectional study in a tertiary care center. Nine hundred and twenty-three obese children and adolescents were evaluated for metabolic characteristics, cholesterol levels, the agreement rate and prevalence of MS across age subgroups with pediatric National Cholesterol Education Program/ Adult Treatment Panel III (NCEP-ATP III) and International Diabetes Federation (IDF) classifications. RESULTS The overall prevalence of MS was 36.2% and 56.7% with NCEPATP III and IDF. The overall concordance was fair (k: 0.269), with substantial values observed only in children older than 10 (k: 0.708) and 16 yr (0.694). Concordant subjects for both classifications, ≤6 yr, had higher triglycerides, blood pressure (p<0.05) and lower HDL-cholesterol (p<0.0001), with respect to those found to be discordant. Concordant subjects ranging 6-10 yr had all parameters higher than those discordant for IDF (p<0.01) and insulin resistance (p<0.05) than those discordant for NCEP-ATP III. Concordant subjects ≥10 yr presented more altered parameters than those included only in NCEP-ATP III (p<0.05). Overt glucose alterations were uncommon (7.4%; confidence interval 95% 0.1-14.9%), although glucose was modestly higher in MS subjects (p<0.01). Total and LDL-cholesterol was lower in subjects with MS than in those without (p<0.05), and in concordant rather than discordant subjects (p<0.05). CONCLUSIONS Classifications of MS do not identify the same pediatric population. Subjects who satisfied any classification were the most compromised. Lipid alterations were precocious in the youngest. Obese youths with MS presented lower total and LDL-cholesterol.
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Affiliation(s)
- F Prodam
- SCDU of Pediatrics, Department of Health Sciences, Università del Piemonte Orientale "A. Avogadro", via Solaroli 17, 28100 Novara, Italy.
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Papacleovoulou G, Abu-Hayyeh S, Nikolopoulou E, Briz O, Owen BM, Nikolova V, Ovadia C, Huang X, Vaarasmaki M, Baumann M, Jansen E, Albrecht C, Jarvelin MR, Marin JJ, Knisely A, Williamson C. Maternal cholestasis during pregnancy programs metabolic disease in offspring. J Clin Invest 2013; 123:3172-81. [PMID: 23934127 PMCID: PMC3696570 DOI: 10.1172/jci68927] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Accepted: 04/04/2013] [Indexed: 12/20/2022] Open
Abstract
The intrauterine environment is a major contributor to increased rates of metabolic disease in adults. Intrahepatic cholestasis of pregnancy (ICP) is a liver disease of pregnancy that affects 0.5%-2% of pregnant women and is characterized by increased bile acid levels in the maternal serum. The influence of ICP on the metabolic health of offspring is unknown. We analyzed the Northern Finland birth cohort 1985-1986 database and found that 16-year-old children of mothers with ICP had altered lipid profiles. Males had increased BMI, and females exhibited increased waist and hip girth compared with the offspring of uncomplicated pregnancies. We further investigated the effect of maternal cholestasis on the metabolism of adult offspring in the mouse. Females from cholestatic mothers developed a severe obese, diabetic phenotype with hepatosteatosis following a Western diet, whereas matched mice not exposed to cholestasis in utero did not. Female littermates were susceptible to metabolic disease before dietary challenge. Human and mouse studies showed an accumulation of lipids in the fetoplacental unit and increased transplacental cholesterol transport in cholestatic pregnancy. We believe this is the first report showing that cholestatic pregnancy in the absence of altered maternal BMI or diabetes can program metabolic disease in the offspring.
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Affiliation(s)
- Georgia Papacleovoulou
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Shadi Abu-Hayyeh
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Evanthia Nikolopoulou
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Oscar Briz
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Bryn M. Owen
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Vanya Nikolova
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Caroline Ovadia
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Xiao Huang
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Marja Vaarasmaki
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Marc Baumann
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Eugene Jansen
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Christiane Albrecht
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Marjo-Riitta Jarvelin
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Jose J.G. Marin
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - A.S. Knisely
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
| | - Catherine Williamson
- Institute of Reproductive and Developmental Biology, Hammersmith Hospital, Imperial College London, London, United Kingdom.
Division of Women’s Health, Women’s Health Academic Centre, King’s College London, London, United Kingdom.
Laboratory of Experimental Hepatology and Drug Targeting (HEVEFARM), IBSAL, CIBERehd, University of Salamanca, Salamanca, Spain.
Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Institute of Biochemistry and Molecular Medicine,
Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Bern, Switzerland.
Institute of Clinical Medicine/Obstetrics and Gynaecology, University of Oulu, Oulu, Finland.
Department of Obstetrics and Gynecology, University Hospital, University of Bern, Bern, Switzerland.
National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Department of Epidemiology and Biostatistics, MRC Health Protection Agency, Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland.
Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Institute of Liver Studies, King’s College Hospital, London, United Kingdom
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Odegaard AO, Choh AC, Nahhas RW, Towne B, Czerwinski SA, Demerath EW. Systematic examination of infant size and growth metrics as risk factors for overweight in young adulthood. PLoS One 2013; 8:e66994. [PMID: 23818973 PMCID: PMC3688577 DOI: 10.1371/journal.pone.0066994] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2012] [Accepted: 05/15/2013] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE To systematically examine infant size and growth, according to the 2006 WHO infant growth standards, as risk factors for overweight status in young adulthood in a historical cohort. Specifically, to assess: Whether accounting for length (weight-for-length) provides a different picture of risk than weight-for-age, intervals of rapid growth in both weight-for-age and weight-for-length metrics, and what particular target ages for infant size and intervals of rapid growth associate most strongly with overweight as a young adult. PATIENTS/METHODS Data analysis of 422 appropriate for gestational age white singleton infants enrolled in the Fels Longitudinal Study. Odds ratios (OR) for overweight and obesity in young adulthood (age 20-29) were calculated using logistic regression models for the metrics at each target age (0, 1, 3, 6, 9, 12, 18, 24 months) comparing ≥85(th) v. <85(th) percentile, as well as rapid growth (Δ≥0.67 Z-score) through target age intervals. Models accounted for both maternal and paternal BMI. RESULTS Infants ≥85(th) percentile of weight-for-age at each target age (except 3 months) had a greater odds of being overweight as a young adult. After accounting for length (weight-for-length) this association was limited to 12, and 18 months. Rapid weight-for-age growth was infrequently associated with overweight as a young adult. Rapid weight-for-length growth from 0 to 24 months, 1 to 6, 9, 12, 18, and 24 months and from 3 to 9, 12, 18, and 24 months was strongly associated with overweight status as a young adult. CONCLUSIONS The WHO weight-for-length metric associates differently with risk of being overweight as a young adult compared to weight-for-age. Intervals of rapid weight-for-length growth ranging from months (0-24), (1-12, 18, and 24) and (3-9, and 12) displayed the largest OR for being overweight as a young adult.
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Affiliation(s)
- Andrew O Odegaard
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
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