The Association between Cardiorespiratory Fitness and the Risk of Breast Cancer in Women.

INTRODUCTION: Studies have shown an inverse association between the risk of breast cancer in women and physical activity. However, information on the association between cardiorespiratory fitness (CRF) assessed objectively by a standardized test and the risk of developing breast cancer is limited. PURPOSE: To examine the CRF-breast cancer risk association in healthy females. METHODS: This retrospective study was derived from the Exercise Testing and Health Outcomes Study cohort ( n = 750,302). Female participants ( n = 44,463; mean age ± SD; 55.1 ± 8.9 yr) who completed an exercise treadmill test evaluation (Bruce protocol) at the Veterans Affairs Medical Centers nationwide from 1999 to 2020 were studied. The cohort was stratified into four age-specific CRF categories (Least-fit, Low-fit, Moderate-fit, and Fit), based on the peak METs achieved during the exercise treadmill test. RESULTS: During 438,613 person-years of observation, 994 women developed breast cancer. After controlling for covariates, the risk of breast cancer was inversely related to exercise capacity. For each 1-MET increase in CRF, the risk of cancer was 7% lower (HR, 0.93; 95% CI, 0.90-0.95; P < 0.001). When risk was assessed across CRF categories with the Least-fit group as the referent, the risk was 18% lower for Low-fit women (HR, 0.82; 95% CI, 0.70-0.96; P = 0.013), 31% for Moderate-fit (HR, 0.69; 95% CI, 0.58-0.82; P < 0.001), and 40% for Fit (HR, 0.60; 95% CI, 0.47-0.75; P < 0.001). CONCLUSIONS: We observed an inverse and graded association between CRF and breast cancer risk in women. Thus, encouraging women to improve CRF may help attenuate the risk of developing breast cancer.

Progression to Insulin Therapy in Patients With Type 2 Diabetes According to Cardiorespiratory Fitness, Body Mass Index, and Statin Therapy.

OBJECTIVE: To evaluate the association between statin therapy, cardiorespiratory fitness (CRF), body mass index (BMI), and progression to insulin therapy in type 2 diabetes mellitus (T2DM). METHODS: Participants were patients with T2DM (mean age, 62.7±8.4 years; men, 178,992; women, 8360) not treated with insulin, with no evidence of uncontrolled cardiovascular disease, who completed an exercise treadmill test between October 1, 1999, and September 3, 2020. Of these, 158,578 were treated with statins and 28,774 were not. We established 5 age-specific CRF categories according to peak metabolic equivalents of task achieved during an exercise treadmill test. RESULTS: During a median follow-up period of 9.0 years, 51,182 patients progressed to insulin therapy with an average annual incidence rate of 28.4 events/1000 person-years. The adjusted progression rate was 27% higher in statin-treated patients (hazard ratio [HR], 1.27; 95% CI, 1.24 to 1.31), related directly to BMI and inversely related to CRF. A progressively higher rate was noted in statin-treated vs non-statin-treated patients within all BMI categories, ranging from 23% for normal weight to 90% for those with BMI of 35 kg/m2 and higher. The statin-CRF interaction revealed 43% higher rate in the least-fit statin-treated patients (HR, 1.43; 95% CI, 1.35 to 1.51) and a progressive decline with increased CRF to 30% lower risk in highly fit statin-treated patients (HR, 0.70; 95% CI, 0.66 to 0.75). CONCLUSION: In patients with T2DM, the statin-related progression to insulin therapy was associated with relatively low CRF and high BMI levels. The progression rate was mitigated by increased CRF regardless of BMI. Clinicians should foster regular exercise for patients with T2DM to enhance CRF and to lessen the rate of progression to insulin therapy.

Cardiorespiratory fitness and risk of heart failure with preserved ejection fraction.

AIMS: Preventive strategies for heart failure with preserved ejection fraction (HFpEF) include pharmacotherapies and lifestyle modifications. However, the association between cardiorespiratory fitness (CRF) assessed objectively by a standardized exercise treadmill test (ETT) and the risk of HFpEF has not been evaluated. Thus, we evaluated the association between CRF and HFpEF incidence. METHODS AND RESULTS: We assessed CRF in US Veterans (624 551 men; mean age 61.2 ± 9.7 years and 43 179 women; mean age 55.0 ± 8.9 years) by a standardized ETT performed between 1999 and 2020 across US Veterans Affairs Medical Centers. All had no evidence of heart failure or myocardial infarction prior to completion of the ETT. We assigned participants to one of five age- and gender-specific CRF categories (quintiles) based on peak metabolic equivalents (METs) achieved during the ETT and four categories based on CRF changes in those with two ETT evaluations (n = 139 434) ≥1.0 year apart. During a median follow-up of 10.1 years (interquartile range 6.0-14.3 years), providing 6 879 229 person-years, there were 16 493 HFpEF events with an average annual rate of 2.4 events per 1000 person-years. The adjusted risk of HFpEF decreased across CRF categories as CRF increased, independent of comorbidities. For fit individuals (≥10.5 METs) the hazard ratio (HR) was 0.48 (95% confidence interval [CI] 0.46-0.51) compared with least fit (≤4.9 METs; referent). Being unfit carried the highest risk (HR 2.88, 95% CI 2.67-3.11) of any other comorbidity. The risk of unfit individuals who became fit was 37% lower (HR 0.63, 95% CI 0.57-0.71), compared to those who remained unfit. CONCLUSIONS: Higher CRF levels are independently associated with lower HFpEF in a dose-response manner. Changes in CRF reflected proportional changes in HFpEF risk, suggesting that the HFpEF risk was modulated by CRF.

Cardiorespiratory Fitness and Mortality Risk Across the Spectra of Age, Race, and Sex.

BACKGROUND: Cardiorespiratory fitness (CRF) is inversely associated with all-cause mortality. However, the association of CRF and mortality risk for different races, women, and elderly individuals has not been fully assessed. OBJECTIVES: The aim of this study was to evaluate the association of CRF and mortality risk across the spectra of age, race, and sex. METHODS: A total of 750,302 U.S. veterans aged 30 to 95 years (mean age 61.3 ± 9.8 years) were studied, including septuagenarians (n = 110,637), octogenarians (n = 26,989), African Americans (n = 142,798), Hispanics (n = 35,197), Native Americans (n = 16,050), and women (n = 45,232). Age- and sex-specific CRF categories (quintiles and 98th percentile) were established objectively on the basis of peak METs achieved during a standardized exercise treadmill test. Multivariable Cox models were used to estimate HRs and 95% CIs for mortality across the CRF categories. RESULTS: During follow-up (median 10.2 years, 7,803,861 person-years of observation), 174,807 subjects died, averaging 22.4 events per 1,000 person-years. The adjusted association of CRF and mortality risk was inverse and graded across the age spectrum, sex, and race. The lowest mortality risk was observed at approximately 14.0 METs for men (HR: 0.24; 95% CI: 0.23-0.25) and women (HR: 0.23; 95% CI: 0.17-0.29), with no evidence of an increase in risk with extremely high CRF. The risk for least fit individuals (20th percentile) was 4-fold higher (HR: 4.09; 95% CI: 3.90-4.20) compared with extremely fit individuals. CONCLUSIONS: The association of CRF and mortality risk across the age spectrum (including septuagenarians and octogenarians), men, women, and all races was inverse, independent, and graded. No increased risk was observed with extreme fitness. Being unfit carried a greater risk than any of the cardiac risk factors examined.

Compounding Effects of Traumatic Brain Injury, Military Status, and Other Factors on Pittsburgh Sleep Quality Index: A Meta-analysis.

INTRODUCTION: Traumatic brain injury (TBI) or concussion is a known risk factor for multiple adverse health outcomes, including disturbed sleep. Although prior studies show adverse effects of TBI on sleep quality, its compounding effect with other factors on sleep is unknown. This meta-analysis aimed to quantify the effects of TBI on subjective sleep quality in the context of military status and other demographic factors. MATERIALS AND METHODS: A programmatic search of PubMed database from inception to June 2020 was conducted to identify studies that compared subjective sleep quality measured using Pittsburgh Sleep Quality Index (PSQI) in individuals with TBI relative to a control group. The meta-analysis included group-wise standard mean difference (SMD) and 95% CI. Pooled means and SDs were obtained for TBI and non-TBI groups with and without military service, and meta-regression was conducted to test for group effects. Exploratory analysis was performed to test for the effect of TBI, non-head injury, military status, sex, and age on sleep quality across studies. RESULTS: Twenty-six articles were included, resulting in a combined total of 5,366 individuals (2,387 TBI and 2,979 controls). Overall, individuals with TBI self-reported poorer sleep quality compared to controls (SMD = 0.63, 95% CI: 0.45 to 0.80). Subgroup analysis revealed differences in the overall effect of TBI on PSQI, with a large effect observed in the civilian subgroup (SMD: 0.80, 95% CI: 0.57 to 1.03) and a medium effect in the civilian subgroup with orthopedic injuries (SMD: 0.40, 95% CI: 0.13 to 0.65) and military/veteran subgroup (SMD: 0.43, 95% CI: 0.14 to 0.71). Exploratory analysis revealed that age and history of military service significantly impacted global PSQI scores. CONCLUSIONS: Poor sleep quality in TBI cohorts may be due to the influence of multiple factors. Military/veteran samples had poorer sleep quality compared to civilians even in the absence of TBI, possibly reflecting unique stressors associated with prior military experiences and the sequelae of these stressors or other physical and/or psychological traumas that combine to heightened vulnerability. These findings suggest that military service members and veterans with TBI are particularly at a higher risk of poor sleep and its associated adverse health outcomes. Additional research is needed to identify potential exposures that may further heighten vulnerability toward poorer sleep quality in those with TBI across both civilian and military/veteran populations.