Healthy Lifestyle in the Primordial Prevention of Cardiovascular Disease Among Young Women

AbstractBackgroundOverall mortality rates from coronary heart disease (CHD) in the United States have declined in recent decades, but the rate has plateaued among younger women. The potential for further reductions in mortality rates among young women through changes in lifestyle is unknown.ObjectivesThe aim of this study was to estimate the proportion of CHD cases and clinical cardiovascular disease (CVD) risk factors among young women that might be attributable to poor adherence to a healthy lifestyle.MethodsA prospective analysis was conducted among 88,940 women ages 27 to 44 years at baseline in the Nurses’ Health Study II who were followed from 1991 to 2011. Lifestyle factors were updated repeatedly by questionnaire. A healthy lifestyle was defined as not smoking, a normal body mass index, physical activity ≥ 2.5 h/week, television viewing ≤ 7 h/week, diet in the top 40% of the Alternative Healthy Eating Index–2010, and 0.1 to 14.9 g/day of alcohol. To estimate the proportion of CHD and clinical CVD risk factors (diabetes, hypertension, and hypercholesterolemia) that could be attributed to poor adherence to a healthy lifestyle, we calculated the population-attributable risk percent.ResultsDuring 20 years of follow-up, we documented 456 incident CHD cases. In multivariable-adjusted models, nonsmoking, a healthy body mass index, exercise, and a healthy diet were independently and significantly associated with lower CHD risk. Compared with women with no healthy lifestyle factors, the hazard ratio for CHD for women with 6 lifestyle factors was 0.08 (95% confidence interval: 0.03 to 0.22). Approximately 73% (95% confidence interval: 39% to 89%) of CHD cases were attributable to poor adherence to a healthy lifestyle. Similarly, 46% (95% confidence interval: 43% to 49%) of clinical CVD risk factor cases were attributable to a poor lifestyle.ConclusionsPrimordial prevention through maintenance of a healthy lifestyle among young women may substantially lower the burden of CVD

Differentiating Between Walking and Stair Climbing Using Raw Accelerometry Data

Wearable accelerometers provide an objective measure of human physical activity. They record high frequency unlabeled three-dimensional time series data. We extract meaningful features from the raw accelerometry data and based on them develop and evaluate a classification method for the detection of walking and its sub-classes, i.e. level walking, descending stairs and ascending stairs. Our methodology is tested on a sample of 32 middle-aged subjects for whom we extracted features based on the Fourier and wavelet transforms. We build subject-specific and group-level classification models utilizing a tree-based methodology. We evaluate the effects of sensor location and tuning parameters on the classification accuracy of the tree models. In the group-level classification setting, we propose a robust feature inter-subject normalization and evaluate its performance compared to unnormalized data. The overall classification accuracy for the three activities at the subject-specific level was on average 87.6%, with the ankle-worn accelerometers showing the best performance with an average accuracy 90.5%. At the group-level, the average overall classification accuracy for the three activities using the normalized features was 80.2% compared to 72.3% for the unnormalized features. In summary, a framework is provided for better use and feature extraction from raw accelerometry data to differentiate among different walking modalities as well as considerations for study design

Change in Physical Activity and Sitting Time After Myocardial Infarction and Mortality Among Postmenopausal Women in the Women\u27s Health Initiative-Observational Study

BACKGROUND: How physical activity (PA) and sitting time may change after first myocardial infarction (MI) and the association with mortality in postmenopausal women is unknown. METHODS AND RESULTS: Participants included postmenopausal women in the Women\u27s Health Initiative-Observational Study, aged 50 to 79 years who experienced a clinical MI during the study. This analysis included 856 women who had adequate data on PA exposure and 533 women for sitting time exposures. Sitting time was self-reported at baseline, year 3, and year 6. Self-reported PA was reported at baseline through year 8. Change in PA and sitting time were calculated as the difference between the cumulative average immediately following MI and the cumulative average immediately preceding MI. The 4 categories of change were: maintained low, decreased, increased, and maintained high. The cut points were \u3e /=7.5 metabolic equivalent of task hours/week versus /=8 h/day versus /day for sitting time. Cox proportional hazard models estimated hazard ratios and 95% CIs for all-cause, coronary heart disease, and cardiovascular disease mortality. Compared with women who maintained low PA (referent), the risk of all-cause mortality was: 0.54 (0.34-0.86) for increased PA and 0.52 (0.36-0.73) for maintained high PA. Women who had pre-MI levels of sitting time /day, every 1 h/day increase in sitting time was associated with a 9% increased risk (hazard ratio=1.09, 95% CI: 1.01, 1.19) of all-cause mortality. CONCLUSIONS: Meeting the recommended PA guidelines pre- and post-MI may have a protective role against mortality in postmenopausal women

Relationship of Sedentary Behavior and Physical Activity to Incident Cardiovascular Disease Results From the Women's Health Initiative

ObjectivesThe aim of this study was to examine the independent and joint associations of sitting time and physical activity with risk of incident cardiovascular disease (CVD).BackgroundSedentary behavior is recognized as a distinct construct beyond lack of leisure-time physical activity, but limited data exist on the interrelationship between these 2 components of energy balance.MethodsParticipants in the prospective Women’s Health Initiative Observational Study (n = 71,018), 50 to 79 years of age and free of CVD at baseline (1993 to 1998), provided information on sedentary behavior, defined as hours of sitting/day, and usual physical activity at baseline and during follow-up through September 2010. First CVD (coronary heart disease or stroke) events were centrally adjudicated.ResultsSitting ≥10 h/day compared with ≤5 h/day was associated with increased CVD risk (hazard ratio: 1.18, 95% confidence interval: 1.09 to 1.29) in multivariable models including physical activity. Low physical activity was also associated with higher CVD risk (p for trend < 0.001). When women were cross-classified by sitting time and physical activity (p for interaction = 0.94), CVD risk was highest in inactive women (≤1.7 metabolic equivalent task-h/week) who also reported ≥10 h/day of sitting. Results were similar for coronary heart disease and stroke when examined separately. Associations between prolonged sitting and risk of CVD were stronger in overweight versus normal weight women and women 70 years of age and older compared with younger women.ConclusionsProlonged sitting time was associated with increased CVD risk, independent of leisure-time physical activity, in postmenopausal women without a history of CVD. A combination of low physical activity and prolonged sitting augments CVD risk

Interventions outside the workplace for reducing sedentary behaviour in adults under 60 years of age

Background Adults spend a majority of their time outside the workplace being sedentary. Large amounts of sedentary behaviour increase the risk of type 2 diabetes, cardiovascular disease, and both all‐cause and cardiovascular disease mortality. Objectives Primary • To assess effects on sedentary time of non‐occupational interventions for reducing sedentary behaviour in adults under 60 years of age Secondary • To describe other health effects and adverse events or unintended consequences of these interventions • To determine whether specific components of interventions are associated with changes in sedentary behaviour • To identify if there are any differential effects of interventions based on health inequalities (e.g. age, sex, income, employment) Search methods We searched CENTRAL, MEDLINE, Embase, Cochrane Database of Systematic Reviews, CINAHL, PsycINFO, SportDiscus, and ClinicalTrials.gov on 14 April 2020. We checked references of included studies, conducted forward citation searching, and contacted authors in the field to identify additional studies. Selection criteria We included randomised controlled trials (RCTs) and cluster RCTs of interventions outside the workplace for community‐dwelling adults aged 18 to 59 years. We included studies only when the intervention had a specific aim or component to change sedentary behaviour. Data collection and analysis Two review authors independently screened titles/abstracts and full‐text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted trial authors for additional information or data when required. We examined the following primary outcomes: device‐measured sedentary time, self‐report sitting time, self‐report TV viewing time, and breaks in sedentary time. Main results We included 13 trials involving 1770 participants, all undertaken in high‐income countries. Ten were RCTs and three were cluster RCTs. The mean age of study participants ranged from 20 to 41 years. A majority of participants were female. All interventions were delivered at the individual level. Intervention components included personal monitoring devices, information or education, counselling, and prompts to reduce sedentary behaviour. We judged no study to be at low risk of bias across all domains. Seven studies were at high risk of bias for blinding of outcome assessment due to use of self‐report outcomes measures. Primary outcomes Interventions outside the workplace probably show little or no difference in device‐measured sedentary time in the short term (mean difference (MD) ‐8.36 min/d, 95% confidence interval (CI) ‐27.12 to 10.40; 4 studies; I² = 0%; moderate‐certainty evidence). We are uncertain whether interventions reduce device‐measured sedentary time in the medium term (MD ‐51.37 min/d, 95% CI ‐126.34 to 23.59; 3 studies; I² = 84%; very low‐certainty evidence) We are uncertain whether interventions outside the workplace reduce self‐report sitting time in the short term (MD ‐64.12 min/d, 95% CI ‐260.91 to 132.67; I² = 86%; very low‐certainty evidence). Interventions outside the workplace may show little or no difference in self‐report TV viewing time in the medium term (MD ‐12.45 min/d, 95% CI ‐50.40 to 25.49; 2 studies; I² = 86%; low‐certainty evidence) or in the long term (MD 0.30 min/d, 95% CI ‐0.63 to 1.23; 2 studies; I² = 0%; low‐certainty evidence). It was not possible to pool the five studies that reported breaks in sedentary time given the variation in definitions used. Secondary outcomes Interventions outside the workplace probably have little or no difference on body mass index in the medium term (MD ‐0.25 kg/m², 95% CI ‐0.48 to ‐0.01; 3 studies; I² = 0%; moderate‐certainty evidence). Interventions may have little or no difference in waist circumference in the medium term (MD ‐2.04 cm, 95% CI ‐9.06 to 4.98; 2 studies; I² = 65%; low‐certainty evidence). Interventions probably have little or no difference on glucose in the short term (MD ‐0.18 mmol/L, 95% CI ‐0.30 to ‐0.06; 2 studies; I² = 0%; moderate‐certainty evidence) and medium term (MD ‐0.08 mmol/L, 95% CI ‐0.21 to 0.05; 2 studies, I² = 0%; moderate‐certainty evidence) Interventions outside the workplace may have little or no difference in device‐measured MVPA in the short term (MD 1.99 min/d, 95% CI ‐4.27 to 8.25; 4 studies; I² = 23%; low‐certainty evidence). We are uncertain whether interventions improve device‐measured MVPA in the medium term (MD 6.59 min/d, 95% CI ‐7.35 to 20.53; 3 studies; I² = 70%; very low‐certainty evidence). We are uncertain whether interventions outside the workplace improve self‐reported light‐intensity PA in the short‐term (MD 156.32 min/d, 95% CI 34.34 to 278.31; 2 studies; I² = 79%; very low‐certainty evidence). Interventions may have little or no difference on step count in the short‐term (MD 226.90 steps/day, 95% CI ‐519.78 to 973.59; 3 studies; I² = 0%; low‐certainty evidence) No data on adverse events or symptoms were reported in the included studies. Authors' conclusions Interventions outside the workplace to reduce sedentary behaviour probably lead to little or no difference in device‐measured sedentary time in the short term, and we are uncertain if they reduce device‐measured sedentary time in the medium term. We are uncertain whether interventions outside the workplace reduce self‐reported sitting time in the short term. Interventions outside the workplace may result in little or no difference in self‐report TV viewing time in the medium or long term. The certainty of evidence is moderate to very low, mainly due to concerns about risk of bias, inconsistent findings, and imprecise results. Future studies should be of longer duration; should recruit participants from varying age, socioeconomic, or ethnic groups; and should gather quality of life, cost‐effectiveness, and adverse event data. We strongly recommend that standard methods of data preparation and analysis are adopted to allow comparison of the effects of interventions to reduce sedentary behaviour

Balance- and Strength-Training Protocols to Improve Chronic Ankle Instability Deficits, Part II: Assessing Patient-Reported Outcome Measures

Context: Assessing global, regional, and fear-of-reinjury outcomes in individuals with chronic ankle instability (CAI) is critical to understanding the effectiveness of clinical interventions. Objective: To determine the improvement of patient-reported outcomes after balance- and strength-training and control protocols among participants with CAI. Design: Randomized controlled clinical trial. Setting: Athletic training research laboratory. Patients or Other Participants: Thirty-nine volunteers with CAI who scored 11 or greater on the Identification of Functional Ankle Instability questionnaire were randomly assigned to 1 of 3 groups: balance-training protocol (7 males, 6 females; age = 23.5 ± 6.5 years, height = 175.0 ± 8.5 cm, mass = 72.8 ± 10.9 kg), strength-training protocol (8 males, 5 females; age = 24.6 ± 7.7 years, height = 173.2 ± 9.0 cm, mass = 76.0 ± 16.2 kg), or control (6 males, 7 females; age = 24.8 ± 9.0 years, height = 175.5 ± 8.4 cm, mass = 79.1 ± 16.8 kg). Intervention(s): Each group met for 20 minutes, 3 times each week, for 6 weeks. The control group completed a mild to moderately strenuous bicycle workout. Main Outcome Measure(s): Global patient-reported outcomes, regional ankle function, and perceived instability were measured using the Disablement in the Physically Active Scale, the Fear-Avoidance Beliefs Questionnaire, the Foot and Ankle Ability Measure, and a visual analog scale for perceived instability. Participants completed the questionnaires at pretest and 6 weeks posttest. A multivariate repeated-measures analysis of variance with follow-up univariate analysis was conducted. The α level was set a priori at .05. Results: No time-by-group interaction was found (P = .78, η2 = 0.09). However, we observed a main effect for time (P = .001, η2 = 0.49). Follow-up univariate analyses revealed differences between the pretest and posttest for the Disablement in the Physically Active Scale (P = .02, η2 = 0.15), Fear-Avoidance Beliefs Questionnaire (P = .001, η2 = 0.27), Foot and Ankle Ability Measure–Activities of Daily Living subscale (P = .003, η2 = 0.22), Foot and Ankle Ability Measure–Sport subscale (P = .001, η2 = 0.36), and visual analog scale (P = .008, η2 = 0.18). Conclusions: Statistically, after the 6-week intervention, all groups improved in global and regional health-related quality of life. Clinicians should compare patient-reported outcomes with clinical measures to have a better understanding of progression during rehabilitation

Elementary School Personnel and Cultural Factors Affecting Health Education Implementation in the High- Stakes Testing Era*

BACKGROUNDDespite proven health and learning benefits, health education implementation in elementary schools is not optimal. This study investigated learning environment, leadership, and training factors that may influence elementary- level health education implementation in the current standardized testing- saturated environment.METHODSSurvey data were collected from principals of 8 Michigan elementary schools and, via focus groups, 30 teachers in their schools. Teacher groups were separated into 2 categories based on principals’ understanding of state health education policies. Grounded theory analysis was used.RESULTSDespite all 30 teachers’ positive attitudes toward health education, numerous consistent implementation barriers were identified; competition for instructional time with tested subjects was most critical. Teachers with principals who indicated a greater understanding of state policies reported more: consistent instruction; availability of resources, and encouragement to teach select topics, especially mental health.CONCLUSIONThat these findings were produced in a state with strong CSHE polices, proven curricula, and expansive support systems are disheartening and accentuate the profound impact of standardized testing on elementary- level health education implementation. More promising, principals’ understanding of applicable state- level policies appeared to generate stronger health education implementation. Future research should focus on the possible impact of time devoted to health instruction on standardized test scores.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/170253/1/josh13071_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/170253/2/josh13071.pd

BMI and Central Obesity With Falls Among Community-Dwelling Older Adults

Introduction: This study examined the associations of BMI category and central obesity status, with falls among community-dwelling older adults in the U.S. Methods: Data were drawn from the 2012 and 2014 U.S. Health and Retirement Study, a nationally representative longitudinal panel study funded by the National Institute of Aging. The study participants were U.S. community-dwelling older adults aged ≥65 years (N=3,383). Multiple logistic regression and Poisson regression analyses examined the associations of BMI category and central obesity (waist circumference >102 cm in men and >88 cm in women) with experiencing a fall and fall injury, after adjusting for all other covariates. A prospective analysis was conducted in which independent variables from 2012 were examined in relation to dependent variables measured in the same participants in 2014. Results: Overall, 35.2% of older adults experienced at least one fall in the past 2 years. Compared with those who were not, centrally obese older adults were more likely to experience a fall (AOR=1.37, 95% CI=1.01, 1.85) and fall more frequently (incidence rate ratio=1.15, 95% CI=1.03, 1.29). Fallers in the obese BMI category were less likely than normal weight fallers to experience a fall injury (AOR=0.56, 95% CI=0.35, 0.91). Conclusions: These findings suggest that (1) central obesity be measured when assessing older adults’ fall risk and (2) specific community prevention strategies for centrally obese older adults be developed to better prevent falls and fall related-injuries

Adolescent Weight and Electronic Vapor Product Use: Comparing BMI-Based With Perceived Weight Status

Introduction: This study examined the associations of BMI-based and perceived body weight status with electronic vapor product use, cigarette smoking, and dual use among U.S. adolescents. Methods: A cross-sectional analysis was conducted in 2017 on data from 15,129 adolescents in the National Youth Risk Behavior Survey, 2015. Multiple logistic regression analyses were used to examine the associations of BMI-based and perceived weight status with electronic vapor product use, cigarette smoking, and dual use, after adjusting for all other covariates. The regression models were stratified by gender. Results: Overall, 25.5% of males used electronic vapor products, 11.6% smoked cigarettes, and 8.1% used both; percentages among females were 22.6%, 9.8%, and 6.8%, respectively. Females who perceived themselves as overweight were more likely than those who perceived themselves as normal weight to be current electronic vapor product users (AOR=1.09, 95% CI=1.01, 1.19) and dual users (AOR=1.23, 95% CI=1.01, 1.49). When compared with normal BMI-based category, males with obese BMI status were more likely to be current cigarette smokers (AOR=1.61, 95% CI=1.06, 2.44), however, only females with overweight BMI status were more likely to be current smokers (AOR=1.89, 95% CI=1.25, 2.86). Conclusions: Findings suggest that the influence of adolescents’ body weight perceptions and BMI-based status should be accounted for when developing nicotine-containing product use prevention programs for adolescents. Specific strategies for influencing female adolescents who perceive themselves as overweight should be included to prevent emerging electronic vapor product and dual use

Adolescent Diet Quality and Cardiovascular Disease Risk Factors and Incident Cardiovascular Disease in Middle-Aged Women

BACKGROUND: Primary prevention of cardiovascular disease (CVD) focuses on treatment of risk factors, including hypercholesterolemia, hypertension, and type 2 diabetes mellitus. We investigated whether a healthy diet in adolescence prevents development of clinical risk factors or incidence of CVD in adulthood. METHODS AND RESULTS: We examined the time to the first development of ≥1 clinical risk factor (hypercholesterolemia, hypertension, or type 2 diabetes mellitus) or CVD in relation to a high school Alternative Healthy Eating Index (HS‐AHEI) within the Nurses’ Health Study II. Among those who completed a food frequency questionnaire about their high school diet and adult diet (mean age 42 years), 27 406 women free of clinical risk factors and 42 112 women free of CVD in 1998 were followed to June 2011. Hazard ratios (HRs) and 95% CIs were adjusted for potential confounders in high school and adulthood. We documented 11 542 first diagnoses of clinical risk factors and 423 CVD events. The HS‐AHEI was associated with a lower rate of risk factors (HR highest versus lowest quintiles 0.82; 95% CI, 0.77–0.87 [P trend <0.001]), was inversely associated with risk of developing ≥1 clinical risk factor in women with a low, medium, and high AHEI score during adulthood (HR high HS‐AHEI/high adult AHEI versus low/low 0.79 [95% CI, 0.74–0.85]), but was not statistically significantly associated with incident CVD. CONCLUSIONS: A healthy diet during adolescence is associated with lower risk of developing CVD risk factors. As diet tracks throughout life, and adult diet prevents CVD, healthy dietary habits that begin early are important for primordial prevention of CVD