1
|
Nichols AR, Chavarro JE, Oken E. Reproductive risk factors across the female lifecourse and later metabolic health. Cell Metab 2024; 36:240-262. [PMID: 38280383 PMCID: PMC10871592 DOI: 10.1016/j.cmet.2024.01.002] [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: 10/06/2023] [Revised: 12/08/2023] [Accepted: 01/05/2024] [Indexed: 01/29/2024]
Abstract
Metabolic health is characterized by optimal blood glucose, lipids, cholesterol, blood pressure, and adiposity. Alterations in these characteristics may lead to the development of type 2 diabetes mellitus or dyslipidemia. Recent evidence suggests that female reproductive characteristics may be overlooked as risk factors that contribute to later metabolic dysfunction. These reproductive traits include the age at menarche, menstrual irregularity, the development of polycystic ovary syndrome, gestational weight change, gestational dysglycemia and dyslipidemia, and the severity and timing of menopausal symptoms. These risk factors may themselves be markers of future dysfunction or may be explained by shared underlying etiologies that promote long-term disease development. Disentangling underlying relationships and identifying potentially modifiable characteristics have an important bearing on therapeutic lifestyle modifications that could ease long-term metabolic burden. Further research that better characterizes associations between reproductive characteristics and metabolic health, clarifies underlying etiologies, and identifies indicators for clinical application is warranted in the prevention and management of metabolic dysfunction.
Collapse
Affiliation(s)
- Amy R Nichols
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Jorge E Chavarro
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Emily Oken
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| |
Collapse
|
2
|
Li W, Wang L, Guo J, Dong W, Zhang S, Li W, Leng J. Seasonal variation and its interaction with pre-pregnancy BMI for GDM: a large population-based study in Tianjin, China. Sci Rep 2023; 13:22837. [PMID: 38129497 PMCID: PMC10739738 DOI: 10.1038/s41598-023-49609-w] [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: 04/24/2023] [Accepted: 12/10/2023] [Indexed: 12/23/2023] Open
Abstract
To evaluate the independent association of seasonal variation with GDM incidence in Tianjin, China, and to test whether there is an additive interaction between seasonal variation and pre-pregnancy body mass index (BMI) on GDM incidence. A population-based observational cohort study was conducted using the healthcare records data from Tianjin, China. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs). Additive interaction between pre-pregnancy BMI groups and seasons was estimated by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). Among the 112,639 pregnant women, 20.8% developed GDM at 24-28 weeks of gestation. The multivariable adjusted ORs and 95% CIs were 1.00, 1.00 (0.96-1.05), 1.15 (1.09-1.20) and 1.22 (1.16-1.29) respectively based on seasons (spring, summer, autumn and winter). Compared with the spring/summer and pre-pregnant BMI < 24 kg/m2 group, co-presence of autumn/winter and pre-pregnancy BMI ≥ 24 kg/m2 increased the OR from 1.00 to 2.70 (95% CI 2.28-3.20), with a significant additive interaction: RERI (0.32, 95% CI 0.19-0.45), S (1.21, 95% CI 1.12-1.31) and AP (0.11, 95% CI 0.07-0.16). Autumn/winter is an independent risk factor for GDM incidence, and can significantly amplify the obesity-associated risk for GDM incidence. The underlying mechanism warrants further investigations. We suggest that seasonality is an additional factor when interpreting OGTT results for the diagnosis of GDM.
Collapse
Affiliation(s)
- Weiqin Li
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Leishen Wang
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Jia Guo
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Wei Dong
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Shuang Zhang
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Wei Li
- Tianjin Women and Children's Health Center, Tianjin, 300070, China
| | - Junhong Leng
- Tianjin Women and Children's Health Center, Tianjin, 300070, China.
| |
Collapse
|
3
|
Gao L, Lei C, Zhou S, Liao Q, Mei L, Zhong Q, Lan X, Chen Y, Wang L. Investigation of optimal gestational weight gain for twin pregnancy in Southwest China: a retrospective study. Sci Rep 2023; 13:5059. [PMID: 36977708 PMCID: PMC10050188 DOI: 10.1038/s41598-023-31766-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 03/16/2023] [Indexed: 03/30/2023] Open
Abstract
There is a lack of data on gestational weight gain (GWG) in twin pregnancies. We divided all the participants into two subgroups: the optimal outcome subgroup and the adverse outcome subgroup. They were also stratified according to prepregnancy body mass index (BMI): underweight (< 18.5 kg/m2), normal weight (18.5-23.9 kg/m2), overweight (24-27.9 kg/m2), and obese (≥ 28 kg/m2). We used 2 steps to confirm the optimal range of GWG. The first step was proposing the optimal range of GWG using a statistical-based method (the interquartile range of GWG in the optimal outcome subgroup). The second step was confirming the proposed optimal range of GWG via compared the incidence of pregnancy complications in groups below or above the optimal GWG and analyzed the relationship between weekly GWG and pregnancy complications to validated the rationality of optimal weekly GWG through logistic regression. The optimal GWG calculated in our study was lower than that recommended by the Institute of Medicine. Except for the obese group, in the other 3 BMI groups, the overall disease incidence within the recommendation was lower than that outside the recommendation. Insufficient weekly GWG increased the risk of gestational diabetes mellitus, premature rupture of membranes, preterm birth and fetal growth restriction. Excessive weekly GWG increased the risk of gestational hypertension and preeclampsia. The association varied with prepregnancy BMI. In conclusion, we provide preliminary Chinese GWG optimal range which derived from twin-pregnant women with optimal outcomes(16-21.5 kg for underweight, 15-21.1 kg for normal weight, 13-20 kg for overweight), except for obesity, due to the limited sample size.
Collapse
Affiliation(s)
- Li Gao
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Cuirong Lei
- Gynecological Oncology Center, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Shuwei Zhou
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Qianqian Liao
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Lingwei Mei
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Qimei Zhong
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Xia Lan
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Ya Chen
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China
| | - Lan Wang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), Chongqing, 401147, China.
| |
Collapse
|
4
|
Shen Y, Zheng Y, Su Y, Jiang S, Ma X, Hu J, Li C, Huang Y, Teng Y, Bao Y, Tao M, Zhou J. Insulin sensitivity, β cell function, and adverse pregnancy outcomes in women with gestational diabetes. Chin Med J (Engl) 2022; 135:2541-2546. [PMID: 36583917 PMCID: PMC9944688 DOI: 10.1097/cm9.0000000000002337] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The potential impact of β cell function and insulin sensitivity on adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM) remains uncertain. We aimed to investigate the association between β cell dysfunction, insulin resistance, and the composite adverse pregnancy outcomes. METHODS This observational study included 482 women diagnosed with GDM during pregnancy. Quantitative metrics on β cell function and insulin sensitivity during pregnancy were calculated using traditional equations. The association of β cell dysfunction and insulin resistance with the risk of the composite adverse pregnancy outcomes was investigated using multivariable-adjusted logistic regression models. RESULTS Multivariable-adjusted odds ratios (ORs) of adverse pregnancy outcomes across quartiles of homeostatic model assessment for insulin resistance (HOMA-IR) were 1.00, 0.95, 1.34, and 2.25, respectively (P for trend = 0.011). When HOMA-IR was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 1.34 (95% confidence interval 1.16-1.56) for each 1-unit increase in HOMA-IR. Multivariable-adjusted ORs of adverse pregnancy outcomes across quartiles of homeostatic model assessment for β cell function (HOMA-β) were 1.00, 0.51, 0.60, and 0.53, respectively (P for trend = 0.068). When HOMA-β was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 0.57 (95% CI 0.24-0.90) for each 1-unit increase in HOMA-β. However, other quantitative metrics were not associated with the composite adverse pregnancy outcomes. CONCLUSIONS We demonstrated a significant association of β cell function and insulin sensitivity with the risk of adverse pregnancy outcomes. We have provided additional evidence on the early identification of adverse pregnancy outcomes besides the glycemic values.
Collapse
Affiliation(s)
- Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yanwei Zheng
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yingying Su
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Susu Jiang
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Xiaojing Ma
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Jiangshan Hu
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Changbin Li
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yajuan Huang
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yincheng Teng
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Minfang Tao
- Department of Gynecology and Obstetrics, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| |
Collapse
|