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Li R, Zhu X, Lee S. Model Selection for Exposure-Mediator Interaction. DATA SCIENCE IN SCIENCE 2024; 3:2360892. [PMID: 38947225 PMCID: PMC11210705 DOI: 10.1080/26941899.2024.2360892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 05/23/2024] [Indexed: 07/02/2024]
Abstract
In mediation analysis, the exposure often influences the mediating effect, i.e., there is an interaction between exposure and mediator on the dependent variable. When the mediator is high-dimensional, it is necessary to identify non-zero mediatorsM and exposure-by-mediator ( X -by- M ) interactions. Although several high-dimensional mediation methods can naturally handle X -by- M interactions, research is scarce in preserving the underlying hierarchical structure between the main effects and the interactions. To fill the knowledge gap, we develop the XMInt procedure to select M and X -by- M interactions in the high-dimensional mediators setting while preserving the hierarchical structure. Our proposed method employs a sequential regularization-based forward-selection approach to identify the mediators and their hierarchically preserved interaction with exposure. Our numerical experiments showed promising selection results. Further, we applied our method to ADNI morphological data and examined the role of cortical thickness and subcortical volumes on the effect of amyloid-beta accumulation on cognitive performance, which could be helpful in understanding the brain compensation mechanism.
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Affiliation(s)
| | - Ruiyang Li
- Department of Biostatistics, Columbia University, New York, USA
| | - Xi Zhu
- Department of Psychiatry, Columbia University, New York, USA
- Mental Health Data Science, New York State Psychiatric Institute and Research Foundation for Mental Hygiene, Inc., New York, USA
| | - Seonjoo Lee
- Department of Biostatistics, Columbia University, New York, USA
- Department of Psychiatry, Columbia University, New York, USA
- Mental Health Data Science, New York State Psychiatric Institute and Research Foundation for Mental Hygiene, Inc., New York, USA
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Amadou A, Freisling H, Sedlmeier AM, Bohmann P, Fontvieille E, Weber A, Konzok J, Stein MJ, Peruchet-Noray L, Jansana A, Noh H, His M, Gan Q, Baurecht H, Fervers B. Multi-Trait Body Shape Phenotypes and Breast Cancer Risk in Postmenopausal Women: A Causal Mediation Analysis in the UK Biobank Cohort. J Epidemiol Glob Health 2024; 14:420-432. [PMID: 38598163 PMCID: PMC11176278 DOI: 10.1007/s44197-024-00226-4] [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: 01/10/2024] [Accepted: 04/01/2024] [Indexed: 04/11/2024] Open
Abstract
Body shape phenotypes combining multiple anthropometric traits have been linked to postmenopausal breast cancer (BC). However, underlying biological pathways remain poorly understood. This study investigated to what extent the associations of body shapes with postmenopausal BC risk is mediated by biochemical markers. The study included 176,686 postmenopausal women from UK Biobank. Four body shape phenotypes were derived from principal component (PC) analysis of height, weight, body mass index, waist and hip circumferences, and waist-to-hip ratio (WHR). The four-way decomposition of the total effect was used to estimate mediation and interaction effects simultaneously as well as the mediated proportions. After 10.9 years median follow-up, 6,396 incident postmenopausal BC were diagnosed. There was strong evidence of positive associations between PC1 (general obesity) and PC2 (tall, low WHR), and BC risk. The association of PC1 with BC risk was positively mediated by testosterone and negatively by insulin-like growth factor-1 (IGF-1), with the overall proportion mediated (sum of the mediated interaction and pure indirect effect (PIE)) accounting for 11.4% (95% confidence intervals: 5.1 to 17.8%) and -12.2% (-20.5% to -4.0%) of the total effect, respectively. Small proportions of the association between PC2 and BC were mediated by IGF-1 (PIE: 2.8% (0.6 to 4.9%)), and sex hormone-binding globulin (SHBG) (PIE: -6.1% (-10.9% to -1.3%)). Our findings are consistent with differential pathways linking different body shapes with BC risk, with a suggestive mediation through testosterone and IGF-1 in the relationship of a generally obese body shape and BC risk, while IGF-1 and SHBG may mediate a tall/lean body shape-BC risk association.
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Affiliation(s)
- Amina Amadou
- Department of Prevention Cancer Environment, Centre Léon Bérard, 28 rue Laënnec, Lyon Cedex 08, 69373, France.
- Inserm U1296 Radiations : Défense, Santé, Environnement, Lyon, France.
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Anja M Sedlmeier
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Patricia Bohmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Emma Fontvieille
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Andrea Weber
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Julian Konzok
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Michael J Stein
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Laia Peruchet-Noray
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Anna Jansana
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Hwayoung Noh
- Department of Prevention Cancer Environment, Centre Léon Bérard, 28 rue Laënnec, Lyon Cedex 08, 69373, France
- Inserm U1296 Radiations : Défense, Santé, Environnement, Lyon, France
| | - Mathilde His
- Department of Prevention Cancer Environment, Centre Léon Bérard, 28 rue Laënnec, Lyon Cedex 08, 69373, France
- Inserm U1296 Radiations : Défense, Santé, Environnement, Lyon, France
| | - Quan Gan
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Béatrice Fervers
- Department of Prevention Cancer Environment, Centre Léon Bérard, 28 rue Laënnec, Lyon Cedex 08, 69373, France
- Inserm U1296 Radiations : Défense, Santé, Environnement, Lyon, France
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Wang Z, Zhang C, Williams PL, Bellavia A, Wylie BJ, Kannan K, Bloom MS, Hunt KJ, James-Todd T. Racial and ethnic disparities in preterm birth: a mediation analysis incorporating mixtures of polybrominated diphenyl ethers. FRONTIERS IN REPRODUCTIVE HEALTH 2024; 5:1285444. [PMID: 38260052 PMCID: PMC10800537 DOI: 10.3389/frph.2023.1285444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/12/2023] [Indexed: 01/24/2024] Open
Abstract
Background Racial and ethnic disparities persist in preterm birth (PTB) and gestational age (GA) at delivery in the United States. It remains unclear whether exposure to environmental chemicals contributes to these disparities. Objectives We applied recent methodologies incorporating environmental mixtures as mediators in causal mediation analysis to examine whether racial and ethnic disparities in GA at delivery and PTB may be partially explained by exposures to polybrominated diphenyl ethers (PBDEs), a class of chemicals used as flame retardants in the United States. Methods Data from a multiracial/ethnic US cohort of 2008 individuals with low-risk singleton pregnancies were utilized, with plasma PBDE concentrations measured during early pregnancy. We performed mediation analyses incorporating three forms of mediators: (1) reducing all PBDEs to a weighted index, (2) selecting a PBDE congener, or (3) including all congeners simultaneously as multiple mediators, to evaluate whether PBDEs may contribute to the racial and ethnic disparities in PTB and GA at delivery, adjusted for potential confounders. Results Among the 2008 participants, 552 self-identified as non-Hispanic White, 504 self-identified as non-Hispanic Black, 568 self-identified as Hispanic, and 384 self-identified as Asian/Pacific Islander. The non-Hispanic Black individuals had the highest mean ∑PBDEs, the shortest mean GA at delivery, and the highest rate of PTB. Overall, the difference in GA at delivery comparing non-Hispanic Black to non-Hispanic White women was -0.30 (95% CI: -0.54, -0.05) weeks. This disparity reduced to -0.23 (95% CI: -0.49, 0.02) and -0.18 (95% CI: -0.46, 0.10) weeks if fixing everyone's weighted index of PBDEs to the median and the 25th percentile levels, respectively. The proportion of disparity mediated by the weighted index of PBDEs was 11.8%. No statistically significant mediation was found for PTB, other forms of mediator(s), or other racial and ethnic groups. Conclusion PBDE mixtures may partially mediate the Black vs. White disparity in GA at delivery. While further validations are needed, lowering the PBDEs at the population level might help reduce this disparity.
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Affiliation(s)
- Zifan Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Cuilin Zhang
- Global Center for Asian Women’s Health, Bia-Echo Asia Centre for Reproductive Longevity & Equality (ACRLE), NUS Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Paige L. Williams
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Andrea Bellavia
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Blair J. Wylie
- Department of Obstetrics and Gynecology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, United States
| | | | - Michael S. Bloom
- Department of Global and Community Health, George Mason University, Fairfax, VA, United States
| | - Kelly J. Hunt
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Tamarra James-Todd
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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Zhu Y, Bi Y, Yu Q, Liu B. Assessment of the prognostic value of preoperative high-sensitive troponin T for myocardial injury and long-term mortality for groups at high risk for cardiovascular events following noncardiac surgery: a retrospective cohort study. Front Med (Lausanne) 2023; 10:1135786. [PMID: 37425305 PMCID: PMC10325788 DOI: 10.3389/fmed.2023.1135786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 06/02/2023] [Indexed: 07/11/2023] Open
Abstract
Background Few studies explored the association between high-sensitive cardiac troponin T (hs-cTnT) and long-term mortality for patients after surgery. This study was conducted to assess the association of hs-cTnT with long-term mortality and to investigate the extent to which this association is mediated via myocardial injury after noncardiac surgery (MINS). Methods This retrospective cohort study included all patients with hs-cTnT measurements who underwent non-cardiac surgery at Sichuan University West China Hospital. Data were collected from February 2018 and November 2020, with follow-up through February 2022. The primary outcome was all-cause mortality within 1 year. As secondary outcomes, MINS, length of hospital stay (LOS), and ICU admission were analyzed. Results The cohort included 7,156 patients (4,299 [60.1%] men; 61.0 [49.0-71.0] years). Among 7,156 patients, there were 2,151 (30.05%) with elevated hs-cTnT(>14 ng/L). After more than 1 year of follow-up, more than 91.8% of mortality information was available. During one-year follow-up after surgery, there were 308 deaths (14.8%) with a preoperative hs-cTnT >14 ng/L, compared with 192 deaths (3.9%) with a preoperative hs-cTnT <=14 ng/L(adjusted hazard ratio [aHR] 1.93, 95% CI 1.58-2.36; p < 0.001). Elevated preoperative hs-cTnT was also associated with several other adverse outcomes (MINS: adjusted odds ratio [aOR] 3.01; 95% CI, 2.46-3.69; p < 0.001; LOS: aOR 1.48, 95%CI 1.34-1.641; p < 0.001; ICU admission: aOR 1.52, 95%CI 1.31-1.76; p < 0.001). MINS explained approximately 33.6% of the variance in mortality due to preoperative hs-cTnT levels. Conclusion Preoperative elevated hs-cTnT concentrations have a significant association with long-term mortality after noncardiac surgery, one-third of which may by accounted for by MINS.
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Affiliation(s)
- Yingchao Zhu
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yaodan Bi
- Department of Anesthesiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Qian Yu
- Department of Anesthesiology, Public Health Clinical Center of Chengdu, Chengdu, Sichuan, China
| | - Bin Liu
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Thompson JA. Bayesian estimation of potential outcomes for mediation analysis of racial disparity for infant mortality. RESEARCH SQUARE 2023:rs.3.rs-2874047. [PMID: 37398241 PMCID: PMC10312987 DOI: 10.21203/rs.3.rs-2874047/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background There is a need for novel methods to determine preventable causes of racial health disparities. This need has been met with the development of improved methods for mediation modeling. Current mediational analysis methods call for an evaluation of statistical interaction or effect modification between the investigated cause and mediator. For racial disparity, this approach facilitates the estimation of racially specific risks for infant mortality. However, current methods for evaluating multiple interacting mediators are inadequate. The first objective of the study was to compare Bayesian estimation of potential outcomes to other approaches to mediation analysis that included interaction. The second objective was to evaluate three potentially interacting mediators of racial disparity for infant mortality by modeling the large dataset from the National Natality Database using Bayesian estimation of potential outcomes. Methods A random sample of observations from the 2003 National Natality Database was used to compare the currently promoted methods for mediation modeling. Racial disparity was modeled as a separate function for each of three potential mediators, (i) maternal smoking, (ii) low birth weight and (iii) teenage maternity. As a second objective, direct Bayesian estimation of potential outcomes modeled infant mortality as function of the interactions among the three mediators and race using the full National Natality Database for the years 2016 to 2018. Results The counterfactual model was inaccurate in estimating the proportion of racial disparity that was attributable to either maternal smoking or teenage maternity. The counterfactual approach did not accurately estimate the probabilities defined by counterfactual definitions. The error was a result of modeling the excess relative risk instead of the risk probabilities. Bayesian approaches did estimate the probabilities of the counterfactual definitions. Results showed that 73% of the racial disparity for infant mortality was attributed to infants born with low birth weight. Conclusions Bayesian estimation of potential outcomes could evaluate whether proposed public health programs would affect races differently and decisions could include consideration of the causal effect the program may have on racial disparity. The large contribution of low birth weight to racial disparity for infant mortality should be further investigated to identify preventable factors for low birth weight.
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Affiliation(s)
- J A Thompson
- College of Veterinary Medicine and Biomedical Science, Texas A&M University, College Station, TX, 77843-4475, USA
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Wang Q, Li X, Zhong W, Liu H, Feng C, Song C, Yu B, Fu Y, Lin X, Yin Y, Chen T, Reinhardt JD, Yang S. Residential greenness and dyslipidemia risk: Dose-response relations and mediation through BMI and air pollution. ENVIRONMENTAL RESEARCH 2023; 217:114810. [PMID: 36395867 DOI: 10.1016/j.envres.2022.114810] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/02/2022] [Accepted: 11/12/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Evidence on associations of residential greenness with dyslipidemia is limited, particularly regarding dose-response relations and mediation. OBJECTIVES To investigate associations between greenness and dyslipidemia, non-linear dose-response relationships and mediators. METHODS This cross-sectional study draws on the 2018 Fujian Behavior and Disease Surveillance (FBDS) cohort that used multi-stage stratified random sampling from the general population of Fujian Province, China. Participants with one or more abnormities in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), or low-density lipoprotein cholesterol (LDL-C) were classified as having dyslipidemia. Residential greenness was operationalized as 3-year average of the normalized difference vegetation index (NDVI500m) and enhanced vegetation index (EVI500m). A doubly robust approach was used for effect quantification. Dose-response relations were studied with natural cubic splines. Mediation via physical activity (PA), body mass index (BMI), PM2.5, PM10, SO2, and NO2 was also examined. RESULTS Data from 43,183 participants were analyzed. Increases in NDVI500m and EVI500m residential greenness were associated with decreased dyslipidemia risk and improved blood lipids. Non-linear dose response relationships were discovered. Significant reduction of dyslipidemia risk was observed at levels of EVI500m > 0.48 and NDVI500m > 0.65. Joint mediation effects of PA, BMI, PM2.5, PM10, NO2, and SO2 on the associations of NDVI500m and EVI500m with dyslipidemia risk were 49.74% and 44.64%, respectively. CONCLUSIONS Increased residential exposure to greenness was associated with decreased risk of dyslipidemia. A non-linear dose-response relationship between greenness and dyslipidemia suggests that specific thresholds of greenness need to be reached in order to achieve effects. BMI, PM2.5, and PM10 partially mediated the association.
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Affiliation(s)
- Qinjian Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaoqing Li
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Wenling Zhong
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Hongyun Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Chao Song
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Yao Fu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xi Lin
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Yanrong Yin
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Tiehui Chen
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Jan D Reinhardt
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China; Department of Rehabilitation Medicine, Jiangsu Province Hospital/Nanjing Medical University First Affiliated Hospital, Nanjing, China; Swiss Paraplegic Research, Nottwil, Switzerland; Department of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, China; International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China.
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Li X, Wang Q, Feng C, Yu B, Lin X, Fu Y, Dong S, Qiu G, Jin Aik DH, Yin Y, Xia P, Huang S, Liu N, Lin X, Zhang Y, Fang X, Zhong W, Jia P, Yang S. Associations and pathways between residential greenness and metabolic syndromes in Fujian Province. Front Public Health 2022; 10:1014380. [PMID: 36620251 PMCID: PMC9815145 DOI: 10.3389/fpubh.2022.1014380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022] Open
Abstract
Background Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association. Methods A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Results Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI500m and EVI500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI500m), followed by NO2 and PM10. Conclusion Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.
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Affiliation(s)
- Xiaoqing Li
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Qinjian Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Xi Lin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Yao Fu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Shu Dong
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ge Qiu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Darren How Jin Aik
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Yanrong Yin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Pincang Xia
- Department for HIV/AIDS and STDs Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Shaofen Huang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Nian Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiuquan Lin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Yefa Zhang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Xin Fang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Wenling Zhong
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China,*Correspondence: Wenling Zhong
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China,Peng Jia
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China,Shujuan Yang
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Zugna D, Popovic M, Fasanelli F, Heude B, Scelo G, Richiardi L. Applied causal inference methods for sequential mediators. BMC Med Res Methodol 2022; 22:301. [PMID: 36424556 PMCID: PMC9686042 DOI: 10.1186/s12874-022-01764-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 10/19/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Mediation analysis aims at estimating to what extent the effect of an exposure on an outcome is explained by a set of mediators on the causal pathway between the exposure and the outcome. The total effect of the exposure on the outcome can be decomposed into an indirect effect, i.e. the effect explained by the mediators jointly, and a direct effect, i.e. the effect unexplained by the mediators. However finer decompositions are possible in presence of independent or sequential mediators. METHODS We review four statistical methods to analyse multiple sequential mediators, the inverse odds ratio weighting approach, the inverse probability weighting approach, the imputation approach and the extended imputation approach. These approaches are compared and implemented using a case-study with the aim to investigate the mediating role of adverse reproductive outcomes and infant respiratory infections in the effect of maternal pregnancy mental health on infant wheezing in the Ninfea birth cohort. RESULTS Using the inverse odds ratio weighting approach, the direct effect of maternal depression or anxiety in pregnancy is equal to a 59% (95% CI: 27%,94%) increased prevalence of infant wheezing and the mediated effect through adverse reproductive outcomes is equal to a 3% (95% CI: -6%,12%) increased prevalence of infant wheezing. When including infant lower respiratory infections in the mediation pathway, the direct effect decreases to 57% (95% CI: 25%,92%) and the indirect effect increases to 5% (95% CI: -5%,15%). The estimates of the effects obtained using the weighting and the imputation approaches are similar. The extended imputation approach suggests that the small joint indirect effect through adverse reproductive outcomes and lower respiratory infections is due entirely to the contribution of infant lower respiratory infections, and not to an increased prevalence of adverse reproductive outcomes. CONCLUSIONS The four methods revealed similar results of small mediating role of adverse reproductive outcomes and early respiratory tract infections in the effect of maternal pregnancy mental health on infant wheezing. The choice of the method depends on what is the effect of main interest, the type of the variables involved in the analysis (binary, categorical, count or continuous) and the confidence in specifying the models for the exposure, the mediators and the outcome.
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Affiliation(s)
- D Zugna
- grid.7605.40000 0001 2336 6580Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, Italy
| | - M Popovic
- grid.7605.40000 0001 2336 6580Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, Italy
| | - F Fasanelli
- grid.7605.40000 0001 2336 6580Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, Italy
| | - B Heude
- grid.513249.80000 0004 8513 0030Université de Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France
| | - G Scelo
- grid.7605.40000 0001 2336 6580Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, Italy
| | - L Richiardi
- grid.7605.40000 0001 2336 6580Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, Italy
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9
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Yu W, Gao C, Zhao X, Li C, Fan B, Lv J, Wei M, He L, Su C, Zhang T. Four-way decomposition of effect of cigarette smoking and body mass index on serum lipid profiles. PLoS One 2022; 17:e0270486. [PMID: 35980977 PMCID: PMC9387787 DOI: 10.1371/journal.pone.0270486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 06/12/2022] [Indexed: 12/02/2022] Open
Abstract
Objective Smoking and obesity are established risk factors of dyslipidemia, however, the interplay between them has not been well studied. This study aims to explore the joint effect of smoking and body mass index (BMI) on serum lipid profiles. Methods The study consisted of 9846 Chinese adults (mean age = 49.9 years, 47.6% males, 31.2% ever smokers), based on the China Health and Nutrition Survey. Serum lipid profiles included total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (APO-A), and apolipoprotein B (Apo-B). The joint effect of smoking and BMI on serum lipids were examined by the four-way decomposition analysis and multivariate linear regression models. Results The four-way decomposition showed that the interplay between smoking and BMI was complicated. There was only indirect effect (the mediated effect) between smoking and BMI on TC, LDL-C and APO-B. The pure indirect effect was -0.023 for TC, -0.018 for LDL-C, and -0.009 for APO-B. For TG, HDL-C and APO-A, the interaction effect was dominant. The reference interaction (the interactive effect when the mediator is left to what it would be in the absence of exposure) was 0.474 (P < 0.001) for TG, -0.245 (P = 0.002) for HDL-C, and -0.222 (P < 0.001) for APO-A, respectively. The effect of BMI on TG, HDL-C and APO-A were significantly higher in smokers than in nonsmokers (TG: 0.151 in smokers versus 0.097 in nonsmokers, HDL-C: -0.037 versus -0.027, APO-A: -0.019 versus -0.009, P for difference < 0.001 for all). Conclusion These findings illustrate the joint effects of smoking and BMI on serum lipid profiles. There were significant interaction effects of smoking and BMI on TG, HDL-C and APO-A, while BMI maybe a mediator for the association of smoking with TC, LDL-C and APO-B. The effects between them were rather complex. Smoking cessation is necessary, especially for those overweight.
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Affiliation(s)
- Wenhao Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Chaonan Gao
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Xiangjuan Zhao
- Maternal and Child Health Care of Shandong Province, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chunxia Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Bingbing Fan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Jiali Lv
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Mengke Wei
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Li He
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (TZ); (CS)
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Jinan, China
- * E-mail: (TZ); (CS)
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10
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Wang P, Asare E, Pitzer VE, Dubrow R, Chen K. Associations between long-term drought and diarrhea among children under five in low- and middle-income countries. Nat Commun 2022; 13:3661. [PMID: 35773263 PMCID: PMC9247069 DOI: 10.1038/s41467-022-31291-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 06/13/2022] [Indexed: 11/30/2022] Open
Abstract
Climate change is projected to intensify drought conditions, which may increase the risk of diarrheal diseases in children. We constructed log-binomial generalized linear mixed models to examine the association between diarrhea risk, ascertained from global-scale nationally representative Demographic and Health Surveys, and drought, represented by the standardized precipitation evapotranspiration index, among children under five in 51 low- and middle-income countries (LMICs). Exposure to 6-month mild or severe drought was associated with an increased diarrhea risk of 5% (95% confidence interval 3-7%) or 8% (5-11%), respectively. The association was stronger among children living in a household that needed longer time to collect water or had no access to water or soap/detergent for handwashing. The association for 24-month drought was strong in dry zones but weak or null in tropical or temperate zones, whereas that for 6-month drought was only observed in tropical or temperate zones. In this work we quantify the associations between exposure to long-term drought and elevated diarrhea risk among children under five in LMICs and suggest that the risk could be reduced through improved water, sanitation, and hygiene practices, made more urgent by the likely increase in drought due to climate change.
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Affiliation(s)
- Pin Wang
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA.
| | - Ernest Asare
- Department of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
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11
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Tai AS, Lin PH, Huang YT, Lin SH. Path-specific effects in the presence of a survival outcome and causally ordered multiple mediators with application to genomic data. Stat Methods Med Res 2022; 31:1916-1933. [PMID: 35635267 DOI: 10.1177/09622802221104239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Causal multimediation analysis (i.e. the causal mediation analysis with multiple mediators) is critical for understanding the effectiveness of interventions, especially in medical research. Deriving the path-specific effects of exposure on the outcome through a set of mediators can provide detail about the causal mechanism of interest However, existing models are usually restricted to partial decomposition, which can only be used to evaluate the cumulative effect of several paths. In genetics studies, partial decomposition fails to reflect the real causal effects mediated by genes, especially in complex gene regulatory networks. Moreover, because of the lack of a generalized identification procedure, the current multimediation analysis cannot be applied to the estimation of path-specific effects for any number of mediators. In this study, we derive the interventional analogs of path-specific effect for complete decomposition to address the difficulty of nonidentifiability. On the basis of two survival models of the outcome, we derive the generalized analytic forms for interventional analogs of path-specific effects by assuming the normal distributions of mediators. We apply the new methodology to investigate the causal mechanism of signature genes in lung cancer based on the cell cycle pathway, and the results clarify the gene pathway in cancer.
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Affiliation(s)
- An-Shun Tai
- Department of Statistics, 34912National Cheng Kung University, Tainan.,Institute of Statistics, 34914National Yang Ming Chiao Tung University, Hsin-Chu
| | - Pei-Hsuan Lin
- Institute of Statistics, 34914National Yang Ming Chiao Tung University, Hsin-Chu
| | - Yen-Tsung Huang
- Institute of Statistical Science, 38017Academia Sinica, Taipei
| | - Sheng-Hsuan Lin
- Institute of Statistics, 34914National Yang Ming Chiao Tung University, Hsin-Chu
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12
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Remigio RV, Turpin R, Raimann JG, Kotanko P, Maddux FW, Sapkota AR, Liang XZ, Puett R, He X, Sapkota A. Assessing proximate intermediates between ambient temperature, hospital admissions, and mortality in hemodialysis patients. ENVIRONMENTAL RESEARCH 2022; 204:112127. [PMID: 34582801 PMCID: PMC8901270 DOI: 10.1016/j.envres.2021.112127] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 08/19/2021] [Accepted: 09/22/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Typical thermoregulatory responses to elevated temperatures among healthy individuals include reduced blood pressure and perspiration. Individuals with end-stage kidney disease (ESKD) are susceptible to systemic fluctuations caused by ambient temperature changes that may increase morbidity and mortality. We investigated whether pre-dialysis systolic blood pressure (preSBP) and interdialytic weight gain (IDWG) can independently mediate the association between ambient temperature, all-cause hospital admissions (ACHA), and all-cause mortality (ACM). METHODS The study population consisted of ESKD patients receiving hemodialysis treatments at Fresenius Medical Care facilities in Philadelphia County, PA, from 2011 to 2019 (n = 1981). Within a time-to-event framework, we estimated the association between daily maximum dry-bulb temperature (TMAX) and, as separate models, ACHA and ACM during warmer calendar months. Clinically measured preSBP and IDWG responses to temperature increases were estimated using linear mixed effect models. We employed the difference (c-c') method to decompose total effect models for ACHA and ACM using preSBP and IDWG as time-dependent mediators. Covariate adjustments for exposure-mediator and total and direct effect models include age, race, ethnicity, blood pressure medication use, treatment location, preSBP, and IDWG. We considered lags up to two days for exposure and 1-day lag for mediator variables (Lag 2-Lag 1) to assure temporality between exposure-outcome models. Sensitivity analyses for 2-day (Lag 2-only) and 1-day (Lag 1-only) lag structures were also conducted. RESULTS Based on Lag 2- Lag 1 temporal ordering, 1 °C increase in daily TMAX was associated with increased hazard of ACHA by 1.4% (adjusted hazard ratio (HR), 1.014; 95% confidence interval, 1.007-1.021) and ACM 7.5% (adjusted HR, 1.075, 1.050-1.100). Short-term lag exposures to 1 °C increase in temperature predicted mean reductions in IDWG and preSBP by 0.013-0.015% and 0.168-0.229 mmHg, respectively. Mediation analysis for ACHA identified significant indirect effects for all three studied pathways (preSBP, IDWG, and preSBP + IDWG) and significant indirect effects for IDWG and conjoined preSBP + IDWG pathways for ACM. Of note, only 1.03% of the association between temperature and ACM was mediated through preSBP. The mechanistic path for IDWG, independent of preSBP, demonstrated inconsistent mediation and, consequently, potential suppression effects in ACHA (-15.5%) and ACM (-6.3%) based on combined pathway models. Proportion mediated estimates from preSBP + IDWG pathways achieved 2.2% and 0.3% in combined pathway analysis for ACHA and ACM outcomes, respectively. Lag 2 discrete-time ACM mediation models exhibited consistent mediation for all three pathways suggesting that 2-day lag in IDWG and preSBP responses can explain 2.11% and 4.41% of total effect association between temperature and mortality, respectively. CONCLUSION We corroborated the previously reported association between ambient temperature, ACHA and ACM. Our results foster the understanding of potential physiological linkages that may explain or suppress temperature-driven hospital admissions and mortality risks. Of note, concomitant changes in preSBP and IDWG may have little intermediary effect when analyzed in combined pathway models. These findings advance our assessment of candidate interventions to reduce the impact of outdoor temperature change on ESKD patients.
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Affiliation(s)
- Richard V Remigio
- Maryland Institute for Applied Environmental Health, University of Maryland-College Park, School of Public Health, College Park, MD, USA.
| | - Rodman Turpin
- Department of Epidemiology and Biostatistics, University of Maryland-College Park, School of Public Health, College Park, MD, USA
| | | | - Peter Kotanko
- Research Division, Renal Research Institute, New York, NY, USA; Icahn School of Medicine, Mount Sinai Hospital, New York, NY, USA
| | | | - Amy Rebecca Sapkota
- Maryland Institute for Applied Environmental Health, University of Maryland-College Park, School of Public Health, College Park, MD, USA
| | - Xin-Zhong Liang
- Department of Atmospheric and Oceanic Sciences, University of Maryland-College Park, College Park, MD, USA
| | - Robin Puett
- Maryland Institute for Applied Environmental Health, University of Maryland-College Park, School of Public Health, College Park, MD, USA
| | - Xin He
- Department of Epidemiology and Biostatistics, University of Maryland-College Park, School of Public Health, College Park, MD, USA
| | - Amir Sapkota
- Maryland Institute for Applied Environmental Health, University of Maryland-College Park, School of Public Health, College Park, MD, USA
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13
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Tai A, Du Y, Lin S. Robust inference on effects attributable to mediators: A controlled‐direct‐effect‐based approach for causal effect decomposition with multiple mediators. Stat Med 2022; 41:1797-1814. [DOI: 10.1002/sim.9329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 12/14/2021] [Accepted: 01/06/2022] [Indexed: 11/10/2022]
Affiliation(s)
- An‐Shun Tai
- Institute of Statistics National Yang Ming Chiao Tung University Hsinchu Taiwan
| | - Yi‐Juan Du
- Institute of Statistics National Yang Ming Chiao Tung University Hsinchu Taiwan
| | - Sheng‐Hsuan Lin
- Institute of Statistics National Yang Ming Chiao Tung University Hsinchu Taiwan
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14
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Gao X, Li L, Luo L. Decomposition of the total effect for two mediators: A natural mediated interaction effect framework. JOURNAL OF CAUSAL INFERENCE 2022; 10:18-44. [PMID: 35633840 PMCID: PMC9139468 DOI: 10.1515/jci-2020-0017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mediation analysis has been used in many disciplines to explain the mechanism or process that underlies an observed relationship between an exposure variable and an outcome variable via the inclusion of mediators. Decompositions of the total effect (TE) of an exposure variable into effects characterizing mediation pathways and interactions have gained an increasing amount of interest in the last decade. In this work, we develop decompositions for scenarios where two mediators are causally sequential or non-sequential. Current developments in this area have primarily focused on either decompositions without interaction components or with interactions but assuming no causally sequential order between the mediators. We propose a new concept called natural mediated interaction (MI) effect that captures the two-way and three-way interactions for both scenarios and extends the two-way MIs in the literature. We develop a unified approach for decomposing the TE into the effects that are due to mediation only, interaction only, both mediation and interaction, neither mediation nor interaction within the counterfactual framework. Finally, we compare our proposed decomposition to an existing method in a non-sequential two-mediator scenario using simulated data, and illustrate the proposed decomposition for a sequential two-mediator scenario using a real data analysis.
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Affiliation(s)
- Xin Gao
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, 87131, USA; Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Li Li
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Li Luo
- Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA; Department of Internal Medicine, University of New Mexico, Albuquerque, NM, 87131, USA
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15
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OUP accepted manuscript. Biometrika 2022. [DOI: 10.1093/biomet/asac004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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16
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Rijnhart JJM, Lamp SJ, Valente MJ, MacKinnon DP, Twisk JWR, Heymans MW. Mediation analysis methods used in observational research: a scoping review and recommendations. BMC Med Res Methodol 2021; 21:226. [PMID: 34689754 PMCID: PMC8543973 DOI: 10.1186/s12874-021-01426-3] [Citation(s) in RCA: 84] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 09/21/2021] [Indexed: 12/02/2022] Open
Abstract
Background Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies. Methods We searched the MEDLINE and EMBASE databases for observational epidemiologic studies published between 2015 and 2019 in which mediation analysis was applied as one of the primary analysis methods. Information was extracted on the characteristics of the mediation model and the applied mediation analysis method. Results We included 174 studies, most of which applied traditional mediation analysis methods (n = 123, 70.7%). Causal mediation analysis was not often used to analyze more complicated mediation models, such as multiple mediator models. Most studies adjusted their analyses for measured confounders, but did not perform sensitivity analyses for unmeasured confounders and did not assess the presence of an exposure-mediator interaction. Conclusions To ensure a causal interpretation of the effect estimates in the mediation model, we recommend that researchers use causal mediation analysis and assess the plausibility of the causal assumptions. The uptake of causal mediation analysis can be enhanced through tutorial papers that demonstrate the application of causal mediation analysis, and through the development of software packages that facilitate the causal mediation analysis of relatively complicated mediation models. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-021-01426-3.
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Affiliation(s)
- Judith J M Rijnhart
- Department of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands.
| | - Sophia J Lamp
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Matthew J Valente
- Department of Psychology, Center for Children and Families, Florida International University, Miami, FL, USA
| | | | - Jos W R Twisk
- Department of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands
| | - Martijn W Heymans
- Department of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands
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17
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Yamamuro S, Shinozaki T, Iimuro S, Matsuyama Y. Mediational g-formula for time-varying treatment and repeated-measured multiple mediators: Application to atorvastatin's effect on cardiovascular disease via cholesterol lowering and anti-inflammatory actions in elderly type 2 diabetics. Stat Methods Med Res 2021; 30:1782-1799. [PMID: 34187236 DOI: 10.1177/09622802211025988] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Modern causal mediation theory has formalized several types of indirect and direct effects of treatment on outcomes regarding specific mediator variables. We reviewed and unified distinct approaches to estimate the "interventional" direct and indirect effects for multiple mediators and time-varying variables. This study was motivated by a clinical trial of elderly type-2 diabetic patients in which atorvastatin was widely prescribed to control patients' cholesterol levels to reduce diabetic complications, including cardiovascular disease. Among atorvastatin's preventive side-effects (pleiotropic effects), we focus on its anti-inflammatory action as measured by white blood cell counts. Hence, we estimate atorvastatin's interventional indirect effects through cholesterol lowering and through anti-inflammatory action, and interventional direct effect bypassing these two actions. In our analysis, total effect (six-year cardiovascular disease risk difference) estimated by standard plug-in g-formula of -3.65% (95% confidence interval: -10.29%, 4.38%) is decomposed into indirect effect via low-density lipoprotein cholesterol (-0.90% [-1.91%, -0.07%]), via white blood cell counts (-0.03% [-0.22%, 0.11%]), and direct effect (-2.84% [-9.71%, 5.41%]) by the proposed parametric mediational g-formula. The SAS program and its evaluation via simulated datasets are provided in the Supplemental materials.
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Affiliation(s)
- Shintaro Yamamuro
- Department of Biostatistics, School of Public Health, University of Tokyo, Tokyo, Japan.,Department of Clinical Data Science, Eisai Co. Ltd., Tokyo, Japan
| | - Tomohiro Shinozaki
- Department of Information and Computer Technology, Faculty of Engineering, 26413Tokyo University of Science, Tokyo University of Science, Tokyo, Japan
| | - Satoshi Iimuro
- Innovation and Research Support Center, Graduate School of Medicine, 34804International University of Health and Welfare, International University of Health and Welfare, Tokyo, Japan
| | - Yutaka Matsuyama
- Department of Biostatistics, School of Public Health, University of Tokyo, Tokyo, Japan
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18
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Adibi JJ, Layden AJ, Birru RL, Miragaia A, Xun X, Smith MC, Yin Q, Millenson ME, O’Connor TG, Barrett ES, Snyder NW, Peddada S, Mitchell RT. First trimester mechanisms of gestational sac placental and foetal teratogenicity: a framework for birth cohort studies. Hum Reprod Update 2021; 27:747-770. [PMID: 33675653 PMCID: PMC8222765 DOI: 10.1093/humupd/dmaa063] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 12/18/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The function of the gestational sac (GS) and the placenta in the closely related processes of embryogenesis and teratogenicity in the first trimester has been minimally described. The prevailing assumption is that direct teratogenic effects are mediated by the critical extraembryonic organ, the placenta, which either blocks or transfers exposures to the foetus. Placental transfer is a dominant mechanism, but there are other paradigms by which the placenta can mediate teratogenic effects. Knowledge of these paradigms and first trimester human developmental biology can be useful to the epidemiologist in the conduct of biomarker-based studies of both maternal and child health. OBJECTIVE AND RATIONALE Our aim is to provide a causal framework for modelling the teratogenic effects of first trimester exposures on child health outcomes mediated by the GS and placenta using biomarker data collected in the first trimester. We initially present first trimester human developmental biology for the sake of informing and strengthening epidemiologic approaches. We then propose analytic approaches of modelling placental mechanisms by way of causal diagrams using classical non-embryolethal teratogens (diethylstilboestrol [DES], folic acid deficiency and cytomegalovirus [CMV]) as illustrative examples. We extend this framework to two chronic exposures of particular current interest, phthalates and maternal adiposity. SEARCH METHODS Information on teratogens was identified by a non-systematic, narrative review. For each teratogen, we included papers that answered the five following questions: (i) why were these exposures declared teratogens? (ii) is there a consensus on biologic mechanism? (iii) is there reported evidence of a placental mechanism? (iv) can we construct a theoretical model of a placental mechanism? and (v) can this knowledge inform future work on measurement and modelling of placental-foetal teratogenesis? We prioritized literature specific to human development, the organogenesis window in the first trimester and non-embryolethal mechanisms. OUTCOMES As a result of our review of the literature on five exposures considered harmful in the first trimester, we developed four analytic strategies to address first trimester placental mechanisms in birth cohort studies: placental transfer and direct effects on the foetus (DES and maternal adiposity), indirect effects through targeted placental molecular pathways (DES and phthalates), pre-placental effects through disruptions in embryonic and extraembryonic tissue layer differentiation (folic acid deficiency), and multi-step mechanisms that involve maternal, placental and foetal immune function and inflammation (DES and CMV). WIDER IMPLICATIONS The significance of this review is to offer a causal approach to classify the large number of potentially harmful exposures in pregnancy when the exposure occurs in the first trimester. Our review will facilitate future research by advancing knowledge of the first trimester mechanisms necessary for researchers to effectively associate environmental exposures with child health outcomes.
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Affiliation(s)
- Jennifer J Adibi
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexander J Layden
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rahel L Birru
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexandra Miragaia
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaoshuang Xun
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Megan C Smith
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Qing Yin
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Thomas G O’Connor
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
- Department of Obstetrics and Gynecology, University of Rochester Medical Center, Rochester, NY, USA
| | - Emily S Barrett
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ, USA
| | - Nathaniel W Snyder
- Department of Microbiology and Immunology, Center for Metabolic Disease Research, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA
| | - Shyamal Peddada
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rod T Mitchell
- MRC Centre for Reproductive Health, The University of Edinburgh, Queens Medical Research Institute, Edinburgh, UK
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Meta-analysis of Total Effect Decomposition in the Presence of Multiple Mediators: The Example of Schizophrenia Treatment. Epidemiology 2021; 32:120-130. [PMID: 33181564 DOI: 10.1097/ede.0000000000001269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Causal mediation analysis addresses mechanistic questions by decomposing and quantifying effects operating through different pathways. Because most individual studies are underpowered to detect mediating effects, we outlined a parametric approach to meta-analyzing causal mediation and interaction analyses with multiple mediators, compared it with a bootstrap-based alternative, and discussed its limitations. METHODS We employed fixed- and random-effects multivariate meta-analyses to integrate evidence on treatment-mediators and mediators-outcome associations across trials. We estimated path-specific effects as functions of meta-analyzed regression coefficients; we obtained standard errors using the delta method. We evaluated the performance of this approach in simulations and applied it to assess the mediating roles of positive symptoms of schizophrenia and weight gain in the treatment effect of paliperidone ER on negative symptoms across four efficacy trials. RESULTS Both simulations and the application showed that the meta-analytic approaches increased statistical power. In the application, we observed substantial mediating effects of positive symptoms (proportions mediated from fixed-effects meta-analysis: (Equation is included in full-text article.)). Weight gain may have beneficial mediating effects; however, such benefit may disappear at high doses when metabolic side effects were excessive. CONCLUSIONS Meta-analyzing causal mediation analysis combines evidence from multiple sources and improves power. Targeting positive symptoms may be an effective way to reduce negative symptoms that are challenging to treat. Future work should focus on extending the existing methods to allow for more flexible modeling of mediation.
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Sint K, Rosenheck R, Lin H. Latent class mediator for multiple indicators of mediation. Stat Med 2021; 40:2800-2820. [PMID: 33687101 PMCID: PMC8187142 DOI: 10.1002/sim.8929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/04/2021] [Accepted: 02/10/2021] [Indexed: 11/11/2022]
Abstract
This paper demonstrates the utility of latent classes in evaluating the effect of an intervention on an outcome through multiple indicators of mediation. These indicators are observed intermediate variables that identify an underlying latent class mediator, with each class representing a different mediating pathway. The use of a latent class mediator allows us to avoid modeling the complex interactions between the multiple indicators and ensures the decomposition of the total mediating effects into additive effects from individual mediating pathways, a desirable feature for evaluating multiple indicators of mediation. This method is suitable when the goal is to estimate the total mediating effects that can be decomposed into the additive effects of distinct mediating pathways. Each indicator may be involved in multiple mediation pathways and at the same time multiple indicators may contribute to a single mediating pathway. The relative importance of each pathway may vary across subjects. We applied this method to the analysis of the first 6 months of data from a 2-year clustered randomized trial for adults in their first episode of schizophrenia. Four indicators of mediation are considered: individual resiliency training; family psychoeducation; supported education and employment; and a structural assessment for medication. The improvement in symptoms was found to be mediated by the latent class mediator derived from these four service indicators. Simulation studies were conducted to assess the performance of the proposed model and showed that the simultaneous estimation through the maximum likelihood yielded little bias when the entropy of the indicators was high.
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Affiliation(s)
- Kyaw Sint
- Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut
| | - Robert Rosenheck
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Haiqun Lin
- School of Nursing and School of Public Health, Rutgers Biomedical and Health Sciences, Rutgers University, the State University of New Jersey, Newark, NJ
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Bellavia A, Dickerson AS, Rotem RS, Hansen J, Gredal O, Weisskopf MG. Joint and interactive effects between health comorbidities and environmental exposures in predicting amyotrophic lateral sclerosis. Int J Hyg Environ Health 2021; 231:113655. [PMID: 33130429 PMCID: PMC7736520 DOI: 10.1016/j.ijheh.2020.113655] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 09/21/2020] [Accepted: 09/28/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Amyotrophic lateral sclerosis (ALS) is a rare yet devastating neurodegenerative condition. The mechanisms leading to ALS are most certainly complex and likely involve a joint contribution of several factors with possible synergistic or antagonistic interactions. To provide a better understanding of the association between non-genetic factors and ALS, we evaluated the joint exposure to multiple health and environmental factors linked with ALS in our previous studies, also screening for high-dimensional interactions. METHODS We used data from a nested case-control study within the Danish population, with 1086 ALS cases from 1982 to 2009, jointly investigating 4 hospital-based diagnoses - diabetes, obesity, physical/stress trauma, cardiovascular disease (CVD) during 1977-2009; and 4 environmental exposures - lead, formaldehyde, diesel exhaust, and solvents, assessed from individual occupational history. All covariates were evaluated as ever/never exposed, and we used targeted machine learning techniques to screen for important joint predictors and interactions. These were then evaluated in a final logistic regression model adjusting for potential confounders (age, SES, geography). All analyses were stratified by sex. RESULTS Among men, trauma and solvents were associated with higher odds of ALS (OR = 1.55, 95% CI: 1.08-2.23; OR = 1.49, 95% CI: 1.17-1.89, respectively), and presented a negative interaction (OR = 0.49, 95% CI: 0.30-0.80). A positive diesel/CVD interaction was observed (OR = 1.56, 95% CI: 0.94-2.60). Among women, solvents, trauma, lead, and CVD were associated with higher odds of ALS, and a negative lead/solvents interaction was documented (OR = 0.52, 95% CI: 0.42-0.63). CONCLUSIONS This study is one of the first attempts to evaluate joint and interactive effects of multiple risk factors on ALS, identifying potential synergistic and antagonistic mechanisms.
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Affiliation(s)
- Andrea Bellavia
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.
| | - Aisha S Dickerson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205, USA
| | - Ran S Rotem
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Johnni Hansen
- Danish Cancer Society, Institute of Cancer Epidemiology, Strandboulevarden 49, DK-2100, Copenhagen, Denmark
| | - Ole Gredal
- Danish Cancer Society, Institute of Cancer Epidemiology, Strandboulevarden 49, DK-2100, Copenhagen, Denmark
| | - Marc G Weisskopf
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
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Adibi JJ, Layden AJ, Yin Q, Xun X, Peddada S, Birru RL. A toolkit for the application of placental-fetal molecular biomarkers in epidemiologic studies of the fetal origins of chronic disease. CURR EPIDEMIOL REP 2020; 8:20-31. [PMID: 33777648 DOI: 10.1007/s40471-020-00258-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Purpose of review In this review, we provide essential background knowledge and an analytical framework for the application of placental-fetal molecular biomarkers in fetal origins chronic disease epidemiology. The widely available and highly quantitative placental hormone human chorionic gonadotropin (hCG) is used as an example. hCG is currently used for diagnosing fetal genetic disorders; yet it can and should be expanded to understanding the fetal origins of chronic diseases. We provide justification and methods to do this. Recent findings Ten papers published in the last 5 years were identified with supportive findings relevant to the application of biomarkers of hCG in epidemiologic studies on the developmental origins of health and disease (DOHaD). Summary There is increasing and consistent evidence that placental-fetal biomarkers may be highly informative in observational studies, as exemplified by hCG, with the correct approaches for measurement and data analysis.
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Affiliation(s)
- Jennifer J Adibi
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health
| | - Alexander J Layden
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health
| | - Qing Yin
- Department of Biostatistics, University of Pittsburgh Graduate School of Public Health
| | - Xiaoshuang Xun
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health
| | - Shyamal Peddada
- Department of Biostatistics, University of Pittsburgh Graduate School of Public Health
| | - Rahel L Birru
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health
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Rizzuto D, Grande G, Bellavia A. Air Pollution, Cardiovascular Disease, and Dementia-Reply. JAMA Neurol 2020; 77:1581-1582. [PMID: 33165589 DOI: 10.1001/jamaneurol.2020.4312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Debora Rizzuto
- Aging Research Center, Department of Neurobiology, Care Science and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.,Stockholm Gerontology Research Center (Äldrecentrum), Stockholm, Sweden
| | - Giulia Grande
- Aging Research Center, Department of Neurobiology, Care Science and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Andrea Bellavia
- Intitute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
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Jérolon A, Baglietto L, Birmelé E, Alarcon F, Perduca V. Causal mediation analysis in presence of multiple mediators uncausally related. Int J Biostat 2020; 17:191-221. [PMID: 32990647 DOI: 10.1515/ijb-2019-0088] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 08/06/2020] [Indexed: 11/15/2022]
Abstract
Mediation analysis aims at disentangling the effects of a treatment on an outcome through alternative causal mechanisms and has become a popular practice in biomedical and social science applications. The causal framework based on counterfactuals is currently the standard approach to mediation, with important methodological advances introduced in the literature in the last decade, especially for simple mediation, that is with one mediator at the time. Among a variety of alternative approaches, Imai et al. showed theoretical results and developed an R package to deal with simple mediation as well as with multiple mediation involving multiple mediators conditionally independent given the treatment and baseline covariates. This approach does not allow to consider the often encountered situation in which an unobserved common cause induces a spurious correlation between the mediators. In this context, which we refer to as mediation with uncausally related mediators, we show that, under appropriate hypothesis, the natural direct and joint indirect effects are non-parametrically identifiable. Moreover, we adopt the quasi-Bayesian algorithm developed by Imai et al. and propose a procedure based on the simulation of counterfactual distributions to estimate not only the direct and joint indirect effects but also the indirect effects through individual mediators. We study the properties of the proposed estimators through simulations. As an illustration, we apply our method on a real data set from a large cohort to assess the effect of hormone replacement treatment on breast cancer risk through three mediators, namely dense mammographic area, nondense area and body mass index.
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Affiliation(s)
- Allan Jérolon
- Laboratoire MAP5 (UMR CNRS 8145), Université de Paris, Paris, Île-de-France, France
| | - Laura Baglietto
- Department of Clinical and Experimental Medicine, Università di Pisa, Pisa, Italy
| | - Etienne Birmelé
- Laboratoire MAP5 (UMR CNRS 8145), Université de Paris, Paris, Île-de-France, France
| | - Flora Alarcon
- Laboratoire MAP5 (UMR CNRS 8145), Université de Paris, Paris, Île-de-France, France
| | - Vittorio Perduca
- Laboratoire MAP5 (UMR CNRS 8145), Université de Paris, Paris, Île-de-France, France
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Chihuri S, Li G. Direct and indirect effects of marijuana use on the risk of fatal 2-vehicle crash initiation. Inj Epidemiol 2020; 7:49. [PMID: 32921302 PMCID: PMC7488993 DOI: 10.1186/s40621-020-00276-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 08/19/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Marijuana and alcohol each play a significant role in fatal crash initiation. We decomposed the total effect of marijuana use in the presence or absence of alcohol on fatal crash initiation into direct and indirect effects. METHODS Pair-matched data on 5856 culpable drivers (initiators) and 5856 nonculpable drivers (noninitiators) involved in the same fatal 2-vehicle crashes recorded in the Fatality Analysis Reporting System between 2011 and 2016 were analyzed using the conditional logistic regression model and the unified mediation and interaction analysis framework. RESULTS Crash initiators were more likely than noninitiators to test positive for marijuana (16.1% vs. 9.2%, P < 0.001), alcohol (28.6% vs. 9.7%, P < 0.001) and both substances (6.3% vs. 1.6%, P < .0001). Adjusted odds ratios of fatal 2-vehicle crash initiation revealed a positive interaction on the additive scale between marijuana and alcohol. Of the total effect of marijuana use on fatal 2-vehicle crash initiation, 68.8% was attributable to the direct effect (51.5% to controlled direct effect and 17.3% to reference interaction effect with alcohol) and 31.2% to the indirect effect (7.8% to mediated interaction effect and 23.4% to pure indirect effect through alcohol). CONCLUSION Our results indicate that the increased odds of fatal 2-vehicle crash initiation associated with marijuana use is due mainly to the direct effect.
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Affiliation(s)
- Stanford Chihuri
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, 622 West 168th St, PH5-505, New York, NY 10032 USA
| | - Guohua Li
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, 622 West 168th St, PH5-505, New York, NY 10032 USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, 622 West 168th St, PH5-505, New York, NY 10032 USA
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Filippini T, Tesauro M, Fiore M, Malagoli C, Consonni M, Violi F, Iacuzio L, Arcolin E, Oliveri Conti G, Cristaldi A, Zuccarello P, Zucchi E, Mazzini L, Pisano F, Gagliardi I, Patti F, Mandrioli J, Ferrante M, Vinceti M. Reply to Comment on "Environmental and Occupational Risk Factors of Amyotrophic Lateral Sclerosis: A Population-Based Case-Control Study". INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17186492. [PMID: 32906597 PMCID: PMC7559024 DOI: 10.3390/ijerph17186492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 08/27/2020] [Indexed: 11/16/2022]
Abstract
We much appreciate the positive comments and interest concerning our study on the environmental and occupational risk factors of amyotrophic lateral sclerosis (ALS) [...].
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Affiliation(s)
- Tommaso Filippini
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
- Correspondence:
| | - Marina Tesauro
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy; (M.T.); (M.C.)
| | - Maria Fiore
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Carlotta Malagoli
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
| | - Michela Consonni
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy; (M.T.); (M.C.)
| | - Federica Violi
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
- Azienda USL-IRCCS di Reggio Emilia, 42122 Reggio Emilia, Italy
| | - Laura Iacuzio
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
- Department of Public Health, Local Health Unit, 41121 Modena, Italy
| | - Elisa Arcolin
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
| | - Gea Oliveri Conti
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Antonio Cristaldi
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Pietro Zuccarello
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Elisabetta Zucchi
- Neurology Unit, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy;
| | - Letizia Mazzini
- ALS Centre Department of Neurology, ‘Maggiore della Carità’ University Hospital, 28100 Novara, Italy; (L.M.); (I.G.)
| | - Fabrizio Pisano
- Neurological Rehabilitation Division, Policlinico San Marco di Zingonia, 24046 Zingonia (BG), Italy;
| | - Ileana Gagliardi
- ALS Centre Department of Neurology, ‘Maggiore della Carità’ University Hospital, 28100 Novara, Italy; (L.M.); (I.G.)
| | - Francesco Patti
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Jessica Mandrioli
- Neurology Unit, Department of Neuroscience, S. Agostino Estense Hospital, Azienda Ospedaliero Universitaria di Modena, 41126 Modena, Italy;
| | - Margherita Ferrante
- Department of Medical, Surgical Sciences and Advanced Technologies “G. F. Ingrassia”, Catania University, 95123 Catania, Italy; (M.F.); (G.O.C.); (A.C.); (P.Z.); (F.P.); (M.F.)
| | - Marco Vinceti
- CREAGEN-Environmental, Genetic and Nutritional Epidemiology Research Center, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (C.M.); (F.V.); (L.I.); (E.A.); (M.V.)
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
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Doré I, Sylvester B, Sabiston C, Sylvestre MP, O’Loughlin J, Brunet J, Bélanger M. Mechanisms underpinning the association between physical activity and mental health in adolescence: a 6-year study. Int J Behav Nutr Phys Act 2020; 17:9. [PMID: 32005251 PMCID: PMC6993479 DOI: 10.1186/s12966-020-0911-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 01/09/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Physical activity (PA) can promote mental health, but the mechanisms underpinning this association are not well-established. This study examined if perceptions of three basic psychological needs (autonomy, competence, relatedness) and moderate-to-vigorous physical activity (MVPA) mediate the association between number of years participating in PA and mental health in adolescence. METHODS Participants included 937 children (55% female) age 10-11 at inception of the longitudinal MATCH study, who provided data every 4 months over 6 years. Mediation analyses were used to assess the natural direct effect of number of years of PA participation (cycles 1-15) during late childhood and adolescence on later mental health (cycle 16), measured with the Mental Health Continuum-Short Form (MHC-SF), and the natural indirect effect through each of self-perceived autonomy, competence and relatedness, and self-report MVPA (cycle 15). RESULTS In single mediator models, indirect effects of autonomy, competence, relatedness and self-report MVPA were statistically significant. In joint mediation models (each of three models including one basic psychological need and MVPA), autonomy, competence and relatedness mediated 71, 27, and 51% of the association respectively; MVPA mediated 27-31% of the association. In the mediation model including all four mediators, relatedness mediated the largest proportion of the association, followed by autonomy and MVPA. CONCLUSION Results support developing strategies to encourage adolescents to engage and remain involved in PA. This could foster perceptions of autonomy, competence, and relatedness as well as MVPA, which in turn may enhance mental health.
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Affiliation(s)
- Isabelle Doré
- School of Kinesiology and Physical Activity Sciences, Faculty of Medicine, Université de Montréal, Montréal, Québec Canada
- CHUM Research Centre, Montréal, Québec Canada
| | | | | | - Marie-Pierre Sylvestre
- CHUM Research Centre, Montréal, Québec Canada
- Université de Montréal, Montréal, Québec Canada
| | - Jennifer O’Loughlin
- CHUM Research Centre, Montréal, Québec Canada
- Université de Montréal, Montréal, Québec Canada
| | | | - Mathieu Bélanger
- Université de Sherbrooke, Moncton, New Brunswick Canada
- Centre de formation médicale du Nouveau-Brunswick, Moncton, New Brunswick Canada
- Research Services, Vitalité Health Network, Moncton, New Brunswick Canada
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Bellavia A, James-Todd T, Williams PL. Approaches for incorporating environmental mixtures as mediators in mediation analysis. ENVIRONMENT INTERNATIONAL 2019; 123:368-374. [PMID: 30572168 PMCID: PMC6367715 DOI: 10.1016/j.envint.2018.12.024] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 12/10/2018] [Accepted: 12/12/2018] [Indexed: 05/21/2023]
Abstract
Mediation analysis offers an essential and rapidly expanding tool in environmental health studies to investigate the contribution of environmental factors towards observed associations between risk factors and health outcomes. When evaluating environmental factors, there may be particular interest in quantifying the impact of exposure to environmental mixtures on human health. In this context, evaluating the joint effect of multiple chemicals or pollutants, rather than individual examination, allows accurate identification of risk factors, assessment of interactions, and ultimately development of more targeted public health interventions. While mediation analysis has been extended to incorporate several methodological complexities specific to environmental factors, little attention has been given to integrating the analysis of environmental mixtures. The aim of this review is to present some of the available methods for environmental mixtures, and discuss how these methods can be integrated within a mediation analysis framework. By incorporating these methods into a mediation framework, investigators will be able to evaluate the contribution of environmental mixtures as mediators of exposure-outcome associations, based on methodologies that are currently available. While standard regression-based methods for multiple mediators can be used, these can easily become unstable as the number of mixture components increases. Summary and classification methods, or hierarchical modeling, can reduce the number of mediators by creating scores or possibly uncorrelated subgroups. This approach allows retrieving indirect effects due to the mixture or to a specific subgroup, but makes identification of component-specific effects and interactions complicated. Finally, one can use various approaches for analyzing mixtures in a two-stage fashion, selecting relevant mediators to be included in the final model. We focused this review on techniques that have been presented to the environmental health community and that can be conducted with major statistical software. We encourage researchers to move beyond the evaluation of one environmental factor at a time to the assessment of the joint effects of environmental mixtures when a mediation model is of interest. Available methods target different aspects related to environmental mixtures and the choice of the suitable approach will depend on data structures and the research question of interest.
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Affiliation(s)
- Andrea Bellavia
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America.
| | - Tamarra James-Todd
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America; Division of Women's Health, Department of Medicine, Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, United States of America
| | - Paige L Williams
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America
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Methods for analytic intercategorical intersectionality in quantitative research: Discrimination as a mediator of health inequalities. Soc Sci Med 2019; 226:236-245. [PMID: 30674435 DOI: 10.1016/j.socscimed.2018.12.015] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 10/22/2018] [Accepted: 12/09/2018] [Indexed: 12/15/2022]
Abstract
RATIONALE Intersectionality as a theoretical framework has gained prominence in qualitative research on social inequity. Intercategorical quantitative applications have focused primarily on describing health or social inequalities across intersectional groups, coded using cross-classified categories or interaction terms. This descriptive intersectionality omits consideration of the mediating processes (e.g., discrimination) through which intersectional positions impact outcome inequalities, which offer opportunities for intervention. OBJECTIVE We argue for the importance of a quantitative analytic intersectionality. We identify methodological challenges and potential solutions in structuring studies to allow for both intersectional heterogeneity in outcomes and in the ways that processes such as discrimination may cause these outcomes for those at different intersections. METHOD To incorporate both mediation and exposure-mediator interaction, we use VanderWeele's three-way decomposition methodology, adapt the interpretation for application to analytic intersectionality studies, and present a step-by-step analytic approach. Using online panel data collected from Canada and the United States in 2016 (N = 2542), we illustrate this approach with a statistical analysis of whether and to what extent observed inequalities in psychological distress across intersections of ethnoracial group and sexual or gender minority (SGM) status may be explained by past-year experiences of day-to-day discrimination, assessed using the Intersectional Discrimination Index (InDI). RESULTS AND CONCLUSIONS We describe actual and adjusted intersectional inequalities in psychological distress and decompose them to identify three component effects for each of 11 intersectional comparison groups (e.g., Indigenous SGM), versus the reference intersectional group that experienced the lowest levels of discrimination (white non-SGM). These reflect the expected inequality in outcome: 1) due to membership in the more discriminated-against group, if its members had experienced the same lower levels of discrimination as the reference intersection; 2) due to unequal levels of discrimination; and 3), due to unequal effects of discrimination. We present considerations for use and interpretation of these methods.
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Bean CG, Pingel R, Hallqvist J, Berg N, Hammarström A. Poor peer relations in adolescence, social support in early adulthood, and depressive symptoms in later adulthood—evaluating mediation and interaction using four-way decomposition analysis. Ann Epidemiol 2019; 29:52-59. [DOI: 10.1016/j.annepidem.2018.10.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Revised: 10/12/2018] [Accepted: 10/20/2018] [Indexed: 10/28/2022]
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Momen M, Ayatollahi Mehrgardi A, Amiri Roudbar M, Kranis A, Mercuri Pinto R, Valente BD, Morota G, Rosa GJM, Gianola D. Including Phenotypic Causal Networks in Genome-Wide Association Studies Using Mixed Effects Structural Equation Models. Front Genet 2018; 9:455. [PMID: 30356716 PMCID: PMC6189326 DOI: 10.3389/fgene.2018.00455] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 09/18/2018] [Indexed: 12/21/2022] Open
Abstract
Network based statistical models accounting for putative causal relationships among multiple phenotypes can be used to infer single-nucleotide polymorphism (SNP) effect which transmitting through a given causal path in genome-wide association studies (GWAS). In GWAS with multiple phenotypes, reconstructing underlying causal structures among traits and SNPs using a single statistical framework is essential for understanding the entirety of genotype-phenotype maps. A structural equation model (SEM) can be used for such purposes. We applied SEM to GWAS (SEM-GWAS) in chickens, taking into account putative causal relationships among breast meat (BM), body weight (BW), hen-house production (HHP), and SNPs. We assessed the performance of SEM-GWAS by comparing the model results with those obtained from traditional multi-trait association analyses (MTM-GWAS). Three different putative causal path diagrams were inferred from highest posterior density (HPD) intervals of 0.75, 0.85, and 0.95 using the inductive causation algorithm. A positive path coefficient was estimated for BM → BW, and negative values were obtained for BM → HHP and BW → HHP in all implemented scenarios. Further, the application of SEM-GWAS enabled the decomposition of SNP effects into direct, indirect, and total effects, identifying whether a SNP effect is acting directly or indirectly on a given trait. In contrast, MTM-GWAS only captured overall genetic effects on traits, which is equivalent to combining the direct and indirect SNP effects from SEM-GWAS. Although MTM-GWAS and SEM-GWAS use the similar probabilistic models, we provide evidence that SEM-GWAS captures complex relationships in terms of causal meaning and mediation and delivers a more comprehensive understanding of SNP effects compared to MTM-GWAS. Our results showed that SEM-GWAS provides important insight regarding the mechanism by which identified SNPs control traits by partitioning them into direct, indirect, and total SNP effects.
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Affiliation(s)
- Mehdi Momen
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | | | - Mahmoud Amiri Roudbar
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Andreas Kranis
- Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
| | - Renan Mercuri Pinto
- Department of Exact Sciences, University of São Paulo-Escola Superior de Agricultura Luiz de Queiroz, Piracicaba, Brazil.,Department of Animal Sciences, University of Wisconsin, Madison, WI, United States
| | - Bruno D Valente
- Department of Animal Sciences, University of Wisconsin, Madison, WI, United States
| | - Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States
| | - Guilherme J M Rosa
- Department of Animal Sciences, University of Wisconsin, Madison, WI, United States.,Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, United States
| | - Daniel Gianola
- Department of Animal Sciences, University of Wisconsin, Madison, WI, United States.,Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, United States.,Department of Dairy Science, University of Wisconsin, Madison, WI, United States
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Almquist YB, Jackisch J, Forsman H, Gauffin K, Vinnerljung B, Hjern A, Brännström L. A decade lost: does educational success mitigate the increased risks of premature death among children with experience of out-of-home care? J Epidemiol Community Health 2018; 72:997-1002. [PMID: 30018058 PMCID: PMC6227815 DOI: 10.1136/jech-2018-210487] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 06/14/2018] [Accepted: 06/19/2018] [Indexed: 11/15/2022]
Abstract
Background Past research has consistently identified children with out-of-home care (OHC) experience as a high-risk group for premature mortality. While many have argued that educational success is a key factor in reducing these individuals’ excessive death risks, empirical evidence has hitherto been limited. The aim of the current study was therefore to examine the potentially mitigating role of educational success in the association between OHC experience and premature mortality. Methods Drawing on a Stockholm cohort born in 1953 (n=15 117), we analysed the associations among placement in OHC (ages 0–12), school performance (ages 13, 16 and 19) and premature all-cause mortality (ages 20–56) by means of Cox and Laplace regression analyses. Results The Cox regression models confirmed the increased risk of premature mortality among individuals with OHC experience. Unadjusted Laplace regression models showed that, based on median survival time, these children died more than a decade before their majority population peers. However, among individuals who performed well at school, that is, those who scored above-average marks at the age of 16 (grade 9) and at the age of 19 (grade 12), the risks of premature mortality did not significantly differ between the two groups. Conclusion Educational success seems to mitigate the increased risks of premature death among children with OHC experience.
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Affiliation(s)
- Ylva B Almquist
- Department of Public Health Sciences, Centre for Health Equity Studies (CHESS), Stockholm University, Stockholm, Sweden
| | - Josephine Jackisch
- Department of Public Health Sciences, Centre for Health Equity Studies (CHESS), Stockholm University, Stockholm, Sweden
| | - Hilma Forsman
- Department of Social Work, Stockholm University, Stockholm, Sweden
| | - Karl Gauffin
- Department of Public Health Sciences, Centre for Health Equity Studies (CHESS), Stockholm University, Stockholm, Sweden
| | - Bo Vinnerljung
- Department of Social Work, Stockholm University, Stockholm, Sweden
| | - Anders Hjern
- Department of Public Health Sciences, Centre for Health Equity Studies (CHESS), Stockholm University, Stockholm, Sweden
| | - Lars Brännström
- Department of Social Work, Stockholm University, Stockholm, Sweden
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Zou X, Zhu Y, Jackson JW, Bellavia A, Fitzmaurice GM, Centorrino F, Valeri L. The role of PANSS symptoms and adverse events in explaining the effects of paliperidone on social functioning: a causal mediation analysis approach. NPJ SCHIZOPHRENIA 2018; 4:13. [PMID: 29950691 PMCID: PMC6021395 DOI: 10.1038/s41537-018-0054-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 03/24/2018] [Accepted: 05/14/2018] [Indexed: 11/09/2022]
Abstract
To date, no study has evaluated the joint role of symptoms and adverse events as mediators of the effect of second-generation antipsychotics on patients' social functioning. We used recently developed methods for mediation analysis with multiple mediators to clarify the interplay of adverse events and symptoms in explaining the effects of paliperidone (R code for implementing the mediation analysis for multiple mediators is provided). We used data from 490 participants in a 6-week randomized dose-response trial that assigned three fixed dosages of ER OROS paliperidone (3, 9, and 15 mg/day). The primary outcome was an individual's score on the social performance scale assessed after 6 weeks. The sum of Positive and Negative Syndrome Scale (PANSS), weight gain, and extrapyramidal symptoms measured via the Simpson-Angus Scale after 5 weeks were investigated as potential mediators and effect modifiers of treatment effects. Results from mediation analyses showed that the improvements in social functioning are partly explained by reduction in PANSS symptoms. Suggestive evidence that adverse events could play a role as mediators was found. In particular, weight gain displayed a non-linear relationship with social functioning, whereby beneficial effects observed at small levels of weight gain were reduced in the presence of excessive weight gain. In conclusion, we found that the short-term effects of paliperidone on social functioning were dependent on the successful reduction in PANSS symptoms and possibly the occurrence of excessive weight gain, thus suggesting future directions for treatment and interventions.
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Affiliation(s)
- Xue Zou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yiwen Zhu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - John W Jackson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andrea Bellavia
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Garrett M Fitzmaurice
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, USA
| | | | - Linda Valeri
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, USA.
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Bellavia A, Zota AR, Valeri L, James-Todd T. Multiple mediators approach to study environmental chemicals as determinants of health disparities. Environ Epidemiol 2018; 2:e015. [PMID: 31531412 PMCID: PMC6748334 DOI: 10.1097/ee9.0000000000000015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 04/17/2018] [Indexed: 11/26/2022] Open
Abstract
A major goal of health disparities research is to identify and intervene upon modifiable risk factors that help explain the observed associations between social factors and adverse health outcomes. To this end, statistical methods incorporating mediation analysis have shown promise, as they quantify the contribution of an intermediate variable in an exposure-outcome association. A growing body of literature suggests that environmental chemicals can contribute to health disparities. However, evaluating environmental chemicals as an important component of health disparities introduces methodological complexities that may make standard mediation approaches inadequate. Specific to environmental health is the issue of evaluating both the source and biomarker of the environmental toxicant in order to calculate the proportion of the disparity that would remain had we intervened on the modifiable factors. Recent methodological developments on multiple mediators can improve efforts to integrate both source and biomarker of exposure into epidemiological studies of health disparities. We illustrate a conceptual framework and present how mediation techniques can be used to address environmental health disparities questions. With this, we provide a methodological tool that has the potential to advance this growing field, while simultaneously informing public health prevention and policy surrounding the impact of environmental factors on health disparities.
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Affiliation(s)
- Andrea Bellavia
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Ami R. Zota
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC
| | - Linda Valeri
- Psychiatric Biostatistics Laboratory, McLean Hospital, Belmont, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Tamarra James-Todd
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Division of Women’s Health, Department of Medicine, Connors Center for Women’s Health and Gender Biology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
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