Metabolically healthy obesity and risk of incident CKD

Metabolic abnormalities, but not obesity per se, associated with chronic kidney disease in a Taiwanese population

BACKGROUND AND AIMS

It is inconclusive whether obesity itself or metabolic abnormalities are linked to chronic kidney disease (CKD). The aim of this study was to examine the association between different subtypes of obesity and metabolic abnormalities with CKD in adults.

METHODS AND RESULTS

This study enrolled 14,983 eligible subjects stratified into metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and metabolically unhealthy obesity (MUO) according to body mass index and metabolic syndrome status (ATP-III criteria). The metabolic healthy phenotype was defined as the absence of both metabolic syndrome and any known diabetes, coronary artery disease, stroke, hypertension or dyslipidemia. Early and advanced CKD were defined as eGFR<60, proteinuria, or structural abnormalities as detected by renal sonography. The prevalence of CKD was 2.5, 3.0, 4.0, 10.6, 9.5, and 10.5% in subjects with MHNW, MHOW, MHO, MUNW, MUOW, and MUO, respectively. In the multivariate analysis, the MUNW (OR:2.22, P < 0.001), MUOW (OR:2.22, P < 0.001), and MUO (OR:2.45, P < 0.001) groups were associated with early CKD. For advanced CKD, the OR was 2.56 (P < 0.001), 2.31 (P < 0.001), and 3.49 (P < 0.001) in the MUNW, MUOW, and MUO groups, respectively. The associated risks of early and advanced CKD were not significant in the MHOW and MHO group. MUOW and MUO were associated with higher risk of CKD compared with MHOW and MHO after adjusting other variables.

CONCLUSIONS

Metabolic abnormalities, but neither overweight nor obesity, were associated with a higher risk of CKD in adults.

Association between Sleep Duration and Incident Chronic Kidney Disease: A Population-Based Cohort Analysis of the NAGALA Study

BACKGROUND

The duration of sleep might be a risk factor for chronic kidney disease (CKD). We investigated the relationship between sleep duration and incident CKD.

METHODS

In this retrospective cohort study of 7,752 men and 6,722 women, we divided the subjects into 4 groups according to sleep duration, i.e., those whose reported regular sleep duration was <6 h (the "<6 h group"), those whose sleep duration was >6 but <7 h (the "6 to <7 h group"), those with a sleep duration of 7 to <8 h (the "7 to <8 h group"), and those with ≥8 h sleep (the "≥8 h group"). CKD was defined as the presence of proteinuria and/or an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. The HR of the 4 groups for incident CKD were calculated with a Cox proportional hazards model, with the 7 to <8 h group set as the reference.

RESULTS

Incident CKD was detected in 1,513 (19.5%) men and 688 (10.2%) women over the median follow-up period of 7.0 (3.3-11.9) years in the men and 6.7 (3.1-10.8) years in the women. There was no association between sleep duration and incident CKD in the women. In the men, the HR of incident CKD was 0.54 (95% CI 0.45-0.64, p < 0.001) in the <6 h group, 0.73 (95% CI 0.66-0.82, p < 0.001) in the 6 to <7 h group, and 0.93 (95% CI 0.78-1.11, p = 0.433) in the ≥8 h group.

CONCLUSION

The risk of incident CKD is lowest in those who sleep <6 h. We revealed that the risk of incident CKD is lowest in those who sleep <6 h among apparently healthy men.

Impact of Transition in Metabolic Health and Obesity on the Incident Chronic Kidney Disease: A Nationwide Cohort Study

CONTEXT

Metabolically healthy obesity (MHO) is a dynamic condition.

OBJECTIVE

To evaluate the risk of chronic kidney disease (CKD) among people with MHO according to its longitudinal change.

DESIGN

Observational study.

SETTING

A nationwide population-based cohort.

PARTICIPANTS

A total of 514 866 people from the Korean National Health Insurance Service-National Sample Cohort.

INTERVENTION

The initial presence and changes of obesity (using body mass index [BMI] and waist circumference [WC]) and metabolic health status.

MAIN OUTCOME MEASURE

Incident CKD from 2011 to 2015.

RESULTS

Of the people classified as MHO at baseline (BMI criteria), 47.6% remained as MHO in 2011 and 2012, whereas 12.1%, 5.5%, and 34.8% were classified as metabolically healthy, non-obese (MHNO), metabolically unhealthy, non-obese, and metabolically unhealthy, obese, respectively. The risk of incident CKD in the baseline MHO group was higher than that in the MHNO group (hazard ratio, 1.23; 95% confidence interval, 1.12-1.36). However, when transition was taken into account, people who converted to MHNO were not at increased risk (hazard ratio, 0.98; 95% confidence interval, 0.72-1.32), whereas the stable MHO group and the groups that evolved to metabolically unhealthy status had a higher risk of incident CKD than the stable MHNO group. When the risk was analyzed using WC criteria, it showed a similar pattern to BMI criteria except for the stable MHO group.

CONCLUSIONS

MHO was a dynamic condition, and people with MHO constituted a heterogeneous group. Although the MHO phenotype was generally associated with incident CKD, maintenance of metabolic health and weight reduction might alleviate the risk of CKD.

Impact of metabolically healthy obesity on the risk of incident gastric cancer: a population-based cohort study

BACKGROUND

The risk of colon or breast cancer in metabolically healthy obese (MHO) were lower than that in metabolically abnormal obese (MAO). We hypothesized that the risk of incident gastric cancer in MHO is lower than that in MAO.

METHODS

This historical cohort study included 19,685 Japanese individuals who received health-checkup programs from 2003 to 2016. Each subject was classified as metabolically healthy (MH) (no metabolic abnormalities) or metabolically abnormal (MA) (one or more metabolic abnormalities), according to four metabolic factors (hypertension, impaired fasting glucose, hypertriglyceridemia and low HDL-cholesterol). Obese (O) or non-obese (NO) was classified by a BMI cutoff of 25.0 kg/m². Hazard ratios of metabolic phenotypes for incident gastric cancer were calculated by the Cox proportional hazard model with adjustments for age, sex, alcohol consumption, smoking and exercise.

RESULTS

Over the median follow-up period of 5.5 (2.9-9.4) years, incident rate of gastric cancer was 0.65 per 1000 persons-years. Incident rate of MHNO, MHO, MANO and MAO were 0.33, 0.25, 0.80 and 1.21 per 1000 persons-years, respectively. Compared with MHNO, the adjusted hazard ratios for development of gastric cancer were 0.69 (95% CI 0.04-3.39, p = 0.723) in MHO, 1.16 (95% CI 0.63-2.12, p = 0.636) in MANO and 2.09 (95% CI 1.10-3.97, p = 0.024) in MAO.

CONCLUSIONS

This study shows that individuals with MAO, but not those with MHO, had an elevated risk for incident gastric cancer. Thus, we should focus more on the presence of metabolic abnormalities rather than obesity itself for incident gastric cancer.

Metabolic Surgery to Treat Obesity in Diabetic Kidney Disease, Chronic Kidney Disease, and End-Stage Kidney Disease; What Are the Unanswered Questions?

Obesity is a major factor in contemporary clinical practice in nephrology. Obesity accelerates the progression of both diabetic and non-diabetic chronic kidney disease and, in renal transplantation, both recipient and donor obesity increase the risk of allograft complications. Obesity is thus a major driver of renal disease progression and a barrier to deceased and living donor kidney transplantation. Large observational studies have highlighted that metabolic surgery reduces the incidence of albuminuria, slows chronic kidney disease progression, and reduces the incidence of end-stage kidney disease over extended follow-up in people with and without type 2 diabetes. The surgical treatment of obesity and its metabolic sequelae has therefore the potential to improve management of diabetic and non-diabetic chronic kidney disease and aid in the slowing of renal decline toward end-stage kidney disease. In the context of patients with end-stage kidney disease, although complications of metabolic surgery are higher, absolute event rates are low and it remains a safe intervention in this population. Pre-transplant metabolic surgery increases access to kidney transplantation in people with obesity and end-stage kidney disease. Metabolic surgery also improves management of metabolic complications post-kidney transplantation, including new-onset diabetes. Procedure selection may be critical to mitigate the risks of oxalate nephropathy and disruption to immunosuppressant pharmacokinetics. Metabolic surgery may also have a role in the treatment of donor obesity, which could increase the living kidney donor pool with potential downstream impact on kidney paired exchange programmes. The present paper provides a comprehensive coverage of the literature concerning renal outcomes in clinical studies of metabolic surgery and integrates findings from relevant mechanistic pre-clinical studies. In so doing the key unanswered questions for the field are brought to the fore for discussion.

FIB-4 Index and Diabetes Mellitus Are Associated with Chronic Kidney Disease in Japanese Patients with Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is associated with chronic kidney disease (CKD). The aim of this retrospective study was to determine the risk factors for progression of CKD in patients with biopsy-proven NAFLD including patatin-like phospholipase domain containing 3 (PNPLA3) polymorphism. A total of 344 patients with biopsy-proven NAFLD were enrolled consecutively in this study. Multivariate analysis identified males (odds ratio (OR) 5.46), age (per 1 year, OR 1.07), and FIB-4 index (≥1.30, OR 3.85) as factors associated with CKD. Of the 154 patients with a baseline estimated glomerular filtration rate (eGFR) ≥60 mL/min, 30 had a deterioration in CKD stage and 15 developed CKD after 3 years. Multivariate analysis identified diabetes mellitus (OR 2.44) as a risk factor for deterioration in CKD stage, while diabetes mellitus (OR 21.54) and baseline eGFR (per 1 mL/min OR 0.88) were risk factors for development of CKD. PNPLA3 did not affect the change in eGFR. In NAFLD patients, a high FIB-4 index was associated with CKD to increases in the index linked to reductions in eGFR. In order to prevent development of CKD, an appropriate therapy focusing on renal function is needed for NAFLD patients, especially those with diabetes.

Association between metabolic body composition status and risk for impaired renal function: A cross-sectional study

BACKGROUND

The risk for obesity-related disorders is proportional to the visceral region and had been observed to be highly related with impaired renal function. In the current study, we aimed to evaluate renal function impairment, according to sex, age, and different status of metabolic body composition.

METHODS

We retrospectively collected from the medical records the basic information and metabolic titers of Chinese adults (13,373 men and 10,175 women) who underwent health checkup from 2013 to 2016. The population was divided into four groups, according to metabolic body composition, including metabolic healthy norms-weight (MHNW), metabolic healthy obesity (MHO), metabolic unhealthy norms-weight (MUNW), and metabolic unhealthy obesity (MUO). The categorical data were compared among the groups and logistic regression analyses were conducted to investigate the association between metabolic body composition status and risk for renal function impairment.

RESULTS

Across all ages in both sexes, the odds ratios (OR) for renal function impairment were higher in the MHO, MUNW, and MUO groups than in the MHNW group, except for women <45 years old in the MUNW group. However, after adjustment, the trend was no longer significant in all groups under 45 years old. For individuals >45 years old, the relatively high risk for renal function impairment remained significantly associated with the MUNW group (OR 2.95, 95% CI 2.02-4.30 in men and OR 1.95, 95% CI 1.35-2.82 in women) and MUO group (OR 2.33, 95% CI 1.82-3.00 in men and OR 2.67, 95% CI 2.04-3.48 in women).

CONCLUSION

Impaired renal function was independently associated with the status of metabolic obesity. However, the trend was only observed in individuals >45 years old, with significant sex difference.

Metabolically Healthy Obesity and Risk of Incident Chronic Kidney Disease in a Korean Cohort Study

BACKGROUND

The incident of chronic kidney disease (CKD) of metabolically healthy obesity (MHO) has not been consistently determined.

METHODS

This study used data of Anseong Ansan community-based cohort, a part of the Korean Genome and Epidemiology Study (KoGES) provided by the Korea Center for Disease Control and Prevention (KCDC). Surveys were received from the Anseung and Ansan residents every two years between 2001-2002 and 2015-2016 for a total of 7 surveys over all. The subjects were divided into 4 phenotypes based on the presenting obesity and metabolic syndrome; 1) metabolically healthy normal weight (MHNW), 2) metabolically healthy obesity (MHO), 3) metabolically abnormal normal weight (MANW), and 4) metabolically abnormal obesity (MAO). Data were analyzed using the Cox proportional hazards regression model.

RESULTS

Of 8,865 subjects, 1,551 cases of 49,995 person-year (3.1%) developed incident CKD. At an adjusted hazard ratio (HR) of 1.13, the MHO group was not associated with a higher risk of incident CKD (95% confidence interval (CI): 0.92-1.41, P =0.234, using MHNW as the reference). The adjusted HRs of the MANW and MAO groups for incident CKD were significantly higher than those of the MHNW groups: 1.31 (95% CI: 1.05-1.64, P=0.017) for MANW and 1.49 (95% CI: 1.23-1.79, P<0.001) for MAO.

CONCLUSION

MHO is not associated with a high risk of CKD, and that MANW and MAO increase the risk of the incident CKD. Thus, it is important to consider metabolic health status rather than obesity when evaluating CKD risk.

The Iberian pig fed with high-fat diet: a model of renal disease in obesity and metabolic syndrome

BACKGROUND

The pathogenesis of renal disease in the context of overweight/obesity, metabolic syndrome, and insulin resistance is not completely understood. This may be due to the lack of a definitive animal model of disease, which limits our understanding of obesity-induced renal damage. We evaluated the changes in renal histology and lipid deposits induced by obesity in a model of insulin resistance: the Iberian swine fed with fat-enriched food.

METHODS

Twenty-eight female sows were randomized to standard (SD) or high-fat diet (HFD: 6.8% of saturated fat) for 100 days. Weight, adiposity, analytics, oral glucose tolerance tests, and measured renal function were determined. Renal histology and lipid deposits in renal tissue were analyzed.

RESULTS

Animals on HFD developed obesity, hypertension, high levels of LDL cholesterol, triglycerides, insulin resistance, and glomerular hyperfiltration. No animal developed overt diabetes. Animals on HFD showed "diabetoid changes", including mesangial expansion [21.40% ± 4 vs.13.20% ± 4.0, p < 0.0001], nodular glomerulosclerosis [7.40% ± 7, 0.75 vs. 2.40% ± 4.7, p = 0.02], and glomerulomegaly (18% vs. 10%, p = 0.010) than those on SD. Tubular atrophy, interstitial fibrosis, inflammation, arteriolar hyalinosis, or fibrointimal thickening were mild and similar between groups. Triglyceride content in renal tissue was higher in animals on HFD than in SD (15.4% ± 0.5 vs. 12.7% ± 0.7; p < 0.01).

CONCLUSIONS

Iberian pigs fed with fat-enriched food showed diabetoid changes and glomerulomegaly as observed in obese humans making this model suitable to study obesity-induced renal disease.

Metabolic phenotypes of obese, overweight, and normal weight individuals and risk of chronic kidney disease: a systematic review and meta-analysis

OBJECTIVE

Chronic kidney disease (CKD) risk is inconsistent in the normal-weight, overweight, and obese individuals due to the heterogeneity of metabolic status. This meta-analysis aimed to examine the combined effects of body mass index (BMI) and metabolic status on CKD risk.

MATERIALS AND METHODS

The MEDLINE, EMBASE, and Web of Knowledge databases were systematically searched up to March 2019 to identify all eligible studies investigating the CKD risk (defined as GFR < 60 mL/min per 1.73 m2 and/or microalbuminuria or proteinuria) associated with the body size phenotypes which are known as metabolically unhealthy normal-weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight, metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO). The classification of subjects in included studies as metabolically unhealthy was based on the presence of three components of metabolic syndrome. BMI categorization was based on the criteria of included studies. The risk estimates and 95% confidence intervals (CIs) were extracted and pooled using random effects analysis.

RESULTS

A total of 9 prospective cohort studies with 128773 participants and 4797 incident cases were included in the meta-analysis. Compared with healthy normal-weight individuals as reference, MUNW and MHO subjects showed an increased risk for CKD events with a pooled RR of 1.58 (95% CI = 1.28-1.96) in MUNW and 1.55 (95% CI = 1.34-1.79) in MHO persons. Also, MHOW was at increased risk for CKD (RR = 1.34, 95% CI = 1.20-1.51). MUHO individuals were at the highest risk for the development of CKD (RR = 2.13, 95% CI = 1.66-2.72).

CONCLUSIONS

Individuals with metabolic abnormality, although at normal-weight, have an increased risk for CKD. Healthy overweight and obese individuals had higher risk; refuting the notion that metabolically healthy overweight and obese phenotypes are benign conditions.

Strong association between metabolically-abnormal obesity and gallstone disease in adults under 50 years

BACKGROUND

Age, obesity, and metabolic syndrome are known risk factors for gallstones; however, the combined impact of these different risk factors on gallstone formation has not yet been examined.

METHODS

This retrospective, cross-sectional study involved 3190 participants, including 207 participants (6.5%) with gallstones and 986 (30.9%) with metabolic syndrome. Participants were divided into four phenotypes according to metabolic syndrome and obesity status: 1378 participants were metabolically healthy and non-obese (MHNO); 826 were metabolically healthy but obese (MHO); 185 were metabolically abnormal but not obese (MANO); and 801 participants were metabolically abnormal and obese (MAO).

RESULTS

The MAO and MANO phenotypes had more gallstones than the MHO and MHNO phenotypes, regardless of age (< 50 or ≥ 50 years old). Multivariate analyses showed that phenotype was an independent risk factor for gallstones in participants < 50 years old (odds ratio (OR) = 1.73, 95% confidence interval (CI) = 1.32-2.28). Younger participants also had a higher risk of gallstones in the MAO (OR = 5.41, 95% CI = 2.31-12.66), MANO (OR = 3.18, 95% CI = 0.86-11.75), and MHO (OR = 2.17, 95% CI = 0.90-5.22) phenotypes than the MHNO phenotype.

CONCLUSIONS

Our retrospective results demonstrate an increased association of gallstones in younger people (< 50 years old) with metabolic syndrome and obesity.

Protein intake is not associated with progression of diabetic kidney disease in patients without macroalbuminuria

BACKGROUND

Diabetic kidney disease is an important problem in individuals with diabetes. The effect of dietary protein intake on the renal function of patients with diabetes is controversial. Here, we sought to clarify the association between dietary protein intake and changes in the urinary albumin excretion (UAE) or estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes.

METHODS

In this retrospective cohort study, we included 144 patients (70 men, mean ± standard deviation of age 64 ± 10 years, and median (interquartile range) of UAE 15.0 (7.0-38.9) mg/gCr) without an eGFR less than 30 mL/min/1.73 m² and/or UAE greater than or equal to 300 mg/gCr. Changes in the UAE or eGFR were defined as (logarithms [UAE+1] or eGFR at follow-up minus logarithms [UAE+1] or eGFR at baseline examination)/follow-up duration (years). Habitual protein intake was estimated by a self-administered diet history questionnaire.

RESULTS

The median follow-up duration was 5 years. Protein intake (g/kg ideal body weight/day) was not associated with the change in the UAE (r = -0.130, p = 0.120) or change in the eGFR (r = -0.074, p = 0.381). Multiple linear regression analyses showed that after adjusting for covariates, the patients' protein intake was not associated with change in their UAE (standardized regression coefficient: 0.044, p = 0.732) or change in their eGFR (standardized regression coefficient: 0.250, p = 0.085).

CONCLUSIONS

Dietary protein intake does not influence changes in the UAE or eGFR among patients with type 2 diabetes without macroalbuminuria.

Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study

AIMS/INTRODUCTION

Metabolic unhealth can be defined by the components of metabolic syndrome, which is closely connected to insulin resistance. We aimed to determine a simple index to identify metabolic unhealth in the Chinese adult population.

MATERIALS AND METHODS

A total of 30,291 individuals were screened from the China National Diabetes and Metabolic Disorders Study carried out from June 2007 to May 2008. Metabolic unhealth was defined using components of metabolic syndrome, except waist circumference. We compared the three surrogate indices of insulin resistance: the product of fasting triglycerides and glucose (TyG), triglycerides divided by high-density lipoprotein cholesterol and the metabolic score for insulin resistance for the evaluation of metabolic status.

RESULTS

All indices had high sensitivity and specificity for the identification of metabolic unhealth, especially the TyG index with an area under the curve of 0.863 for men and 0.867 for women. Participants were divided into subgroups for further analysis. The TyG index also showed high diagnostic values, especially for younger individuals and men with normal waist circumference. Sex-specific cut-offs for three indices were also used to define metabolic unhealth. The TyG index showed the highest agreement with κ values of 0.603 and 0.605 for men and women between the components of metabolic syndrome and three indices.

CONCLUSIONS

We propose that the TyG index, just read in one blood laboratory test report, is simpler and more suitable for the identification of metabolically unhealthy individuals as well as who have high risk of cardiometabolic diseases of the Chinese adult population.

Effect of Metabolically Healthy Obesity on the Development of Carotid Plaque in the General Population: A Community-Based Cohort Study

Aim: Obesity and metabolic syndrome (MetS) frequently coexist and are both important risk factors for cardiovascular disease. However, the pathophysiological role of obesity without MetS, also referred to as metabolically healthy obesity (MHO), remains unclear. In this study, we aim to clarify the effect of MHO on the development of carotid plaque using a community-based cohort.

Methods: We examined 1,241 subjects who underwent health checkups at our institute. Obesity was defined as body mass index of ≥ 25.0 kg/m². Subjects were divided into three groups: non-obese, MHO, and metabolically unhealthy obesity (MUO).

Results: The prevalence of carotid plaque, defined as intima-media thickness (IMT) ≥ 1.1 mm, was higher in subjects with MUO and MHO than in non-obese subjects. Multivariable analysis demonstrated that MHO (odds ratio 1.6, p = 0.012) and MUO (odds ratio 1.9, p = 0.003) as well as age of ≥ 65 years, male sex, hypertension, and diabetes mellitus were independently associated with carotid plaque formation. A similar trend was observed in each subgroup according to age and sex.

Conclusions: MHO increased the prevalence of carotid plaque when compared with non-obese subjects, suggesting the potential significance of MHO in the development of subsequent cardiovascular diseases.

The Association between Obesity Phenotypes and Early Renal Function Decline in Adults without Hypertension, Dyslipidemia, and Diabetes

Background

The prevalence of chronic kidney disease is increasing worldwide. Several studies have suggested that obesity is associated with early renal dysfunction. However, little is known about the relationship between obesity phenotypes and early renal function decline. Therefore, this study aimed to identify the relationship between obesity phenotypes and early renal function decline in adults without hypertension, dyslipidemia, and diabetes.

Methods

We conducted a cross-sectional analysis of clinical and anthropometric data from 1,219 patients who underwent a routine health checkup in 2014. We excluded adults with cardiovascular disease, renal disease, diabetes, hypertension, dyslipidemia, or low glomerular filtration rate (<60 mL/min/1.73 m²). Renal function was determined according to the estimated glomerular filtration rate calculated using the Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin C equation.

Results

Age, sex, body mass index, waist circumference, triglyceride, low-density lipoprotein, and fasting glucose had an association with the estimated glomerular filtration rate. After adjusting for age, sex, smoking status, and alcohol intake, the odds ratios of the metabolically abnormal normal weight and metabolically abnormal obese phenotypes for the presence of low estimated glomerular filtration rates were 1.807 (95% confidence interval, 1.009– 3.236) and 1.834 (95% confidence interval, 1.162–2.895), compared with the metabolically healthy normal weight phenotype. However, the metabolically healthy obese phenotype did not show a significant association with early renal function decline.

Conclusion

In this cross-sectional study, we confirmed the association between the metabolically abnormal normal weight and metabolically abnormal obese phenotypes and early kidney function decline in adults without hypertension, dyslipidemia, and diabetes.

Obesity without metabolic disorder and silent brain infarcts in aneurologically healthy population

OBJECTIVE

Obesity without metabolic disorder [Ob(+)MD(-)] is a unique subcategory of obesity where individuals are protected from the obesity-related complications. Although conflicting clinical outcomes have been reported, there has been no study of the effects of Ob(+)MD(-) on cerebrovascular disease. In this study, we evaluated the association between the Ob(+)MD(-) phenotype and silent brain infarcts (SBI) in a neurologically healthy population.

SUBJECTS/METHODS

We evaluated a consecutive series of healthy volunteers recruited between January 2006 and December 2013. MD(-) status was assessed using five clinical markers: blood pressure, triglycerides, high-density lipoprotein, fasting plasma glucose, and waist circumference. Obesity was defined when body mass index ≥ 25 kg/m². SBI was defined as asymptomatic, well-defined lesions with a diameter ≥ 3 mm with the same signal characteristics as the cerebrospinal fluid on T1- or T2-weighted images.

RESULTS

A total of 3165 subjects were assessed, and 262 (8%) SBI cases were identified. In multivariate analyses, non-obesity with metabolic disorder [Ob(-)MD(+)] (adjusted odds ratio [aOR] = 1.65, 95% confidence interval [CI] = 1.07-2.56, P = 0.025) and obesity with metabolic disorder [Ob(+)MD(+)] (aOR = 1.75, 95% CI = 1.12-2.75, P = 0.014) were closely associated with SBI after adjustment for confounders. Meanwhile, Ob(+)MD(-) did not show any significant association with SBI (aOR = 0.85, 95% CI = 0.20-3.72, P = 0.832). These findings may indicate that metabolic abnormality, irrespective of obesity status, is a main risk factor of SBI. When we compared SBI burdens between the four metabolic phenotypes, the Ob(+)MD(+) and Ob(-)MD(+) groups had higher rates of multiple lesions than the Ob(+)MD(-) and non-obesity without metabolic disorder groups.

CONCLUSIONS

The presence of metabolic abnormality, and not obesity per se, is independently associated with the prevalence of SBI in a healthy population.

Triglyceride-glucose index is a predictor of incident chronic kidney disease: a population-based longitudinal study

BACKGROUND

Insulin resistance is one of the risks of chronic kidney disease (CKD). The triglyceride-glucose index (TyG index) has been suggested as a marker of moderate insulin resistance. We aimed to investigate the association between TyG index and incident CKD.

METHODS

In this historical cohort study of 11,712 participants (6026 men and 5686 women), we investigated the impact of TyG index on incident CKD. CKD was defined as estimated GFR less than 60 mL/min/1.73 m² and/or proteinuria detected by dipstick test in fasting morning urine. TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2]. Cox proportional hazard models were performed to investigate the impact of TyG index on incident CKD, adjusting for age, BMI categories, waist circumference, smoking status, exercise, logarithm of alcohol consumption, systolic blood pressure, serum albumin, hemoglobin A1c, hyperuricemia, low HDL-cholesterol concentration, high LDL-cholesterol concentration, CRP, creatinine, and gamma-glutamyltransferase.

RESULTS

During the median 4.0-year follow-up duration for men and 3.7-year follow-up duration for women, 261 participants (120 men and 141 women) developed CKD. In Cox proportional hazard model, TyG index presented the significant risks for incident CKD in both men and women (men, hazard ratio 1.32, 95% confidence interval 1.02-1.70, p = 0.036, women, hazard ratio 1.50, 95% confidence interval 1.05-2.13, p = 0.024).

CONCLUSION

This study revealed that TyG index can be a predictor of incident CKD.

Association of Variability in Body Mass Index and Metabolic Health With Cardiometabolic Disease Risk

Background Metabolic syndrome is associated with high risk of cardiovascular disease, although risk may differ according to the specific conditions present and variability in those conditions. Methods and Results We defined obesity (body mass index [BMI] ≥30 kg/m2) and metabolic health (<2 nonobesity National Cholesterol Education Program Adult Treatment Panel III conditions) among 3632 Framingham Heart Study offspring cohort participants (mean age, 50.8 years; 53.8% women) who were followed up from 1987 to 2014. We defined participants whose variance independent of the mean for a metabolic syndrome-associated measure was in the top quintile as being "variable" for that measure. Variable metabolic health was defined as ≥2 variable nonobesity metabolic syndrome components. We investigated the interaction between obesity and metabolic health in their associations with cardiometabolic disease and cardiovascular disease using Cox proportional hazards regression. In addition, we estimated the associations of BMI variability and variable metabolic health with study outcomes within categories of obesity and metabolic health status, respectively. We observed 567 incident obesity (41 439 person-years), 771 incident metabolically unhealthy state (25 765 person-years), 272 incident diabetes mellitus (56 233 person-years), 503 incident hypertension (12 957 person-years), 589 cardiovascular disease (60 300 person-years), and 195 chronic kidney disease (47 370 person-years) events on follow-up. Obesity and being metabolically unhealthy were independently and positively associated with all outcomes. BMI variability, compared with stable BMI, was associated with 163%, 67%, 58%, and 74% higher risks of having obesity, becoming metabolically unhealthy, having diabetes mellitus, and having hypertension, respectively, among nonobese participants. Variable metabolic health, compared with stable metabolic health, was associated with a 28% higher risk of cardiovascular disease, among metabolically healthy participants. Conclusions We did not observe evidence for a positive interaction between obesity and metabolic health status with regard to study outcomes. BMI and metabolic health variability are associated with adverse health outcomes.

MC4R Single Nucleotide Polymorphisms Were Associated with Metabolically Healthy and Unhealthy Obesity in Chinese Northern Han Populations

Melanocortin-4 receptor (MC4R) has been reported to be associated with the risk of obesity, and metabolically unhealthy obese (MUHO) patients tend to have a greater risk of cardiovascular complications than metabolically healthy obese (MHO) patients. Therefore, we aimed to study single nucleotide polymorphisms (SNPs) in the MC4R gene associated with metabolically healthy and unhealthy obesity in Chinese Northern Han populations. A total of 1100 Chinese Northern Han subjects were recruited and divided into four groups according to the criteria of the Adult Treatment Panel-III (ATP-III) and World Health Organization (WHO): MUHO (n = 300), MHO (n = 196), metabolic unhealthy normal weight (MUH-NW) (n = 303), and metabolic healthy normal weight (MH-NW) (n = 301). DNA samples were extracted, and six SNPs of the MC4R gene, including rs2331841, rs656710, rs17782313, rs571312, rs12970134, and rs11872992, were genotyped with the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) method. Among the six SNPs of the MC4R gene, rs2331841 (A/G) was the most significant and could account for 0.9% of obesity etiology. Compared with the normal weight group, rs2331841 of the MC4R gene was associated with obesity (P=0.032). The obesity risk of subjects with the AG genotype in the rs2331841 site was 82% higher than the risk of those with the GG genotype (β = 0.60, OR = 1.82, P=0.030). After adjusting for sex and age, the frequency of the A allele in the rs2331841 site was higher in the MUHO group than in the MH-NW group (27.9% vs. 21.1%, respectively, OR = 1.49, 95% CI 1.14-1.96, P=0.005) and in the MUHO group than in the MHO group (27.9% vs. 22.3%, respectively, OR = 1.39, 95% CI 1.02-1.92, P=0.039). Among the three genotypes of rs2331841, the subjects with the AA/AG genotype had higher diastolic blood pressure (DBP) than those with the GG genotype. Our data first suggest that SNPs in the rs2331841 site of the MC4R gene are closely related to obesity and its related metabolic disorders in Chinese Northern Han populations. The participants with an A allele of rs2331841 had a higher risk of obesity and MUHO than other participants.

Changes in obese metabolic phenotypes over time and risk of incident chronic kidney disease

AIM

To examine the association between metabolically healthy obese (MHO) phenotype and incident chronic kidney disease (CKD) and study whether changes in metabolic phenotypes over time could affect CKD risk.

METHODS

A total of 8589 subjects from the Korean Genome and Epidemiology Study were categorized into four groups based on the presence of obesity and metabolic abnormalities (MA). The primary endpoint was an onset of incident CKD defined as an estimated glomerular filtration rate of ≤ 60 mL/min/1.73 m² . Multivariable Cox analysis and time-varying Cox analysis were performed to delineate the relationship between obese metabolic phenotypes and incident CKD after adjustment for sociodemographic factors and clinical and laboratory parameters.

RESULTS

During a mean follow-up duration of 9.3 years, CKD occurred in 782 (9.1%) participants. In the multivariable Cox model, the hazard ratio (HR) for incident CKD in the MHO, metabolically abnormal non-obese (MANO), and metabolically abnormal obese (MAO) groups was 1.42 (P = 0.002), 1.45 (P < 0.001), and 1.77 (P < 0.001), respectively, compared with the metabolically healthy non-obese (MHNO) group. Time-varying analysis with these four phenotypes as time-varying exposures showed the same results. Furthermore, subjects with persistent MHO through follow-up were at a 2.0-fold increased risk of CKD (P < 0.001). 41.0% of subjects experienced phenotype changes during follow-up. Over the long term, the MHO group had a higher proportion of transition to the MA phenotype and unfavourable metabolic profiles than the MHNO group. Among MHO subjects, those who transitioned to MAO were at a 4.1-fold increased risk of incident CKD than those who regressed to MHNO. In addition, transition to MHO from other groups carried a higher risk of CKD than persistent MHNO.

CONCLUSION

MHO subjects are at increased risk for incident CKD.

Low urine pH is a risk for non-alcoholic fatty liver disease: A population-based longitudinal study

BACKGROUND

Low urine pH has a close association with insulin resistance. This study was aimed to investigate the association between urine pH and incident non-alcoholic fatty liver disease (NAFLD), which is associated with insulin resistance.

SUBJECTS AND METHODS

In this historical cohort study of 11,012 participants (5503 men and 5509 women), we investigated the effect of urine pH on incident NAFLD. NAFLD was defined as having fatty liver diagnosed by abdominal ultrasonography and excluding the participants consumed ethanol over 60g/day for men and 40g/day for women. We divided the participants into three groups according to urine pH; the lowest group (urine pH≤5.5), the middle group (urine pH=6.0) and the highest group (urine pH≥6.5). Cox proportional hazards models was performed to investigate the effect of urine pH on incident NAFLD, adjusting for age, sex, body mass index, smoking, exercise, alcohol consumption, alanine aminotransferase, triglycerides, systolic blood pressure, uric acid and fasting plasma glucose.

RESULTS

Over the median 6.8-year follow-up duration, 2023 participants developed NAFLD, and the crude proportions were 20.3% (case/N=1104/5447) in the lowest urine pH group, 16.3% (487/2989) in the middle urine pH group and 16.8% (432/2576) in the highest urine pH group. The lowest urine pH group showed a significantly higher risk for incident NAFLD than the highest urine pH group (adjusted hazard ratio 1.48, 95% confidence interval 1.31-1.66, P<0.001).

CONCLUSION

Low urine pH is associated with incident NAFLD. Our findings indicate that urine pH can be an additional data when considering further diagnostic investigation for NAFLD in patients who have other risk factors.

Preventive Nephrology: The Role of Obesity in Different Stages of Chronic Kidney Disease

BACKGROUND

Obesity is increasing worldwide and has become a nontraditional risk factor in chronic kidney disease (CKD).

SUMMARY

Obesity-related nephropathy may aggravate renal complications of the metabolic syndrome and progress to advanced CKD stages, while obesity in early stages of CKD is clearly related to the development of kidney disease. A high body mass index (BMI) in advanced CKD stages and dialysis is an advantage for survival (so called "obesity paradox"). A high lean body to fat mass index indicates a beneficial state of body composition. In contrast, loss of muscle mass with increasing fat mass causes "sarcopenia obesity," which is related to unfavorable outcomes in renal replacement therapy. Obesity (BMI > 30-35) in renal transplant recipients is associated with a higher risk of complications such as delayed graft function, increased rates of rejection, and graft loss. While conservative management of morbid obesity is failing in most cases, bariatric surgery seems to be an option in some cases to improve renal complications in the early stage of CKD or in transplant candidates.

KEY MESSAGE

In conclusion, obesity is increasingly prevalent among CKD patients. Adequate management with respect to the specific role of obesity in different stages of CKD should be integrated in routine renal care.

Impact of respiratory function on the progression from metabolically healthy non-overweight to metabolically abnormal phenotype

BACKGROUND AND AIMS

Recent studies identified that metabolically abnormal non-overweight phenotype is a risk factor for cardiovascular diseases. However, only little is known about risk factors for the progression from metabolically healthy non-overweight (MHNO) to metabolically abnormal phenotype. In this study, we investigated the impact of respiratory function on the progression from MHNO to metabolically abnormal phenotype.

METHODS AND RESULTS

In this retrospective cohort study, 8949 (3872 men and 5077 women) individuals with MHNO, who participated in a health-checkup program from 2004 to 2015, were enrolled. Four metabolic factors (high-normal blood pressure or hypertension, impaired fasting glucose or diabetes, hypertriglyceridemia, and low HDL cholesterol concentration) were used to define metabolically healthy (less than two factors) or metabolically abnormal (two or more factors) phenotypes. Respiratory function was measured by spirometry. Over a median 4.0 years of follow-up, 927 participants progressed to metabolically abnormal phenotype. The percentage of FVC for predicted values (HR 0.98, 95% CI 0.93-1.03, p = 0.418) was not associated with the progression to metabolically abnormal phenotype after adjusting for covariates, including age, sex, alcohol consumption, exercise, smoking status, and body mass index, whereas the percentage of FEV₁ for predicted values (%FEV₁) (HR 0.87, 95% CI 0.84-0.91, p < 0.001) and the FEV₁/FVC ratio (HR 0.86, 95% CI 0.78-0.95, p = 0.004) were associated with the progression to metabolically abnormal phenotype.

CONCLUSION

Decrease in respiratory function in terms of %FEV₁ and the FEV₁/FVC ratio is associated with the progression to metabolically abnormal phenotype in individuals with MHNO.

The Association Between Metabolically Healthy Obesity and the Risk of Proteinuria: The Kansai Healthcare Study

Background

Metabolically healthy obesity seems to be a unique phenotype for the risk of cardiometabolic diseases. However, it is not known whether this phenotype is associated with the risk of proteinuria.

Methods

Study subjects were 9,185 non-diabetic Japanese male workers aged 40–55 years who had no proteinuria, an estimated glomerular filtration rate ≥60 mL/min/1.73 m², no history of cancer, and no use of antihypertensive or lipid-lowering medications at baseline. Obesity was defined as body mass index ≥25.0 kg/m². Metabolic health was defined as the presence of no Adult Treatment Panel III components of the metabolic syndrome criteria, excluding waist circumference, and metabolic unhealth was defined as the presence of one or more metabolic syndrome components, excluding waist circumference. “Consecutive proteinuria” was considered positive if proteinuria was detected twice consecutively as 1+ or higher on urine dipstick at annual examinations to exclude chance proteinuria as much as possible.

Results

During the 81,660 person-years follow-up period, we confirmed 390 cases of consecutive proteinuria. Compared with metabolically healthy non-obesity, metabolically healthy obesity was not associated with the risk of consecutive proteinuria (multiple-adjusted hazard ratio [HR] 0.86; 95% confidence interval [CI], 0.37–1.99), but metabolically unhealthy non-obesity with ≥2 metabolic syndrome components (HR 1.77; 95% CI, 1.30–2.42), metabolically unhealthy obesity with one component (HR 1.71; 95% CI, 1.12–2.61), and metabolically unhealthy obesity with ≥2 metabolic syndrome components (HR 2.77; 95% CI, 2.01–3.82) were associated with an increased risk of consecutive proteinuria.

Conclusions

Metabolically healthy obesity did not increase the risk of consecutive proteinuria in Japanese middle-aged men.

Metabolically healthy obesity and risk of leukoaraiosis; a population based cross-sectional study

Metabolically healthy obese (MHO) individual is known to be defended from the metabolic complications of obesity. Leukoaraiosis, which is commonly detected on brain magnetic resonance imaging (MRI), is now recognized as a risk of stroke, dementia and death. However, the association between MHO and the prevalence of leukoaraiosis is unclear. In this cross-sectional study of 796 participants who received a medical examination program, we investigated the association between MHO and the prevalence of leukoaraiosis. We used common clinical markers for definition of metabolic healthy status: blood pressure, fasting plasma glucose, triglycerides and high-density lipoprotein cholesterol concentrations. Obesity was defined by body mass index ≥25.0 kg/m². We diagnosed leukoaraiosis by fluid-attenuated inversion recovery without hypointensity on T1-weighted images or the presence of a hyperintensity on T2-weighted images. The crude prevalence proportion of leukoaraiosis was 44.5% (case/n = 171/384) in metabolically healthy nonobese (MHNO) individual, 46.3% (44/95) in MHO individual, 62.3% (114/183) in metabolically unhealthy nonobese (MUNO) individual or 56.6% (77/136) in MUO individual. The odds ratios of prevalence of leukoaraiosis were 1.19 (95% CI 0.74-1.90, p = 0.471) for MHO, 1.79 (1.22-2.62, p = 0.003) for MUNO and 1.56 (1.03-2.37, p = 0.037) for MUO individuals after adjusting for sex, age, smoking statues, habit of exercise and alcohol, compared with MHNO individual. We revealed that MHO individuals were not related with the higher risk of leukoaraiosis, whereas MUNO and MUO individuals were.

The magnitude of obesity and metabolic syndrome among diabetic chronic kidney disease population: A nationwide study

Background

Although the prevalence of obesity and metabolic syndrome (MetS) among dialysis patients has been exceeding than general population, little is known regarding obesity and MetS in non-dialysis chronic kidney disease (CKD). We aimed to find the magnitude of obesity and MetS and their associations with impaired renal function among type 2 diabetes mellitus (T2DM) patients.

Methods

A national survey of T2DM patients was collected in the Thai National Health Security Office database during 2014–5. The sampling frame was designated as distinct geographic regions throughout the country. A stratified two-stage cluster sampling was used to select the study population. Anthropometry and 12-hour fasting blood samples were obtained by trained personnel. BMI of ≥25 kg/m² was classified as obesity. MetS was defined as having elevated waist circumference (>90 and >80 cm in men and women, respectively) plus any two of the followings: triglyceride ≥150 mg/dL, HDL-C <40 in men or <50 mg/dL in women, blood pressure ≥130/85 mmHg, and fasting blood sugar ≥100 mg/dL. CKD was defined as an impaired renal function (eGFR <60 mL/min/1.73m² according to the CKD-EPI equation). Logistic regression analysis was performed to examine the relationship between obesity and MetS with the presence of CKD.

Results

A total of 32,616 diabetic patients were finally recruited from 997 hospitals. The mean age was 61.5±10.9 years with 67.5% women. Of the participants, 35.4% were CKD patients. The prevalence of obesity was 46.5% in CKD and 54.1% in non-CKD patients with T2DM (p<0.001). In contrast, the prevalence of MetS in CKD patients was higher than their non-CKD counterparts (71.3 vs 68.8%, p<0.001). Moreover, there was an association between the prevalence of MetS with CKD stage from 3a to 5 (70.1, 72.3, 73.4, and 72.7%, respectively, p trend = 0.02). MetS, but not obesity, had a significant association with CKD in T2DM patients after adjusting for age, sex, and comorbidities [OR 1.14; 95% CI 1.06–1.22, p<0.001]. When stratified by each component of MetS, only high serum triglyceride and low HDL-C levels were increased in patients with CKD stage 4 and 5 compared with CKD stage 3 (p<0.001) and had a significant relationship with impaired renal function.

Conclusion

There were relatively high prevalences of both obesity and MetS in T2DM patients. A higher prevalence of MetS, but lower prevalence of obesity, was observed among diabetic CKD group compared with their non-CKD counterparts. MetS, as a surrogate of insulin resistance, appeared to be more important than obesity in the development of impaired renal function in diabetic population.

Intake of Carbohydrate to Fiber Ratio Is a Useful Marker for Metabolic Syndrome in Patients with Type 2 Diabetes: A Cross-Sectional Study

BACKGROUND/AIMS

The effect of low carbohydrate diet on human health is still controversial. Whole grain, which is carbohydrate rich in fiber, has protective effects on human health. Thus, we assumed that intake of carbohydrate to fiber ratio has an important role in human health.

METHODS

This is a post-hoc analysis of a cross-sectional study of 164 patients with type 2 diabetes. Habitual food and nutrient intake were assessed and estimated by a self-administered diet history questionnaire. Intake of carbohydrate to fiber ratio was defined as carbohydrate (g)/fiber intake (g). Logistic regression analyses were performed to reveal the association between intake of carbohydrate to fiber ratio and metabolic syndrome (MetS).

RESULTS

Intake of carbohydrate to fiber ratio has closely associated with metabolic parameters, including triglycerides (r = 0.21, p = 0.007) and high-density lipoprotein cholesterol (r = -0.23, p = 0.003). Intake of carbohydrate to fiber ratio was associated with MetS (OR 1.06 [95% CI 1.00-1.13], p = 0.047) after adjusting for covariates, whereas carbohydrate intake (1.00 [0.99-1.01], p = 0.752) or carbohydrate energy/total energy (1.00 [0.94-1.07], p = 0.962) was not associated with MetS.

CONCLUSIONS

Intake of carbohydrate to fiber ratio was associated with MetS, whereas carbohydrate intake was not.

Ectopic fat obesity presents the greatest risk for incident type 2 diabetes: a population-based longitudinal study

OBJECTIVES

Obesity is a risk factor for type 2 diabetes mellitus. Among obesity, visceral fat obesity, and ectopic fat obesity, it has been unclear which has the greatest effect on incident diabetes.

METHODS

In this historical cohort study of 8430 men and 7034 women, we investigated the effect of obesity phenotypes on incident diabetes. Obesity, visceral fat obesity, and ectopic fat obesity were defined as body mass index ≥25 kg/m², waist circumference ≥90 cm in men or ≥80 cm in women, and having fatty liver diagnosed by abdominal ultrasonography, respectively. We divided the participants into eight groups according to the presence or absence of the three obesity phenotypes.

RESULTS

During the median 5.8 years follow-up for men and 5.1 years follow-up for women, 286 men and 87 women developed diabetes. Compared to the non-obese group, the hazard ratios (HRs) of incident diabetes in the only-obesity, only-visceral fat obesity, only-ectopic fat obesity groups, and with all-three types of obesity group were 1.85 (95%CI 1.06-3.26, p = 0.05) in men and 1.79 (0.24-13.21, p = 0.60) in women, 3.41 (2.51-4.64, p < 0.001) in men and 2.30 (0.87-6.05, p = 0.12) in women, 4.74 (1.91-11.70, p < 0.001) in men and 13.99 (7.23-27.09, p < 0.001) in women and 10.5 (8.02-13.8, p < 0.001) in men and 30.0 (18.0-50.0, p < 0.001) in women. Moreover, the risk of incident diabetes of the groups with ectopic fat obesity were almost higher than that of the four groups without ectopic fat obesity.

CONCLUSION

Ectopic fat obesity presented the greatest risk of incident type 2 diabetes.

Late-night-dinner is associated with poor glycemic control in people with type 2 diabetes: The KAMOGAWA-DM cohort study

Skipping breakfast or irregular breakfast is associated with poor glycemic control. However, a relationship between the timing of dinner and glycemic control in people with type 2 diabetes remains indefinite. Therefore, we investigated the relationship between late-night-dinner and glycemic control in people with type 2 diabetes. We performed questionnaire survey for lifestyle factors in this cross-sectional study. We defined having dinner later than eight pm as late-night-dinner. We examined the differences in clinical and metabolic parameters between those who have late-night-dinner and those who do not have. We also examined the relationship between late-night-dinner and HbA1c, using multiple regression analysis. Ninety-five people (23.2%) had a late-night-dinner, among 409 people with type 2 diabetes. Metabolic parameters (mean (SD) or median (interquartile range)) of people with late-night-dinner were worse than those of without, including body mass index (BMI) (24.4 (4.0) vs. 23.2 (3.4) kg/m², p = 0.006), triglycerides (1.5 (1.1-2.1) vs. 1.2 (0.8-1.7) mmol/L, p < 0.001), HDL-cholesterol (1.4 (0.4) vs. 1.6 (0.4) mmol/L, p = 0.004) and hemoglobin A1c (58.1 (13.3) vs. 55.2 (10.2) mmol/mol, (7.5 (1.2) vs. 7.2 (0.9) %), p = 0.023)). Late-night-dinner (standardized regression coefficient = 0.13, p = 0.028) was associated with hemoglobin A1c after adjusting for age, BMI, sex, duration of diabetes, smoking, exercise, alcohol, snacking after dinner, nighttime sleep duration, time from dinner to bedtime, skipping breakfast, and medication for diabetes. Late-night-dinner is independently associated with poor glycemic control in people with type 2 diabetes.

Metabolically Healthy Obesity and Risk of Kidney Function Decline

OBJECTIVE

The aim of this study was to examine the association between BMI categories, stratified by metabolic health status, and the risk of kidney function decline (KFD).

METHODS

In this study, 42,128 adult patients with a stable BMI were classified over a 3-year baseline window by BMI and metabolic health status (assessed by Adult Treatment Panel-III criteria). KFD was defined as an estimated glomerular filtration rate (eGFR) decline ≥ 30%, eGFR < 15 mL/min/1.73 m² , or receipt of dialysis and/or transplant.

RESULTS

Over a median of 5.1 years (interquartile range 2.1-8.9), 6,533 (15.5%) individuals developed KFD. Compared with the normal weight, metabolically healthy category, metabolically healthy obesity was associated with a higher risk of KFD (adjusted hazard ratio [aHR] 1.52; 95% CI: 1.22-1.89). aHRs for KFD were 1.17 (95% CI: 0.89-1.53), 2.21 (95% CI: 1.59-3.08), and 2.20 (95% CI: 1.55-3.11) for metabolically healthy obesity with BMI 30 to 34.9, BMI 35 to 39.9, and BMI ≥ 40 kg/m² . These associations were consistent among men and women, patients with eGFR ≥ or < 90 mL/min/1.73 m² , and age ≥ or < 55 years. The risk of KFD was highest among metabolically unhealthy individuals with BMI ≥ 40 (aHR 4.02; 95% CI: 3.40-4.75 vs. metabolically healthy individuals with normal weight).

CONCLUSIONS

Obesity, whether in the presence or absence of metabolic health, is a risk factor for KFD.

Combined effect of body mass index and metabolic status on the risk of prevalent and incident chronic kidney disease: a systematic review and meta-analysis

OBJECTIVE

The risk of chronic kidney disease (CKD) differs in the normal weight, overweight, and obese individuals owing to metabolic abnormality. We aimed to determine the combined effects of body mass index (BMI) and metabolic status on the risk of the prevalence and incidence of CKD.

METHODS

Pubmed, Scopus, Web of science, and abstracts from recently relevant meetings prior to April 2016 were searched to identify eligible studies. Pooled relative risks (RR) and 95% confidence intervals (CI) were calculated using a random effects model.

RESULTS

Eight cross-sectional studies and four longitudinal follow-up studies with a total of 14787 and 166718 participants were separately included in present study. Compared with metabolically healthy normal weight individuals, metabolically healthy obese individuals showed increased risk for CKD, with RR of 1.235 (95%CI: 1.027 to 1.484), while metabolically health overweight individuals still presented in a healthy pattern, RR=1.094(95%CI: 0.774 to 1.547). In addition, metabolically abnormal groups had much higher risk for CKD, with RR of 1.572 (95%CI: 1.373 to 1.801), 1.652(95%CI: 1.139 to 2.397) and 1.898(95%CI: 1.505 to 2.395) across metabolically unhealthy normal weight, overweight and obese individuals respectively.

CONCLUSION

Individuals with abnormal metabolic status are at a significantly elevated risk for CKD, regardless of BMI. For metabolically healthy individuals, CKD risk increases with the growth of BMI, and obese persons eventually have a higher risk.

Interaction of Metabolic Health and Obesity on Subclinical Target Organ Damage

BACKGROUND

Metabolically healthy obese (MHO) individuals generally show better cardiovascular prognosis compared with metabolically unhealthy counterparts, which may be related to different patterns of target organ damage (TOD). We aimed to investigate the patterns of TOD related to obesity and metabolic unhealthiness.

METHODS

A total of 659 Korean adults (mean age, 60.0 ± 11.8 years; male, 51.1%) undergoing health examinations were stratified into four groups according to obesity (body mass index ≥25.0 kg/m²) and metabolic healthiness (meeting ≤1 criteria of metabolic syndrome excluding abdominal circumference): metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), MHO, and metabolically unhealthy obese (MUO). Four measures of TOD were evaluated: arterial stiffness, renal dysfunction, left ventricular (LV) diastolic dysfunction, and LV hypertrophy (LVH).

RESULTS

In multivariable analyses, compared with the MHNO group, the MHO group showed 2.31 times higher odds for LVH, whereas, the MUNO group showed 3.14 and 6.28 times higher odds for increased arterial stiffness and renal dysfunction, respectively. Metabolic unhealthiness was associated with increased arterial stiffness [odds ratio (OR) 2.73; confidence interval (95% CI) 1.72-4.34], renal dysfunction (OR 4.02; 95% CI 1.54-10.49), and LV diastolic dysfunction (OR 2.28; 95% CI 1.14-4.55). Meanwhile, obesity showed weaker association with LVH and LV diastolic dysfunction, and was not associated with increased arterial stiffness and renal dysfunction in multivariable analyses.

CONCLUSIONS

Metabolic unhealthiness shows more association with TOD than obesity, which may contribute to the higher risk of cardiometabolic abnormalities in MUNO compared with MHO.

Metabolically healthy obesity without fatty liver and risk of incident type 2 diabetes: A meta-analysis of prospective cohort studies

OBJECTIVE

A meta-analysis indicated that metabolically healthy obesity (MHO) presents a risk of incident type 2 diabetes, but it has not yet been established whether MHO without fatty liver (w/o FL) also presents a risk of incident diabetes.

METHODS

plus the presence of non or one of the following factors: hypertension, impaired fasting glucose, low high-density lipoprotein cholesterol, and hypertriglyceridemia. Using a random effects model, we calculated the pooled relative risks (RRs) and 95% confidence intervals (CIs) of incident diabetes.

RESULTS

Our meta-analysis included three studies from the databases plus the NAGALA study, with a total of 134,667 subjects, including 8675 MHO subjects w/o FL and 7218 MHO subjects with fatty liver (wFL). Compared to the metabolically healthy non-overweight subjects w/o FL, the RRs of incident diabetes in the MHO w/o FL and MHO wFL groups were 1.42 (95%CI 1.11-1.77) and 3.28 (95%CI 2.30-4.67).

CONCLUSIONS

Our meta-analysis results demonstrate that the MHO phenotype, with or without fatty liver, presents a risk of the development of type 2 diabetes. Individuals with MHO who do not have fatty liver should be monitored carefully - similarly to those with fatty liver - for the development of diabetes.

[Obesity-related glomerulopathy: Mechanisms of development, clinical course]

Obesity and overweight are recognized as epidemics of non-communicable diseases in the 21st century. The kidneys are a target organ for obesity, damage to which is considered to be an independent risk factor for the development of renal failure. Obesity-related glomerulopathy (OGP) is one of the types of renal injury in obesity, which is characterized by the development of proteinuria in patients with a body mass index (BMI) of >30 kg/m2 in the absence of other causes of kidney damage. The pathogenesis of OGP is multifactorial. It is associated with intrarenal hemodynamic disorders - the development of renal hyperfiltration, the damaging action of adipose tissue hormones (hyperleptinemia, activation of the renin-angiotensin-aldosterone system, decreased production of adiponectin); with ectopic lipid accumulation in the kidney. The morphological pattern of OGP is characterized by a low glomerular density (oligonephronia) that leads to glomerular and tubular hypertrophy; by the development of perihilar focal segmental glomerulosclerosis (FSGS), obvious podocyte damages, and the development of a fatty kidney. The clinical picture of OGP is characterized by the slow and gradual development of albuminuria, not exceeding Stage A3 (300-1999 mg/day). Approximately one-third of patients develop partial nephrotic syndrome with massive proteinuria, but without edema and hypoproteinemia. Complete nephrotic syndrome is observed in not more than 6% of patients with OGP. In the course of the disease, 50% of patients develop hypertension and more than 80% do dyslipidemia. Stages IV-V chronic kidney disease may develop 20-30 years after the disease occurs.

Weight gain since age of 20 as risk of metabolic syndrome even in non-overweight individuals

PURPOSE

Metabolic syndrome (MetS), regardless of the presence of obesity, is known as a risk of diabetes and cardiovascular disease. Weight gain after age 20 reported to be associated with these diseases. Impact of the difference between the body mass index (BMI) at examination and BMI at age 20 (ΔBMI_exa-20y) on MetS, especially in non-overweight individuals, remains to be elucidated.

METHODS

We analyzed the data of 24,363 individuals (14,301 men and 10,062 women) in this cross-sectional study. The diagnosis of MetS was diagnosed when three or more of the following criteria were present: hypertension, hyperglycemia, hypertriglyceridemia, low HDL-cholesterol level, and abdominal obesity. Logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) adjusting for age, alcohol, smoking, exercise, and BMI at examination.

RESULTS

Compared to the lowest ΔBMI_exa-20y tertile (ΔBMI_exa-20y < 1.2 kg/m² in men and ≤0 kg/m² in women), the highest tertile (ΔBMI_exa-20y ≥ 3.2 kg/m² in men and ≥2.0 kg/m² in women) was associated with the risk of the presence of MetS (multivariate OR = 1.80, 95%CI 1.53-2.11, p < 0.001 in men and OR = 3.27, 95%CI 2.22-4.96, p < 0.001 in women). This result was also applicable in non-overweight individuals (multivariate OR = 2.06, 95%CI 1.46-2.92, p < 0.001 in men and OR = 2.49, 95%CI 1.40-4.64, p < 0.001 in women).

CONCLUSIONS

Our analyses showed that ΔBMI_exa-20y is associated with the risk of the presence of MetS, even in non-overweight individuals. It is thus important to check weight changes from early adulthood, even in non-overweight individuals.

Association between kidney function and genetic polymorphisms in atherosclerotic and chronic kidney diseases: A cross-sectional study in Japanese male workers

Background

Several single nucleotide polymorphisms (SNPs) have been implicated in the predisposition to chronic kidney disease (CKD). Atherosclerotic disease is deeply involved in the incidence of CKD; however, whether SNPs related to arteriosclerosis are involved in CKD remains unclear. This study aimed to identify SNPs associated with CKD and to examine whether risk allele accumulation is associated with CKD.

Methods

We conducted a cross-sectional study using data of 4814 male workers to examine the association between estimated glomerular filtration rate (eGFR) and 59 candidate polymorphisms (17 CKD, 42 atherosclerotic diseases). We defined the genetic risk score (GRS) as the total number of risk alleles that showed a significant association in this analysis and examined the relationship with CKD (eGFR < 60 ml/min/1.73m²). Multivariate logistic regression, discrimination by area under the receiver operating characteristic curve, integrated discrimination improvement (IDI), and category-free net reclassification improvement (cNRI) were evaluated.

Results

In total, 432 participants were categorized as having CKD. We found eight candidate SNPs with P value < 0.05 (CX3CR1 rs3732379, SHROOM3 rs17319721, MTP rs1800591, PIP5K1B rs4744712, APOA5 rs662799, BRAP rs3782886, SPATA5L1 rs2467853, and MCP1 rs1024611) in the multivariate linear regression adjusted for age, body mass index, systolic blood pressure, and fasting blood glucose. Among these eight SNPs, BRAP rs3782886 and SPATA5L1 rs2467853 were significantly associated with eGFR (false discovery rate < 0.05). GRS was significantly associated with CKD (odds ratio, 1.17; 95% confidence interval, 1.09–1.26). C-statisics improved from 0.775 to 0.780 but showed no statistical significance. However, adding GRS significantly improved IDI and cNRI (0.0057, P = 0.0028, and 0.212, P < 0.001, respectively).

Conclusions

After adjustment for clinical factors, kidney function was associated with BRAP rs3782886 and SPATA5L1 rs2467853 and the GRS for CKD that we developed was associated CKD.

Combined effect of body mass index and waist-height ratio on incident diabetes; a population based cohort study

We investigated the impact of combined effect of body mass index and waist-to-height ratio on risk of diabetes. Overweight and abdominal obesity were defined as body mass index ≥23 kg/m² and waist-to-height ratio ≥0.5, respectively. We divided participants into four groups according to presence of overweight and/or abdominal obesity. About 20% individuals with overweight did not complicated with an abdominal obesity. Among 3,737 participants, 286 participants had diabetes at baseline-examination. Adjusted odds ratios for prevalence of diabetes compared with non-overweight participants without abdominal obesity were as follow: 1.87 (95% confidence interval 1.09-3.14, p = 0.024) in non-overweight participants with abdominal obesity, 1.51 (0.87-2.55, p = 0.141) in overweight participants without abdominal obesity and 3.25 (2.37-4.52, p<0.001) in overweight participants with abdominal obesity. In the follow-up examination, 86 participants were diagnosed as diabetes among 2,263 participants. Adjusted odds ratios for incident diabetes were as follow: 2.59 (0.98-6.44, p = 0.056) in non-overweight participants with abdominal obesity, 1.65 (0.64-4.00, p = 0.288) in overweight participants without abdominal obesity and 2.77 (1.55-5.15, p<0.001) in overweight participants with abdominal obesity. Non-overweight individuals with abdominal obesity as well as overweight individuals with abdominal obesity was associated with diabetes compared with non-overweight individuals without abdominal obesity.

Fatty liver as a risk factor for progression from metabolically healthy to metabolically abnormal in non-overweight individuals

PURPOSE

Recent studies identified that metabolically abnormal non-obese phenotype is a risk factor for cardiovascular diseases. However, little is known about risk factor for progression from metabolically healthy non-overweight to metabolically abnormal phenotype. We hypothesized that fatty liver had a clinical impact on progression from metabolically healthy non-overweight to metabolically abnormal phenotype.

METHODS

In this retrospective cohort study, 14,093 Japanese (7557 men and 6736 women), who received the health-checkup program from 2004 to 2012, were enrolled. Overweight and obesity were defined as body mass index 23.0-25.0 and ≥25.0 kg/m². Four metabolic factors (impaired fasting glucose, hypertension, hypertriglyceridemia and low high density lipoprotein-cholesterol concentration) were used for definition of metabolically healthy (less than two factors) or metabolically abnormal (two or more). We divided the participants into three groups: metabolically healthy non-overweight (9755 individuals, men/women = 4290/5465), metabolically healthy overweight (2547 individuals, 1800/747) and metabolically healthy obesity (1791 individuals, 1267/524). Fatty liver was diagnosed by ultrasonography.

RESULTS

Over the median follow-up period of 5.3 years, 873 metabolically healthy non-overweight, 512 metabolically healthy overweight and 536 metabolically healthy obesity individuals progressed to metabolically abnormal. The adjusted hazard risks of fatty liver on progression were 1.49 (95% confidence interval 1.20-1.83, p = 0.005) in metabolically healthy non-overweight, 1.37 (1.12-1.66, p = 0.002) in metabolically healthy overweight and 1.38 (1.15-1.66, p < 0.001) in metabolically healthy obesity, after adjusting for age, sex, alcohol, smoking, exercise, impaired fasting glucose, hypertension, hypertriglyceridemia, low high density lipoprotein-cholesterol concentration, and abdominal obesity.

CONCLUSIONS

Fatty liver is an independent risk factor for progression from metabolically healthy status to metabolically abnormal phenotype, even in non-overweight individuals.

Metabolically healthy obesity: a friend or foe?

Obesity is associated with a reduced life expectancy, largely because obese individuals are at an increased risk of type 2 diabetes, cardiovascular disease, and several types of cancer. Much interest has recently focused on the concept of "all obesity is not created equally." Obese individuals without the metabolic abnormalities that commonly accompany excess adiposity, a condition known as metabolically healthy obesity (MHO), account for a substantial proportion of the obese adult population. Numerous possible mechanisms underlying MHO have been suggested, including adipose tissue distribution and inflammation. However, the prognostic value of MHO is controversial and considerably challenging. The lack of a standard definition for metabolic health and obesity as well as the dynamic properties of MHO may have contributed to these inconsistent results. This review aimed to present several current issues regarding MHO including its definition, epidemiology, natural course, suggested mechanisms, and clinical implications in the context of patient prognosis.

Left Ventricular Geometry Determines Prognosis and Reverse J-Shaped Relation Between Blood Pressure and Mortality in Ischemic Stroke Patients

OBJECTIVES

This study sought to investigate the prognostic significance of left ventricular (LV) mass and geometry in ischemic stroke survivors, as well as the LV geometry-specific differences in the blood pressure-mortality relationship.

BACKGROUND

LV mass and geometry are well-known prognostic factors in various populations; however, there are no data on their role in ischemic stroke patients.

METHODS

We prospectively recruited 2,328 consecutive patients admitted with acute ischemic stroke to our institute between 2002 and 2010. Of these, 2,069 patients were analyzed in whom echocardiographic data were available to assess LV mass and geometry.

RESULTS

All-cause mortality was significantly greater in patients with concentric hypertrophy (adjusted hazard ratio [HR]: 1.417; 95% confidence interval [CI]: 1.045 to 1.920) and concentric remodeling (HR: 1.540; 95% CI: 1.115 to 2.127) but nonsignificantly in those with eccentric hypertrophy (HR: 1.388; 95% CI: 0.996 to 1.935) compared with normal geometry in multivariate analyses. Relative wall thickness was a significant predictor of all-cause mortality (HR: 1.149 per 0.1-U increase in relative wall thickness; 95% CI: 1.021 to 1.307), whereas LV mass index was not (HR: 1.003 per 1 g/m² increase in LV mass index; 95% CI: 0.999 to 1.007). Similar results were observed with cardiovascular mortality. In multivariable fractional polynomials, patients with altered LV geometry showed reverse J-curve relationships between acute-phase systolic blood pressure and all-cause or cardiovascular mortality, with the highest risks in the lower extremes, whereas those with normal geometry did not.

CONCLUSIONS

Echocardiographic assessment of LV geometry provided independent and additive prognostic information in ischemic stroke patients. A reverse J-shaped relation of mortality with blood pressure was found in patients with abnormal LV geometry.

Nonoverweight nonalcoholic fatty liver disease and incident cardiovascular disease: A post hoc analysis of a cohort study

Nonalcoholic fatty liver disease (NAFLD) is known as a risk of incident cardiovascular disease (CVD). About 20% of NAFLD occurs in nonobese individuals. However, it remains to be elucidated the association between nonoverweight with NAFLD and a risk of incident CVD. Therefore, we investigated the risk of nonoverweight with NAFLD for incident CVD.We performed a post-hoc analysis of the previous prospective cohort study, in which 1647 Japanese were enrolled. Abdominal ultrasonography was used to diagnose NAFLD. Overweight was defined as body mass index ≥23 kg/m, which is recommended by World Health Organization for Asian. We divided participants into 4 phenotypes by existence of NAFLD and/or overweight. The hazard risks of the 4 phenotypes for incident CVD were calculated by Cox hazard model after adjusting for age, sex, smoking status, exercise, hypertension, hyperglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol at baseline examination.Incident proportions of CVD were 0.6% in nonoverweight without NAFLD, 8.8% in nonoverweight with NAFLD, 1.8% in overweight without NAFLD, and 3.3% in overweight with NAFLD. Compared with nonoverweight without NAFLD, the adjusted hazard ratios of incident CVD were 10.4 (95% confidence interval 2.61-44.0, P = .001) in nonoverweight with NAFLD, 1.96 (0.54-7.88, P = .31) in overweight without NAFLD, and 3.14 (0.84-13.2, P = .09) in overweight with NAFLD.Nonoverweight with NAFLD was associated with higher risk of incident CVD. We should pay attention to NAFLD, even in nonoverweight individuals, to prevent further CVD events.

Fatty liver associated with metabolic derangement in patients with chronic kidney disease: A controlled attenuation parameter study

BACKGROUND

Hepatic steatosis measured with controlled attenuation parameter (CAP) using transient elastography predicts metabolic syndrome in the general population. We investigated whether CAP predicted metabolic syndrome in chronic kidney disease patients.

METHODS

CAP was measured with transient elastography in 465 predialysis chronic kidney disease patients (mean age, 57.5 years).

RESULTS

The median CAP value was 239 (202-274) dB/m. In 195 (41.9%) patients with metabolic syndrome, diabetes mellitus was more prevalent (105 [53.8%] vs. 71 [26.3%], P < 0.001), with significantly increased urine albumin-to-creatinine ratio (184 [38-706] vs. 56 [16-408] mg/g Cr, P = 0.003), high sensitivity C-reactive protein levels (5.4 [1.4-28.2] vs. 1.7 [0.6-9.9] mg/L, P < 0.001), and CAP (248 [210-302] vs. 226 [196-259] dB/m, P < 0.001). In multiple linear regression analysis, CAP was independently related to body mass index (β = 0.742, P < 0.001), triglyceride levels (β = 2.034, P < 0.001), estimated glomerular filtration rate (β = 0.316, P = 0.001), serum albumin (β = 1.386, P < 0.001), alanine aminotransferase (β = 0.064, P = 0.029), and total bilirubin (β = -0.881, P = 0.009). In multiple logistic regression analysis, increased CAP was independently associated with increased metabolic syndrome risk (per 10 dB/m increase; odds ratio, 1.093; 95% confidence interval, 1.009-1.183; P = 0.029) even after adjusting for multiple confounding factors.

CONCLUSION

Increased CAP measured with transient elastography significantly correlated with and could predict increased metabolic syndrome risk in chronic kidney disease patients.

Metabolically healthy obesity and incident chronic kidney disease: The role of systemic inflammation in a prospective study

OBJECTIVE

To investigate the association between the metabolically healthy obesity (MHO) phenotype and incident chronic kidney disease (CKD) in a Chinese population and whether systemic inflammation affects this association.

METHODS

A cohort study was performed with 2,491 Chinese adults. Body mass index ≥ 25.0 kg/m² was defined as obesity. CKD was defined as estimated glomerular filtration rate < 60 mL/min per 1.73 m² or urinary albumin-to-creatinine ratio ≥ 30 mg/g. High-sensitivity C-reactive protein (hsCRP) was used as a surrogate marker of systemic inflammation.

RESULTS

Over a median follow-up period of 3.9 years, 243 of 2,491 participants developed incident CKD (9.8%). Compared with metabolically healthy nonobesity (MHNO), MHO was associated with incident CKD (odds ratio [OR] = 1.65, 95% confidence interval [CI] 1.01-2.69), but not after adjustment for hsCRP. The MHO/hsCRP ≥ 0.20 mg/L group, but not the MHO/hsCRP < 0.20 mg/L group, had an increased OR for incident CKD (OR = 2.66, 95% CI 1.37-5.14), with the MHNO/hsCRP < 0.20 mg/L group as the reference.

CONCLUSIONS

MHO was significantly associated with incident CKD, and the level of systemic inflammation partially explained this association.

A systematic review and meta-analysis suggests obesity predicts onset of chronic kidney disease in the general population

Obesity and chronic kidney disease (CKD) are public health priorities that share core pathophysiological mechanisms. However, whether high body mass index (BMI) increases risk of CKD de novo remains ill-defined. To evaluate the role of BMI in predicting CKD onset in the general adult population, we performed a systematic review and meta-analysis of PubMed and ISI Web of Science databases articles published between January 2000 and August 2016 without language restriction. We selected studies in adult individuals from a general population with normal renal function at baseline that reported the risk of low estimated glomerular filtration (eGFR) (under 60 mL/min/1.73m²) and/or albuminuria (1+ at dipstick or an albumin creatinine ratio of 3.4 mg/mmol or more) as hazard ratio, odds ratio or relative risk related to obesity, overweight, or BMI as continuous value. A total of 39 cohorts covering 630, 677 participants with a mean follow-up of 6.8 years were selected. Obesity increased the relative risk, 95% confidence interval and heterogeneity (I²) of developing low eGFR (1.28, 1.07-1.54, [I²: 95.0%]) and albuminuria (1.51, 1.36-1.67, [I²: 62.7%]). Increase of BMI unit was also associated with higher risk of low eGFR (1.02, 1.01-1.03, [I²: 24.3%]) and albuminuria (1.02, 1.00-1.04, [I²: 0%]). Conversely, overweight did not predict onset of either low eGFR (1.06, 0.94-1.21, [I²: 50.0%]) or albuminuria (1.24, 0.98-1.58, [I²: 49.4%]). Thus, a high BMI predicts onset of albuminuria without kidney failure (CKD stages 1-2) as well as CKD stages 3 and higher, the effect being significant only in obese individuals. Hence, our findings may have implications to improve risk stratification and recommendations on body weight control in the general population.