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Zeng N, Li C, Mei H, Wu S, Liu C, Wang X, Shi J, Lu L, Bao Y. Bidirectional Association between Sarcopenia and Depressive Symptoms among Chinese Middle- and Older-Aged Adults: Longitudinal Observational Study. Brain Sci 2024; 14:593. [PMID: 38928593 PMCID: PMC11201564 DOI: 10.3390/brainsci14060593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/20/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND The study aimed to examine the bidirectional relationship between sarcopenia and depressive symptoms in a national, community-based cohort study, despite the unclear temporal sequence demonstrated previously. METHODS Data were derived from four waves (2011 baseline and 2013, 2015, and 2018 follow-ups) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 17,708 participants aged 45 years or older who had baseline data on both sarcopenia status and depressive symptoms in 2011 were included in the study. For the two cohort analyses, a total of 8092 adults without depressive symptoms and 11,292 participants without sarcopenia in 2011 were included. Sarcopenia status was defined according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Depressive symptoms were defined as a score of 20 or higher on the 10-item Center for Epidemiologic Studies Depressive Scale (CES-D-10). Cox proportional hazard regression models were conducted to examine the risk of depressive symptoms and sarcopenia risk, while cross-lagged panel models were used to examine the temporal sequence between depressive symptoms and sarcopenia over time. RESULTS During a total of 48,305.1 person-years follow-up, 1262 cases of incident depressive symptoms were identified. Sarcopenia exhibited a dose-response relationship with a higher risk of depressive symptoms (HR = 1.7, 95%CI: 1.2-2.3 for sarcopenia, and HR = 1.5, 95%CI: 1.2-1.8 for possible sarcopenia, p trend < 0.001). In the second cohort analysis, 240 incident sarcopenia cases were identified over 39,621.1 person-years. Depressive symptoms (HR = 1.5, 95%CI: 1.2-2.0) are significantly associated with a higher risk of developing sarcopenia after multivariable adjustment (p < 0.001, Cross-lagged panel analyses demonstrated that depressive symptoms were associated with subsequent sarcopenia (β = 0.003, p < 0.001). Simultaneously, baseline sarcopenia was also associated with subsequent depressive symptoms (β = 0.428, p < 0.001). CONCLUSION This study identified a bidirectional relationship between depressive symptoms and sarcopenia. It seems more probable that baseline sarcopenia is associated with subsequent depressive symptoms in a stronger pattern than the reverse pathway. The interlinkage indicated that maintaining normal muscle mass and strength may serve as a crucial intervention strategy for alleviating mood disorders.
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Affiliation(s)
- Na Zeng
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Chao Li
- Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China;
| | - Huan Mei
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Shuilin Wu
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Chang Liu
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Xiaokun Wang
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
| | - Lin Lu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
- National Clinical Research Center for Mental Disorders, Key of Mental Health, Ministry of Health (Peking University), Peking University Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
| | - Yanping Bao
- School of Public Health, Peking University, Beijing 100191, China; (N.Z.); (H.M.); (S.W.); (C.L.); (X.W.)
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China;
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Jin S, Liu J, Jia Y, Sun C, Na L. Temporal relationships between blood glucose, lipids and BMI, and their impacts on atherosclerosis: a prospective cohort study. BMJ Open 2024; 14:e079521. [PMID: 38839391 PMCID: PMC11163681 DOI: 10.1136/bmjopen-2023-079521] [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: 09/03/2023] [Accepted: 04/29/2024] [Indexed: 06/07/2024] Open
Abstract
OBJECTIVES This study aimed to explore the temporal relationship between blood glucose, lipids and body mass index (BMI), and their impacts on atherosclerosis (AS). DESIGN A prospective cohort study was designed. SETTING AND PARTICIPANTS A total of 2659 subjects from Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases, and aged from 20 to 74 years were included. PRIMARY AND SECONDARY OUTCOME MEASURES Body weight, height, fasting blood glucose (FBG) and 2-hour postprandial glucose (2-h PG), blood lipids including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c) were measured at baseline and follow-up. Brachial ankle pulse wave velocity (baPWV) was examined at follow-up as a marker of AS risk. Logistic regression analysis, cross-lagged path analysis and mediation analysis were performed to explore the temporal relationships between blood glucose, lipids and BMI, and their impacts on AS risk. RESULTS Logistic regression analysis indicated that increased FBG, 2-h PG, TC, TG, LDL-c and BMI were positively associated with AS risk, while increased HDL-c was negatively associated with AS risk. The path coefficients from baseline blood parameters to the follow-up BMI were significantly greater than those from baseline BMI to the follow-up blood parameters. Mediation analysis suggested that increased FBG, 2-h PG, TC, TG and LDL-c could increase AS risk via increasing BMI, the effect intensity from strong to weak was LDL-c>TC>TG>FBG>2 h PG, while increased HDL-c could decrease AS risk via decreasing BMI. CONCLUSIONS Changes in blood glucose and lipids could cause change in BMI, which mediated the impacts of blood glucose and lipids on AS risk. These results highlight the importance and provide support for the early and comprehensive strategies of AS prevention and control.
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Affiliation(s)
- Shanshan Jin
- Nutrition, Chengdu Women's and Children's Central Hospital, Chengdu, China
- Department of Nutrition and Food Hygiene, Harbin Medical University, Harbin, China
| | - Junyi Liu
- Department of Nutrition and Food Hygiene, Harbin Medical University, Harbin, China
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
| | - Yubing Jia
- Department of Nutrition and Food Hygiene, Harbin Medical University, Harbin, China
| | - Changhao Sun
- Department of Nutrition and Food Hygiene, Harbin Medical University, Harbin, China
| | - Lixin Na
- Department of Nutrition and Food Hygiene, Harbin Medical University, Harbin, China
- Department of Nutrition and Food Hygiene, Shanghai University of Medicine and Health Sciences, Shanghai, China
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Zhao B, Yu Z, Sun J, Cheng W, Yu T, Yang Y, Wei Z, Yin Z. Light pollution during pregnancy influences the growth of offspring in rats. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 279:116485. [PMID: 38788564 DOI: 10.1016/j.ecoenv.2024.116485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 04/25/2024] [Accepted: 05/18/2024] [Indexed: 05/26/2024]
Abstract
OBJECTIVE To investigate the effects of excessive light exposure during gestation on intrauterine development and early growth of neonates in rats. METHODS Pregnant rats were randomly allocated to three groups: the constant light exposure group, non-light exposure group and control group. Blood samples were collected from the tail vein to analyze melatonin and cortisol levels. Weight, daily food and water consumption were recorded. Uterine weight, placental weight and placental diameter were measured on gestational day 19. Natural birth and neonate growth were also monitored. The expression of NR1D1(nuclear receptor subfamily 1 group D member 1) in offspring's SCN (suprachiasmatic nuclei), liver and adipose tissue was measured. Expression of NR1D1, MT1(melatonin 1 A receptor) and 11β-HSD2 (placental 11β-hydroxysteroid dehydrogenase type 2) in placenta was also measured. Finally, the expression of MT1 and 11β-HSD2 in NR1D1 siRNA transfected JEG-3 cells was evaluated. RESULTS There were no significant differences in maternal weight gain, pregnancy duration, uterine weight, placental body weight, placental diameter, fetal number among three groups. There were no significant differences in weights or lengths of offspring at birth. Compared to other two groups, constant light exposure group showed significantly more rapid growth of offspring in 21st day post-birth. The expression of NR1D1 in SCN, liver and adipose tissues of offspring was not significantly different among three groups. The maternal serum melatonin and cortisol levels of the constant light exposure group were lower and higher than other two groups, respectively. The expressions of NR1D1, MT1 and 11β-HSD2 were all decreased in placenta of the constant light exposure group. The expression of MT1 and 11β-HSD2 in JEG-3 cells were decreased after NR1D1 siRNA transfection. CONCLUSION Excessive light exposure during pregnancy results in elevated cortisol and reduced melatonin exposure to fetuses in uterus, potentially contributing to an accelerated early growth of offspring in rats.
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Affiliation(s)
- Baojing Zhao
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Reproductive Health and Genetics, No 81 Meishan Road, Hefei, Anhui 230032, China; Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, Anhui 230032, China
| | - Zhen Yu
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, Anhui 230032, China; Engineering Research Center of Biopreservation and Artificial Organs, Ministry of Education, No 81 Meishan Road, Hefei, Anhui 230032, China
| | - Junjie Sun
- Department of Nuclear Medicine, School of Laboratory Medicine, Bengbu Medical College, No.2600 Donghai Road, Bengbu, Anhui 233030, China
| | - Weisheng Cheng
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, Anhui 230032, China
| | - Tao Yu
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China
| | - Yuanyuan Yang
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China
| | - Zhaolian Wei
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, Anhui 230032, China; Engineering Research Center of Biopreservation and Artificial Organs, Ministry of Education, No 81 Meishan Road, Hefei, Anhui 230032, China; Biopreservation and Artificial Organs, Anhui Provincial Engineering Research Center, Anhui Medical University, No 81 Meishan Road, Hefei, Anhui 230032, China.
| | - Zongzhi Yin
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, Anhui 230022, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei, Anhui 230032, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Reproductive Health and Genetics, No 81 Meishan Road, Hefei, Anhui 230032, China.
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Tian X, Chen S, Xu Q, Zhang Y, Xia X, Wang P, Wu S, Wang A. Temporal relationship between arterial stiffness and blood pressure variability and joint effect on cardiovascular disease. Hypertens Res 2024; 47:1133-1143. [PMID: 38145991 DOI: 10.1038/s41440-023-01541-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/16/2023] [Accepted: 11/18/2023] [Indexed: 12/27/2023]
Abstract
Although arterial stiffness measured by brachial-ankle pulse wave velocity (baPWV) and blood pressure (BP) significantly correlated, the relationship between baPWV and BP variation (BPV) was unclear. This study aimed to examine the temporal relationship between brachial-ankle pulse wave velocity (baPWV) and systolic blood pressure variation (SBPV) and their joint effect on the development of cardiovascular disease (CVD). This study included 6632 participants with repeated assessments of baPWV and BP during 2006 to 2018. The baseline and follow-up SBPV was calculated as absolute SBP difference divided by mean SBP over sequential visits, using data between 2006-2010 and 2014-2018, respectively. Cross-lagged analysis was used to assess the temporal relation between baPWV and SBPV, and logistic analysis was used to assess the joint effect of baPWV and SBPV on CVD. After adjustment for confounder, the path coefficient from baseline baPWV to follow-up SBPV (β1 = 0.040; P = 0.0012) was significantly had greater than the path from baseline SBPV to follow-up baPWV (β2 = 0.009; P = 0.3830), with P = 0.0232 for the difference between β1 and β2. This unidirectional relationship from baseline baPWV to follow-up SBPV was consistent in patients without hypertension, with isolated systolic, high systolic and diastolic, uncontrolled and controlled hypertension. In addition, participants with high levels of baseline baPWV and follow-up SBPV had greater risk of CVD (odds ratio, 5.82; 95% confidence interval, 2.50-12.60) than those with low-low levels. The findings suggested that arterial stiffness appeared to precede the increase in SBPV and their joint effect is predictive of the development of CVD.
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Affiliation(s)
- Xue Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, 57 Xinhua East Rd, Tangshan, 063000, China
| | - Qin Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yijun Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xue Xia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Penglian Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, 57 Xinhua East Rd, Tangshan, 063000, China.
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China.
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Tian X, Xia X, Zhang Y, Xu Q, Luo Y, Wang A. Temporary relationship between sleep duration and depression and its impact on future risk of cardiovascular disease. J Affect Disord 2024; 350:559-564. [PMID: 38266925 DOI: 10.1016/j.jad.2024.01.185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/13/2024] [Accepted: 01/18/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND Although sleep duration and depression were correlated, their temporal sequence and how the sequence influence on future risk of cardiovascular disease (CVD) remained undetermined. This study aimed to explore the temporal relationship between sleep duration and depression, and its association with future CVD risk. METHODS We included 10,629 middle-aged and elderly participants with repeated measurements of sleep duration and depressive symptoms (measured by Center for Epidemiological Studies-Depression scale [CESD]) at the first two visits from the China Health and Retirement Longitudinal Study. Cross-lagged analysis and mediation analysis were used to examine the temporal relationship between sleep duration and depression and its impact on future risk of CVD. RESULTS The adjusted cross-lagged path coefficient from baseline sleep duration to follow-up CES-D (β1 = -0.191; 95 % confidence interval [CI], -0.239 to -0.142) was significantly greatly than that from baseline CES-D to follow-up sleep duration (β2 = -0.031; 95 % CI, -0.031 to -0.024) (Pdifference < 0.0001). Similarly, the path coefficient from baseline sleep duration to annual changes in CES-D was significantly greater than that from baseline CES-D to annual changes in sleep duration (β1 = -0.093 versus β2 = -0.015, Pdifference < 0.0001). The path coefficient from baseline sleep duration to follow-up CES-D in CVD group was significantly greater than that in those without CVD (Pdifference of β1 = 0.0378). Furthermore, 27.93 % of the total association of sleep duration with CVD was mediated by depression symptoms. CONCLUSIONS The findings provide evidence that decrease in sleep duration probably precedes the increased in depressive symptoms, and depression partially mediated the pathway from sleep duration to incident CVD.
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Affiliation(s)
- Xue Tian
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xue Xia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yijun Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Qin Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanxia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China.
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Cui K, Meng W, Li Z, Zeng X, Li X, Ge X. Dynamics, association, and temporal sequence of cognitive function and frailty: a longitudinal study among Chinese community-dwelling older adults. BMC Geriatr 2023; 23:658. [PMID: 37833637 PMCID: PMC10571451 DOI: 10.1186/s12877-023-04328-9] [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: 06/28/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Little is known about the association of longitudinal dynamics between cognitive function and frailty in Chinese older adults. The temporal sequences between cognitive function and frailty remains unclear. Our study investigates this directionality association using longitudinal data. METHODS Latent growth and multivariate latent growth models were employed to examine dynamics of cognition and frailty and their association among 2824 older adults in China. Cross-lagged panel analyses were used to assess the temporal sequences between frailty and cognition. The relation between cognitive domains and frailty was also examined using aforementioned methods. RESULTS Cognitive function was negatively associated with frailty status. Higher initial level of cognition indicated lower baseline level (β=-0.175, P < 0.001) and change rate (β=-0.041, P = 0.002) of frailty. We observed a reciprocal association between frailty and cognitive function rather than a unidirectional causal relationship. The initial cognitive performance for all components were negatively associated with baseline (β ranged between - 0.098 to -0.023) and change rate (β ranged between - 0.007 to -0.024) of frail status. No consistent associations between change rate of cognitive components and either initial level or change rate of frailty were detected. CONCLUSIONS Our study detected a reciprocal association between cognition and frailty rather than a unidirectional causal relationship. Our results also revealed different connections between cognitive performance and frailty across diverse cognitive domains.
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Affiliation(s)
- Kai Cui
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China
| | - Weihan Meng
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China
| | - Zhiqiang Li
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China
| | - Xinning Zeng
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China
| | - Xiaozhe Li
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China
| | - Xiaoyan Ge
- School of Public Health, Jinzhou Medical University, 40 Songpo Road, Jinzhou, 121000, P. R. China.
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Ekperikpe US, Mandal S, Holt SJ, Daniels JK, Johnson TD, Cooper JS, Safir SM, Cornelius DC, Williams JM. Metformin reduces insulin resistance and attenuates progressive renal injury in prepubertal obese Dahl salt-sensitive rats. Am J Physiol Renal Physiol 2023; 325:F363-F376. [PMID: 37498548 PMCID: PMC10639024 DOI: 10.1152/ajprenal.00078.2023] [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: 04/06/2023] [Revised: 07/12/2023] [Accepted: 07/24/2023] [Indexed: 07/28/2023] Open
Abstract
Prepubertal obesity is currently an epidemic and is considered as a major risk factor for renal injury. Previous studies have demonstrated that insulin resistance contributes to renal injury in obesity, independent of diabetes. However, studies examining the relationship between insulin resistance and renal injury in obese children are lacking. Recently, we reported that progressive renal injury in Dahl salt-sensitive (SS) leptin receptor mutant (SSLepRmutant) rats was associated with insulin resistance before puberty. Therefore, the aim of the present study was to examine whether decreasing insulin resistance with metformin will reduce renal injury in SSLepRmutant rats. Four-wk-old SS and SSLepRmutant rats were separated into the following two groups: 1) vehicle and 2) metformin (300 mg/kg/day) via chow diet for 4 wk. Chronic administration of metformin markedly reduced insulin resistance and dyslipidemia in SSLepRmutant rats. We did not detect any differences in mean arterial pressure between vehicle and metformin-treated SS and SSLepRmutant rats. Proteinuria was significantly greater in SSLepRmutant rats versus SS rats throughout the study, and metformin administration significantly reduced proteinuria in SSLepRmutant rats. At the end of the protocol, metformin prevented the renal hyperfiltration observed in SSLepRmutant rats versus SS rats. Glomerular and tubular injury and renal inflammation and fibrosis were significantly higher in vehicle-treated SSLepRmutant rats versus SS rats, and metformin reduced these parameters in SSLepRmutant rats. These data suggest that reducing insulin resistance with metformin prevents renal hyperfiltration and progressive renal injury in SSLepRmutant rats before puberty and may be therapeutically useful in managing renal injury during prepubertal obesity.NEW & NOTEWORTHY Childhood/prepubertal obesity is a public health concern that is associated with early signs of proteinuria. Insulin resistance has been described in obese children. However, studies investigating the role of insulin resistance during childhood obesity-associated renal injury are limited. This study provides evidence of an early relationship between insulin resistance and renal injury in a rat model of prepubertal obesity. These data also suggest that reducing insulin resistance with metformin may be renoprotective in obese children.
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Affiliation(s)
- Ubong S Ekperikpe
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Sautan Mandal
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Stephen J Holt
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Jacori K Daniels
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Tyler D Johnson
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Jonita S Cooper
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Sarah M Safir
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Denise C Cornelius
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
| | - Jan M Williams
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi, United States
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Wada K, Nagata C, Yamakawa M, Nakashima Y, Koda S, Uji T, Tsuji M, Nagai H, Itakura N, Harada K, Takahara O, Yamanaka H. Association of dietary fibre intake with subsequent fasting glucose levels and indicators of adiposity in school-age Japanese children. Public Health Nutr 2023; 26:1617-1625. [PMID: 37226764 PMCID: PMC10410373 DOI: 10.1017/s136898002300099x] [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: 01/07/2022] [Revised: 08/29/2022] [Accepted: 10/19/2022] [Indexed: 05/26/2023]
Abstract
OBJECTIVE To evaluate the relationships of fibre intake with subsequent BMI sd-score, waist-to-height ratio and serum fasting glucose levels among school-age Japanese children. DESIGN This is a prospective study of school-age Japanese children. Participants were followed from 6-7 to 9-10 years of age (follow-up rate: 92·0 %). Fibre intake was assessed using a validated FFQ. Serum fasting glucose was measured by a hexokinase enzymatic method. Using a general linear model, the associations between dietary fibre intake at baseline and BMI sd-score, waist-to-height ratio, and serum levels of fasting glucose at follow-up were evaluated after considering potential confounding factors. SETTING Public elementary schools in a city in Japan. PARTICIPANTS A total of 2784 students. RESULTS The estimated means for fasting glucose at 9-10 years of age were 86·45, 85·68, 85·88 and 85·58 mg/dl in the lowest, second, third and highest quartile of fibre intake at 6-7 years of age, respectively (P = 0·033, trend P = 0·018). Higher fibre intake at 6-7 years of age was associated with lower waist-to-height ratio at 9-10 years of age (trend P = 0·023). The change in fibre intake was inversely associated with concurrent change of BMI sd-score (trend P = 0·044). CONCLUSION These results suggest that dietary fibre intake may be potentially effective to limit excess weight gain and lower glucose levels during childhood.
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Affiliation(s)
- Keiko Wada
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Chisato Nagata
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Michiyo Yamakawa
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Yuma Nakashima
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Sachi Koda
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Takahiro Uji
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
| | - Michiko Tsuji
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu501-1194, Japan
- Department of Food Science and Nutrition, Nagoya Women’s University, Nagoya, Japan
| | | | | | - Kou Harada
- Hekinan Medical Association, Hekinan, Japan
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Tian X, Chen S, Wang P, Xu Q, Zhang Y, Zhang X, Wu S, Luo Y, Wang A. Temporal relationship between hyperuricemia and hypertension and its impact on future risk of cardiovascular disease. Eur J Intern Med 2023; 111:82-89. [PMID: 36890009 DOI: 10.1016/j.ejim.2023.02.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 02/21/2023] [Accepted: 02/28/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND Although hyperuricemia and hypertension are significantly correlated, their temporal relationship and whether this relationship is associated with risk of cardiovascular disease (CVD) are largely unknown. This study aimed to examine temporal relationship between hyperuricemia and hypertension, and its association with future risk of CVD. METHODS This study included 60,285 participants from the Kailuan study. Measurement of serum uric acid (SUA), systolic and diastolic blood pressure (SBP and DBP) were obtained twice at 2006 (baseline) and 2010. Cross-lagged and mediation analysis were used to examine the temporal relationship between hyperuricemia and hypertension, and the association of this temporal relationship with CVD events risk after 2010. RESULTS After adjusting for covariates, the cross-lagged path coefficients (β1) from baseline SUA to follow-up SBP and DBP were significantly greatly than path coefficients (β2) from baseline SBP and DBP to follow-up SUA (β1=0.041 versus β2=0.003; Pdifference<0.0001 for SBP; β1=0.040 versus β2=0.000; Pdifference<0.0001 for DBP). The path coefficients from baseline SUA to follow-up SBP and DBP in group with incident CVD were significantly greatly than that in group without incident CVD (Pdifference of β1 in the two groups was 0.0018 for SBP and 0.0340 for DBP). Furthermore, SBP and DBP partially mediated the effect of SUA on incident CVD, the mediation effect was 57.64% for SBP and 46.27% for DBP. Similar mediated results were observed for stroke and myocardial infarction. CONCLUSION Increased SUA levels probably precede elevated BP, and BP partially mediates the pathway from SUA to incident CVD.
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Affiliation(s)
- Xue Tian
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Penglian Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qin Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yijun Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xiaoli Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
| | - Yanxia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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Wu S, Tian X, Chen S, Zhang Y, Zhang X, Xu Q, Wang A. Arterial stiffness and blood pressure in treated hypertension: a longitudinal study. J Hypertens 2023; 41:768-774. [PMID: 36883462 DOI: 10.1097/hjh.0000000000003400] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
OBJECTIVES It has been reported that an increase in arterial stiffness precedes an increase in blood pressure (BP) in the general population. Whether BP lowering results from of reducing arterial wall or vice versa in antihypertensive treatment is unclear. This study aimed to investigate the association between arterial stiffness and BP in patients with treated hypertension. METHODS This study included 3277 participants who were treated with antihypertensive agents and with repeated measurements of branchial-ankle pulse wave velocity (baPWV) and BP during 2010-2016 from the Kailuan study. Temporal relation between baPWV and BP was assessed by cross-lagged path analyses. RESULTS After adjustment for potential confounders, the standard regression coefficient from baseline baPWV to follow-up SBP was 0.14 [95% confidence interval (95% CI), 0.10-0.18], which was significantly greater than that from baseline SBP to follow-up baPWV (0.05; 95% CI, 0.02-0.08) ( P < 0.0001 for difference). Similar results were observed for the cross-lagged analysis with changes of baPWV and mean arterial pressure. Further analysis showed that the yearly rate of change in SBP during the follow-up period significantly varied across increasing quartiles of baseline baPWV ( P < 0.0001), whereas the yearly rate of change in baPWV showed a nonsignificantly varied trend across quartiles of baseline SBP ( P = 0.2443). CONCLUSION These findings provided strong evidence that reduction in arterial stiffness through antihypertensive treatment could precede BP lowering.
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Affiliation(s)
- Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan
| | - Xue Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan
| | - Yijun Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xiaoli Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital
| | - Qin Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital
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Nie X, Mu G, Guo Y, Yang S, Wang X, Ye Z, Tan Q, Wang M, Zhou M, Ma J, Chen W. Associations of selenium exposure with blood lipids: Exploring mediating DNA methylation sites in general Chinese urban non-smokers. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161815. [PMID: 36708841 DOI: 10.1016/j.scitotenv.2023.161815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/17/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Selenium (Se) is widely distributed in the total environment and people are commonly exposed to Se, while the potential effects and mechanisms of Se exposure on blood lipids have not been well established. This study aimed to assess the associations of urinary Se (SeU) with blood lipids and explore the potential mediating DNA methylation sites. We included 2844 non-smoke participants from the second follow-up (2017-2018) of the Wuhan-Zhuhai cohort (WHZH) in this study. SeU and blood lipids [i.e., total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL)] for all participants were determined. The associations of SeU with blood lipids were analyzed by generalized linear models. Then, we conducted the blood lipids related epigenome-wide association studies (EWAS) among 221 never smokers, and the mediation analysis was conducted to explore the potential mediating cytosine-phosphoguanine (CpG) sites in the above associations. In this study, the SeU concentration of the participants in this study was 1.40 (0.94, 2.08) μg/mmol Cr. The SeU was positively associated with TC and LDL, and not associated with TG and HDL. We found 131, 3, and 1 new CpG sites related to TC, HDL, and LDL, respectively. Mediation analyses found that the methylation of cg06964030 (within MIR1306) and cg15824094 (within PLCH2) significantly mediated the positive association between SeU and TC. In conclusion, high levels of Se exposure were associated with increased TC and LDL among non-smokers, and the methylation of MIR1306 and PLCH2 partly mediated Se-associated TC increase. These findings provide new insights into the effects and mechanisms of Se exposure on lipids metabolism and highlight the importance of controlling Se exposure and intake for preventing high blood lipids.
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Affiliation(s)
- Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xing Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Mengyi Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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12
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Xu Z, Chen M, Yao Y, Yu L, Yan P, Cui H, Li P, Liao J, Zhang B, Yao Y, Liu Z, Jiang X, Liu T, Xiao C. Temporal relationship between sleep duration and obesity among Chinese Han people and ethnic minorities. BMC Public Health 2023; 23:503. [PMID: 36922806 PMCID: PMC10015728 DOI: 10.1186/s12889-023-15413-4] [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: 11/11/2022] [Accepted: 03/09/2023] [Indexed: 03/17/2023] Open
Abstract
BACKGROUND No studies have assessed the association between sleep duration and obesity in Chinese ethnic minorities. Whether the relationship between sleep duration and obesity is different between Chinese Han people and Chinese ethnic minorities remains unclear. The study aimed to explore the relationship between sleep duration and obesity among Chinese Han people and Chinese ethnic minorities. METHODS We applied data from the Guizhou Population Health Cohort Study (GPHCS), which 9,280 participants were recruited in the baseline survey from 2010 to 2012, and 8,163 completed the follow-up survey from 2016 to 2020. A total of 5,096 participants (3,188 Han Chinese and 1,908 ethnic minorities) were included in the ultimate analysis. Information on sleep duration (total 24-hour sleep time), body mass index (BMI), and waist circumference (WC) was collected at the baseline and follow-up survey, respectively. Cross-lagged panel analyses were conducted to explore the temporal relationship between sleep duration and obesity for Han people and ethnic minorities. RESULTS For Han people, the results from cross-lagged panel analyses indicated that baseline sleep duration was significantly associated with follow-up BMI (βBMI = -0.041, 95% CIBMI: -0.072 ~ -0.009) and follow-up WC (βWC = -0.070, 95%CIWC: -0.103 ~ -0.038), but baseline BMI (βBMI = -0.016, 95% CIBMI: -0.050 ~ 0.018) and baseline WC (βWC = -0.019, 95% CIWC: -0.053 ~ 0.016) were not associated with follow-up sleep duration. In addition, the relationship between baseline sleep duration and follow-up BMI was gender-specific and significant only in the Han people female (βBMI = -0.047, 95% CIBMI: -0.090 ~ -0.003) but not in the Han people male (βBMI = -0.029, 95% CIBMI: -0.075 ~ 0.016). For ethnic minorities, the results indicated that there was no relationship between sleep duration and obesity at all, either from sleep duration to obesity (βBMI = 0.028, 95%CIBMI: -0.012 ~ 0.068; βWC = 0.020, 95%CIWC: -0.022 ~ 0.062), or from obesity to sleep duration (βBMI = -0.022, 95%CIBMI: -0.067 ~ 0.022; βWC = -0.042, 95%CIWC: -0.087 ~ 0.003). CONCLUSION The relationship pattern between sleep duration and obesity across Han people and ethnic minorities is different. Future sleep-aimed overweight and obesity intervention should be conducted according to population characteristics.
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Affiliation(s)
- Zhengxing Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Min Chen
- Guizhou Province Centre for Disease Control and Prevention, 101 Bageyan Road, Yunyan District, 550004, Guiyang, Guizhou Province, China
| | - Yuntong Yao
- Guizhou Province Centre for Disease Control and Prevention, 101 Bageyan Road, Yunyan District, 550004, Guiyang, Guizhou Province, China
| | - Lisha Yu
- Guizhou Province Centre for Disease Control and Prevention, 101 Bageyan Road, Yunyan District, 550004, Guiyang, Guizhou Province, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Ping Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Jiaqiang Liao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
- Department of Hygienic Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16, Section 3, Renmin Nan Lu, 610041, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Tao Liu
- Guizhou Province Centre for Disease Control and Prevention, 101 Bageyan Road, Yunyan District, 550004, Guiyang, Guizhou Province, China.
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China.
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16, Section 3, Renmin Nan Lu, 610041, Chengdu, Sichuan, China.
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Li H, Zhang J, Zou X, Jia X, Zheng D, Guo X, Xie W, Yang Q. The Bidirectional Association Between Cognitive Function and Gait Speed in Chinese Older Adults: Longitudinal Observational Study. JMIR Public Health Surveill 2023; 9:e44274. [PMID: 36917163 PMCID: PMC10131755 DOI: 10.2196/44274] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/08/2023] [Accepted: 01/19/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Cognitive and gait speed decline are common conditions in older adults and are often associated with future adverse consequences. Although an association between cognitive function and gait speed has been demonstrated, its temporal sequence remains unclear, especially in older Chinese adults. Clarifying this could help identify interventions to improve public health in older adults. OBJECTIVE This study aims to examine the longitudinal reciprocal association between gait speed and cognitive function and the possible temporal sequence of changes in both factors in a national longitudinal cohort. METHODS Data were derived from 2 waves (2011 baseline and 2015 follow-up) of the China Health and Retirement Longitudinal Study (CHARLS). Participants 60 years or older, without dementia or Parkinson disease at baseline, and with completed data on gait speed and cognition at both baseline and follow-up were included. Usual gait speed was measured over two 2.5-m walks. Mental intactness and episodic memory were used to assess global cognitive function. Cross-lagged panel models and linear mixed-effects models were used to examine the association between cognition and gait speed over time. Standardized coefficients were reported. RESULTS A total of 3009 participants (mean age 66.4 years, SD 5.4 years; 1422/3009, 47.26%, female participants) were eligible for inclusion in our analyses. Cross-lagged panel analyses revealed that after accounting for baseline gait speed, cognition, and potential confounders, baseline global cognition (β=.117, 95% CI 0.082-0.152; P<.001), mental intactness (β=.082, 95% CI 0.047-0.118; P<.001), and episodic memory (β=.102, 95% CI 0.067-0.137; P<.001) were associated with subsequent gait speed. Simultaneously, baseline gait speed was also associated with subsequent global cognition (β=.056, 95% CI 0.024-0.087; P=.001), mental intactness (β=.039, 95% CI 0.008-0.069; P=.01), and episodic memory (β=.057, 95% CI 0.023-0.092; P=.001). The comparison of standardized cross-lagged coefficients suggested that the effect size of baseline global cognition on subsequent gait speed was significantly larger than the reverse effect (χ12=6.50, P for difference=.01). However, the effects of both mental intactness and episodic memory on subsequent gait speed were not significantly stronger than those of the reverse pathway (χ12=3.33, P for difference=.07 and χ12=3.21, P for difference=.07). Linear mixed-effects analyses further supported these bidirectional relationships, revealing that lower baseline cognitive scores predicted steeper declines in gait speed trajectory, and slower baseline gait speed predicted more declines in cognitive trajectory over time. CONCLUSIONS There is a longitudinal bidirectional association between usual gait speed and both global cognitive function and specific domains of mental intactness and episodic memory among Chinese older adults. Baseline global cognition is likely to have a stronger association with subsequent gait speed than the reverse pathway. This interlinkage is noteworthy and may have implications for public health. Maintaining normal cognitive function may be an important interventional strategy for mitigating age-related gait speed reduction.
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Affiliation(s)
- Haibin Li
- Department of Cardiac Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.,Heart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Jiajia Zhang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xinye Zou
- Department of Education, University of Cambridge, Cambridge, United Kingdom
| | - Xiuqin Jia
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Deqiang Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Wuxiang Xie
- Peking University Clinical Research Institute, Peking University First Hospital, Beijing, China
| | - Qi Yang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.,Beijing Laboratory for Cardiovascular Precision Medicine, Beijing, China.,Key Laboratory of Medical Engineering for Cardiovascular Disease, Ministry of Education, Beijing, China
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Zhao Y, Yang X, Wu Y, Huang H, Hu F, Zhang M, Sun L, Hu D. Association of triglyceride-glucose index and its 6-year change with risk of hypertension: A prospective cohort study. Nutr Metab Cardiovasc Dis 2023; 33:568-576. [PMID: 36642606 DOI: 10.1016/j.numecd.2022.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 12/02/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND AIM We aimed to investigate the association of triglyceride-glucose (TyG) index and its dynamic change with risk of hypertension in rural Chinese and, further, to explore whether the TyG index mediates the obesity-related hypertension. METHODS AND RESULTS A prospective cohort study, including 10,309 subjects without hypertension at baseline, was conducted in 2007-2008 and followed up in 2013-2014. TyG index was calculated as Ln[fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Logistic regression model was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). Mediation analysis was performed to examine the contribution of the TyG index to the association of obesity-hypertension incidence. During a median follow-up of 6 years, 2073 subjects developed hypertension. In multivariate logistic model adjusted for age, sex, alcohol drinking, smoking, physical activity and education, monthly income, family history of hypertension, TC, and HDL-C, the risk of hypertension was 1.14 (1.07-1.22) for per-SD increase in TyG. After additional controlling for obesity, this association was nonsignificant (1.06, 0.99-1.13) and (1.05, 0.99-1.13) for BMI and WC, respectively. Increasing trends were found for hypertension incidence as the TyG change increased, with or without adjustment for obesity (all Ptrend < 0.05). With per-SD increment in TyG change, the risks of hypertension incidence were 1.14 (1.07-1.22) for absolute TyG change, and 1.15 (1.08-1.22) for relative TyG change in multivariate logistic model; the results were significant after further adjustment for BMI or WC, respectively. The TyG index partially mediated the obesity-incident hypertension association: 6.84% for BMI and 6.68% for WC, respectively. CONCLUSIONS Elevated TyG index and its dynamic change were positively associated with risk of incident hypertension in rural Chinese population, and the TyG index may play a partially mediating role in obesity-related incident hypertension.
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Affiliation(s)
- Yang Zhao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xingjin Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yuying Wu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Hao Huang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Fulan Hu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Ming Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Liang Sun
- Department of Social Medicine and Health Service Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
| | - Dongsheng Hu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
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Liu L, Wei J, Wang Y, Feng Q, Guo S, Liu G, Dong J, Jiang L, Li Q, Nie J, Yang J. Effect of Club cell secretory proteins on the association of tobacco smoke and PAH co-exposure with lung function decline: A longitudinal observation of Chinese coke oven workers. Int J Hyg Environ Health 2023; 247:114058. [PMID: 36334377 DOI: 10.1016/j.ijheh.2022.114058] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/18/2022] [Accepted: 10/22/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Exposure to polycyclic aromatic hydrocarbons (PAH) and tobacco smoke is associated with epithelial damage and reduced lung function. Club cell secretory protein (CC16) is a known biomarker for lung epithelial cells. However, the potential relationships between PAH and tobacco smoke exposure, CC16 levels, and reduced lung function remain unclear. OBJECTIVES This longitudinal study aimed to explore the potential role of CC16 in the association of tobacco smoke and PAH co-exposure with lung function. METHODS We enrolled 313 workers from a coking plant in China in 2014 and followed them up in 2019. The concentrations of PAH and nicotine metabolites in urine were determined using high-performance liquid chromatography (HPLC) with a fluorescence detector and HPLC-tandem mass spectrometry, respectively. The plasma CC16 concentration was determined using an enzyme-linked immunosorbent assay. RESULTS An analysis of the generalized estimating equation showed that each 1-unit increase in log-transformation of the last tertile of trans-3'-hydroxycotinine (3HC) was associated with a 3.30 ng/ml decrease in CC16. Restricted cubic spline analysis revealed a significant nonlinear dose-effect association between cotinine (COT) and CC16 (Pnonlinear = 0.018). In the low- CC16 subgroup, we found a significant association between total nicotine metabolites and forced vital capacity (FVC%) (β: 1.45, 95% CI: 2.87, -0.03), and the associations of nicotine (NIC), COT, and 3HC with FVC% were all of marginal significance. High levels of total hydroxyl polycyclic aromatic hydrocarbons (ΣOH-PAH) and NIC in the urine had an interactive effect on the decline of CC16 (P < 0.05). Cross-lagged panel analysis indicated that the decrease in CC16 preceded the decrease in FVC%. CC16 mediated the association between elevated nicotine metabolites and decreased FVC% in the low- CC16 subgroup. CONCLUSIONS CC16 plays an essential role in the association of PAH and tobacco smoke exposure with reduced lung function. Coke oven workers with low plasma CC16 levels are more likely to experience decreased lung function after tobacco smoke exposure.
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Affiliation(s)
- Lu Liu
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China
| | - Jiajun Wei
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China
| | - Yong Wang
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China
| | - Quan Feng
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China
| | - Shugang Guo
- Shanxi Provincial Center for Disease Control and Prevention, China
| | - Gaisheng Liu
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Jun Dong
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Liuquan Jiang
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Qiang Li
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Jisheng Nie
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China
| | - Jin Yang
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China; NHC Key Laboratory of Pneumoconiosis, China.
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Muhammad T, Irshad C, Rajan SI. BMI mediates the association of family medical history with self-reported hypertension and diabetes among older adults: Evidence from baseline wave of the longitudinal aging study in India. SSM Popul Health 2022; 19:101175. [PMID: 35898561 PMCID: PMC9310107 DOI: 10.1016/j.ssmph.2022.101175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/14/2022] [Accepted: 07/14/2022] [Indexed: 12/09/2022] Open
Abstract
Background This study explored the association between family history of hypertension and diabetes with their diagnosis among older Indian adults. The study further examined the role of body mass index (BMI) as a potential mediator in these associations. Methods Data from the Longitudinal Ageing Study in India (LASI, 2017-18), wave-1 were used. The sample for the study included 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis has been conducted to assess the prevalence of self-reported hypertension and diabetes. Further, multivariable logistic regression models were used to test the research hypotheses of this study. The Karlson-Holm-Breen (KHB) mediation analysis was conducted to recover the direct and indirect effects of BMI in the association of family medical history and diagnosis of hypertension and diabetes. Results A proportion of 32.70% of older adults were diagnosed with hypertension and 14.23% of older adults were diagnosed with diabetes. A proportion of 19.48% and 14.69% of older adults had a family history of hypertension and diabetes, respectively. Also, 16.57% and 5.53% of older adults were overweight and obese, respectively in the current study. Older adults who had family history of hypertension had higher odds of being diagnosed with hypertension [aOR: 2.23, CI: 2.07-2.39] than those who had no such family history. This association was mediated by BMI (percent mediated: 6.31%). Similarly, older adults who had family history of diabetes had higher odds of being diagnosed with diabetes [aOR: 2.63, CI: 2.41-2.88] than those who had no such family history. This association was mediated by BMI (percent effect mediated: 6.66%). Conclusion The study highlights the relevance of using family medical history data along with information on BMI as potential source for the control and management of hypertension and diabetes among older population.
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Affiliation(s)
- T. Muhammad
- Department of Family & Generations, International Institute for Population Sciences, Mumbai, 400088, India
| | - C.V. Irshad
- Department of Humanities & Social Sciences, Indian Institute of Technology, Madras, 600036, India
| | - S. Irudaya Rajan
- The International Institute of Migration and Development, Thiruvananthapuram, 695011, India
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Yu W, Zhou G, Fan B, Gao C, Li C, Wei M, Lv J, He L, Feng G, Zhang T. Temporal sequence of blood lipids and insulin resistance in perimenopausal women: the study of women's health across the nation. BMJ Open Diabetes Res Care 2022; 10:e002653. [PMID: 35351687 PMCID: PMC8966521 DOI: 10.1136/bmjdrc-2021-002653] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 03/13/2022] [Indexed: 11/05/2022] Open
Abstract
INTRODUCTION To explore the temporal relationship between blood lipids and insulin resistance in perimenopausal women. RESEARCH DESIGN AND METHODS The longitudinal cohort consisted of 1386 women (mean age 46.4 years at baseline) in the Study of Women's Health Across the Nation. Exploratory factor analysis was used to identify appropriate latent factors of lipids (total cholesterol (TC); triglyceride (TG); high-density lipoprotein cholesterol (HDL-C); low-density lipoprotein cholesterol (LDL-C); lipoprotein A-I (LpA-I); apolipoprotein A-I (ApoA-I); apolipoprotein B (ApoB)). Cross-lagged path analysis was used to explore the temporal sequence of blood lipids and homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS Three latent lipid factors were defined as: the TG factor, the cholesterol transport factor (CT), including TC, LDL-C, and ApoB; the reverse cholesterol transport factor (RCT), including HDL-C, LpA-I, and ApoA-I. The cumulative variance contribution rate of the three factors was 86.3%. The synchronous correlations between baseline TG, RCT, CT, and baseline HOMA-IR were 0.284, -0.174, and 0.112 (p<0.05 for all). After adjusting for age, race, smoking, drinking, body mass index, and follow-up years, the path coefficients of TG→HOMA-IR (0.073, p=0.004), and HOMA-IR→TG (0.057, p=0.006) suggested a bidirectional relationship between TG and HOMA-IR. The path coefficients of RCT→HOMA-IR (-0.091, P < 0.001) and HOMA-IR→RCT (-0.058, p=0.002) were also significant, but the path coefficients of CT→HOMA-IR (0.031, p=0.206) and HOMA-IR→CT (-0.028, p=0.113) were not. The sensitivity analyses showed consistent results. CONCLUSIONS These findings provide evidence that TG and the reverse cholesterol transport-related lipids are related with insulin resistance bidirectionally, while there is no temporal relationship between the cholesterol transport factor and insulin resistance.
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Affiliation(s)
- Wenhao Yu
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Guangshuai Zhou
- Department of Human Resources, Zibo Central Hospital, Zibo, Shandong, China
| | - Bingbing Fan
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Chaonan Gao
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Chunxia Li
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Mengke Wei
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Jiali Lv
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Li He
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Guoshuang Feng
- Big Data and Engineering Research Center, Beijing Children's Hospital Capital Medical University, Beijing, China
| | - Tao Zhang
- Department of Biostatistics, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Liu L, Feng Q, Wang Y, Zhao X, Guo S, Guo L, Liu G, Jiang L, Li Q, Pan B, Nie J, Yang J. Interaction of polycyclic aromatic hydrocarbon exposure and high-fasting plasma glucose on lung function decline in coke oven workers: a cross-lagged panel analysis. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2022; 90:103811. [PMID: 35038546 DOI: 10.1016/j.etap.2022.103811] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/21/2021] [Accepted: 01/11/2022] [Indexed: 06/14/2023]
Abstract
Individuals with abnormal fasting plasma glucose (FPG) may be more susceptible to lung diseases associated with environmental pollutants. A cross-sectional survey of 629 workers in 2017 and a panel study of 304 workers from 2014 to 2019 were performed in China. The results showed that elevated total hydroxylated polycyclic aromatic hydrocarbon (ΣOH-PAH) concentration was associated with lower the percentage of predicted forced vital capacity (FVC%) among high-FPG workers (β for the cross-sectional analysis: -1.78%, 95%CI: -2.92%, -0.64%; β for the panel study: -1.10%, 95%CI: -2.19%, -0.02%). The absolute value of the cross-lagged path coefficient from FPG to FVC% (β2 = -0.096) was significantly greater than that from FVC% to FPG (β1 = 0.037). Our results suggest that FPG abnormalities may precede the lung function decline induced by PAH exposure and that high-FPG and high ΣOH-PAH levels have an interactive effect on lung function decline.
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Affiliation(s)
- Lu Liu
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Quan Feng
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Yong Wang
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Xinyu Zhao
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Shugang Guo
- Shanxi Provincial Center for Disease Control and Prevention, China
| | - Lan Guo
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Gaisheng Liu
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Liuquan Jiang
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Qiang Li
- Center of Occupational Disease Prevention, Xishan Coal Electricity (Group) Co., Ltd, China
| | - Baolong Pan
- General Hospital of Taiyuan Iron & Steel (Group) Co., Ltd, China
| | - Jisheng Nie
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China
| | - Jin Yang
- Department of Occupational Health, School of Public Health, Shanxi Medical University, China.
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19
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Gao X, Li S, Dong S, Li J, Yan Y, Zhang T, Chen W. Association Between Body Weight and Telomere Length Is Predominantly Mediated Through C-Reactive Protein. J Clin Endocrinol Metab 2021; 106:e4634-e4640. [PMID: 34153093 DOI: 10.1210/clinem/dgab455] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Both obesity and inflammation are related to accelerated aging. It is not yet known whether inflammation mediates the effects of obesity on aging. OBJECTIVE This work aims to dissect the direct effect of body mass index (BMI) and its indirect effect through C-reactive protein (CRP) on leukocyte telomere length (LTL) to determine the mediation effect of CRP on the BMI-LTL association. METHODS The study cohort included 5451 adults (1404 Mexican American, 3114 White, and 933 Black individuals; 53.5% male; mean age = 49.2 years) from the 1999 to 2002 National Health and Nutrition Examination Survey. General mediation models were used to examine the mediation effect of CRP on the BMI-LTL association. RESULTS After adjusting for age, race, sex, physical activity, alcohol use, and serum cotinine, the total effect of BMI on LTL was significant (standardized regression coefficient, β = -.054, P < .001) without CRP included in the model. With inclusion of CRP in the model, the indirect effect of BMI on LTL through CRP was estimated at β equal to -.023 (P < .001), and the direct effect of BMI on LTL in its absolute value decreased to β equal to -.031 (P = .025). The mediation effect of CRP was estimated at 42.6%. The mediation model parameters did not differ significantly between race and sex groups. CONCLUSION These results suggest that the inverse BMI-LTL association is partly mediated by obesity-induced inflammation. The significant direct effect of BMI on LTL with removal of the mediation effect through CRP indicates that obesity is associated with LTL attrition also through other noninflammatory mechanisms.
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Affiliation(s)
- Xiao Gao
- The Second Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150001, China
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Hospitals and Clinics of Minnesota, Minneapolis, Minnesota 55404, USA
| | - Shiqiu Dong
- Department of Clinical Medicine, Heilongjiang Nursing College, Harbin, Heilongjiang 150080, China
| | - Jiaqi Li
- The Second Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150001, China
| | - Yinkun Yan
- Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, Shandong 250012, China
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112, USA
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Wang L, Liu X, Wei D, Kang N, Nie L, Liu P, Fan K, Zhang L, Hou J, Li X, Xu S, Jing T, Li W, Wang C, Mao Z, Huo W. The mediation role of SOCS3 methylation in the effect of serum testosterone on type 2 diabetes. J Diabetes 2021; 13:701-712. [PMID: 33576141 DOI: 10.1111/1753-0407.13167] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 01/21/2021] [Accepted: 02/03/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Previous studies reported that testosterone and DNA methylation of suppressor of cytokine signaling-3 (SOCS3) were associated with type 2 diabetes (T2D). Testosterone affects SOCS3 gene expression. Therefore, we aimed to investigate how the SOCS3 methylation mediates the relationship between testosterone and T2D among Chinese rural adults. METHODS A case-control study comprised 365 T2D patients and 651 controls was conducted. Liquid chromatography-tandem mass spectrometry and MethylTarget were used to determine the levels of serum testosterone and DNA methylation of SOCS3 gene, respectively. The odds ratio (OR) of testosterone or SOCS3 methylation for T2D was calculated using logistic regression models, and β value of testosterone for SOCS3 methylation was evaluated by linear regression models. Furthermore, through mediation analysis the mediating effect of SOCS3 methylation on the association of testosterone with T2D was estimated. RESULTS After adjusting for multiple variables, the protective effect of testosterone on T2D was found in men (OR = 0.61, 95% confidence interval [CI]: 0.47-0.80), and the methylation of Chr17:76356190 or Chr17:76356199 was negatively related to T2D in both men and women. Moreover, testosterone was positively associated with Chr17:76356190 methylation in men and Chr17:76356199 methylation in women (both P < .05). The mediation analysis showed that the Chr17:76356190 methylation partly mediated effect of testosterone on T2D in men was approximately 8.2%. CONCLUSIONS High levels of serum testosterone in men and Chr17:76356190 and Chr17:76356199 (SOCS3) methylation were related to a lower prevalent T2D. In addition, Chr17:76356190 methylation partially mediated the effect of testosterone on T2D in Chinese rural men.
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Affiliation(s)
- Lulu Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaotiao Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Dandan Wei
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Luting Nie
- Department of Occupational and Environmental Health Sciences, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Pengling Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Keliang Fan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xing Li
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Shunqing Xu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Jing
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenjie Li
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wenqian Huo
- Department of Occupational and Environmental Health Sciences, College of Public Health, Zhengzhou University, Zhengzhou, China
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21
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Dong SS, Zhang K, Guo Y, Ding JM, Rong Y, Feng JC, Yao S, Hao RH, Jiang F, Chen JB, Wu H, Chen XF, Yang TL. Phenome-wide investigation of the causal associations between childhood BMI and adult trait outcomes: a two-sample Mendelian randomization study. Genome Med 2021; 13:48. [PMID: 33771188 PMCID: PMC8004431 DOI: 10.1186/s13073-021-00865-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 03/11/2021] [Indexed: 12/28/2022] Open
Abstract
Background Childhood obesity is reported to be associated with the risk of many diseases in adulthood. However, observational studies cannot fully account for confounding factors. We aimed to systematically assess the causal associations between childhood body mass index (BMI) and various adult traits/diseases using two-sample Mendelian randomization (MR). Methods After data filtering, 263 adult traits genetically correlated with childhood BMI (P < 0.05) were subjected to MR analyses. Inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods were used to estimate the causal effects. Multivariable MR analysis was performed to test whether the effects of childhood BMI on adult traits are independent from adult BMI. Results We identified potential causal effects of childhood obesity on 60 adult traits (27 disease-related traits, 27 lifestyle factors, and 6 other traits). Higher childhood BMI was associated with a reduced overall health rating (β = − 0.10, 95% CI − 0.13 to − 0.07, P = 6.26 × 10−11). Specifically, higher childhood BMI was associated with increased odds of coronary artery disease (OR = 1.09, 95% CI 1.06 to 1.11, P = 4.28 × 10−11), essential hypertension (OR = 1.12, 95% CI 1.08 to 1.16, P = 1.27 × 10−11), type 2 diabetes (OR = 1.36, 95% CI 1.30 to 1.43, P = 1.57 × 10−34), and arthrosis (OR = 1.09, 95% CI 1.06 to 1.12, P = 8.80 × 10−9). However, after accounting for adult BMI, the detrimental effects of childhood BMI on disease-related traits were no longer present (P > 0.05). For dietary habits, different from conventional understanding, we found that higher childhood BMI was associated with low calorie density food intake. However, this association might be specific to the UK Biobank population. Conclusions In summary, we provided a phenome-wide view of the effects of childhood BMI on adult traits. Multivariable MR analysis suggested that the associations between childhood BMI and increased risks of diseases in adulthood are likely attributed to individuals remaining obese in later life. Therefore, ensuring that childhood obesity does not persist into later life might be useful for reducing the detrimental effects of childhood obesity on adult diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00865-3.
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Affiliation(s)
- Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Kun Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Jing-Miao Ding
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yu Rong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Jun-Cheng Feng
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Shi Yao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Ruo-Han Hao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Feng Jiang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Jia-Bin Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Hao Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China. .,National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China.
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22
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Xu C, Zhou G, Zhao M, Zhang X, Fang L, Guan Q, Zhang H, Gao L, Zhang T, Zhao J. Bidirectional temporal relationship between obesity and hyperinsulinemia: longitudinal observation from a Chinese cohort. BMJ Open Diabetes Res Care 2021; 9:9/1/e002059. [PMID: 33632707 PMCID: PMC7908912 DOI: 10.1136/bmjdrc-2020-002059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 01/28/2021] [Accepted: 02/07/2021] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION Although obesity and hyperinsulinemia are closely intercorrelated, their temporal sequence is still uncertain. This study aims to investigate the temporal relationship patterns between obesity measures and hyperinsulinemia in Chinese adults. RESEARCH DESIGN AND METHODS The longitudinal cohort consisted of 2493 participants (860 males and 1633 female, mean age 56.71 years at follow-up) for whom measurements of obesity and hyperinsulinemia measures were collected twice between 2011 and 2014, with an average follow-up time of 3 years. Cross-lagged panel analysis was used to examine the temporal relationship between obesity measures (body mass index (BMI); waist circumference (WC); hip circumference (HC); waist-to-hip ratio (WHR)) and hyperinsulinemia (insulin, homeostasis model assessment of insulin resistance (HOMA-IR), or homeostasis model assessment of beta cell function (HOMA-%β)). RESULTS After the adjustment of age, sex, smoking, drinking and follow-up years, in the BMI-insulin model, the path coefficient (β2=0.229; p<0.001) of baseline BMI to follow-up insulin was significantly greater than the path coefficient (β1=0.073; p<0.001) of baseline insulin to follow-up BMI (p<0.001 for β2>β1). In the WHR-insulin model, the path coefficient (β1=0.152; p<0.001) of baseline insulin to follow-up WHR was significantly greater than the path coefficient (β2=0.077; p<0.001) of baseline WHR to follow-up insulin (p=0.007 for β1>β2). In the WC/HC-insulin model, the path coefficients of baseline insulin to follow-up WC or HC (β1s) were also greater than the path coefficients of baseline WC or HC to follow-up insulin (β2s), but the difference between β1s and β2s were not significant. The similar temporal patterns were founded between obesity measures with HOMA-IR or HOMA-%β. CONCLUSIONS These findings indicate that there is a bidirectional relationship between obesity and hyperinsulinemia, and abdominal obesity measures are more sensitive to hyperinsulinemia measures than BMI.
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Affiliation(s)
- Chao Xu
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Guangshuai Zhou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Quality Management Office, Zibo Central Hospital, Zibo, China
| | - Meng Zhao
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Xu Zhang
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Li Fang
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Qingbo Guan
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Haiqing Zhang
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
| | - Ling Gao
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
- Scientific Center, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jiajun Zhao
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Endocrinology, Shandong Academy of Clinical Medicine, Jinan, China
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China
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23
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Azegami T, Uchida K, Tokumura M, Mori M. Blood Pressure Tracking From Childhood to Adulthood. Front Pediatr 2021; 9:785356. [PMID: 34869128 PMCID: PMC8634726 DOI: 10.3389/fped.2021.785356] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 10/26/2021] [Indexed: 11/13/2022] Open
Abstract
Hypertension is the most common non-communicable disease among adults and is the most important modifiable risk factor for premature cardiovascular disease. The increasing worldwide burden of hypertension is a major global health issue. Early prevention with lifestyle modification or pharmaceutical treatment reduces the incidence of hypertension and the risk of subsequent cardiovascular disease. Therefore, identification of young persons at risk for hypertension has the obvious benefit of providing a chance for early intervention. Previous studies have demonstrated the positive association of elevated childhood blood pressure with hypertension in adulthood. Accumulated evidence also indicates the possibility that elevated pediatric blood pressure is associated with increased risk of future cardiovascular disease. In this article, we review the tracking of blood pressure from childhood to adulthood and emphasize the importance of pediatric blood pressure monitoring and control for predicting and preventing adult hypertension and cardiovascular disease.
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24
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Vogelezang S, Bradfield JP, Ahluwalia TS, Curtin JA, Lakka TA, Grarup N, Scholz M, van der Most PJ, Monnereau C, Stergiakouli E, Heiskala A, Horikoshi M, Fedko IO, Vilor-Tejedor N, Cousminer DL, Standl M, Wang CA, Viikari J, Geller F, Íñiguez C, Pitkänen N, Chesi A, Bacelis J, Yengo L, Torrent M, Ntalla I, Helgeland Ø, Selzam S, Vonk JM, Zafarmand MH, Heude B, Farooqi IS, Alyass A, Beaumont RN, Have CT, Rzehak P, Bilbao JR, Schnurr TM, Barroso I, Bønnelykke K, Beilin LJ, Carstensen L, Charles MA, Chawes B, Clément K, Closa-Monasterolo R, Custovic A, Eriksson JG, Escribano J, Groen-Blokhuis M, Grote V, Gruszfeld D, Hakonarson H, Hansen T, Hattersley AT, Hollensted M, Hottenga JJ, Hyppönen E, Johansson S, Joro R, Kähönen M, Karhunen V, Kiess W, Knight BA, Koletzko B, Kühnapfel A, Landgraf K, Langhendries JP, Lehtimäki T, Leinonen JT, Li A, Lindi V, Lowry E, Bustamante M, Medina-Gomez C, Melbye M, Michaelsen KF, Morgen CS, Mori TA, Nielsen TRH, Niinikoski H, Oldehinkel AJ, Pahkala K, Panoutsopoulou K, Pedersen O, Pennell CE, Power C, Reijneveld SA, Rivadeneira F, Simpson A, Sly PD, Stokholm J, Teo KK, Thiering E, Timpson NJ, Uitterlinden AG, van Beijsterveldt CEM, van Schaik BDC, Vaudel M, Verduci E, Vinding RK, Vogel M, Zeggini E, Sebert S, Lind MV, Brown CD, Santa-Marina L, Reischl E, Frithioff-Bøjsøe C, Meyre D, Wheeler E, Ong K, Nohr EA, Vrijkotte TGM, Koppelman GH, Plomin R, Njølstad PR, Dedoussis GD, Froguel P, Sørensen TIA, Jacobsson B, Freathy RM, Zemel BS, Raitakari O, Vrijheid M, Feenstra B, Lyytikäinen LP, Snieder H, Kirsten H, Holt PG, Heinrich J, Widén E, Sunyer J, Boomsma DI, Järvelin MR, Körner A, Davey Smith G, Holm JC, Atalay M, Murray C, Bisgaard H, McCarthy MI, Jaddoe VWV, Grant SFA, Felix JF. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet 2020; 16:e1008718. [PMID: 33045005 PMCID: PMC7581004 DOI: 10.1371/journal.pgen.1008718] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 10/22/2020] [Accepted: 03/16/2020] [Indexed: 01/22/2023] Open
Abstract
The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.
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Affiliation(s)
- Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jonathan P. Bradfield
- Quantinuum Research LLC, San Diego, California, United States of America
- Center for Applied Genomics, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Tarunveer S. Ahluwalia
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - John A. Curtin
- Division of Infection Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Timo A. Lakka
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Claire Monnereau
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Evie Stergiakouli
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- School of Oral and Dental Sciences, University of Bristol, Bristol, United Kingdom
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Momoko Horikoshi
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Iryna O. Fedko
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Natalia Vilor-Tejedor
- ISGlobal, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- BarcelonaBeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Diana L. Cousminer
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - Carol A. Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, Australia
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Carmen Íñiguez
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Statistics and Computational Research–Universitat de València, València, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, València, Spain
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Alessandra Chesi
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Jonas Bacelis
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Obstetrics and Gynecology, Gothenburg Sweden
| | - Loic Yengo
- University Lille, Centre National de la Recherche Scientifique, Institut Pasteur de Lille, UMR 8199—European Genomic Institute for Diabetes, Lille, France
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Maties Torrent
- Area de Salut de Menorca ib-salut, Menorca, Spain
- Institut d'Investigacio Sanitaria Illes Balears (IdISBa), Palma de Mallorca, Spain
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Øyvind Helgeland
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Saskia Selzam
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Judith M. Vonk
- Department of Epidemiology, GRIAC (Groningen Research Institute for Asthma and COPD), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Mohammed H. Zafarmand
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Department of Obstetrics & Gynecology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Barbara Heude
- Université de Paris, CRESS, INSERM, INRA, Paris, France
| | - Ismaa Sadaf Farooqi
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Robin N. Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom
| | - Christian T. Have
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Jose Ramon Bilbao
- University of the Basque Country (UPV/EHU), Leioa, Spain
- Biocrues-Bizkaia Health Research Institute, Barakaldo, Spain
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Spain
| | - Theresia M. Schnurr
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Inês Barroso
- Wellcome Sanger Institute, Cambridge, United Kingdom
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Lawrence J. Beilin
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Lisbeth Carstensen
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | | | - Bo Chawes
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Karine Clément
- Nutrition and Obesities; systemic approaches research unit, Sorbonne University, INSERM, Pitie- Salpêtrière Hospital, Assistance Publique hôpital de Paris, Paris, France
| | - Ricardo Closa-Monasterolo
- Pediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Joaquin Escribano
- Pediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Maria Groen-Blokhuis
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Dariusz Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Andrew T. Hattersley
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom
- NIHR Exeter Clinical Research Facility, College of Medicine and Health, University of Exeter, and Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Danish Diabetes Academy, Odense, Denmark
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Stefan Johansson
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Raimo Joro
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, United Kingdom
| | - Wieland Kiess
- Center for Pediatric Research, University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
| | - Bridget A. Knight
- NIHR Exeter Clinical Research Facility, College of Medicine and Health, University of Exeter, and Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Andreas Kühnapfel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Kathrin Landgraf
- Center for Pediatric Research, University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jaakko T. Leinonen
- Institute For Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
| | - Aihuali Li
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Virpi Lindi
- University of Eastern Finland Library Kuopio, Kuopio, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu University Hospital, Oulu, Finland
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carolina Medina-Gomez
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Medicine, Stanford School of Medicine, Stanford, California, United States of America
| | - Kim F. Michaelsen
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Camilla S. Morgen
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- National Insitute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Trevor A. Mori
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Tenna R. H. Nielsen
- Department of Pediatrics, Hvidovre Hospital, Hvidovre, Denmark
- The Children’s Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Harri Niinikoski
- Department of Physiology, University of Turku, Turku, Finland
- Department of Pediatrics, University of Turku, Turku, Finland
| | - Albertine J. Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center, Groningen, the Netherlands
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland
| | - Kalliope Panoutsopoulou
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Craig E. Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, Australia
| | - Christine Power
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Sijmen A. Reijneveld
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Angela Simpson
- Division of Infection Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Peter D. Sly
- Child Health Research Centre, University of Queensland, Brisbane, Australia
- World Health Organization, WHO Collaborating Centre for Children’s Health and Environment, Brisbane, Queensland, Australia
| | - Jakob Stokholm
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Kook K. Teo
- Department of Medicine, McMaster University, Hamilton, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging NCHA), Leiden, the Netherlands
| | | | - Barbera D. C. van Schaik
- Bioinformatics Laboratory, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Marc Vaudel
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Elvira Verduci
- Department of Pediatrics, San Paolo Hospital, University of Milan, Milan, Italy
| | - Rebecca K. Vinding
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Mandy Vogel
- Center for Pediatric Research, University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
- Institute of Translational Genomics, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu University Hospital, Oulu, Finland
- Section of Genomics of Common Disease, Department of Medicine, Imperial College London, London, United Kingdom
| | - Mads V. Lind
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Christopher D. Brown
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Loreto Santa-Marina
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiologia y Salud Publica-CIBERESP), Barcelona, Spain
- Biodonostia Health Research Institute, San Sebastian, Spain
- Subdirección Salud Pública de Gipuzkoa, San Sebastian, Spain
| | - Eva Reischl
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen, Munich, Germany
| | - Christine Frithioff-Bøjsøe
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children’s Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen N, Denmark
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Eleanor Wheeler
- Wellcome Sanger Institute, Cambridge, United Kingdom
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Ken Ong
- Medical Research Council Epidemiology Unit & Department of Paediatrics, University of Cambridge, Addenbrooke’s Hospital, Cambridge, England
| | - Ellen A. Nohr
- Research Unit for Gynaecology and Obstetrics, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Tanja G. M. Vrijkotte
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Gerard H. Koppelman
- University Medical Center Groningen, University of Groningen, Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, the Netherlands
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Pål R. Njølstad
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics and Adolescents, Haukeland University Hospital, Bergen, Norway
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
| | - George D. Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Philippe Froguel
- University Lille, Centre National de la Recherche Scientifique, Institut Pasteur de Lille, UMR 8199—European Genomic Institute for Diabetes, Lille, France
- Section of Genomics of Common Disease, Department of Medicine, Imperial College London, London, United Kingdom
| | - Thorkild I. A. Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Obstetrics and Gynecology, Gothenburg Sweden
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Rachel M. Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Babette S. Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
- Division of Gastroenterology, Hepatology and Nutrition, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Patrick G. Holt
- Telethon Kids Institute, The University of Western Australia, Perth, Western Australia, Australia
| | - Joachim Heinrich
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Inner City Clinic, University Hospital Munich, Ludwig-Maximilians-Universität of Munich, Munich, Germany
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Elisabeth Widén
- Institute For Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health research institute and Amsterdam Reproduction & Development research Institute, Amsterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, United Kingdom
| | - Antje Körner
- Center for Pediatric Research, University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children’s Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen N, Denmark
| | - Mustafa Atalay
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland
| | - Clare Murray
- Division of Infection Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Hans Bisgaard
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | | | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Struan F. A. Grant
- Center for Applied Genomics, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- * E-mail:
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25
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Liu X, Qian X, Tu R, Mao Z, Huo W, Zhang H, Jiang J, Zhang X, Tian Z, Li Y, Wang C. SOCS3 methylation mediated the effect of sedentary time on type 2 diabetes mellitus: The Henan Rural Cohort study. Nutr Metab Cardiovasc Dis 2020; 30:634-643. [PMID: 31848053 DOI: 10.1016/j.numecd.2019.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 11/09/2019] [Accepted: 11/15/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND AIMS To assess the associations of sedentary time, suppressor of cytokine signaling (SOCS)-3 DNA methylation with type 2 diabetes mellitus (T2DM), and further identify the role of SOCS3 methylation in mediating the association of sedentary time with T2DM in a Chinese rural population. METHODS AND RESULTS A case-control study including 1032 participants from the Henan Rural Cohort study was conducted. Restricted cubic spline analysis and logistic regression model were performed to evaluate the associations between sedentary time, SOCS3 methylation and T2DM. The mediation effect of SOCS3 methylation on the association between sedentary time and T2DM was assessed. Sensitivity analysis was conducted by excluding individuals with diagnosed T2DM. Linear dose-response relationships were found between sedentary time, methylation level of Chr17:76356190 (one novel site on SOCS3) and T2DM. Compared with the first quartile (less than 5 h/d) of sedentary time, the adjusted odds ratio (OR, 95% confidence interval, 95%CI) for those in the third (7-10 h/d) and fourth (≥10 h/d) quartiles were 1.87 (1.22-2.85) and 3.54 (2.14-5.85), respectively. Participants in the fourth quartile of methylation level of Chr17:76356190 had lower risk of T2DM than those in the first quartile (OR (95%CI): 0.23 (0.14-0.38)). Mediation analysis showed 9.66% (6.38%-14.80%) of the association between sedentary time and T2DM was attributable to Chr17:76356190. The comparable effect estimates were observed between sedentary time, methylation level of Chr17:76356190 and undiagnosed T2DM. CONCLUSION Sedentary time and methylation level of Chr17:76356190 were both independently associated with T2DM in the Chinese rural population. Furthermore, Chr17:76356190 appeared to partially mediate the effect of sedentary time on T2DM. CHINESE CLINICAL TRIAL REGISTRATION ChiCTR-OOC-15006699 (URL: http://www.chictr.org.cn/showproj.aspx?proj=11375).
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Affiliation(s)
- Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xinling Qian
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wenqian Huo
- Department of Occupational and Environmental Health Sciences, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Haiqing Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Jingjing Jiang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xia Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhongyan Tian
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yuqian Li
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
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26
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Piri Z, Barzin M, Mahdavi M, Guity K, Azizi F, Hosseinpanah F, Valizadeh M. The role of childhood BMI in predicting early adulthood dysglycemia: Tehran lipid and glucose study. Nutr Metab Cardiovasc Dis 2020; 30:313-319. [PMID: 31744715 DOI: 10.1016/j.numecd.2019.09.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 08/07/2019] [Accepted: 09/19/2019] [Indexed: 11/19/2022]
Abstract
BACKGROUND AND AIM Increased adiposity is associated with insulin resistance and glycemic disturbances. We aimed to determine whether childhood overweight or obesity are independent factors in predicting adulthood dysglycemia (prediabetes or type 2 diabetes). METHODS AND RESULTS In this population-based cohort study, 1290 normoglycemic subjects aged 3-11 years were followed for incidence of dysglycemia. Cox-proportional hazard models were employed to evaluate the association of obesity and overweight with incidence of dysglycemia by adjustments for age, sex, parental risk factors and baseline individual risk factors. The participants, with a mean age of 7.7 ± 2.5 years, were followed for a median of 14.9 years. During follow up, 158 subjects developed dysglycemia (18 type 2 diabetes, 140 prediabetes), contributing to a total cumulative incidence of 24.7%. The unadjusted HR for developing adult dysglycemia were 1.6 (95% CI; 1.0-2.4) and 1.7 (95% CI; 1.0-3.0) in overweight and obese children, respectively. Further adjustments for age, sex, parental risk factors and baseline individual risk factors changed the results in both overweight and obese children. CONCLUSION These findings show that overweight or obesity in childhood have no independent role for developing adulthood dysglycemia.
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Affiliation(s)
- Zahra Piri
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Barzin
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Mahdavi
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farhad Hosseinpanah
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Majid Valizadeh
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Xie Y, Guo R, Li Z, Guo X, Sun G, Sun Z, Zheng J, Sun Y, Zheng L. Temporal relationship between body mass index and triglyceride-glucose index and its impact on the incident of hypertension. Nutr Metab Cardiovasc Dis 2019; 29:1220-1229. [PMID: 31383505 DOI: 10.1016/j.numecd.2019.07.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 05/22/2019] [Accepted: 07/02/2019] [Indexed: 01/03/2023]
Abstract
BACKGROUND AND AIMS Obesity and insulin levels can influence each other by metabolism. However, their temporal sequences and influence on hypertension are generally unknown, especially in Chinese adults. Recently, some scholars have proposed that triglycerides-glucose index (TyG) is an important indicator of insulin resistance. The study aims to describe the relationship between body mass index (BMI) and TyG index and its impact on hypertension. METHODS AND RESULTS A total of 4081 adults (56.33% women) without antihypertensive, hypoglycemic or lipid-lowering medications were selected for the present study. Measurements of BMI and TyG index were obtained twice from 2012 to 2017. Cross-lagged panel analysis was used to describe the temporal sequences between BMI and TyG index, and the effect of their temporal relationship patterns on hypertension was explored through mediation analysis. After adjusting for confounding factors (age, sex, ethnicity et al.), the cross-lagged path coefficient from baseline BMI to follow-up TyG (ρ2 = 0.135, P < 0.001) was significantly greater than the path coefficient from baseline TyG to follow-up BMI (ρ1 = 0.043, P < 0.001), and P < 0.001 for the difference between ρ1 and ρ2. Furthermore, the sensitivity analyses between women and men revealed identical findings. In addition, TyG index mediation effect on BMI-hypertension was estimated to be 38.45% (P < 0.001) in total population, 25.24% in women and 57.35% in men. CONCLUSION These results provided evidence that the temporal relationship between BMI and insulin resistance is reciprocal and a higher BMI precedes hyperinsulinemia in Chinese adults. This relationship plays an essential role in the development of hypertension, while there is a difference between women and men.
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Affiliation(s)
- Yanxia Xie
- Department of Clinical Epidemiology, Library, Department of Health Policy and Hospital Management, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China
| | - Rongrong Guo
- Department of Clinical Epidemiology, Library, Department of Health Policy and Hospital Management, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China
| | - Zhao Li
- Department of Cardiology, The First Affiliated Hospital of China Medical University, 155 Nanjing Street, Heping District, Shenyang, 110001, PR China
| | - Xiaofan Guo
- Department of Cardiology, The First Affiliated Hospital of China Medical University, 155 Nanjing Street, Heping District, Shenyang, 110001, PR China
| | - Guozhe Sun
- Department of Cardiology, The First Affiliated Hospital of China Medical University, 155 Nanjing Street, Heping District, Shenyang, 110001, PR China
| | - Zhaoqing Sun
- Department of Cardiology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China
| | - Jia Zheng
- Department of Clinical Epidemiology, Library, Department of Health Policy and Hospital Management, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China
| | - Yingxian Sun
- Department of Cardiology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China.
| | - Liqiang Zheng
- Department of Clinical Epidemiology, Library, Department of Health Policy and Hospital Management, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, 110004, PR China.
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28
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Wada K, Yamakawa M, Konishi K, Goto Y, Mizuta F, Koda S, Uji T, Tamura T, Nakamura K, Tsuji M, Nagai H, Itakura N, Harada K, Takahara O, Yamanaka H, Nagata C. Associations of Cell Phone Use and Screen Viewing with Overweight in Children. Child Obes 2019; 15:417-425. [PMID: 31298567 DOI: 10.1089/chi.2018.0312] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background: Effects of using mobile devices on childhood obesity have not been well studied. We aimed to ascertain whether cell phone use and screen viewing are associated with excess body weight in a cross-sectional study of Japanese school children. Methods: Subjects were 3141 students, ages 6 to 7 years, who participated in the Hekinan Children's Study conducted during 2011-2015. Participants were asked to submit a parent-administered questionnaire on child and parent demographics, health status, and lifestyles, including cell phone use and screen time. Heights and weights were measured at the schools. Being overweight was defined according to the cutoff point for children specified by the Extended International Obesity Task Force. Among 2596 analytic children, the odds ratios (ORs) for being overweight were estimated according to cell phone use, time spent watching television, and time spent on games and computers using the logistic regression models. Analyses were conducted after adjustments for potential confounders, including dietary intake, physical activities, sleep duration, and quality of sleep. Results: After multivariate adjustments, cell phone users were found to have an OR of 1.74 for being overweight compared with nonusers. Cell phone use of longer duration was associated with higher risk of being overweight (trend p = 0.018). Time spent watching television was positively associated with the risk of being overweight (trend p = 0.003). Conclusions: Just as earlier studies have shown for television viewing, cell phone use might be a risk factor related to being overweight among children.
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Affiliation(s)
- Keiko Wada
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Michiyo Yamakawa
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Kie Konishi
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Yuko Goto
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Fumi Mizuta
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Sachi Koda
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Takahiro Uji
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Takashi Tamura
- Department of Preventive Medicine, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Kozue Nakamura
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan.,Gifu City Healthcare Center, Gifu, Japan
| | - Michiko Tsuji
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan.,Department of Food Science and Nutrition, Nagoya Women's University, Nagoya, Japan
| | | | | | - Kou Harada
- Hekinan Medical Association, Hekinan, Japan
| | | | | | - Chisato Nagata
- Department of Epidemiology and Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
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29
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Nagata C, Wada K, Sahashi Y, Tamura T, Konishi K, Goto Y, Yamakawa M, Koda S, Mizuta F, Uji T, Nakamura K, Tsuji M, Nagai H, Itakura N, Harada K, Takahara O, Yamanaka H. The Hekinan Children's Study: Design and Profile of Participants at Baseline. J Epidemiol 2019; 29:272-277. [PMID: 30344192 PMCID: PMC6556436 DOI: 10.2188/jea.je20180005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 06/24/2018] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The early life environment is now recognized as a key factor contributing to susceptibility to certain diseases in later life. METHODS We initiated a cohort study among school children in 2011 to primarily investigate the associations between lifestyle and environmental factors and some surrogate markers of chronic diseases, such as cardiometabolic risk factors (ie, obesity, high blood pressure, high blood glucose, insulin, or lipids) and cancer risk factors (ie, height and age at menarche). A baseline questionnaire asked for information, including demographic variables, medical history and use of medication, dietary habits, physical activity, sleep habits, and behavioral and emotional problems of children. Follow-up surveys are planned for the fourth grade of elementary school and the first grade of junior high school. At these follow-up surveys, fasting blood samples will be obtained to measure cardiometabolic markers. We also checked the validity of a food frequency questionnaire, which was originally created for 6-year-olds but was modified for use in older children. RESULTS A total of 3,141 first-year students at elementary schools in Hekinan City, Aichi Prefecture, participated in the study. The response rate was 87.4%. The means of age and body mass index were 6.99 (standard deviation, 0.28) years and 15.3 (standard deviation, 1.7) kg/m2, respectively, in the 3,067 Japanese children (1,639 boys and 1,428 girls). CONCLUSIONS This cohort will reveal determinants of cardiometabolic risk factors and cancer risk factors during childhood.
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Affiliation(s)
- Chisato Nagata
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Keiko Wada
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Yukari Sahashi
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Takashi Tamura
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kie Konishi
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Yuko Goto
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Michiyo Yamakawa
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Sachi Koda
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Fumi Mizuta
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Takahiro Uji
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Kozue Nakamura
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
- Department of Food and Nutrition, Gifu City Women’s College, Gifu, Japan
| | - Michiko Tsuji
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
- Department of Food Science and Nutrition, Nagoya Women’s University, Nagoya, Japan
| | | | | | - Kou Harada
- Hekinan Medical Association, Hekinan, Aichi, Japan
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30
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Hypertension Editors' Picks. Hypertension 2019; 73:e67-e82. [PMID: 31030605 DOI: 10.1161/hypertensionaha.119.13143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Tekola-Ayele F, Lee A, Workalemahu T, Sánchez-Pozos K. Shared genetic underpinnings of childhood obesity and adult cardiometabolic diseases. Hum Genomics 2019; 13:17. [PMID: 30947744 PMCID: PMC6449964 DOI: 10.1186/s40246-019-0202-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 03/20/2019] [Indexed: 12/12/2022] Open
Abstract
Background Obesity during childhood can lead to increased risk of adverse cardiometabolic diseases such as type 2 diabetes and coronary artery disease during adult life. Evidence for strong genetic correlations between child and adult body mass index (BMI) suggest the possibility of shared genetic effects. We performed a test for pleiotropy (shared genetics) and functional enrichment of single nucleotide polymorphisms (SNPs) associated with childhood BMI and 15 adult cardiometabolic traits using a unified statistical approach that integrates pleiotropy and functional annotation data. Results Pleiotropic genetic effects were significantly abundant in 13 out of 15 childhood BMI-adult cardiometabolic trait tests (P < 3.3 × 10−3). SNPs associated with both childhood BMI and adult traits were more likely to be functionally deleterious than SNPs associated with neither trait. Genetic variants associated with increased childhood obesity tend to increase risk of cardiometabolic diseases in adulthood. We replicated 39 genetic loci that are known to be associated with childhood BMI and adult traits (coronary artery disease, HDL cholesterol, myocardial infarction, triglycerides, total cholesterol, type 2 diabetes, BMI, waist circumference, and waist-to-hip ratio) in previous genome-wide association studies. We also found a novel association of rs12446632 near GPRC5B, which is highly expressed in adipose tissue and the central nervous system, with adult HDL cholesterol. Conclusions This study found significant pleiotropic genetic effects and enrichment of functional annotations in genetic variants that were jointly associated with childhood obesity and adult cardiometabolic diseases. The findings provide new avenues to disentangle the genetic basis of life course associations between childhood obesity and adult cardiometabolic diseases. Electronic supplementary material The online version of this article (10.1186/s40246-019-0202-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3204, Bethesda, MD, 20892-7004, USA.
| | - Anthony Lee
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3204, Bethesda, MD, 20892-7004, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3204, Bethesda, MD, 20892-7004, USA
| | - Katy Sánchez-Pozos
- Laboratorio de Endocrinologia Molecular, Hospital Juárez de México, Mexico City, Mexico
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Sayon-Orea C, Bes-Rastrollo M, Song M, Hang D, Hu FB, Ruiz-Estigarribia L, Martinez-Gonzalez MA. Body shape trajectories and the incidence of hypertension in a Mediterranean cohort: The sun study. Nutr Metab Cardiovasc Dis 2019; 29:244-253. [PMID: 30745261 DOI: 10.1016/j.numecd.2018.12.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 11/05/2018] [Accepted: 12/14/2018] [Indexed: 12/14/2022]
Abstract
AIMS Our aim was to assess the association between trajectories of body-shape across the first 40 years of life and subsequent development of hypertension in a Mediterranean cohort. METHODS AND RESULTS We used a group-based modeling approach to assess body shape trajectories from age 5 to 40 years, among 7514 participants included in the SUN study (1999-2016), and assessed the subsequent incidence of hypertension. To create the trajectories, we used a censored normal model as a polynomial function of age. Cox models were used to estimates hazard ratios (HR) for hypertension according to body shape trajectories. Identified trajectories were "childhood lean -mid-life increase", "childhood medium-mid-life stable", " childhood heavy -mid-life decrease", and "childhood heavy -mid-life increase" for women; and "childhood lean-mid-life increase", "childhood medium-mid-life stable", "childhood medium -mid-life increase" and "childhood heavy-mid-life stable" for men. After a follow-up of 63,068 person-years, 865 incident cases of hypertension were found. Among women, compared to those in the "childhood medium-mid-life stable" trajectory, those, in the "childhood heavy -mid-life increase" trajectory showed higher risk to develop hypertension [HR = 1.72 (1.17-2.53)]. In men, compared with those in the "childhood medium-mid-life stable" trajectory, those in the "childhood lean and childhood medium -mid-life increase" and the "childhood heavy- mid-life stable" trajectories showed higher subsequent incidence of hypertension [HR = 1.43 (1.11-1.85), HR = 1.52 (1.17-1.97) and HR = 1.56 (1.14-2.14), respectively] after adjusting for potential confounders (including age, lifestyles, dietary intake, personality traits, physical activity and sedentary behaviors). CONCLUSIONS Our results suggest that mid-life increases in body shape or maintaining a heavy body shape during early and middle life in men and childhood heavy-mid-life increase in women is associated with a higher subsequent risk of developing hypertension in this Mediterranean population.
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Affiliation(s)
- C Sayon-Orea
- Department of Preventive Medicine, Complejo Hospitalario de Navarra, Pamplona, Spain; University of Navarra, Department of Preventive Medicine and Public Health, School of Medicine-Clínica Universidad de Navarra, Pamplona, Spain.
| | - M Bes-Rastrollo
- University of Navarra, Department of Preventive Medicine and Public Health, School of Medicine-Clínica Universidad de Navarra, Pamplona, Spain; Centro de Investigacion Biomedica en Red Area de Fisiologia de la Obesidad y la Nutricion (CIBEROBN), Madrid, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - M Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA; Clinical and Translational Epidemiology Unit Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
| | - D Hang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - F B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - L Ruiz-Estigarribia
- University of Navarra, Department of Preventive Medicine and Public Health, School of Medicine-Clínica Universidad de Navarra, Pamplona, Spain
| | - M A Martinez-Gonzalez
- University of Navarra, Department of Preventive Medicine and Public Health, School of Medicine-Clínica Universidad de Navarra, Pamplona, Spain; Centro de Investigacion Biomedica en Red Area de Fisiologia de la Obesidad y la Nutricion (CIBEROBN), Madrid, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Zheng W, Mu J, Chu C, Hu J, Yan Y, Ma Q, Lv Y, Xu X, Wang K, Wang Y, Deng Y, Yan B, Yang R, Yang J, Ren Y, Yuan Z. Association of Blood Pressure Trajectories in Early Life with Subclinical Renal Damage in Middle Age. J Am Soc Nephrol 2018; 29:2835-2846. [PMID: 30420422 DOI: 10.1681/asn.2018030263] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 10/10/2018] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Although high BP is one of the most important factors affecting renal function, whether longitudinal BP trajectories in early life course are associated with renal function damage in later life is unclear. METHODS To investigate the correlation between BP trajectories from childhood to adulthood and renal function in middle age, we used group-based trajectory models to identify BP trajectories in 2430 individuals (aged 6-15 years old at baseline) participating in the ongoing Hanzhong Adolescent Hypertension Cohort. We tested the association between these trajectories and subclinical renal damage in middle age, adjusting for several covariates. RESULTS We identified four distinct systolic BP trajectories among 2430 subjects: low stable, moderate stable, high stable, and moderate increasing on the basis of systolic BP levels at baseline and during the 30-year follow-up period. The urinary albumin-to-creatinine ratio (uACR) was higher in moderate stable, high stable, and moderate increasing groups compared with the low stable group. A total of 228 individuals had subclinical renal disease by 2017. Compared with the low stable trajectory group, the other groups had increasingly greater odds of experiencing subclinical renal disease in middle age. These associations were not altered after adjustment for other covariates, except for in the moderate stable group. Analyzed results were similar for the mean arterial pressure and diastolic BP trajectory groups. CONCLUSIONS Higher BP trajectories were correlated with higher of uACR levels and risk of subclinical renal disease in middle age. Identifying long-term BP trajectories from early age may assist in predicting individuals' renal function in later life.
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Affiliation(s)
- Wenling Zheng
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Jianjun Mu
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China;
| | - Chao Chu
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Jiawen Hu
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Yu Yan
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Qiong Ma
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Yongbo Lv
- Department of Cardiovascular Medicine, Second Affiliated Hospital of Medical College, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - Xianjing Xu
- Department of Cardiovascular Medicine, Henan Province People's Hospital, Zhengzhou, People's Republic of China
| | - Keke Wang
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Yang Wang
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
| | - Ying Deng
- Department of Cardiovascular Medicine, Hanzhong No. 405 Hospital, Hanzhong, People's Republic of China
| | - Bo Yan
- Department of Cardiovascular Medicine, Hanzhong Central Hospital, Hanzhong, People's Republic of China; and
| | - Ruihai Yang
- Institute of Cardiovascular Sciences, Hanzhong People's Hospital, Hanzhong, People's Republic of China
| | - Jun Yang
- Institute of Cardiovascular Sciences, Hanzhong People's Hospital, Hanzhong, People's Republic of China
| | - Yong Ren
- Institute of Cardiovascular Sciences, Hanzhong People's Hospital, Hanzhong, People's Republic of China
| | - Zuyi Yuan
- Department of Cardiovascular Medicine, First Affiliated Hospital of Medical College, Xi'an Jiaotong University and Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, People's Republic of China
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Li Y, Zhang T, Han T, Li S, Bazzano L, He J, Chen W. Impact of cigarette smoking on the relationship between body mass index and insulin: Longitudinal observation from the Bogalusa Heart Study. Diabetes Obes Metab 2018; 20:1578-1584. [PMID: 29446554 PMCID: PMC5999532 DOI: 10.1111/dom.13259] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 02/06/2018] [Accepted: 02/08/2018] [Indexed: 01/19/2023]
Abstract
OBJECTIVES Despite the inverse association between cigarette smoking and body mass index (BMI), it is unknown whether the effect of smoking on insulin is mediated through decreased BMI. This study aims to examine the temporal relationship between BMI and insulin, the impact of smoking on this relationship and the mediation effect of BMI on the association between smoking and insulin levels. METHODS The longitudinal cohort consisted of 1121 adults (807 white and 314 black participants, mean age, 42.0 years at follow-up) for whom BMI and fasting insulin were measured twice, with an average follow-up period of 17.1 years. Cross-lagged panel and mediation analysis models were used to examine the temporal relationship between BMI and insulin, and the mediation effect of BMI on the smoking-insulin association. RESULTS Smoking was inversely associated with insulin (regression coefficient, -0.073; P = .015 at baseline and -0.121; P < .001 at follow-up), adjusting for age, race and gender. After additional adjustment for follow-up periods, the cross-lagged path coefficient from BMI to insulin (β, 0.226; P < .001) was significantly greater than that from insulin to BMI (β, -0.029; P = .208), with P < .001 for the difference. The path coefficient from BMI to insulin was significantly greater in non-smokers (β, 0.273; P < .001) than in smokers (β, 0.122; P = .046), with P = .013 for the difference. The mediation effect of BMI on the smoking-insulin association was estimated at 53.4% (P = .030) at baseline and 58.7% (P < .001) at follow-up. CONCLUSIONS These findings suggest that cigarette smoking has a significant impact on the one-directional relationship from BMI to insulin. The insulin-lowering effect of smoking is predominantly mediated through decreased BMI as the result of smoking.
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Affiliation(s)
- Ying Li
- Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Tianshu Han
- Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Shengxu Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Lydia Bazzano
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Jiang He
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
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Geng T, Smith CE, Li C, Huang T. Childhood BMI and Adult Type 2 Diabetes, Coronary Artery Diseases, Chronic Kidney Disease, and Cardiometabolic Traits: A Mendelian Randomization Analysis. Diabetes Care 2018; 41:1089-1096. [PMID: 29483184 DOI: 10.2337/dc17-2141] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Accepted: 02/04/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To test the causal effect of childhood BMI on adult cardiometabolic diseases using a Mendelian randomization analysis. RESEARCH DESIGN AND METHODS We used 15 single nucleotide polymorphisms as instrumental variables for childhood BMI to test the causal effect of childhood BMI on cardiometabolic diseases using summary-level data from consortia. RESULTS We found that a 1-SD increase in childhood BMI (kg/m2) was associated with an 83% increase in risk of type 2 diabetes (odds ratio [OR] 1.83 [95% CI 1.46, 2.30]; P = 2.5 × 10-7) and a 28% increase in risk of coronary artery disease (CAD) (OR 1.28 [95% CI 1.17, 1.39]; P = 2.1 × 10-8) at the Bonferroni-adjusted level of significance (P < 0.017) in adults. In addition, a 1-SD increase in childhood BMI was associated with a 0.587-SD increase in adulthood BMI (kg/m2), a 0.062-SD increase in hip circumference (cm), a 0.602-SD increase in waist circumference (cm), a 0.111 pmol/L increase in log fasting insulin, a 0.068 increase in log-transformed HOMA of ß-cell function (%), a 0.126 increase in log-transformed HOMA of insulin resistance (%), and a 0.109-SD increase in triglyceride (mg/dL) but a 0.138-SD decrease in HDL (mg/dL) in adults at the Bonferroni-adjusted level of significance (P < 0.0026). CONCLUSIONS A genetic predisposition to higher childhood BMI was associated with increased risk of type 2 diabetes and CAD in adult life. These results provide evidence supportive of a causal association between childhood BMI and these outcomes.
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Affiliation(s)
- Tingting Geng
- Epidemiology Domain, Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Caren E Smith
- Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Changwei Li
- Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA
| | - Tao Huang
- Epidemiology Domain, Saw Swee Hock School of Public Health, National University of Singapore, Singapore .,Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Han T, Meng X, Shan R, Zi T, Li Y, Ma H, Zhao Y, Shi D, Qu R, Guo X, Liu L, Na L, Li Y, Sun C. Temporal relationship between hyperuricemia and obesity, and its association with future risk of type 2 diabetes. Int J Obes (Lond) 2018; 42:1336-1344. [PMID: 29717279 DOI: 10.1038/s41366-018-0074-5] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 02/06/2018] [Accepted: 02/15/2018] [Indexed: 01/11/2023]
Abstract
BACKGROUND/OBJECTIVES Although hyperuricemia and obesity are significantly correlated, their temporal relationship and whether this relationship is associated with future risk of diabetes are largely unknown. This study examined temporal relationship between hyperuricemia and obesity, and its association with future risk of type 2 diabetes. SUBJECTS/METHODS This study examined two longitudinal cohorts totally including 17,044 subjects from China with an average of 6.0 years follow-up. Measurements of body mass index (BMI), waist circumference (WC), percentage of body fat and fasting serum uric acid were obtained at two time points. Cross-lagged panel and mediation analysis were used to examine the temporal relationship between hyperuricemia and obesity, and the association of this temporal relationship with follow-up diabetes. RESULTS In combined data of the two cohorts, the cross-lagged path coefficient (β1 = 0.121; 95% confidence interval (CI): 0.108-0.135) from baseline uric acid to the follow-up BMI was significantly greater than the path coefficient (β2 = 0.055, 95% CI: 0.038-0.072) from baseline BMI to the follow-up uric acid (P = 8.14e-10 for the difference between β1 and β2) with adjustment for covariates. The separate cross-lagged path models of uric acid with WC and percentage of body fat showed temporal patterns similar to that noted for uric acid with BMI. Further, the path coefficient (β1) from baseline uric acid to follow-up BMI in the group with diabetes was significantly greater than without diabetes (P = 0.003 for the difference of β1s in the two groups). BMI partially mediated the association of uric acid with risk of diabetes, and the percentage of mediated-association was estimated at 20.3% (95% CI: 15.7-24.8%). Results of these analyses in the combined data were consistent with those in the two cohorts, respectively. CONCLUSIONS These findings indicated that increased uric acid levels probably associated with obesity and type 2 diabetes, and more definite research is needed to define any role for uric acid in relation to these diseases.
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Affiliation(s)
- Tianshu Han
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Xing Meng
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Ruiqi Shan
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Tianqi Zi
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Yingmei Li
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Hao Ma
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Yanhe Zhao
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Dan Shi
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Rongge Qu
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Xiaoyu Guo
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Lei Liu
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Lixin Na
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China.
| | - Ying Li
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China.
| | - Changhao Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People's Republic of China.
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Pasquel FJ, Gregg EW, Ali MK. The Evolving Epidemiology of Atherosclerotic Cardiovascular Disease in People with Diabetes. Endocrinol Metab Clin North Am 2018; 47:1-32. [PMID: 29407046 DOI: 10.1016/j.ecl.2017.11.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Atherosclerotic cardiovascular disease (ASCVD) is a leading global cause of death and accounts for most deaths among individuals with diabetes. This article reviews the latest observational and trial data on changes in the relationship between diabetes and ASCVD risk, remaining gaps in how the role of each risk factor is understood, and current knowledge about specific interventions. Differences between high-income countries and low-income and middle-income countries are examined, barriers and facilitators are discussed, and a discussion around the concept of ideal cardiovascular health factors (Life's Simple 7) is focused on.
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Affiliation(s)
- Francisco J Pasquel
- Division of Endocrinology, Emory University School of Medicine, 69 Jesse Hill Jr. Drive Southeast, Atlanta, GA 30303, USA.
| | - Edward W Gregg
- Division of Diabetes Translation, Centers for Disease Control and Prevention, 4770 Buford Highway, Mailstop F-75, Atlanta, GA 30341, USA
| | - Mohammed K Ali
- Division of Diabetes Translation, Centers for Disease Control and Prevention, 4770 Buford Highway, Mailstop F-75, Atlanta, GA 30341, USA; Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, GA 30322, USA; Department of Family and Preventive Medicine, Emory University School of Medicine, 4500 North Shallowford Road, Suite B, Atlanta, GA 30338, USA
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Han T, Lan L, Qu R, Xu Q, Jiang R, Na L, Sun C. Temporal Relationship Between Hyperuricemia and Insulin Resistance and Its Impact on Future Risk of Hypertension. Hypertension 2017; 70:703-711. [PMID: 28808071 DOI: 10.1161/hypertensionaha.117.09508] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2017] [Revised: 05/01/2017] [Accepted: 06/26/2017] [Indexed: 12/22/2022]
Abstract
Although hyperuricemia and insulin resistance significantly correlated, their temporal sequence and how the sequence influence on future risk of hypertension are largely unknown. This study assessed temporal relationship between uric acid and insulin resistance and its impact on future risk of hypertension by examining a longitudinal cohort including 8543 subjects aged 20 to 74 years from China, with an average follow-up of 5.3 years. Measurements of fasting uric acid, as well as fasting and 2-hour serum glucose and insulin, were obtained at baseline and follow-up. Indicators of hepatic and peripheral insulin resistance were calculated. Cross-lagged panel and mediation analysis were used to examine the temporal relationship between uric acid and insulin resistance and its impact on follow-up hypertension. After adjusting for covariates, the cross-lagged path coefficients (β1 values) from baseline uric acid to follow-up insulin resistance indices were significantly greater than path coefficients (β2 values) from baseline insulin resistance indices to follow-up uric acid (β1=0.110 versus β2=0.017; P<0.001, for hepatic insulin resistance; β1=-0.208 versus β2=-0.021; P<0.001, for peripheral insulin resistance). The path coefficients from baseline uric acid to follow-up insulin resistance indices in the hypertensive group were significantly greater than that in the normotensive group (P<0.001 for the difference of β1 values in the 2 groups). Insulin resistance partially mediated the effect of uric acid on subsequent hypertension, and the mediation effect of peripheral insulin resistance was significantly greater than that of hepatic insulin resistance (31.3% versus 13.2%; P<0.001, for the difference of mediation effects). These findings provide evidence that higher uric acid levels probably precede insulin resistance, and peripheral insulin resistance likely plays a more important role in the development of hypertension than hepatic insulin resistance does.
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Affiliation(s)
- Tianshu Han
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.)
| | - Li Lan
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.)
| | - Rongge Qu
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.)
| | - Qian Xu
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.)
| | - Ruyue Jiang
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.)
| | - Lixin Na
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.).
| | - Changhao Sun
- From the National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, P. R. China (T.H., R.Q., Q.X., R.J., L.N., C.S.); and Harbin Center for Disease Control and Prevention, P. R. China (L.L.).
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Heianza Y, Qi L. Gene-Diet Interaction and Precision Nutrition in Obesity. Int J Mol Sci 2017; 18:ijms18040787. [PMID: 28387720 PMCID: PMC5412371 DOI: 10.3390/ijms18040787] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 03/30/2017] [Accepted: 04/03/2017] [Indexed: 02/06/2023] Open
Abstract
The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.
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Affiliation(s)
- Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
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Zhang T, Zhang H, Li Y, Li S, Fernandez C, Bazzano L, He J, Xue F, Chen W. Long-term Impact of Temporal Sequence from Childhood Obesity to Hyperinsulinemia on Adult Metabolic Syndrome and Diabetes: The Bogalusa Heart Study. Sci Rep 2017; 7:43422. [PMID: 28230104 PMCID: PMC5322533 DOI: 10.1038/srep43422] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Accepted: 01/24/2017] [Indexed: 01/21/2023] Open
Abstract
This study aims to delineate the temporal relations between body mass index (BMI) and insulin in childhood and their impact on adult metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM).The longitudinal cohort consisted of 609 whites and 339 blacks who had BMI and fasting insulin measured twice in childhood (mean age = 10.5 years at baseline and 15.9 years at follow-up). Incident MetS and T2DM were identified in adulthood (mean age = 30.5 years). Cross-lagged panel and mediation analysis models were used. After adjusting for age, race, gender, and follow-up years, the cross-lagged path coefficient of BMI → insulin (β = 0.326, p < 0.001) was significantly greater than that of insulin → BMI (β = −0.023, p = 0.207) in childhood, with p < 0.001 for the difference in βs. The path coefficient for BMI → insulin was significantly greater in MetS than in non-MetS groups (0.510 vs 0.190, p < 0.001), and greater in hyperglycemia than in normoglycemia groups (0.503 vs 0.285, p = 0.026). The mediation effect of childhood insulin on the BMI-MetS and BMI-hyperglycemia associations was estimated at 19.2% (p < 0.001) and 18.3% (p < 0.001), respectively. These findings provide evidence that higher BMI levels precede hyperinsulinemia during childhood, and this one-directional relation plays a significant role in the development of MetS and T2DM in adult life.
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Affiliation(s)
- Tao Zhang
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China.,Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Huijie Zhang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.,Department of Endocrinology and Metabolism, the First Hospital of Xiamen, Xiamen University, Xiamen, China
| | - Ying Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.,Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Shengxu Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Camilo Fernandez
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Lydia Bazzano
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Jiang He
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
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