Metabolically healthy and unhealthy obesity phenotypes and risk of renal stone: a cohort study

Changes in metabolic overweight phenotypes over time and risk of nephrolithiasis: a cohort study

BACKGROUND

Overweight/obesity is considered an independent risk factor for nephrolithiasis, but little is known about its effect on nephrolithiasis according to metabolic health status.

OBJECTIVES

We aimed to investigate the association between various metabolic overweight phenotypes and the occurrence of nephrolithiasis. It also explores whether changes in these phenotypes over time influence the risk of nephrolithiasis.

MATERIALS AND METHODS

A total of 10,315 participants free of nephrolithiasis who underwent an annual health checkup from 2017 to 2022 were included in our prospective cohort study. They were categorized into four groups according to the presence of overweight and metabolic abnormalities (MA). The primary endpoint was the occurrence of renal stones. Multivariable Cox analysis was conducted to elucidate the relationship between metabolic overweight phenotypes and incident nephrolithiasis.

RESULTS

During a median follow-up duration of 4.02 years, nephrolithiasis occurred in 1,468 (14.23%) participants. In the full cohort, we observed that the 5-year cumulative incidences of nephrolithiasis were highest in the metabolically healthy overweight (MHO) and metabolically abnormal overweight (MAO) groups. The hazard ratios (HRs) for nephrolithiasis, relative to metabolically healthy normal weight (MHNW), ranged from 1.19 (95% CI:1.03-1.37; MHO) to 1.32 (95% CI:1.15-1.51; MAO). Furthermore, individuals with persistent MHO throughout follow-up were at a 1.42-fold increased risk of nephrolithiasis (P < 0.001), and 32.17% of individuals experienced changes in phenotype during follow-up. Among MAO subjects, those who transitioned to MHO and MHNW had a 26% and 45% lower risk of incident nephrolithiasis, respectively, compared to those who persisted in the MAO phenotype.

CONCLUSION

Individuals in the MHO and MAO groups exhibit an elevated risk of incident nephrolithiasis in this prospective cohort study. A significant proportion of nephrolithiasis cases may be potentially preventable through the appropriate management of metabolic risk factors for MAO subjects.

Analysis of metabolic syndrome in bilateral upper urinary tract stones: A retrospective study of 3905 cases

Bilateral upper urinary tract stones are significantly related to renal function damage. However, few studies characterized the risk factors of bilateral upper urinary tract stones. We retrospectively enrolled 3905 patients with urinary tract stones from March 2019 to March 2022 at the Second Hospital of Tianjin Medical University. Patients were divided into two groups according to the location of the stones, and the related data were evaluated. In this study, 2485 unilateral and 1420 bilateral stone patients were included. Multivariate logistic regression analysis showed that BMI, gout, hyperparathyroidism, uric acid stone, urine PH, 24-h urinary calcium, blood uric acid, and metabolic syndrome (Mets) were independent risk factors for bilateral stone formation(P < 0.05). Based on these results, we construct a discrimination model. This model revealed good discrimination with an area under the receiver operating characteristic curves of 0.617, and the sensitivity and specificity were 0.592 and 0.586, respectively. Furthermore, the number of Mets components increased the risk of bilateral upper urinary tract stones. Hypertension, hyperglycemia, and low HDL level were strongly associated with bilateral upper urinary tract stones (P < 0.05). Patients with 5 components Mets had 1.89-fold higher risk of bilateral upper urinary tract stones than those with 1 component Mets (OR 3.381; 95 % CI 1.221-9.360; P = 0.013). Additionally, male patients with Mets had higher risk of bilateral upper urinary tract stones than female patients. Our analysis revealed that eight clinical factors were associated with the formation of bilateral upper urinary tract stones, namely BMI, gout, hyperparathyroidism, uric acid stone, urine PH, 24-h urinary calcium, blood uric acid, and Mets. This study could help clinicians adjust treatment strategies for high-risk patients with bilateral upper urinary tract stones.

Machine learning models for screening clinically significant nephrolithiasis in overweight and obese populations

PURPOSES

Our aim is to build and evaluate models to screen for clinically significant nephrolithiasis in overweight and obesity populations using machine learning (ML) methodologies and simple health checkup clinical and urine parameters easily obtained in clinics.

METHODS

We developed ML models to screen for clinically significant nephrolithiasis (kidney stone > 2 mm) in overweight and obese populations (body mass index, BMI ≥ 25 kg/m2) using gender, age, BMI, gout, diabetes mellitus, estimated glomerular filtration rate, bacteriuria, urine pH, urine red blood cell counts, and urine specific gravity. The data were collected from hospitals in Kaohsiung, Taiwan between 2012 and 2021.

RESULTS

Of the 2928 subjects we enrolled, 1148 (39.21%) had clinically significant nephrolithiasis and 1780 (60.79%) did not. The testing dataset consisted of data collected from 574 subjects, 235 (40.94%) with clinically significant nephrolithiasis and 339 (59.06%) without. One model had a testing area under curve of 0.965 (95% CI, 0.9506-0.9794), a sensitivity of 0.860 (95% CI, 0.8152-0.9040), a specificity of 0.947 (95% CI, 0.9230-0.9708), a positive predictive value of 0.918 (95% CI, 0.8820-0.9544), and negative predictive value of 0.907 (95% CI, 0.8756-0.9371).

CONCLUSION

This ML-based model was found able to effectively distinguish the overweight and obese subjects with clinically significant nephrolithiasis from those without. We believe that such a model can serve as an easily accessible and reliable screening tool for nephrolithiasis in overweight and obesity populations and make possible early intervention such as lifestyle modifications and medication for prevention stone complications.

Obesity, metabolic dysfunction, and risk of kidney stone disease: a national cross-sectional study

BACKGROUND

This study aimed to investigate the association between different metabolic syndrome-body mass index (MetS-BMI) phenotypes and the risk of kidney stones.

MATERIALS AND METHODS

Participants aged 20-80 years from six consecutive cycles of the NHANES 2007-2018 were included in this study. According to their MetS status and BMI, the included participants were allocated into six mutually exclusive groups: metabolically healthy normal weight (MHN)/overweight (MHOW)/obesity (MHO) and metabolically unhealthy normal weight (MUN)/overweight (MUOW)/obesity (MUO). To explore the association between MetS-BMI phenotypes and the risk of kidney stones, binary logistic regression was used to determine the odds ratios (ORs).

RESULTS

A total of 13,589 participants were included. It was revealed that all the phenotypes with obesity displayed higher risks of kidney stones (OR = 1.38, p < 0.01 for MHO & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). The risk increased significantly when metabolic dysfunction coexisted with overweight and obesity (OR = 1.39, p < 0.05 for MUOW & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). Of note, the ORs for the MUO and MUOW groups were higher than those for the MHO and MHOW groups, respectively.

CONCLUSIONS

Obesity and unhealthy metabolic status can jointly increase the risk of kidney stones. Assessing the metabolic status of all individuals may be beneficial for preventing kidney stones.

Metabolic health status and renal disorders: a cross-sectional study

Previous surveys suggests that body mass index (BMI) may be positively related to development of chronic kidney disease (CKD). However, this association might be altered by metabolic syndrome. Therefore, we aimed to evaluate the association of metabolic health status with CKD. The present cross-sectional study was carried out on 3322 representative sample of Iranian adults. Metabolic syndrome was identified based on the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) and BMI was assessed by anthropometric measurements. Estimated glomerular filtration rate (eGFR) was calculated by modification of diet in renal disease-Chronic Kidney Disease Epidemiology Collaboration (MDRD-EPI) formula. Subjects were categorized into four phenotypes: metabolically healthy normal weight (MHNW), metabolically healthy overweight and obesity (MHO), metabolically unhealthy normal weight (MUHNW), and metabolically unhealthy overweight and obesity (MUHO). Based on multivariate-adjusted models, the risk of CKD was significantly higher in MUHO compared with MHNW (OR: 1.48; p < 0.05). Although MUHNW and MUHO were associated with lower eGFR and albuminuria, the significant association was not observed in case of hematuria. Furthermore, subjects with kidney stones tended to be in MHO (OR: 1.42; p < 0.05) and MUHO phenotypes (OR: 1.64; p < 0.05), in comparison to the MHNW phenotype. The odds of kidney disorders were higher in adults with metabolic syndrome, regardless of BMI. However, this relationship might be strengthened by the concomitance of metabolic syndrome and obesity. To verify our findings, clarify the causality, and elucidate the underlying mechanisms, further research are warranted.

Prognostic value of total body muscle-fat ratio in patients with kidney stone disease: A US population-based study

Purpose

To examine the relationship between the muscle-fat ratio (MFR) and kidney stone disease (KSD) in the adult population of the United States between 2011 and 2018, and whether it can be used as a predictor of KSD prognosis.

Materials and methods

We conducted a cross-sectional study analysing 9326 patients from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. We analyzed all participants by sex, age, race, level of education, marital status, household income-to-poverty ratio, hypertension, diabetes, vigorous physical activity, moderate physical activity, blood urea nitrogen, creatinine, uric acid, cotinine, and MFR. Dose-response curves with a restricted cubic spline function, univariate and multifactorial logistic regression were used for the analysis of the correlation between MFR and KSD. Finally, we created predictive models based on age, race, hypertension, diabetes mellitus, cotinine and MFR. The prediction model was evaluated using calibration curves, receiver operating characteristic curves and clinical decision curves from the training and test sets.

Results

Of the 9326 participants, 8582 (92%) self-reported that they did not have KSD and 744 (8%) self-reported that they had KSD. Univariate and multifactorial logistic regression showed that MFR was negatively associated with the prevalence of KSD (odds ratio [OR]: 0.770, 95% CI: 0.703-0.843; OR: 0.815, 95% CI: 0.738-0.897). Similarly, the risk of developing KSD decreased with increasing MFR as shown by the dose curves in the restricted cubic bar graphs. Furthermore, there is some accuracy (AUC = 0.652) and clinical applicability to the model we constructed based on the results of multifactorial logistic regression.

Conclusion

The MFR is protective factor against the developing KSD in adults in the USA.

Association between metabolically healthy obesity and kidney stones: results from the 2011-2018 National Health and Nutrition Examination Survey

Introduction

The risk of kidney stones in metabolically healthy obesity (MHO) individuals is largely unexplored. This study using percent body fat (%BF) to categorize obesity, to investigate the association between MHO as well as other metabolic syndrome-obesity combined phenotypes and kidney stones in a national representative population.

Materials and methods

This cross-sectional study included 4,287 participants in the National Health and Nutrition Examination Survey from 2011 to 2018. Metabolically healthy status was defined as not having any component of metabolic syndrome or insulin resistance. Obesity was identified by %BF, which was measured and assessed by dual-energy x-ray absorptiometry (DXA) scan. Participants were cross-classified by metabolic health and obesity status. The outcome was self-report kidney stones. Multivariable logistic regression model was used to examine the association between MHO and kidney stones.

Results

A total of 358 participants had kidney stones [weighted prevalence (SE): 8.61% (0.56%)]. The weighted prevalence (SE) of kidney stones in MHN, MHOW, and MHO groups was 3.13% (1.10%), 4.97% (1.36%), and 8.55% (2.09%), respectively. After adjusting for age, sex, race and ethnicity, education level, smoking status, alcohol consumption, physical activity, daily water intake, CKD stage 3-5, and hyperuricemia, MHO individuals (OR: 2.90, 95% CI: 1.18, 7.0) had a significantly higher risk of kidney stones than those with metabolically healthy normal weight. In metabolically healthy participants, a 5% increment in %BF was associated with a significantly higher risk of kidney stones (OR: 1.60, 95% CI: 1.20, 2.14). Furthermore, a nonlinear dose-response relationship between %BF and the kidney stones was observed in metabolically healthy participants (P for non-linearity = 0.046).

Conclusion

Using %BF to define obesity, MHO phenotype was significantly associated with higher risks of kidney stones, suggesting that obesity can independently contribute to kidney stones in the absence of metabolic abnormalities and insulin resistance. Regarding kidney stones prevention, MHO individuals might still benefit from lifestyle interventions aimed at healthy body composition maintenance.

Metabolically Healthy Obesity and Carotid Plaque among Steelworkers in North China: The Role of Inflammation

This study aimed to investigate the association between metabolically healthy obesity (MHO) and carotid plaque. In this cross-sectional survey, 3467 steelworkers in North China were surveyed. There are two criteria for defining a carotid plaque: (1) the lesion structure exceeds 50% of the peripheral intima-media thickness value or invades the arterial lumen by at least 0.5 mm; (2) a thickness > 1.5 mm from the intima−lumen interface to the media−adventitia interface. Metabolic health was defined as the nonexistence of one of the metabolic syndrome (MetS) diagnostic criteria for metabolic abnormalities. Obesity was defined as having a BMI ≥ 25 kg/m2. To calculate the odds ratio (OR) for the prevalence carotid plaque, a logistic regression was used for the analysis. The prevalence of carotid plaque in the subjects was 14.3% for metabolically healthy non-obesity (MHNO), 32.4% for MHO, 18.9% for metabolically unhealthy non-obesity (MUNO), and 46.8% for metabolically unhealthy obesity (MUO). The odds ratios for suffering from carotid plaque were 1.27 (95% CI: 0.69 to 2.32) for MHO, 1.83 (95% CI: 1.29 to 2.58) for MUNO, and 1.81 (1.28 to 2.56) for MUO in comparison with MHNO after adjusting for confounders. There was no association between the MHO phenotype and carotid plaque prevalence among steelworkers in North China.

Sex disparities and the risk of urolithiasis: a large cross-sectional study

BACKGROUND

Urolithiasis is one of the most common diseases in urology, with a lifetime prevalence of 14% and is more prevalent in males compared to females. We designed to explore sex disparities in the Chinese population to provide evidence for prevention measures and mechanisms of stone formation.

MATERIALS AND METHODS

A total of 98232 Chinese individuals who had undergone a comprehensive examination in 2017 were included. Fully adjusted odds ratios for kidney stones were measured using restricted cubic splines. Multiple imputations was applied for missing values. Propensity score matching was utilised for sensitivity analysis.

RESULTS

Among the 98232 included participants, 42762 participants (43.53%) were females and 55470 participants (56.47%) were males. Patients' factors might cast an influence on the development of kidney stone disease distinctly between the two genders. A risk factor for one gender might have no effect on the other gender. The risk for urolithiasis in females continuously rises as ageing, while for males the risk presents a trend to ascend until the age of around 53 and then descend.

CONCLUSIONS

Patients' factors might influence the development of kidney stones distinctly between the two genders. As age grew, the risk to develop kidney stones in females continuously ascended, while the risk in males presented a trend to ascend and then descend, which was presumably related to the weakening of the androgen signals.Key messagesWe found that patients' factors might cast an influence on the development of kidney stone disease distinctly between the two sexes.The association between age and urolithiasis presents distinct trends in the two sexesThe results will provide evidence to explore the mechanisms underlying such differences can cast light on potential therapeutic targets and promote the development of tailored therapy strategies in prospect.

Association between body fat distribution and kidney stones: Evidence from a US population

Objectives

We aimed to evaluate the relationship between the proportion of Android to Gynoid ratio and the incidence of kidney stones among US adults.

Methods

Participants aged 20-59 years from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) database were selected to assess the association between Android to Gynoid ratio and kidney stone prevalence using logistic regression analysis, subgroup analysis and calculation of dose-response curves.

Results

This study ultimately included 10858 participants, of whom 859 self-reported a history of kidney stones. And after adjusting for all confounders, an increased Android to Gynoid ratio was associated with an increased prevalence of kidney stones (OR=2.75, 95% CI:1.62-4.88). And subgroup analysis showed an increased prevalence of kidney stones in women (OR=3.55, 95% CI: 1.54-8.22), non-diabetic (OR=2.59, 95% CI: 1.45-4.60), 60 > age ≥ 40 years (OR=3.51, 95% CI: 1.83-6.71), Mexican-American (OR=4.35, 95% CI: 1.40- 13.53) and white (OR=3.86, 95% CI: 1.82-8.18) groups, there was a significant positive association between A/G ratio and kidney stones. In contrast, in the hypertensive subgroup, the A/G ratio was associated with kidney stones in all groups.

Conclusions

Higher Android to Gynoid ratio is associated with a high prevalence of kidney stone disease.

Association of Metabolically Healthy Obesity and Glomerular Filtration Rate among Male Steelworkers in North China

This study aims to investigate the association between metabolically healthy obesity (MHO) and the early stages of renal dysfunction and whether systemic inflammation affects the study's outcome. Male steelworkers in northern China were investigated in this cross-sectional survey (n = 6309). A decrease in estimated glomerular filtration rate (eGFR) was used as the primary outcome, which was defined as an eGFR of ≤89 mL/min/1.73 m². A BMI ≥ 25 kg/m² was used to determine obesity. In the definition of metabolic health, the absence of metabolic syndrome components is considered metabolically healthy. An assessment of inflammation was carried out using a surrogate marker called high-sensitivity C-reactive protein (hs-CRP). The adjusted odds ratio (OR) and confidence intervals (CIs) were estimated using the multivariable logistic regression model. After adjusting for hs-CRP, MHO (OR = 1.97; 95% CI: 1.21 to 3.21) was significantly associated with decreased eGFR compared to metabolically healthy non-obesity (MHNO). With the MHNO/hs-CRP ≤ 0.01 mg/dL group as a reference, the OR was 2.17 (95% CI: 1.17 to 4.02) for decreased eGFR in the group with MHO/hs-CRP > 0.01 mg/dL. MHO is associated with renal dysfunction at an early stage. To some degree, this risk can be explained by the level of inflammation.

Obesity phenotypes related to musculoskeletal disorders; a cross-sectional study from RaNCD cohort

BACKGROUND

This study was evaluated the association between obesity phenotypes and risk of lower torso musculoskeletal disorders including low back pain (LBP), low back stiffness (LBS), arthralgia, and joint stiffness in Ravansar non-communicable diseases (RaNCD) cohort study.

METHODS

In this cross-sectional study, 6940 adults were examined for the presence of lower torso musculoskeletal disorders by a physician. Obesity phenotypes including metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) were defined based on the International Diabetes Federation, as well as, body mass index > 30 kg/m2. Metabolically unhealthy non-obesity (MUNO) phenotype was considered as unhealthy metabolic without obesity.

RESULTS

The prevalence of LBP, LBS, arthralgia, and joint stiffness in MHO, MUO, and MUNO were significantly higher than in healthy participants compared to obesity phenotypes. Logistic regression showed that MHO phenotype was significantly increased with risk of LBP (OR: 1.19, CI 95%: 1.01-1.41), LBS (OR: 1.44, CI 95%: 1.12-1.86), arthralgia (OR: 1.54, CI 95%: 1.33-1.78), and joint stiffness (OR: 1.84, CI 95%: 1.35-2.52). Moreover, MUO phenotype was positively associated with risk of LBS (OR: 1.46, CI 95%: 1.09-1.94) and arthralgia (OR: 1.66, CI 95%: 1.41-1.96). In addition, MUNO phenotype was associated with a higher risk of arthralgia (OR: 1.21, CI 95%: 1.06-1.37).

CONCLUSION

All three phenotypes, MHO, MUO and MUNO were significantly increased the risk of arthralgia. However, MHO phenotype was significantly associated with a higher risk of all examined lower torso musculoskeletal disorders in the current study.

Relationship between hepatitis C and kidney stone in US females: Results from the National Health and Nutrition Examination Survey in 2007–2018

Background

The main objective of this study is to explore the effects of hepatitis C (HCV) on the prevalence rate of kidney stones in US women.

Method

Dates for HCV infection and kidney stones were collected from National Health and Nutrition Examination Survey (NHANES) database, a cross-sectional study. The analysis samples included adults aged ≥20 years and women from six consecutive cycles of the NHANES 2007–2018. The association between HCV infection and kidney stones was performed by using logistic regression models. Subgroup analyses were conducted to find sensitive crowds.

Results

A total of 13,262 participants were enrolled, including 201 infected with HCV. After adjustment for potential confounders, we revealed a positive relationship between HCV and kidney stones (OR = 1.70, 95%CI:1.13–2.56). The crowds' statistically significant difference was characterized by other races (OR = 8.17, 95%CI:1.62–41.22) and BMI within 25–29.9 kg/m2 (OR = 2.45, 95%CI:1.24–4.83).

Conclusions

HCV infection may affect the prevalence of urolithiasis in US women, even the causal relationship remains unclear, the relation deserves special attention. We considered such a study an ideal way to begin exploring the effects of HCV on kidney stones.

Assessing causal associations of obesity and diabetes with kidney stones using Mendelian randomization analysis

BACKGROUND

Obesity and type 2 diabetes have been associated with an increased risk of kidney stones in observational studies, but the causality of these associations remains unestablished. We conducted a Mendelian randomization study to determine these associations.

METHODS

Independent single nucleotide polymorphisms at the genome-wide significance threshold (p < 5 × 10^-8) were selected as instrumental variables and were identified from meta-analyses of genome-wide association studies on body mass index (up to 806,834 individuals) and type 2 diabetes (228,499 cases and 1,178,783 non-cases). Summary-level data for the associations of exposure-associated SNPs with kidney stones were obtained from the UK Biobank study (3540 cases and 357,654 non-cases) and the FinnGen consortium (3856 cases and 172,757 non-cases). Causal estimates from two sources were combined using the meta-analysis method.

RESULTS

Higher genetically predicted body mass index and genetic liability to type 2 diabetes were associated with an increased risk of kidney stones in both the UK Biobank study and FinnGen consortium. In the meta-analysis of results from the two data sources, the odds ratios of kidney stones were 1.33 (95% confidence interval, 1.17, 1.51; p < 0.001) per one standard deviation increase in genetically predicted body mass index (~4.8 kg/m²) and 1.15 (95% confidence interval, 1.10, 1.20; p < 0.001) for one unit increase in genetically predicted log-transformed odds of type 2 diabetes.

INTERPRETATION

This study based on genetic data suggests that a high body mass index and type 2 diabetes may be causal risk factors for kidney stone formation.

Introduction to Nephrocardiology

The interaction between nephrology and cardiovascular medicine is much broader than the cardiorenal syndrome. Many different aspects of cardiovascular medicine are interconnected with and substantially influenced by the conditions that fall into the realm of nephrology, and vice versa. Those aspects include pathophysiology, risk factors, epidemiology, prognosis, prevention, diagnosis, monitoring, and therapy. Discovery of the interconnected areas and development of appropriate knowledge and skill to optimally approach those circumstances can improve the quality of care and outcome of a large population of patients. Therefore, establishment of the distinct subspeciality of nephrocardiology is imperative.