Improving lifestyle behaviors during chemotherapy for breast cancer: The Lifestyle, Exercise, and Nutrition Early After Diagnosis (LEANer) Trial.

BACKGROUND: Little is known about improving physical activity (PA) and diet during and after chemotherapy for breast cancer. This secondary analysis examines changes in PA and diet quality during a yearlong intervention for patients with breast cancer undergoing chemotherapy and evaluates factors associated with these changes. METHODS: Newly diagnosed patients with breast cancer (N = 173) undergoing chemotherapy were randomized to a year-long nutrition and exercise intervention (n = 87) or usual care (UC, n = 86). Mixed models compared 1-year changes in PA and diet quality via the Healthy Eating Index (HEI)-2015 by study arm. Among the intervention group, baseline factors associated with change in PA and diet were assessed with multivariable linear and logistic regression. RESULTS: At 1 year, compared with UC, the intervention arm increased PA more (mean difference = 136.1 minutes/week; 95% CI, 90.2-182.0), participated in more strength training (56% vs. 15%; p < .001), and had suggestive improvements in HEI-2015 (mean difference = 2.5; 95% CI, -0.3 to 5.3; p = .08). In the intervention arm, lower fatigue was associated with improved PA (p = .04) and higher education was associated with improved HEI-2015 (p = .001) at 1 year. Higher HEI-2015 (p = .04) and married/living with someone (p = .05) were associated with higher odds of participating in strength training at 1 year. CONCLUSIONS: This year-long lifestyle intervention for patients with breast cancer undergoing chemotherapy resulted in increases in PA and suggestive improvements in diet quality. Behavior change was associated with baseline fatigue, diet quality, education, and married/living with someone. Addressing these factors in interventions may improve uptake of lifestyle behaviors in trials during and after chemotherapy.

Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure.

Regression calibration as developed by Rosner, Spiegelman, and Willett is used to adjust the bias in effect estimates due to measurement error in continuous exposures. The method involves two models: a measurement error model relating the mismeasured exposure to the true (or gold-standard) exposure and an outcome model relating the mismeasured exposure to the outcome. However, no comprehensive guidance exists for determining which covariates should be included in each model. In this article, we investigate the selection of the minimal and most efficient covariate adjustment sets under a causal inference framework. We show that to address the measurement error, researchers must adjust for, in both measurement error and outcome models, any common causes (1) of true exposure and the outcome and (2) of measurement error and the outcome. We also show that adjusting for so-called prognostic variables that are independent of true exposure and measurement error in the outcome model, may increase efficiency, while adjusting for any covariates that are associated only with true exposure generally results in efficiency loss in realistic settings. We apply the proposed covariate selection approach to the Health Professional Follow-up Study dataset to study the effect of fiber intake on cardiovascular disease. Finally, we extend the originally proposed estimators to a nonparametric setting where effect modification by covariates is allowed.

Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies.

BACKGROUND: Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery. METHODS: We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors. RESULTS: There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87). CONCLUSIONS: These methods will be useful for evaluating intervention packages in studies with network features.

Overall, Direct, Spillover, and Composite Effects of Components of a Peer-Driven Intervention Package on Injection Risk Behavior Among People Who Inject Drugs in the HPTN 037 Study.

We sought to disentangle effects of the components of a peer-education intervention on self-reported injection risk behaviors among people who inject drugs (n = 560) in Philadelphia, US. We examined 226 egocentric groups/networks randomized to receive (or not) the intervention. Peer-education training consisted of two components delivered to the intervention network index individual only: (1) an initial training and (2) "booster" training sessions during 6- and 12-month follow up visits. In this secondary data analysis, using inverse-probability-weighted log-binomial mixed effects models, we estimated the effects of the components of the network-level peer-education intervention upon subsequent risk behaviors. This included contrasting outcome rates if a participant is a network member [non-index] under the network exposure versus under the network control condition (i.e., spillover effects). We found that compared to control networks, among intervention networks, the overall rates of injection risk behaviors were lower in both those recently exposed (i.e., at the prior visit) to a booster (rate ratio [95% confidence interval]: 0.61 [0.46-0.82]) and those not recently exposed to it (0.81 [0.67-0.98]). Only the boosters had statistically significant spillover effects (e.g., 0.59 [0.41-0.86] for recent exposure). Thus, both intervention components reduced injection risk behaviors with evidence of spillover effects for the boosters. Spillover should be assessed for an intervention that has an observable behavioral measure. Efforts to fully understand the impact of peer education should include routine evaluation of spillover effects. To maximize impact, boosters can be provided along with strategies to recruit especially committed peer educators and to increase attendance at trainings. Clinical Trials Registration Clinicaltrials.gov NCT00038688 June 5, 2002.

RESUMEN: Intentamos desenmarañar los efectos de los componentes de una intervención de educación entre pares sobre los comportamientos de inyección de riesgo autorreportados entre personas que se inyectan drogas (n = 560; 226 grupos/redes egocéntricos(as)) aleatorizados(as) a recibir (o no) la intervención en Filadelfia, EUA. Dos componentes fueron administrados a índices de redes de intervención: una capacitación inicial y sesiones de "refuerzo" durante visitas de seguimiento. Usando modelos log-binomial de efectos mixtos ponderados por probabilidad inversa, estimamos los efectos de dichos componentes sobre los comportamientos de riesgo posteriores. Encontramos que en comparación con las redes control, en las redes de intervención, las tasas generales de comportamientos de inyección de riesgo fueron más bajas en ambas aquellas expuestas recientemente a un refuerzo (razón de tasas [intervalo de confianza del 95%]: 0.61 [0.46­0.82]) y aquellas no expuestas recientemente (0.81 [0.67­0.98]). Solamente los refuerzos tuvieron efectos derrame (i.e., contraste de las tasas de resultados si es miembro [no índice] de una red en una red con exposición reciente versus bajo la condición control) significativos (p. ej., 0.59 [0.41­0.86] para la exposición reciente).

Is the Product Method More Efficient Than the Difference Method for Assessing Mediation?

Mediation analysis is widely used in biomedical research to quantify the extent to which the effect from an exposure on a health outcome is through a mediator and the extent to which the effect is direct. A traditional approach for quantifying mediation is through the difference method. The other popular approach uses a counterfactual framework from which the product method arises. However, there is little prior work to articulate which method is more efficient for estimating 2 key quantities in mediation analysis, the natural indirect effect and mediation proportion. To fill in this gap, we investigated the asymptotic relative efficiency for mediation measure estimators given by the product method and the difference method. We considered 4 data types characterized by continuous and binary mediators and outcomes. Under certain conditions, we show analytically that the product method is equally efficient to the difference method, or more efficient. However, our numerical studies demonstrate that the difference method is usually at least 90% as efficient as the product method under realistic scenarios in epidemiologic research, especially for estimating the mediation proportion. We demonstrate the efficiency results by analyzing the MaxART study (Eswatini, 2014-2017), which aimed to evaluate the effectiveness of the early access to antiretroviral therapy among human immunodeficiency virus-positive patients.

Vitamin D Supplements for Prevention of Tuberculosis Infection and Disease.

BACKGROUND: Vitamin D metabolites support innate immune responses to Mycobacterium tuberculosis. Data from phase 3, randomized, controlled trials of vitamin D supplementation to prevent tuberculosis infection are lacking. METHODS: We randomly assigned children who had negative results for M. tuberculosis infection according to the QuantiFERON-TB Gold In-Tube assay (QFT) to receive a weekly oral dose of either 14,000 IU of vitamin D3 or placebo for 3 years. The primary outcome was a positive QFT result at the 3-year follow-up, expressed as a proportion of children. Secondary outcomes included the serum 25-hydroxyvitamin D (25[OH]D) level at the end of the trial and the incidence of tuberculosis disease, acute respiratory infection, and adverse events. RESULTS: A total of 8851 children underwent randomization: 4418 were assigned to the vitamin D group, and 4433 to the placebo group; 95.6% of children had a baseline serum 25(OH)D level of less than 20 ng per milliliter. Among children with a valid QFT result at the end of the trial, the percentage with a positive result was 3.6% (147 of 4074 children) in the vitamin D group and 3.3% (134 of 4043) in the placebo group (adjusted risk ratio, 1.10; 95% confidence interval [CI], 0.87 to 1.38; P = 0.42). The mean 25(OH)D level at the end of the trial was 31.0 ng per milliliter in the vitamin D group and 10.7 ng per milliliter in the placebo group (mean between-group difference, 20.3 ng per milliliter; 95% CI, 19.9 to 20.6). Tuberculosis disease was diagnosed in 21 children in the vitamin D group and in 25 children in the placebo group (adjusted risk ratio, 0.87; 95% CI, 0.49 to 1.55). A total of 29 children in the vitamin D group and 34 in the placebo group were hospitalized for treatment of acute respiratory infection (adjusted risk ratio, 0.86; 95% CI, 0.52 to 1.40). The incidence of adverse events did not differ significantly between the two groups. CONCLUSIONS: Vitamin D supplementation did not result in a lower risk of tuberculosis infection, tuberculosis disease, or acute respiratory infection than placebo among vitamin D-deficient schoolchildren in Mongolia. (Funded by the National Institutes of Health; ClinicalTrials.gov number, NCT02276755.).

Correcting for bias due to mismeasured exposure history in longitudinal studies with continuous outcomes.

Epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories in relation to continuous outcomes, for example, cognitive function. However, the individual exposure measurements that constitute the history upon which an exposure history function is constructed are usually mismeasured. To obtain unbiased estimates of the effects for mismeasured functions in longitudinal studies, a method incorporating main and validation studies was developed. Simulation studies under several realistic assumptions were conducted to assess its performance compared to standard analysis, and we found that the proposed method has good performance in terms of finite sample bias reduction and nominal confidence interval coverage. We applied it to a study of long-term exposure to PM 2.5 $\text{PM}_{2.5}$ , in relation to cognitive decline in the Nurses' Health Study Previously, it was found that the 2-year decline in the standard measure of cognition was 0.018 (95% CI, -0.034 to -0.001) units worse per 10 µ g/m 3 $\mu \text{g/m}^3$ increase in PM 2.5 $\text{PM}_{2.5}$ exposure. After correction, the estimated impact of PM 2.5 $\text{PM}_{2.5}$ on cognitive decline increased to 0.027 (95% CI, -0.059 to 0.005) units lower per 10 µ g/m 3 $\mu \text{g/m}^3$ increase. To put this into perspective, effects of this magnitude are about 2/3 of those found in our data associated with each additional year of aging: 0.044 (95% CI, -0.047 to -0.040) units per 1 year older after applying our correction method.

Mediation analysis in the presence of continuous exposure measurement error.

The difference method is used in mediation analysis to quantify the extent to which a mediator explains the mechanisms underlying the pathway between an exposure and an outcome. In many health science studies, the exposures are almost never measured without error, which can result in biased effect estimates. This article investigates methods for mediation analysis when a continuous exposure is mismeasured. Under a linear exposure measurement error model, we prove that the bias of indirect effect and mediation proportion can go in either direction but the mediation proportion is usually be less biased when the associations between the exposure and its error-prone counterpart are similar with and without adjustment for the mediator. We further propose methods to adjust for exposure measurement error with continuous and binary outcomes. The proposed approaches require a main study/validation study design where in the validation study, data are available for characterizing the relationship between the true exposure and its error-prone counterpart. The proposed approaches are then applied to the Health Professional Follow-up Study, 1986-2016, to investigate the impact of body mass index (BMI) as a mediator for mediating the effect of physical activity on the risk of cardiovascular diseases. Our results reveal that physical activity is significantly associated with a lower risk of cardiovascular disease incidence, and approximately half of the total effect of physical activity is mediated by BMI after accounting for exposure measurement error. Extensive simulation studies are conducted to demonstrate the validity and efficiency of the proposed approaches in finite samples.

Trusted residents and housing assistance to decrease violence exposure in New Haven (TRUE HAVEN): a strengths-based and community-driven stepped-wedge intervention to reduce gun violence.

BACKGROUND: We describe the rationale and study design for "TRUsted rEsidents and Housing Assistance to decrease Violence Exposure in New Haven (TRUE HAVEN)," a prospective type 1 hybrid effectiveness/implementation study of a multi-level intervention using a stepped wedge design. TRUE HAVEN aims to lower rates of community gun violence by fostering the stability, wealth, and well-being of individuals and families directly impacted by incarceration through the provision of stable housing and by breaking the cycle of trauma. DESIGN: TRUE HAVEN is an ongoing, multi-level intervention with three primary components: financial education paired with housing support (individual level), trauma-informed counseling (neighborhood level), and policy changes to address structural racism (city/state level). Six neighborhoods with among the highest rates of gun violence in New Haven, Connecticut, will receive the individual and neighborhood level intervention components sequentially beginning at staggered 6-month steps. Residents of these neighborhoods will be eligible to participate in the housing stability and financial education component if they were recently incarcerated or are family members of currently incarcerated people; participants will receive intense financial education and follow-up for six months and be eligible for special down payment and rental assistance programs. In addition, trusted community members and organization leaders within each target neighborhood will participate in trauma-informed care training sessions to then be able to recognize when their peers are suffering from trauma symptoms, to support these affected peers, and to destigmatize accessing professional mental health services and connect them to these services when needed. Finally, a multi-stakeholder coalition will be convened to address policies that act as barriers to housing stability or accessing mental healthcare. Interventions will be delivered through existing partnerships with community-based organizations and networks. The primary outcome is neighborhood rate of incident gun violence. To inform future implementation and optimize the intervention package as the study progresses, we will use the Learn As You Go approach to optimize and assess the effectiveness of the intervention package on the primary study outcome. DISCUSSION: Results from this protocol will yield novel evidence for whether and how addressing structural racism citywide leads to a reduction in gun violence. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05723614. Registration date: February 01, 2023. Please refer to https://clinicaltrials.gov/ct2/show/NCT05723614 for public and scientific inquiries.

Estimation and inference for the population attributable risk in the presence of misclassification.

Because it describes the proportion of disease cases that could be prevented if an exposure were entirely eliminated from a target population as a result of an intervention, estimation of the population attributable risk (PAR) has become an important goal of public health research. In epidemiologic studies, categorical covariates are often misclassified. We present methods for obtaining point and interval estimates of the PAR and the partial PAR (pPAR) in the presence of misclassification, filling an important existing gap in public health evaluation methods. We use a likelihood-based approach to estimate parameters in the models for the disease and for the misclassification process, under main study/internal validation study and main study/external validation study designs, and various plausible assumptions about transportability. We assessed the finite sample perf ormance of this method via a simulation study, and used it to obtain corrected point and interval estimates of the pPAR for high red meat intake and alcohol intake in relation to colorectal cancer incidence in the HPFS, where we found that the estimated pPAR for the two risk factors increased by up to 317% after correcting for bias due to misclassification.

Anemia Etiology in Ethiopia: Assessment of Nutritional, Infectious Disease, and Other Risk Factors in a Population-Based Cross-Sectional Survey of Women, Men, and Children.

BACKGROUND: While the causes of anemia at an individual level (such as certain nutritional deficiencies, infections, and genetic disorders) are well defined, there is limited understanding of the relative burden of anemia attributable to each cause within populations. OBJECTIVES: We sought to estimate the proportion of anemia cases attributable to nutrition, infectious diseases, and other risk factors among women, men, and children in 6 regions of Ethiopia. METHODS: A population-based cross-sectional study was conducted. Data were obtained from 2520 women of reproductive age (15-49 y), 1044 adult men (15-49 y), and 1528 children (6-59 mo). Participants provided venous blood samples for assessment of their hemoglobin concentration; ferritin, folate, vitamin B12, and C-reactive protein levels; and the presence of malaria infection. Stool samples were collected to ascertain the helminth infection status. Sociodemographic questionnaires and a 24-h diet recall were administered. Population-weighted prevalences of anemia and risk factors were calculated. Multivariable-adjusted associations of risk factors with anemia and partial population attributable risk percentages were estimated using generalized linear models. RESULTS: The anemia prevalences were 17% (95% CI: 13%-21%) among women, 8% (95% CI: 6%-12%) among men, and 22% (95% CI: 19%-26%) among children. Low serum ferritin contributed to 11% (95% CI: -1% to 23%) of anemia cases among women, 9% (95% CI: 0%-17%) among men, and 21% (95% CI: 4%-34%) among children. The proportions of anemia attributable to low serum folate were estimated at 25% (95% CI: 5%-41%) among women and 29% (95% CI: 11%-43%) among men. Dietary iron intake was adequate for nearly all participants, while inadequacy was common for folate and vitamin B12. Inflammation and malaria were responsible for less than 1 in 10 anemia cases. CONCLUSIONS: Folate deficiency, iron deficiency, and inflammation appear to be important contributors to anemia in Ethiopia. Folic acid food fortification, targeted iron interventions, and strategies to reduce infections may be considered as potential public health interventions to reduce anemia in Ethiopia.

'Mental health and self-rated health among U.S. South Asians: the role of religious group involvement'.

Objectives: Only one community-based study has assessed religious group involvement and health outcomes among South Asians in the U.S., with mixed results. Here, using a large, South Asian community-based sample, the effects of six religious group involvement predictors - religious tradition, attendance, group prayer, giving/receiving congregational emotional support, congregational neglect, and congregational criticism - were examined in relation to four health outcomes: self-rated health, positive mental health functioning, trait anxiety, and trait anger.Design: The study used a new religion/spirituality questionnaire in the Mediators of Atherosclerosis Among South Asians Living in America (MASALA), the largest study of mental and physical well-being among U.S. South Asians. Associations were assessed cross-sectionally using OLS regression in both the full sample (N = 928) and a subsample of congregation members (N = 312).Results: Jains reported better self-rated health compared to Hindus and Muslims. Group prayer involvement, when measured ordinally, was positively associated with self-rated health and mental health functioning. In reference group comparisons, individuals who participated in group prayer once/day or more had lower levels of anxiety and anger compared to several comparison groups in which individuals prayed less than once a day. Religious service attendance was associated with higher levels of anxiety. Giving/receiving congregational emotional support was positively associated with self-rated health and mental health functioning, and inversely associated with anxiety. Congregational criticism was associated with higher levels of anger and anxiety.Conclusions: This study provided a new assessment of religious group involvement and health in the U.S. South Asian population. Religious group participation was associated with mental and self-rated health in well-controlled models, indicating this is a fruitful area for further research. Group religious involvement may be a health-promoting resource for U.S. South Asians who are religiously active, but it is not an unalloyed boon.

Adjunctive testing by cytology, p16/Ki-67 dual-stained cytology or HPV16/18 E6 oncoprotein for the management of HPV16/18 screen-positive women.

High-risk human papillomavirus type 16/18 (HPV16/18) genotyping is unable to accurately discriminate nonprogressive infections from those that will progress to cervical cancer. Our study aimed to assesses if additional testing either with liquid-based cytology (LBC) or the putative progression markers p16/Ki-67 and HPV16/18 E6 oncoprotein (E6) can improve the efficiency of HPV16/18 genotyping for triaging high-risk HPV (hrHPV)-positive women through better cancer risk stratification. Women attending colposcopy after positive HPV16/18 genotyping results within the Forwarding Research for Improved Detection and Access for Cervical Cancer Screening and Triage (FRIDA) hrHPV-based screening study in Tlaxcala, Mexico, underwent further testing with LBC, p16/Ki-67 dual-stained (DS) cytology and E6. We calculated measures of test performance for detecting histologically confirmed cervical intraepithelial neoplasia grade 2 or higher (CIN2+) and grade 3 or higher (CIN3+). A number of 475 (64.3%) of 739 HPV16/18-positive women had complete results for all tests. Triage positivity rates were 14.1%, 18.5% and 24.4%, for LBC, E6 and DS, respectively. Compared with LBC, DS had higher sensitivity (24.4% vs 60.0%) although lower specificity (87.0% vs 79.3%) for CIN3+ (P < .001), whereas E6 had a sensitivity of 37.8% and a specificity of 83.5%. No invasive cancer was missed by DS or E6, but 75% were in normal cytology. DS test was associated with nearly 75% reduction of colposcopy referrals compared with the direct referral of all HPV16/18-positive women, giving the least number of colposcopies (n = 4.3) per CIN3+ detected. We show that adjunctive testing of HPV16/18-positive women with DS may greatly reduce unnecessary colposcopy referrals within HPV-based screening employing HPV16/18 genotyping while retaining acceptable sensitivity for CIN2+ and CIN3+.

A maximum likelihood approach to power calculations for stepped wedge designs of binary outcomes.

In stepped wedge designs (SWD), clusters are randomized to the time period during which new patients will receive the intervention under study in a sequential rollout over time. By the study's end, patients at all clusters receive the intervention, eliminating ethical concerns related to withholding potentially efficacious treatments. This is a practical option in many large-scale public health implementation settings. Little statistical theory for these designs exists for binary outcomes. To address this, we utilized a maximum likelihood approach and developed numerical methods to determine the asymptotic power of the SWD for binary outcomes. We studied how the power of a SWD for detecting risk differences varies as a function of the number of clusters, cluster size, the baseline risk, the intervention effect, the intra-cluster correlation coefficient, and the time effect. We studied the robustness of power to the assumed form of the distribution of the cluster random effects, as well as how power is affected by variable cluster size. % SWD power is sensitive to neither, in contrast to the parallel cluster randomized design which is highly sensitive to variable cluster size. We also found that the approximate weighted least square approach of Hussey and Hughes (2007, Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 28, 182-191) for binary outcomes under-estimates the power in some regions of the parameter spaces, and over-estimates it in others. The new method was applied to the design of a large-scale intervention program on post-partum intra-uterine device insertion services for preventing unintended pregnancy in the first 1.5 years following childbirth in Tanzania, where it was found that the previously available method under-estimated the power.

Longitudinal analysis of client appointment adherence under Universal Test and Treat strategy: A stepped-wedge trial.

OBJECTIVES: Universal Test and Treat (UTT) strategies are being adopted across sub-Saharan Africa based on clinical benefits to morbidity and mortality and to attain targets of the Joint United Nations Programme on HIV/AIDS (UNAIDS). Universal Test and Treat is expected to change the client population at clinics, due to more asymptomatic HIV clients initiating antiretroviral therapy (ART). We assessed the impact of UTT on client appointment adherence at 14 government-managed health facilities in Eswatini's public sector health system. METHODS: We assessed the impact of UTT on client adherence to appointment schedules from 2014 to 2017 in a stepped-wedge trial. Repeated measures analysis was used to assess adherence to each scheduled appointment (primary definition: presenting for care within 7 days after the scheduled appointment), adjusting for time, age, sex, stage, marital status, ART status and facility. RESULTS: Among 3354 clients (62.1% female; 57.4% < 35 years), a median (interquartile range) of 10 (6-15) appointments were scheduled during follow-up. In a multivariable-adjusted model, appointment adherence was significantly greater in clients who were female [odds ratio (OR) = 1.38, 95% confidence interval (CI): 1.25-1.52], older (e.g. 40 to < 50 years vs. < 20 years; OR = 1.45, 95% CI: 1.00-2.09), married (OR = 1.31, 95% CI: 1.19-1.44), had lower WHO stage at study enrolment (1-2 vs. 3-4: OR = 1.26, 95% CI: 1.13-1.41), and were currently on ART (OR = 3.55, 95% CI: 2.62-4.82). However, UTT strategy was not significantly associated with client adherence to scheduled appointments (OR = 1.02, 95% CI: 0.72-1.45). CONCLUSIONS: Despite transitioning to UTT, there was no change in visit adherence, a reassuring finding given the large volume of clients currently being initiated at earlier stages of HIV.

Estimating the natural indirect effect and the mediation proportion via the product method.

BACKGROUND: The natural indirect effect (NIE) and mediation proportion (MP) are two measures of primary interest in mediation analysis. The standard approach for mediation analysis is through the product method, which involves a model for the outcome conditional on the mediator and exposure and another model describing the exposure-mediator relationship. The purpose of this article is to comprehensively develop and investigate the finite-sample performance of NIE and MP estimators via the product method. METHODS: With four common data types with a continuous/binary outcome and a continuous/binary mediator, we propose closed-form interval estimators for NIE and MP via the theory of multivariate delta method, and evaluate its empirical performance relative to the bootstrap approach. In addition, we have observed that the rare outcome assumption is frequently invoked to approximate the NIE and MP with a binary outcome, although this approximation may lead to non-negligible bias when the outcome is common. We therefore introduce the exact expressions for NIE and MP with a binary outcome without the rare outcome assumption and compare its performance with the approximate estimators. RESULTS: Simulation studies suggest that the proposed interval estimator provides satisfactory coverage when the sample size ≥500 for the scenarios with a continuous outcome and sample size ≥20,000 and number of cases ≥500 for the scenarios with a binary outcome. In the binary outcome scenarios, the approximate estimators based on the rare outcome assumption worked well when outcome prevalence less than 5% but could lead to substantial bias when the outcome is common; in contrast, the exact estimators always perform well under all outcome prevalences considered. CONCLUSIONS: Under samples sizes commonly encountered in epidemiology and public health research, the proposed interval estimator is valid for constructing confidence interval. For a binary outcome, the exact estimator without the rare outcome assumption is more robust and stable to estimate NIE and MP. An R package mediateP is developed to implement the methods for point and variance estimation discussed in this paper.

ANALYSIS OF "LEARN-AS-YOU-GO" (LAGO) STUDIES.

In Learn-As-you-GO (LAGO) adaptive studies, the intervention is a complex multicomponent package, and is adapted in stages during the study based on past outcome data. This design formalizes standard practice in public health intervention studies. An effective intervention package is sought, while minimizing intervention package cost. In LAGO study data, the interventions in later stages depend upon the outcomes in the previous stages, violating standard statistical theory. We develop an estimator for the intervention effects, and prove consistency and asymptotic normality using a novel coupling argument, ensuring the validity of the test for the hypothesis of no overall intervention effect. We develop a confidence set for the optimal intervention package and confidence bands for the success probabilities under alternative package compositions. We illustrate our methods in the BetterBirth Study, which aimed to improve maternal and neonatal outcomes among 157,689 births in Uttar Pradesh, India through a multicomponent intervention package.

Facilitators and barriers to healthy eating in a worksite cafeteria: a qualitative study.

BACKGROUND: Worksite-based nutrition interventions can serve as access points to facilitate healthy eating and translate existing knowledge of cardiometabolic disease prevention. We explored perceptions, facilitators, and barriers for healthy eating in a cafeteria at a large worksite in Mexico City. METHODS: We conducted an exploratory qualitative study in a large department store in Mexico City with ~ 1500 employees. We conducted eight focus group discussions (FGD) with 63 employees stratified by job category (sales, maintenance, shipping, restaurant, cafeteria, administrative staff, and sales managers). Employees were invited to participate in the FGD if they were at the store at the day and time of the FGD for their job type. FGDs were audio-recorded, transcribed verbatim and analyzed using the thematic method. This process involved the researches´ familiarizing themselves with the data, generating initial codes, searching for themes, reviewing the themes, defining and naming themes, and then interpreting the data. RESULTS: Employees defined healthy eating as eating foods that are fresh, diverse, and prepared hygienically. The most commonly reported facilitators of healthy eating at the worksite were availability of affordable healthy food options and employees' high health awareness. Major barriers to healthy eating included unavailability of healthy foods, unpleasant taste of food, and preference for fatty foods and meat. For lower-wage workers, affordability was a major concern. Other barriers included lack of time to eat work and long working hours. CONCLUSION: A broad range of factors affect healthy eating at the cafeteria, some related to nutrition and some related to the employees type of job. Availability of healthy, hygienic, and tasty food at an affordable price could lead to healthier food choices in the worksite cafeteria. These strategies, along with work schedules that allow sufficient time for healthy eating, may help improve dietary behaviors and health of employees.

Health system gaps in cardiovascular disease prevention and management in Nepal.

BACKGROUND: Cardiovascular diseases (CVDs) are the leading cause of deaths and disability in Nepal. Health systems can improve CVD health outcomes even in resource-limited settings by directing efforts to meet critical system gaps. This study aimed to identify Nepal's health systems gaps to prevent and manage CVDs. METHODS: We formed a task force composed of the government and non-government representatives and assessed health system performance across six building blocks: governance, service delivery, human resources, medical products, information system, and financing in terms of equity, access, coverage, efficiency, quality, safety and sustainability. We reviewed 125 national health policies, plans, strategies, guidelines, reports and websites and conducted 52 key informant interviews. We grouped notes from desk review and transcripts' codes into equity, access, coverage, efficiency, quality, safety and sustainability of the health system. RESULTS: National health insurance covers less than 10% of the population; and more than 50% of the health spending is out of pocket. The efficiency of CVDs prevention and management programs in Nepal is affected by the shortage of human resources, weak monitoring and supervision, and inadequate engagement of stakeholders. There are policies and strategies in place to ensure quality of care, however their implementation and supervision is weak. The total budget on health has been increasing over the past five years. However, the funding on CVDs is negligible. CONCLUSION: Governments at the federal, provincial and local levels should prioritize CVDs care and partner with non-government organizations to improve preventive and curative CVDs services.

Erythrocyte membrane fatty acids and breast cancer risk by tumor tissue expression of immuno-inflammatory markers and fatty acid synthase: a nested case-control study.

BACKGROUND: Previous studies of fatty acids and breast cancer risk have shown mixed results, which may be due in part to tumor heterogeneity. Prior research has also illustrated an important role of specific fatty acids in immune regulation, T cell function, and inflammation, indicating that the effects of specific fatty acids on breast cancer risk may vary by tumor expression of immuno-inflammatory markers. We therefore aimed to evaluate the relationships between prediagnostic erythrocyte membrane fatty acids and breast cancer risk by tumor tissue expression of immuno-inflammatory markers (CD4, CD8, CD20, CD163, COX-2) and fatty acid synthase (FAS). METHODS: We conducted a matched case-control study nested within the Nurses' Health Study II (n = 235 cases and 235 controls). Blood samples were collected from 1996 to 1999. Tumor tissue blocks were collected for cases diagnosed after blood collection and through 2006. Unconditional nominal polytomous logistic regression adjusted for matching factors and potential confounders was used to assess whether associations between fatty acids and breast cancer risk varied by tumor expression subtype, ascertained via immunohistochemistry. Odds ratios (OR) and 95% confidence intervals (CI) were estimated separately by tumor expression subtype using unconditional logistic regression. RESULTS: Associations between fatty acids and breast cancer risk did not vary substantially by tumor CD4, CD20, CD163, or COX-2. However, n-3 polyunsaturated fatty acids (PUFAs) were inversely associated with CD8low but not CD8high cancers (CD8low ORT3 vs T1 = 0.45, 95% CI 0.23-0.87, Ptrend = 0.02; CD8high ORT3 vs T1 = 1.19, 95% CI 0.62-2.26, Ptrend = 0.62; Phet = 0.04). n-6 PUFAs were suggestively inversely associated with CD8high but not CD8low cancers (CD8high ORT3 vs T1 = 0.61, 95% CI 0.32-1.14, Ptrend = 0.11; CD8low ORT3 vs T1 = 1.63, 95% CI 0.87-3.04, Ptrend = 0.12; Phet = 0.02). Trans fatty acids were positively associated with FAShigh but not FASlow tumors (FAShigh ORT3 vs T1 = 2.94, 95% CI 1.46-5.91, Ptrend = 0.002; FASlow ORT3 vs T1 = 0.99, 95% CI 0.52-1.92, Ptrend = 0.97; Phet = 0.01). CONCLUSION: Results indicate that the effects of n-3 PUFAs, n-6 PUFAs, and trans fatty acids on breast cancer risk may vary by tumor tissue expression subtypes. Findings suggest potential immuno-modulatory and FAS-mediated mechanisms.