Dairy intake and cardiovascular diseases risk factors: a cross-sectional study on Iranian obese and overweight women.

OBJECTIVE: Atherosclerotic cardiovascular disease (ASCVD) is one of the leading causes of death worldwide. Dietary interventions can directly affect several ASCVD risk factors. This study aimed to assess an association between dairy consumption and the odds of ASCVD and its risk factors in women with overweight and obesity. METHODS: The present cross-sectional study was conducted on 390 Iranian women aged 18-48 years and body mass index (BMI) ≥ 25 kg/m². Dairy consumption was assessed using a 147-item food frequency questionnaire. Participants were divided into tertiles based on their dairy consumption with 130 (33.3%) women in each category. RESULTS: The participants had an average age of 36.73 ± 9.18 years, and the mean BMI was 31.28 ± 4.30 kg/m2. In the unadjusted model, individuals in the third tertile of dairy consumption had 0.79 times lower odds of ASCVD compared to those in the first tertile (OR: 0.21; 95% Confidence Interval (CI): 0.11, 0.41; P-value = 0.001). Additionally, we observed a significant inverse relationship between higher dairy intake and adiposity markers, blood pressure, and Triglyceride glucose-body mass index (TyG-BMI). CONCLUSION: The study revealed a negative association between dairy intake and the risk of ASCVD but this association diminished after adjusting for confounding factors. It also found a negative association between dairy consumption with BMI, fat mass index, body fat, blood pressure, and TyG-BMI.

The Joint Association of Fitness and Fatness on Cardiovascular Disease Mortality: A Meta-Analysis.

The joint association of cardiorespiratory fitness (CRF) and body mass index (BMI) on cardiovascular disease (CVD) mortality was determined. PubMed and CINAHL were searched following PRISMA guidelines. Included studies were prospective, had objective assessments of maximal CRF and BMI, and compared the joint impact of CRF and BMI on CVD mortality risk to normal weight, fit referents. Pooled hazard ratios and 95% confidence intervals were calculated from eight articles with nine independent groups using a random effects model. Unfit individuals had two to three times the risk of mortality across all levels of BMI. Overweight and obese-fit individuals had 25% and 42% increased mortality risk, respectively, compared to normal weight-fit individuals. However, for the obese-fit group, a one study removed analysis for five studies resulted in non-significant changes in mortality risk. Researchers, clinicians, and public health officials are encouraged to employ CRF interventions to reduce CDV mortality risk.

Impact of EPOC adjustment on estimation of energy expenditure using activity monitors.

PURPOSE: To examine the accuracy of activity monitors in estimating energy expenditure (EE) during activities of varying mode and intensity and to evaluate the impact of including energy expended during recovery from activity (EPOC) on the EE estimate. EE estimates obtained from the Fitbit Surge (FBS), Garmin Vívofit (GV) and SenseWear Armband Mini (SWA) were compared to criterion EE with and without EPOC adjustments during moderate- and vigorous-intensity treadmill and cycling activities. METHODS: Participants (N = 34; 23 males) completed counterbalanced treadmill or cycling conditions, comprised of a resting metabolic rate measurement, 10-min bouts of moderate- and vigorous-intensity activity and an EPOC measurement. Participants simultaneously wore the three activity monitors and a portable metabolic analyser. RESULTS: The FBS provided lowest percent error (PE) during treadmill walking (4.4%) and the GV during moderate (6.4%) and vigorous (-0.1%) cycling bouts. EPOC-adjusted PE was higher than non-EPOC PE across all monitors and activities. Mean absolute error rate (MAPE), indicating overall measurement error, was the smallest for the FBS (14.1%) during moderate treadmill walking and the largest for the SWA (53.5%) for vigorous intensity cycling. Only the FBS had comparable non-EPOC (14.6%) and EPOC-adjusted (17.6%) MAPE during treadmill walking. CONCLUSION: The activity monitors tended to underestimate EE during moderate and vigorous treadmill and cycling activities. The EE estimates from the activity monitors did not account for the energy cost met by anaerobic means during activity, as suggested by the higher EPOC-adjusted EE error rates.

An Evaluation of Time-Trial-Based Predictions of V[Combining Dot Above]O2max and Recommended Training Paces for Collegiate and Recreational Runners.

Scudamore, EM, Barry, VW, and Coons, JM. An Evaluation of time-trial-based predictions of V[Combining Dot Above]O2max and recommended training paces for collegiate and recreational runners. J Strength Cond Res 32(4): 1137-1143, 2018-The purpose of the current study was to determine the accuracy of Jack Daniels' VDOT Running Calculator for the prediction of V[Combining Dot Above]O2max, and recommendations of interval and training paces (pIN and pTH) in samples of National Collegiate Athletic Association Division 1 track athletes (ATH, n = 11) and recreational runners (REC; n = 9). Predicted variable data were obtained using results from indoor 5-km time-trials. Data from the VDOT Calculator were compared with laboratory-tested V[Combining Dot Above]O2max, pace at V[Combining Dot Above]O2max (V[Combining Dot Above]O2maxpace), and lactate threshold pace (LTpace). Results indicated that VDOT underestimated V[Combining Dot Above]O2max in ATH (t(10) = -6.00, p < 0.001, d = 1.75) and REC (t(8) = -8.96, p < 0.001, d = 3.44). Follow-up between-groups analysis indicated that the difference between VDOT and V[Combining Dot Above]O2max was significantly greater in REC than in ATH (p = 0.0031, d = 1.59). pIN was slower than V[Combining Dot Above]O2maxpace in REC (t(8) = -4.26, p = 0.003, d = 1.76), but not different in ATH (t(10) = 0.52, p = 0.614, d = 0.14). Conversely, pTH was faster than LTpace in ATH (t(8) = -4.17, p = 0.003, d = 1.49), but not different in REC (t(8) = 1.64, p = 0.139, d = 0.57). Practically, pTH can be confidently used for threshold training regardless of the ability level. pIN also seemed to be accurate for ATH, but may be not be optimal for improving V[Combining Dot Above]O2max in REC. Practitioners should interpret VDOT with caution as it may underestimate V[Combining Dot Above]O2max.

Effect of Caffeine on near Maximal Blood Pressure and Blood Pressure Recovery in Physically-Active, College-Aged Females.

The purpose of this study is to determine how caffeine affects exercise blood pressure (BP) and active and passive recovery BP after vigorous intensity exercise in physically active college-aged females. Fifteen physically active, ACSM stratified low-risk females (age (y): 23.53 ± 4.07, weight (kg): 60.34 ± 3.67, height (cm): 165.14 ± 7.20, BMI (kg/m2): 22.18 ± 1.55) participated in two Bruce protocol exercise tests. Before each test participants consumed 1) a placebo or 2) 3.3 mg·kg-1 of caffeine at least one hour before exercise in a counterbalanced double-blinded fashion. After reaching 85% of their age-predicted maximum heart rate, BP was taken and participants began an active (i.e. walking) recovery phase for 6 minutes followed by a passive (i.e. sitting) recovery phase. BP was assessed every two minutes in each phase. Recovery times were assessed until active and passive BP equaled 20 mmHg and 10 mmHg above resting, respectively. Participants completed each test 1-2 weeks a part. Maximal systolic and diastolic blood pressures were not significantly different between the two trials. Active recovery, passive recovery, and total recovery times were all significantly longer during the caffeine trial than the placebo trial. Furthermore, the time to reach age-predicted maximum heart rate was significantly shorter in the placebo trial than the caffeine trial. While caffeine consumption did not significantly affect maximal blood pressure, it did affect active and passive recovery time following vigorous intensity exercise in physically active females. Exercise endurance also improved after consuming caffeine in this population.

Live vs. digital video disk exercise in college--aged females.

Although exercise digital video disk (DVD) sales have substantially increased over the past decade, little is known on the effectiveness of personal training vs. DVD exercises. The purpose of this study was to compare energy expenditures and heart rates of live and DVD vigorously intense exercise sessions. Twenty active and low-to-moderate fit, college-aged females completed 2 identical exercise sessions. Each exercise session consisted of 6 exercises; 1 session was completed with a personal trainer and the other with a DVD. A portable metabolic analyzer was used to measure oxygen consumption and record heart rate. Both energy expenditure (p < 0.001) and heart rate (p = 0.001) were significantly higher during the live exercise session as compared with the DVD exercise session. Rate of perceived exertion was significantly higher for the live exercise session compared with the DVD exercise session (p = 0.045). Finally, the majority (89%) of the participants reported that they preferred the live exercise session over the DVD exercise session. The results suggest that low-to-moderately fit college-aged females not only prefer exercise sessions with a personal trainer but will also demonstrate higher energy expenditures and heart rates.

Fitness vs. fatness on all-cause mortality: a meta-analysis.

The purpose of this study was to quantify the joint association of cardiorespiratory fitness (CRF) and weight status on mortality from all causes using meta-analytical methodology. Studies were included if they were (1) prospective, (2) objectively measured CRF and body mass index (BMI), and (3) jointly assessed CRF and BMI with all-cause mortality. Ten articles were included in the final analysis. Pooled hazard ratios were assessed for each comparison group (i.e. normal weight-unfit, overweight-unfit and -fit, and obese-unfit and -fit) using a random-effects model. Compared to normal weight-fit individuals, unfit individuals had twice the risk of mortality regardless of BMI. Overweight and obese-fit individuals had similar mortality risks as normal weight-fit individuals. Furthermore, the obesity paradox may not influence fit individuals. Researchers, clinicians, and public health officials should focus on physical activity and fitness-based interventions rather than weight-loss driven approaches to reduce mortality risk.

Cardiometabolic results from an armband-based weight loss trial.

PURPOSE: This report examines the blood chemistry and blood pressure (BP) results from the Lifestyle Education for Activity and Nutrition (LEAN) study, a randomized weight loss trial. A primary purpose of the study was to evaluate the effects of real-time self-monitoring of energy balance (using the SenseWear(™) Armband, BodyMedia, Inc Pittsburgh, PA) on these health factors. METHODS: 164 sedentary overweight or obese adults (46.8 ± 10.8 years; BMI 33.3 ± 5.2 kg/m(2); 80% women) took part in the 9-month study. Participants were randomized into 4 conditions: a standard care condition with an evidence-based weight loss manual (n = 40), a group-based behavioral weight loss program (n = 44), an armband alone condition (n = 41), and a group plus armband (n = 39) condition. BP, fasting blood lipids and glucose were measured at baseline and 9 months. RESULTS: 99 participants (60%) completed both baseline and follow-up measurements for BP and blood chemistry analysis. Missing data were handled by baseline carried forward. None of the intervention groups had significant changes in blood lipids or BP when compared to standard care after adjustment for covariates, though within-group lowering was found for systolic BP in group and group + armband conditions, a rise in total cholesterol and LDL were found in standard care and group conditions, and a lowering of triglycerides was found in the two armband conditions. Compared with the standard care condition, fasting glucose decreased significantly for participants in the group, armband, and group + armband conditions (all P < 0.05), respectively. CONCLUSION: Our results suggest that using an armband program is an effective strategy to decrease fasting blood glucose. This indicates that devices, such as the armband, can be a successful way to disseminate programs that can improve health risk factors. This can be accomplished without group-based behavioral programs, thereby potentially reducing costs.

Electronic feedback in a diet- and physical activity-based lifestyle intervention for weight loss: a randomized controlled trial.

BACKGROUND: The SenseWear™ Armband (SWA) (BodyMedia, Inc. Pittsburgh, PA) is a physical activity and lifestyle monitor that objectively and accurately measures free-living energy balance and sleep and includes software for self-monitoring of daily energy expenditure and energy intake. The real-time feedback of the SWA can improve individual self-monitoring and, therefore, enhance weight loss outcomes. METHODS: We recruited 197 sedentary overweight or obese adults (age, 46.8 ± 10.8 y; body mass index (BMI), 33.3 ± 5.2 kg/m(2); 81% women, 32% African-American) from the greater Columbia, South Carolina area. Participants were randomized into 1 of 4 groups, a self-directed weight loss program via an evidence-based weight loss manual (Standard Care, n = 50), a group-based behavioral weight loss program (GWL, n = 49), the armband alone (SWA-alone, n = 49), or the GWL plus the armband (GWL+SWA, n = 49), during the 9-month intervention. The primary outcome was change in body weight and waist circumference. A mixed-model repeated-measures analysis compared change in the intervention groups to the standard care group on weight and waist circumference status after adjusting for age, sex, race, education, energy expenditure, and recruitment wave. RESULTS: Body weight was available for 62% of participants at 9 months (52% standard care, 70% intervention). There was significant weight loss in all 3 intervention groups (GWL, 1.86 kg, P = 0.05; SWA-alone, 3.55 kg, P = 0.0002; GWL+SWA, 6.59 kg, P < 0.0001) but not in the Standard Care group (0.89 kg, P = 0.39) at month 9. Only the GWL+SWA group achieved significant weight loss at month 9 compared to the Standard Care group (P = 0.04). Significant waist circumference reductions were achieved in all 4 groups at month 9 (Standard Care, 3.49 cm, P = 0.0004; GWL, 2.42 cm, P = 0.008; SWA-alone, 3.59 cm, P < 0.0001; GWL+SWA, 6.77 cm, P < 0.0001), but no intervention group had significantly reduced waist circumference compared to the Standard Care group. CONCLUSIONS: Continuous self-monitoring from wearable technology with real-time feedback may be particularly useful to enhance lifestyle changes that promote weight loss in sedentary overweight or obese adults. This strategy, combined with a group-based behavioral intervention, may yield optimal weight loss.

Using a technology-based intervention to promote weight loss in sedentary overweight or obese adults: a randomized controlled trial study design.

PURPOSE: The SenseWear™ Armband is an activity monitor developed to improve lifestyle self-monitoring. Currently, few studies assess electronic self-monitoring and weight loss with a lifestyle intervention program. To our knowledge, only one study has used the SenseWear Armband in combination with a lifestyle intervention to improve weight loss, and no studies have evaluated whether a self-monitoring intervention based solely on the armband can promote weight loss. Consequently, the aims of the study were to assess weight loss from electronic self-monitoring, to compare these values to the lifestyle intervention and standard care groups, and to compare weight loss with lifestyle intervention with and without the armband. PATIENTS AND METHODS: We recruited 197 sedentary overweight or obese adults (age, 46.8 ± 10.8 years; BMI, 33.3 ± 5.2 kg/m(2)) to participate in the 9-month study. Participants were randomized into one of four weight loss groups: 1) the standard care group received a self-directed weight loss program, complete with an evidence-based weight loss manual (standard care, n = 50); 2) a 14-week group-based behavioral weight loss program followed by weekly, biweekly, and monthly telephone counseling calls (GWL, n = 49); 3) the use of the armband to help improve lifestyle self-monitoring (SWA alone, n = 49); or (4) the group-based behavioral weight loss program and follow-up telephone counseling calls plus the armband (GWL + SWA, n = 49). All participants received the evidence-based weight loss manual at baseline. All measures were performed at baseline and months 4 and 9. The primary outcomes were weight loss and waist circumference reduction. RESULTS: This study is a well-designed randomized controlled study powered to detect a 0.5-kg weight loss and 0.6-cm waist circumference reduction in overweight and obese sedentary adults. CONCLUSION: Innovative technologies are providing lifestyle self-monitoring and weight loss tools. Utilizing these technologies may be an important step in improving the current obesity epidemic.