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Chen Y, Wu L, Wang J, Li W, Liao Z, Zhang T, Xie X, Liu G, Chen F. Body mass index growth trajectories and body composition influencing factors: An ambidirectional preschooler cohort. Nutrition 2024; 125:112500. [PMID: 38964261 DOI: 10.1016/j.nut.2024.112500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/10/2024] [Accepted: 05/11/2024] [Indexed: 07/06/2024]
Abstract
OBJECTIVES The purpose of the present study was to explore the latent growth trajectory of body mass index (BMI) from birth to 24 months and comprehensively analyze body composition development influencing factor in preschool children. METHODS This ambidirectional cohort study was conducted in Tianjin, China, from 2017 to 2020, and children's regular medical check-up data from birth to 24 months were retrospectively collected. The growth models were used to fit BMI z-score trajectories for children aged 0-24 months. Crossover analysis and interaction model were used to explore the interaction of influencing factors. RESULTS We analyzed the growth trajectories of 3217 children, of these, 1493 children with complete follow-up data were included in the influencing factors analysis. Trajectories and parental prepregnancy BMI (ppBMI) were independent factors influencing children's body composition. When paternal ppBMI ≥24 kg/m2, regardless of maternal ppBMI, the risk of overweight and obesity in senior-class children was increased. The high trajectories played a partial mediating role in the association between paternal ppBMI and body composition in preschool children. CONCLUSIONS BMI growth in children aged 0-24 months can be divided into three latent trajectories: low, middle, and high. These trajectories and parental ppBMI were independent and interactive factors influencing children's body composition. The high trajectories played a partial mediating role in the association between paternal ppBMI and body composition in preschool children. It is necessary to pay attention to the BMI growth level of children aged 0-24 months, which plays an important role in the development of body fat in the future.
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Affiliation(s)
- Yiren Chen
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Lijun Wu
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Jing Wang
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Weiqin Li
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Zijun Liao
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Ting Zhang
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Xianghui Xie
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Gongshu Liu
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Fangfang Chen
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China.
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Nichols AR, Haeri S, Rudine A, Burns N, Rathouz PJ, Hedderson MM, Abrams SA, Foster SF, Rickman R, McDonnold M, Widen EM. Prenatal Weight Change Trajectories and Perinatal Outcomes among Twin Gestations. Am J Perinatol 2024; 41:1445-1454. [PMID: 37164320 PMCID: PMC10782825 DOI: 10.1055/a-2091-1254] [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] [Indexed: 05/12/2023]
Abstract
OBJECTIVE Despite an increase in twin pregnancies in recent decades, the Institute of Medicine twin weight gain recommendations remain provisional and provide no guidance for the pattern or timing of weight change. We sought to characterize gestational weight change trajectory patterns and examine associations with birth outcomes in a cohort of twin pregnancies. STUDY DESIGN Prenatal and delivery records were examined for 320 twin pregnancies from a maternal-fetal medicine practice in Austin, TX 2011-2019. Prenatal weights for those with >1 measured weight in the first trimester and ≥3 prenatal weights were included in analyses. Trajectories were estimated to 32 weeks (mean delivery: 33.7 ± 3.3 weeks) using flexible latent class mixed models with low-rank thin-plate splines. Associations between trajectory classes and infant outcomes were analyzed using multivariable Poisson or linear regression. RESULTS Weight change from prepregnancy to delivery was 15.4 ± 6.3 kg for people with an underweight body mass index, 15.4 ± 5.8 kg for healthy weight, 14.7 ± 6.9 kg for overweight, and 12.5 ± 6.4 kg for obesity. Three trajectory classes were identified: low (Class 1), moderate (Class 2), or high gain (Class 3). Class 1 (24.7%) maintained weight for 15 weeks and then gained an estimated 6.6 kg at 32 weeks. Class 2 (60.9%) exhibited steady gain with 13.5 kg predicted total gain, and Class 3 (14.4%) showed rapid gain across pregnancy with 21.3 kg predicted gain. Compared to Class 1, Class 3 was associated with higher birth weight z-score (β = 0.63, 95% confidence interval [CI]: 0.31,0.96), increased risk for large for gestational age (IRR = 5.60, 95% CI: 1.59, 19.67), and birth <32 weeks (IRR = 2.44, 95% CI: 1.10, 5.4) that was attenuated in sensitivity analyses. Class 2 was associated with moderately elevated birth weight z-score (β = 0.24, 95% CI: 0.00, 0.48, p = 0.050). CONCLUSION Gestational weight change followed a low, moderate, or high trajectory; both moderate and high gain patterns were associated with increased infant size outcomes. Optimal patterns of weight change that balance risk during the prenatal, perinatal, and neonatal periods require further investigation, particularly in high-risk twin pregnancies. KEY POINTS · A majority gained weight below IOM twin recommendations.. · Three patterns of GWC across pregnancy were identified.. · Moderate or high GWC was associated with infant size..
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Affiliation(s)
- Amy R Nichols
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
| | - Sina Haeri
- Women's Center of Texas, St. David's Healthcare, Austin, Texas
| | - Anthony Rudine
- Office of Research, St. David's Healthcare, Austin, Texas
| | - Natalie Burns
- Department of Statistics, University of Florida, Gainesville, Florida
| | - Paul J Rathouz
- Department of Population Health and Biomedical Data Science Hub, The University of Texas at Austin Dell Medical School, Austin, Texas
| | - Monique M Hedderson
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Steven A Abrams
- Department of Pediatrics, The University of Texas at Austin Dell Medical School, Austin, Texas
| | - Saralyn F Foster
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
| | - Rachel Rickman
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
| | | | - Elizabeth M Widen
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
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Foster SF, Rundle AG, Tsai I, Genkinger JM, Burns NR, Hoepner LA, Abrego MR, Dube S, Nichols AR, Ramirez-Carvey J, Oberfield SE, Hassoun A, Perera F, Widen EM. Postpartum Obesity Is Associated With Increases in Child Adiposity in Midchildhood in a Cohort of Black and Dominican Youth. Curr Dev Nutr 2024; 8:103770. [PMID: 38948110 PMCID: PMC11214177 DOI: 10.1016/j.cdnut.2024.103770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/18/2024] [Accepted: 05/07/2024] [Indexed: 07/02/2024] Open
Abstract
Background Obesity disproportionately affects marginalized and low-income populations. Birth parent obesity from the prenatal period and childhood has been associated with child obesity. It is unknown whether prenatal or postnatal birth parent obesity has differential effects on subsequent changes in adiposity and metabolic health in children. Objectives We evaluated how birth parent obesity 7 y after delivery was associated with child body composition changes and cardiometabolic health in midchildhood and further assessed the influence of the perinatal and postpartum period on associations. Methods Black and Dominican pregnant individuals were enrolled, and dyads (n = 319) were followed up at child age 7 and 9 y. Measures included, height, weight, waist circumference (WC), and percent body fat (BF%). Multiple linear regression was used to relate postpartum weight status with child outcomes accounting for attrition, and a series of secondary analyses were conducted with additional adjustment for perinatal weight status, gestational weight gain (GWG), and/or long-term weight retention to evaluate how these factors influenced associations. Results Almost one-quarter (23%) of birth parents and 24.1% children were classified with obesity at child age 7 y, while at 9 y, 30% of children had obesity. Birth parent obesity at child age 7 y was associated with greater changes, from ages 7 to 9 y, in child BMI z-score (β: 0.13; 95% CI: 0.02, 0.24) and BF% (β: 1.15; 95% CI: 0.22, 2.09) but not obesity at age 9 y. All observed associations crossed the null after additional adjustment for prenatal factors. Conclusions Birth parent obesity at 7-y postpartum is associated with greater gains in child BMI z-score and BF% in midchildhood. These associations diminish after accounting for prenatal size, suggesting a lasting impact of the perinatal environment and that interventions supporting families from the prenatal period through childhood are needed.
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Affiliation(s)
- Saralyn F Foster
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Andrew G Rundle
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
| | - Irene Tsai
- School of Medicine, Stony Brook University, Stony Brook, NY, United States
| | - Jeanine M Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
| | - Natalie R Burns
- Department of Statistics, University of Florida, Gainesville, FL, United States
| | - Lori A Hoepner
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Department of Environmental and Occupational Health Sciences, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
| | - Marcela R Abrego
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Sara Dube
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Amy R Nichols
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Judyth Ramirez-Carvey
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
| | - Sharon E Oberfield
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Division of Pediatric Endocrinology, Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, NY, United States
| | - Abeer Hassoun
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
- Division of Pediatric Endocrinology, Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, NY, United States
| | - Frederica Perera
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
| | - Elizabeth M Widen
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
- Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University Medical Center, New York, NY, United States
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Nichols AR, Burns N, Xu F, Foster SF, Rickman R, Hedderson MM, Widen EM. Novel approaches to examining weight changes in pregnancies affected by obesity. Am J Clin Nutr 2023; 117:1026-1034. [PMID: 36878431 PMCID: PMC10273092 DOI: 10.1016/j.ajcnut.2023.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 02/16/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023] Open
Abstract
BACKGROUND Current gestational weight change (GWC) recommendations for obese individuals were established with limited evidence of the pattern and timing of weight change across pregnancy. Similarly, the recommendation of 5-9 kg does not differentiate by the severity of obesity. OBJECTIVES We sought to describe GWC trajectory classes by obesity grade and associated infant outcomes among a large, diverse cohort. METHODS The study population included 22,355 individuals with singleton pregnancies, obesity (BMI ≥30.0 kg/m2), and normal glucose tolerance who delivered at Kaiser Permanente Northern California between 2008 and 2013. Obesity grade-specific GWC trajectories were modeled at 38 wk using flexible latent class mixed modeling (package lcmm) in R. Multivariable Poisson or linear regression models estimated the associations between the GWC trajectory class and infant outcomes (size-for-gestational age and preterm birth) by obesity grade. RESULTS Five GWC trajectory classes were identified for each obesity grade, each with a distinct pattern of weight change before 15 wk (including loss, stability, and gain) followed by weight gain thereafter (low, moderate, and high). Two classes with high overall gain were associated with an increased risk for large for gestational age (LGA) in obesity grade 1 (IRR = 1.27; 95% CI: 1.10, 1.46; IRR = 1.47; 95% CI: 1.24, 1.74). Both high (IRR = 2.02; 95% CI: 1.61, 2.52; IRR = 1.98; 95% CI: 1.52, 2.58) and 2 moderate-gain classes (IRR = 1.40; 95% CI 1.14, 1.71; IRR = 1.51; 95% CI: 1.20, 1.90) were associated with LGA in grade 2, and only early loss/late moderate-gain class 3 (IRR = 1.30; 95% CI: 1.04, 1.62) was associated in grade 3. This class was also associated with preterm birth in grade 2. No associations were detected between GWC and small for gestational age (SGA). CONCLUSIONS Among the pregnancies affected by obesity, GWC was not linear or uniform. Different patterns of high gain were associated with an increased risk for LGA with the greatest magnitude in obesity grade 2, whereas GWC patterns were not associated with SGA.
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Affiliation(s)
- Amy R Nichols
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Natalie Burns
- Department of Statistics, University of Florida, Gainesville, FL, United States
| | - Fei Xu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, United States
| | - Saralyn F Foster
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Rachel Rickman
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Monique M Hedderson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, United States.
| | - Elizabeth M Widen
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, TX, United States.
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Widen EM, Burns N, Kahn LG, Grewal J, Backlund G, Nichols AR, Rickman R, Foster S, Nhan-Chang CL, Zhang C, Wapner R, Wing DA, Owen J, Skupski DW, Ranzini AC, Newman R, Grobman W, Daniels MJ. Prenatal weight and regional body composition trajectories and neonatal body composition: The NICHD Foetal Growth Studies. Pediatr Obes 2023; 18:e12994. [PMID: 36605025 PMCID: PMC9924063 DOI: 10.1111/ijpo.12994] [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: 07/19/2022] [Accepted: 11/30/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND Gestational weight gain (GWG) and anthropometric trajectories may affect foetal programming and are potentially modifiable. OBJECTIVES To assess concomitant patterns of change in weight, circumferences and adiposity across gestation as an integrated prenatal exposure, and determine how they relate to neonatal body composition. METHODS Data are from a prospective cohort of singleton pregnancies (n = 2182) enrolled in United States perinatal centres, 2009-2013. Overall and by prepregnancy BMI group (overweight/obesity and healthy weight), joint latent trajectory models were fit with prenatal weight, mid-upper arm circumference (MUAC), triceps (TSF) and subscapular (SSF) skinfolds. Differences in neonatal body composition by trajectory class were assessed via weighted least squares. RESULTS Six trajectory patterns reflecting co-occurring changes in weight and MUAC, SSF and TSF across pregnancy were identified overall and by body mass index (BMI) group. Among people with a healthy weight BMI, some differences were observed for neonatal subcutaneous adipose tissue, and among individuals with overweight/obesity some differences in neonatal lean mass were found. Neonatal adiposity measures were higher among infants born to individuals with prepregnancy overweight/obesity. CONCLUSIONS Six integrated trajectory patterns of prenatal weight, subcutaneous adipose tissue and circumferences were observed that were minimally associated with neonatal body composition, suggesting a stronger influence of prepregnancy BMI.
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Affiliation(s)
- Elizabeth M Widen
- Department of Nutritional Sciences, University of Texas at Austin, Austin, Texas, USA
- Department of Women's Health & Pediatrics, Dell Medical School, University of Texas at Austin, Austin, Texas, USA
| | - Natalie Burns
- Department of Statistics, University of Florida, Gainesville, Florida, USA
| | - Linda G Kahn
- Departments of Pediatrics and Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Jagteshwar Grewal
- Division of Population Health Research, Division of Intramural Research, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA
| | - Grant Backlund
- Department of Statistics, University of Florida, Gainesville, Florida, USA
| | - Amy R Nichols
- Department of Nutritional Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Rachel Rickman
- Department of Nutritional Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Saralyn Foster
- Department of Nutritional Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Chia-Ling Nhan-Chang
- Department of Obstetrics and Gynecology, Columbia University Medical Center, Columbia, South Carolina, USA
| | - Cuilin Zhang
- Division of Population Health Research, Division of Intramural Research, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University Medical Center, Columbia, South Carolina, USA
| | - Deborah A Wing
- Division of Maternal-Fetal Medicine, Department of Obstetrics-Gynecology, University of California, Irvine, School of Medicine, Irvine, and Fountain Valley Regional Hospital and Medical Center, Fountain Valley, California, USA
| | - John Owen
- Division of Maternal and Fetal Medicine, Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Daniel W Skupski
- Department of Obstetrics and Gynecology, New York-Presbyterian Queens Hospital, Queens, New York, USA
| | - Angela C Ranzini
- Division of Maternal and Fetal Medicine, Department of Obstetrics and Gynecology, St Peter's University Hospital, New Brunswick, New Jersey, USA
| | - Roger Newman
- Department of Obstetrics and Gynecology, Medical University of South Carolina, Columbia, South Carolina, USA
| | - William Grobman
- Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University (WAG), New Rochelle, New York, USA
| | - Michael J Daniels
- Department of Statistics, University of Florida, Gainesville, Florida, USA
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Xie J, Han Y, Peng L, Zhang J, Gong X, Du Y, Ren X, Zhou L, Li Y, Zeng P, Shao J. BMI growth trajectory from birth to 5 years and its sex-specific association with prepregnant BMI and gestational weight gain. Front Nutr 2023; 10:1101158. [PMID: 36866049 PMCID: PMC9971005 DOI: 10.3389/fnut.2023.1101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/18/2023] [Indexed: 02/16/2023] Open
Abstract
Objective The purpose of the study was to identify the latent body mass index (BMI) z-score trajectories of children from birth to 5 years of age and evaluate their sex-specific association with prepregnant BMI and gestational weight gain (GWG). Methods This was a retrospective longitudinal cohort study performed in China. In total, three distinct BMI-z trajectories from birth to 5 years of age were determined for both genders using the latent class growth modeling. The logistic regression model was used to assess the associations of maternal prepregnant BMI and GWG with childhood BMI-z growth trajectories. Results Excessive GWG increased the risks of children falling into high-BMI-z trajectory relative to adequate GWG (OR = 2.04, 95% CI: 1.29, 3.20) in boys; girls born to mothers with prepregnancy underweight had a higher risk of low-BMI-z trajectory than girls born to mothers with prepregnancy adequate weight (OR = 1.85, 95% CI: 1.22, 2.79). Conclusion BMI-z growth trajectories of children from 0 to 5 years of age have population heterogeneity. Prepregnant BMI and GWG are associated with child BMI-z trajectories. It is necessary to monitor weight status before and during pregnancy to promote maternal and child health.
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Affiliation(s)
- Jinting Xie
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yan Han
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Lei Peng
- Xuzhou Maternal and Child Health Family Planning Service Center, Xuzhou, Jiangsu, China
| | - Jingjing Zhang
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xiangjun Gong
- Xuzhou Maternal and Child Health Family Planning Service Center, Xuzhou, Jiangsu, China
| | - Yan Du
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xiangmei Ren
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Li Zhou
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yuanhong Li
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ping Zeng
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jihong Shao
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,*Correspondence: Jihong Shao,
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