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Zhang Y, Liu P, Zhou W, Hu J, Cui L, Chen ZJ. Association of large for gestational age with cardiovascular metabolic risks: a systematic review and meta-analysis. Obesity (Silver Spring) 2023; 31:1255-1269. [PMID: 37140379 DOI: 10.1002/oby.23701] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/27/2022] [Accepted: 11/28/2022] [Indexed: 05/05/2023]
Abstract
OBJECTIVE The aim of this study was to clarify the relationships among large for gestational age (LGA) and cardiometabolic risk factors. METHODS PubMed, Web of Science, and the Cochrane Library databases were searched to identify studies on LGA and outcomes of interest, including BMI, blood pressure, glucose metabolism, and lipid profiles. Data were independently extracted by two reviewers. A meta-analysis was performed using a random-effects model. The Newcastle-Ottawa Scale and funnel graph were used to assess the quality and publication bias, respectively. RESULTS Overall, 42 studies involving 841,325 individuals were included. Compared with individuals born appropriate for gestational age, individuals born LGA had higher odds of overweight and obesity (odds ratios [OR] = 1.44, 95% CI: 1.31-1.59), type 1 diabetes (OR = 1.28, 95% CI: 1.15-1.43), hypertension (OR = 1.23, 95% CI: 1.01-1.51), and metabolic syndrome (OR = 1.43, 95%; CI: 1.05-1.96). No significant difference was found in hypertriglyceridemia and hypercholesterolemia. Stratified analyses showed that, compared with individuals born appropriate for gestational age, individuals born LGA had higher odds for overweight and obesity from toddler age to puberty age (toddler age: OR = 2.12, 95% CI: 1.22-3.70; preschool: OR = 1.81, 95% CI: 1.55-2.12; school age: OR = 1.53, 95% CI: 1.09-2.14; puberty: OR = 1.40, 95% CI: 1.11-1.77). CONCLUSIONS LGA is associated with increased odds of obesity and metabolic syndrome later in life. Future studies should focus on elucidating the potential mechanisms and identifying risk factors.
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Affiliation(s)
- Yiyuan Zhang
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
| | - Peihao Liu
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
| | - Wei Zhou
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
| | - Jingmei Hu
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
| | - Linlin Cui
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
| | - Zi-Jiang Chen
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, China
- Shandong Key Laboratory of Reproductive Medicine, Jinan, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, China
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China
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Tadese K, Ernst V, Weaver AL, Thacher TD, Rajjo T, Kumar S, Kaufman T, Wi CI, Lynch BA. Association of Perinatal Factors With Severe Obesity and Dyslipidemia in Adulthood. J Prim Care Community Health 2022; 13:21501327211058982. [PMID: 35249418 PMCID: PMC8905209 DOI: 10.1177/21501327211058982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Background: Perinatal factors including gestational age, birthweight, size for gestational age, delivery route, maternal parity, maternal age, maternal education, socioeconomic status, race, and sex, are associated with the future risk of obesity and co-morbid conditions. This study evaluated the relationship of birthweight for gestational age and perinatal factors with severe obesity and dyslipidemia in adulthood. Methods: We conducted a population-based, retrospective birth cohort study of infants born to residents of Olmsted County, MN between 1976 and 1982. Outcomes were assessed after age 18 years until October 2020, including severe obesity (BMI ≥ 40 kg/m2) and dyslipidemia (total cholesterol ≥200 mg/dL, non-high density lipoprotein [non-HDL] cholesterol ≥145 mg/dL or HDL cholesterol <40 mg/dL). We obtained mother’s age, education level, and parity as well as newborn sex, race, type of delivery, single/multiple birth, gestational age, and birthweight from birth certificate data. Individual-level socioeconomic status (SES) of the household at birth was determined with the HOUSES index. Results: Of 10 938 birth cohort subjects, 7394 had clinic visits after age 18 years and were included, with 2630 having severe obesity (n = 798) or dyslipidemia (n = 2357) as adults. In multivariable models, female sex, singleton birth, less maternal education, and lower SES defined by HOUSES were independently associated with an increased risk of severe obesity in adulthood. Non-white race, singleton birth, and lower birthweight were independently associated with adult dyslipidemia. Birthweight for gestational age was not associated with severe obesity or dyslipidemia. Conclusion: Perinatal factors were associated with both severe obesity and dyslipidemia in adulthood. Lower SES at birth was predictive of severe obesity in adulthood, highlighting the opportunity to investigate modifiable perinatal social determinants to reduce the risk of severe obesity.
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Affiliation(s)
- Kristene Tadese
- Mayo Clinic Alix School of Medicine, Rochester, MN, USA
- Brian A. Lynch, Department of Pediatric and Adolescent Medicine, Mayo Clinic, 200 1st Street NW, Rochester, MN 55905-0002, USA.
| | - Vivian Ernst
- Department of Family Medicine, Mayo Clinic, Rochester, MN, USA
| | - Amy L. Weaver
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Tom D. Thacher
- Department of Family Medicine, Mayo Clinic, Rochester, MN, USA
| | - Tamim Rajjo
- Department of Family Medicine, Mayo Clinic, Rochester, MN, USA
| | - Seema Kumar
- Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Tara Kaufman
- Department of Family Medicine, Mayo Clinic, Rochester, MN, USA
| | - Chung-Il Wi
- Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Brian A. Lynch
- Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
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Yang X, Leng J, Liu H, Wang L, Li W, Li W, Yang X, Liu M, Hu G. Maternal gestational diabetes and childhood hyperlipidemia. Diabet Med 2021; 38:e14606. [PMID: 34021927 PMCID: PMC8511106 DOI: 10.1111/dme.14606] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 05/27/2021] [Accepted: 05/19/2021] [Indexed: 11/29/2022]
Abstract
AIMS Aim of this study is to assess dyslipidemia risk between children exposed to maternal gestational diabetes mellitus (GDM) and those not exposed. METHODS We recruited 1144 mother-child pairs (572 GDM and 572 non-GDM women matched by their offspring's age and sex). The age of offspring ranged from 3 to 9 years old. We used general linear models to compare mean values of different lipid profiles among children born to mothers with and without GDM. Logistic regression models were used to assess associations of maternal GDM with abnormal lipid profiles in offspring. RESULTS After adjustment for maternal and children's characteristics, children born to mothers with GDM had lower mean values of high-density-lipoprotein (HDL) cholesterol (1.40 ± 0.01 vs. 1.50 ± 0.01; p < 0.001) and higher mean levels of triglycerides/HDL cholesterol ratio (0.37 ± 0.01 vs. 0.35 ± 0.01; p < 0.05) in comparison with their counterparts born to mothers without GDM. Multivariate-adjusted odds ratios among children exposed to mothers with GDM compared with the counterparts were 2.11 (95% confidence interval [CI 1.15-3.88]) for low HDL cholesterol and 1.35 (95% CI 1.00-1.81) for high triglycerides/HDL cholesterol ratio, respectively. CONCLUSIONS Maternal GDM was associated with an increased risk of hyperlipidemia in the offspring during early childhood aged from 3 to 9 years old.
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Affiliation(s)
- Xiaoyun Yang
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, China
| | - Junhong Leng
- Tianjin Women’s and Children’s Health Center, Tianjin, China
| | - Huikun Liu
- Tianjin Women’s and Children’s Health Center, Tianjin, China
| | - Leishen Wang
- Tianjin Women’s and Children’s Health Center, Tianjin, China
| | - Weiqin Li
- Tianjin Women’s and Children’s Health Center, Tianjin, China
| | - Wei Li
- Tianjin Women’s and Children’s Health Center, Tianjin, China
| | - Xilin Yang
- Department of Epidemiology, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Ming Liu
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, China
| | - Gang Hu
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
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