Young people are consuming large amounts of microplastics (MPs) due to the booming development of the take-out industry. To investigate the association between MPs exposure and obesity, 121 ...volunteers were divided into high MPs exposure (HME) and low MPs exposure (LME) according to the frequency of take-out food consumption. Fecal samples were collected for MPs detection using Raman spectra analysis, and identification of the gut microbiota was based on 16 S rDNA/ITS, while metabolite analysis was performed by LC-MS/MS. High levels of MPs and body mass index (BMI) were observed in the HME group (P < 0.05). Both the multiple linear regression (MLR) model and the binary logistic regression (BLR) (OR: 1.264, 95 % CI: 1.108–1.441, P < 0.001) analysis showed a positive correlation between MPs content and BMI. Microbial community analysis revealed that Veillonella, Alistipes and Dothideomycotes (pathogenic fungi) increased in HME participants, whereas Faecalibacterium and Coprococcus decreased. Meanwhile, analysis of stool metabolites showed that vancomycin resistance, selenocompound metabolism and drug metabolism pathways were enhanced in HME participants. These findings indicate that frequent consumption of take-out food may elevate the intake of microplastics, consequently modifying the gut microbiota and metabolites of young adults, and could represent a potential risk factor for obesity.
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•Susceptible students with higher frequency of take-out (i.e., n ≥ 14 times/week) have higher concentrations of microplastics in their feces.•Microplastics were associated with high BMI in both multiple linear regression and binary logistic regression.•High MPs exposure could increase the abundance of Veillonella, Alistpes and Dothideomycotes (pathogenic fungi) in the intestine, leading to obesity.•Compared to low MPs exposure group, vancomycin resistance, selenocompound metabolism, drug metabolism metabolic pathways of HME enhanced.
The obesity paradox refers to a phenomenon by which obese individuals experience lower risk of mortality and even protective associations from chronic disease sequelae when compared with the ...non-obese and underweight population. Prior literature has demonstrated an obesity paradox after cardiac and other surgical procedures. However, the relationship between body mass index (BMI) and perioperative complications for patients undergoing major open lower extremity arterial revascularization is unclear.
We queried the Vascular Quality Initiative for individuals receiving unilateral infrainguinal bypass between 2003 and 2020. We used multivariable logistic regression to assess the relationship of BMI categories (underweight <18.5 kg/m2, non-obese 18.5-24.9 kg/m2, overweight 25-29.9 kg/m2, Class 1 obesity 30-34.9 kg/m2, Class 2 obesity 35-39.9 kg/m2, and Class 3 obesity >40 kg/m2) with 30-day mortality, surgical site infection, and adverse cardiovascular events. We adjusted the models for key patient demographics, comorbidities, and technical and perioperative characteristics.
From 2003 to 2020, 60,588 arterial bypass procedures met inclusion criteria for analysis. Upon multivariable logistic regression with the non-obese category as the reference group, odds of 30-day mortality were significantly decreased among the overweight (odds ratio OR, 0.64; 95% confidence interval CI, 0.53-0.78), Class 1 obese (OR, 0.65; 95% CI, 0.52-0.81), Class 2 obese (OR, 0.66; 95% CI, 0.48-0.90), and Class 3 obese (OR, 0.61; 95% CI, 0.39-0.97) patient categories. Conversely, odds of 30-day mortality were increased in the underweight patient group (OR, 1.58; 95% CI, 1.16-2.13). Furthermore, a BMI-dependent positive association was present, with odds of surgical site infections with patients in Class 3 obesity having the highest odds (OR, 2.10; 95% CI, 1.60-2.76). Finally, among the adverse cardiovascular event outcomes assessed, only myocardial infarction (MI) demonstrated decreased odds among overweight (OR, 0.82; 95% CI, 0.71-0.96), Class 1 obese (OR, 0.78; 95% CI, 0.65-0.93), and Class 2 obese (OR, 0.66; 95% CI, 0.51-0.86) patient populations. Odds of MI among the underweight and Class 3 obesity groups were not significant.
The obesity paradox is evident in patients undergoing lower extremity bypass procedures, particularly with odds of 30-day mortality and MI. Our findings suggest that having higher BMI (overweight and Class 1-3 obesity) is not associated with increased mortality and should not be interpreted as a contraindication for lower extremity arterial bypass surgery. However, these patients should be under vigilant surveillance for surgical site infections. Finally, patients that are underweight have a significantly increased odds of 30-day mortality and may be more suitable candidates for endovascular therapy.
The authors sought to report the prevalence, clinical associations, and prognostic consequences of malnutrition in outpatients with heart failure (HF).
Malnutrition may be common in HF and associated ...with adverse outcomes, but few data exist.
We applied the geriatric nutritional risk index (GNRI), controlling nutritional status (CONUT) score, and prognostic nutritional index (PNI) to consecutive patients referred with suspected HF to a clinic serving a local population (n = 550,000).
Of 4,021 patients enrolled, HF was confirmed in 3,386 (61% men; median age: 75 years; interquartile range IQR: 67 to 81 years, median N-terminal pro-B-type natriuretic peptide NT-proBNP 1,103 ng/l IQR: 415 to 2,631 ng/l). Left ventricular ejection fraction was <40% in 35% of patients. Using scores for GNRI ≤91, CONUT >4, and PNI ≤38, 6.7%, 10.0%, and 7.5% patients were moderately or severely malnourished, respectively; 57% were at least mildly malnourished by at least 1 score. Worse scores were most strongly related to older age, lower body mass index, worse symptoms and renal function, atrial fibrillation, anemia, and reduced mobility. During a median follow-up of 1,573 days (IQR: 702 to 2,799 days), 1,723 (51%) patients died. For patients moderately or severely malnourished, 1-year mortality was 28% for CONUT, 41% for GNRI, and 36% for PNI, compared with 9% for those with mild malnutrition or normal nutritional status. A model including only age, urea, and logNT-proBNP, predicted 1-year survival (C-statistic: 0.719) and was slightly improved by adding nutritional indices (up to 0.724; p < 0.001) but not body mass index.
Malnutrition is common among outpatients with HF and is strongly related to increased mortality.
This study aimed to detect the relationship between nickel exposure and body mass index (BMI), waist circumference and incidence of obesity in the general population of the United States. The ...National Health and Nutrition Examination Survey (NHANES) 2017–2018 database was utilized, and the sample comprised 1702 participants aged 18 years and above with complete urinary nickel, body mass index, and waist circumference data. Obesity was determined using BMI and waist circumference data. The multivariate linear regression and logistic regression models were utilized to detect the association between urinary nickel concentration and BMI, waist circumference, and incidence of obesity. After multivariable adjustment, the log-transformed urinary nickel concentration was inversely associated with BMI β = −0.87; 95% confidence interval (CI): (−1.36, −0.38) and waist circumference β = −1.51; 95% CI: (−2.93, −0.08). Compared with the lowest tertile of urinary nickel, the β value and 95% CI of BMI and waist circumference for the highest tertile were β = −1.65.95% CI: (−2.85, −0.45) and β = −2.78, 95% CI: (−6.17, 0.62), respectively. The log-transformed urinary nickel concentration was also negatively associated with obesity status adjusted odds ratio (OR) = 0.81, 95% CI: (0.64, 1.01). Compared with the lowest tertile of urinary nickel, the adjusted OR and 95% CI of obesity status for the highest tertile were OR = 0.64 and 95% CI: (0.37, 1.12). Smooth curve fitting and the generalized additive model indicated that elevated urinary nickel concentration was associated with decreased BMI, waist circumference, and incidence of obesity. The negative association was consistent and robust in different subgroups, according to stratified analysis. This study found that nickel exposure may be negatively associated with BMI, waist circumference and incidence of obesity in US Adults.
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•Relationship between nickel exposure and obesity status was studied in US adults.•Urinary nickel level was negatively associated with BMI and waist circumference.•Nickel exposure may be negatively associated with incidence of obesity.
Abstract
Objective
To review the peer-reviewed literature on relationships between intuitive eating and health indicators and suggest areas of inquiry for future research. We define the fundamental ...principles of intuitive eating as: (i) eating when hungry; (ii) stopping eating when no longer hungry/full; and (iii) no restrictions on types of food eaten unless for medical reasons.
Design
We include articles cited by PubMed, PsycInfo and Science Direct published in peer-reviewed journals or theses that include ‘intuitive eating’ or related concepts in the title or abstract and that test relationships between intuitive eating and physical or mental health indicators.
Results
We found twenty-six articles that met our criteria: seventeen cross-sectional survey studies and nine clinical studies, eight of which were randomised controlled trials. The cross-sectional surveys indicate that intuitive eating is negatively associated with BMI, positively associated with various psychological health indicators, and possibly positively associated with improved dietary intake and/or eating behaviours, but not associated with higher levels of physical activity. From the clinical studies, we conclude that the implementation of intuitive eating results in weight maintenance but perhaps not weight loss, improved psychological health, possibly improved physical health indicators other than BMI (e.g. blood pressure; cholesterol levels) and dietary intake and/or eating behaviours, but probably not higher levels of physical activity.
Conclusions
Research on intuitive eating has increased in recent years. Extant research demonstrates substantial and consistent associations between intuitive eating and both lower BMI and better psychological health. Additional research can add to the breadth and depth of these findings. The article concludes with several suggestions for future research.
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•TheADIPOQ gene variants alters its expression, affecting adiponectin levels, that may vary with changes in body weight.•We examined the relationship between ADIPOQ variants and T2D ...in normal, overweight and obese women with T2D vs. controls.•The rs17300539 variant increases T2D susceptibility and hypadiponectinemia among women.•The rs2241766 variant is associated with obesity and hypoadiponectinemia.•The GGCAATGAA haplotype shows a significant correlation with the risk of developing T2D and hypoadiponectinemia.
Although prior studies have shown that adiponectin synthesis is genetically determined and that its levels influence susceptibility to T2D, the results in this regard have been inconsistent. This study aims, to investigate the relationship between adiponectin gene variants with the risk of developing T2D among Tunisian women and in relation to their BMI status. A cohort of 491 Tunisian T2D women and 373 non-diabetic subjects participated in the study. Nine ADIPOQ variants namely rs16861194, rs17300539, rs266729, rs822395, rs822396, rs2241766, rs1501299, rs2241767 and rs3774261 were selected and genotyped using the TaqMan® SNP genotyping assay. Fasting serum adiponectin levels were quantified using ELISA. The results showed that only the rs17300539 variant exhibited a significant association with the risk of T2D. However, upon considering T2D group stratification based on BMI (normal weight 18–24.99 Kg/m2, overweight 25–29.99 Kg/m2 and obese 30–34.99 Kg/m2), the ADIPOQ rs2241766 variant emerged as a contributing risk factor for increased BMI in obese women with T2D. Linear regression analysis revealed that the minor allele (A), (GA) and (AA) genotypes of rs17300539 as well as the (G) allele and (GG) genotype of rs2241766 were significantly associated with hypoadiponectinemia in T2D subjects. Two haplotypes namely GGCAATGAA and AGCCGTGGA, were identified as conferring a higher risk of T2D with the GGCAATGAA haplotype also correlating with hypoadiponectinemia. Our study underscores the importance of the rs17300539 variant and the GGCAATGAA haplotype in the risk of T2D and hypoadiponectinemia. Additionally, the presence of the rs2241766 variant highlights its association with ‘diabesity’ and hypoadiponectinemia among Tunisian T2D women.
To summarise the evidence on the associations between body mass index (BMI) and BMI in early adulthood, height, waist circumference (WC) and waist-to-hip ratio (WHR), and risk of ...lympho-haematopoietic cancers.
We conducted a meta-analysis of prospective studies and identified relevant studies published up to December 2017 by searching PubMed. A random-effects model was used to calculate dose–response summary relative risks (RRs).
Our findings showed BMI, and BMI in early adulthood (aged 18–21years) is associated with the risk of Hodgkin’s and non-Hodgkin’s lymphoma (HL and NHL), diffuse large beta-cell lymphoma (DLBCL), Leukaemia including acute and chronic myeloid lymphoma (AML and CML), and chronic lymphocytic leukaemia (CLL) and multiple myeloma (MM). The summary RR per 5kg/m2 increase in BMI were 1.12 95% confidence interval (CI): 1.05–1.20 for HL, 1.05 (95% CI: 1.03–1.08) for NHL, 1.11 (95% CI: 1.05–1.16) for DLBCL, 1.06 (95% CI: 1.03–1.09) for ML, 1.09 (95% CI: 1.03–1.15) for leukaemia, 1.13 (95% CI: 1.04–1.24) for AML, 1.13 (95% CI: 1.05–1.22) for CML and 1.04 (95% CI: 1.00–1.09) for CLL, and were1.12 (95% CI: 1.05–1.19) for NHL, 1.22 (95% CI: 1.09–1.37) for DLBCL, and 1.19 (95% CI: 1.03–1.38) for FL for BMI in early adulthood analysis. Results on mortality showed a 15%, 16% and 17% increased risk of NHL, MM and leukaemia, respectively. Greater height increased the risk of NHL by 7%, DLBCL by 10%, FL by 9%, MM by 5% and Leukaemia by 7%. WHR was associated with increased risk of DLBCL by 12%. No association was found between higher WC and risk of MM.
Our results revealed that general adiposity in adulthood and early adulthood, and greater height may increase the risk of almost all types of lympho-haematopoietic cancers and this adds to a growing body of evidence linking body fatness to several types of cancers.
To explore the longitudinal association between social-jetlag (SJL) and obesity development among adolescents, sex-difference and related modifying factors in the association.
Based on ...Shanghai-Adolescent-Cohort during 2017–2021, a total of 609 students were investigated. In grade 6, 7 and 9, the information on SJL was collected using questionnaires, and anthropometric measures were conducted. The fingernail cortisol and progesterone levels in grade 6 (using LC-MS/MS) and body composition in grade 9 (using Inbody-S10) were measured. By the latent-class-mixture-modeling, two trajectories for SJL (high-level vs. low-level) throughout 4 years were developed. The prospective associations of SJL trajectories and weight/fat gains were analyzed by sex and under different (high/moderate/low) cortisol/progesterone stratifications.
In grades 6–9, 39.00%–44.50 % of adolescents experienced at least 1 h of SJL. Compared with the low-level SJL trajectory, the high-level SJL trajectory was associated with greater differences in body-mass-index Z-scores and waist-to-height ratios across 4 years, higher levels of body-fat-percentage and fat-mass-index in grade 9 (P-values<0.05), and such associations were stronger among girls and under moderate-to-high (vs. low) baseline cortisol and progesterone levels. However, no significant associations among boys were observed.
High-level SJL in adolescents may be associated with the development of obesity, especially among adolescent girls and under relatively high baseline cortisol and progesterone levels.
•We found that about 40 % of adolescents experienced ≥1 h of social jetlag (SJL).•High (vs. low)-level SJL trajectory was associated with more weight gains in teens.•Such association had sex-difference and was stronger among adolescent girls.•Such association was stronger under high (vs. low) cortisol/progesterone levels.•Multiple obesity indicators and a wide range of confounders were used in the study.
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