Abstract
Coronavirus disease 2019 (COVID-19) vaccines have been reported to have a short-term effect on the menstrual cycle, delaying the onset of the next menses. However, the analytical methods ...that have been used to study this are subject to a statistical phenomenon called “length-biased sampling” that calls the results into question. Those data are important and should be reanalyzed in an unbiased way.
Investigators measuring exposure biomarkers in urine typically adjust for creatinine to account for dilution-dependent sample variation in urine concentrations. Similarly, it is standard to adjust ...for serum lipids when measuring lipophilic chemicals in serum. However, there is controversy regarding the best approach, and existing methods may not effectively correct for measurement error.
We compared adjustment methods, including novel approaches, using simulated case-control data.
Using a directed acyclic graph framework, we defined six causal scenarios for epidemiologic studies of environmental chemicals measured in urine or serum. The scenarios include variables known to influence creatinine (e.g., age and hydration) or serum lipid levels (e.g., body mass index and recent fat intake). Over a range of true effect sizes, we analyzed each scenario using seven adjustment approaches and estimated the corresponding bias and confidence interval coverage across 1,000 simulated studies.
For urinary biomarker measurements, our novel method, which incorporates both covariate-adjusted standardization and the inclusion of creatinine as a covariate in the regression model, had low bias and possessed 95% confidence interval coverage of nearly 95% for most simulated scenarios. For serum biomarker measurements, a similar approach involving standardization plus serum lipid level adjustment generally performed well.
To control measurement error bias caused by variations in serum lipids or by urinary diluteness, we recommend improved methods for standardizing exposure concentrations across individuals.
Anorexia and bulimia nervosa may have long-term effects on overall and reproductive health. We studied predictors of self-reported eating disorders and associations with later health events. We ...estimated odds ratios (ORs) for these associations in 47,759 participants from the Sister Study. Two percent (n = 967) of participants reported a history of an eating disorder. Risk factors included being non-Hispanic white, having well-educated parents, recent birth cohort (OR = 2.16, 95% confidence interval CI: 2.01-2.32 per decade), and having a sister with an eating disorder (OR = 3.68, CI: 1.92-7.02). As adults, women who had experienced eating disorders were more likely to smoke, to be underweight, to have had depression, to have had a later first birth, to have experienced bleeding or nausea during pregnancy, or to have had a miscarriage or induced abortion. In this descriptive analysis, we identified predictors of and possible long-term health consequences of eating disorders. Eating disorders may have become more common over time. Interventions should focus on prevention and mitigation of long-term adverse health effects.
Fecundability (conception rate per menstrual cycle) varies among non-contracepting couples. Time-to-pregnancy studies can identify exposures contributing to that variability, using three designs: ...incident cohort, prevalent cohort, and retrospective. Typically, researchers then apply semi-parametric, generalized linear time-to-pregnancy models to data, with either a log or a logit "link," to estimate either a fecundability ratio (FR) or a fecundability odds ratio (FOR). The ongoing-attempt study design can also be informative.
We consider a different generalized linear model, based on an inverse link. It models the heterogeneity as beta distributed and enables estimation of both the FR and FOR, defined based on population mean fecundabilities, without requiring constancy across attempt time. Under an ongoing-attempt design, the parameter associated with a dichotomous exposure has no clear meaning with a log or a logit link, but under the proposed approach estimates the ratio of the two average times to pregnancy. Basing simulations on conception rates from a large study, we compare the three analytic approaches for confidence interval coverage and power. We also assess the performance of a commonly used method for verifying the constancy of FOR or FR across time.
The inverse-link approach had slightly less power than the others, but its estimates maintained nominal confidence interval coverage under nonconstancy. A popular method for testing constancy across time for the FR and FOR had poor power.
The inverse-link analysis offers a useful alternative to the usual methods, with estimation performance that generalizes to the ongoing-attempt design and does not require hard-to-verify constancy assumptions.
Epidemiologic studies on the association between metals and body mass index (BMI) have been cross-sectional and have demonstrated inconsistent associations. Our study prospectively examined whether ...metals measured at baseline were associated with later BMI. We considered metals individually and as joint exposure to pre-defined metal groupings.
We measured concentrations of 16 metals in toenails collected at baseline (2003–2009) in a subset of 1221 women from the Sister Study. We calculated BMI from height and weight reported on a follow-up questionnaire an average of 5.2 years (range = 3.5–8.3) after baseline. Multivariable linear regression was used to estimate β coefficients and 95% confidence intervals (CIs) for associations between BMI and individual metals (with estimates given per interquartile range (IQR) increase or in quartiles). Quantile g-computation was used to examine joint associations between groups of metals and BMI. Groups considered were (1) all metals combined, and metals classified as (2) non-essential or (3) essential.
In individual metal models we found that, with the exception of cobalt, no single metal was strongly related to BMI. In our mixture analyses, a quartile increase in all non-essential metals was associated with higher BMI (β = 0.32; 95%CI: 0.00, 0.63 kg/m2), whereas essential metals were suggestively associated with lower BMI (β = −0.25; 95%CI: −0.58, 0.07 kg/m2).
In this population of women who were, on average, overweight, essential metals were jointly associated with slightly healthier, lower BMI whereas non-essential metals were jointly associated with slightly higher, unhealthier BMI, after controlling for other health indicators and predictors of metals exposures.
•This study prospectively examined whether metals were associated with BMI.•In single metal models cobalt was inversely associated with BMI.•Other metals were not strongly related to BMI individually.•Increasing all non-essential metals jointly was positively associated with BMI.•Results show the importance of a prospective design and examining metal mixtures.
The prevalence of binge drinking in the United States is rising. While alcohol is a risk factor for breast cancer, less is known about the impact of episodic heavy drinking. In 2003-2009, women aged ...35-74 years who were free of breast cancer were enrolled in the Sister Study (n = 50,884). Residents of the United States or Puerto Rico who had a sister with breast cancer were eligible. Multivariable Cox regression was used to estimate adjusted hazard ratios and 95% confidence intervals for breast cancer. During follow-up (mean = 6.4 years), 1,843 invasive breast cancers were diagnosed. Increased breast cancer risk was observed for higher lifetime alcohol intake (for ≥230 drinks/year vs. <60 drinks/year, hazard ratio (HR) = 1.35, 95% confidence interval (CI): 1.15, 1.58). Relative to low-level drinkers (<60 drinks/year), hazard ratios were increased for ever binge drinking (HR = 1.29, 95% CI: 1.15, 1.45) or blacking out (HR = 1.39, 95% CI: 1.17, 1.64). Compared with low-level drinkers who never binged, moderate drinkers (60-229 drinks/year) who binged had a higher risk (HR = 1.25, 95% CI: 1.08, 1.44). There was evidence of effect modification between moderate lifetime drinking and binging (relative excess risk due to interaction = 0.33, 95% CI: 0.10, 0.57). Our findings support the established association between lifetime alcohol intake and breast cancer and provide evidence for an increased risk associated with heavy episodic drinking, especially among moderate lifetime drinkers.
The Sister Study was designed to address gaps in the study of environment and breast cancer by taking advantage of more frequent breast cancer diagnoses among women with a sister history of breast ...cancer and the presumed enrichment of shared environmental and genetic exposures.
The Sister Study sought a large cohort of women never diagnosed with breast cancer but who had a sister (full or half) diagnosed with breast cancer.
A multifaceted national effort employed novel strategies to recruit a diverse cohort, and collected biological and environmental samples and extensive data on potential breast cancer risk factors.
The Sister Study enrolled 50,884 U.S. and Puerto Rican women 35-74y of age (median 56 y). Although the majority were non-Hispanic white, well educated, and economically well off, substantial numbers of harder-to-recruit women also enrolled (race/ethnicity other than non-Hispanic white: 16%; no college degree: 35%; household income <$50,000: 26%). Although all had a biologic sister with breast cancer, 16.5% had average or lower risk of breast cancer according to the Breast Cancer Risk Assessment Tool (Gail score). Most were postmenopausal (66%), parous with a first full-term pregnancy <30y of age (79%), never-smokers (56%) with body mass indexes (BMIs) of <29.9
kg/m
(70%). Few (5%) reported any cancer prior to enrollment.
The Sister Study is a unique cohort designed to efficiently study environmental and genetic risk factors for breast cancer. Extensive exposure data over the life-course and baseline specimens provide important opportunities for studying breast cancer and other health outcomes in women. Collaborations are welcome. https://doi.org/10.1289/EHP1923.
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