Disparities in cancer incidence by sexual orientation.

INTRODUCTION: Cancer risk factors are more common among sexual minority populations (e.g., lesbian, bisexual) than their heterosexual peers, yet little is known about cancer incidence across sexual orientation groups. METHODS: The 1989-2017 data from the Nurses' Health Study II, a longitudinal cohort of female nurses across the United States, were analyzed (N = 101,543). Sexual orientation-related cancer disparities were quantified by comparing any cancer incidence among four sexual minority groups based on self-disclosure-(1) heterosexual with past same-sex attractions/partners/identity; (2) mostly heterosexual; (3) bisexual; and (4) lesbian women-to completely heterosexual women using age-adjusted incidence rate ratios (aIRR) calculated by the Mantel-Haenszel method. Additionally, subanalyses at 21 cancer disease sites (e.g., breast, colon/rectum) were conducted. RESULTS: For all-cancer analyses, there were no statistically significant differences in cancer incidence at the 5% type I error cutoff among sexual minority groups when compared to completely heterosexual women; the aIRR was 1.17 (95% CI,0.99-1.38) among lesbian women and 0.80 (0.58-1.10) among bisexual women. For the site-specific analyses, incidences at multiple sites were significantly higher among lesbian women compared to completely heterosexual women: thyroid cancer (aIRR, 1.87 [1.03-3.41]), basal cell carcinoma (aIRR, 1.85 [1.09-3.14]), and non-Hodgkin lymphoma (aIRR, 2.13 [1.10-4.12]). CONCLUSION: Lesbian women may be disproportionately burdened by cancer relative to their heterosexual peers. Sexual minority populations must be explicitly included in cancer prevention efforts. Comprehensive and standardized sexual orientation data must be systematically collected so nuanced sexual orientation-related cancer disparities can be accurately assessed for both common and rare cancers.

History of Infertility and Midlife Cardiovascular Health in Female Individuals.

Importance: Fertility status is a marker for future health, and infertility has been associated with risk for later cancer and diabetes, but associations with midlife cardiovascular health (CVH) in female individuals remain understudied. Objective: To evaluate the association of infertility history with CVH at midlife (approximately age 50 years) among parous individuals. Design, Setting, and Participants: Project Viva is a prospective cohort study of pregnant participants enrolled between 1999 and 2002 who delivered a singleton live birth in the greater Boston, Massachusetts, area. Infertility history was collected at a midlife visit between 2017 and 2021, approximately 18 years after enrollment. Data analysis was performed from January to June 2023. Exposures: The primary exposure was any lifetime history of infertility identified by self-report, medical record, diagnosis, or claims for infertility treatment. Main Outcomes and Measures: The American Heart Association's Life's Essential 8 (LE8) is a construct for ranking CVH that includes scores from 0 to 100 (higher scores denote better health status) in 4 behavioral (diet, physical activity, sleep, and smoking status) and 4 biomedical (body mass index, blood pressure, blood lipids, and glycemia) domains to form an overall assessment of CVH. Associations of a history of infertility (yes or no) with mean LE8 total, behavioral, biomedical, and blood biomarker (lipids and glycemia) scores were examined, adjusting for age at outcome (midlife visit), race and ethnicity, education, household income, age at menarche, and perceived body size at age 10 years. Results: Of 468 included participants (mean [SD] age at the midlife visit, 50.6 [5.3] years) with exposure and outcome data, 160 (34.2%) experienced any infertility. Mean (SD) LE8 scores were 76.3 (12.2) overall, 76.5 (13.4) for the behavioral domain, 76.0 (17.5) for the biomedical domain, and 78.9 (19.2) for the blood biomarkers subdomain. In adjusted models, the estimated overall LE8 score at midlife was 2.94 points lower (95% CI, -5.13 to -0.74 points), the biomedical score was 4.07 points lower (95% CI, -7.33 to -0.78 points), and the blood subdomain score was 5.98 points lower (95% CI, -9.71 to -2.26 points) among those with vs without history of infertility. The point estimate also was lower for the behavioral domain score (ß = -1.81; 95% CI, -4.28 to 0.66), although the result was not statistically significant. Conclusions and Relevance: This cohort study of parous individuals found evidence for an association between a history of infertility and lower overall and biomedical CVH scores. Future study of enhanced cardiovascular preventive strategies among those who experience infertility is warranted.

Causal Effects of Stochastic PrEP Interventions on HIV Incidence Among Men Who Have Sex With Men.

Antiretroviral preexposure prophylaxis (PrEP) is highly effective in preventing human immunodeficiency virus (HIV) infection, but uptake has been limited and inequitable. Although interventions to increase PrEP uptake are being evaluated in clinical trials among men who have sex with men (MSM), those trials cannot evaluate effects on HIV incidence. Estimates from observational studies of the causal effects of PrEP-uptake interventions on HIV incidence can inform decisions about intervention scale-up. We used longitudinal electronic health record data from HIV-negative MSM accessing care at Fenway Health, a community health center in Boston, Massachusetts, from January 2012 through February 2018, with 2 years of follow-up. We considered stochastic interventions that increased the chance of initiating PrEP in several high-priority subgroups. We estimated the effects of these interventions on population-level HIV incidence using a novel inverse-probability weighted estimator of the generalized g-formula, adjusting for baseline and time-varying confounders. Our results suggest that even modest increases in PrEP initiation in high-priority subgroups of MSM could meaningfully reduce HIV incidence in the overall population of MSM. Interventions tailored to Black and Latino MSM should be prioritized to maximize equity and impact.

Causal inference with recurrent and competing events.

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in athletes. Competing events, such as death, complicate causal inference in studies of recurrent events because once a competing event occurs, an individual cannot have more recurrent events. Several statistical estimands have been studied in recurrent event settings, with and without competing events. However, the causal interpretations of these estimands, and the conditions that are required to identify these estimands from observed data, have yet to be formalized. Here we use a formal framework for causal inference to formulate several causal estimands in recurrent event settings, with and without competing events. When competing events exist, we clarify when commonly used classical statistical estimands can be interpreted as causal quantities from the causal mediation literature, such as (controlled) direct effects and total effects. Furthermore, we show that recent results on interventionist mediation estimands allow us to define new causal estimands with recurrent and competing events that may be of particular clinical relevance in many subject matter settings. We use causal directed acyclic graphs and single world intervention graphs to illustrate how to reason about identification conditions for the various causal estimands based on subject matter knowledge. Furthermore, using results on counting processes, we show that our causal estimands and their identification conditions, which are articulated in discrete time, converge to classical continuous time counterparts in the limit of fine discretizations of time. We propose estimators and establish their consistency for the various identifying functionals. Finally, we use the proposed estimators to compute the effect of blood pressure lowering treatment on the recurrence of acute kidney injury using data from the Systolic Blood Pressure Intervention Trial.

Plasma concentrations of per- and polyfluoroalkyl substances in pregnancy and breastfeeding duration in Project Viva.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may disrupt mammary gland development and function; thereby inhibiting milk supply and breastfeeding duration. However, conclusions on the potential effects of PFAS and breastfeeding duration are limited by prior epidemiologic studies that inconsistently adjusted for past cumulative breastfeeding duration and by a lack of examination of the joint effects of PFAS mixtures. METHODS: In Project Viva, a longitudinal cohort that enrolled pregnant participants from 1999 to 2002 in the greater Boston, MA area, we studied 1079 women who ever attempted to lactate. We investigated associations of plasma concentrations of select PFAS in early pregnancy (mean: 10.1 weeks gestation) with breastfeeding termination by 9 months, after which women typically cite self-weaning as the reason for terminating breastfeeding. We used Cox regression for single-PFAS models and quantile g-computation for mixture models, adjusting for sociodemographics, prior breastfeeding duration, and weeks of gestation at the time of blood draw. RESULTS: We detected 6 PFAS [perfluorooctane sulfonate; perfluorooctanoate (PFOA); perfluorohexane sulfonate; perfluorononanoate; 2-(N-ethyl-perfluorooctane sulfonamido) acetate (EtFOSAA); 2-(N-methyl-perfluorooctane sulfonamide) acetate (MeFOSAA)] in >98 % of samples. Sixty percent of lactating women terminated breastfeeding by 9 months postpartum. Women with higher plasma concentrations of PFOA, EtFOSAA, and MeFOSAA had a greater hazard of terminating breastfeeding in the first 9 months postpartum [HR (95 % CI) per doubling concentration: 1.20 (1.04, 1.38) for PFOA; 1.10 (1.01, 1.20) for EtFOSAA; 1.18 (1.08, 1.30) for MeFOSAA]. In the quantile g-computation model, simultaneously increasing all PFAS in the mixture by one quartile was associated with 1.17 (95 % CI: 1.05, 1.31) greater hazard of terminating breastfeeding in the first 9 months. CONCLUSION: Our findings suggest that exposure to PFAS may be associated with reduced breastfeeding duration and draw further attention to environmental chemicals that may dysregulate human lactation.

Emulating Target Trials Comparing Early and Delayed Intubation Strategies.

BACKGROUND: Whether intubation should be initiated early in the clinical course of critically ill patients remains a matter of debate. Results from prior observational studies are difficult to interpret because of avoidable flaws including immortal time bias, inappropriate eligibility criteria, and unrealistic treatment strategies. RESEARCH QUESTION: Do treatment strategies that intubate patients early in the critical care admission improve 30-day survival compared with strategies that delay intubation? STUDY DESIGN AND METHODS: We estimated the effect of strategies that require early intubation of critically ill patients compared with those that delay intubation. With data extracted from the Medical Information Mart for Intensive Care-IV database, we emulated three target trials, varying the flexibility of the treatment strategies and the baseline eligibility criteria. RESULTS: Under unrealistically strict treatment strategies with broad eligibility criteria, the 30-day mortality risk was 7.1 percentage points higher for intubating early compared with delaying intubation (95% CI, 6.2-7.9). Risk differences were 0.4 (95% CI, -0.1 to 0.9) and -0.9 (95% CI, -2.5 to 0.7) percentage points in subsequent target trial emulations that included more realistic treatment strategies and eligibility criteria. INTERPRETATION: When realistic treatment strategies and eligibility criteria are used, strategies that delay intubation result in similar 30-day mortality risks compared with those that intubate early. Delaying intubation ultimately avoids intubation in most patients.

Incidence and Outcomes of Non-Ventilator-Associated Hospital-Acquired Pneumonia in 284 US Hospitals Using Electronic Surveillance Criteria.

Importance: Non-ventilator-associated hospital-acquired pneumonia (NV-HAP) is a common and deadly hospital-acquired infection. However, inconsistent surveillance methods and unclear estimates of attributable mortality challenge prevention. Objective: To estimate the incidence, variability, outcomes, and population attributable mortality of NV-HAP. Design, Setting, and Participants: This cohort study retrospectively applied clinical surveillance criteria for NV-HAP to electronic health record data from 284 US hospitals. Adult patients admitted to the Veterans Health Administration hospital from 2015 to 2020 and HCA Healthcare hospitals from 2018 to 2020 were included. The medical records of 250 patients who met the surveillance criteria were reviewed for accuracy. Exposures: NV-HAP, defined as sustained deterioration in oxygenation for 2 or more days in a patient who was not ventilated concurrent with abnormal temperature or white blood cell count, performance of chest imaging, and 3 or more days of new antibiotics. Main Outcomes and Measures: NV-HAP incidence, length-of-stay, and crude inpatient mortality. Attributable inpatient mortality by 60 days follow-up was estimated using inverse probability weighting, accounting for both baseline and time-varying confounding. Results: Among 6 022 185 hospitalizations (median [IQR] age, 66 [54-75] years; 1 829 475 [26.1%] female), there were 32 797 NV-HAP events (0.55 per 100 admissions [95% CI, 0.54-0.55] per 100 admissions and 0.96 per 1000 patient-days [95% CI, 0.95-0.97] per 1000 patient-days). Patients with NV-HAP had multiple comorbidities (median [IQR], 6 [4-7]), including congestive heart failure (9680 [29.5%]), neurologic conditions (8255 [25.2%]), chronic lung disease (6439 [19.6%]), and cancer (5,467 [16.7%]); 24 568 cases (74.9%) occurred outside intensive care units. Crude inpatient mortality was 22.4% (7361 of 32 797) for NV-HAP vs 1.9% (115 530 of 6 022 185) for all hospitalizations; 12 449 (8.0%) were discharged to hospice. Median [IQR] length-of-stay was 16 (11-26) days vs 4 (3-6) days. On medical record review, pneumonia was confirmed by reviewers or bedside clinicians in 202 of 250 patients (81%). It was estimated that NV-HAP accounted for 7.3% (95% CI, 7.1%-7.5%) of all hospital deaths (total hospital population inpatient death risk of 1.87% with NV-HAP events included vs 1.73% with NV-HAP events excluded; risk ratio, 0.927; 95% CI, 0.925-0.929). Conclusions and Relevance: In this cohort study, NV-HAP, which was defined using electronic surveillance criteria, was present in approximately 1 in 200 hospitalizations, of whom 1 in 5 died in the hospital. NV-HAP may account for up to 7% of all hospital deaths. These findings underscore the need to systematically monitor NV-HAP, define best practices for prevention, and track their impact.

Considering Questions Before Methods in Dementia Research With Competing Events and Causal Goals.

Studying causal exposure effects on dementia is challenging when death is a competing event. Researchers often interpret death as a potential source of bias, although bias cannot be defined or assessed if the causal question is not explicitly specified. Here we discuss 2 possible notions of a causal effect on dementia risk: the "controlled direct effect" and the "total effect." We provide definitions and discuss the "censoring" assumptions needed for identification in either case and their link to familiar statistical methods. We illustrate concepts in a hypothetical randomized trial on smoking cessation in late midlife, and emulate such a trial using observational data from the Rotterdam Study, the Netherlands, 1990-2015. We estimated a total effect of smoking cessation (compared with continued smoking) on 20-year dementia risk of 2.1 (95% confidence interval: -0.1, 4.2) percentage points and a controlled direct effect of smoking cessation on 20-year dementia risk had death been prevented of -2.7 (95% confidence interval: -6.1, 0.8) percentage points. Our study highlights how analyses corresponding to different causal questions can have different results, here with point estimates on opposite sides of the null. Having a clear causal question in view of the competing event and transparent and explicit assumptions are essential to interpreting results and potential bias.

Associations of urinary metabolite concentrations of phthalates and phthalate replacements with body composition from mid-childhood to early adolescence.

BACKGROUND: Phthalates may adversely influence body composition by lowering anabolic hormones and activating peroxisome-proliferator activated receptor gamma. However, data are limited in adolescence when body mass distributions rapidly change and bone accrual peaks. Also, potential health effects of certain phthalate/replacements [e.g., di-2-ethylhexyl terephthalate (DEHTP)] have not been well studied. METHODS: Among 579 children in the Project Viva cohort, we used linear regression to evaluate associations of urinary concentrations of 19 phthalate/replacement metabolites from mid-childhood (median: 7.6 years; 2007-2010) with annualized change in areal bone mineral density (aBMD) and lean, total fat, and truncal fat mass as measured by dual-energy X-ray absorptiometry between mid-childhood and early adolescence (median: 12.8 years). We used quantile g-computation to assess associations of the overall chemical mixture with body composition. We adjusted for sociodemographics and tested for sex-specific associations. RESULTS: Urinary concentrations were highest for mono-2-ethyl-5-carboxypentyl phthalate [median (IQR): 46.7 (69.1) ng/mL]. We detected metabolites of most replacement phthalates in a relatively small number of participants [e.g., 28% for mono-2-ethyl-5-hydrohexyl terephthalate (MEHHTP; metabolite of DEHTP)]. Detectable (vs. non-detectable) MEHHTP was associated with less bone and greater fat accrual in males and greater bone and lean mass accrual in females [e.g., change in aBMD Z-score/year (95% CI): -0.049 (-0.085, -0.013) in males versus 0.042 (0.007, 0.076) in females; pinteraction<0.01]. Children with higher concentrations of mono-oxo-isononyl phthalate and mono-3-carboxypropyl phthalate (MCPP) had greater bone accrual. Males with higher concentrations of MCPP and mono-carboxynonyl phthalate had greater accrual of lean mass. Other phthalate/replacement biomarkers, and their mixtures, were not associated with longitudinal changes in body composition. CONCLUSIONS: Concentrations of select phthalate/replacement metabolites in mid-childhood were associated with changes in body composition through early adolescence. As use of phthalate replacements such as DEHTP may be increasing, further investigation can help better understand the potential effects of early-life exposures.

Longitudinal incremental propensity score interventions for limited resource settings.

Many real-life treatments are of limited supply and cannot be provided to all individuals in the population. For example, patients on the liver transplant waiting list usually cannot be assigned a liver transplant immediately at the time they reach highest priority because a suitable organ is not immediately available. In settings with limited supply, investigators are often interested in the effects of treatment strategies in which a limited proportion of patients receive an organ at a given time, that is, treatment regimes satisfying resource constraints. Here, we describe an estimand that allows us to define causal effects of treatment strategies that satisfy resource constraints: incremental propensity score interventions (IPSIs) for limited resources. IPSIs flexibly constrain time-varying resource utilization through proportional scaling of patients' natural propensities for treatment, thereby preserving existing propensity rank ordering compared to the status quo. We derive a simple class of inverse-probability-weighted estimators, and we apply one such estimator to evaluate the effect of restricting or expanding utilization of "increased risk" liver organs to treat patients with end-stage liver disease.

Intervention treatment distributions that depend on the observed treatment process and model double robustness in causal survival analysis.

The generalized g-formula can be used to estimate the probability of survival under a sustained treatment strategy. When treatment strategies are deterministic, estimators derived from the so-called efficient influence function (EIF) for the g-formula will be doubly robust to model misspecification. In recent years, several practical applications have motivated estimation of the g-formula under non-deterministic treatment strategies where treatment assignment at each time point depends on the observed treatment process. In this case, EIF-based estimators may or may not be doubly robust. In this paper, we provide sufficient conditions to ensure the existence of doubly robust estimators for intervention treatment distributions that depend on the observed treatment process for point treatment interventions and give a class of intervention treatment distributions dependent on the observed treatment process that guarantee model doubly and multiply robust estimators in longitudinal settings. Motivated by an application to pre-exposure prophylaxis (PrEP) initiation studies, we propose a new treatment intervention dependent on the observed treatment process. We show there exist (1) estimators that are doubly and multiply robust to model misspecification and (2) estimators that when used with machine learning algorithms can attain fast convergence rates for our proposed intervention. Finally, we explore the finite sample performance of our estimators via simulation studies.

Comparison of Rates of Type 2 Diabetes in Adults and Children Treated With Anticonvulsant Mood Stabilizers.

Importance: Anticonvulsant mood stabilizer treatment is associated with an increased risk of weight gain, but little is known about the risk of developing type 2 diabetes (T2D). Objective: To evaluate the comparative safety of anticonvulsant mood stabilizers on risk of T2D in adults and children by emulating a target trial. Design, Setting, and Participants: This observational cohort study used data from IBM MarketScan (2010-2019), with a 5-year follow-up period. The nationwide sample of US commercially insured patients included children (aged 10-19 years) and adults (aged 20-65 years) who initiated anticonvulsant mood stabilizer treatment. Data were analyzed from August 2020 to May 2021. Exposures: Initiation and continuation of carbamazepine, lamotrigine, oxcarbazepine, or valproate. Main Outcomes and Measures: Onset of T2D during follow-up. Weighted pooled logistic regression was used to estimate the association of initiation and continuation of carbamazepine, lamotrigine, oxcarbazepine, or valproate with the risk of developing T2D. Inverse probability weights were used to control for confounding and loss to follow-up by measured baseline and time-varying covariates. Results: The analysis included 274 206 adults (159 428 women [58%]; mean [SD] age, 39.9 [13.2] years) and 74 005 children (38 672 girls [52%]; mean [SD] age, 15.6 [2.6] years) who initiated an anticonvulsant mood stabilizer. In adults, initiation of valproate was associated with an increased risk of developing T2D compared with initiation of lamotrigine (5-year risk difference [RD], 1.17%; 95% CI, 0.66% to 1.76%). The number needed to harm was 87 patients initiating valproate for 1 patient to develop T2D within 5 years compared with initiation of lamotrigine. Point estimates were similar when evaluating the association of treatment continuation (5-year RD, 1.99%; 95% CI, -0.64% to 5.31%). The estimated association was smaller and more variable comparing carbamazepine and oxcarbazepine to lamotrigine. In children, RDs were much smaller and more variable (5-year RD for initiation of oxcarbazepine vs lamotrigine, 0.29%; 95% CI, -0.12% to 0.69%; 5-year RD for initiation of valproate vs lamotrigine, 0.18%; 95% CI, -0.09% to 0.49%). Conclusions and Relevance: In this cohort study, valproate was associated with the highest risk of developing T2D in adults. The comparative safety was generally similar in children, but estimates were small and variable. In the absence of randomized trials, emulating target trials within health care databases can generate the age-specific drug safety data needed to inform treatment decision-making.

Estimated causal effects of complementary feeding behaviors on early childhood diet quality in a US cohort.

BACKGROUND: Complementary feeding (CF) provides an opportunity to shape children's future dietary habits, setting the foundation for good nutrition and health. OBJECTIVES: We estimated effects of 3 CF behaviors on early childhood diet quality using inverse probability (IP) weighting of marginal structural models (MSMs). METHODS: Among 1041 children from the Boston-area Project Viva cohort, we estimated effects on the mean Youth Healthy Eating Index (YHEI) score in early childhood of 1) delayed (≥12 mo) compared with early (<12 mo) introduction of sweets and fruit juice; 2) continued compared with ceased offering of initially refused foods; and 3) early (<12 mo) compared with late (≥12 mo) introduction of flavor/texture variety. Mothers reported CF behaviors at 1 y and completed FFQs for children in early childhood (median age: 3.1 y). We estimated average treatment effects (ATEs) using IP weighting of MSMs to adjust for both confounding and selection bias due to censored outcomes and examined effect modification by child sex and breastfeeding compared with formula feeding at 6 mo. RESULTS: Twelve percent of mothers delayed introducing sweets/fruit juice, 93% continued offering initially refused foods, and 32% introduced flavor/texture variety early. The mean ± SD YHEI score was 52.8 ± 9.2 points. In adjusted models, we estimated a higher mean YHEI score with delayed (compared with early) sweets and fruit juice among breastfeeding children (ATE: 4.5 points; 95% CI: 1.0, 7.4 points), as well as with continued (compared with ceased) offering of refused foods among females (ATE: 5.4 points; 95% CI: 0.8, 9.1 points). The ATE for early (compared with late) flavor/texture variety was 1.7 points (95% CI: 0.3, 3.2 points) overall and stronger (2.8 points; 95% CI: 0.7, 5.1 points) among the formula-fed group. CONCLUSIONS: Delayed introduction of sweets/juice, continued offering of refused foods, and early flavor/texture variety may all result in higher childhood diet quality. Effects may depend on child sex and infant breastfeeding status.

Revisiting the g-null Paradox.

The (noniterative conditional expectation) parametric g-formula is an approach to estimating causal effects of sustained treatment strategies from observational data. An often-cited limitation of the parametric g-formula is the g-null paradox: a phenomenon in which model misspecification in the parametric g-formula is guaranteed in some settings consistent with the conditions that motivate its use (i.e., when identifiability conditions hold and measured time-varying confounders are affected by past treatment). Many users of the parametric g-formula acknowledge the g-null paradox as a limitation when reporting results but still require clarity on its meaning and implications. Here, we revisit the g-null paradox to clarify its role in causal inference studies. In doing so, we present analytic examples and a simulation-based illustration of the bias of parametric g-formula estimates under the conditions associated with this paradox. Our results highlight the importance of avoiding overly parsimonious models for the components of the g-formula when using this method.

Longitudinal Analysis of Food Insufficiency and Cardiovascular Disease Risk Factors in the CARDIA study.

INTRODUCTION: Most previous studies on food insecurity and cardiovascular disease risk factors are cross-sectional. Without longitudinal data, it is unclear whether food insecurity precedes poor health and how exposure timing impacts these relationships. METHODS: Data from 2000 to 2001, 2005 to 2006, and 2010 to 2011 of the Coronary Artery Risk Development in Young Adults study were used. Food insufficiency-a screener measure related to food insecurity-was assessed in 2000-2001 and 2005-2006 using a single item. Cardiovascular disease risk factors were objectively assessed in 2010-2011. Impacts of food insufficiency patterns (food sufficient, food insufficient in 2000-2001 only, food insufficient in 2005-2006 only, food insufficient in both 2000-2001 and 2005-2006) on cardiovascular disease risk factors were estimated using inverse probability weighting of marginal structural models. Covariates that change over time were adjusted for using stabilized weights; baseline covariates were adjusted for in the marginal structural models. Analyses were conducted in 2020-2021. RESULTS: The baseline sample included 2,596 participants (56% women, 47% White). In unadjusted analyses, all food insufficiency patterns were associated with higher BMI, waist circumference, and blood pressure than food sufficiency. After accounting for covariates, estimates were attenuated but still consistent with adverse effects of food insufficiency, particularly among women. CONCLUSIONS: After covariate adjustment, food insufficiency was associated with several cardiovascular disease risk factors. Findings from this study should be replicated in other settings and populations. If verified, this evidence could provide justification for intervening in food insecurity to reduce future cardiovascular disease risk.

Marginal Structural Models for Life-Course Theories and Social Epidemiology: Definitions, Sources of Bias, and Simulated Illustrations.

Social epidemiology aims to identify social structural risk factors, thus informing targets and timing of interventions. Ascertaining which interventions will be most effective and when they should be implemented is challenging because social conditions vary across the life course and are subject to time-varying confounding. Marginal structural models (MSMs) may be useful but can present unique challenges when studying social epidemiologic exposures over the life course. We describe selected MSMs corresponding to common theoretical life-course models and identify key issues for consideration related to time-varying confounding and late study enrollment. Using simulated data mimicking a cohort study evaluating the effects of depression in early, mid-, and late life on late-life stroke risk, we examined whether and when specific study characteristics and analytical strategies may induce bias. In the context of time-varying confounding, inverse-probability-weighted estimation of correctly specified MSMs accurately estimated the target causal effects, while conventional regression models showed significant bias. When no measure of early-life depression was available, neither MSMs nor conventional models were unbiased, due to confounding by early-life depression. To inform interventions, researchers need to identify timing of effects and consider whether missing data regarding exposures earlier in life may lead to biased estimates.

A generalized theory of separable effects in competing event settings.

In competing event settings, a counterfactual contrast of cause-specific cumulative incidences quantifies the total causal effect of a treatment on the event of interest. However, effects of treatment on the competing event may indirectly contribute to this total effect, complicating its interpretation. We previously proposed the separable effects to define direct and indirect effects of the treatment on the event of interest. This definition was given in a simple setting, where the treatment was decomposed into two components acting along two separate causal pathways. Here we generalize the notion of separable effects, allowing for interpretation, identification and estimation in a wide variety of settings. We propose and discuss a definition of separable effects that is applicable to general time-varying structures, where the separable effects can still be meaningfully interpreted as effects of modified treatments, even when they cannot be regarded as direct and indirect effects. For these settings we derive weaker conditions for identification of separable effects in studies where decomposed, or otherwise modified, treatments are not yet available; in particular, these conditions allow for time-varying common causes of the event of interest, the competing events and loss to follow-up. We also propose semi-parametric weighted estimators that are straightforward to implement. We stress that unlike previous definitions of direct and indirect effects, the separable effects can be subject to empirical scrutiny in future studies.