Loneliness, social isolation, and cardiovascular disease among nonveteran and veteran women.

We examined the prospective associations of social isolation and loneliness with incident cardiovascular disease (CVD) among aging nonveteran and veteran women, and effect modification by veteran status. Participants with no history of myocardial infarction (MI), stroke, coronary heart disease (CHD), or coronary heart failure from the Women's Health Initiative Extension Study II self-reported social isolation, loneliness, health behaviors, health status, and veteran status. CVD and CVD subevents were physician adjudicated. Hazard ratios (HR) and 95% confidence intervals (CI) for the Interquartile Range (IQR) in social isolation (IQR = 1) and loneliness (IQR=.33) were calculated using Cox proportional hazard models adjusting for sociodemographic, health behavior, and health status characteristics. Veteran status was tested as an effect modifier. Among 52,442 women (Mean age = 79 ± 6.1; veterans n = 1023; 89.2% non-Hispanic White), 3579 major CVD events occurred over an average 5.8 follow-up years. Compared to nonveterans, veteran women reported higher levels of social isolation (p < .01) and loneliness (p < .01). The CVD HR was 1.07 (95% CI, 1.04-1.10) for the IQR in social isolation and 1.03 (95% CI, 1.10-1.06) for the IQR in loneliness. The HR for the IQR in both social isolation and loneliness was 1.10 (95% CI, 1.05-1.15). Social isolation was associated with CHD (HR = 1.12; 95% CI, 1.03-1.21). The CHD HR for the IQR in social isolation was 1.12 (95% CI, 1.03-1.21). Associations did not differ by veteran status (all p-interactions > 0.08). Findings suggest that the adverse associations of social isolation and loneliness with CVD are similar among veteran and nonveteran women.

Correlates of physical activity and sedentary behavior among cancer survivors and cancer-free women: The Women's Health Accelerometry Collaboration.

BACKGROUND: Describing correlates of physical activity (PA) and sedentary behavior (SB) among postmenopausal cancer survivors can help identify risk profiles and can be used to support development of targeted interventions to improve PA and reduce SB in this population. OBJECTIVE: To describe PA/SB and identify correlates of PA/SB among cancer and cancer-free post-menopausal women. METHODS: Women from the Women's Health Study (N = 16,629) and Women's Health Initiative/Objective Physical Activity and Cardiovascular Health Study (N = 6,079) were asked to wear an accelerometer on the hip for 7 days. Multiple mixed-effects linear regression models were used to identify sociodemographic-, health-, and chronic condition-related correlates (independent variables) associated with PA and SB (dependent variables) among women with (n = 2,554) and without (n = 20,154) a history of cancer. All correlates were mutually adjusted for each other. RESULTS: In unadjusted analyses, women with a history of cancer took fewer mean daily steps (4,572 (standard deviation 2557) vs 5,029 (2679) steps/day) and had lower mean moderate-to-vigorous PA (74.9 (45.0) vs. 81.6 (46.7) minutes/day) than cancer-free women. In adjusted analyses, for cancer and cancer-free women, age, diabetes, overweight, and obesity were inversely associated with all metrics of PA (average vector magnitude, time in moderate-to-vigorous PA, step volume, time at ≥40 steps/minutes, and peak 30-minute step cadence). In unadjusted analyses, mean SB was similar for those with and without cancer (529.7 (98.1) vs. 521.7 (101.2) minutes/day). In adjusted analyses, for cancer and cancer-free women, age, diabetes, cardiovascular disease, current smoking, overweight, and obesity were positive correlates of SB, while Black or Hispanic race/ethnicity, weekly/daily alcohol intake, and excellent/very good/good self-rated health were inverse correlates of SB. CONCLUSION: Several sociodemographic, health, and chronic conditions were correlates of PA/SB for postmenopausal women with and without cancer. Future studies should examine longitudinal relationships to gain insight into potential determinants of PA/SB.

Development, validation, and transportability of several machine-learned, non-exercise-based VO2max prediction models for older adults.

PURPOSE: There exist few maximal oxygen uptake (VO2max) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO2max is infeasible in large epidemiologic cohort studies, we sought to develop, validate, compare, and assess the transportability of several ML VO2max prediction algorithms. METHODS: The Baltimore Longitudinal Study of Aging (BLSA) participants with valid VO2max tests were included (n = 1080). Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine (SVM) algorithms were trained to predict VO2max values. We developed these algorithms for: (a) for the overall BLSA, (b) by sex, (c) using all BLSA variables, and (d) for variables common in aging cohorts. Finally, we quantified the associations between measured and predicted VO2max and mortality. RESULTS: The age was 69.0 ± 10.4 years (mean ± SD) and the measured VO2max was 21.6 ± 5.9 mL/kg/min. Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine yielded root mean squared errors of 3.4 mL/kg/min, 3.6 mL/kg/min, 3.4 mL/kg/min, 3.6 mL/kg/min, and 3.5 mL/kg/min, respectively. Incremental quartiles of measured VO2max showed an inverse gradient in mortality risk. Predicted VO2max variables yielded similar effect estimates but were not robust to adjustment. CONCLUSION: Measured VO2max is a strong predictor of mortality. Using ML can improve the accuracy of prediction as compared to simpler approaches but estimates of association with mortality remain sensitive to adjustment. Future studies should seek to reproduce these results so that VO2max, an important vital sign, can be more broadly studied as a modifiable target for promoting functional resiliency and healthy aging.

An empowerment model for managing menopause.

Menopause eventually happens to all people with typically functioning ovaries, and almost one billion women worldwide are postmenopausal. Although the biology of typical menopause is ubiquitous, the experience varies substantially. Factors contributing to the experience include not only individual factors, such as the nature and severity of symptoms, but also psychological, social, and contextual considerations, many of which are modifiable. In this first paper in the Lancet Series on menopause, we argue for a new approach that goes beyond the treatment of specific symptoms, to encompass a broad model to support women transitioning this life stage, using the model of empowerment. WHO defines empowerment as an active process of gaining knowledge, confidence, and self-determination to self-manage health and make informed decisions about care. Rather than focusing on menopause as an endocrine deficiency, we propose an empowerment model that recognises factors modifying the experience, in which the patient is an expert in their own condition and the health-care worker supports the patient to become an equal and active partner in managing their own care.

Prospective Associations of Accelerometer-Measured Machine-Learned Sedentary Behavior With Death Among Older Women: The OPACH Study.

BACKGROUND: Sedentary behavior is a recognized mortality risk factor. The novel and validated convolutional neural network hip accelerometer posture algorithm highly accurately classifies sitting and postural changes compared with accelerometer count cut points. We examined the prospective associations of convolutional neural network hip accelerometer posture-classified total sitting time and mean sitting bout duration with all-cause and cardiovascular disease (CVD) death. METHODS AND RESULTS: Women (n=5856; mean±SD age, 79±7 years; 33% Black women, 17% Hispanic or Latina women, 50% White women) in the Women's Health Initiative Objective Physical Activity and Cardiovascular Health (OPACH) Study wore the ActiGraph GT3X+ for ~7 days from May 2012 to April 2014 and were followed through February 19, 2022 for all-cause and CVD death. The convolutional neural network hip accelerometer posture algorithm classified total sitting time and mean sitting bout duration from GT3X+ output. Over follow-up (median, 8.4 years; range, 0.1-9.9), there were 1733 deaths (632 from CVD). Adjusted Cox regression hazard ratios (HRs) comparing women in the highest total sitting time quartile (>696 min/d) to those in the lowest (<556.0 min/d) were 1.57 (95% CI; 1.35-1.83; P-trend<0.001) for all-cause death and 1.78 (95% CI; 1.36-2.31; P-trend<0.001) for CVD death. HRs comparing women in the longest mean sitting bout duration quartile (>15 minutes) to the shortest (<9.3 minutes) were 1.43 (95% CI; 1.23-1.66; P-trend<0.001) for all-cause death and 1.52 (95% CI; 1.18-1.96; P-trend<0.001) for CVD death. Apparent nonlinear associations for total sitting time suggested higher all-cause death (P nonlinear=0.009) and CVD death (P nonlinear=0.008) risk after ~660 to 700 min/d. CONCLUSIONS: Higher total sitting time and longer mean sitting bout duration are associated with higher all-cause and CVD mortality risk among older women. These data support interventions aimed at reducing both total sitting time and interrupting prolonged sitting.

Accelerometer-Measured Physical Activity, Sedentary Time, and Heart Failure Risk in Women Aged 63 to 99 Years.

Importance: Heart failure (HF) prevention is paramount to public health in the 21st century. Objective: To examine incident HF and its subtypes with preserved ejection fraction (HFpEF) and reduced EF (HFrEF) according to accelerometer-measured physical activity (PA) and sedentary time. Design, Setting, and Participants: This was a prospective cohort study, the Objective Physical Activity and Cardiovascular Health (OPACH) in Older Women study, conducted from March 2012 to April 2014. Included in the analysis were women aged 63 to 99 years without known HF, who completed hip-worn triaxial accelerometry for 7 consecutive days. Follow-up for incident HF occurred through February 2022. Data were analyzed from March to December 2023. Exposure: Daily PA (total, light, moderate to vigorous PA [MVPA], steps) and sedentary (total, mean bout duration) behavior. Main Outcomes and Measures: Adjudicated incident HF, HFpEF, and HFrEF. Results: A total of 5951 women (mean [SD] age, 78.6 [6.8] years) without known HF were included in this analysis. Women self-identified with the following race and ethnicity categories: 2004 non-Hispanic Black (33.7%), 1022 Hispanic (17.2%), and 2925 non-Hispanic White (49.2%). There were 407 HF cases (257 HFpEF; 110 HFrEF) identified through a mean (SD) of 7.5 (2.6) years (range, 0.01-9.9 years) of follow-up. Fully adjusted hazard ratios (HRs) for overall HF, HFpEF, and HFrEF associated with a 1-SD increment were 0.85 (95% CI, 0.75-0.95), 0.78 (95% CI, 0.67-0.91), and 1.02 (95% CI, 0.81-1.28) for minutes per day total PA; 0.74 (95% CI, 0.63-0.88), 0.71 (95% CI, 0.57-0.88), and 0.83 (95% CI, 0.62-1.12) for steps per day; and 1.17 (95% CI, 1.04-1.33), 1.29 (95% CI, 1.10-1.51), and 0.94 (95% CI, 0.75-1.18) for minutes per day total sedentary. Cubic spline curves for overall HF and HFpEF were significant inverse for total PA and steps per day and positive for total sedentary. Light PA and MVPA were inversely associated with overall HF (HR per 1 SD: 0.88; 95% CI, 0.78-0.98 and 0.84; 95% CI, 0.73-0.97) and HFpEF (0.80; 95% CI, 0.70-0.93 and 0.85; 95% CI, 0.72-1.01) but not HFrEF. Associations did not meaningfully differ when stratified by age, race and ethnicity, body mass index, physical function, or comorbidity score. Results for sedentary bout duration were inconsistent. Conclusions and Relevance: Higher accelerometer-measured PA (MVPA, light PA, steps per day) was associated with lower risk (and greater total sedentary time with higher risk) of overall HF and HFpEF in a racially and ethnically diverse cohort of older women. Increasing PA and reducing sedentary time for primary HFpEF prevention may have relevant implications for cardiovascular resilience and healthy aging in later life.

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.

The association of leukocyte telomere length with exceptional longevity among older women.

The association of leukocyte telomere length (LTL) with survival to late life with intact mobility has not been adequately studied. This prospective cohort study consisted of 1451 postmenopausal women from a Women's Health Initiative ancillary study, who were eligible, because of birth year, to survive to age 90 as of March 6, 2021. LTL was measured by Southern blot at baseline (1993-1998). Associations between LTL and survival to age 90 were evaluated using logistic regression models adjusted for socio-demographic characteristics, health factors, and lifestyle factors. Multinominal logistic regression was utilized to examine associations of LTL with survival to age 90 with or without intact mobility. Mediation analysis examined the extent to which incident coronary heart disease and stroke-mediated the association between LTL and longevity. Overall, 76.7% of women were White, and 23.3% were Black; average age at baseline was 70.4±3.5 years. Relative to death before age 90, the odds of survival to age 90 were 60% higher (OR, 1.60; 95% CI, 1.28-2.01), the odds of survival to age 90 with mobility limitation were 72% higher (OR, 1.72; 95% CI, 1.33-2.21), and the odds of survival to age 90 with intact mobility were 44% higher (OR, 1.44; 95% CI, 1.06-1.95) for every one kilobase longer LTL. Absence of CHD, stroke, or CHD/stroke mediated the association of LTL with survival to age 90 by 11.1%, 37.4%, and 31.3%, respectively; however, these findings were not significant. Longer LTL was associated with higher odds of survival to age 90 among older women.

Calibrating Physical Activity and Sedentary Behavior for Hip-Worn Accelerometry in Older Women With Two Epoch Lengths: The Women's Health Initiative Objective Physical Activity and Cardiovascular Health Calibration Study.

Purpose: The purpose of this study was to develop 60-second epoch accelerometer intensity cutpoints for vertical axis count and vector magnitude (VM) output from hip-worn tri-axial accelerometers among women 60-91 years. We also compared these cutpoints against cutpoints derived by multiplying 15-second epoch cutpoints by four. Methods: Two hundred apparently healthy women wore an ActiGraph GT3X+ accelerometer on their hip while performing a variety of laboratory-based activities that were sedentary (watching television, assembling a puzzle), low light (washing/drying dishes), high light (laundry, dust mopping), or MVPA (400-meter walk) intensity. Oxygen uptake was measured using an Oxycon™ portable calorimeter. Sedentary behavior and physical activity intensity cutpoints for vertical axis and VM counts were derived for 60-second epochs from receiver operating characteristic (ROC) and by multiplying the 15-second cutpoints by four); both were compared to oxygen uptake. Results: The median age was 74.5 years (interquartile range 70-83). The 60-second epoch cutpoints for vertical counts were 0 sedentary, 1-73 low light, 74-578 high light, and >=579 MVPA. The 60-second epoch cutpoints for VM were 0-88 sedentary, 89-663 low light, 664-1730 high light, and >=1731 MVPA. For both sets of cutpoints, the ROC approach yielded more accurate estimates than the multiplication approach. Conclusion: The derived 60-second epoch cutpoints for vertical counts and VM can be applied to epidemiologic studies to define sedentary behavior and physical activity intensities in older adult populations.

Feasibility of a Health Coach Intervention to Reduce Sitting Time and Improve Physical Functioning Among Breast Cancer Survivors: Pilot Intervention Study.

BACKGROUND: Sedentary behavior among breast cancer survivors is associated with increased risk of poor physical function and worse quality of life. While moderate to vigorous physical activity can improve outcomes for cancer survivors, many are unable to engage in that intensity of physical activity. Decreasing sitting time may be a more feasible behavioral target to potentially mitigate the impact of cancer and its treatments. OBJECTIVE: The purpose of this study was to investigate the feasibility and preliminary impact of an intervention to reduce sitting time on changes to physical function and quality of life in breast cancer survivors, from baseline to a 3-month follow-up. METHODS: Female breast cancer survivors with self-reported difficulties with physical function received one-on-one, in-person personalized health coaching sessions aimed at reducing sitting time. At baseline and follow-up, participants wore the activPAL (thigh-worn accelerometer; PAL Technologies) for 3 months and completed physical function tests (4-Meter Walk Test, Timed Up and Go, and 30-Second Chair Stand) and Patient-Reported Outcomes Measurement Information System (PROMIS) self-reported outcomes. Changes in physical function and sedentary behavior outcomes were assessed by linear mixed models. RESULTS: On average, participants (n=20) were aged 64.5 (SD 9.4) years; had a BMI of 30.4 (SD 4.5) kg/m2; and identified as Black or African American (n=3, 15%), Hispanic or Latina (n=4, 20%), and non-Hispanic White (n=14, 55%). Average time since diagnosis was 5.8 (SD 2.2) years with participants receiving chemotherapy (n=8, 40%), radiotherapy (n=18, 90%), or endocrine therapy (n=17, 85%). The intervention led to significant reductions in sitting time: activPAL average daily sitting time decreased from 645.7 (SD 72.4) to 532.7 (SD 142.1; ß=-112.9; P=.001) minutes and average daily long sitting bouts (bout length ≥20 min) decreased from 468.3 (SD 94.9) to 366.9 (SD 150.4; ß=-101.4; P=.002) minutes. All physical function tests had significant improvements: on average, 4-Meter Walk Test performance decreased from 4.23 (SD 0.95) to 3.61 (SD 2.53; ß=-.63; P=.002) seconds, Timed Up and Go performance decreased from 10.30 (SD 3.32) to 8.84 (SD 1.58; ß=-1.46; P=.003) seconds, and 30-Second Chair Stand performance increased from 9.75 (SD 2.81) to 13.20 completions (SD 2.53; ß=3.45; P<.001). PROMIS self-reported physical function score improved from 44.59 (SD 4.40) to 47.12 (SD 5.68; ß=2.53; P=.05) and average fatigue decreased from 52.51 (SD 10.38) to 47.73 (SD 8.43; ß=-4.78; P=.02). CONCLUSIONS: This 3-month pilot study suggests that decreasing time spent sitting may be helpful for breast cancer survivors experiencing difficulties with physical function and fatigue. Reducing sitting time is a novel and potentially more feasible approach to improving health and quality of life in cancer survivors.

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

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

Low movement, deep-learned sitting patterns, and sedentary behavior in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE).

BACKGROUND/OBJECTIVES: Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined. METHODS: Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score). RESULTS: After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well. CONCLUSIONS: Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.

Binge eating age of onset, frequency, and associated emotional distress among women aged 60 years and over.

Emerging research indicates that binge eating is prevalent among older adult women. This study explored the characteristics of older women (aged 60+ years) with objective binge episodes (OBE) in later-life, including age of onset, distress, and frequency of OBE. Data consist of telephone clinical interviews conducted with individuals presenting for participation in a biomedical study of older women with OBE to establish inclusion criteria. Of 71 participants interviewed, 77.5% met DSM-5 criteria for OBE (≥1/week for ≥3 months); 33.3% reported OBE onset before age 40, 17.9% reported midlife onset (ages 40-55), and 48.7% reported late-life onset (56+). Regarding distress, older women with OBE in later-life reported themes of age-related self-blame surrounding eating, loss of control, and cognitive fixation on satiation. Among older women with OBE in later-life, onset in mid- to later-life may be relatively common. Furthermore, distress regarding OBEs was significant, highlighting the need for intervention research among this population.

Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study.

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65-100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model's assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

Accelerometer-measured physical activity and postmenopausal breast cancer incidence in the Women's Health Accelerometry Collaboration.

BACKGROUND: Few studies have examined accelerometer-measured physical activity and incident breast cancer (BC). Thus, this study examined associations between accelerometer-measured vector magnitude counts per 15 seconds (VM/15s) and average daily minutes of light physical activity (LPA), moderate-to-vigorous PA (MVPA), and total PA (TPA) and BC risk among women in the Women's Health Accelerometry Collaboration (WHAC). METHODS: The WHAC comprised 21,089 postmenopausal women (15,375 from the Women's Health Study [WHS]; 5714 from the Women's Health Initiative Objective Physical Activity and Cardiovascular Health Study [OPACH]). Women wore an ActiGraph GT3X+ on the hip for ≥4 days and were followed for 7.4 average years to identify physician-adjudicated in situ (n = 94) or invasive (n = 546) BCs. Multivariable stratified Cox regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for tertiles of physical activity measures in association with incident BC overall and by cohort. Effect measure modification was examined by age, race/ethnicity, and body mass index (BMI). RESULTS: In covariate-adjusted models, the highest (vs. lowest) tertiles of VM/15s, TPA, LPA, and MVPA were associated with BC HRs of 0.80 (95% CI, 0.64-0.99), 0.84 (95% CI, 0.69-1.02), 0.89 (95% CI, 0.73-1.08), and 0.81 (95% CI, 0.64-1.01), respectively. Further adjustment for BMI or physical function attenuated these associations. Associations were more pronounced among OPACH than WHS women for VM/15s, MVPA, and TPA; younger than older women for MVPA; and women with BMI ≥30 than <30 kg/m2 for LPA. CONCLUSION: Greater levels of accelerometer-assessed PA were associated with lower BC risk. Associations varied by age and obesity and were not independent of BMI or physical function.

Accelerometer-measured physical activity and sitting with incident mild cognitive impairment or probable dementia among older women.

INTRODUCTION: Physical activity (PA) is prospectively inversely associated with dementia risk, but few studies examined accelerometer measures of PA and sitting with rigorously-adjudicated mild cognitive impairment (MCI) and dementia risk. METHODS: We examined the associations of accelerometer measures (PA and sitting) with incident MCI/probable dementia in the Women's Health Initiative (n = 1277; mean age = 82 ± 6 years) RESULTS: Over a median follow-up of 4.2 years, 267 MCI/probable dementia cases were identified. Adjusted Cox regression HRs (95% CI) across moderate-to-vigorous PA (MVPA) min/d quartiles were 1.00 (reference), 1.28 (0.90 to 1.81), 0.79 (0.53 to 1.17), and 0.69 (0.45 to 1.06); P-trend = 0.01. Adjusted HRs (95% CI) across steps/d quartiles were 1.00 (reference), 0.73 (0.51 to 1.03), 0.64 (0.43 to 0.94), and 0.38 (0.23 to 0.61); P-trend < 0.001. The HR (95% CI) for each 1-SD increment in MVPA (31 min/d) and steps/d (1865) were 0.79 (0.67 to 0.94) and 0.67 (0.54 to 0.82), respectively. Sitting was not associated with MCI/probable dementia. DISCUSSION: Findings suggest ≥ moderate intensity PA, particularly stepping, associates with lower MCI and dementia risk. HIGHLIGHTS: Few studies have examined accelerometer-measured physical activity, including steps, and sitting with incident ADRD. Moderate-to-vigorous physical activity and steps, but not light physical activity or sitting, were inversely associated with lower ADRD risk. Among older women, at least moderate intensity physical activity may be needed to reduce ADRD risk.

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

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

Validation, Recalibration, and Predictive Accuracy of Published V̇O 2max Prediction Equations for Adults Ages 50-96 Yr.

PURPOSE: Maximal oxygen uptake ( ) is the criterion measure of cardiorespiratory fitness. Lower cardiorespiratory fitness is a strong predictor of poor health outcomes, including all-cause mortality. Because testing is resource intensive, several non-exercise-based V˙O 2max prediction equations have been published. We assess these equations' ability to predict measured V˙O 2max , recalibrate these equations, and quantify the association of measured and predicted V˙O 2max with all-cause mortality. METHODS: Baltimore Longitudinal Study of Aging participants with valid V˙O 2max tests were included ( n = 1080). Using published V˙O 2max prediction equations, we calculated predicted V˙O 2max and present performance metrics before and after recalibration (deriving new regression estimates by regressing measured V˙O 2max on Baltimore Longitudinal Study of Aging covariates). Cox proportional hazards models were fit to quantify associations of measured, predicted, and recalibration-predicted values of V˙O 2max with mortality. RESULTS: Mean age and V˙O 2max were 69.0 ± 10.4 yr and 21.6 ± 5.9 mL·kg -1 ·min -1 , respectively. The prediction equations yielded root mean square error values ranging from 4.2 to 20.4 mL·kg -1 ·min -1 . After recalibration, these values decreased to 3.9-4.2 mL·kg -1 ·min -1 . Adjusting for all covariates, all-cause mortality risk was 66% lower for the highest quartile of measured V˙O 2max relative to the lowest. Predicted V˙O 2max variables yielded similar estimates in unadjusted models but were not robust to adjustment. CONCLUSIONS: Measured V˙O 2max is an extremely strong predictor of all-cause mortality. Several published V˙O 2max prediction equations yielded the following: 1) reasonable performance metrics relative to measured V˙O 2max especially when recalibrated, and 2) all-cause mortality hazard ratios similar to those of measured V˙O 2max , especially when recalibrated, yet 3) were not robust to adjustment for basic demographic covariates likely because these were used in the equation for predicted V˙O 2max .