Background. A high body mass index (BMI) is associated with several cardiovascular diseases, diabetes and chronic kidney disease, cancers, and other selected health conditions.
Objectives. To ...quantify the deaths and disability-adjusted life years (DALYs) attributed to high BMI in persons aged ≥20 years in South Africa (SA) for 2000, 2006 and 2012.
Methods. The comparative risk assessment (CRA) methodology was followed. Meta-regressions of the BMI mean and standard deviation from nine national surveys spanning 1998 - 2017 were conducted to provide estimates by age and sex for adults aged ≥20 years. Population attributable fractions were calculated for selected health outcomes using relative risks identified by the Global Burden of Disease Study (2017), and applied to deaths and DALY estimates from the second South African National Burden of Disease Study to estimate the burden attributed to high BMI in a customised Microsoft Excel workbook. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. BMI was assumed to follow a log-normal distribution, and the theoretical minimum value of BMI below which no risk was estimated was assumed to follow a uniform distribution from 20 kg/m2 to 25 kg/m2.
Results. Between 2000 and 2012, mean BMI increased by 6% from 27.7 kg/m2 (95% confidence interval (CI) 27.6 - 27.9) to 29.4 kg/m2 (95% CI 29.3 - 29.5) for females, and by 3% from 23.9 kg/m2 (95% CI 23.7 - 24.1) to 24.6 kg/m2 (95% CI 24.5 - 24.8) for males. In 2012, high BMI caused 58 757 deaths (95% uncertainty interval (UI) 46 740 - 67 590) or 11.1% (95% UI 8.8 - 12.8) of all deaths, and 1.42 million DALYs (95% UI 1.15 - 1.61) or 6.9% (95% UI 5.6 - 7.8) of all DALYs. Over the study period, the burden in females was ~1.5 - 1.8 times higher than that in males. Type 2 diabetes mellitus became the leading cause of death attributable to high BMI in 2012 (n=12 382 deaths), followed by hypertensive heart disease (n=12 146), haemorrhagic stroke (n=9 141), ischaemic heart disease (n=7 499) and ischaemic stroke (n=4 044). The age-standardised attributable DALY rate per 100 000 population for males increased by 6.6% from 3 777 (95% UI 2 639 - 4 869) in 2000 to 4 026 (95% UI 2 831 - 5 115) in 2012, while it increased by 7.8% for females from 6 042 (95% UI 5 064 - 6 702) to 6 513 (95% UI 5 597 - 7 033).
Conclusion. Average BMI increased between 2000 and 2012 and accounted for a growing proportion of total deaths and DALYs. There is a need to develop, implement and evaluate comprehensive interventions to achieve lasting change in the determinants and impact of overweight and obesity, particularly among women.
Obesity and overweight have become increasingly prevalent in developing countries like China. This paper explores the evolvement of body mass index (BMI) of the Chinese population using a nationally ...representative sample. Focusing on familial transmission of BMI, we model married couple's BMI jointly and explore how parents' BMI affect children's BMI. In particular, we use spousal and parental characteristics as proxy variables to account for potential omitted variables bias and explicitly model common couple effect with the correlated random-effects model for couple' BMI. Our analysis suggests strong and positive spousal dependence and intergenerational transmissions of BMI in Chinese families. The influences of spousal BMI, parental BMI and a variety of social economic characteristics are found to depend on gender, region of residence (urban versus rural) and evolve over time. We find positive effects of spousal BMI that are significant, asymmetric (greater for wife than for husband), and generally vary across regions. For grown children, we find parental BMI to be the most important predictors for children's BMI. Since families can play an essential role in preventing obesity, our results can be useful for developing health intervention programs and promoting healthy lifestyle.
The occurrence of in-hospital seizures for aneurysmal subarachnoid hemorrhage (aSAH) ranges from 3.7% to 15.2%, and seizures remain an important factor affecting patient prognosis. Therefore, the ...timely identification of patients at a higher risk for aSAH-associated seizures after endovascular treatment is of paramount importance. This study aims to analyze the risk factors for in-hospital seizures after endovascular treatment for aSAH.
The study comprised 547 patients at 3 centers from January 2019 to September 2021. In the context of this study, 2 models were utilized: the first model involved no variable adjustment, while the second model included all potential confounders in the multivariate logistic regression analysis. Additionally, the dose-response relationship between biomarkers and seizure occurrence was assessed using restricted cubic spline.
Among these patients, 28 (5.1%) developed seizures during hospitalization. In Model 2, the modified Fisher score (adjusted odds ratio OR: 3.138, 95% confidence interval CI: 1.226–8.036), body mass index (adjusted OR: 0.852, 95% CI: 0.749–0.970), aspect ratio (adjusted OR: 0.264, 95% CI: 0.115–0.604), and aspartate transaminase (adjusted OR: 1.017, 95% CI: 1.001–1.035) were showed as factors contributing to an increased risk of aSAH-associated seizures.
Body mass index, aspartate transaminase, aspect ratio, modified Fisher scores, and Hunt-Hess scores were correlated with the formation of aSAH-associated seizures after endovascular treatment.
Background
Approximately one third of thromboembolic (TE) events are related to obesity, but to which extent elevated body mass index (BMI) during the distinct periods of childhood and puberty ...contributes is not known. We aimed to evaluate the impact of high BMI during childhood and puberty for the risk of adult venous and arterial thromboembolic events (VTE, ATE, respectively) in men.
Methods
We included 37,672 men from the BMI Epidemiology Study (BEST) Gothenburg with data on weight and height in childhood, young adult age, and on pubertal BMI change. Information on outcomes (VTE n = 1683, ATE n = 144, or any first TE event VTE or ATE; n = 1780) was retrieved from Swedish national registers. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated by Cox regressions.
Results
Both BMI at 8 years of age and the pubertal BMI change were associated with VTE, independently of each other (BMI at 8: HR 1.06 per standard deviation SD increase, 95% CI, 1.01;1.11; pubertal BMI change: HR 1.11 per SD increase, 95% CI, 1.06;1.16). Individuals with normal weight during childhood followed by young adult overweight (HR 1.40, 95% CI, 1.15;1.72), and individuals with overweight at both childhood and young adult age (HR 1.48, 95% CI, 1.14;1.92), had a significantly increased risk of VTE in adult life, compared with the normal weight reference group. Individuals with overweight in childhood and in young adult age had increased risk of ATE and TE.
Conclusion
Young adult overweight was a strong determinant, and childhood overweight a moderate determinant, of the risk of VTE in adult men.
•Observational cohort study including 5115 participants over 30 years.•Current cannabis was associated with lower BMI, probably due to residual confounding.•Cannabis cessation or cumulative cannabis ...exposure were not associated with BMI.
With increasing use of cannabis, we need to know if cannabis use and Body Mass Index (BMI) are associated.
The Coronary Artery Risk Development in Young Adults Study followed Black and White adults over 30 years with assessments every 2 to 5 years in four centers in the USA. We assessed self-reported current and computed cumulative cannabis exposure at every visit, and studied associations with BMI, adjusted for relevant covariables in mixed longitudinal models. We also applied marginal structural models (MSM) accounting for the probability of having stopped cannabis over the last 5 years.
At the Year 30 visit, 1,912 (58 %) identified as women and 1,600 (48 %) as Black, mean age was 56 (SD 2) years. While 2,849 (85 %) had ever used cannabis, 479 (14 %) currently used cannabis. Overall, participants contributed to 35,882 individual visits over 30 years. In multivariable adjusted models, mean BMI was significantly lower in daily cannabis users (26.6 kg/m2, 95 %CI 26.3 to 27.0) than in participants without current use (27.7 kg/m2, 95 %CI 27.5 to 27.9, p < 0.001). Cumulative cannabis use was not associated with BMI. The MSM showed no change in BMI when stopping cannabis use over a 5-year period (β=0.2 kg/m2 total, 95 %CI -0.2 to 0.6).
Current cannabis use was associated with lower BMI, but cumulative cannabis use and cessation were not. This suggests that recreational cannabis use may not lead to clinically relevant changes in BMI and that the association between current cannabis use and lower BMI is likely due to residual confounding.
The epidemiology of obesity Chooi, Yu Chung; Ding, Cherlyn; Magkos, Faidon
Metabolism, clinical and experimental,
March 2019, 2019-Mar, 2019-03-00, 20190301, Letnik:
92
Journal Article
Recenzirano
Obesity is a complex multifactorial disease. The worldwide prevalence of overweight and obesity has doubled since 1980 to an extent that nearly a third of the world's population is now classified as ...overweight or obese. Obesity rates have increased in all ages and both sexes irrespective of geographical locality, ethnicity or socioeconomic status, although the prevalence of obesity is generally greater in older persons and women. This trend was similar across regions and countries, although absolute prevalence rates of overweight and obesity varied widely. For some developed countries, the prevalence rates of obesity seem to have levelled off during the past few years. Body mass index (BMI) is typically used to define overweight and obesity in epidemiological studies. However, BMI has low sensitivity and there is a large inter-individual variability in the percent body fat for any given BMI value, partly attributed to age, sex, and ethnicity. For instance, Asians have greater percent body fat than Caucasians for the same BMI. Greater cardiometabolic risk has also been associated with the localization of excess fat in the visceral adipose tissue and ectopic depots (such as muscle and liver), as well as in cases of increased fat to lean mass ratio (e.g. metabolically-obese normal-weight). These data suggest that obesity may be far more common and requires more urgent attention than what large epidemiological studies suggest. Simply relying on BMI to assess its prevalence could hinder future interventions aimed at obesity prevention and control.
Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to control external devices. This paper presents the decoding of intuitive upper extremity imagery for ...multi-directional arm reaching tasks in three-dimensional (3D) environments. We designed and implemented an experimental environment in which electroencephalogram (EEG) signals can be acquired for movement execution and imagery. Fifteen subjects participated in our experiments. We proposed a multi-directional convolution neural network-bidirectional long short-term memory network (MDCBN)-based deep learning framework. The decoding performances for six directions in 3D space were measured by the correlation coefficient (CC) and the normalized root mean square error (NRMSE) between predicted and baseline velocity profiles. The grand-averaged CCs of multi-direction were 0.47 and 0.45 for the execution and imagery sessions, respectively, across all subjects. The NRMSE values were below 0.2 for both sessions. Furthermore, in this study, the proposed MDCBN was evaluated by two online experiments for real-time robotic arm control, and the grand-averaged success rates were approximately 0.60 (±0.14) and 0.43 (±0.09), respectively. Hence, we demonstrate the feasibility of intuitive robotic arm control based on EEG signals for real-world environments.
Previous studies have demonstrated an association between BMI and the development of sarcoidosis. We investigated this association and the association between OSA and the development of sarcoidosis ...in a US Veterans Health Administration database.
Is the presence of OSA or the BMI associated with the development of sarcoidosis over the subsequent 12 months?
We identified patients with sarcoidosis and OSA through International Classification of Diseases, Ninth and Tenth Revision, codes. We selected a random sample of control participants with no record of sarcoidosis. All patients with sarcoidosis had at least one BMI value recorded in the 12 months before the sarcoidosis diagnosis was made. For the patients without sarcoidosis, the BMI values were obtained over intervals 12 months before a random date. We compared the BMI and the percentage of patients with OSA in the sarcoidosis group and in patients without sarcoidosis.
We analyzed 10,512 patients with sarcoidosis and 2,709,884 patients without sarcoidosis. We found no association between BMI and the rate of sarcoidosis developing. Post hoc statistical power calculations verified that these null results were meaningful and not the result of insufficient statistical power. We also found that a diagnosis of OSA was protective of sarcoidosis developing. Using a conditional logistic regression model with strata for age, sex, and BMI in the same 12-month period, a 49.0% lower odds of sarcoidosis was found in patients with OSA compared with patients without a diagnosis of OSA. Although the primary outcomes were assessed at 12 months before the diagnosis of sarcoidosis, these results basically held when examined at 3 and 6 months before the diagnosis was made.
These findings suggest that increased BMI is not associated positively with a greater odds of sarcoidosis developing. Furthermore, these results suggest that the presence of OSA lowers the odds of sarcoidosis developing.
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Background: Hemorrhoids is a common anorectal condition affecting a vast majority of population all around the world. The establishment of a definite association of hemorrhoids with bowel habits and ...other factors like BMI is less explored. Objectives: To find out the association of hemorrhoids especially with bowel habits and to establish the association of BMI with respect to the onset of hemorrhoids. Methodology: This case control study was conducted among 90 cases and controls from the hospitals affiliated to Kasturba Medical college, Mangalore. Data were analyzed using SPSS version 29. Uni-variate analysis was done, and the odds ratio and confidence levels were tested and determined using binary logistic regression. Results: Majority of the controls were normal with respect to BMI categorization (36.8%) whereas 34.9% of the cases were obese (p=0.095) . The number of people who consumed mixed diet was greater in the cases (72.3%) than in the controls (64.4%). 61.5% of patients complained of blood in stools compared to 2.2% of controls, there were 10.5% of cases with pus in stools and none in controls (p=0.249). Use of laxatives was seen in 27.7% of cases and only 2.1% of controls (p=0.001). A total score of >=15 was indicative of constipation. 12.8% showed constipation compared to none in the controls. (p=0.026). Conclusion: Association of constipation with hemorrhoids was statistically significant. The occurrence of hemorrhoids was not associated with the body mass index of the individual and the occurrence of diarrhea was not significant with respect to hemorrhoids.