Background: Increases in population waist circumference (WC) are happening at a different speed than body mass index (BMI). Assessing recent trends in WC and BMI gives us a better glimpse of how fat ...distribution has varied in and across populations and allows a better prediction of obesity associated-diseases. We investigated the changes in WC relative to BMI in five countries and assessed whether any secular changes in mean WC occurred independently of BMI. Methods: We used adult data from 1997 to 2020 from the US, England, Chile, Mexico and Peru nationally representative surveys. Sex-specific country-stratified (for the US, also race-/ethnicity) regressions were used to estimate the annual change in mean WC relative to BMI level, adjusting for age and survey year. We also tested interactions between BMI and survey year. Results: We observed increases in predicted mean WC for a given BMI level across countries except for Peru and USA-Non-Hispanic Black and USA-Mexican American populations. Overall results showed that mean WC among females increased more than males. Among females, mean WC increased more over time only at higher levels of BMI. The largest annual increase in WC was found in USA-Non-Hispanic White females (0.27cm/year, 95% CI 0.18, 0.36) with the largest reduction observed for Peru females (-0.27cm/year, 95% CI -0.46, -0.07) at BMI 35kg/m2. In contrast, males showed a more stable annual change in WC independently of BMI. Only significant increases were observed for Mexico and England males with the higher annual mean change observed for Mexico males at a BMI of 35 kg/m2 (0.14cm/year, 95% CI 0.08, 0.20). The largest reduction in WC was observed for Peru males (-0.47cm/year, 95% CI -0.76, -0.17) at that same BMI level. Conclusions: Over the last two decades, we observed across countries that secular increases in mean WC have been larger in females than males. These changes have largely occurred independently of the level of BMI. These differences bring a significant increase in disparities in abdominal obesity-associated diseases.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Introduction Body image distortion and/or dissatisfaction may occur primarily due to body fat accumulation and/or distribution. The aim of this study was to evaluate the frequency of body image ...perception and (dis)satisfaction categories in adult men and women according to the adiposity classification. Methods This is a cross-sectional study (n = 514; 33-79 years; 265 women) that is part of a prospective cohort (Pró-Saúde study). Adiposity measurements were determined by two methods: anthropometry, used to calculate the body mass index (BMI) and dual-energy X-ray absorptiometry (DXA), to estimate body fat percentage. Participants were grouped as "no excess adiposity" and "excess adiposity", considering BMI and body fat percentage (>30% for men, >40% for women). Perception and (dis)satisfaction with body image were evaluated using the Kakeshita scale, composed by 15 silhouettes, developed for the Brazilian population. Degree of distortion (perceived BMI - real BMI) and dissatisfaction (perceived BMI - desired BMI) were calculated. Results A high proportion of men (58.6%; 74.3%), and especially of women (82.6%; 86.8%), presented body size overestimation and dissatisfaction due to excess weight, respectively. A relevant fraction of the women (32.6%) and men (30.8%) who were dissatisfied due to excess weight did not present excess adiposity, especially if classified by DXA. Variability in degree of distortion was hardly explained by anthropometric and DXA variables in women (<5%) and men (~22%). Both anthropometric and DXA measurements accounted for ~30% and ~50% of the variability in degree of dissatisfaction among women and men, respectively. Conclusion Our results suggest a high frequency of body image distortion in Brazilian adult individuals, as well as dissatisfaction with excess weight, especially among women with excess adiposity. The findings indicate that anthropometric measurements explain much of the variability in degree of body image dissatisfaction in men, with no apparent advantage of the use of more refined DXA measurements.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background: Ultra -processed food (UPF) consumption and physical inactivity are independently associated with weight gain, obesity, and other adverse health outcomes. Health behaviors often cluster ...to- gether, yet it is unclear if UPF consumption is associated with usual physical activity (PA) patterns. The objective was to evaluate whether or not UPF consumption (% energy) differed between sedentary and active adults. Methods: This cross-sectional study included 40 adults (73% female, aged 39 ± 15 years, body mass index (BMI) 25.8 ± 4.9 kg/m2). PA was assessed using the Stanford Leisure Time Activity Categorical Item (L-Cat) and categorized as sedentary (L-Cat 1-2), low activity (L- Cat 3), or meeting PA guidelines (>150 min/wk; L-Cat 4-6). Dietary intake was assessed using three 24-hour recalls, and UPF consump- tion (% energy) was determined independently by two researchers using the NOVA classification system. Analyses included indepen- dent samples t-test and one-way AN OVA. Results: Mean UPF consumption was 53 ± 21% of total energy. UPF consumption was lower in participants who met PA guidelines (n = 18) compared to sedentary participants (n = 11) (47 ± 20% vs 64 ± 17% UPF, respectively, P = 0.03). Energy intake was not differ- ent between those who met PA guidelines (1879 ± 438 kcal) and sedentary individuals (1918 ± 512 kcal) (p = 0.83). However, BMI was lower in those who met PA guidelines compared with those who were sedentary (24 ± 4 vs 28 ± 5 kg/m2, respectively, P = 0.04). Individuals with a low level of PA that did not meet PA guidelines (n = 11) consumed 52 ± 23% energy from UPF, which was not different from sedentary or active individuals (p = 0.10). Conclusions: Meeting PA guidelines is associated with a lower UPF consumption and a lower BMI. In addition to a hypocaloric diet, interventions could investigate whether or not reducing UPF consumption and increasing PA is effective for weight reduction and improvements in other health outcomes.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background: Body surface area (BSA) has application for calculation of clinical indices (liver volume, cardiac index), diagnostic (radio contrast) and therapeutic dosing (steroids, growth hormone, ...fluids) in children. BSA estimates are derived using height and weight-based prediction equations. The Mosteller equation is most commonly used in children and was developed in a dataset (Boyd, published 1935) that included adults and children with a body mass index (BMI) lower than the BMI of current populations. A 3-dimensional photonic scanner (3DPS) (C9036-02, Hamamatsu Photonics K.K., Japan) that uses four high resolution cameras can provide whole body and regional BSA measures in children. This study aimed to compare BSA3DPS with BSAMosteller.with the hypothesis that the results will differ given that the 3DPS is digitally estimating the body's surface. Methods: BSA3DPS was obtained in 38 children (19 males) aged 3-17 years (Mean 10.4 years, SD 3.5), mean BMI z score males 0.67(1.06); females 0.68(1.35) and varied race (White 39%, African American 13%, Asian 5%, Mixed 5% and other) and ethnicities (Hispanic = 20). BSAMosteller (meter2) was estimated using the Mosteller equation {square root of Height in centimeters)· weight in kilograms)/3600}. Pearson correlation analysis and paired T- test were performed. Results: BSA3DPS and BSAMosteller did not differ (p = 0.27). Results were highly correlated (r = 0.997). Subset analysis in children with obesity (n = 9) showed similarly strong correlation (r = 0.994). Conclusions: Mosteller equation developed in a population of children and adults with lower mean BMI than the current population from past decades, produced BSA results that did not differ to a modern 3DPS surface scanning approach. Further studies are required to confirm these findings in a larger cohort, including individuals with obesity and varying in body shape.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
IntroductionDefibrillation testing (DT) is recommended during the subcutaneous defibrillator (S‐ICD) placement. We sought to compare 10 J shock impedance in sinus rhythm (SR) with 65 J defibrillation ...impedance and evaluate device position on a postimplant chest X‐ray (CXR) using an intermuscular (IM) technique.MethodsConsecutive S‐ICD implantations between 12/2019 and 12/2020 at The Ohio State University were reviewed. All implantations were performed using a two‐incision IM technique. Standard DT with 65 J shock and 10 J shock in SR were performed unless contraindicated. The PRAETORIAN score was calculated based on CXR.ResultsA total of 37 patients (age: 47.2 ± 15.8 years old, male: n = 26 70.3%, body mass index: 30.1 ± 6.7 kg/m2) underwent IM S‐ICD implantation, and of those, 27 (73%) underwent both 65 J shock and 10 J shock in SR. The coefficient of determination (R2) between 10 J shock impedance and 65 J shock impedance was 0.84. The mean of an impedance difference was 1.6 ± 4.8 Ω (minimum – 11 and maximum 8). Postimplant CXR was available for 33 out of 37 patients (89.2%). The PRAETORIAN score was less than 90 in all patients and the mean score was 32.7 ± 8.8.ConclusionWe demonstrated that 10 J shock impedance in SR correlated well with 65 J defibrillation impedance during IM S‐ICD implantation. An IM implantation technique provides excellent generator location on postimplant CXR. The IM technique combined with 10 J shock in SR may be sufficient to predict and ensure the defibrillation efficacy of the S‐ICD.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Multivariable regression analyses were performed adjusting for demographics, hospital-level characteristics, and relevant comorbidities. Multivariate analysis demonstrated that patients in category ...IV had a significantly higher odds of mortality compared to other BMI subgroups (OR = 1.16, 95% CI: 1.07-1.29, P-value < 0.00). The relationship between extremely low or high BMI values and CDI mortality that has been observed emphasizes the significance of taking BMI into account as a risk factor and potential prognostic indicator in CDI management.
Weigh More, Lose Less Bone Tai, Brurya; Shefer, Gabi; Sack, Jessica ...
Obesity (Silver Spring, Md.),
11/2023, Volume:
31
Journal Article
Peer reviewed
Background: Several reports indicated that intentional weight loss can result in reduction in bone mineral density (BMD), particularly in postmenopausal women, and older individuals. This is a ...post-hoc analysis of a prospective multidisciplinary weight loss trial, in search of predictors of bone loss in the Metabolic Syndrome (MS). Methods: 73 MS subjects (ATPIII criteria; F/M = 34/39) participated in a 1-year intensive multidisciplinary treatment, based on personalized physical training and a low calorie/high protein Mediterranean diet. Baseline (±SD): age 53.3 ± 11.2 years; weight 98.6 kg ± 16.8; BMI 34.4 ± 3.8 kg/m2; lean body mass (LBM) 55.48 kg ± 11.66 kg; Spine BMD 1.21 ± 016 g/cm2, femur neck BMD 0.99 ± 0.13 g/cm2. Results: By the end of 1-year BMI declined by 9.1% (p < 0.001); LBM declined by 2.68% (p < 0.001). There were no significant overall changes in spine or femur BMD; no difference in the change in BMD between participants under the age of 50 years or above 51 years, and between male and female subjects. Despite the lack of overall change in BMD during weight loss, when individual changes in spinal BMD were analyzed, participants who clustered above the median post-treatment versus pre-treatment BMD level, showed a higher initial BMI compared to participants whose change in spinal BMD was below the median level (BMI 35.6 ± 3.6 vs. 32.5 ± 3.52 kg/m2, respectively (p < 0.0001). Conclusions: In subjects with MS undergoing intensive and closely supervised multidisciplinary intentional 1 year weight loss program, higher initial weight is associated with lesser spine bone loss.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
