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

Association between Metabolically Healthy Status and Risk of Gastrointestinal Cancer

PURPOSE

Although obesity is associated with numerous diseases, the risks of disease may depend on metabolically healthy status. Nevertheless, it is unclear to whether metabolically healthy status affects risk of gastrointestinal (GI) cancer in general Chinese population.

MATERIALS AND METHODS

A total of 114,995 participants who met the criteria were included from the Kailuan Study. The study participants were divided into four groups according to body mass index (BMI)/waist circumference (WC) and metabolic status. Incident of GI cancer (esophageal cancer, gastric cancer, liver cancer, biliary cancer, pancreatic cancer, and colorectal cancer) during 2006-2020 were confirmed by review of medical records. The Cox proportional hazard regression models were used to assess the association metabolically healthy status with the risk of GI cancer by calculating the hazard ratios (HR) and 95% confidence interval (CI).

RESULTS

During a mean 13.76 years of follow-up, we documented 2,311 GI cancers. Multivariate Cox regression analysis showed that compared with the metabolically healthy normal-weight group, metabolically healthy obese (MHO) participants demonstrated an increased risk of developing GI cancer (HR, 1.54; 95% CI, 1.11 to 2.13) by BMI categories. However, such associations were not found for WC category. These associations were moderated by age, sex, and anatomical site of the tumor. Individuals with metabolic unhealthy normal-weight or metabolic unhealthy obesity phenotype also have an increased risk of GI cancer.

CONCLUSION

MHO phenotype was associated with increased risk of GI cancer. Moreover, individuals who complicated by metabolic unhealthy status have an increased risk of developing GI cancer. Hence, clinicians should consider the risk of incident GI cancer in people with abnormal metabolically healthy status and counsel them about metabolic fitness and weight control.

The risk for chronic kidney disease in metabolically healthy obese patients: A systematic review and meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is associated with obesity and metabolic syndrome. Nevertheless, the association of CKD with phenotype referred as metabolically healthy obese or overweight is unclear. In this this systematic review and meta-analysis, we investigate the relationships between obesity and CKD independent of metabolic syndrome by appraising published evidence in studies focusing on metabolically healthy obese people.

MATERIALS AND METHODS

We performed a literature search through three databases Embase (Elsevier), the Cochrane Central Register of Controlled Trials (Wiley) and PubMed/Medline Web of Science up to March 2022 with the following terms: "chronic kidney disease", "kidney function", "obesity", "metabolic syndrome", "metabolically healthy obesity", "metabolically healthy overweight". Metabolically unhealthy was defined an individual having at least 3 of the following: abdominal obesity, high blood pressure, hypertriglyceridemia, low HDL cholesterol and hyperglycaemia. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting. Prospective, retrospective, randomized and nonrandomized studies fitting the search criteria were included in our results.

RESULTS

Our final analysis included 16 studies with a total number of 4.965.285 participants. There is considerable heterogeneity in terms of study design, participant characteristics and number of participants across individual studies. In comparison to healthy normal weight patients, the risk was progressively higher in overweight (RR 1.29, 95% CI 1.27 to 1.32, p < 0.001) and obese patients (RR 1.47, 95% CI 1.31 to 1.65, p < 0.001).

CONCLUSION

Metabolically healthy overweight and obese individuals have higher risk of CKD compared to individuals without weight excess.

Urinary Sodium-to-Potassium Ratio and Incident Chronic Kidney Disease: Results From the Korean Genome and Epidemiology Study

OBJECTIVE

To evaluate the association of sodium-potassium intake balance on kidney function.

PATIENTS AND METHODS

Data from the Korean Genome and Epidemiology Study were used. The participants were enrolled between June 1, 2001, and January 31, 2003, and were followed-up until December 31, 2016. The 24-hour excretion levels of sodium and potassium were calculated using the Kawasaki formula with spot urinary potassium and sodium measurements. Participants were categorized into tertiles according to the estimated 24-hour urinary sodium-to-potassium (Na/K) ratio. The primary outcome was incident chronic kidney disease (CKD), defined as an estimated glomerular filtration rate of <60 mL/min per 1.73 m² in two or more consecutive measurements during the follow-up period.

RESULTS

This study included 4088 participants with normal kidney function. The mean age was 52.4±8.9 years, and 1747 (42.7%) were men. The median estimated 24-hour urinary sodium excretion level, potassium excretion level, and Na/K ratio (inter quartile range) were 4.9 (4.1-5.8) g/d, 2.1 (1.8-2.5) g/d, and 2.3 (1.9-2.7) g/d, respectively. During 37,950 person-years of follow-up (median, 11.5 years), 532 participants developed CKD, and the corresponding incidence rate was 14.0 (95% CI, 12.9-15.3) per 1000 person-years. Multivariable Cox hazard analysis revealed that the risk of incident CKD was significantly lower in the lowest tertile than in the highest tertile (HR, 0.78; 95% CI, 0.63-0.97). However, no significant association was found with incident CKD risk when urinary excretion levels of sodium or potassium were evaluated individually.

CONCLUSION

A low urinary Na/K ratio may relate with lower CKD development risk in adults with preserved kidney function.

Abdominal obesity phenotypes are associated with the risk of developing non-alcoholic fatty liver disease: insights from the general population

Background

The diversity of obesity-related metabolic characteristics generates different obesity phenotypes and corresponding metabolic diseases. This study aims to explore the correlation of different abdominal obesity phenotypes with non-alcoholic fatty liver disease (NAFLD).

Methods

The current study included 14,251 subjects, 7411 males and 6840 females. Abdominal obesity was defined as waist circumference ≥ 85 cm in males and ≥ 80 cm in females; according to the diagnostic criteria for metabolic syndrome recommended by the National Cholesterol Education Program Adult Treatment Panel III, having more than one metabolic abnormality (except waist circumference criteria) was defined as metabolically unhealthy. All subjects were divided into 4 abdominal obesity phenotypes based on the presence ( +) or absence (− ) of metabolically healthy/unhealthy (MH) and abdominal obesity (AO) at baseline: metabolically healthy + non-abdominal obesity (MH⁻AO⁻); metabolically healthy + abdominal obesity (MH⁻AO⁺); metabolically unhealthy + non-abdominal obesity (MH⁺AO⁻); metabolically unhealthy + abdominal obesity (MH⁺AO⁺). The relationship between each phenotype and NAFLD was analyzed using multivariate logistic regression.

Results

A total of 2507 (17.59%) subjects in this study were diagnosed with NAFLD. The prevalence rates of NAFLD in female subjects with MH⁻AO⁻, MH⁻AO⁺, MH⁺AO⁻, and MH⁺AO⁺ phenotypes were 1.73%, 24.42%, 7.60%, and 59.35%, respectively. Among male subjects with MH⁻AO⁻, MH⁻AO⁺, MH⁺AO⁻, and MH⁺AO⁺ phenotypes, the prevalence rates were 9.93%, 50.54%, 25.49%, and 73.22%, respectively. After fully adjusting for confounding factors, with the MH⁻AO⁻ phenotype as the reference phenotype, male MH⁻AO⁺ and MH⁺AO⁺ phenotypes increased the risk of NAFLD by 42% and 47%, respectively (MH⁻AO⁺: OR 1.42, 95%CI 1.13,1.78; MH⁺AO⁺: OR 1.47, 95%CI 1.08,2.01); the corresponding risks of MH⁻AO⁺ and MH⁺AO⁺ in females increased by 113% and 134%, respectively (MH⁻AO⁺: OR 2.13, 95%CI 1.47,3.09; MH⁺AO⁺: OR 2.34, 95%CI 1.32,4.17); by contrast, there was no significant increase in the risk of NAFLD in the MH⁺AO⁻ phenotype in both sexes.

Conclusions

This first report on the relationship of abdominal obesity phenotypes with NAFLD showed that both MH⁻AO⁺ and MH⁺AO⁺ phenotypes were associated with a higher risk of NAFLD, especially in the female population. These data provided a new reference for the screening and prevention of NAFLD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02393-9.

Abnormal Obesity Phenotype Is Associated with Reduced eGFR among Diabetes Mellitus and Hypertensive Patients in a Peri-Urban Community in Ghana

Background

Diabetes mellitus (DM) is a chronic disease characterized by hyperglycemia due to obesity and defects in insulin action. Significant complications of DM include kidney disease due to its association with hypertension and obesity. Thus, the contribution of the various obesity phenotypes to the kidney impairment observed among hypertensive and diabetes mellitus patients is of major concern.

Aim

The study assessed the association between obesity phenotypes and reduced glomerular filtration rate among diabetes mellitus and hypertensive patients.

Methods

Three hundred and ten (310) adult patients diagnosed with type 2 diabetes mellitus, hypertension, or both who attended the Presbyterian Hospital, Dormaa Ahenkro, from October 2016 to March 2017 were recruited for the study. Blood samples were collected to analyze biochemical parameters (fasting blood glucose (FBG), lipid profile, and creatinine). Questionnaires were used to collect sociodemographic information, and anthropometrics were appropriately measured. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation, and reduced eGFR was defined as eGFR <90 ml/min/1.73 m².

Results

The prevalence of metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically abnormal nonobese (MANO), and metabolically abnormal obese (MAO) phenotypes among the study participants was 30.65%, 4.50%, 52.90%, and 11.94%, respectively. The highest prevalence of reduced eGFR (29/37 (78.38%)) was seen among the MAO group. This was followed by the MANO, MHO, and MHNO with a reduced eGFR prevalence of 62.20%, 57.64%, and 37.89%, respectively. After normalization with MHNO, the reduced eGFR was 1.51, 1.64, and 2.06 times expressed in MHO, MANO, and MAO. For the total samples, when MHNO was maintained as a reference, reduced eGFR was significantly associated with MANO (aOR = 3.07 (95% CI = 1.76–5.35), P < 0.001) and MAO (aOR = 5.67 (95% CI = 2.66–17.27), P < 0.001) even after adjusting for age, gender, smoking, and alcohol intake. This association was maintained among the female study participants when stratified by gender, and in addition, among the female participants, reduced eGFR was also associated with MHO (aOR = 4.19 (95% CI = 1.06–16.53), P=0.041).

Conclusion

There is a high prevalence of abnormal metabolic phenotypes among diabetes mellitus patients, and these were significantly associated with reduced eGFR among our study participants.

Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus?

Metabolically healthy obese (MHO) individuals are reported to have a lower risk of developing cardiovascular diseases in comparison with individuals with metabolic syndrome. However, the association between MHO and type 2 diabetes (T2DM) is still controversial. Some studies indicated that MHO is a favorable phenotype for T2DM, but more studies showed that MHO individuals have an increased risk of developing T2DM compared with metabolically healthy normal-weight individuals, especially among those who would acquire metabolically unhealthy obesity. This has been supported by finding insulin resistance and low-grade inflammatory responses in MHO individuals with a tendency for impaired beta-cell dysfunction. Studies also showed that liver fat accumulation increased the risk of incidence of T2DM in MHO. Here, we reviewed current literature on the relationship between MHO and T2DM, discussed the determinants for the development of diabetes in MHO, and summarized the measures for the prevention of T2DM in MHO.

Metabolic Health, Obesity, and Renal Function: 2013-2018 National Health and Nutrition Examination Surveys

Rising rates of metabolic syndrome, obesity, and mortality from chronic kidney disease (CKD) have prompted further investigation into the association between metabolic phenotypes and CKD. Purpose: To report the frequency of strictly defined metabolic phenotypes, renal function within each phenotype, and individual risk factors associated with reduced renal function. We utilized the 2013-2018 National Health and Nutrition Examination Surveys (NHANES) and complex survey sample weighting techniques to represent 220 million non-institutionalized U.S. civilians. Metabolic health was defined as having zero of the risk factors defined by the National Cholesterol Education Program with the exception of obesity, which was defined as BMI ≥ 30 kg/m2 in non-Asians and BMI ≥ 25 kg/m2 in Asians. The metabolically healthy normal (MUN) phenotype comprised the highest proportion of the population (38.40%), whereas the metabolically healthy obese (MHO) was the smallest (5.59%). Compared to the MHN reference group, renal function was lowest in the strictly defined MUN (B = -9.60, p < 0.001) and highest in the MHO (B = 2.50, p > 0.05), and this persisted when an increased number of risk factors were used to define metabolic syndrome. Systolic blood pressure had the strongest correlation with overall eGFR (r = -0.25, p < 0.001), and individuals with low HDL had higher renal function compared to the overall sample. The MUN phenotype had the greatest association with poor renal function. While the MHO had higher renal function, this may be due to a transient state caused by renal hyperfiltration. Further research should be done to investigate the association between dyslipidemia and CKD.

The risk of Alzheimer's disease according to dynamic changes in metabolic health and obesity: a nationwide population-based cohort study

We evaluated the association of metabolic health and obesity phenotypes with the risk of Alzheimer's disease (AD). This study enrolled 136,847 elderly participants aged 60 or above from the Korean National Health Insurance System. At baseline examinations in 2009 and 2010, subjects were categorized into four groups: the metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) groups. Based on the phenotypic transition after 2 years, the subjects were further categorized into 16 subgroups. They were followed from 2009 to 2015 to monitor for AD development. The MHO phenotype protected subjects from AD, relative to the MHNO phenotype (HR, 0.73; 95% CI, 0.65-0.81). Among subjects initially classified as MHO, 41.8% remained MHO, with a significantly lower risk of AD compared with the stable MHNO group (HR, 0.62; 95% CI, 0.50-0.77). Among MUO subjects at baseline, those who changed phenotype to MUNO were at higher risk of AD (HR, 1.47; 95% CI, 1.28-1.70), and the transition to the MHO phenotype protected subjects from AD (HR, 0.62; 95% CI, 0.50-0.78). The MHO phenotype conferred a decreased risk of AD. Maintenance or recovery of metabolic health might mitigate AD risk among obese individuals.

Obesity Without Metabolic Abnormality and Incident CKD: A Population-Based British Cohort Study

RATIONALE & OBJECTIVE

Metabolically healthy obesity (obesity without any metabolic abnormality) is not considered to be associated with increased risk of morbidity and mortality. We examined and quantified the association between metabolically healthy overweight/obesity and the risk of incident chronic kidney disease (CKD) in a British primary care population.

STUDY DESIGN

Retrospective population-based cohort study.

SETTING & PARTICIPANTS

4,447,955 of the 5,182,908 adults in The Health Improvement Network (THIN) database (United Kingdom, 1995-2015) with a recorded body mass index (BMI) at the time of registration date who were free of CKD and cardiovascular disease.

EXPOSURE

11 body size phenotypes were created, defined by BMI categories (underweight, normal weight, overweight, and obesity) and 3 metabolic abnormalities (diabetes, hypertension, and dyslipidemia).

OUTCOME

Incident CKD defined as a recorded code for kidney replacement therapy, a recorded diagnosis of CKD, or by an estimated glomerular filtration rate of<60mL/min/1.73m² for≥90 days, or a urinary albumin-creatinine ratio>3mg/mmol for≥90 days.

RESULTS

Of the 4.5 million individuals, 1,040,921 (23.4%) and 588,909 (13.2%) had metabolically healthy overweight and metabolically healthy obesity, respectively. During a mean follow-up interval of 5.4±4.3 (SD) years, compared with individuals with a metabolically healthy normal weight (n=1,656,231), there was a higher risk of incident CKD among those who had metabolically healthy overweight (adjusted HR, 1.30 [95% CI, 1.28-1.33]) and metabolically healthy obesity (adjusted HR, 1.66 [95% CI, 1.62-1.70]). The association was stronger in those younger than 65 years of age. In all BMI categories, there was greater risk of incident CKD with a greater number of metabolic abnormalities in a graded manner.

LIMITATIONS

Potential misclassification of metabolic status due to delayed diagnosis and residual confounding due to unmeasured factors.

CONCLUSIONS

Overweight and obesity without metabolic abnormality are associated with a higher risk of incident CKD compared with those with normal body weight and no metabolic abnormality.

Obesity measures at baseline, their trajectories over time, and the incidence of chronic kidney disease: A 14 year cohort study among Korean adults

BACKGROUND AND AIMS

We investigated the association of baseline obesity measures, i.e. body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR), and their trajectories over time with incident chronic kidney disease (CKD).

METHODS AND RESULTS

Utilizing data from 2001 to 2014 for 9796 Korean adults without CKD at baseline, the association of baseline obesity measures with incident CKD was evaluated using logistic regression. Further, among 5605 subjects with repeated measures, the effect of the trajectories in obesity measures on CKD incidence was investigated via Cox regression. Baseline obesity in terms of BMI, WC, and HC increased the odds of incident CKD (odds ratio (OR) 1.19, 95% confidence interval (CI) 1.05-1.33; OR 1.22, 95% CI 1.07-1.38; and OR 1.25, 95% CI 1.11-1.41, respectively), while baseline WHR did not show such an association. A "became non-obese" BMI, WC, or WHR trajectory, and a "constantly not large" HC trajectory decreased the hazard of incident CKD (hazard ratio (HR) 0.70, 95% CI 0.50-0.99; HR 0.61, 95% CI 0.40-0.92; HR 0.55, 95% CI 0.35-0.85; and HR 0.81, 95% CI 0.69-0.95, respectively) when compared with a "constantly obese or became obese" trajectory.

CONCLUSION

Both baseline obesity and obesity trajectories over time were associated with CKD incidence. BMI and WC were equally good measures of CKD risk, while WHR was not. Separately examining WC and HC components of WHR (= WC/HC) may explain WHR's inconsistency, and WHR's usefulness as a measure of CKD risk should be reevaluated.

Obesity as a predictive factor for chronic kidney disease in adults: systematic review and meta-analysis

Chronic kidney disease (CKD) is one of the main chronic diseases affecting the world population due to its high prevalence and increasing morbidity. Similarly, obesity gained the interest of the scientific community as it directly or indirectly increases mortality from cardiovascular causes, and its prevalence characterizes a pandemic. The objective of this study was to investigate obesity measured by body mass index as a predictor for end-stage renal disease in the general adult population. A systematic review and meta-analysis was carried out by searching 10 databases for prospective or retrospective cohort studies, with no restrictions on the language of publication, including adults with obesity without previous renal disease and who evolved to CKD (diagnosed by estimated glomerular filtration rate below 60 mL&mac_middot;min^-1&mac_middot;(1.73 m²)^-1 over the follow-up period. The R software and Meta package were used for data analysis. After removing duplicates, 5431 studies were submitted to the steps of the systematic review, and 21 articles were included in the data analysis. In total, 3,504,303 patients, 521,216 with obesity, and an average follow-up time of 9.86 years were included. The relative risk of obese people for developing CKD in the random effects model was 1.81 (95%CI: 1.52-2.16). The evidence found in this meta-analysis confirmed that obese people are at higher risk of developing CKD that the non-obese population (1.81 times higher), with obesity being a priority risk factor in preventive actions.

Metabolic Phenotypes and Chronic Kidney Disease: A Cross-Sectional Assessment of Patients from a Large Federally Qualified Health Center

The purpose of this study is to determine if renal function varies by metabolic phenotype. A total of 9599 patients from a large Federally Qualified Health Center (FQHC) were included in the analysis. Metabolic health was classified as the absence of metabolic abnormalities defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, excluding waist circumference. Obesity was defined as body mass index >30 kg/m² and renal health as an estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m². Linear and logistic regressions were used to analyze the data. The metabolically healthy overweight (MHO) phenotype had the highest eGFR (104.86 ± 28.76 mL/min/1.72 m²) and lowest unadjusted odds of chronic kidney disease (CKD) (OR = 0.46, 95%CI = 0.168, 1.267, p = 0.133), while the metabolically unhealthy normal weight (MUN) phenotype demonstrated the lowest eGFR (91.34 ± 33.28 mL/min/1.72 m²) and the highest unadjusted odds of CKD (OR = 3.63, p < 0.0001). After controlling for age, sex, and smoking status, the metabolically unhealthy obese (MUO) (OR = 1.80, 95%CI = 1.08, 3.00, p = 0.024) was the only phenotype with significantly higher odds of CKD as compared to the reference. We demonstrate that the metabolically unhealthy phenotypes have the highest odds of CKD compared to metabolically healthy individuals.

Metabolic healthy obesity is associated with higher incidence of mild decrease estimate glomerular rate in rural northeast Chinese

BACKGROUND

Metabolic healthy obesity (MHO), a phenotype of obesity, seems to be associated with a lower risk of cardiovascular disease. However, MHO has a close relationship with a higher incidence of metabolic syndrome and diabetes. This study aimed to investigate the prevalence of MHO at baseline, the changes in the obese metabolic phenotype at follow-up and the relationship of this phenotype with the incidence of mildly reduced estimated glomerular filtration rate (eGFR) in rural Northeast Chinese.

METHODS

The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate eGFR. A total of 4903 participants aged ≥35 years with eGFR > 90 ml/min/1.73 m² at baseline were enrolled and successfully followed. All participants completed the questionnaires, anthropometric measurements, and blood tests during baseline and follow-up. Mild renal dysfunction was defined as mildly reduced eGFR between 60 and 90 ml/min/1.73 m².

RESULTS

The prevalence of MHO was 20.0% at baseline (19.0% for women and 21.1% for men), which was secondary to metabolic abnormal obesity (MAO) (24.4, 27.2% for women and 21.5% for men). A total of 38.4% of women and 38.9% of men experienced phenotypic changes during follow-up. The cumulative incidence of mildly reduced eGFR in the MHO group was 20.1% (17.7% for women and 22.3% for men), which was also secondary to the incidence in the MAO group (20.8, 18.6% for women and 23.5% for men). After adjusting for age, current smoking, current drinking, chronic diseases, LDL-C, ALT, and AST, MHO was associated with a higher incidence of mildly reduced eGFR among women [OR (95% CI) =1.6 (1.2, 2.3)] and men [OR (95% CI) =1.6(1.2, 2.1)], whereas MAO was related to a higher incidence of mildly reduced eGFR among men only [OR (95% CI) =1.7 (1.3, 2.3)].

CONCLUSION

MHO was associated with a higher incidence of mildly reduced eGFR in both sexes; however, there was a specific relationship between MAO and mildly reduced eGFR in men only. Therefore, it is necessary to monitor kidney function among participants with both MHO and MAO.

Metabolic health is a determining factor for incident colorectal cancer in the obese population: A nationwide population-based cohort study

Background

The association of the risk of colorectal cancer (CRC) with obesity or obesity‐induced metabolic disturbances remains controversial. We assessed the association of metabolic health status with incident CRC among subjects with obesity.

Methods

This study included 319,397 subjects from the Korean National Health Insurance Service‐National Health Screening Cohort. Transitions in metabolic health status and obesity were examined during 2009–2010 and 2011–2012. We categorized subjects with obesity into four separate groups according to their dynamic metabolic health status: metabolically healthy obesity (MHO), MHO to metabolically unhealthy obesity (MUO), MUO to MHO, and stable MUO. Subjects were followed up from 2009 to 2015 for incident CRC.

Results

The stable MHO group showed no increased risk of incident CRC (hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.83–1.14). However, the MHO to MUO group had a higher risk of incident CRC than the stable metabolically healthy nonobese (MHNO) group (HR, 1.34; 95% CI, 1.15–1.57). Among patients with MUO at baseline, those in the subgroup who transitioned to MHO group were not at increased risk of CRC (HR, 1.06; 95% CI, 0.91–1.25), whereas those who remained in the stable MUO group had a higher risk of incident CRC than those in the stable MHNO group (HR, 1.29; 95% CI, 1.19–1.41).

Conclusions

The transition of metabolic health was a determining factor for CRC among subjects with obesity. Hence, maintenance or recovery of metabolic health should be addressed to prevent CRC in individuals with obesity.

Association of Longitudinal Trajectories of Systolic BP with Risk of Incident CKD: Results from the Korean Genome and Epidemiology Study

BACKGROUND

Although hypertension is a well known risk factor for CKD, few studies have evaluated the association between temporal trends of systolic BP and kidney function decline in persons without hypertension.

METHODS

We studied whether changes in systolic BP over time could influence incident CKD development in 4643 individuals without CKD and hypertension participating in the Korean Genome and Epidemiology Study, a prospective community-based cohort study. Using group-based trajectory modeling, we categorized three distinct systolic BP trajectories: decreasing, stable, and increasing. The primary outcome was incident CKD development, defined as two consecutive eGFR measurements <60 ml/min per 1.73 m².

RESULTS

Among participants with an increasing systolic BP trajectory, systolic BP increased from 105 to 124 mm Hg. During 31,936 person-years of follow-up (median 7.7 years), 339 participants developed incident CKD. CKD incidence rates were 8.9, 9.6, and 17.8 cases per 1000 person-years in participants with decreasing, stable, and increasing systolic BP trajectories, respectively. In multivariable cause-specific Cox analysis, after adjustment of baseline eGFR, systolic BP, and other confounders, increasing systolic BP trajectory associated with a 1.57-fold higher risk of incident CKD (95% confidence interval, 1.20 to 2.06) compared with a stable trajectory. There was a significant effect modification of baseline systolic BP on the association between systolic BP trajectories and CKD risk (P value for interaction =0.02), and this association was particularly evident in participants with baseline systolic BP <120 mm Hg. In addition, increasing systolic BP trajectory versus a stable trajectory was associated with higher risk of new development of albuminuria.

CONCLUSIONS

Increasing systolic BP over time without reaching the hypertension threshold is associated with a significantly increased risk of incident CKD in healthy adults.

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.

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.

Non-AIDS comorbidity burden differs by sex, race, and insurance type in aging adults in HIV care

OBJECTIVE

To understand the epidemiology of non-AIDS-related chronic comorbidities (NACMs) among aging persons with HIV (PWH).

DESIGN

Prospective multicenter observational study to assess, in an age-stratified fashion, number and types of NACMs by demographic and HIV factors.

METHODS

Eligible participants were seen during 1 January 1997 to 30 June 2015, followed for more than 5 years, received antiretroviral therapy (ART), and virally suppressed (HIV viral load <200 copies/ml ≥75% of observation time). Age was stratified (18-40, 41-50, 51-60, ≥61 years). NACMs included cardiovascular disease, cancer, hypertension, diabetes, dyslipidemia, arthritis, viral hepatitis, anemia, and psychiatric illness.

RESULTS

Of 1540 patients, 1247 (81%) were men, 406 (26%) non-Hispanic blacks (NHB), 183 (12%) Hispanics/Latinos, 575 (37%) with public insurance, 939 (61%) MSM, and 125 (8%) with injection drug use history. By age strata 18-40, 41-50, 51-60, and at least 61 years, there were 180, 502, 560, and 298 patients, respectively. Median HIV Outpatient Study observation was 10.8 years (range: min-max = 5.0-18.5). Mean number of NACMs increased with older age category (1.4, 2.1, 3.0, and 3.9, respectively; P < 0.001), as did prevalence of most NACMs (P < 0.001). Age-related differences in NACM numbers were primarily due to anemia, hepatitis C virus infection, and diabetes. Differences (all P < 0.05) in NACM number existed by sex (women >men, 3.9 vs. 3.4), race/ethnicity (NHB >non-NHB, 3.8 vs. 3.4), and insurance status (public >private, 4.3 vs. 3.1).

CONCLUSIONS

Age-related increases existed in prevalence and number of NACMs, with disproportionate burden among women, NHBs, and the publicly insured. These groups should be targeted for screening and prevention strategies aimed at NACM reduction.

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.

Carbohydrate-Rich Diet Is Associated with Increased Risk of Incident Chronic Kidney Disease in Non-Diabetic Subjects

Despite the potential relationship with metabolic derangements, the association between dietary carbohydrate intake and renal function remains unknown. The present study investigated the impact of dietary carbohydrate intake on the development of incident chronic kidney disease (CKD) in a large-scale prospective cohort with normal renal function. A total of 6746 and 1058 subjects without and with diabetes mellitus (DM) were analyzed, respectively. Carbohydrate intake was assessed by a 24-h dietary recall food frequency questionnaire. The primary endpoint was CKD development, defined as a composite of estimated glomerular filtration rate (eGFR) of ≤60 mL/min/1.73 m2 and the development of proteinuria. CKD newly developed in 20.1% and 36.0% of subjects during median follow-ups of 140 and 119 months in the non-DM and DM subjects, respectively. Categorization of non-DM subjects into dietary carbohydrate density quartiles revealed a significantly higher risk of CKD development in the third and fourth quartiles than in the first quartile (P = 0.037 for first vs. third; P = 0.001 for first vs. fourth). A significant risk elevation was also found with increased carbohydrate density when carbohydrate density was treated as a continuous variable (P = 0.008). However, there was no significant difference in the incident CKD risk among those with DM according to dietary carbohydrate density quartiles. Carbohydrate-rich diets may increase the risk of CKD development in non-DM subjects.

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.