Increase In Between Body Mass Index Research Articles

Do Body Mass Index and Nutritional Risk Score 2002 Influence the In-Hospital Mortality of Patients Following Cardiac Arrest?

Contemporarily, cardiac arrest (CA) remains one of the leading causes of death. Poor nutritional status can increase the post-CA mortality risk. The aim of this study was to determine the relationship between body mass index (BMI) and Nutritional Risk Score 2002 (NRS 2002) results and in-hospital mortality in patients admitted to the intensive care unit (ICU) after in-hospital and out-of-hospital cardiac arrest. A retrospective study and analysis of medical records of 161 patients admitted to the ICU of the University Clinical Hospital in Wrocław (Wrocław, Poland) was conducted. No significant differences in body mass index (BMI) and nutritional risk score (NRS 2002) values were observed between non-survivors and survivors. Non-survivors had significantly lower albumin concentration (p = 0.017) and total cholesterol (TC) (p = 0.015). In multivariate analysis BMI and NRS 2002 scores were not, per se, associated with the in-hospital mortality defined as the odds of death (Model 1: p: 0.700, 0.430; Model 2: p: 0.576, 0.599). Univariate analysis revealed significant associations between the hazard ratio (HR) and TG (p ≈ 0.017, HR: 0.23) and hsCRP (p ≈ 0.018, HR: 0.34). In multivariate analysis, mortality risk over time was influenced by higher scores in parameters such as BMI (HR = 0.164; p = 0.048) and hsCRP (HR = 1.006, p = 0.002). BMI and NRS 2002, on their own (unconditionally - in the whole study group) did not alter the odds of mortality in patients admitted to the intensive care unit (ICU) after in-hospital and out-of-hospital cardiac arrest. The risk of in-hospital mortality (expressed as hazard ratio - the risk over the time period of the study) increased with an increase in BMI but not with NRS 2002.

BMI and TLC increase Neoadjuvant Chemotherapy Response in Patients with Locally Advanced Breast Cancer

Anthracycline-based neoadjuvant chemotherapy is the recommended therapy for locally advanced breast cancer (LABC) patients. Unfortunately, no study has reported the relationship between body mass index (BMI), total lymphocyte count (TLC), and responses to this type of chemotherapy. This study aimed to determine the relationship between BMI, TLC, and response to doxorubicin/epirubicin neoadjuvant chemotherapy in LABC patients. A retrospective cohort design was applied to medical records of LABC patients undergoing neoadjuvant chemotherapy at Ulin General Hospital Banjarmasin, Indonesia, from July to December 2021. BMI and TLC data were assessed based on the values before chemotherapy, while the chemotherapy response was measured using the RECIST 1.1 criteria after 3 cycles. Multinomial logistic regression test with 95% confidence level was used to analyze these data. The results showed that as many as 71% of patients experienced a Partial Response (PR), while 5% and 23% of the patients demonstrated Stable Disease (SD) and Progressive Disease (PD), respectively. Each increase in BMI of 1 kg/m2 was significantly associated with an increase in the occurrence of PR and PD by 1.26 times and 1.29 times, respectively, when compared to the occurrence of PD. Meanwhile, an increase in TLC of 100 cells/mm3 was associated with an increase in the occurrence of PR by 6.83 times and an increase in the occurrence of SD. of 6.94 when compared to the occurrence of PD. Therefore, there is a significant relationship between BMI, TLC, and response to anthracycline-based neoadjuvant chemotherapy in LABC patients

Relationship between body mass index and spinal pathology in community-dwelling older adults.

To clarify the relationship between body mass index (BMI) and spinal pathologies including spinal sagittal balance, back extensor strength (BES), paraspinal muscle mass, prevalent vertebral fracture, disc degeneration, Modic changes, low back pain, and quality of life (QOL) in community-dwelling older adults. This study included 380 participants (age: ≥ 65years, male/female: 152/228) from the Shiraniwa Study. Multivariate nonlinear regression analysis was used to investigate the relationship between BMI and sagittal vertical axis (SVA), BES, paraspinal muscle mass, visual analog scale (VAS) for low back pain, Oswestry Disability Index (ODI), and EuroQoL-5 Dimension (EQ5D) score after adjusting for sex, age, Hospital Anxiety and Depression Scale score, and Charlson Comorbidity Index. In addition, multiple logistic regression analysis was used to investigate the association between BMI and prevalent vertebral fracture, disc degeneration, and Modic changes. BMI was significantly correlated with SVA, BES, paraspinal muscle mass, VAS, ODI, and EQ5D score. The increase in BMI was associated with the deterioration of all outcomes, which accelerated when the BMI increased from approximately 22-23kg/m2. Moreover, overweight/obesity was significantly correlated with disc degeneration and Modic changes. Increased BMI is significantly associated with spinal pathologies such as SVA, BES, paraspinal muscle mass, VAS, QOL, disc degeneration, and Modic changes. The findings suggest that measures for controlling overweight and obesity among older adults can play an important role in the prevention and treatment of spinal pathologies.

Correlation between Body Mass Index and Cognitive Function in Patients with Atrial Fibrillation.

Evidence regarding the relationship between body mass index (BMI) and cognitive function was limited. Therefore, the objective of this research is to investigate whether BMI is independently related to cognitive function in Chinese patients with atrial fibrillation after adjusting for other covariates. The present study is a cross-sectional study. A total of 281 patients with atrial fibrillation who were hospitalized at the Affiliated Hospital of Jining Medical University in Shandong Province from January 2021 to November 2021 were included in the study. The target independent variable and the dependent variable were BMI and cognitive function in patients with atrial fibrillation, respectively. The patients' general information, BMI, past history, medication history, and other disease-related data were collected. The Montreal cognitive assessment scale (MoCA) was used to evaluate cognitive function. A total of 244 patients with atrial fibrillation were collected in this study, with an average age of (67.28 ± 10.33) years, of whom 55.3% were male. The average BMI was (25.33 ± 4.27) kg/m2, and the average cognitive function score was (19.25 ± 6.88) points. The results of the smooth curve fitting and threshold effect tests showed that there was a curve correlation between BMI and cognitive function score, and its inflection point was 24.56 kg/m2. To the left of the inflection point, the relationship was significant; the effect size and the confidence interval were 0.43 and 0.01-0.85, respectively. To the right of the inflection point, there was no significant correlation between BMI and cognitive function (P=0.152). When BMI is lower than 24.56 kg/m2, the cognitive function score increases by 0.43 points for each unit increase in BMI in patients with atrial fibrillation. An increase in BMI at this time is a protective factor for cognitive function. Within the normal range of BMI, the higher the BMI in atrial fibrillation patients, the higher the cognitive function score. We encourage atrial fibrillation patients with normal BMI to maintain their current weight.

Association Between Body Mass Index and 30-Day Mortality in Patients with Pulmonary Hypertension Undergoing Non-cardiothoracic, Non-obstetric Surgery.

Evidence regarding the association between body mass index (BMI) and outcomes in non-cardiothoracic, non-obstetric surgery patients with pulmonary hypertension (PHTN) is limited. We aimed to investigate the association between BMI and 30-day mortality in non-cardiothoracic, non-obstetric surgery patients with pulmonary hypertension. We performed a secondary analysis of non-cardiothoracic, non-obstetric procedures on patients with PHTN between 2007 and 2013 at a single institution. Multivariable logistic regression models were used to estimate the association between BMI and 30-day mortality. Interaction and stratified analyses were conducted according to age, sex, PHTN medical therapy, anticipated inpatient or outpatient post-procedure status, procedure length > 2h, open surgical approach, and PHTN severity class. A total of 513 participants were included, with men accounting for 55.8% of the sample; the 30-day mortality was 1.9%. In the multivariate regression models, BMI was significantly associated with 30-day mortality after adjusting for potential covariates. A 1kg/m2 increase in BMI was associated with a 15% decrease in 30-day mortality (adjusted OR = 0.85, 95% CI: 0.73-0.98, P = 0.03). Stratified analyses indicated that this negative correlation was robust. In this study, we found that low BMI is associated with increased risk of death in patients undergoing non-cardiothoracic, non-obstetric surgery requiring general anesthesia. Further studies are needed to confirm our findings.

Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches

BackgroundTraditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association.AimsWe studied the causal association between BMI and lung cancer incidence using observational and MR approaches.MethodsWe followed up 62,453 cancer-free Norwegian adults from 1995–97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0–29.9 and ≥ 30.0 kg/m2. BMI change over ten years between HUNT1 (1984–86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking.ResultsDuring a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58–0.92) for BMI 25.0–29.9 kg/m2 and 0.53 (0.37–0.76) for BMI ≥ 30 kg/m2 compared with BMI < 25.0 kg/m2 in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose–response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m2 increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02–1.53). No associations were found with other lung cancer histologic types.ConclusionsOur study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma.

Body mass index and pancreatic adenocarcinoma: A nationwide registry-based cohort study.

An association between body mass index (BMI) and pancreatic cancer is suggested in observational studies. However, further studies are required to substantiate available evidence. The aim of this study was to explore the association between BMI and pancreatic ductal adenocarcinoma (PDAC) risk, treatment, and mortality. A registry-based cohort study was performed by combining data from four registries in Norway. Baseline data were collected between 1963 and 1975 with follow-up data collected until 2018. Kaplan-Meier curves and multivariable Cox regressions were estimated. Chi-square tests were used to analyze differences between groups. The study cohort consisted of 1,723,692 individuals. A total of 8973 PDAC cases were identified during 55,744,749 person-years of follow-up. A 5 kg/m2 increase in BMI was associated with an increased risk of PDAC if high BMI at young age (16-29 years) (hazard ratio (HR): 1.21, 95% confidence interval (CI): 1.13-1.31), both for men (HR: 1.30, 95% CI: 1.15-1.46) and women (HR: 1.16, 95% CI: 1.05-1.28). In men, there was a 52% increase in risk of early-onset PDAC (<age 50) (HR: 1.52, 95% CI: 1.13-2.03) with 5 kg/m2 increase in BMI. A total of 2645 individuals were diagnosed with stage 1-3 disease, of whom 1131 underwent curative surgery. In all, 49% of normal weight, 38% overweight, and 30% obese individuals with stage 1-3 PDAC underwent surgery with curative intent (p < 0.001). Cancer survival was lower in overweight and obese individuals for both sexes. Analysis adjusted for sex, age, and period of diagnosis confirmed increased risk of cancer death in obese individuals. This study suggests that increased BMI in young adults may increase the risk of PDAC, and higher BMI in men is associated with an increased risk of early onset PDAC (<age 50). Overweight and obese individuals were less likely to undergo curative surgery and obese individuals had a higher risk of cancer-related death.

Associations between early-life growth pattern and body size and follicular lymphoma risk and survival: a family-based case-control study

BackgroundThe influence of early-life growth pattern and body size on follicular lymphoma (FL) risk and survival is unclear. In this study, we aimed to investigate the association between gestational age, growth during childhood, body size, changes in body shape over time, and FL risk and survival. MethodsWe conducted a population-based family case-control study and included 706 cases and 490 controls. We ascertained gestational age, growth during childhood, body size and body shape using questionnaires and followed-up cases (median=83 months) using record linkage with national death records. We used a group-based trajectory modeling approach to identify body shape trajectories from ages 5–70. We examined associations with FL risk using unconditional logistic regression and used Cox regression to assess the association between body mass index (BMI) and all-cause and FL-specific mortality among cases. ResultsWe found no association between gestational age, childhood height and FL risk. We observed a modest increase in FL risk with being obese 5 years prior to enrolment (OR=1.43, 95 %CI=0.99–2.06; BMI ≥30 kg/m2) and per 5-kg/m2 increase in BMI 5 years prior to enrolment (OR=1.14, 95 %CI=0.99–1.31). The excess risk for obesity 5 years prior to enrolment was higher for ever-smokers (OR=2.00, 95 %CI=1.08–3.69) than never-smokers (OR=1.14, 95 %CI=0.71–1.84). We found no association between FL risk and BMI at enrolment, BMI for heaviest lifetime weight, the highest categories of adult weight or height, trouser size, body shape at different ages or body shape trajectory. We also observed no association between all-cause or FL-specific mortality and excess adiposity at or prior to enrolment. ConclusionWe observed a weak association between elevated BMI and FL risk, and no association with all-cause or FL-specific mortality, consistent with previous studies. Future studies incorporating biomarkers are needed to elucidate possible mechanisms underlying the role of body composition in FL etiology.

Body-Mass Index-Based Effective Dose Determination in Commonly Performed Computed Tomography Examinations in Adults

Purpose: With the widespread application of ionizing radiation in medical practice, concerns have been increased regarding the hazardous effects of radiation. Studies have demonstrated that some variables such as body dimensions affect the absorbed radiation dose. In this study, the association between Body Mass Index (BMI) and absorbed dose in Computed Tomography (CT) is investigated.&#x0D; Materials and Methods: A total of 550 adult patients (age ≥ 15 years) were included in the study. The height and weight of the patients were recorded for BMI calculation. Dosimetry data were acquired from digital imaging and communications in medicine dose reports. The patients were categorized into five groups according to their BMI, the categorized information was then imported into ImPACT Dose software for calculation of Size-Specific Dose Estimate (SSDE) and organ and effective doses. The relationship between patient BMI and the effective dose was also determined.&#x0D; Results: A higher BMI contributed to increased radiation dose and SSDE in patients who had undergone chest or abdomen-pelvis CT examination (p &lt; 0.05). &#x0D; Conclusion: The radiation dose is related to a patient’s BMI and rises with an increase in BMI. Accordingly, it is suggested that BMI and other variables, such as the type of scan and other body dimensions, which affect the radiation dose, can be used to estimate the radiation dose before performing CT. This estimation can be considered for the justification and optimization of CT examinations.

MRI background parenchymal enhancement, breast density and breast cancer risk factors: A cross-sectional study in pre- and post-menopausal women

Breast tissue enhances on contrast MRI and is called background parenchymal enhancement (BPE). Having high BPE has been associated with an increased risk of breast cancer. We examined the relationship between BPE and the amount of fibroglandular tissue on MRI (MRI-FGT) and breast cancer risk factors. This was a cross-sectional study of 415 women without breast cancer undergoing contrast-enhanced breast MRI at Memorial Sloan Kettering Cancer Center. All women completed a questionnaire assessing exposures at the time of MRI. Prevalence ratios (PR) and 95% confidence intervals (CI) describing the relationship between breast cancer risk factors and BPE and MRI-FGT were generated using modified Poisson regression. In multivariable-adjusted models a positive association between body mass index (BMI) and BPE was observed, with a 5-unit increase in BMI associated with a 14% and 44% increase in prevalence of high BPE in pre- and post-menopausal women, respectively. Conversely, a strong inverse relationship between BMI and MRI-FGT was observed in both pre- (PR = 0.66, 95% CI 0.57, 0.76) and post-menopausal (PR = 0.66, 95% CI 0.56, 0.78) women. Use of preventive medication (e.g., tamoxifen) was associated with having low BPE, while no association was observed for MRI-FGT. BPE is an imaging marker available from standard contrast-enhanced MRI, that is influenced by endogenous and exogenous hormonal exposures in both pre- and post-menopausal women.

The Effects of Body Mass Index &amp; Spine Flexibility on Surgical Outcomes for Patients with Adolescent Idiopathic Scoliosis

Retrospective cohort study. To investigate the relationship between body mass index (BMI), spine flexibility index (FI), and their combined effects on adolescent idiopathic scoliosis (AIS) surgical outcomes. BMI and FI are two factors considered during presurgical planning for AIS correction, but there is sparse research about their relationship. We hypothesize that AIS patients with increased BMI may be associated with decreased FI-a combination which could lead to worsened surgical outcomes. AIS patients ages 11 to 19 at surgery, who underwent posterior fusion at a single center from 2011 to 2017, were reviewed. Patients without proper radiographs to assess FI, or a previous spine surgical history, were excluded. FI was categorized as stiff (FI<50) or flexible (FI≥50), and patients were separated by major curve region. BMI was categorized as underweight (less than fifth percentile), healthy weight (fifth-85th percentile), overweight (85th-95th percentile), or obese (>95th percentile). Regression analysis was conducted to test BMI and FI's effects on intraoperative, immediate postoperative, and two-year postoperative outcomes. A total of 543 patients (82% female), with an average age of 14.9 years, were included. In all, 346 patients had available two-year data. A 10% increase in BMI was associated with a 1.3% decrease in FI for patients with major thoracolumbar/lumbar curves ( P =0.01). Obese patients were most likely to have a postoperative complication ( P =0.003) or a two-year complication ( P =0.04). Revision surgery occurred after 58% of postoperative complications (15/26) and 80% of two-year complications (4/5). FI was negatively associated with initial curve magnitude ( P <0.001), operative time ( P =0.02), and blood loss ( P =0.02). Overweight patients with flexible curves were 10.0 times more likely to sustain a postoperative complication than healthy weight patients with stiff curves ( P =0.001). Elevated BMI was associated with decreased FI in patients with major thoracolumbar/lumbar curves. Patients with a high BMI and high FI were associated with the greatest risk of postoperative complication.

Threshold effects of body mass index on cognitive function and heterogeneity by sex and cardiovascular risk factors.

BackgroundDisclosing the underlying relationship between body mass index (BMI) and cognitive decline is imperative for cognitive impairment prevention and early detection. Empirical studies have indicated the risk of abnormal BMI leading to cognitive impairment. However, the relative risk of underweight or overweight on cognitive function is obscure. This study investigated the asymmetric causal effect of BMI on cognitive decline below and above an unknown threshold and the heterogeneity in the threshold level and the magnitude of the threshold effect due to sex and cardiovascular risk factors.MethodsThis study used 2010–2018 panel data from the Korean Longitudinal Study of Aging that assessed sociodemographic and health-related trends in Korean middle-aged to older population. A generalized method of moments estimator of the panel threshold model was applied to estimate the potential nonlinear pattern between BMI and cognitive function.ResultsThere was a threshold effect in the relationship between BMI and cognitive function. An increase in BMI below the threshold was associated with higher cognitive function, whereas a further increase in BMI above the threshold led to cognitive decline. The nonlinear pattern between BMI and cognitive function differed by sex and cardiovascular risk appearing more distinctively within men or the cardiovascular risk group.ConclusionsThe detrimental impact of being underweight or overweight on cognitive function is heterogeneous by sex or cardiovascular risk. For obese men or individuals with cardiovascular risk factors, maintaining adequate BMI should be highlighted to help prevent cognitive decline.

Lifetime body mass index and grip strength at age 46years: the 1970 British Cohort Study.

BackgroundOngoing rises in obesity prevalence have prompted growing concerns about potential increases in the burden of age‐related musculoskeletal conditions including sarcopenia and sarcopenic obesity. This is of particular concern for future generations of older adults who have lived more of their lives in an obesogenic environment than current generations of older adults. We aimed to study longitudinal associations between body mass index (BMI) and grip strength in midlife using data from a large population‐based sample, the 1970 British Cohort Study (BCS70).MethodsBCS70 participants with valid measures of maximum grip strength at age 46 years were included in analyses [3671 males (49%) and 3876 females (51%)]. Using sex‐specific linear regression models, we examined associations of (i) BMI at ages 10, 16, 30, and 46 years; (ii) body fat percentage (BF%) and waist–hip ratio at age 46 years; (iii) BMI gains between 10–16, 16–30, and 30–46; and (iv) age at onset of obesity, with grip strength.ResultsAt age 46 years, mean (standard deviation) grip strength was 48.10 kg (8.98) in males and 29.61 kg (5.81) in females. Higher BMI at all ages was associated with stronger grip, and the scale of associations was greater in males than females from age 16 onwards (P sex interactions < 0.01). For example, in fully adjusted models, a 1 standard deviation increase in BMI at age 16 was associated with mean differences in grip strength at age 46 years of 1.41 kg (95% confidence interval: 1.07, 1.75) in males and 0.72 kg (0.53, 0.91) in females. Higher BF% at age 46 was also associated with stronger grip in both sexes. Greater gains in BMI between ages 10 and 16 were associated with stronger grip in both sexes, but subsequent gains in BMI were only associated with stronger grip in males. Associations of greater length of exposure to obesity and stronger grip were also more consistent among males than females. For example, in fully adjusted models, mean grip strength at age 46 years of males and females who had been obese since age 10 or 16 years was 4.39 kg (1.85, 6.93) and 1.25 kg (−0.18, 2.69) higher than males and females who had never been obese, respectively.ConclusionsHigher BMI from childhood onwards is associated with stronger grip at age 46 years. This suggests that, at this age, anabolic effects of fat on muscle are outweighing the catabolic effects thought to lead to the manifestation of sarcopenic obesity later in life, especially among men. Midlife may be an optimal time to intervene to prevent sarcopenic obesity.

Impact of bmi on operative time in women undergoing benign hysterectomy

Our objective was to investigate the relationship between body mass index (BMI) and operative time (OT) for benign hysterectomy and determine if BMI with or without other clinical factors can predict OT to better utilize operative room scheduling. This was a secondary analysis of women undergoing laparoscopic, abdominal, or vaginal hysterectomy between 2014-2019 using the American College of Surgeons National Surgical Quality Improvement Program database (NSQIP), N = 117,691. Hysterectomies performed for cancer were excluded. BMI was defined as a continuous variable, and our primary outcome was log10 transformed OT. Multivariable linear regression was used to analyze the relationship between OR time and BMI with covariates including age, uterine weight, route of hysterectomy, smoking status, parity, prior pelvic and abdominal surgery, endometriosis, and subspecialty performing the surgery. A predictive model using 16 variables that could be reliably obtained preoperatively was initially created. A parsimonious model that would be more easily used was selected by including only variables that accounted for >10% of the total Eta2 (i.e., the sum of the proportion of variance associated with all effects included). The final reduced model included only BMI, age divided into quintiles, and route of hysterectomy. Within NSQIP database, route of hysterectomy was 22% abdominal (AH), 16% vaginal (VH), and 62% laparoscopic (LH). The mean OTs were 144, 133, and 158 minutes for AH, VH, and LH, respectively. Uterine weight >250g, prior abdominal surgery, and endometriosis were all statistically associated with increasing operative time; however, the relationship between BMI and operative time was not modified by these factors – the two-way interactions between those factors and BMI were not significant. Route of surgery is a modifier of OT when stratified by BMI; for every 10-unit increase in BMI, estimated OT increased by 9, 7, and 8 minutes for AH, VH, and LH, respectively. Neither the large model with 16 variables nor the concise model with 3 variables accounted for a large percentage of the total variability in log10(OT). R2 values 6.2% and 3.9% for full and reduced models, respectively. There is a positive correlation between BMI and OT for benign hysterectomy across all routes of surgery. Increasing BMI differentially impacts the OT in AH greater than LH and VH. Operative time for hysterectomy is highly variable and its estimation based on patient characteristics and other preoperative variables is difficult to reliably predict.

Locally structured correlation (LSC) plots describe inhomogeneity in normally distributed correlated bivariate variables

BackgroundThe association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.MethodsWe consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named “global standard deviation”, reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in “locally structured standard deviations” and reflect patterns of “locally structured correlations (LSC)”. LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.ResultsThe correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.ConclusionLocally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.

Association of Body Mass Index and Waist Circumference with Prostate-Specific Antigen

Objective: Prostate-specific antigen (PSA) is widely used as a screening tool of prostate cancer, although there has been a controversy about efficacy. In Korea, rapid growth of obesity prevalence in adult men is a one of the biggest health problems. The objective of this study was to evaluate the potential association between body mass index (BMI), waist circumference (WC) and PSA.Methods: We calculated BMI and WC of a total of 25,603 males who visited the Soonchunhyang University Cheonan Hospital Health Promotion Center from January 2016 to December 2020. This was categorized as follows: BMI &lt; 23 kg/m2 (normal), 23 kg/m2 ≤ BMI &lt; 25 kg/m2 (overweight), BMI ≥ 25 kg/m2 (obesity) and WC &lt; 90 cm (normal), WC ≥ 90 cm (abdominal obesity). We analyzed the association between BMI, WC and PSA.Results: The mean PSA value was 1.08 ng/mL, 1.03 ng/mL, and 0.97 ng/mL at normal, overweight, and obesity group, respectively. The mean PSA value was 1.04 ng/mL and 0.96 ng/mL at normal and abdominal obesity group. Thus, the mean PSA value decreased with an increase in BMI and WC category (P &lt; 0.001). The correlation coefficient between BMI, WC and PSA was -0.055, -0.044 and they were statistically significant (P &lt; 0.001).Conclusion: We observed a significant negative correlation between BMI, WC and PSA value. Therefore, PSA value should be considered in relation to BMI and WC.

Absence of Obesity Paradox in All-Cause Mortality Among Chinese Patients With an Implantable Cardioverter Defibrillator: A Multicenter Cohort Study

Background: The results of studies on the obesity paradox in all-cause mortality are inconsistent in patients equipped with an implantable cardioverter-defibrillator (ICD). There is a lack of relevant studies on Chinese populations with large sample size. This study aimed to investigate whether the obesity paradox in all-cause mortality is present among the Chinese population with an ICD.Methods: We conducted a retrospective analysis of multicenter data from the Study of Home Monitoring System Safety and Efficacy in Cardiac Implantable Electronic Device–implanted Patients (SUMMIT) registry in China. The outcome was all-cause mortality. The Kaplan–Meier curves, Cox proportional hazards models, and smooth curve fitting were used to investigate the association between body mass index (BMI) and all-cause mortality.Results: After inclusion and exclusion criteria, 970 patients with an ICD were enrolled. After a median follow-up of 5 years (interquartile, 4.1–6.0 years), in 213 (22.0%) patients occurred all-cause mortality. According to the Kaplan–Meier curves and multivariate Cox proportional hazards models, BMI had no significant impact on all-cause mortality, whether as a continuous variable or a categorical variable classified by various BMI categorization criteria. The fully adjusted smoothed curve fit showed a linear relationship between BMI and all-cause mortality (p-value of 0.14 for the non-linearity test), with the curve showing no statistically significant association between BMI and all-cause mortality [per 1 kg/m2 increase in BMI, hazard ratio (HR) 0.97, 95% CI 0.93–1.02, p = 0.2644].Conclusions: The obesity paradox in all-cause mortality was absent in the Chinese patients with an ICD. Prospective studies are needed to further explore this phenomenon.

Correlation between body mass index and in-hospital mortality in patients with ST-segment elevation myocardial infarction in Erbil city- Iraq

Background: Although High body mass index is associated with many cardiovascular diseases including coronary artery disease. Its effect on in-hospital death in patients with acute ST-segment elevation myocardial infarction (STEMI) is still a subject of controversy. Objective: To determine the correlation between body mass index (BMI) and in-hospital mortality in those patients. Patients and Methods: In this cross-sectional study, 180 adult patients with acute STEMI were enrolled and their BMI was measured. The participants were classified according to BMI into three groups as normal, overweight, and obese. A correlation between in-hospital mortality due to STEMI and BMI was evaluated. Results: Of the total participants, 62 (34.4%) were normally weighted, 61(33.8%) were over-weighted, and 57(31.6%) were obese. There was a significant difference (p= &lt;0.001) between the groups concerning troponin I, hs-CRP, GRACE score, and the probability of in-hospital death. There were 16 (8.8%) in-hospital deaths during the study distributed as follows; 1(1.6%) in the normal-weight group, 5(8.1%) in the overweight group, and 10 (17.5%) in the obese group. In-hospital death showed a significant difference (p=0.04) between the study groups. In addition, a significant positive correlation(r=0.9) was found between BMI and in-hospital death. Conclusion: A robust positive correlation was detected between BMI and in-hospital mortality due to acute STEMI. When BMI increases, the number of deaths also increases exponentially. Keywords: Body mass index, ST-segment elevation myocardial infarction, mortality

Ethnic Differences in the Association Between Body Mass Index and Type 2 Diabetes Risk: A Meta-Analysis of Prospective Cohort Studies

ObjectivesThe association between body mass index (BMI) and total body adiposity differs across ethnic groups. For instance, South Asians (SA) and East Asians (EA) have lower body fat for a given BMI level than Europeans, while the opposite is true for African-Caribbeans (AC). This suggests that the relationship between BMI and type 2 diabetes (T2D) risk may also vary depending on ethnicity. We conducted a meta-analysis to investigate whether the association between BMI and the risk of T2D differs across ethnic groups. MethodsMEDLINE, EMBASE and Web of Science were searched up to July 2020. We included prospective cohort studies of >2 years, which investigated the association between BMI and T2D incidence among adults of a specified ethnicity. Linear and non-linear dose-response meta-analyses were performed using random effects models, with subgroup analyses by ethnicity. The heterogeneity among studies was estimated using the Cochran Q test and I2 statistic. Study quality was assessed with the Newcastle-Ottawa Scale. Results54 studies were included. Cohorts were stratified into the following ethnic subgroups: AC (N = 67,453), EA (N = 1,012,135), European (N = 206,424), Indigenous (N = 10,533), Latin American (LA) (N = 4,669), SA (N = 9,395), and Southeast Asian (SEA) (N = 51,129). Linear dose-response associations between 1 kg/m2 increase in BMI and T2D were observed for the SEA (RR = 1.26; 95% CI, 1.10, 1.30) and SA (RR = 1.11; 95% CI: 1.04, 1.19) subgroups with no evidence of departure from linearity. Associations departed from linearity for all other subgroups. At a BMI level of 30 kg/m2, the non-linear dose-response curves for each of the other subgroups displayed the following risk ratios; AC: RR = 3.13 (95% CI, 1.95, 5.02), EA: RR = 2.39 (95% CI, 1.96, 2.92), European: RR = 7.41 (95% CI, 3.88, 14.18), Indigenous: RR = 8.15 (95% CI, 6.07; 10.95), and LA: RR = 12.82 (95% CI, 5.50, 29.92). For all subgroups, there was a high degree of interstudy heterogeneity (I2 > 75%). ConclusionsOur findings indicated that the association between BMI and the risk of T2D differs across ethnic groups, suggesting that ethnic-specific BMI cut-offs could be helpful in identifying cardiometabolic risk profiles across different populations. Funding SourcesCanadian Institutes for Health Research.

Abstract P116: Higher Body Mass Index Trajectories Are Associated With Lower Levels Of Physical Activity Measured By A Smartwatch

Introduction: The prevalence of obesity is rising. Most previous studies that examined the relationship between body mass index (BMI) and physical activity measured BMI at a single time-point, ignoring the time-varying nature of BMI. The relationship between BMI trajectories and habitual physical activity in community settings remains unclear. Objective: To assess the relationship between BMI trajectories and habitual physical activity measured by daily steps from a smartwatch, among participants enrolled in the electronic Framingham Heart Study (eFHS). We hypothesized that participants whose BMI trajectories increased over a 14-year period prior to the step assessment take fewer daily steps, compared to participants who maintained stable BMI trajectories during the same time period. Methods: We used a semiparametric group-based modelling method to identify BMI trajectory patterns. Participants who attended exams 1, 2, and 3 were included in building the trajectories. Daily steps were recorded from the smartwatch provided at exam 3 with “active days” defined as days with ≥ 5watch wear-hours. We excluded participants with &lt;30 active days. The median follow-up period for step count was 357 days (IQR: 467 days). We used generalized linear models that accounted for correlation between daily steps in the same individuals to examine the longitudinal relationship between BMI trajectory groups and daily step counts, adjusting for relevant covariates. Results: We identified three trajectory groups for the 837 eFHS participants. Group 1 included 292 participants (mean age 54 years, 57% women) whose BMI was stable (slope: 0.005, p=0.75); Group 2 included 468 participants (mean age 53 years, 56% women) whose BMI increased slightly (slope: 0.123, p&lt;9.2e-17); and Group 3 included 77 participants (mean age 50 years, 70% women) who had the largest increase of BMI (slope: 0.318, p=2.8e-22).Adjusting for age, sex, wear time and race/ethnicity, participants in group 3 (Δ1437 steps P&lt; 0.0001) and Group 2 (Δ422 steps, P=0.04) took significantly fewer steps, compared to participants in Group 1 (Model 1). The effect sizes were slightly attenuated but remained significant after additionally adjusting for hypertension, type 2 diabetes, current smoking, and cardiovascular disease: Group 3 took 1258 fewer steps, P=0.0001; Group 2 took 406 fewer steps, P=0.04 (Model 2). We further adjusted for sleep apnea, education, and marital status in Model 3 and observed that on average Group 3 took 1120 fewer steps (P= 0.0007) and Group 2 took 382 fewer steps (P= 0.06), compared to Group 1. Conclusion: Participants whose BMI trajectory increased over time took significantly fewer steps compared to participants with more stable BMI trajectories. Our findings suggest that levels of physical activity may correlate with greater weight gain during adulthood.