The association between reproductive history and abdominal adipose tissue among postmenopausal women: results from the Women's Health Initiative.

STUDY QUESTION: What is the association between reproductive health history (e.g. age at menarche, menopause, reproductive lifespan) with abdominal adiposity in postmenopausal women? SUMMARY ANSWER: Higher visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) tissue levels were observed among women with earlier menarche, earlier menopause, and greater parity. WHAT IS KNOWN ALREADY: Postmenopausal women are predisposed to accumulation of VAT and SAT. Reproductive health variables are known predictors of overall obesity status in women, defined by BMI. STUDY DESIGN, SIZE, DURATION: This study is a secondary analysis of data collected from the baseline visit of the Women's Health Initiative (WHI). The WHI is a large prospective study of postmenopausal women, including both a randomized trial and observational study. There were 10 184 women included in this analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data were collected from a reproductive health history questionnaire, dual-energy x-ray absorptiometry scans, and anthropometric measures at WHI baseline. Reproductive history was measured via self-report, and included age at menarche, variables related to pregnancy, and age at menopause. Reproductive lifespan was calculated as age at menopause minus age at menarche. Statistical analyses included descriptive analyses and multivariable linear regression models to examine the association between reproductive history with VAT, SAT, total body fat, and BMI. MAIN RESULTS AND THE ROLE OF CHANCE: Women who reported early menarche (<10 years) or early menopause (<40 years) had the highest levels of VAT. Adjusted multivariable linear regression results demonstrate women who experienced menarche >15 years had 23 cm2 less VAT (95% CI: -31.4, -14.4) and 47 cm2 less SAT (95% CI: -61.8, -33.4) than women who experienced menarche at age 10 years or earlier. A similar pattern was observed for age at menopause: compared to women who experienced menopause <40 years, menopause at 50-55 years was associated with 19.3 cm2 (95% CI: -25.4, -13.3) less VAT and 27.4 cm2 (-29.6, 10.3) less SAT. High parity (>3 pregnancies) was also associated with VAT and SAT. For example, adjusted beta coefficients for VAT were 8.36 (4.33, 12.4) and 17.9 (12.6, 23.2) comparing three to four pregnancies with the referent, one to two pregnancies. LIMITATIONS, REASONS FOR CAUTION: The WHI reproductive health history questionnaire may be subject to poor recall owing to a long look-back window. Residual confounding may be present given lack of data on early life characteristics, such as maternal and pre-menarche characteristics. WIDER IMPLICATIONS OF THE FINDINGS: This study contributes to our understanding of reproductive lifespan, including menarche and menopause, as an important predictor of late-life adiposity in women. Reproductive health has also been recognized as a sentinel marker for chronic disease in late life. Given established links between adiposity and cardiometabolic outcomes, this research has implications for future research, clinical practice, and public health policy that makes use of reproductive health history as an opportunity for chronic disease prevention. STUDY FUNDING/COMPETING INTEREST(S): HRB and AOO are supported by the National Institute of Health National Institute of Aging (R01AG055018-04). JWB reports royalties from 'ACSM'S Body Composition Assessment Book' and consulting fees from the WHI. The remaining authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.

A protocol for remote collection of skeletal muscle mass via D3-creatine dilution in community-dwelling postmenopausal women from the Women's Health Initiative.

BACKGROUND: There is emerging evidence that cancer and its treatments may accelerate the normal aging process, increasing the magnitude and rate of decline in functional capacity. This accelerated aging process is hypothesized to hasten the occurrence of common adverse age-related outcomes in cancer survivors, including loss of muscle mass and decrease in physical function. However, there is no data describing age-related loss of muscle mass and its relation to physical function in the long-term in cancer survivors. METHODS: This study protocol describes the use of a novel method of muscle mass measurement, D3-creatine dilution method (D3Cr), in a large sample (n~6000) of community dwelling postmenopausal women from the Women's Health Initiative (WHI). D3Cr will be used to obtain a direct measure of muscle mass remotely. Participants will be drawn from two sub-cohorts embedded within the WHI that have recently completed an in-home visit. Cancer survivors will be drawn from the Life and Longevity After Cancer (LILAC) cohort, and cancer-free controls will be drawn from the WHI Long Life Study 2. The overall objective of this study is to examine the antecedents and consequences of low muscle mass in cancer survivors. The study aims are to: 1) create age-standardized muscle mass percentile curves and z-scores to characterize the distribution of D3- muscle mass in cancer survivors and non-cancer controls, 2) compare muscle mass, physical function, and functional decline in cancer survivors and non- cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction algorithms to detect low muscle mass. DISCUSSION: The D3Cr method will transform our ability to measure muscle mass in large-scale epidemiologic research. This study is an opportunity to advance our understanding of a key source of morbidity among older and long-term female cancer survivors. This project will fill knowledge gaps, including the antecedents and consequences of low muscle mass, and use innovative methods to overcome common sources of bias in cancer research. The results of this study will be used to develop interventions to mitigate the harmful effects of low muscle mass in older adults and promote healthy survivorship in cancer survivors in the old (>65) and oldest-old (>85) age groups.

Low physical function Post-Cancer diagnosis is associated with higher mortality risk in postmenopausal women.

BACKGROUND: Postmenopausal women with cancer experience an accelerated physical dysfunction beyond that expected through aging alone due to cancer and its treatments. The aim of this study is to determine whether declines in physical function after cancer diagnosis are associated with all-cause mortality and cancer-specific mortality. METHODS: This prospective cohort study included 8,068 postmenopausal women enrolled in the Women's Health Initiative (WHI) who were diagnosed with cancer and had physical function assessed within 1-year of cancer diagnosis. Self-reported physical function was measured using the 10-item physical function subscale of the RAND 36-Item Health Survey. Cause of death was determined by medical record review with central adjudication and linkage to the National Death Index. Death was adjudicated through February 2022. RESULTS: Over a median follow-up of 7.7 years from cancer diagnosis 3,316 (41.1%) women died. Our results showed that for every 10% decline in the physical function score after cancer diagnosis, all-cause mortality and cancer-specific mortality were significantly reduced by 12% (HR, 0.88; 95% CI, 0.87 to 0.89) and (HR, 0.88; 95%CI, 0.86 to 0.91), respectively. Further categorical analyses showed a significant dose-response relationship between post-diagnosis physical function categories and mortality outcomes (trend test P < .001), where the median survival time for women in the lowest physical function quartile was 9.1 (8.6, 10.6) years compared to 18.4 (15.8, 22.0) years for women in the highest physical function quartile. CONCLUSION: Postmenopausal women with low physical function after cancer diagnosis may be at higher risk of mortality from all causes and cancer-related mortality.

Application of a Web-based Tool for Quantitative Bias Analysis: The Example of Misclassification Due to Self-reported Body Mass Index.

BACKGROUND: We describe the use of Apisensr, a web-based application that can be used to implement quantitative bias analysis for misclassification, selection bias, and unmeasured confounding. We apply Apisensr using an example of exposure misclassification bias due to use of self-reported body mass index (BMI) to define obesity status in an analysis of the relationship between obesity and diabetes. METHODS: We used publicly available data from the National Health and Nutrition Examination Survey. The analysis consisted of: (1) estimating bias parameter values (sensitivity, specificity, negative predictive value, and positive predictive value) for self-reported obesity by sex, age, and race-ethnicity compared to obesity defined by measured BMI, and (2) using Apisensr to adjust for exposure misclassification. RESULTS: The discrepancy between self-reported and measured obesity varied by demographic group (sensitivity range: 75%-89%; specificity range: 91%-99%). Using Apisensr for quantitative bias analysis, there was a clear pattern in the results: the relationship between obesity and diabetes was underestimated using self-report in all age, sex, and race-ethnicity categories compared to measured obesity. For example, in non-Hispanic White men aged 40-59 years, prevalence odds ratios for diabetes were 3.06 (95% confidence inerval = 1.78, 5.30) using self-reported BMI and 4.11 (95% confidence interval = 2.56, 6.75) after bias analysis adjusting for misclassification. CONCLUSION: Apisensr is an easy-to-use, web-based Shiny app designed to facilitate quantitative bias analysis. Our results also provide estimates of bias parameter values that can be used by other researchers interested in examining obesity defined by self-reported BMI.

Mediators of the Association Between Socioeconomic Status and Survival After Out-of-Hospital Cardiac Arrest: A Systematic Review.

Low socioeconomic status (SES) is associated with poor outcomes after out-of-hospital cardiac arrest (OHCA). Patient characteristics, care processes, and other contextual factors may mediate the association between SES and survival after OHCA. Interventions that target these mediating factors may reduce disparities in OHCA outcomes across the socioeconomic spectrum. This systematic review identified and quantified mediators of the SES-survival after OHCA association. Electronic databases (MEDLINE, Embase, PubMed, Web of Science) and grey literature sources were searched from inception to July or August 2023. Observational studies of OHCA patients that conducted mediation analyses to evaluate potential mediators of the association between SES (defined by income, education, occupation, or a composite index) and survival outcomes were included. A total of 10 studies were included in this review. Income (n = 9), education (n = 4), occupation (n = 1), and composite indices (n = 1) were used to define SES. The proportion of OHCA cases that had bystander involvement, presented with an initial shockable rhythm, and survived to hospital discharge or 30 days increased with higher SES. Common mediators of the SES-survival association that were evaluated included initial rhythm (n = 6), emergency medical services response time (n = 5), and bystander cardiopulmonary resuscitation (n = 4). Initial rhythm was the most important mediator of this association, with a median percent excess risk explained of 37.4% (range 28.6%-40.0%; n = 5; 1 study reported no mediation) and mediation proportion of 41.8% (n = 1). To mitigate socioeconomic disparities in outcomes after OHCA, interventions should target potentially modifiable mediators, such as initial rhythm, which may involve improving bystander awareness of OHCA and the need for prompt resuscitation.

Association of Later-Life Weight Changes With Survival to Ages 90, 95, and 100: The Women's Health Initiative.

BACKGROUND: Associations of weight changes and intentionality of weight loss with longevity are not well described. METHODS: Using longitudinal data from the Women's Health Initiative (N = 54 437; 61-81 years), we examined associations of weight changes and intentionality of weight loss with survival to ages 90, 95, and 100. Weight was measured at baseline, year 3, and year 10, and participants were classified as having weight loss (≥5% decrease from baseline), weight gain (≥5% increase from baseline), or stable weight (<5% change from baseline). Participants reported intentionality of weight loss at year 3. RESULTS: A total of 30 647 (56.3%) women survived to ≥90 years. After adjustment for relevant covariates, 3-year weight loss of ≥5% vs stable weight was associated with lower odds of survival to ages 90 (OR, 0.67; 95% CI, 0.64-0.71), 95 (OR, 0.65; 95% CI, 0.60-0.71), and 100 (OR, 0.62; 95% CI, 0.49-0.78). Compared to intentional weight loss, unintentional weight loss was more strongly associated with lower odds of survival to age 90 (OR, 0.83; 95% CI, 0.74-0.94 and OR, 0.49; 95% CI, 0.44-0.55, respectively). Three-year weight gain of ≥5% vs stable weight was not associated with survival to age 90, 95, or 100. The pattern of results was similar among normal weight, overweight, and obese women in body mass index (BMI)-stratified analyses. CONCLUSIONS: Weight loss of ≥5% vs stable weight was associated with lower odds of longevity, more strongly for unintentional weight loss than for intentional weight loss. Potential inaccuracy of self-reported intentionality of weight loss and residual confounding were limitations.

First-line opioid agonist treatment as prevention against assisting others in initiating injection drug use: A longitudinal cohort study of people who inject drugs in Vancouver, Canada.

Background: Among people who inject drugs, frequent injecting and experiencing withdrawal are associated with facilitating others' first injections. As these factors may reflect an underlying substance use disorder, we investigated whether first-line oral opioid agonist treatment (OAT; methadone or buprenorphine/naloxone) reduces the likelihood that people who inject drugs help others initiate injecting. Methods: We used questionnaire data from semi-annual visits between December 2014-May 2018 on 334 people who inject drugs with frequent non-medical opioid use in Vancouver, Canada. We estimated the effect of current first-line OAT on subsequent injection initiation assistance provision (i.e., helped someone initiate injecting in the following six months) using inverse-probability-weighted estimation of repeated measures marginal structural models to reduce confounding and informative censoring by time-fixed and time-varying covariates. Results: By follow-up visit, 54-64% of participants reported current first-line OAT whereas 3.4-6.9% provided subsequent injection initiation assistance. Per the primary weighted estimate (n = 1114 person-visits), participants currently on first-line OAT (versus no OAT) were 50% less likely, on average, to subsequently help someone initiate injecting (relative risk [RR]=0.50, 95% CI=0.23-1.11). First-line OAT was associated with reduced risk of subsequent injection initiation assistance provision in participants who, at baseline, injected opioids less than daily (RR=0.15, 95% CI=0.05-0.44) but not in those who injected opioids daily (RR=0.86, 95% CI=0.35-2.11). Conclusions: First-line OAT seemingly reduces the short-term likelihood that people who inject drugs facilitate first injections. However, the extent of this potential effect remains uncertain due to imprecise estimation and observed heterogeneity by baseline opioid injecting frequency.

Hepatitis B and C in individuals with a history of antipsychotic medication use: A population-based evaluation.

BACKGROUND: A better understanding of links between mental illness and risk of bloodborne infectious disease could inform preventive and therapeutic strategies in individuals with mental illness. METHODS: We performed a cross-sectional study using the National Health and Nutrition Examination Survey (NHANES) to estimate the seroprevalence of hepatitis B and C in individuals with and without a prior prescription for antipsychotic medications, and to determine whether differences in seroprevalence could be explained by differential distribution in known infection risk factors. Multivariable logistic regression models were used to examine the association between receipt of antipsychotic medication and HBV and HCV seropositivity. RESULTS: Those who had HBV core antibody had 1.64 (95% CI: 0.89, 3.02) times the odds and those with HCV antibody (anti-HCV) had 3.48 (95% CI: 1.71, 7.09) times the odds of having a prescription for at least one antipsychotic medication compared to those who did not have HBV core antibody or HCV antibody, respectively. While prior antipsychotic receipt was a potent risk marker for HCV seropositivity, risk was explained by adjusting for known bloodborne infection risk factors (adjusted ORs 1.01 [95% CI: 0.50, 2.02] and 1.38 [95% CI: 0.44, 4.36] for HBV and HCV, respectively). CONCLUSIONS: Prior receipt of antipsychotic medications is a strong predictor of HCV (and to a lesser extent HBV) seropositivity. Treatment with antipsychotic medications should be considered as additional risk markers for individuals who may benefit from targeted prevention, screening, and harm reduction interventions for HCV.

Longitudinal patterns of abdominal visceral and subcutaneous adipose tissue, total body composition, and anthropometric measures in postmenopausal women: Results from the Women's Health Initiative.

BACKGROUND: Abdominal adiposity, including visceral and subcutaneous abdominal adipose tissue (VAT and SAT), is recognized as a strong risk factor for cardiometabolic disease, cancer, and mortality. OBJECTIVE: The primary aim of this analysis is to describe longitudinal patterns of change in abdominal adipose tissue in postmenopausal women, overall and stratified by age, race/ethnicity, and years since menopause. METHODS: The data are from six years of follow up on 10,184 postmenopausal women (7828 non-Hispanic White women, 1423 non-Hispanic Black women, and 703 Hispanic women) who participated in the Women's Health Initiative (WHI). The WHI is a large prospective cohort study of postmenopausal women across the United States. All participants in this analysis had DXA scans in the 1990s as part of the WHI protocol. Hologic APEX software was used to re-analyze archived DXA scans and obtain measures of abdominal adipose tissue. Analyses examined differences in abdominal adipose tissue, overall adiposity, and anthropometric variables. RESULTS: There were important differences in VAT and SAT by age and race/ethnicity. In women <60 years, VAT increased over the follow-up period, while in women ≥70 years, VAT decreased. Non-Hispanic Black women had the highest levels of SAT. Hispanic women had the highest VAT levels. Women more than ten years since menopause had less SAT and more VAT than women less than ten years since menopause, resulting in a higher VAT/SAT ratio. There was a moderate to strong correlation between measures of abdominal adipose tissue and anthropometric measurements of body size. Still, there were substantial differences in the quantity of VAT and SAT within BMI and waist circumference categories. CONCLUSIONS: These results demonstrate differences in VAT and SAT according to age, race/ethnicity, time since menopause, and compared to standard measures of body composition in a large and diverse cohort of postmenopausal women.

Long-term Trajectories of Physical Function Decline in Women With and Without Cancer.

Importance: Patients with cancer experience acute declines in physical function, hypothesized to reflect accelerated aging driven by cancer-related symptoms and effects of cancer therapies. No study has examined long-term trajectories of physical function by cancer site, stage, or treatment compared with cancer-free controls. Objective: Examine trajectories of physical function a decade before and after cancer diagnosis among older survivors and cancer-free controls. Design, Setting, and Participants: This prospective cohort study enrolled patients from 1993 to 1998 and followed up until December 2020. The Women's Health Initiative, a diverse cohort of postmenopausal women, included 9203 incident cancers (5989 breast, 1352 colorectal, 960 endometrial, and 902 lung) matched to up to 5 controls (n = 45 358) on age/year of enrollment and study arm. Exposures: Cancer diagnosis (site, stage, and treatment) via Medicare and medical records. Main Outcomes and Measures: Trajectories of self-reported physical function (RAND Short Form 36 [RAND-36] scale; range: 0-100, higher scores indicate superior physical function) estimated from linear mixed effects models with slope changes at diagnosis and 1-year after diagnosis. Results: This study included 9203 women with cancer and 45 358 matched controls. For the women with cancer, the mean (SD) age at diagnosis was 73.0 (7.6) years. Prediagnosis, physical function declines of survivors with local cancers were similar to controls; after diagnosis, survivors experienced accelerated declines relative to controls, whose scores declined 1 to 2 points per year. Short-term declines in the year following diagnosis were most severe in women with regional disease (eg, -5.3 [95% CI, -6.4 to -4.3] points per year in regional vs -2.8 [95% CI, -3.4 to -2.3] for local breast cancer) or who received systemic therapy (eg, for local endometrial cancer, -7.9 [95% CI, -12.2 to -3.6] points per year with any chemotherapy; -3.1 [95% CI, -6.0 to -0.3] with radiation therapy alone; and -2.6 [95% CI, -4.2 to -1.0] with neither, respectively). While rates of physical function decline slowed in the later postdiagnosis period (eg, women with regional colorectal cancer declined -4.3 [95% CI, -5.9 to -2.6] points per year in the year following diagnosis vs -1.4 [95% CI, -1.7 to -1.0] points per year in the decade thereafter), survivors had estimated physical function significantly below that of age-matched controls 5 years after diagnosis. Conclusions and Relevance: In this prospective cohort study, survivors of cancer experienced accelerated declines in physical function after diagnosis, and physical function remained below that of age-matched controls even years later. Patients with cancer may benefit from supportive interventions to preserve physical functioning.

Association of muscle mass measured by D3-Creatine (D3Cr), sarcopenic obesity, and insulin-glucose homeostasis in postmenopausal women.

The D3-Creatine (D3Cr) dilution method is a direct and accurate measure of skeletal muscle mass. In this study, we examined the association of D3Cr muscle mass with measures of insulin-glucose homeostasis in community dwelling postmenopausal women. Additionally, we examined association of sarcopenic obesity, defined as low D3Cr muscle mass and high percent body fat, with fasting plasma glucose, insulin, hemoglobin A1c and insulin resistance. Insulin resistance was measured by the homeostatic measure of insulin resistance (HOMA-IR). This pilot study included 74 participants (mean age = 82.3 years) from the Women's Health Initiative-Buffalo site. The D3Cr method was initiated at a clinic visit and used to measure muscle mass via remote urine sample collection. Descriptive and graphical approaches and age-adjusted linear regression models were used to analyze study data. We examined muscle mass as an absolute value (kg) and scaled to body weight (D3Cr muscle mass/kg). There was an inverse relationship between skeletal muscle mass, and impaired insulin-glucose homeostasis. Women with low muscle mass had higher levels of insulin (uIU/mL; ß = -0.40; 95% CI: -0.79, -0.01), fasting plasma glucose (mg/dL; ß = -0.1; 95% CI: -0.2, 0.03), HbA1c (%; ß = -2.30; 95% CI: -5.7, 1.1), and calculated homeostatic model of insulin resistance, HOMA-IR, (ß = -1.49; 95% CI: -2.9, -0.1). Sarcopenic obesity was common in this population of women; 41% of participants were categorized as having low muscle mass and high percent body fat. Results demonstrate that D3Cr muscle mass is independently associated with measures of insulin-glucose homeostasis, but obesity is a stronger predictor of insulin resistance than muscle mass.

Relationship between BMI trajectories and cardiometabolic outcomes in postmenopausal women: a growth mixture modeling approach.

PURPOSE: The objective of this manuscript is to identify longitudinal trajectories of change in body mass index (BMI) after menopause and investigate the association of BMI trajectories with risk of diabetes and cardiovascular disease (CVD) among postmenopausal women. METHODS: Using data from 54,073 participants in the Women's Health Initiative (WHI) clinical trials, we used growth mixture modeling (GMM) to develop BMI trajectories. Cox proportional hazards models were used to examine the relationship between BMI trajectories with incident diabetes and CVD. Further, we stratified by hormone therapy trial arm and time since menopause. RESULTS: Using GMM, we identified five BMI trajectories. We did not find evidence of substantial change in BMI over time; the trajectories were stable over the study follow-up period in this sample of postmenopausal women. Risk of diabetes and CVD increased by BMI trajectory; risk was greater for women in moderate-high, high, and very high BMI trajectories compared to those in the lowest trajectory group. CONCLUSIONS: Despite minimal change in BMI over the follow-up period, our results demonstrate a strong association of high BMI with diabetes and CVD. These results highlight the importance of further longitudinal research focused on adverse health effects of BMI in older women.

Serum Follicle-Stimulating Hormone and 5-Year Change in Adiposity in Healthy Postmenopausal Women.

CONTEXT: Evidence from animal studies suggests that the gradual rise in follicle-stimulating hormone (FSH) during reproductive senescence may contribute to the change in adiposity distribution characteristic of menopause. The potential independent role the interrelationships of FSH and estradiol (E2) may play in postmenopausal adiposity changes are not well studied. OBJECTIVE: Our objective was to evaluate the associations of FSH and dual x-ray absorptiometry (DXA)-derived adiposity measures, with consideration of estradiol and postmenopausal hormone therapy use. METHODS: In a sample of 667 postmenopausal women from the Women's Health Initiative Buffalo OsteoPerio Ancillary Study, we studied the associations of serum FSH and E2 levels with dual x-ray absorptiometry (DXA)-derived adiposity measures via cross-sectional and longitudinal analyses (5-year follow-up). RESULTS: In cross-sectional analyses, FSH levels were inversely associated with all measures of adiposity in models adjusted for age, years since menopause, smoking status, pack-years, and hormone therapy (HT) use; these associations were not influenced by adjustment for serum E2. In longitudinal analyses, the subset of women who discontinued HT over follow-up (n = 242) experienced the largest increase in FSH (+33.9 mIU/mL) and decrease in E2 (-44.3 pg/mL) and gains in all adiposity measures in unadjusted analyses. In adjusted analyses, an increase in FSH was associated with a gain in percentage of total body fat, total body fat mass, and subcutaneous adipose tissue (SAT). CONCLUSION: While cross-sectional findings suggest that FSH is inversely associated with adiposity, our longitudinal findings suggest that greater increases in FSH were associated with greater increases in percentage of total body fat, total body fat mass, and SAT. Future studies are needed to provide additional insight into FSH-adiposity mechanisms in larger samples.

Propensity score methods for merging observational and experimental datasets.

We consider how to merge a limited amount of data from a randomized controlled trial (RCT) into a much larger set of data from an observational data base (ODB), to estimate an average causal treatment effect. Our methods are based on stratification. The strata are defined in terms of effect moderators as well as propensity scores estimated in the ODB. Data from the RCT are placed into the strata they would have occupied, had they been in the ODB instead. We assume that treatment differences are comparable in the two data sources. Our first "spiked-in" method simply inserts the RCT data into their corresponding ODB strata. We also consider a data-driven convex combination of the ODB and RCT treatment effect estimates within each stratum. Using the delta method and simulations, we identify a bias problem with the spiked-in estimator that is ameliorated by the convex combination estimator. We apply our methods to data from the Women's Health Initiative, a study of thousands of postmenopausal women which has both observational and experimental data on hormone therapy (HT). Using half of the RCT to define a gold standard, we find that a version of the spiked-in estimator yields lower-MSE estimates of the causal impact of HT on coronary heart disease than would be achieved using either a small RCT or the observational component on its own.

Monte Carlo Simulation Approaches for Quantitative Bias Analysis: A Tutorial.

Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated data set. In this article, we review 2 strategies for quantitative bias analysis: 1) traditional probabilistic quantitative bias analysis and 2) quantitative bias analysis with generated data. An important difference between the 2 strategies relates to the type of data (real vs. generated data) used in the analysis. Monte Carlo simulations are used in both approaches, but the simulation process is used for different purposes in each. For both approaches, we outline and describe the steps required to carry out the quantitative bias analysis and also present a bias-analysis tutorial demonstrating how both approaches can be applied in the context of an analysis for selection bias. Our goal is to highlight the utility of quantitative bias analysis for practicing epidemiologists and increase the use of these methods in the epidemiologic literature.

MRI Based Validation of Abdominal Adipose Tissue Measurements From DXA in Postmenopausal Women.

INTRODUCTION: Visceral adipose tissue (VAT) is a hypothesized driver of chronic disease. Dual-energy X-ray absorptiometry (DXA) potentially offers a lower cost and more available alternative compared to gold-standard magnetic resonance imaging (MRI) for quantification of abdominal fat sub-compartments, VAT and subcutaneous adipose tissue (SAT). We sought to validate VAT and SAT area (cm2) from historical DXA scans against MRI. METHODOLOGY: Participants (n = 69) from the Women's Health Initiative (WHI) completed a 3 T MRI scan and a whole body DXA scan (Hologic QDR2000 or QDR4500; 2004-2005). A subset of 43 participants were scanned on both DXA devices. DXA-derived VAT and SAT at the 4th lumbar vertebrae (5 cm wide) were analyzed using APEX software (v4.0, Hologic, Inc., Marlborough, MA). MRI VAT and SAT areas for the corresponding DXA region of interest were quantified using sliceOmatic software (v5.0, Tomovision, Magog, Canada). Pearson correlations between MRI and DXA-derived VAT and SAT were computed, and a Bland-Altman analysis was performed. RESULTS: Participants were primarily non-Hispanic white (86%) with a mean age of 70.51 ± 5.79 years and a mean BMI of 27.33 ± 5.40 kg/m2. Correlations between MRI and DXA measured VAT and SAT were 0.90 and 0.92, respectively (p ≤ 0.001). Bland-Altman plots showed that DXA-VAT slightly overestimated VAT on the QDR4500 (-3.31 cm2); this bias was greater in the smaller subset measured on the older DXA model (QDR2000; -30.71 cm2). The overestimation of DXA-SAT was large (-85.16 to -118.66 cm2), but differences were relatively uniform for the QDR4500. CONCLUSIONS: New software applied to historic Hologic DXA scans provide estimates of VAT and SAT that are well-correlated with criterion MRI among postmenopausal women.