Negative control exposure analysis is a very effective tool in evaluating the effect of unmeasured confounding in observational epidemiological studies. Several biases, including recall bias, time-varying confounding factors, measurement bias and so on, can affect the credibility of negative control exposure analysis for causal interpretations. The article focuses on the implications of differential measurement error across exposed group and negative controls to causal interpretations on negative control exposure analysis.
BrewBKGongTWilliamsDM, et al. Using fathers as a negative control exposure to test the Developmental Origins of Health and Disease hypothesis: a case study on maternal distress and offspring asthma using Swedish register data. Scand J Public Health2017;45:36–40.
2.
BaoWMichelsKBTobiasDK, et al. Parental smoking during pregnancy and the risk of gestational diabetes in the daughter. Int J Epidemiol2016;45:160–169.
3.
JulvezJRibas-FitóNTorrentM, et al. Maternal smoking habits and cognitive development of children at age 4 years in a population-based birth cohort. Int J Epidemiol2007;36:825–832.
4.
OgrodniczukJSOliffeJL.Men and depression. Can Fam Physician2011;57:153–155.
5.
SmithDTMouzonDMElliottM.Reviewing the assumptions about men’s mental health: an exploration of the gender binary. Am J Mens Health2018;12:78–89.
6.
SandersonEMacdonald-WallisCDavey SmithG.Negative control exposure studies in the presence of measurement error: implications for attempted effect estimate calibration. Int J Epidemiol2018;47:587–596.
7.
CochranSVRabinowitzFE.Gender-sensitive recommendations for assessment and treatment of depression in ME. Prof Psychol Res Pr2003;34:132–140.
8.
LipsitchMTchetgenECohenT.Negative controls: a tool for detecting confounding and bias in observational studies. Epidemiology2010;21:383–388.
