Antepartum Intimate Partner Violence: Development of a Risk Prediction Model.

Objectives: To explore socio-behavioral, clinical, and imaging findings associated with antepartum intimate partner violence (IPV) and aid in risk stratification of at-risk individuals. Methods: We analyzed electronic medical records during indexed pregnancies for 108 pregnant patients who self-reported antepartum IPV (cases) and 106 age-matched pregnant patients who did not self-report antepartum IPV (controls). Sociodemographic, clinical, and radiology data were analyzed via chi-squared and Fisher's exact tests with p < 0.05 as the threshold for significance. Stepwise logistic regression was applied to derive a risk prediction model. Results: The proportion of cases reporting emotional IPV (76% vs. 52%) and/or physical IPV (45% vs. 31%) during pregnancy significantly increased from prior to pregnancy. Cases were significantly more likely to report prepregnancy substance use (odds ratio [OR] = 2.60; 95% confidence interval [CI]: 1.13-5.98), sexually transmitted infections (OR = 3.48; 95%CI: 1.64-7.37), abortion (OR = 3.17; 95%CI: 1.79, 5.59), and preterm birth (OR = 5.97; 95%CI: 1.69-21.15). During pregnancy, cases were more likely to report unstable housing (OR = 5.26; 95%CI: 2.67-10.36), multigravidity (OR = 2.83; 95%CI: 1.44-5.58), multiparity (OR = 3.75; 95%CI: 1.72-8.20), anxiety (OR = 3.35; 95%CI: 1.85-6.08), depression (OR = 5.58; 95%CI: 3.07-10.16), substance use (OR = 2.92; 95%CI: 1.28-6.65), urinary tract infection (UTI) (OR = 3.26; 95%CI: 1.14-9.32), intrauterine growth restriction (OR = 10.71; 95%CI: 1.35-85.25), and cesarean delivery (OR = 2.25; 95%CI: 1.26-4.02). Cases had significantly more OBGYN abnormalities on imaging and canceled more radiological studies (OR = 5.31). Logistic regression found housing status, sexually transmitted infection history, preterm delivery history, abortion history, depression, and antepartum UTI predictive of antepartum IPV. The risk prediction model achieved good calibration with an area under the curve of 0.79. Conclusions: This study identifies significant disparities among patients experiencing antepartum IPV, and our proposed risk prediction model can inform risk assessment in this setting.

Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts.

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = - 0.98 standard deviations; 95% CI: - 1.11, - 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

Mitigation of Effect Modification by Psychological Status in Patients with Hearing Loss.

Importance: Although patient-reported outcomes provide valuable insights, these subjective data may not align with objective test results. Hearing loss is a pervasive problem, such that concordance between subjective perceptions of hearing ability and objective audiogram assessments would be beneficial. Objectives: To determine (1) whether psychological status is an effect modifier of the association between subjective patient reports of hearing ability and objective audiometry results, and (2) whether any effect modification observed in standard static questionnaires would be either mitigated or exacerbated by adaptive testing based on Item Response Theory analyses. Design, Setting, and Participants: This diagnostic study at a tertiary care center and community-based practice included consecutive adults who presented with queries related to hearing loss. Participants were recruited and enrolled and data analyses occurred from 2022 to 2024. Exposures: Participants prospectively reported their hearing-specific abilities through either a standard static or adaptive version of the Inner Effectiveness of Auditory Rehabilitation (EAR) scale, alongside validated measures of their mental health and audiometry. Word recognition scores (WRS) and pure tone averages (PTA) were used to analyze audiometric testing. Main Outcomes and Measures: The association between subjective Inner EAR results and audiometry was evaluated. Stratified analyses were used to assess for effect modification by psychological status. The results of standard static and adaptive testing were compared. Results: In this study of 395 patients (mean [range] age, 55.9 [18-89] years; 210 [53.2%] female), standard static Inner EAR mean scores were appropriately higher in patients with higher (better) WRS (50.7, 95% CI, 46.4-54.9), compared with patients with lower (worse) WRS (34.7, 95% CI, 24.3-45.1). However, among patients with worse mental health, there was no association between standard static Inner EAR scores and WRS. In contrast, adaptive Inner EAR mean scores were significantly higher for those with better WRS, regardless of mental health status. Thus, effect modification was observed in standard static assessments, whereas adaptive testing remained durably associated with audiometry, regardless of mental health. Conclusions and Relevance: Psychological status was an effect modifier of the association between standard Inner EAR scale scores and audiometry, with a positive association observed only in those with better mental health. Adaptive testing scores, however, remained significantly associated with audiometry, even when mental status was worse. Adaptive testing may stabilize the association between subjective and objective hearing outcomes.

Recreational physical activity and breast cancer risk by menopausal status and tumor hormone receptor status: results from the Nurses' Health Studies.

PURPOSE: Physical activity is associated with lower breast cancer risk, especially in postmenopausal women. Associations in premenopausal women are less well established. METHODS: We evaluated recreational physical activity and breast cancer risk in the Nurses' Health Study (NHS) and NHSII (187,278 women; n = 12,785 breast cancers; follow-up: NHS = 1986-2016, NHSII = 1989-2017) by menopausal status and estrogen (ER) and progesterone (PR) receptor status. Physical activity was evaluated as updated cumulative average of metabolic equivalent of task (MET)-h/week. Cox proportional hazards models were used to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI). RESULTS: Recreational physical activity was inversely associated with breast cancer risk in pre- and postmenopausal women. Higher activity levels were associated with lower risk of ER+/PR + breast cancer in both pre- and postmenopausal women (e.g., total recreational activity, ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83, 95%CI = (0.70-0.99), postmenopausal HR = 0.86 (0.78-0.95); pheterogeneity = 0.97). Results were attenuated with adjustment for current body mass index (BMI) among postmenopausal, but not premenopausal, women (e.g., ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83 (0.69-0.98); postmenopausal HR = 0.95 (0.85-1.05); pheterogeneity = 0.99). In analyses of moderate-vigorous activity and breast cancer risk, no heterogeneity by menopausal status was observed (phet ≥ 0.53; e.g., ≥ 27 vs < 3 MET-h/week, ER+/PR+, premenopausal HR = 0.88 (0.69-1.11); postmenopausal HR = 0.71 (0.58-0.88). No associations were observed for ER-/PR- disease. CONCLUSIONS: Recreational physical activity was associated with lower breast cancer risk in both pre- and postmenopausal women, supporting recreational physical activity as an accessible, modifiable exposure associated with reduced breast cancer risk regardless of menopausal status.

Associations of reproductive breast cancer risk factors with expression of stem cell markers in benign breast tissue.

Background: We investigated the associations of reproductive factors known to influence breast cancer risk with the expression of breast stem cell markers CD44, CD24, and ALDH1A1 in benign breast biopsy samples. Methods: We included 439 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on reproductive and other breast cancer risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was performed on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as % of cells that stained positive for a specific marker out of the total cell count. Generalized linear regression was used to examine the associations of reproductive factors with a log-transformed expression of each marker (in epithelium and stroma), adjusted for other breast cancer risk factors. Results: In multivariate analysis, the time between menarche and age at first birth was inversely associated with CD44 in epithelium (ß per 5 years = -0.38, 95% CI -0.69; -0.06). Age at first birth and the time between menarche and age at first birth were inversely associated with ALDH1A1 (stroma: ß per 5 years = -0.43, 95% CI -0.76; -0.10 and ß = -0.47, 95% CI -0.79; -0.15, respectively; epithelium: ß = -0.15, 95% CI -0.30; -0.01 and ß = -0.17, 95% CI -0.30; -0.03, respectively). Time since last pregnancy was inversely associated with stromal ALDH1A1 (ß per 5 years = -0.55, 95% CI -0.98; -0.11). No associations were found for CD24. The observed associations were similar in premenopausal women. In postmenopausal women, lifetime duration of breastfeeding was inversely associated with stromal ALDH1A1 expression (ß for ≥24 vs. 0 to <1 months = -2.24, 95% CI 3.96; -0.51, p-trend = 0.01). Conclusion: Early-life reproductive factors may influence CD44 and ALDH1A1 expression in benign breast tissue.

Associations of early-life and adult anthropometric measures with the expression of stem cell markers CD44, CD24, and ALDH1A1 in women with benign breast biopsies.

BACKGROUND: According to the stem cell hypothesis, breast carcinogenesis may be related to the breast stem cell pool size. However, little is known about associations of breast cancer risk factors, such as anthropometric measures, with the expression of stem cell markers in non-cancerous breast tissue. METHODS: The analysis included 414 women with biopsy-confirmed benign breast disease (BBD) in the Nurses' Health Study (NHS) and NHSII. Birthweight, weight at age 18, current weight, and current height were reported via self-administered questionnaire. Immunohistochemical staining of stem cell markers (CD44, CD24, ALDH1A1) in histopathologically normal epithelial and stromal breast tissue was quantified with an automated computational image analysis system. Linear regression was used to examine the associations of early-life and adult anthropometric measures with log-transformed stem cell marker expression, adjusting for potential confounders. RESULTS: Birthweight (≥10.0 vs. <5.5 lbs: ß [95% CI]=4.29 [1.02, 7.56]; p-trend=0.001 in stroma) and adult height (≥67.0 vs. <63.0 inch: 0.86 [0.14, 1.58]; p-trend=0.02 in epithelium and stroma combined) were positively associated with CD44 expression. Childhood body fatness was inversely (p-trend=0.03) and adult height was positively associated with CD24 expression in combined stroma and epithelium (p-trend=0.03). CONCLUSION: Our data suggest that anthropometric measures, such as birthweight, adult height, and childhood body fatness, may be associated with the stem cell expression among women with BBD. IMPACT: Anthropometric measures, such as birthweight, height, and childhood body fatness, may have long-term impacts on stem cell population in the breast.

Reproductive factors related to childbearing and a novel automated mammographic measure, V.

BACKGROUND: We investigated the associations between several reproductive factors related to childbearing and the variation (V) measure (a novel, objective, single summary measure of breast image intensity) by menopausal status. METHODS: Our study included 3,814 cancer-free women within the Nurses' Health Study (NHS) and NHSII cohorts. The data on reproductive variables and covariates were obtained from biennial questionnaires closest to the mammogram date. V-measures were obtained from mammographic images using a previously developed algorithm capturing the standard deviation of pixel values. We used multivariate linear regression to examine the associations of parity, age at first birth, time between menarche and first birth, time since last pregnancy, and lifetime breastfeeding duration with V-measure, adjusting for breast cancer risk factors, including percent mammographic density (PMD). We further examined if these associations were statistically accounted for (mediated) by PMD. RESULTS: Among premenopausal women, none of the reproductive factors were associated with V. Among postmenopausal women, inverse associations of parity and positive associations of age at first birth with V were mediated by PMD (percent mediated: nulliparity: 66.7%, p<0.0001; parity: 50.5%, p<0.01; age at first birth 76.1%, p<0.001) and were no longer significant in PMD-adjusted models. Lifetime duration of breastfeeding was positively associated with V (>36 vs. 0-<1 months ß=0.29, 95% CI 0.07; 0.52, p-trend<0.01), independent of PMD. CONCLUSIONS: Parity, age at first birth, and breastfeeding were associated with postmenopausal V. IMPACT: This study highlights associations of reproductive factors with mammographic image intensity.

Metformin and other anti-diabetic medication use and breast cancer incidence in the Nurses' Health Studies.

We aimed to examine the association between the use of metformin and other anti-diabetic medications and breast cancer incidence within two large prospective cohort studies. We followed 185,181 women who participated in the Nurses' Health Study (NHS; 1994-2016) and the NHSII (1995-2017), with baseline corresponding to the date metformin was approved for type 2 diabetes (T2D) treatment in the US Information on T2D diagnosis, anti-diabetes medications, and other covariates was self-reported at baseline and repeatedly assessed by follow-up questionnaires every 2 years. Breast cancer cases were self-reported and confirmed by medical record review. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between medication use and breast cancer were estimated using Cox proportional hazards regression models, adjusting for breast cancer risk factors. During 3,324,881 person-years of follow-up, we ascertained 9,192 incident invasive breast cancer cases, of which 451 were among women with T2D. Compared with women without T2D (n = 169,263), neither metformin use (HR = 0.97; 95% CI = 0.81-1.15) nor other anti-diabetic medications use (HR = 1.11; 95% CI = 0.90-1.36) associated with significantly lower breast cancer incidence. Among women with T2D (n = 15,918), compared with metformin never users, metformin ever use was not significantly inversely associated with breast cancer (HR = 0.92; 95% CI = 0.74-1.15). Although we observed that past use of metformin was inversely associated with breast cancer in the T2D population (HR = 0.67; 95% CI = 0.48-0.94), current use (HR = 1.01; 95% CI = 0.80-1.27) and longer duration of metformin use were not associated with breast cancer (each 2-year interval: HR = 1.01; 95% CI = 0.95-1.07). Overall, metformin use was not associated with the risk of developing breast cancer among the overall cohort population or among women with T2D.

Timing and duration of dog walking and dog owner's chronotype in relation to incident depression risk among middle to older-aged female nurses.

BACKGROUND: We examined associations between dog ownership, morning dog walking and its timing and duration, and depression risk in female nurses, exploring effect modification by chronotype. We hypothesized that dog ownership and morning walking with the dog are associated with lower odds of depression, and that the latter is particularly beneficial for evening chronotypes by helping them to synchronize their biological clock with the solar system. METHODS: 26,169 depression-free US women aged 53-72 from the Nurses' Health Study 2 (NHS2) were prospectively followed from 2017-2019. We used age- and multivariable-adjusted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for depression according to dog ownership, and morning dog walking, duration, and timing. RESULTS: Overall, there was no association between owning a dog (ORvs_no_pets = 1.12, 95%CI = 0.91-1.37), morning dog walking (ORvs_not = 0.87, 95%CI = 0.64-1.18), or the duration (OR>30min vs. ≤15mins = 0.68, 95%CI = 0.35-1.29) or timing of morning dog walks (ORafter9am vs. before7am = 1.06, 95%CI = 0.54-2.05) and depression. Chronotype of dog owners appeared to modify these associations. Compared to women of the same chronotype but without pets, dog owners with evening chronotypes had a significantly increased odds of depression (OR = 1.60, 95%CI = 1.12-2.29), whereas morning chronotypes did not (OR = 0.94, 95%CI = 0.71-1.23). Further, our data suggested that evening chronotypes benefited more from walking their dog themselves in the morning (OR = 0.75, 95%CI = 0.46-1.23, Pintx = 0.064;) than morning chronotypes. CONCLUSIONS: Overall, dog ownership was not associated with depression risk though it was increased among evening chronotypes. Walking their dog in the morning might help evening chronotypes to lower their odds of depression, though more data are needed to confirm this finding.

Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older.

BACKGROUND: To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models. METHODS: We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668). The Nurses' Health Study development cohort (n = 48 102) regression coefficients were applied to the validation cohorts. We compared our model's performance with breast cancer risk assessment tool (Gail) and International Breast Cancer Intervention Study (IBIS) models by computing breast cancer risk estimates and C statistics. RESULTS: When predicting 10-year breast cancer risk, our model's C index was 0.569 in BWHS, 0.572 in WHI-ES, and 0.576 in MEC. The Gail model's C statistic was 0.554 in BWHS, 0.564 in WHI-ES, and 0.551 in MEC; IBIS's C statistic was 0.547 in BWHS, 0.552 in WHI-ES, and 0.562 in MEC. The Gail model underpredicted breast cancer risk in WHI-ES; IBIS underpredicted breast cancer risk in WHI-ES and in MEC but overpredicted breast cancer risk in BWHS. Our model calibrated well. Our model's C index for predicting 10-year nonbreast cancer death was 0.760 in WHI-ES and 0.763 in MEC. CONCLUSIONS: Our competing-risk model performs as well as existing breast cancer prediction models in diverse cohorts and predicts nonbreast cancer death. We are developing a website to disseminate our model.

Validity and Reproducibility of a Semiquantitative Food Frequency Questionnaire for Measuring Intakes of Foods and Food Groups.

We evaluated the validity and reproducibility of a semiquantitative food frequency questionnaire (FFQ) for measuring intakes of 149 foods and 25 food groups among 736 participants of the Women's Lifestyle Validation Study (WLVS, 2010-2012) and 649 participants of the Men's Lifestyle Validation Study (MLVS, 2011-2013). Validity of the FFQ compared with two 7-day dietary records measured 6 months apart and the reproducibility between 2 FFQs administered 1 year apart (FFQ1 and FFQ2) were assessed using Spearman correlations and intraclass correlation coefficients. The average 1-year reproducibility of FFQ-measured foods was 0.64 in both the WLVS and MLVS. Reproducibility of the food groups (mean = 0.71 among women and 0.72 among men) was generally higher than that for individual foods. Among women, the average validity correlation for individual foods was 0.59 when comparing FFQ2 with the 7-day dietary records. Among men, the corresponding average validity correlation was 0.61. Compared with individual foods, food groups had slightly higher validity correlations in both women (range, 0.45-0.92; mean = 0.61) and men (range, 0.46-0.88; mean = 0.65). This study reaffirms that the FFQ performs well in measuring most foods and food groups and provides data to adjust for measurement errors in epidemiologic studies of foods and food groups.

Elevated Blood Pressure and Aldosterone Dysregulation in Young Black Women Versus White Women on Controlled Sodium Diets.

CONTEXT: Black women have a higher prevalence of hypertension as compared to White women. Differences in dietary sodium intake have been implicated as a contributing factor for the disparities in hypertension. OBJECTIVE: Our objective was to understand whether young Black women would have higher systolic blood pressure (SBP) than White women even on controlled sodium diets and to determine whether SBP differences were due to differences in dietary sodium intake and/or aldosterone regulation. DESIGN: The analyses included 525 hypertensive and normotensive women (ages 18-71) from the International Hypertensive Pathotype consortium, who were maintained on liberal sodium (LIB; >200 mEq sodium/day) and restricted sodium (RES; 10 mEq sodium/day) diets. RESULTS: Multivariate regression analyses (adjusted for age, race, study site, body mass index) found that Black women (ages 18-50) had significantly higher SBP than White women on both sodium diets: +8.7 ± 2.7 mmHg (P-value = .002) on a LIB diet and +8.5 ± 2.5 mmHg (P-value = .001) on a RES diet. Even among 18- to 35-year-olds-who were normotensive and nonobese-Black women had higher SBP: +7.9 ± 2.4 mmHg (P-value = .001) on a LIB diet and +7.6 ± 2.7 mmHg (P-value = .005) on a RES diet. Younger Black women also had higher plasma aldosterone concentration to plasma renin activity ratio (ARR) on both LIB and RES diets as well as a higher sodium-modulated aldosterone suppression-stimulation index-an indicator of aldosterone dysregulation. In younger Black women-but not in White women-there was a significant association between SBP and ARR on both LIB and RES diets. CONCLUSION: Young Black women had increased SBP and ARR as compared to White women on LIB and RES diets, which offers insights into the possible mechanisms for the increased hypertension and cardiovascular disease risk in an at-risk and understudied population.

Red meat intake and risk of type 2 diabetes in a prospective cohort study of United States females and males.

BACKGROUND: Studies with methodological advancements are warranted to confirm the relation of red meat consumption to the incidence of type 2 diabetes (T2D). OBJECTIVE: We aimed to assess the relationships of intakes of total, processed, and unprocessed red meat to risk of T2D and to estimate the effects of substituting different protein sources for red meats on T2D risk. METHODS: Our study included 216,695 participants (81% females) from the Nurses' Health Study (NHS), NHS II, and Health Professionals Follow-up Study (HPFS). Red meat intakes were assessed with semiquantitative food frequency questionnaires (FFQs) every 2 to 4 y since the study baselines. We used multivariable-adjusted proportional hazards models to estimate the associations between red meats and T2D. RESULTS: Over 5,483,981 person-years of follow-up, we documented 22,761 T2D cases. Intakes of total, processed, and unprocessed red meat were positively and approximately linearly associated with higher risks of T2D. Comparing the highest to the lowest quintiles, hazard ratios (HR) were 1.62 (95% confidence interval [CI]: 1.53, 1.71) for total red meat, 1.51 (95% CI: 1.44, 1.58) for processed red meat, and 1.40 (95% CI: 1.33, 1.47) for unprocessed red meat. The percentage lower risk of T2D associated with substituting 1 serving/d of nuts and legumes for total red meat was 30% (HR = 0.70, 95% CI: 0.66, 0.74), for processed red meat was 41% (HR = 0.59, 95% CI: 0.55, 0.64), and for unprocessed red meat was 29% (HR = 0.71, 95% CI: 0.67, 0.75); Substituting 1 serving/d of dairy for total, processed, or unprocessed red meat was also associated with significantly lower risk of T2D. The observed associations became stronger after we calibrated dietary intakes to intakes assessed by weighed diet records. CONCLUSIONS: Our study supports current dietary recommendations for limiting consumption of red meat intake and emphasizes the importance of different alternative sources of protein for T2D prevention.

Evaluation of Risk Prediction with Hierarchical Data: Dependency Adjusted Confidence Intervals for the AUC.

The area under the true ROC curve (AUC) is routinely used to determine how strongly a given model discriminates between the levels of a binary outcome. Standard inference with the AUC requires that outcomes be independent of each other. To overcome this limitation, a method was developed for the estimation of the variance of the AUC in the setting of two-level hierarchical data using probit-transformed prediction scores generated from generalized estimating equation models, thereby allowing for the application of inferential methods. This manuscript presents an extension of this approach so that inference for the AUC may be performed in a three-level hierarchical data setting (e.g., eyes nested within persons and persons nested within families). A method that accounts for the effect of tied prediction scores on inference is also described. The performance of 95% confidence intervals around the AUC was assessed through the simulation of three-level clustered data in multiple settings, including ones with tied data and variable cluster sizes. Across all settings, the actual 95% confidence interval coverage varied from 0.943 to 0.958, and the ratio of the theoretical variance to the empirical variance of the AUC varied from 0.920 to 1.013. The results are better than those from existing methods. Two examples of applying the proposed methodology are presented.

Exposure to Particulate Matter Air Pollution and Age of Menarche in a Nationwide Cohort of U.S. Girls.

BACKGROUND: It remains unclear whether in utero and childhood exposure to air pollution affects pubertal development, particularly age of menarche in girls. OBJECTIVE: The aim of this study was to determine whether residential ambient particulate matter (PM) exposure in utero and during childhood is associated with age of menarche. METHODS: We studied 5,201 girls in the Growing Up Today Study 2 (2004-present) who were 10-17 y of age at enrollment (47.7% premenarchal; 52.3% postmenarchal). Exposure to three size fractions of PM [fine PM with aerodynamic diameter ≤2.5µm (PM2.5), PM with aerodynamic diameters between 2.5µm and 10µm (PM2.5-10), and PM with aerodynamic diameter 10µm (PM10)] was assigned based on maternal residential address, updated every 2 y, using nationwide spatiotemporal models. We estimated average PM exposure in utero, and time-varying windows: annual average exposure in the prior 1 and 2 y and cumulative average from birth. Age of menarche was self-reported on three surveys administered in 2004, 2006, and 2008. We calculated hazard ratios (HR) for menarche for an interquartile range (IQR) increase in PM exposure using Cox proportional hazard models adjusting for potential confounders. RESULTS: Girls attained menarche at 12.3 y of age on average. In the adjusted model, higher residential exposure to ambient PM2.5 during all time windows was associated with earlier age of menarche. The HRs of menarche for each IQR (4 µg/m3) increase in exposure to PM2.5 during the in utero period, 1 y prior to menarche, and throughout childhood were 1.03 [95% confidence interval (CI): 1.00, 1.06], 1.06 (95% CI: 1.02, 1.10) and 1.06 (95% CI: 1.02, 1.10), respectively. Effect estimates for PM10 exposure were similar, albeit attenuated, for all time windows. PM2.5-10 exposure was not associated with age of menarche. DISCUSSION: Among a large, nationwide, prospective cohort of U.S. girls, higher exposure to PM2.5 and PM10 in utero and throughout childhood was associated with an earlier age of menarche. Our results suggest that PM2.5 and PM10 may have endocrine-disrupting properties that could lead to altered timing of menarche. https://doi.org/10.1289/EHP12110.

A Randomized, Double-Blind, Placebo-Controlled Decentralized Trial to Assess Sleep, Health Outcomes, and Overall Well-Being in Healthy Adults Reporting Disturbed Sleep, Taking a Melatonin-Free Supplement.

Inadequate sleep is a global health concern. Sleep is multidimensional and complex; new multi-ingredient agents are needed. This study assessed the comparative effects of two multi-ingredient supplements on sleep relative to placebo. Adults (N = 620) seeking better sleep were randomly assigned to receive one of three study products. Sleep A (contained lower (0.35 mg THC and higher levels of botanicals (75 mg each hops oil and valerian oil), Sleep B (contained higher THC (0.85 mg) and lower botanicals (20 mg each hops oil and valerian oil) or placebo) for 4 weeks. Sleep disturbance was assessed at baseline and weekly using NIH's Patient-Reported Outcomes Measurement Information System (PROMIS™) Sleep Disturbance SF 8A survey. Anxiety, stress, pain, and well-being were assessed using validated measures at baseline and weekly. A linear mixed-effects regression model was used to assess the change in health outcome score between active product groups and the placebo. There was a significant difference in sleep disturbance, anxiety, stress, and well-being between Sleep A and placebo. There was no significant difference in any health parameter between Sleep B and placebo. Side effects were mild or moderate. There were no significant differences in the frequency of side effects between the study groups. A botanical blend containing a low concentration of THC improved sleep disturbance, anxiety, stress, and well-being in healthy individuals that reported better sleep as a primary health concern.

Design issues in crossover trials involving patients with Parkinson's disease.

Background and objectives: Crossover designs are frequently used to assess treatments for patients with Parkinson's disease. Typically, two-period two-treatment trials include a washout period between the 2 periods and assume that the washout period is sufficiently long to eliminate carryover effects. A complementary strategy might be to jointly model carryover and treatment effects, though this has rarely been done in Parkinson's disease crossover studies. The primary objective of this research is to demonstrate a modeling approach that assesses treatment and carryover effects in one unified mixed model analysis and to examine how it performs in a simulation study and a real data analysis example, as compared to other data analytic approaches used in Parkinson's disease crossover studies. Methods: We examined how three different methods of analysis (standard crossover t-test, mixed model with a carryover term included in model statement, and mixed model with no carryover term) performed in a simulation study and illustrated the methods in a real data example in Parkinson's disease. Results: The simulation study based on the presence of a carryover effect indicated that mixed models with a carryover term and an unstructured correlation matrix provided unbiased estimates of treatment effect and appropriate type I error. The methods are illustrated in a real data example involving Parkinson's disease. Our literature review revealed that a majority of crossover studies included a washout period but did not assess whether the washout was sufficiently long to eliminate the possibility of carryover. Discussion: We recommend using a mixed model with a carryover term and an unstructured correlation matrix to obtain unbiased estimates of treatment effect.

Analytical method for detecting outlier evaluators.

BACKGROUND: Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential 'outlier' evaluators are needed to improve data quality during data collection stage. METHODS: In this paper, we propose a two-stage algorithm to detect 'outlier' evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators' effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect 'outlier' evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential 'outlier' audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses' Health Study II. RESULTS: Our simulation study shows that our method not only can detect true 'outlier' evaluators, but also is less likely to falsely reject true 'normal' evaluators. CONCLUSIONS: Our two-stage 'outlier' detection algorithm is a flexible approach that can effectively detect 'outlier' evaluators, and thus data quality can be improved during data collection stage.

Incidence of and Risk Factors for Cataract in Anterior Uveitis.

PURPOSE: To estimate the incidence/risk factors for cataract in noninfectious anterior uveitis. DESIGN: Retrospective multicenter cohort study (6 US tertiary uveitis sites, 1978-2010). METHODS: Data were harvested by trained expert reviewers, using protocol-driven review of experts' charts. We studied cataract incidence-newly reduced visual acuity worse than 20/40 attributed to cataract; or incident cataract surgery-in 3923 eyes of 2567 patients with anterior uveitis. RESULTS: Cataract developed in 507 eyes (54/1000 eye-years, 95% CI 49-59). Time-updated risk factors associated with cataract included older age (≥65 vs <18 years: adjusted hazard ratio [aHR] 5.04, 95% CI 3.04-8.33), higher anterior chamber cell grade (P(trend)=0.001), prior incisional glaucoma surgery (aHR 1.86, 95% CI 1.10-3.14), band keratopathy (aHR 2.23, 95% CI 1.47-3.37), posterior synechiae (aHR 3.71, 95% CI 2.83-4.87), and elevated intraocular pressure ≥30 vs 6-20 mm Hg (aHR 2.57, 95% CI 1.38-4.77). Primary acute (aHR 0.59, 95% CI 0.30-1.15) and recurrent acute (aHR 0.74, 95% CI 0.55-0.98) had lower cataract risk than chronic anterior uveitis. Higher-dose prednisolone acetate 1%-equivalent use (≥2 drops/day) was associated with >2-fold higher cataract risk in eyes with anterior chamber cell grades 0.5+ or lower but was not associated with higher cataract risk in the presence of anterior chamber cells of grade 1+ or higher. CONCLUSIONS: Cataract complicates anterior uveitis in ∼5.4/100 eye-years. Several fixed and modifiable risk factors were identified, yielding a point system to guide cataract risk minimization. Topical corticosteroids only were associated with increased cataract risk when anterior chamber cells were absent or minimally present, suggesting their use to treat active inflammation (which itself is cataractogenic) does not cause a net increase in cataract incidence.

Family History of Age-Related Macular Degeneration and Genetics Predict Progression to Advanced Age-Related Macular Degeneration Adjusting for Macular Status, Demographic, and Lifestyle Factors.

PURPOSE: To determine if a family history of age-related macular degeneration (AMD) and genetic variants identify eyes at higher risk for progression to advanced AMD (AAMD), after controlling for baseline demographics, behavioral factors, and macular status. DESIGN: Prospective, longitudinal cohort study. METHODS: Eyes were classified using the Age-Related Eye Disease Study severity scale. Non-genetic and genetic predictors for progression to AAMD, geographic atrophy, and neovascular disease were evaluated. Cox proportional hazards models using the eye as the unit of analysis were used to calculate hazard ratios (HRs), accounting for correlated data. Discrimination between progressing and non-progressing eyes was assessed using C-statistics and net reclassification improvement (NRI). RESULTS: Among 4910 eyes, 863 progressed to AAMD over 12 years. Baseline AMD severity scale and status of the fellow eye were important predictors; genes provided additional discrimination. A family history of AMD also independently predicted progression after accounting for genetic and other covariates: 1 family member versus none (HR 1.21 [95% confidence interval {CI} 1.02-1.43]; P = 0.03); ≥2 family members versus none (HR 1.55 [95% CI 1.26-1.90]; P < 0.001). A composite risk score calculated using ß estimates of both non-genetic and significant genetic factors predicted progression to AAMD (HR 5.57; 90th vs 10th percentile; area under the receiver operating characteristic curve [AUC] = 0.92), providing superior fit compared with other models, including one with only ocular variables (NRI = 0.34; P < 0.001; AUC = 0.87, ΔAUC 0.05 ± 0.005; P < 0.001). CONCLUSION: Genetic variants and family history provided additional discrimination for predicting progression to AAMD, after accounting for baseline macular status and other covariates.