Ariel Chernofsky

Causal mediation analysis decomposes the total effect of an exposure on an outcome into: 1. the indirect effect through a mediator and 2. the remaining “direct" effect through all other pathways. When the outcome is a time-to-event/survival time, censoring makes identifying the indirect and direct effects on the expected value scale untenable. We propose a semi-parametric estimator of the indirect and direct effects on the restricted mean survival time (RMST) scale using the pseudo-value approach for estimating conditional RMSTs. The pseudo-value approach is generalizable to various forms of outcome censoring. We demonstrate the use of the pseudo-value based estimator to right and interval censored data. Our estimator applies to any set of identification assumptions that lead to the Mediation Formula, including natural, organic, randomized and separable indirect and direct effects. A simulation study demonstrates the performance of the estimators for right and interval censored outcomes under various scenarios. The methodology is applied to an HIV cure example with the intention of estimating the indirect effect of a putative treatment on time-to-viral rebound mediated through the viral reservoir.

Background: Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings. Objective: The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting. Methods: Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices. Results: We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity. Conclusions: Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

Causal indirect and direct effects provide an interpretable method for decomposing the total effect of an exposure on an outcome into the indirect effect through a mediator and the direct effect through all other pathways. A natural choice for a mediator in a randomized clinical trial is the treatment's targeted biomarker. However, when the mediator is a biomarker, values can be subject to an assay lower limit. The mediator is affected by the treatment and is a putative cause of the outcome, so the assay lower limit presents a compounded problem in mediation analysis. We propose two approaches to estimate indirect and direct effects with a mediator subject to an assay limit: (1) extrapolation and (2) numerical optimization and integration of the observed likelihood. Since these estimation methods solely rely on the so-called Mediation Formula, they apply to most approaches to causal mediation analysis: natural, separable, and organic indirect, and direct effects. A simulation study compares the two estimation approaches to imputing with half the assay limit. Using HIV interruption study data from the AIDS Clinical Trials Group described in Li et al 2016, AIDS; Lok and Bosch 2021, Epidemiology, we illustrate our methods by estimating the organic/pure indirect effect of a hypothetical HIV curative treatment on viral suppression mediated by two HIV persistence measures: cell-associated HIV-RNA and single-copy plasma HIV-RNA.

BACKGROUND Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings. OBJECTIVE The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting. METHODS Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices. RESULTS We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity. CONCLUSIONS Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

Background: Taking fewer than the widely promoted “10 000 steps per day” has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose–response relationship between steps per day and CVD can help inform clinical and public health guidelines. Methods: Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance–weighted random effects models. Results: The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults. Conclusions: For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician–patient communication and population health to reduce the risk of CVD.

Background: Cardiorespiratory fitness is a powerful predictor of health outcomes that is currently underused in primary prevention, especially in young adults. We sought to develop a blood‐based biomarker of cardiorespiratory fitness that is easily translatable across populations. Methods and Results: Maximal effort cardiopulmonary exercise testing for quantification of cardiorespiratory fitness (by peak oxygen uptake) and profiling of >200 metabolites at rest were performed in the FHS (Framingham Heart Study; 2016–2019). A metabolomic fitness score was derived/validated in the FHS and was associated with long‐term outcomes in the younger CARDIA (Coronary Artery Risk Development in Young Adults) study. In the FHS (derivation, N=451; validation, N=914; age 54±8 years, 53% women, body mass index 27.7±5.3 kg/m ² ), we used LASSO (least absolute shrinkage and selection operator) regression to develop a multimetabolite score to predict peak oxygen uptake (correlation with peak oxygen uptake r =0.77 in derivation, 0.61 in validation; both P P P =0.0003) in models adjusted for age, sex, and race, which remained robust with adjustment for clinical risk factors. Conclusions: A blood‐based biomarker of cardiorespiratory fitness largely independent of traditional risk factors is associated with long‐term risk of cardiovascular disease and mortality in young adults.

Background: Cardiorespiratory fitness is not limited by pulmonary mechanical reasons in the majority of adults. However, the degree to which lung function contributes to exercise response patterns among ostensibly healthy individuals remains unclear.Methods: We examined 2314 Framingham Heart Study participants who underwent cardiopulmonary exercise testing (CPET) and pulmonary function testing. We investigated the association of forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC), FEV₁/FVC and diffusing capacity of the lung for carbon monoxide (D_LCO) with the primary outcome of peak oxygen uptake (V′O₂) along with other CPET parameters using multivariable linear regression. Finally, we investigated the association of total and peripheral pulmonary blood vessel volume with peakV′O₂.Results: We found lower FEV₁, FVC andD_LCOwere associated with lower peakV′O₂. For example, a 1 L lower FEV₁and FVC was associated with a 7.1% (95% CI 5.1–9.1%) and 6.0% (95% CI 4.3–7.7%) lower peakV′O₂, respectively. By contrast, FEV₁/FVC was not associated with peakV′O₂. Lower lung function was associated with lower oxygen uptake efficiency slope, oxygen pulse slope,V′O₂at anaerobic threshold (AT), minute ventilation (V′_E) at AT and breathing reserve. In addition, lower total and peripheral pulmonary blood vessel volume were associated with lower peakV′O₂.Conclusions: In a large, community-based cohort of adults, we found lower FEV₁, FVC andD_LCOwere associated with lower exercise capacity, as well as oxygen uptake efficiency slope and ventilatory efficiency. In addition, lower total and peripheral pulmonary blood vessel volume were associated with lower peakV′O₂. These findings underscore the importance of lung function and blood vessel volume as contributors to overall exercise capacity.

While greater physical activity (PA) is associated with improved health outcomes, the direct links between distinct components of PA, their changes over time, and cardiorespiratory fitness are incompletely understood. Maximum effort cardiopulmonary exercise testing (CPET) and objective PA measures [sedentary time (SED), steps/day, and moderate-vigorous PA (MVPA)] via accelerometers worn for 1 week concurrent with CPET and 7.8 years prior were obtained in 2070 Framingham Heart Study participants [age 54 ± 9 years, 51% women, SED 810 ± 83 min/day, steps/day 7737 ± 3520, MVPA 22.3 ± 20.3 min/day, peak oxygen uptake (VO₂) 23.6 ± 6.9 mL/kg/min]. Adjusted for clinical risk factors, increases in steps/day and MVPA and reduced SED between the two assessments were associated with distinct aspects of cardiorespiratory fitness (measured by VO₂) during initiation, early-moderate level, peak exercise, and recovery, with the highest effect estimates for MVPA (false discovery rate 2. Individuals with high (above-mean) steps or MVPA demonstrated above average peak VO₂ values regardless of whether they had high or low SED. Our findings provide a detailed assessment of relations of different types of PA with multidimensional cardiorespiratory fitness measures and suggest favourable longitudinal changes in PA (and MVPA in particular) are associated with greater objective fitness. An overview of the study design is displayed. Cardiopulmonary fitness measures were associated with omnidirectional accelerometry data concurrent with exercise testing and from ≈8 years prior to evaluate the relations of physical activity and fitness.