메뉴 건너뛰기




Volumn 178, Issue 12, 2013, Pages 1681-1686

Causal inference in occupational epidemiology: Accounting for the healthy worker effect by using structural nested models

Author keywords

Causal inference; Healthy worker effect; Marginal structural models; Occupational epidemiology; Structural nested models

Indexed keywords

COHORT ANALYSIS; EMPIRICAL ANALYSIS; EPIDEMIOLOGY; OCCUPATIONAL EXPOSURE; SOFTWARE;

EID: 84890675733     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwt215     Document Type: Review
Times cited : (33)

References (40)
  • 1
    • 0028196995 scopus 로고
    • The evolving concept of the healthy worker survivor effect
    • Arrighi HM, Hertz-Picciotto I. The evolving concept of the healthy worker survivor effect. Epidemiology. 1994;5(2): 189-196.
    • (1994) Epidemiology. , vol.5 , Issue.2 , pp. 189-196
    • Arrighi, H.M.1    Hertz-Picciotto, I.2
  • 3
    • 84878536226 scopus 로고    scopus 로고
    • The healthy worker effect in cancer incidence studies
    • Kirkeleit J, Riise T, Bjørge T, et al. The healthy worker effect in cancer incidence studies. Am J Epidemiol. 2013;177(11): 1218-1224.
    • (2013) Am J Epidemiol. , vol.177 , Issue.11 , pp. 1218-1224
    • Kirkeleit, J.1    Riise, T.2    Bjørge, T.3
  • 4
    • 84890767522 scopus 로고    scopus 로고
    • Estimating the effect of cumulative occupational asbestos exposure on time to lung cancer mortality using structural nested failure time models to account for the healthy worker survivor bias
    • In press
    • Naimi AI, Cole SR, Hudgens MG, et al. Estimating the effect of cumulative occupational asbestos exposure on time to lung cancer mortality using structural nested failure time models to account for the healthy worker survivor bias. Epidemiology. In press.
    • Epidemiology
    • Naimi, A.I.1    Cole, S.R.2    Hudgens, M.G.3
  • 5
    • 84856939012 scopus 로고    scopus 로고
    • A comparison of standard methods with G-estimation of accelerated failure-time models to address the healthy-worker survivor effect: Application in a cohort of autoworkers exposed to metalworking fluids
    • Chevrier J, Picciotto S, Eisen EA. A comparison of standard methods with G-estimation of accelerated failure-time models to address the healthy-worker survivor effect: application in a cohort of autoworkers exposed to metalworking fluids. Epidemiology. 2012;23(2):212-219.
    • (2012) Epidemiology. , vol.23 , Issue.2 , pp. 212-219
    • Chevrier, J.1    Picciotto, S.2    Eisen, E.A.3
  • 6
    • 0017046116 scopus 로고
    • Low mortality rates in industrial cohort studies due to selection for work and survival in the industry
    • Fox AJ, Collier PF. Low mortality rates in industrial cohort studies due to selection for work and survival in the industry. Br J Prev Soc Med. 1976;30(4):225-230.
    • (1976) Br J Prev Soc Med. , vol.30 , Issue.4 , pp. 225-230
    • Fox, A.J.1    Collier, P.F.2
  • 7
    • 0017285868 scopus 로고
    • Standardized mortality ratios and the "healthy worker effect": Scratching beneath the surface
    • McMichael AJ. Standardized mortality ratios and the "healthy worker effect": scratching beneath the surface. J Occup Med. 1976;18(3):165-168.
    • (1976) J Occup Med. , vol.18 , Issue.3 , pp. 165-168
    • McMichael, A.J.1
  • 8
    • 46149139403 scopus 로고
    • A new approach to causal inference in mortality studies with a sustained exposure period-application to control of the healthy worker survivor effect
    • Robins JM. A new approach to causal inference in mortality studies with a sustained exposure period-application to control of the healthy worker survivor effect. Math Model. 1986;7(9-12):1393-1512.
    • (1986) Math Model. , vol.7 , Issue.9-12 , pp. 1393-1512
    • Robins, J.M.1
  • 10
    • 0027515256 scopus 로고
    • Definitions, sources, magnitude, effect modifiers, and strategies of reduction of the healthy worker effect
    • Arrighi HM, Hertz-Picciotto I. Definitions, sources, magnitude, effect modifiers, and strategies of reduction of the healthy worker effect. J Occup Med. 1993;35(9):890-892.
    • (1993) J Occup Med. , vol.35 , Issue.9 , pp. 890-892
    • Arrighi, H.M.1    Hertz-Picciotto, I.2
  • 11
    • 0029683682 scopus 로고    scopus 로고
    • Controlling the healthy worker survivor effect: An example of arsenic exposure and respiratory cancer
    • Arrighi HM, Hertz-Picciotto I. Controlling the healthy worker survivor effect: an example of arsenic exposure and respiratory cancer. Occup Environ Med. 1996;53(7):455-462.
    • (1996) Occup Environ Med. , vol.53 , Issue.7 , pp. 455-462
    • Arrighi, H.M.1    Hertz-Picciotto, I.2
  • 12
    • 0018367005 scopus 로고
    • An analysis of the mortality of workers in a nuclear facility
    • Gilbert ES, Marks S. An analysis of the mortality of workers in a nuclear facility. Radiat Res. 1979;79(1):122-148.
    • (1979) Radiat Res. , vol.79 , Issue.1 , pp. 122-148
    • Gilbert, E.S.1    Marks, S.2
  • 13
    • 0019943175 scopus 로고
    • Some confounding factors in the study of mortality and occupational exposures
    • Gilbert ES. Some confounding factors in the study of mortality and occupational exposures. Am J Epidemiol. 1982;116(1): 177-188.
    • (1982) Am J Epidemiol. , vol.116 , Issue.1 , pp. 177-188
    • Gilbert, E.S.1
  • 14
    • 77956888769 scopus 로고
    • Causal diagrams for empirical research
    • Pearl J. Causal diagrams for empirical research. Biometrika. 1995;82(4):669-688.
    • (1995) Biometrika. , vol.82 , Issue.4 , pp. 669-688
    • Pearl, J.1
  • 16
    • 84877966202 scopus 로고    scopus 로고
    • Assessing the component associations of the healthy worker survivor bias: Occupational asbestos exposure and lung cancer mortality
    • Naimi AI, Cole S, Hudgens M, et al. Assessing the component associations of the healthy worker survivor bias: occupational asbestos exposure and lung cancer mortality. Ann Epidemiol. 2013;23(6):334-341.
    • (2013) Ann Epidemiol. , vol.23 , Issue.6 , pp. 334-341
    • Naimi, A.I.1    Cole, S.2    Hudgens, M.3
  • 17
    • 0038334174 scopus 로고    scopus 로고
    • Quantifying biases in causal models: Classical confounding vs collider-stratification bias
    • Greenland S. Quantifying biases in causal models: classical confounding vs collider-stratification bias. Epidemiology. 2003;14(3):300-306.
    • (2003) Epidemiology. , vol.14 , Issue.3 , pp. 300-306
    • Greenland, S.1
  • 18
    • 77952717253 scopus 로고    scopus 로고
    • Illustrating bias due to conditioning on a collider
    • Cole SR, Platt RW, Schisterman EF, et al. Illustrating bias due to conditioning on a collider. Int J Epidemiol. 2010;39(2): 417-420.
    • (2010) Int J Epidemiol. , vol.39 , Issue.2 , pp. 417-420
    • Cole, S.R.1    Platt, R.W.2    Schisterman, E.F.3
  • 19
    • 0033839024 scopus 로고    scopus 로고
    • Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men
    • Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology. 2000;11(5): 561-570.
    • (2000) Epidemiology. , vol.11 , Issue.5 , pp. 561-570
    • Hernán, M.A.1    Brumback, B.2    Robins, J.M.3
  • 20
    • 0033847784 scopus 로고    scopus 로고
    • Marginal structural models and causal inference in epidemiology
    • Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550-560.
    • (2000) Epidemiology. , vol.11 , Issue.5 , pp. 550-560
    • Robins, J.M.1    Hernán, M.A.2    Brumback, B.3
  • 21
    • 77950467310 scopus 로고    scopus 로고
    • Relation between three classes of structural models for the effect of a timevarying exposure on survival
    • Young JG, Hernán MA, Picciotto S, et al. Relation between three classes of structural models for the effect of a timevarying exposure on survival. Lifetime Data Anal. 2010;16(1): 71-84.
    • (2010) Lifetime Data Anal. , vol.16 , Issue.1 , pp. 71-84
    • Young, J.G.1    Hernán, M.A.2    Picciotto, S.3
  • 22
    • 84920420698 scopus 로고
    • Statistics and causal inference
    • Holland PW. Statistics and causal inference. J Am Stat Assoc. 1986;81(396):945-960.
    • (1986) J Am Stat Assoc. , vol.81 , Issue.396 , pp. 945-960
    • Holland, P.W.1
  • 23
    • 74549138178 scopus 로고    scopus 로고
    • Concerning the consistency assumption in causal inference
    • Vander Weele TJ. Concerning the consistency assumption in causal inference. Epidemiology. 2009;20(6):880-883.
    • (2009) Epidemiology. , vol.20 , Issue.6 , pp. 880-883
    • Vander Weele, T.J.1
  • 24
    • 84862907581 scopus 로고    scopus 로고
    • Diagnosing and responding to violations in the positivity assumption
    • Petersen ML, Porter KE, Gruber S, et al. Diagnosing and responding to violations in the positivity assumption. Stat Methods Med Res. 2012;21(1):31-54.
    • (2012) Stat Methods Med Res. , vol.21 , Issue.1 , pp. 31-54
    • Petersen, M.L.1    Porter, K.E.2    Gruber, S.3
  • 25
    • 49549090865 scopus 로고    scopus 로고
    • Toward causal inference with interference
    • Hudgens MG, Halloran ME. Toward causal inference with interference. J Am Stat Assoc. 2008;103(482):832-842.
    • (2008) J Am Stat Assoc. , vol.103 , Issue.482 , pp. 832-842
    • Hudgens, M.G.1    Halloran, M.E.2
  • 26
    • 0022973522 scopus 로고
    • Identifiability, exchangeability, and epidemiological confounding
    • Greenland S, Robins J. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol. 1986;15(3): 413-419.
    • (1986) Int J Epidemiol. , vol.15 , Issue.3 , pp. 413-419
    • Greenland, S.1    Robins, J.2
  • 27
    • 34548438170 scopus 로고    scopus 로고
    • Causal mediation analyses with rank preserving models
    • Have TR, Joffe MM, Lynch KG, et al. Causal mediation analyses with rank preserving models. Biometrics. 2007;63(3): 926-934.
    • (2007) Biometrics. , vol.63 , Issue.3 , pp. 926-934
    • Have, T.R.1    Joffe, M.M.2    Lynch, K.G.3
  • 28
    • 70349130001 scopus 로고    scopus 로고
    • Identifiability, exchangeability and confounding revisited
    • Greenland S, Robins J. Identifiability, exchangeability and confounding revisited. Epidemiol Perspect Innov. 2009;6(1):4.
    • (2009) Epidemiol Perspect Innov. , vol.6 , Issue.1 , pp. 4
    • Greenland, S.1    Robins, J.2
  • 29
    • 84856810963 scopus 로고    scopus 로고
    • Structural nested models, G-estimation, and the healthy worker effect: The promise (mostly unrealized) and the pitfalls
    • Joffe MM. Structural nested models, G-estimation, and the healthy worker effect: the promise (mostly unrealized) and the pitfalls. Epidemiology. 2012;23(2):220-222.
    • (2012) Epidemiology. , vol.23 , Issue.2 , pp. 220-222
    • Joffe, M.M.1
  • 30
    • 80051552334 scopus 로고    scopus 로고
    • A comparison of methods to estimate the hazard ratio under conditions of timevarying confounding and nonpositivity
    • Naimi AI, Cole SR, Westreich DJ, et al. A comparison of methods to estimate the hazard ratio under conditions of timevarying confounding and nonpositivity. Epidemiology. 2011;22(5):718-723.
    • (2011) Epidemiology. , vol.22 , Issue.5 , pp. 718-723
    • Naimi, A.I.1    Cole, S.R.2    Westreich, D.J.3
  • 31
    • 79960565984 scopus 로고    scopus 로고
    • Quantification of the healthy worker effect: A nationwide cohort study among electricians in Denmark
    • Thygesen L, Hvidtfeldt U, Mikkelsen S, et al. Quantification of the healthy worker effect: a nationwide cohort study among electricians in Denmark. BMC Public Health. 2010; 11(1):571.
    • (2010) BMC Public Health. , vol.11 , Issue.1 , pp. 571
    • Thygesen, L.1    Hvidtfeldt, U.2    Mikkelsen, S.3
  • 32
    • 84882456860 scopus 로고    scopus 로고
    • Work related asthma. A causal analysis controlling the healthy worker effect
    • Dumas O, Le Moual N, Siroux V, et al. Work related asthma. A causal analysis controlling the healthy worker effect. Occup Environ Med. 2013;70(9):603-610.
    • (2013) Occup Environ Med. , vol.70 , Issue.9 , pp. 603-610
    • Dumas, O.1    Le Moual, N.2    Siroux, V.3
  • 33
    • 85056259802 scopus 로고    scopus 로고
    • Estimation of the causal effects of time-varying exposures
    • In: Fitzmaurice G, Davidian M, Verbeke G, et al, eds. Boca Raton, FL: Chapman & Hall
    • Robins J, Hernán M. Estimation of the causal effects of time-varying exposures. In: Fitzmaurice G, Davidian M, Verbeke G, et al, eds. Advances in Longitudinal Data Analysis. Boca Raton, FL: Chapman & Hall; 2009:553-599.
    • (2009) Advances in Longitudinal Data Analysis , pp. 553-599
    • Robins, J.1    Hernán, M.2
  • 34
    • 84863991676 scopus 로고    scopus 로고
    • A simulation study of finite-sample properties of marginal structural Cox proportional hazards models
    • Westreich D, Cole SR, Schisterman EF, et al. A simulation study of finite-sample properties of marginal structural Cox proportional hazards models. Stat Med. 2012;31(19): 2098-2109.
    • (2012) Stat Med. , vol.31 , Issue.19 , pp. 2098-2109
    • Westreich, D.1    Cole, S.R.2    Schisterman, E.F.3
  • 35
    • 84877281930 scopus 로고    scopus 로고
    • Analysis of occupational asbestos exposure and lung cancer mortality using the G formula
    • Cole SR, Richardson DB, Chu H, et al. Analysis of occupational asbestos exposure and lung cancer mortality using the G formula. Am J Epidemiol. 2013;177(9):989-996.
    • (2013) Am J Epidemiol. , vol.177 , Issue.9 , pp. 989-996
    • Cole, S.R.1    Richardson, D.B.2    Chu, H.3
  • 36
    • 0002317236 scopus 로고    scopus 로고
    • Structural nested failure time models
    • In: Andersen P, Keiding N, eds. Chichester, United Kingdom: John Wiley and Sons
    • Robins JM. Structural nested failure time models. In: Andersen P, Keiding N, eds. The Encyclopedia of Biostatistics. Chichester, United Kingdom: John Wiley and Sons; 1998:4372-4389.
    • (1998) The Encyclopedia of Biostatistics , pp. 4372-4389
    • Robins, J.M.1
  • 37
    • 0027275180 scopus 로고
    • Estimating the causal effect of smoking cessation in the presence of confounding factors using a rank preserving structural failure time model
    • Mark SD, Robins JM. Estimating the causal effect of smoking cessation in the presence of confounding factors using a rank preserving structural failure time model. Stat Med. 1993;12(17): 1605-1628.
    • (1993) Stat Med. , vol.12 , Issue.17 , pp. 1605-1628
    • Mark, S.D.1    Robins, J.M.2
  • 38
    • 0032529330 scopus 로고    scopus 로고
    • G-estimation of causal effects: Isolated systolic hypertension and cardiovascular death in the framingham heart study
    • Witteman JC, D'Agostino RB, Stijnen T, et al. G-estimation of causal effects: isolated systolic hypertension and cardiovascular death in the Framingham Heart Study. Am J Epidemiol. 1998;148(4):390-401.
    • (1998) Am J Epidemiol. , vol.148 , Issue.4 , pp. 390-401
    • Witteman, J.C.1    D'Agostino, R.B.2    Stijnen, T.3
  • 40
    • 84858865220 scopus 로고    scopus 로고
    • G-estimation and artificial censoring: Problems, challenges, and applications
    • Joffe MM, Yang WP, Feldman H. G-estimation and artificial censoring: problems, challenges, and applications. Biometrics. 2012;68(1):275-286.
    • (2012) Biometrics. , vol.68 , Issue.1 , pp. 275-286
    • Joffe, M.M.1    Yang, W.P.2    Feldman, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.