Overadjustment Bias and Unnecessary Adjustment in Epidemiologic Studies

Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjustment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size

Time-modified Confounding

According to the authors, time-modified confounding occurs when the causal relation between a time-fixed or time-varying confounder and the treatment or outcome changes over time. A key difference between previously described time-varying confounding and the proposed time-modified confounding is that, in the former, the values of the confounding variable change over time while, in the latter, the effects of the confounder change over time. Using marginal structural models, the authors propose an approach to account for time-modified confounding when the relation between the confounder and treatment is modified over time. An illustrative example and simulation show that, when time-modified confounding is present, a marginal structural model with inverse probability-of-treatment weights specified to account for time-modified confounding remains approximately unbiased with appropriate confidence limit coverage, while models that do not account for time-modified confounding are biased. Correct specification of the treatment model, including accounting for potential variation over time in confounding, is an important assumption of marginal structural models. When the effect of confounders on either the treatment or outcome changes over time, time-modified confounding should be considered

A simulation study of finite-sample properties of marginal structural Cox proportional hazards models

Motivated by a previously published study of HIV treatment, we simulated data subject to time-varying confounding affected by prior treatment to examine some finite-sample properties of marginal structural Cox proportional hazards models. We compared (a) unadjusted, (b) regression-adjusted, (c) unstabilized and (d) stabilized marginal structural (inverse probability-of-treatment [IPT] weighted) model estimators of effect in terms of bias, standard error, root mean squared error (MSE) and 95% confidence limit coverage over a range of research scenarios, including relatively small sample sizes and ten study assessments. In the base-case scenario resembling the motivating example, where the true hazard ratio was 0.5, both IPT-weighted analyses were unbiased while crude and adjusted analyses showed substantial bias towards and across the null. Stabilized IPT-weighted analyses remained unbiased across a range of scenarios, including relatively small sample size; however, the standard error was generally smaller in crude and adjusted models. In many cases, unstabilized weighted analysis showed a substantial increase in standard error compared to other approaches. Root MSE was smallest in the IPT-weighted analyses for the base-case scenario. In situations where time-varying confounding affected by prior treatment was absent, IPT-weighted analyses were less precise and therefore had greater root MSE compared with adjusted analyses. The 95% confidence limit coverage was close to nominal for all stabilized IPT-weighted but poor in crude, adjusted, and unstabilized IPT-weighted analysis. Under realistic scenarios, marginal structural Cox proportional hazards models performed according to expectations based on large-sample theory and provided accurate estimates of the hazard ratio

Adherence to the Mediterranean diet and body fat distribution in reproductive aged women

Background/Objectives Adherence to the Mediterranean Diet (MD) high in fruits, vegetables and monounsaturated fats, has been associated with lower body mass index. Associations with measured body fat, including regional adiposity, have not been previously investigated. We examined the associations between the alternate Mediterranean Diet Score (aMED), anthropometry and measured adiposity by dual energy x-ray absorptiometry. Subjects/Methods This study included 248 healthy females, aged 18–44 years from the BioCycle Study. Each woman’s aMED (range 0–9) was calculated from up to eight 24-hr dietary recalls over 1–2 menstrual cycles (>97% had ≥7 recalls). Multiple linear regression was used to determine whether aMED and its specific components were associated with total and regional adiposity after adjusting for age, race, education, physical activity and energy intake. Results: Participants had an average (SD) aMED of 4.2 (1.7) and percent body fat of 29.5 (6.0)%. Significant inverse associations were found between aMED and all the examined adiposity measures except waist to hip ratio. Among the DXA measures, a 1-unit increment in aMED was associated with a 0.06 (95% CI:−0.09,−0.02) lower trunk-to-leg fat ratio (T/L), a measure of upper to lower body fat. In an analysis examining T/L as an outcome with the separate components of the aMED, T/L was lower with increased legume consumption (β=−0.280, 95% CI:−0.550,−0.010) but was higher with increased consumption of red and processed meat (β=0.060, 95% CI:0.002,0.117). Conclusions: Adherence to the aMED was associated with lower total and regional adiposity, adding to the mounting evidence of the health benefits of the MD

Tampon use, environmental chemicals and oxidative stress in the BioCycle study

Background Tampons are used by up to 86% of US women and are a rarely considered potential source of pesticide and metal exposure. Tampons may be of particular concern given the likely higher absorption that occurs in the vagina. Our objective was to examine the potential associations between tampon use and metal concentrations, and biomarkers of inflammation and oxidative stress among healthy women. Methods We used information from a prospective cohort of 259 regularly menstruating women, aged 18–44, followed for two menstrual cycles. Tampon use was assessed using information provided in participant study diaries. Metal concentrations were measured from a blood sample collected at enrollment. Oxidative stress and inflammation biomarker concentrations were determined from blood samples collected at up to 8 clinic visits for each cycle. Linear regression models were used to estimate associations of tampon use with metal exposure, and linear mixed models to estimate associations of tampon use with inflammation and oxidative stress biomarkers at different times during the menstrual cycle. Results We observed non-significantly higher mean levels of mercury for tampon users compared to non-tampon users (exp(β) = 1.25, 95% CI = 0.93, 1.68). We found no evidence of an association between tampon use and inflammation biomarkers. We observed consistently higher isoprostane levels, an oxidative stress biomarker, among tampon users compared to non-tampon users (e.g. exp.(β) = 1.05, 95%CI = 0.96, 1.16, for the average isoprostane during the menstruating week); however, these results were not statistically significant. Conclusions While our results are not statistically significant, we observed suggestive associations between tampon use and elevated levels of mercury and oxidative stress biomarkers. Although our finding should be interpreted in light of our limitations, they indicate that tampons may be a source of exposure to metals and chemicals that have been largely ignored, and any related health effects are an important public health concern

The Impact of Dietary Folate Intake on Reproductive Function in Premenopausal Women: A Prospective Cohort Study

Background: Folic acid is recommended to reproductive-aged women to prevent birth defects, though little is known about the effects of dietary intake on other reproductive outcomes. Improved pregnancy rates have been documented after folic acid supplement use, suggesting a possible link with ovulation, however research is limited. Our objective was to evaluate the association between dietary folate intake, hormone levels, and sporadic anovulation in healthy, regularly menstruating women. Methodology/Principal Findings: The BioCycle study (2005–2007) prospectively followed 259 healthy women aged 18–44 years from the western New York region for up to 2 menstrual cycles. Total folate and specific sources of folate were assessed up to 4 times per cycle by 24-hour recall. Estradiol, progesterone, luteinizing hormone, and follicle-stimulating hormone were measured in serum up to 8 times per cycle, timed using fertility monitors. Anovulation was defined as a cycle with peak progesterone concentration ≤5 ng/mL and no LH peak in the mid/late luteal phase. Higher intake of dietary folate (in dietary equivalents) across tertiles had a marginally significant association with greater luteal progesterone levels (P trend 0.08). Higher intake of synthetic folate was significantly associated with higher luteal progesterone levels (P trend 0.05). Specifically, women in the 3rd tertile of synthetic folate intake had, on average, 16.0% (95% CI, 0.5–33.8%) higher luteal progesterone levels compared to women in the 1st tertile. Moreover, consumption of synthetic folate was significantly and inversely associated with anovulation such that women in the 3rd tertile had a 64% (95% CI, 8–86%) decreased odds of anovulation compared to the women in the 1st tertile (P trend 0.03). Conclusions/Significance: These findings suggest that a diet high in synthetic folate may be associated with increased progesterone levels and lower risk of sporadic anovulation. Further study of the effect of dietary folate and folic acid supplement use on reproductive health is warranted

An information criterion for marginal structural models

Marginal structural models were developed as a semiparametric alternative to the G-computation formula to estimate causal effects of exposures. In practice, these models are often specified using parametric regression models. As such, the usual conventions regarding regression model specification apply. This paper outlines strategies for marginal structural model specification, and considerations for the functional form of the exposure metric in the final structural model. We propose a quasi-likelihood information criterion adapted from use in generalized estimating equations. We evaluate the properties of our proposed information criterion using a limited simulation study. We illustrate our approach using two empirical examples. In the first example, we use data from a randomized breastfeeding promotion trial to estimate the effect of breastfeeding duration on infant weight at one year. In the second example, we use data from two prospective cohorts studies to estimate the effect of highly active antiretroviral therapy on CD4 count in an observational cohort of HIV-infected men and women. The marginal structural model specified should reflect the scientific question being addressed, but can also assist in exploration of other plausible and closely related questions. In marginal structural models, as in any regression setting, correct inference depends on correct model specification. Our proposed information criterion provides a formal method for comparing model fit for different specifications