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The prevalence of cardiovascular diseases (CVDs) in Korea tends to be increasing. It has worsened during the COVID-19 pandemic. Increasing evidence shows heavy metals are associated with increased CVD risk. We aimed to determine the association between the serum heavy metal levels and 10-year risk of CVDs and to predict risks of CVDs based on marginal effects. Heavy metals were measured by a graphite furnace atomic absorption spectrometry and direct mercury analyzer. The results show a significant relationship between the increase in cadmium, lead, mercury, hs-CRP levels and the 10-year risk of CVD after adjustment for serum cotinine, age group, sex, body mass index, a family history of CVDs, diabetes or hyperlipidemia, high-risk drinking, physical activity, and diabetes. A doubling of serum cadmium, lead, mercury, and hs-CRP was associated with the increase in the 10-year risk of CVD by 0.14%, 0.10%, 0.11% and 0.22%, respectively. Therefore, a special concern should be given to the harmful impacts of heavy metals on the 10-year risk of CVD. It is important to develop a prevention strategy targeting the high-risk population to slow down this progression to risk factors related to heavy metals and reduce prevalence. Remarkedly, hs-CRP is the most validated and widely used inflammatory marker, and could be a potential clinical value in predicting and monitoring CVDs.

A scarcity of research assesses the effects of exposure to a combination of chemicals on lipid profiles as well as molecular mechanisms related to dyslipidemia. A cross-sectional study of 3692 adults aims to identify the association between chemical mixtures, including blood and urine 26 chemicals, and lipid profiles among Korean adults (aged ≥ 18) using linear regression models, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR). In silico toxicogenomic data-mining, we assessed molecular mechanisms linked with dyslipidemia, including genes, miRNAs, pathways, biological processes, and diseases. In the linear regression models, heavy metals, volatile organic compound metabolites, and phthalate metabolites were found to be related to HDL-C, triglycerides, LDL-C, total lipids, and total cholesterol, and significant trends were observed for these chemical quartiles ( p  < 0.01). The WQS index was significantly linked with HDL-C, triglycerides, LDL-C, total cholesterol, and total lipids. The qgcomp index also found a significant association between chemicals and HDL-C, triglycerides, and total lipids. In BKMR analysis, the overall effect of the chemical mixture was significantly associated with HDL-C, triglycerides, total cholesterol, and total lipids. We found that mixed chemicals interacted with the PPARA gene and were linked with dyslipidemia. Several pathways (“SREBF and miR33 in cholesterol,” “estrogen receptor pathway and lipid homeostasis,” and “regulation of PGC-1α”), “negative regulation of hepatocyte apoptotic process,” “negative regulation of sequestering of triglycerides,” “regulation of hepatocyte apoptotic process,” and “negative regulation of cholesterol storage,” and “abdominal obesity metabolic syndrome” were identified as key molecular mechanisms that may be affected by mixed chemicals and implicated in the development of dyslipidemia. The highest interaction and expression of miRNAs involved in the process of dyslipidemia were also described. Especially, the cutoff levels for chemical exposure levels related to lipid profiles were also provided.

Little is known about associations between depression and serum heavy metal levels, dietary vitamin intakes. Thus, we sought to determine the nature of these associations and to predict risks of depression using marginal effects. A data set of 16,371 individuals aged ≥10 years that participated in Korea National Health and Nutrition Examination Surveys (KNHANES) conducted from 2009 to 2017 (excluding 2014 and 2015) was used to obtain information on sociodemographics, family histories, lifestyles, serum heavy metal levels, food intakes, and depression. Serum cadmium (Cd) and lead (Pb) levels were analyzed by graphite furnace atomic absorption spectrometry and mercury (Hg) levels using a mercury analyzer. Daily vitamin intakes were calculated by 24-h dietary recall. The results obtained showed that females are at higher risk of depression than males. A doubling of serum Cd was associated with a 21% increase in depression (AOR 1.21, 95% CI: 1.07–1.37, p = 0.002), whereas twofold increases in daily vitamin B1, B3 and vitamin A intakes reduced the risk of depression by 17% (0.83, 95% CI: 0.73–0.95, p = 0.005), 20% (0.80, 95% CI: 0.70–0.91, p = 0.001), and 8% (0.92, 95% CI: 0.85–0.99, p = 0.020), respectively. Interactions between heavy metals, vitamin intakes, and sex did not influence the risk of depression. The result shows that increased daily dietary vitamin intake might protect the public against depression. Further studies are needed to reduce the risks posed by heavy metals and to determine more comprehensively the effects of daily dietary vitamin intake on depression.

Gemigliptin is one of the latest dipeptidyl peptidase-4 inhibitors developed by LG Life Sciences. Since the early 2000s, several randomized controlled trials (RCTs) of gemigliptin have been conducted. However, no study has directly compared its antidiabetic effects through a systematic review and meta-analysis. Therefore, in this study, we performed a systematic review and meta-analysis on RCTs. In particular, a subsequent meta-analysis was performed using Bayesian inference, and an updated quality management system model was integrated throughout our study. The mean differences and 95% confidence intervals for glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), homeostatic model assessment beta cell function (HOMA-β), and low-density lipoprotein (LDL) were evaluated for the efficacy outcomes of gemigliptin as compared to those of placebo and other oral antidiabetic drugs (OADs). In conclusion, we found that gemigliptin was superior to placebo and comparable to other OADs in terms of the effect on HbA1c, FPG, HOMA-β, and LDL. Further, gemigliptin was more effective than other OADs in HbA1c and HOMA-β in Bayesian inference analysis and statistically significant to other OADs in HbA1c and HOMA-β in sensitivity analysis excluding metformin. However, to confirm the results, more studies need to be analysed and the minimum clinically important difference must be applied.

The burden of metabolic syndrome (MetS) has increased worldwide, especially during the COVID-19 pandemic, and this phenomenon is related to environmental, dietary, and lifestyle risk factors. We aimed to determine the association between the levels of serum heavy metals, hs-CRP, vitamins, and curry intake and to predict risks of MetS based on marginal effects. A data set of 60,256 Koreans aged ≥ 15 years between 2009 and 2017 was used to obtain information on sociodemographic, lifestyle, family history characteristics, MetS, food intake survey, and serum heavy metals. Daily intake of vitamins was measured by a one-day 24 h recall, and curry consumption was calculated using a food frequency questionnaire. Serum heavy metal levels were quantified by graphite furnace atomic absorption spectrometry and using a mercury analyzer. We found that vitamin B1, B2, B3, C, and A intakes were significantly lower in subjects with than without MetS. In contrast, serum levels of Pb, Hg, Cd, vitamin A, E, and hs-CRP were significantly higher in subjects with MetS. The risk of MetS was significantly lower for high curry consumers than low curry consumers (adjusted odds ratio 0.85, 95%CI 0.74–0.98). The risks of MetS were reduced by 12% and 1%, when vitamin B1 and C intakes increased by one mg, respectively, but were increased by 14%, 3%, and 9%, when serum levels of Pb, Hg, and hs-CRP increased by one unit. These results show that the potential health benefits resulting from vitamin and curry intakes could protect the public against the dual burden of communicable and non-communicable diseases. Further studies are required to reduce risk factors associated with serum heavy metal levels and to determine whether interactions between vitamin and curry consumption influence the presence of MetS.

The present study aimed to determine thiamine intake levels and the association between thiamine intake, diabetes, cardiovascular diseases and mental health. Participants were interviewed to obtain data on socio-demographic characteristics, lifestyle, current medications, medical and family history. The daily intake of thiamine was assessed by a 24-h recall. The mean age of the 34 700 study subjects was 42⋅9 years (sd 22⋅8, min–max: 1–80) and 19 342 (55⋅7 %) were women. The levels of thiamine intake were 1⋅126 mg (2016), 1⋅115 mg (2017) and 1⋅087 mg (2018) for women, which were equal to or only slightly above the recommended intake of 1⋅10 mg/d for women. The levels of thiamine intake from 2014–15 and 2016–18 significantly decreased. The estimated percentage of insufficient thiamine intake was 37⋅8 % (95 % CI 37⋅3, 38⋅4). Multivariable regression analysis adjusted for potential confounders showed that thiamine intake was critically associated with lower risks of hypertension, MI or angina, type 2 diabetes, depression and dyslipidemia. The daily thiamine intake from food can reversal the risks of hypertension (OR 0⋅95; 95 % CI 0⋅90, 0⋅99), MI or angina (OR 0⋅84; 95 % CI 0⋅74, 0⋅95), type 2 diabetes (OR 0⋅86; 95 % CI 0⋅81, 0⋅93), depression (OR 0⋅90; 95 % CI 0⋅83, 0⋅97) and dyslipidemia (OR 0⋅90; 95 % CI 0⋅86, 0⋅95), respectively. Further works are needed to identify the effects of thiamine and non-communicable diseases (NCDs) and mental health. A preventive thiamine supplementation strategy should be adopted to target NCDs and mental health and risk factors associated with thiamine deficiency. The optimisation of NCD control and mental health protection is also a vital integral part of Korea's public health system.

Evogliptin is one of the latest dipeptidyl peptidase-4 (DPP-4) inhibitor, and a number of clinical trials have been performed following its development, including several randomized controlled trials (RCTs) performed to evaluate its efficacy and tolerability. In our study, we performed a systematic review and meta-analysis of its efficacy and tolerability by collecting RCTs and confirmed the results with Bayesian inference. Moreover, an updated quality-management system was integrated into the study process of systematic review. PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov were searched for literature published between May 1990 and November 2020. We selected 6 homogeneous RCTs in 1017 subjects for efficacy and 1070 subjects for tolerability analysis. Regarding the efficacy profile, the mean differences from baseline (95% CIs) in hemoglobin (Hb) A1c and fasting plasma glucose (FPG) were generated as end points and derived from each study. Regarding the tolerability profile, risk ratios of adverse events (AEs), serious AEs, adverse drug reactions, and hypoglycemia were generated from baseline to outcome measurements as derived from each study. A subsequent meta-analysis was performed with Bayesian inference. For HbA1c and FPG, the results suggested a statistically significant improvement with evogliptin versus placebo (HbA1c, −0.44 [95% CI, −0.54 to −0.34; P < 0.00001] and posterior median, −0.38 [95% CI, −0.51 to −0.24]; FPG, −0.61 [95% CI, −0.90 to −0.31; P < 0.0001] and posterior median, −0.48 [95% CI, −0.90 to −0.16]), but no statistically significant difference with evogliptin versus other DPP-4 inhibitors (HbA1c, −0.01 [95% CI, −0.14 to 0.12] and posterior median, −0.06 [95% CI, −0.25 to 0.12]; FPG, 0.17 [95% CI, −0.10 to 0.44] and posterior median, 0.27 [95% CI, −0.12 to 0.65]). In terms of tolerability, the overall prevalence of adverse events, including hypoglycemia, was similar between evogliptin and other DPP-4 inhibitors and placebo. Evogliptin appears more efficacious in terms of changes in HbA1c and FPG compared with placebo, with an efficacy comparable to those of other DPP-4 inhibitors, although with the limited data studied and the minuscule sample sizes, the predictions of posterior medians, mean differences, and risk ratios of HbA1c, FPG, and AEs by Bayesian inference were consistent with our findings through our quality-management system. [Display omitted]

Fimasartan, one of the newest angiotensin receptor blockers (ARBs) available worldwide, has been investigated extensively since its initial development. Our study group conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating fimasartan and comparators for their blood pressure (BP)-lowering effect. Moreover, we employed a cross-inference (frequentist and Bayesian inference) system, which has never been used in the medical field, to confirm the results of our study. In addition, a quality management system was integrated throughout the study for data quality. PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, ClinicalKey, and ClinicalTrial.gov were searched for RCT studies from March 1998 to March 2022. In each study, the mean differences (MDs) and 95% CIs were identified for reductions in clinic sitting systolic and diastolic BP (SiSBP/SiDBP) or 24-hour mean systolic BP and diastolic BP by ambulatory BP monitoring (ASBP/ADBP) from baseline between the fimasartan and comparator groups, followed by meta-analysis. A subsequent meta-analysis was performed with frequentist and Bayesian inference as a tool in the cross-checking system. Eleven RCTs with a total of 2459 subjects were included in the study. The clinic SiSBP/SiDBP–lowering effect of fimasartan was significantly greater relative to those of comparators (MD for clinic SiSBP, −2.58 mm Hg [95% CI, −4.35 to −0.81; P = 0.004]; MD for clinic SiDBP, −2.13 mm Hg [95% CI, −2.96 to −1.30; P = 0.00001]). The ASBP/ADBP–lowering effect of fimasartan was also significantly greater relative to those of comparators (MD for ASBP, −3.58 mm Hg [95% CI, −5.74 to −1.43; P = 0.001]; MD for ADBP, −1.99 mm Hg [95% CI, −3.34 to −0.63; P = 0.004]). Fimasartan seems to be more effective in lowering BP than its comparators, including other ARBs. Although there is a limited amount of data and a minuscule number of study subjects available, the results of cross-inference (frequentist + Bayesian) were fairly consistent with the meta-analysis results through our quality management system. [Display omitted]

Little is known about the association between a mixture of heavy metals and obesity among individuals ≥50 years of age with comorbidities. Thus, we identified the associations of serum cadmium (Cd), lead (Pb), and mercury (Hg) with obesity using linear regression models; weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) were conducted as secondary analyses. Of the 6434 subjects included in the analysis, 13.8% had obesity and 44.6% had abdominal obesity. In the logistic regression model, serum Hg was associated with obesity and abdominal obesity, and significant trends were observed for these heavy metal tertiles (p < 0.001). Serum Hg levels were also associated with body mass index (BMI) and waist circumference (WC). The WQS index was significantly associated with both obesity (OR = 1.43, 95% CI: 1.40–1.46) and abdominal obesity (β = 1.51, 95% CI: 1.48–1.54). The qgcomp index also found a significant association between heavy metals and both obesity (OR = 1.35, 95% CI: 1.12–1.63) and abdominal obesity (OR = 1.34, 95% CI: 1.12–1.60). Serum Hg was the most heavily weighed heavy metal in these models. In BKMR analysis, the overall effect of the mixture was significantly associated with obesity, BMI, and WC. Serum Hg showed positive trends and was observed as the most important factor associated with obesity, BMI, and WC. Our findings were largely robust to secondary analyses that used three novel mixture modeling approaches: WQS, qpcomp, and BKMR. Given increasing exposure to heavy metals, well-characterized cohorts of individuals aged ≥50 years are required to determine the mixed effects of heavy metals on obesity and related diseases.

We aim to examine the association between chemical mixtures and obesity. Blood and urinary levels of tween-six chemicals were measured in adults who participated in the KoNEHS. We identified the associations of chemicals with obesity using linear regression models. Weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) were conducted as secondary analyses. Of the 3,692 participants included in the analysis, 18.0% had obesity. In the logistic regression model, mercury (Hg), lead (Pb), and 3PBA levels were associated with obesity, and significant trends were observed for these chemical tertiles ( p  < 0.001). Hg, Pb, and 3PBA levels were also associated with BMI. The WQS index was significantly associated with both obesity ( OR  = 2.15, 95% CI: 2.11–2.20) and BMI ( β  = 0.39, 95% CI: 0.37–0.51). The qgcomp index also found a significant association between chemicals and both obesity ( OR  = 1.70, 95% CI: 1.56–1.85) and BMI ( β  = 0.40, 95% CI: 0.39–0.41). Hg, Pb, and 3PBA were the most heavily weighed chemicals in these models. In BKMR analysis, the overall effect of the mixture was significantly associated with obesity. Hg, Pb, and 3PBA showed positive trends and were observed as the most important factors associated with obesity. Given increasing exposure to chemicals, there is a need to investigate the associations between chemical exposures, either separately or together, and incident obesity risk factors in well-characterized cohorts of different populations, and to identify potential approaches to chemical exposure prevention.