The Prognostic Significance of Body Mass Index and Metabolic Parameter Variabilities in Predialysis CKD: A Nationwide Observational Cohort Study

2021 ◽  
pp. ASN.2020121694
Author(s):  
Sehoon Park ◽  
Semin Cho ◽  
Soojin Lee ◽  
Yaerim Kim ◽  
Sanghyun Park ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Mass ◽  
Metabolic Parameters ◽  
Metabolic Parameter ◽  
Content Type ◽  
All Cause Mortality ◽  
Metabolic Syndrome Components ◽  
Worse Prognosis

BackgroundThe association between variabilities in body mass index (BMI) or metabolic parameters and prognosis of patients with CKD has rarely been studied.MethodsIn this retrospective observational study on the basis of South Korea’s national health screening database, we identified individuals who received ≥3 health screenings, including those with persistent predialysis CKD (eGFR <60 ml/min per 1.73 m2 or dipstick albuminuria ≥1). The study exposure was variability in BMI or metabolic parameters until baseline assessment, calculated as the variation independent of the mean and stratified into quartiles (with Q4 the highest quartile and Q1 the lowest). We used Cox regression adjusted for various clinical characteristics to analyze risks of all-cause mortality and incident myocardial infarction, stroke, and KRT.ResultsThe study included 84,636 patients with predialysis CKD. Comparing Q4 versus Q1, higher BMI variability was significantly associated with higher risks of all-cause mortality (hazard ratio [HR], 1.66; 95% confidence interval [95% CI], 1.53 to 1.81), P [for trend] <0.001), KRT (HR, 1.20; 95% CI, 1.09 to 1.33; P<0.001), myocardial infarction (HR, 1.19; 95% CI, 1.05 to 1.36, P=0.003), and stroke (HR, 1.19; 95% CI, 1.07 to 1.33, P=0.01). The results were similar in the subgroups divided according to positive or negative trends in BMI during the exposure assessment period. Variabilities in certain metabolic syndrome components (e.g., fasting blood glucose) also were significantly associated with prognosis of patients with predialysis CKD. Those with a higher number of metabolic syndrome components with high variability had a worse prognosis.ConclusionsHigher variabilities in BMI and certain metabolic syndrome components are significantly associated with a worse prognosis in patients with predialysis CKD.

scholarly journals All cause mortality and body mass index in a young Asian occupational cohort without baseline metabolic syndrome components

2016 ◽  
Vol 224 ◽  
pp. 271-278 ◽  
Author(s):  
Ki-Chul Sung ◽  
Seungho Ryu ◽  
Jong-Young Lee ◽  
SungHo Lee ◽  
EunSun Cheong ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Mass ◽  
All Cause Mortality ◽  
Occupational Cohort ◽  
Metabolic Syndrome Components

The role of body mass index or metabolic syndrome components causing depression in women: An observation from weight reduction clinical trial

2021 ◽  
Author(s):  
Ranakishor Pelluri ◽  
Srikanth Kongara ◽  
Jithendra Chimakurthy ◽  
Shriraam Mahadevan ◽  
Vanitharani Nagasubramanian
Keyword(s):  
Metabolic Syndrome ◽  
Clinical Trial ◽  
Body Mass Index ◽  
Body Mass ◽  
Weight Reduction ◽  
Metabolic Syndrome Components

scholarly journals Consistently Stable or Decreased Body Mass Index in Young Adulthood and Longitudinal Changes in Metabolic Syndrome Components

Circulation ◽  
2007 ◽  
Vol 115 (8) ◽  
pp. 1004-1011 ◽  
Author(s):  
Donald M. Lloyd-Jones ◽  
Kiang Liu ◽  
Laura A. Colangelo ◽  
Lijing L. Yan ◽  
Liviu Klein ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Mass ◽  
Young Adulthood ◽  
Longitudinal Changes ◽  
Metabolic Syndrome Components

scholarly journals Testosterone: Relationships with Metabolic Disorders in Men—An Observational Study from SPECT-China

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jing Cheng ◽  
Bing Han ◽  
Qin Li ◽  
Fangzhen Xia ◽  
Hualing Zhai ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Mass ◽  
Weight Status ◽  
Metabolic Disorders ◽  
Metabolic Parameters ◽  
Total Testosterone ◽  
Logistic Regressions ◽  
Obesity Indices

Background. The strength of associations between total testosterone (TT) and metabolic parameters may vary in different nature of population structure; however, no study has ever given this information in Chinese population, especially those without metabolic syndrome (MS). We aimed to analyze the association magnitudes between TT and multiple metabolic parameters in general Chinese men. Methods. 4309 men were recruited from SPECT-China study in 2014-2015, which was performed in 22 sites in East China. TT, weight status, and various metabolic parameters were measured. Linear and logistic regressions were used to analyze the associations. Results. Men in lower TT quartiles had worse metabolic parameters including body mass index, triglycerides, HbA1c, and HOMA-IR (all P for trend < 0.001). Body mass index (B −0.32, 95%CI −0.35 to −0.29) and obesity (OR 0.40, 95%CI 0.35–0.45) had the largest association magnitude per one SD increment in TT, while blood pressure and hypertension (OR 0.90, 95%CI 0.84–0.98) had the smallest. These associations also persisted in individuals without metabolic syndrome. Conclusions. Obesity indices had closer relationships with TT than most other metabolic measures with blood pressure the least close. These associations remained robust after adjustment for adiposity and in subjects without metabolic syndrome.

PPARγ Pro12Ala Polymorphism Influences the Relationship between Dietary Fat Intake, Adiposity and Lipid Profile in Patients with Type 2 Diabetes

2018 ◽  
Vol 88 (5-6) ◽  
pp. 263-269 ◽  
Author(s):  
Fariba Koohdani ◽  
Gity Sotoudeh ◽  
Zahra Kalantar ◽  
Anahita Mansoori
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Fatty Acids ◽  
Polyunsaturated Fatty Acids ◽  
Body Mass ◽  
Dietary Fat ◽  
Fat Intake ◽  
Pro12ala Polymorphism ◽  
Dietary Fat Intake ◽  
Metabolic Syndrome Components

Abstract. Background: Peroxisome proliferator-activated receptor γ (PPARγ) Pro12Ala polymorphism (rs1801282) has been associated with metabolic syndrome components in some studies. Moreover, the PPARγ gene may mediate the physiological response to dietary fat intake in a ligand-dependent manner. Methods: Metabolic syndrome components (body mass index, waist circumference, and lipid profile) were determined in 290 type 2 diabetes mellitus patients in a cross-sectional study. DNA genotyping for determining PPARγ Pro12Ala polymorphism was conducted using the polymerase chain reaction-restriction length polymorphism method. A semi-quantitative food frequency questionnaire was used to assess the participants’ dietary intakes in the previous year. Results: There were significant differences between the two genotype groups of PPARγ Pro12Ala polymorphism, Ala carriers (Pro/Ala + Ala/Ala) versus non-Ala carriers (Pro/Pro), in terms of mean body mass index (p = 0.04) and waist circumference (p = 0.02). Below the median percentage of energy from monounsaturated and polyunsaturated fatty acids, Ala carriers had a higher body mass index (p = 0.01) compared to non-Ala carriers. Furthermore, a significant interaction between this single-nucleotide polymorphism and polyunsaturated fatty acids intake on serum triglyceride levels (p = 0.01) was seen, and in higher polyunsaturated fatty acids intake (≥ median) Ala carriers had lower triglyceride levels than non-Ala carriers (p = 0.007). Conclusions: The findings of the current study support a significant association between PPARγ Pro12Ala polymorphism and metabolic syndrome components, and they suggest that this polymorphism can modulate the biological response of dietary fat intake on body mass index and triglyceride levels.

Body mass index status is effective in identifying metabolic syndrome components and insulin resistance in Pacific Island teenagers living in New Zealand

Metabolism ◽  
2008 ◽  
Vol 57 (4) ◽  
pp. 511-516 ◽  
Author(s):  
Andrea M. Grant ◽  
Finau K. Taungapeau ◽  
Kirsten A. McAuley ◽  
Rachael W. Taylor ◽  
Sheila M. Williams ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Body Mass Index ◽  
New Zealand ◽  
Body Mass ◽  
Pacific Island ◽  
Body Mass Index Status ◽  
Metabolic Syndrome Components

scholarly journals Impact of Fecal Microbiota Transplantation on Obesity and Metabolic Syndrome—A Systematic Review

Nutrients ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2291 ◽  
Author(s):  
Zhang ◽  
Mocanu ◽  
Cai ◽  
Dang ◽  
Slater ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Insulin Sensitivity ◽  
Body Mass ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Fecal Microbiota Transplantation ◽  
Fecal Microbiota ◽  
Metabolic Parameters ◽  
Fasting Plasma

Fecal microbiota transplantation (FMT) is a gut microbial-modulation strategy that has been investigated for the treatment of a variety of human diseases, including obesity-associated metabolic disorders. This study appraises current literature and provides an overview of the effectiveness and limitations of FMT as a potential therapeutic strategy for obesity and metabolic syndrome (MS). Five electronic databases and two gray literature sources were searched up to 10 December 2018. All interventional and observational studies that contained information on the relevant population (adult patients with obesity and MS), intervention (receiving allogeneic FMT) and outcomes (metabolic parameters) were eligible. From 1096 unique citations, three randomized placebo-controlled studies (76 patients with obesity and MS, body mass index = 34.8 ± 4.1 kg/m2, fasting plasma glucose = 5.8 ± 0.7 mmol/L) were included for review. Studies reported mixed results with regards to improvement in metabolic parameters. Two studies reported improved peripheral insulin sensitivity (rate of glucose disappearance, RD) at 6 weeks in patients receiving donor FMT versus patients receiving the placebo control. In addition, one study observed lower HbA1c levels in FMT patients at 6 weeks. No differences in fasting plasma glucose, hepatic insulin sensitivity, body mass index (BMI), or cholesterol markers were observed between two groups across all included studies. While promising, the influence of FMT on long-term clinical endpoints needs to be further explored. Future studies are also required to better understand the mechanisms through which changes in gut microbial ecology and engraftment of microbiota affect metabolic outcomes for patients with obesity and MS. In addition, further research is needed to better define the optimal fecal microbial preparation, dosing, and method of delivery.

scholarly journals Renal Function Effect on the Association Between Body Mass Index and Mortality Risk After Acute Myocardial Infarction

2021 ◽  
Vol 8 ◽  
Author(s):  
Shin Yeong Kang ◽  
Weon Kim ◽  
Jin Sug Kim ◽  
Kyung Hwan Jeong ◽  
Myung Ho Jeong ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Body Mass Index ◽  
Renal Function ◽  
Body Mass ◽  
Mortality Risk ◽  
Cardiac Death ◽  
Survival Benefit ◽  
Interactive Effects ◽  
All Cause Mortality

Background: Body mass index (BMI) is a critical determinant of mortality after acute myocardial infarction (AMI), and higher BMI is associated with survival benefit in patients with renal impairment. However, there are no studies investigating the interactive effects of BMI and renal function on mortality risk after AMI occurrence.Methods: We enrolled 12,647 AMI patients from Korea Acute Myocardial Infarction Registry between November 2011 and December 2015. Patients were categorized based on estimated Glomerular Filtration Rate (eGFR) and BMI. The primary endpoint was all-cause mortality after AMI treatment.Results: Within each renal function category, the absolute mortality rate was decreased in patients with higher BMI. However, the adjusted hazard ratio (HR) of all-cause mortality for higher BMI was decreased as renal function worsened [adjusted HR (95% confidence interval) at BMI ≥ 25 kg/m2: 0.63 (0.41–0.99), 0.76 (0.59–0.97), and 0.84 (0.65–1.08) for patients with eGFR ≥ 90, 90–45, and &lt;45 mL/min/1.73 m2, respectively]. There was a significant interaction between BMI and renal function (P for interaction = 0.010). The protective effect of higher BMI was preserved against non-cardiac death and it was also decreased with lowering eGFR in competing risks models [adjusted HR at BMI ≥25 kg/m2: 0.38 (0.18–0.83), 0.76 (0.59–0.97), and 0.84 (0.65–1.08) for patients with eGFR ≥ 90, 90–45, and &lt;45 mL/min/1.73 m2, respectively; P for interaction = 0.03]. However, renal function did not significantly affect the association between BMI and risk of cardiac death (P for interaction = 0.20).Conclusions: The effect of BMI on the mortality risk after AMI was dependent on renal function. The association between greater BMI and survival benefit was weakened as renal function was decreased. In addition, the negative effect of renal function on the BMI – mortality association was pronounced in the non-cardiac death.

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