Fitness Assessments of Women with Polycystic Ovary Syndrome: A Prospective Process Feasibility Study

Background: Fitness is a marker of physiological and mental health. The purpose of this pilot study was to assess the feasibility of processes to recruit women with polycystic ovary syndrome (PCOS) during the Covid pandemic and collect their health and fitness data. Additionally, the data was used to explore possible associations between anthropometrics, PCOS biomarkers, health-related quality-of-life (HRQoL), and depressive symptoms with that of fitness and self-reported physical activity levels among women with PCOS. Method(s): A convenience sample of women with PCOS (n = 15) were recruited via flyers and the snowball method. Participants completed surveys, anthropometrics, a dual energy x-ray absorptiometry scan, blood work, and a fitness assessment. Data were statistically analyzed using Spearman correlations. Result(s): Feasibility measures of recruitment and retention rates were 83% and 100%, respectively. Fidelity measurement for process averaged 97%. Participants (age 25.9 (+/- 6.2), mostly White (80%), single (60%), and employed full-time (67%)) were categorized as obese (body mass index (BMI) 32.2 kg/m2 +/- 8.3, percent bodyfat 41.1% +/- 8.1) with <=1 comorbidity. Most participants were not regularly physically active and had high free testosterone levels (7.6 pg/mL+/-4.3), elevated high-density lipoprotein (63.2 mg/dL+/-12.9), fair cardiovascular capacity, and below average muscular strength/endurance. The following statistically significant and strong associations were found: (1) VO2 max with percent bodyfat (-0.59;p = 0.02), sex hormone binding globulin (0.73;p = 0.00), HRQoL (0.72;p = 0.00), and depressive symptoms (-0.67;p = 0.00), (2) abdominal strength with BMI (-0.66;p = 0.01) and high density lipoprotein (HDL) (0.59;p = 0.02), (3) physical activity level with percent bodyfat (-0.72;p = 0.00), and (4) resistance training with low density lipoprotein (LDL) (-0.52;p = 0.05). Conclusion(s): Collecting health and fitness data from women with PCOS is a feasible research approach. Randomized controlled trials in which health and fitness data are collected from women with PCOS are needed to confirm possible associations between fitness and PCOS clinical features and is in the planning process. Copyright: Copyright © 2023 The Author(s).

Impact of COVID-19 Lockdown on Anthropometric Body Measurements and Nutritional Behaviors in a Colombian Cohort Receiving Online Nutritional Advice

Objective: In this study, we aimed to retrospectively assess the change in weight before and after the COVID-19 mandatory lockdown in Colombia among adults who received nutritional and healthy lifestyle recommendations at weight loss and wellness clinics by telehealth. The primary objective was to describe and compare the mean weight reduction measured at the baseline and by the end of the lockdown. Secondary objectives include describing and comparing body fat percentage, muscle mass percentage, and BMI measured at the baseline and by the end of the lockdown. Method(s): One hundred and seventy-two middle-aged (18-68 years old) women and men received online nutritional and healthy lifestyle advice during the COVID-19 lockdown in Colombia. Weight, fat (%), muscle mass (%), and BMI were assessed before and after the lockdown. We included baseline measurements taken before the lockdown from March 1st to June 20th, 2020, and post-lockdown measurements from August 31st to October 20th, 2020. Exclusion criteria included pregnancy or breastfeeding women, acutely decompensated diabetes, hypertension, CKD, Hypothyroidism or taking any of the obesity treatment medications approved in Colombia, including liraglutide, semaglutide or orlistat. A retrospective analysis was completed to compare the change in mean body anthropometrics. Shapiro Wilk test was used to assess for normality. Paired T Test and Wilcoxon sign test were used to compare the distribution of body anthropometrics before and after the lockdown. IRB approval was obtained before exporting and analyzing the collection of data. Result(s): Out of 205 subjects and after a review of exclusion criteria, 172 subjects were included in the data analysis. 90.1% (155) were women. 52.3% (135) had overweight or obesity. After the COVID-19 lockdown, the mean weight loss reduction was 8.79 kg (SD +/- 5.45, p<0.0001), corresponding to an 11.4% weight loss reduction. The mean fat mass percentage loss was 2.89 % (SD +/- 2.64, p<0.0001), and the mean BMI presented a reduction of 3.16 (SD +/- 1.96, p <0.0001). The mean muscle percentage loss was 0.10% (SD +/- 2.67, p 0.482). Discussion/Conclusion: Subjects receiving telehealth nutritional advice in Colombia during the COVID-19 lockdown had significant clinical and statistical weight, BMI, and fat loss reduction. Muscle mass was preserved;however, this mean change was not statistically significant. Physical inactivity during the lockdown period was a potential contributor to a nonsignificant mean muscle mass change. The subjects in this study were highly motivated to virtually attend weight loss and wellness clinics and to improve body anthropometrics by optimizing lifestyle changes. Telehealth weight loss strategies should always be considered when in-person patient interaction is not available.Copyright © 2023

Anthropometric Measurements and Admission Parameters as Predictors of Acute Respiratory Distress Syndrome in Hospitalized COVID-19 Patients.

Aim: We aimed to single out admission predictors of acute respiratory distress syndrome (ARDS) in hospitalized COVID-19 patients and investigate the role of bioelectrical impedance (BIA) measurements in ARDS development. Method: An observational, prospective cohort study was conducted on 407 consecutive COVID-19 patients hospitalized at the University Clinical Center Kragujevac between September 2021 and March 2022. Patients were followed during the hospitalization, and ARDS was observed as a primary endpoint. Body composition was assessed using the BMI, body fat percentage (BF%), and visceral fat (VF) via BIA. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis. Results: Patients with BMI above 30 kg/m2, very high BF%, and/or very high VF levels were at a significantly higher risk of developing ARDS compared to nonobese patients (OR: 4.568, 8.892, and 2.448, respectively). In addition, after performing multiple regression analysis, six admission predictors of ARDS were singled out: (1) very high BF (aOR 8.059), (2) SaO2 < 87.5 (aOR 5.120), (3) IL-6 > 59.75 (aOR 4.089), (4) low lymphocyte count (aOR 2.880), (5) female sex (aOR 2.290), and (6) age < 68.5 (aOR 1.976). Conclusion: Obesity is an important risk factor for the clinical deterioration of hospitalized COVID-19 patients. BF%, assessed through BIA measuring, was the strongest independent predictor of ARDS in hospitalized COVID-19 patients.

The Role of Bioelectrical Impedance Analysis in Predicting COVID-19 Outcome.

Background: Published data regarding the impact of obesity on COVID-19 outcomes are inconsistent. However, in most studies, body composition was assessed using body mass index (BMI) alone, thus neglecting the presence and distribution of adipose tissue. Therefore, we aimed to investigate the impact of body and visceral fat on COVID-19 outcomes. Methods: Observational, prospective cohort study included 216 consecutive COVID-19 patients hospitalized at University Clinical Center Kragujevac (Serbia) from October to December 2021. Body composition was assessed using the BMI, body fat percentage (%BF), and visceral fat (VF) via bioelectrical impedance analysis (BIA). In addition to anthropometric measurements, variables in the research were socio-demographic and medical history data, as well as admission inflammatory biomarkers. Primary end-points were fatal outcomes and intensive care unit (ICU) admission. Results: The overall prevalence of obesity was 39.3% according to BMI and 50.9% according to % BF, while 38.4% of patients had very high VF levels. After adjusting odds ratio values for cofounding variables and obesity-related conditions, all three anthropometric parameters were significant predictors of primary end-points. However, we note that % BF and VF, compared to BMI, were stronger predictors of both mortality (aOR 3.353, aOR 3.05, and aOR 2.387, respectively) and ICU admission [adjusted odds ratio (aOR) 7.141, aOR 3.424, and aOR 3.133, respectively]. Conclusion: Obesity is linked with COVID-19 mortality and ICU admission, with BIA measurements being stronger predictors of outcome compared to BMI use alone.

Cardiorespiratory fitness assessment on active patientswhokept attending their phase III exercise-based cardiac rehabilitation during the COVID-19 era

Background: Cardiorespiratory fitness (CRF) is a powerful predictor of all-cause mortality among individuals with coronary artery disease (CAD). A structured community-based phase III cardiac rehabilitation (CR) is very important in lifelong maintenance of phase II CRF and health gains. During the COVID-19 pandemic, CR programs had to adapt, mainly using new technologies and remote follow-up. The CRF impact in patients (Ps) who kept going their phase III program, during this troubled era is still unknown. Purpose: Assess the variation in CRF and prognostic parameters in Ps with CAD who maintain high adherence levels in their phase III CR before and during the COVID-19 pandemic. Methods: A cohort of Ps enrolled in a community-based phase 3 CR program, with active participation at the end of 2019, was included in this retrospective study. The inclusion criteria for this study were high levels of attendance (>80%) to the CR program before and during COVID-19 and high levels of physical activity with more than 150 mins of moderate to vigorous physical activity (MVPA). All Ps were evaluated with transthoracic echocardiography (TTE) and a cardiorespiratory exercise test (CPET) in a cycloergometer in 2019 and between october and november of 2021. All Ps had used accelerometers to measure their physical activity levels and dual-energy absorptiometry (DEXA) scan to evaluate their body composition. Between 2020 and 2021, Ps had online (in lockdown periods) and face to face exercise training sessions, 3xtimes per week, 60 mins each exercise session. A t-test paired two sample for means was used to compare CPET variables before the beginning of the first COVID lockdown (end of 2019) and after the removal of the majority of restrictions (end of 2021). Results: A total of 30 Ps with high levels of adherence were included (99.6% male, 65 ± 9 years old). In this cohort, the majority had history of an ACS before the referral to the CR program (73.3%) and 55.6 ± 10.4% of left ventricular ejection fraction. There was no significant difference in body mass index (27.9 ± 3.2 kg/m2 vs 28.1 ± 3.6 kg/m2, p=0.493 but there was a significant increase in the percentage of body fat mass (30.1 ± 5.7% vs 31.0 ± 6.6%, p= 0.042). There was a maintenance on MVPA levels (352 ± 137 minutes/week vs 313 ± 194 minutes/week, p = 0.106) during this period. When comparing the 2 CPET results, Ps achieved higher exercise loads in the 2021 test (175 ± 51W vs 185 ± 52W, p=0.005), higher VO2 peak (25.3 ± 6.9 ml/kg/min vs 21.5 ± 6.3 ml/kg/min, p =0.001) and higher percentage of predicted VO2max (78.8 ± 16.8% vs 95.27 ± 20.8%, p = 0.001). Conclusion: In spite of all the difficulties in maintaining a phase III CR program during the COVID-19 pandemic, we observed that in physically active CAD Ps, with the aid of new technologies and remote follow-up (during the lockdown periods) and face to face exercise sessions, it is still possible to have functional gains and improvements in CRF. (Figure Presented).

Evaluation of Dietary Management Using Artificial Intelligence and Human Interventions: Nonrandomized Controlled Trial.

BACKGROUND: There has been an increase in personal health records with the increased use of wearable devices and smartphone apps to improve health. Traditional health promotion programs by human professionals have limitations in terms of cost and reach. Due to labor shortages and to save costs, there has been a growing emphasis in the medical field on building health guidance systems using artificial intelligence (AI). AI will replace advanced human tasks to some extent in the future. However, it is difficult to sustain behavioral change through technology alone at present. OBJECTIVE: This study investigates whether AI alone can effectively encourage healthy behaviors or whether human interventions are needed to achieve and sustain health-related behavioral change. We examined the effectiveness of AI and human interventions to encourage dietary management behaviors. In addition, we elucidated the conditions for maximizing the effect of AI on health improvement. We hypothesized that the combination of AI and human interventions will maximize their effectiveness. METHODS: We conducted a 3-month experiment by recruiting participants who were users of a smartphone diet management app. We recruited 102 participants and divided them into 3 groups. Treatment group I received text messages using the standard features of the app (AI-based text message intervention). Treatment group II received video messages from a companion, in addition to the text messages (combined text message and human video message intervention by AI). The control group used the app to keep a dietary record, but no feedback was provided (no intervention). We examine the participants' continuity and the effects on physical indicators. RESULTS: Combined AI and video messaging (treatment group II) led to a lower dropout rate from the program compared to the control group, and the Cox proportional-hazards model estimate showed a hazard ratio (HR) of 0.078, which was statistically significant at the 5% level. Further, human intervention with AI and video messaging significantly reduced the body fat percentage (BFP) of participants after 3 months compared to the control group, and the rate of reduction was greater in the group with more individualized intervention. The AI-based text messages affected the BMI but had no significant effect on the BFP. CONCLUSIONS: This experiment shows that it is challenging to sustain participants' healthy behavior with AI intervention alone. The results also suggest that even if the health information conveyed is the same, the information conveyed by humans and AI is more effective in improving health than the information sent by AI alone. The support received from the companion in the form of video messages may have promoted voluntary health behaviors. It is noteworthy that companions were competent, even though they were nonexperts. This means that person-to-person communication is crucial for health interventions.

Body Fat Percentage and Normal-Weight Obesity in the Chinese Population: Development of a Simple Evaluation Indicator Using Anthropometric Measurements.

Few studies explore the associations between body fat percentage (BFP) prediction and evaluation indicators for Chinese with normal-weight obesity. We aimed to explore convenient and cost-free BFP evaluation indicators to routinely monitor BFP status in Chinese patients with normal-weight obesity. Participants (N = 164) were divided into three groups according to body mass index (BMI) and BFP: normal-weight lean, normal-weight obese, and overweight and obese. Differences in body composition and circumference were compared to examine the relationship between BFP and circumference, determine a simple evaluation indicator reflecting BFP, and identify cutoff values for normal-weight obesity circumference. Significant differences in body composition and circumference were observed among the three groups. The correlation between thigh/height, hip/height, (hip + waist)/height, and BFP was stronger than that with BMI. The (hip + waist)/height ratio was the indicator most reflective of BFP (95% confidence interval: 3.004-9.018, p = 0.013), and a ratio above 1.115 (95% confidence interval: 0.936-0.992, p < 0.001) was predictive of normal-weight obesity. Furthermore, we suggest that the upper value for a normal BMI in Chinese individuals be lowered to 23.4 kg/m2 (95% confidence interval: 0.984-0.999, p < 0.001). The (hip + waist)/height ratio can be used with body mass index for a more accurate evaluations of BFP abnormalities and health risks.

The association between depression and metabolic syndrome components in adolescents with obesity

Background: Obesity has metabolic consequences that were reported to have worsened by the co-existence of depression in adults. This relationship is explained by an overactive stress response and adoption of unhealthy lifestyle habits. The relationship between depression with obesity, its severity, and consequences is concerning, especially after an increase in prevalence of both during COVID-19. No data regarding this association is available for children and adolescents. The purpose of this study is to compare the prevalence of metabolic syndrome (MS) components in youth with obesity who are identified with depression and youth who are obese and are not diagnosed with depression. Methods: A retrospective review of patients with obesity seen at a pediatric weight management clinic between July 1, 2018 and June 30, 2021 was performed. Demographic, anthropometric, clinical and laboratory data, and PHQ-9 depression screening tool scores were ed. Results: Out of 160 patients, only 46% had PHQ9 scores less than 5, which suggested no depression. 42 (26%) had a current/prior diagnosis of depression. Moderate to severe depression (scores >= 10) was found in 25% of patients, including 18% of patients never diagnosed with depression. Scores were higher among those reporting daytime fatigue or trouble sleeping, and among patients that ate out 7 or more times per week compared to those that ate out less frequently. There were statistically significant associations between increasing weight, BMI, body fat percentage, diastolic blood pressure, and fasting blood insulin with higher PHQ9 scores (p < 0.02 for all). Nonsignificant correlations were found between PHQ9 scores and SBP of serum lipids (spearman's r < 30 for all). Conclusions: More than half of the adolescents with obesity had significant depression scores. Adolescents with higher PHQ9 scores had higher measurements of BMI, body fat percentage, diastolic blood pressure, and serum insulin. Screening and management of depression should be an important component of obesity management in adolescents. Further studies are needed to confirm our findings. comorbidity of depression is common in adolescents with obesity and often non-diagnosed.

Performance of Body Mass Index in Identifying Obesity Defined by Body Fat Percentage and Hypertension Among Malaysian Population: A Retrospective Study.

PURPOSE: Body mass index (BMI) is used universally to define obesity. Many studies have indicated that the current BMI cutoff value for obesity may be inaccurate in identifying individuals with excess body fat (BF) and at risk for cardiovascular diseases (CVD). This study aims to assess the performance of BMI in diagnosing obesity defined by BF percentage (BF%). PATIENTS AND METHODS: A total of 136 participants who attended an annual health screening programme were recruited. The subjects completed the health examinations, including BMI, BF% and blood pressure measurement. A receiver operating curve (ROC) analysis was conducted to determine the optimal cutoff value of BMI in classifying obesity based on BF% (>25%). RESULTS: The ROC analysis revealed that the optimal BMI cutoff value in classifying subjects with obesity based on BF% was 24.8 kg/m2. The agreement between the classification scheme based on the new BMI cutoff (>24.8 kg/m2) and BF% was higher (κ=0.722) compared to the standard BMI cutoff (>27.5 kg/m2) (κ=0.532). BMI 24.8 kg/m2 also had higher sensitivity (80.0%) than 27.5 kg/m2 (56.0%) in detecting subjects with high adiposity. The new BMI cutoff also showed a sensitivity of 63.9% in identifying subjects with hypertension compared to the standard cutoff (36.1%). CONCLUSION: The current definition of obesity based on BMI value needs to be reassessed by taking BF% into account. A new BMI cutoff point, 24.8 kg/m2 for obesity, can identify a higher percentage of Malaysian at risk for CVD.

A Multidomain Approach to Assessing the Convergent and Concurrent Validity of a Mobile Application When Compared to Conventional Methods of Determining Body Composition.

Determining body composition via mobile application may circumvent limitations of conventional methods. However, the accuracy of many technologies remains unknown. This investigation assessed the convergent and concurrent validity of a mobile application (LS) that employs 2-dimensional digital photography (LS2D) and 3-dimensional photonic scanning (LS3D). Measures of body composition including circumferences, waist-to-hip ratio (WHR), and body fat percentage (BF%) were obtained from 240 healthy adults using LS and a diverse set of conventional methods-Gulick tape, bioelectrical impedance analysis (BIA), and skinfolds. Convergent validity was consistently high-indicating these methods vary proportionally and can thus reliably detect changes despite individual measurement differences. The span of the Limits of Agreement (LoA) using LS were comparable to the LoA between conventional methods. LS3D exhibited high agreement relative to Gulick tape in the measurement of WHR, despite poor agreement with individual waist and hip circumferences. In BF%, LS2D exhibited high agreement with BIA and skinfold methods, whereas LS3D demonstrated low agreement. Interestingly, the low inferred bias between LS3D and DXA using existing data suggests that LS3D may have high agreement with dual-energy x-ray absorptiometry. Overall, the suitability of LS2D and LS3D to replace conventional methods must be based on an individual user's criteria.

The impact of vitamin D supplementation on body fat mass in elite male collegiate athletes.

BACKGROUND: Whether vitamin D supplementation has any effect on body fat percentage, especially among elite athletes, remains unclear. The aim of this study was to evaluate the effect of vitamin D supplementation on serum vitamin D level in elite male collegiate athletes and to analyze its effect on body fat percentage. METHODS: We enrolled a total of 42 elite male collegiate athletes in this prospective cohort study. In March 2020, body composition monitoring and blood test were performed. All athletes were provided with vitamin D3 supplement tablets of 25 µg/day. The use of the supplement was dependent on athletes' preference. During the study period, their club activities were stopped for 2 months due to the coronavirus disease 2019 outbreak. A second examination, similar to the first one, was performed after approximately 3 months. Supplement usage by each athlete was also confirmed. The participants were divided into a non-supplement group (without supplementation, n = 15) and a supplement group (with supplementation, n = 27). RESULTS: Regarding baseline data at initial examination, the non-supplement and supplement groups showed significant differences in the mean body fat percentage (9.0% and 12.1%, respectively; P = 0.03) and serum 25(OH)D level (22.7 and 18.5 ng/mL, respectively, P = 0.02). At the time of the second examination, there were no significant differences in the results of both the groups. In terms of mean change value from the first to the second examination, there were significant differences in body fat percentage (1.9 and 0.2%, respectively, P = 0.02) and serum 25(OH)D level (1.7 and 7.2 ng/mL, respectively, P < 0.001) between the two groups. A significant negative correlation was observed between the change ratio of body fat percentage and change value of serum 25(OH)D level (r = - 0.37, P = 0.02). CONCLUSIONS: Vitamin D supplementation of 25 µg/day significantly increased the serum 25(OH)D level in elite male collegiate athletes. Vitamin D supplementation may play a role in maintaining athletes' body fat percentage under circumstances where sports activity has decreased.

Comparison of Bioelectrical Impedance-Based Methods on Body Composition in Young Patients with Obesity.

(1) Background: The determination of body composition is an important method to investigate patients with obesity and to evaluate the efficacy of individualized medical interventions. Bioelectrical impedance-based methods are non-invasive and widely applied but need to be validated for their use in young patients with obesity. (2) Methods: We compiled data from three independent studies on children and adolescents with obesity, measuring body composition with two bioelectrical impedance-based devices (TANITA and BIACORPUS). For a small patient group, additional data were collected with air displacement plethysmography (BOD POD) and dual-energy X-ray absorptiometry (DXA). (3) Results: Our combined data on 123 patients (age: 6-18 years, body mass index (BMI): 21-59 kg/m²) and the individual studies showed that TANITA and BIACORPUS yield significantly different results on body composition, TANITA overestimating body fat percentage and fat mass relative to BIACORPUS and underestimating fat-free mass (p < 0.001 for all three parameters). A Bland-Altman plot indicated little agreement between methods, which produce clinically relevant differences for all three parameters. We detected gender-specific differences with both methods, with body fat percentage being lower (p < 0.01) and fat-free mass higher (p < 0.001) in males than females. (4) Conclusions: Both bioelectrical impedance-based methods provide significantly different results on body composition in young patients with obesity and thus cannot be used interchangeably, requiring adherence to a specific device for repetitive measurements to ascertain comparability of data.