White Blood Cell Count and C-Reactive Protein Independently Predicted Incident Diabetes: Yuport Medical Checkup Center Study

The association of a low-inflammatory diet with the trajectory of multimorbidity: a large community-based longitudinal study

BACKGROUND

A proinflammatory diet has been associated with a risk of individual chronic diseases, however, evidence on the association between inflammatory dietary patterns and the trajectory of chronic disease multimorbidity is sparse.

OBJECTIVES

We aimed to investigate the associations of a low-inflammatory diet with the multimorbidity trajectory.

METHODS

Within the UK Biobank, 102,424 chronic disease-free participants (mean age 54.7 ± 7.9 y, 54.8% female) were followed up to detect multimorbidity trajectory (annual change in the number of 59 chronic diseases). Baseline inflammatory diet index (IDI) and empirical dietary inflammatory pattern (EDIP) were separately calculated from the weighted sum of 32 posteriori-derived (15 anti-inflammatory) and 18 prior-defined (9 anti-inflammatory) food groups, and tertiled as low-, moderate-, and high-inflammatory diet. Data were analyzed using linear mixed effects model, Cox model, and Laplace regression with adjustment for potential confounders.

RESULTS

During the follow-up (median 10.23 y), 15,672 and 35,801 participants developed 1 and 2+ chronic conditions, respectively. Adherence to a low-inflammatory diet was associated with decreased multimorbidity risk (hazard ratio [HRIDI] = 0.84, 95% confidence interval [CI]: 0.81, 0.86; HREDIP = 0.91, 95% CI: 0.89, 0.94) and a slower multimorbidity accumulation (βIDI = -0.033, 95% CI: -0.036, -0.029; βEDIP = -0.006, 95% CI: -0.010, -0.003) compared with a high-inflammatory diet, especially in participants aged > 60 y (βIDI = -0.051, 95% CI: -0.059, -0.042; βEDIP = -0.020, 95% CI: -0.029, -0.012; both P-interactions < 0.05). The 50th percentile difference (95% CI) of chronic disease-free survival time was prolonged by 0.81 (0.64, 0.97) and 0.49 (0.34, 0.64) y for participants with a low IDI and EDIP, respectively. Higher IDI and EDIP were associated with the development of 4 and 3 multimorbidity clusters (especially for cardiometabolic diseases), respectively.

CONCLUSIONS

A low-inflammatory diet is associated with a lower risk and slower accumulation of multimorbidity (especially in participants aged > 60 y). A low-inflammatory diet may prolong chronic disease-free survival time.

Chronic low-grade inflammation associated with higher risk and earlier onset of cardiometabolic multimorbidity in middle-aged and older adults: a population-based cohort study

Evidence regarding the role of chronic low-grade inflammation in the progression of cardiometabolic diseases (CMDs) and cardiometabolic multimorbidity (CMM) is currently limited. This prospective cohort study, utilising data from the UK Biobank, included 273,804 adults aged 40-69 years initially free of CMD at baseline. CMM was defined as the coexistence of two or more CMDs, such as coronary artery disease, type 2 diabetes mellitus, hypertension and stroke. The aggregated inflammation score (INFLA-score), incorporating C-reactive protein, white blood cell count, platelet count and granulocyte-to-lymphocyte ratio, quantified chronic low-grade inflammation. Absolute risks (ARs), hazard ratios (HRs) and 95% confidence intervals (CIs) assessed the association of increased INFLA-score with the risk of CMMs and CMDs. The accelerated failure time model explored the effect of INFLA-score on the time to CMM onset, and a restricted cubic spline characterised the dose-dependent relationship between INFLA-score and CMM risk. After a median follow-up of 166.37 months, 13,755 cases of CMM were identified. In quartiles with increasing INFLA-score levels, CMM ARs were 4.41%, 4.49%, 5.04% and 6.01%, respectively; HR increased by 2%, 15% and 36%, respectively, compared to the lowest quartile. The INFLA-score and CMM risk relationship was nonlinear (P for nonlinear < 0.001), exhibiting a significant risk trend change at a score of 9. For INFLA-score < 9, CMM risk increased by 1.9% for each 1-point increase; for INFLA-score ≥ 9, the risk increased by 5.9% for each 1-point increase. Additionally, a higher INFLA-score was associated with an earlier onset of CMM (P < 0.001). Compared to the first INFLA-score quartile, the AFT model revealed adjusted median times to CMM occurrence were 2.92, 6.10 and 13.19 months earlier in the second, third and fourth quartile groups, respectively. Chronic low-grade inflammation is associated with a higher risk of cardiometabolic multimorbidity and earlier onset among middle-aged and older adults. Monitoring and screening the INFLA-score in adults without CMDs may improve early prevention of CMM.

The MACROD2 rs6110695 A>G Polymorphism and the Metabolites Indoleacrylic Acid and Butyrylcarnitine Potentially Have Clinical Relevance to WBC Count Prediction

Our previous study suggested that the Mono-ADP ribosylhydrolase 2 (MACROD2) rs6110695 A>G polymorphism is significantly associated with white blood cell (WBC) count in the Korean population. The present study aimed to evaluate the clinical relevance of the MACROD2 rs6110695 A>G polymorphism for predicting WBC count by utilizing plasma metabolites and a single-nucleotide polymorphism (SNP). Two groups were characterized by MACROD2 rs6110695 A>G SNP genotypes among 139 healthy subjects based on the genetic information provided in our previous work: rs6110695 AA genotype group (n = 129) and rs6110695 AG genotype group (n = 10). Plasma global metabolic profiling was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). To estimate the predictive abilities of WBC count models using the rs6110695 genotype and/or significant differential metabolites, multiple linear regression analysis and receiver operating characteristic (ROC) curve analysis were conducted. The AG genotype had greater WBC-to-apolipoprotein (apo) A-I ratios; counts of WBCs, lymphocytes, monocytes, and granulocytes; monocyte-to-lymphocyte ratio (MLR); and monocyte-to-platelet ratio (MPR) than the AA genotype. In terms of metabolic profile, indoleacetic acid, and butyrylcarnitine levels were considerably distinct between the two groups, and these metabolites were considered to be meaningful prognostic variables for the rs6110695 genotype. Finally, ROC curve analysis demonstrated that the model containing the rs6110695 genotype and the two main metabolites was reliable. The present study revealed that individuals carrying the rs6110695 AG genotype with high plasma indoleacrylic acid and butyrylcarnitine levels might have elevated WBC counts. The rs6110695 genotype and the concentrations of indoleacrylic acid and butyrylcarnitine could contribute to reducing the risk of chronic diseases in the future.

The role of peripheral white blood cell counts in the association between central adiposity and glycemic status

AIMS

Although central adiposity is a well-known risk factor for diabetes, the underlying mechanism remains unclear. The aim of this study was to explore the potential mediation role of circulating WBC counts in the association between central adiposity and the risk of diabetes.

MATERIALS AND METHODS

A cross-sectional study was conducted using data from the Fuqing cohort study, which included 6,613 participants aged 35-75 years. Logistic regression analysis and Spearman's rank correlation analysis were used to examine the relationships between waist-to-hip ratio, WBC counts and glycemic status. Both simple and parallel multiple mediation models were used to explore the potential mediation effects of WBCs on the association of waist-to-hip ratio with diabetes.

RESULTS

The study revealed a positive relationship between waist-to-hip ratio and risk of prediabetes (OR = 1.53; 95% CI, 1.35 to 1.74) and diabetes (OR = 2.89; 95% CI, 2.45 to 3.40). Moreover, elevated peripheral WBC counts were associated with both central adiposity and worsening glycemic status (P < 0.05). The mediation analysis with single mediators demonstrated that there is a significant indirect effect of central adiposity on prediabetes risk through total WBC count, neutrophil count, lymphocyte count, and monocyte count; the proportions mediated were 9.92%, 6.98%, 6.07%, and 3.84%, respectively. Additionally, total WBC count, neutrophil count, lymphocyte count, monocyte count and basophil count mediated 11.79%, 11.51%, 6.29%, 4.78%, and 1.76%, respectively, of the association between central adiposity and diabetes. In the parallel multiple mediation model using all five types of WBC as mediators simultaneously, a significant indirect effect (OR = 1.09; 95% CI, 1.06 to 1.14) were observed, with a mediated proportion of 12.77%.

CONCLUSIONS

Central adiposity was independently associated with an elevated risk of diabetes in a Chinese adult population; levels of circulating WBC may contribute to its underlying mechanisms.

Validation of the Framingham Diabetes Risk Model Using Community-Based KoGES Data

BACKGROUND

An 8-year prediction of the Framingham Diabetes Risk Model (FDRM) was proposed, but the predictor has a gap with current clinical standards. Therefore, we evaluated the validity of the original FDRM in Korean population data, developed a modified FDRM by redefining the predictors based on current knowledge, and evaluated the internal and external validity.

METHODS

Using data from a community-based cohort in Korea (n = 5,409), we calculated the probability of diabetes through FDRM, and developed a modified FDRM based on modified definitions of hypertension (HTN) and diabetes. We also added clinical features related to diabetes to the predictive model. Model performance was evaluated and compared by area under the curve (AUC).

RESULTS

During the 8-year follow-up, the cumulative incidence of diabetes was 8.5%. The modified FDRM consisted of age, obesity, HTN, hypo-high-density lipoprotein cholesterol, elevated triglyceride, fasting glucose, and hemoglobin A1c. The expanded clinical model added γ-glutamyl transpeptidase to the modified FDRM. The FDRM showed an estimated AUC of 0.71, and the model's performance improved to an AUC of 0.82 after applying the redefined predictor. Adding clinical features (AUC = 0.83) to the modified FDRM further improved in discrimination, but this was not maintained in the validation data set. External validation was evaluated on population-based cohort data and both modified models performed well, with AUC above 0.82.

CONCLUSION

The performance of FDRM in the Korean population was found to be acceptable for predicting diabetes, but it was improved when corrected with redefined predictors. The validity of the modified model needs to be further evaluated.

Association between systemic immune-inflammation index and diabetes: a population-based study from the NHANES

Background

Systemic Immune-Inflammation Index (SII) has been reported to be associated with diabetes. We aimed to assess possible links between SII and diabetes.

Methods

Data were obtained from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) database. After removing missing data for SII and diabetes, we examined patients older than 20 years. Simultaneously, the relationship between SII and diabetes was examined using weighted multivariate regression analysis, subgroup analysis, and smooth curve fitting.

Results

There were 7877 subjects in this study, the average SII was 524.91 ± 358.90, and the prevalence of diabetes was 16.07%. Weighted multivariate regression analysis found that SII was positively associated with diabetes, and in model 3, this positive association remained stable (OR = 1.04; 95% CI: 1.02-1.06; p = 0.0006), indicating that each additional unit of SII, the possibility of having diabetes increased by 4%. Gender, age, BMI, regular exercise, high blood pressure, and smoking did not significantly affect this positive link, according to the interaction test (p for trend>0.05).

Discussion

Additional prospective studies are required to examine the precise connection between higher SII levels and diabetes, which may be associated with higher SII levels.

White cell count trajectory and type 2 diabetes in health management population: a retrospective cohort study

OBJECTIVE

The purposes of current research were to investigate the time-dependent dynamic alteration of white cell count (WCC) in health management populations and to analyse its association with the type 2 diabetes mellitus (T2DM).

DESIGN

Retrospective cohort research.

SETTING

Shengjing Hospital of China Medical University in China's Shenyang.

PARTICIPANTS

The number of non-diabetic subjects (median age: 40 years) totaled 7924 in the present work.

PRIMARY AND SECONDARY OUTCOME MEASURES

Assessment and grouping of changes in WCC between 2016 and 2019 were accomplished through group-based trajectory modelling. Newly diagnosed incidence associated with T2DM was estimated based on varying trajectories of WCC by the Kaplan-Meier method. Statistical differences in the incidences of new-onset T2DM among various WCC trajectory groups were examined through log-rank test. The influence of WCC trajectory alterations on the new-onset T2DM was evaluated with a multiparameter Cox (proportional-hazards) model.

RESULTS

During a 3-year (2016-2019) period, the T2DM development was noted in 3.14% (249) of the subjects. The trajectory model of WCC change was divided into four groups. For participants with low stability (trajectory 1), medium stability (trajectory 2), medium stability (trajectory 3) and high stability (trajectory 4), the incidence of T2DM was separately 2.2%, 2.62%, 4.82% and 7.4%, respectively. After adjusting for the underlying confounders, new-onset T2DM HRs (95% CIs) for trajectories 3 and 4 were separately 1.94 (1.32 to 2.83) and 3.08 (1.82 to 5.21) compared with the trajectory 1, implying that the T2DM risks were statistically significantly high.

CONCLUSION

The 3-year T2DM incidence was impacted independently by the WCC trajectory fluctuations. The grouping trajectory can reflect the dynamic change of WCC over time, which is more representative than the measured WCC at a single time point.

Relationship between the ApoB/ApoA-I ratio trajectory and risk of type 2 diabetes in China: a retrospective cohort study

PURPOSE

Little research has investigated the correlation of changes in long-term apolipoprotein B/apolipoprotein A-I (ApoB/ApoA-I) ratio with risk of new-onset type 2 diabetes (T2D) among ordinary people. Therefore, the research took long-term ApoB/ApoA-I ratio trajectories as independent variables for exploring their association with the risk of newly diagnosed T2D.

METHODS

Altogether 5362 non-diabetic participants with a median age of 49 were enrolled in the cohort study. Their ApoB/ApoA-I ratio trajectories from 2016 to 2019 were analyzed and grouped using group-based trajectory modeling. The Kaplan-Meier approach was employed for calculating the newly diagnosed T2D-related incidence with different ApoB/ApoA-I ratio trajectories. A log-rank test was conducted for testing the presence of statistical difference in new-onset T2D incidence among the different ApoB/ApoA-I ratio trajectory groups. A multivariate Cox proportional hazards regression model was adopted for analyzing how ApoB/ApoA-I ratio trajectory changes affected new-onset T2D.

RESULTS

From 2016 to 2019, 199 patients developed T2D (3% in 3 years). The incidence of T2D was 2.0%, 3.28%, 5.86%, and 6.92% for low, middle, upper, and high ApoB/ApoA-I ratio trajectories, respectively. Following adjustment of underlying confounding factors, in contrast to low ApoB/ApoA-I ratio trajectory, new-onset T2D risk ratios and hazard ratio (HR) (95% confidence intervals [CI]) for the middle lower ApoB/ApoA-I ratio trajectory, and upper middle and high ApoB/ApoA-I ratio trajectories were [HR (95% CI)] 1.35(0.88-2.08), 1.98(1.27-3.09) and 2.42(1.35-4.34), respectively, indicating high and statistically significant risks of T2D.

CONCLUSION

Variations of the ApoB/ApoA-I ratio trajectory exerted independent effects on the 3-year incidence of T2D. Long-term monitoring on the ApoB/ApoA-I ratio locus may help improve the identification on patients with T2D.

Novel predictor of the occurrence of DKA in T1DM patients without infection: A combination of neutrophil/lymphocyte ratio and white blood cells

The role of inflammation has been identified in the pathogenesis of diabetic ketoacidosis (DKA). The neutrophil/lymphocyte ratio (NLR) and white blood cells (WBC) can be used to predict a systemic inflammatory response. Changes in NLR and WBC levels have never been explored in type 1 diabetes mellitus (T1DM) patients with DKA and an uninfected state. This retrospective study included a total of 644 participants. NLR and WBC were measured in the control group (n = 316) and in T1DM patients with mild-DKA (n = 92), severe-DKA (n = 52), and non-DKA (n = 184) in an uninfected state. Then, we assessed the independent predictors of DKA occurrence in T1DM patients in an uninfected state. The diagnostic performance of variables was determined by receiver operating characteristic curve analysis. Serum NLR of T1DM patients is significantly higher than that of normal controls, and if DKA occurs, NLR increases further and increases with the severity of DKA. In addition to diastolic blood pressure, blood urea nitrogen, glycated hemoglobin (HbA1c), and WBC, NLR was also independently associated with DKA in T1DM patients with an uninfected state (OR = 1.386, 95% CI: 1.127-1.705, p = 0.002). Furthermore, the diagnosis analysis showed that except for NLR and WBC, the area under the curve (AUC) of indicators with a statistical difference in patients with and without DKA were 0.747 for DKA diagnosis, and after the addition of NLR and WBC, the AUC was 0.806. The increased NLR level represents a low-cost and highly accessible predictor for DKA in T1DM patients with an uninfected state. The addition of inflammation indicators can play a statistically significant role in the prediction model of the DKA occurrence.

High-sensitivity C-reactive protein and risk of type 2 diabetes: A nationwide cohort study and updated meta-analysis

OBJECTIVE

To prospectively examine the association of high sensitivity C-reactive protein (hs-CRP) with incident type 2 diabetes mellitus (T2DM) among middle-aged and elderly Chinese, and validate the association in an updated meta-analysis of prospective studies.

METHODS

We used data from the China Health and Retirement Longitudinal Study, started in 2011-2012 with follow ups in 2013-2014 and 2015-2016. Multivariable Cox proportional hazard regressions were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between hs-CRP level and incident T2DM. An updated meta-analysis was conducted to combine our estimates with those in previous prospective studies.

RESULTS

Included in the analyses were 7985 participants (mean age: 59.38 years; men: 46.73%). Higher hs-CRP was associated with increased risk of T2DM (multivariable-adjusted HR, 1.30; 95% CI: 1.03, 1.64 for comparing extreme quartiles). The association was stronger in participants with body mass index (BMI) of 24.0 kg/m² or higher than those with a BMI lower than 24.0 kg/m² (p for interaction = 0.038). In a meta-analysis of 28 cohorts, 2 case-cohort, and 6 nested case-control studies among 125,356 participants with 10,759 cases, the pooled relative risk for T2DM was 1.77 (95% CI: 1.60, 1.96) for the highest versus lowest level of hs-CRP.

CONCLUSIONS

Hs-CRP was associated with higher risk of T2DM in middle-aged and elderly Chinese, and this association was confirmed by an updated meta-analysis of prospective studies. Our findings highlight the role of elevated hs-CRP in the development of T2DM.

Network of biomarkers and their mediation effects on the associations between regular exercise and the incidence of cardiovascular & metabolic diseases

This study aimed to understand the biological process related to the prevention of cardiovascular & metabolic diseases (CMD), including diabetes, hypertension, and dyslipidemia via regular exercise. This study included 17,053 subjects aged 40–69 years in the Health Examinees Study from 2004 to 2012. Participation in regular exercise was investigated by questionnaires. Data on 42 biomarkers were collected from anthropometric measures and laboratory tests. We examined the associations between regular exercise and biomarkers using general linear models, between biomarkers and the risk of CMD using cox proportional hazard models, and the mediation effect of biomarkers using mediation analyses. Biomarker networks were constructed based on the significant differential correlations (p < 0.05) between the exercise and non-exercise groups in men and women, respectively. We observed significant mediators in 14 and 16 of the biomarkers in men and women, respectively. Triglyceride level was a noteworthy mediator in decreasing the risk of CMD with exercise, explaining 23.79% in men and 58.20% in women. The biomarker network showed comprehensive relationships and associations among exercise, biomarkers, and CMD. Body composition-related biomarkers were likely to play major roles in men, while obesity-related biomarkers seemed to be key factors in women.

High intake of vegetables is linked to lower white blood cell profile and the effect is mediated by the gut microbiome

BACKGROUND

Chronic inflammation, which can be modulated by diet, is linked to high white blood cell counts and correlates with higher cardiometabolic risk and risk of more severe infections, as in the case of COVID-19.

METHODS

Here, we assessed the association between white blood cell profile (lymphocytes, basophils, eosinophils, neutrophils, monocytes and total white blood cells) as markers of chronic inflammation, habitual diet and gut microbiome composition (determined by sequencing of the 16S RNA) in 986 healthy individuals from the PREDICT-1 nutritional intervention study. We then investigated whether the gut microbiome mediates part of the benefits of vegetable intake on lymphocyte counts.

RESULTS

Higher levels of white blood cells, lymphocytes and basophils were all significantly correlated with lower habitual intake of vegetables, with vegetable intake explaining between 3.59 and 6.58% of variation in white blood cells after adjusting for covariates and multiple testing using false discovery rate (q < 0.1). No such association was seen with fruit intake. A mediation analysis found that 20.00% of the effect of vegetable intake on lymphocyte counts was mediated by one bacterial genus, Collinsella, known to increase with the intake of processed foods and previously associated with fatty liver disease. We further correlated white blood cells to other inflammatory markers including IL6 and GlycA, fasting and post-prandial glucose levels and found a significant relationship between inflammation and diet.

CONCLUSION

A habitual diet high in vegetables, but not fruits, is linked to a lower inflammatory profile for white blood cells, and a fifth of the effect is mediated by the genus Collinsella.

TRIAL REGISTRATION

The ClinicalTrials.gov registration identifier is NCT03479866 .

Association between White Blood Cells Count and Diabetes Mellitus in Tabari Cohort Study: A Case-Control Study

BACKGROUND

White Blood Cells (WBC) can be a useful marker to predict diabetes. In this study, we aimed to investigate the association between WBC count with type 2 diabetes in a large-scaled population-based cohort study.

METHODS

In the present study we used a subset of data collected in enrolment phase of Tabari cohort study. Participants with fasting blood glucose ≥126 or those who report as having diabetes or taking glucose-lowering medications were selected as case group (1765 participants) and control group included participants who did not report as having diabetes (1765 participants) and they randomly selected from the baseline population. Hematology indices were measured for all participants using Celltac Alpha MEK-6510 K. Chi-squared and independent t-test were used to compare categorical and continuous variables, respectively.

RESULTS

The mean of WBC in diabetic patients and control group was 6.89 ± 1.67 and 6.37 ± 1.49 respectively (P ≤ 0.001). The odds of diabetes based on WBC count in crud model was 1.23 [CI 95% 1.181.28] and after adjustment for all possible confounding factor was 1.17 [CI 95% 1.111.23].

CONCLUSIONS

Results of the present study showed a significant association between WBC count and diabetes. This association remained significant after adjustment for all possible confounders.

Body-weight fluctuation and risk of diabetes in older adults: The China Health and Retirement Longitudinal Study (CHARLS)

AIMS

Body-weight fluctuation is associated with an increased risk of all-cause mortality. Yet no studies investigate its association with risk of diabetes in adults aged ≥ 60 years. This study aimed to address this issue.

METHODS

A total of 1,565 participants free of diabetes at baseline in the CHARLS were followed for 4-year. Body-weight was collected at baseline and every 2-year. Body-weight fluctuation was primarily calculated as the root-mean-square-error deviation from the regression line of body-weights against years. The risk of diabetes was estimated using logistic regression analysis.

RESULTS

During the 4-year follow-up, 153 participants developed diabetes. The risk of diabetes was increased by 23% (odds ratio [OR] 1.23, 95% confidence interval [CI] 1.06 to 1.43) per every 1-standard deviation higher of body-weight fluctuation after controlling for cardiovascular risk factors. The association appeared pronounced among participants with poor physical performance (both P < 0.03). Participants with overweight/obesity and a high body-weight fluctuation had the largest increase in the risk for diabetes (OR 3.03). Body-weight fluctuation correlated with hemoglobin A1c and white blood cells at follow-up or their change scores from baseline, especially in females (all P < 0.02).

CONCLUSIONS

Body-weight fluctuation led to an increased risk of diabetes in adults aged ≥ 60 years.

Correlation Between Ideal Cardiovascular Health Metrics and Plasma hs-CRP Levels in a North China Population: One Four-Year Follow-Up Study

Background

This prospective cohort study aimed to evaluate the potential association of ideal cardiovascular health metrics with the plasma levels of highly sensitive C-reactive protein (hs-CRP) among people in North China.

Methods

A total of 80,968 participants were included in this study at baseline. Data relating to seven health metrics and plasma hs-CRP levels were collected at baseline and the end of follow-up. The change in health metrics of each individual was compared and recorded. The potential association of gain or loss of each health metric, as well as the change in the total number of health metrics that each individual had during follow-up, with the risk of increased hs-CRP level, were explored by multiple Cox proportional hazards models.

Results

A total of 72,321 participants (94.51%) completed the follow-up, and the average follow-up time was 4.1 years. Ideal body mass index (BMI), physical activity, smoking status and total cholesterol all had significant impacts on hs-CRP levels, with ideal BMI having the largest impact. Losing ideal BMI during follow-up raised the probability of hs-CRP increase during the follow-up time by 1.72 (95% CI, 1.59–1.86) times for men and 2.05 (95% CI, 1.76–2.39) times for women. The effects of ideal salt intake and blood pressure on hs-CRP levels were uncertain. Changes in the total number of ideal metrics for each individual had a significant cumulative effect on hs-CRP. The hazard ratio of loss of four to six health metrics during follow-up on the risk of hs-CRP increase was 1.69 (95% CI, 1.38–2.06) for men and 1.52 (95% CI, 1.13–2.04) for women.

Conclusion

Loss or gain of ideal cardiovascular health metrics is associated with significant fluctuations in plasma hs-CRP levels. The cardiovascular benefits brought by the ideal health metrics are mediated at least in part by reducing systemic inflammation in the body.

Monocyte-lymphocyte ratio is a valuable predictor for diabetic nephropathy in patients with type 2 diabetes

Diabetic nephropathy (DN) is serious threat to human health. Therefore, early prediction of its occurrence is important. This study aimed to assess the predictive significance of monocyte-lymphocyte ratio (MLR) for DN.A total of 301 patients with type 2 diabetes (T2D), including 212 T2D patients without diabetic-related complications and 99 DN patients, were enrolled. Peripheral white blood cells were measured before treatment to calculate MLR, and the risk factors and predictive significance for T2D and DN were assessed.T2D patients without diabetic-related complications had higher MLR than control patients (P < .01). However, MLR was significantly higher in DN patients than in T2D patients without diabetic-related complications (P < .001). According to MLR quartiles, higher MLR in DN patients was correlated with higher serum creatinine, estimated glomerular filtration rate, and urinary albumin excretion (UAE) levels (P < .01 or P < .001). Furthermore, MLR was positively correlated with UAE level (R = 0.5973; P < .01) and an independent predictor for DN (odds ratio: 7.667; 95% confidence interval [CI]: 3.689-21.312; P < .001). The area under the receiver-operating characteristic (ROC) curve for MLR was 0.874 (95%CI: 0.830-0.918, P < .001). When the optimal cutoff value was 0.23, the sensitivity and specificity of MLR for DN prediction were 0.85 and 0.74, respectively.The present findings suggest that MLR is a powerful independent predictor for DN.