Literature DB >> 25668685

Attenuation of exposure-response rate ratios at higher exposures: a simulation study focusing on frailty and measurement error.

Kyle Steenland1, Conny Karnes, Lyndsey Darrow, Vaughn Barry.   

Abstract

BACKGROUND: Positive exposure-response trends for rate ratios (RRs) often diminish at higher exposures. Depletion of susceptibles with higher exposure and increased measurement error at higher exposures are possible reasons.
METHODS: We conducted simulations to investigate attenuation under various assumptions about susceptibility to exposure effects and measurement error, considering a hypothetical occupational cohort, using an excess relative risk model. We simulated an occupational cohort in which entry occurred over time. The metric of interest was cumulative exposure, which had a strong linear effect (RR = 4 for mean exposure), maximizing potential depletion. Measurement error of both classical and Berkson types was also simulated, increasing with increasing exposure. We conducted 100 simulations per scenario, each with 25,000 subjects enrolled from years 1940 to 2010, followed through 2010.
RESULTS: With less than 100% susceptibility to exposure (a requirement for depletion), there was only modest evidence of depletion of susceptibles with increasing cumulative exposure distributed normally. There was correspondingly little attenuation of RRs, and linear exposure-response models fit well. Adding classical measurement error to cumulative exposure, increasing with increasing exposure, resulted in some modest attenuation. Using log normal instead of normally distributed cumulative exposure also resulted in some attenuation.
CONCLUSIONS: Strong attenuation of relatively strong linear exposure-response trends using cumulative exposure, with relatively common disease and heterogeneous susceptibility, does not appear likely due to depletion of susceptibles. Strong attenuation seems more likely to be due to other mechanisms.

Entities:  

Mesh:

Year:  2015        PMID: 25668685     DOI: 10.1097/EDE.0000000000000259

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  4 in total

1.  Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models.

Authors:  Sabine Hoffmann; Dominique Laurier; Estelle Rage; Chantal Guihenneuc; Sophie Ancelet
Journal:  PLoS One       Date:  2018-02-06       Impact factor: 3.240

2.  Exposure measurement error in air pollution studies: A framework for assessing shared, multiplicative measurement error in ensemble learning estimates of nitrogen oxides.

Authors:  Mariam S Girguis; Lianfa Li; Fred Lurmann; Jun Wu; Robert Urman; Edward Rappaport; Carrie Breton; Frank Gilliland; Daniel Stram; Rima Habre
Journal:  Environ Int       Date:  2019-02-01       Impact factor: 9.621

3.  Urinary arsenic and heart disease mortality in NHANES 2003-2014.

Authors:  Anne E Nigra; Katherine A Moon; Miranda R Jones; Tiffany R Sanchez; Ana Navas-Acien
Journal:  Environ Res       Date:  2021-06-06       Impact factor: 8.431

4.  Consequences of Depletion of Susceptibles for Hazard Ratio Estimators Based on Propensity Scores.

Authors:  Bruce Fireman; Susan Gruber; Zilu Zhang; Robert Wellman; Jennifer Clark Nelson; Jessica Franklin; Judith Maro; Catherine Rogers Murray; Sengwee Toh; Joshua Gagne; Sebastian Schneeweiss; Laura Amsden; Richard Wyss
Journal:  Epidemiology       Date:  2020-11       Impact factor: 4.860

  4 in total

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