Association of Serum Magnesium with Insulin Resistance and Type 2 Diabetes among Adults in China

Hypomagnesemia induces impaired glucose metabolism and insulin resistance in patients with Gitelman syndrome

AIMS

To investigate the contributing factors of impaired glucose metabolism in patients with Gitelman syndrome (GS).

METHODS

This study collected clinical data and conducted oral glucose tolerance tests (OGTT) on 44 GS patients, with 60 non-functioning adrenal incidentaloma (NFAI) patients serving as controls.

RESULTS

Compared to NFAI patients, GS patients exhibited a significantly higher prevalence of impaired glucose metabolism (P < 0.001), with markedly higher homeostasis model assessment of insulin resistance (HOMA-IR), lower quantitative insulin sensitivity check index, and lower Matsuda index compared to NFAI patients (all P < 0.001). The homeostasis model assessment for β cells was elevated (P = 0.003) and the insulin secretion sensitivity index-2 was reduced (P = 0.007) in GS patients relative to NFAI patients. Logistic regression identified hypomagnesemia (P = 0.042) and hypokalemia (P = 0.046) as risk factors for dysregulated glucose metabolism in GS patients. Additionally, higher body mass index (BMI) (P = 0.016) and hypomagnesemia (P = 0.045) were significant contributors to IR. Notably, GS patients had a steeper linear regression slope between BMI and HOMA-IR compared to NFAI patients (P = 0.016). A negative linear correlation between plasma magnesium and BMI (R = 0.54, P < 0.001) was found in GS patients.

CONCLUSIONS

Hypomagnesemia may contribute to increased BMI, exacerbating impaired glucose metabolism and IR in GS patients.

Classification and identification of risk factors for type 2 diabetes

The risk factors for type 2 diabetes mellitus (T2DM) have been increasingly researched, but the lack of systematic identification and categorization makes it difficult for clinicians to quickly and accurately access and understand all the risk factors, which are categorized in this paper into five categories: Social determinants, lifestyle, checkable/testable risk factors, history of illness and medication, and other factors, which are discussed in a narrative review. Meanwhile, this paper points out the problems of the current research, helps to improve the systematic categorisation and practicality of T2DM risk factors, and provides a professional research basis for clinical practice and industry decision-making.

Association Between Serum Essential Metal Elements and Blood Pressure in Children: A Cohort Study

A limited number of cohort studies have explored the impact of serum essential metal elements on blood pressure (BP) or glycolipids and their regulatory mechanism in children. This study aimed to investigate the relationship between serum metal concentrations of iron (Fe), zinc (Zn), calcium (Ca), copper (Cu), and magnesium (Mg) and BP in children, and explore the potential mediating effects of glycolipid profiles. This cohort study included 1993 children (3566 BP measurements) aged 6-14 years in Chongqing, China. Serum essential metals, BP, lipid profiles, and glucose and insulin levels were measured. The relationship between serum metal levels and BP was analyzed using generalized linear and regression models, and a mediation analysis was performed to examine the potential mediating role of glycolipids. After adjusting for confounders, positive associations were found between serum Fe and Zn levels and BP parameters (all P < 0.05). A "U" style relationship between Cu and BP was found. Stronger associations were found in children aged ≤ 10 years, with sex-specific differences for Fe, Zn, and Cu. The relationship between elevated BP and serum Mg and Ca was not found. Our study found that triglycerides showed a significant relationship with Fe and Zn levels (P < 0.005). Moreover, triglycerides, partially mediate the effects of Zn on elevated BP. Serum Fe, Zn, and Cu concentrations were associated with BP in children, and age and sex differences were observed. Triglycerides may play a mediating role. These findings highlight the importance of maintaining an optimal serum essential metal status for cardiovascular health in children and suggest potential early prevention strategies.

Effects of Various Heavy Metal Exposures on Insulin Resistance in Non-diabetic Populations: Interpretability Analysis from Machine Learning Modeling Perspective

Increasing and compelling evidence has been proved that heavy metal exposure is involved in the development of insulin resistance (IR). We trained an interpretable predictive machine learning (ML) model for IR in the non-diabetic populations based on levels of heavy metal exposure. A total of 4354 participants from the NHANES (2003-2020) with complete information were randomly divided into a training set and a test set. Twelve ML algorithms, including random forest (RF), XGBoost (XGB), logistic regression (LR), GaussianNB (GNB), ridge regression (RR), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), AdaBoost (AB), Gradient Boosting Decision Tree (GBDT), Voting Classifier (VC), and K-Nearest Neighbour (KNN), were constructed for IR prediction using the training set. Among these models, the RF algorithm had the best predictive performance, showing an accuracy of 80.14%, an AUC of 0.856, and an F1 score of 0.74 in the test set. We embedded three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) in RF model for model interpretation. Urinary Ba, urinary Mo, blood Pb, and blood Cd levels were identified as the main influencers of IR. Within a specific range, urinary Ba (0.56-3.56 µg/L) and urinary Mo (1.06-20.25 µg/L) levels exhibited the most pronounced upwards trend with the risk of IR, while blood Pb (0.05-2.81 µg/dL) and blood Cd (0.24-0.65 µg/L) levels showed a declining trend with IR. The findings on the synergistic effects demonstrated that controlling urinary Ba levels might be more crucial for the management of IR. The SHAP decision plot offered personalized care for IR based on heavy metal control. In conclusion, by utilizing interpretable ML approaches, we emphasize the predictive value of heavy metals for IR, especially Ba, Mo, Pb, and Cd.

High serum magnesium level is associated with increased mortality in patients with sepsis: an international, multicenter retrospective study

Magnesium imbalances commonly exist in septic patients. However, the association of serum magnesium levels with mortality in septic patients remains uncertain. Herein, we elucidated the association between serum magnesium and all-cause mortality in septic patients from American and Chinese cohorts by analyzing data from 9099 patients in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and 1727 patients from a university-affiliated hospital' intensive care unit in China. Patients in both cohorts were categorized into five groups based on serum magnesium quintiles from the MIMIC-IV dataset. Patients with higher serum magnesium levels exhibited an increased risk of 28-day mortality in both cohorts. The restricted cubic spline (RCS) curves revealed a progressively elevated risk of 28-day mortality with increasing serum magnesium in MIMIC-IV cohort, while a J-shaped correlation was observed in institutional cohort. Our findings have validated the association between high serum magnesium and high mortality in sepsis across different races and medical conditions. Serum magnesium levels might be useful in identifying septic patients at higher mortality risk.

Dietary Potassium and Magnesium Intake with Risk of Type 2 Diabetes Mellitus Among Rural China: the Henan Rural Cohort Study

Previous studies exploring the relationship between dietary potassium and magnesium intake and the risk of type 2 diabetes mellitus (T2DM) have yielded inconsistent results and the lack evidence from rural China. Therefore, we aimed to investigate the association between dietary potassium and magnesium intake and the risk of T2DM in rural China. Data was collected from the Henan Rural Cohort Study in 2017. A validated semi-quantitative food frequency questionnaire assessed dietary potassium and magnesium intake. Logistic regression models were used to calculate odds ratio (ORs) and 95% confidence intervals (CIs) to evaluate the effect of dietary potassium, magnesium and the potassium-magnesium ratio on the risk of T2DM. A total of 38384 individuals were included in the study, and 3616 participants developed T2DM. Logistic regression analysis revealed that the OR (95% CI) of the highest versus dietary potassium and magnesium and potassium-magnesium ratio intakes were 0.67 (0.59, 0.75), 0.76 (0.67, 0.88), and 0.57 (0.50, 0.66), respectively, compared to the subjects with the lowest quartile of intakes. In addition, gender partially influences the relationship between dietary magnesium and T2DM prevalence (P-interaction = 0.042). The group with the highest dietary potassium and dietary magnesium intake had the lowest risk of T2DM, with an OR (95% CI) of 0.63 (0.51-0.77). Dietary potassium and magnesium intake are important modifiable risk factors for T2DM in rural China. Dietary potassium intake > 1.8g/day, dietary magnesium intake > 358.6mg/day and < 414.7mg/day and potassium-magnesium ratio >5.1 should be encouraged to prevent better and manage T2DM.

Mediation effect of body mass index on the association between serum magnesium level and insulin resistance in children from Mexico City

BACKGROUND/OBJECTIVES

Reduced serum magnesium (Mg) levels have been associated with obesity, insulin resistance (IR), type 2 diabetes, and metabolic syndrome in adults. However, in the children population, the evidence is still limited. In this cross-sectional study, we aimed to analyze the association of serum Mg levels with the frequency of overweight and obesity and cardiometabolic traits in 189 schoolchildren (91 girls and 98 boys) between 6 and 12 years old from Mexico City.

SUBJECTS/METHODS

Anthropometrical data were collected and biochemical parameters were measured by enzymatic colorimetric assay. Serum Mg level was analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The triglyceride-glucose (TyG) index was used as a surrogate marker to evaluate IR.

RESULTS

Serum Mg level was negatively associated with overweight (Odds ratio [OR] = 0.377, 95% confidence interval [CI] 0.231-0.614, p < 0.001) and obesity (OR = 0.345, 95% CI 0.202-0.589, p < 0.001). Serum Mg level resulted negatively associated with body mass index (BMI, β = -1.16 ± 0.26, p < 0.001), BMI z-score (β = -0.48 ± 0.10, p < 0.001) and TyG index (β = -0.04 ± 0.04, p = 0.041). Through a mediation analysis was estimated that BMI z-score accounts for 60.5% of the negative association of serum Mg level with IR (Sobel test: z = 2.761; p = 0.005).

CONCLUSION

Our results evidence that BMI z-score mediate part of the negative association of serum Mg level and IR in Mexican schoolchildren.

Association Between Serum Magnesium Levels and Glycemic Control in Type 2 Diabetes

Introduction

Serum magnesium is a crucial mineral within the human body. It is imperative for diabetic patients to maintain optimal serum magnesium levels. We focus on the relationship between glycemic control and serum magnesium in type 2 diabetes mellitus (T2DM).

Methods

The retrospective, observational, cross-sectional study comprised 1694 patients recruited from the People's Hospital of Yuxi. Fasting blood samples were collected for analysis, accompanied by the recording of participants' demographic characteristics. Patients were categorized into two groups based on whether their glycosylated hemoglobin (HbA1c) levels < 7%. A t-test was employed to identify significant differences between the two groups. Correlation coefficients were calculated using Pearson's method. A Logistic regression analysis was conducted to assess the association between variables and glycemic control. A linear regression analysis was performed to assess the relationship between serum magnesium levels and HbA1c.

Results

Patients with poor glycemic control exhibited elevated age, low-density lipoprotein (LDL-C), fasting plasma glucose (FPG), and homeostasis model assessment (HOMA-IR) compared to those with good glycemic control (P < 0.001). Additionally, total cholesterol (TC) levels were significantly higher in patients with poor glycemic control. Conversely, high-density lipoprotein (HDL-C) and serum magnesium levels were lower in patients with poor glycemic control. Serum magnesium levels exhibited negative correlations with HOMA-IR (r = -0.05, P < 0.05), HbA1c (r = -0.29, P < 0.05), and FPG (r = -0.20, P < 0.05). Moreover, serum magnesium was significantly associated with reduced odds of glycemic control (OR = 0.0005, 95% CI 0.0001-0.0027, P < 0.001).

Conclusion

The serum magnesium level in patients with T2DM is closely associated with glycemic control.

Association of Dietary Selenium Intake with Type 2 Diabetes in Middle-Aged and Older Adults in China

The relationship between distinct dietary selenium intake and type 2 diabetes (T2D) is still a topic of uncertainty. This study examined the relationship between dietary selenium intake and T2D risk among middle-aged and older Chinese adults. Dietary selenium intake was assessed through three 24 h recalls, using data from the China Health and Nutrition Survey. To investigate the relationship and the potential dose-response pattern between selenium intake and the likelihood of developing T2D, we employed both the restricted cubic spline analysis and the Cox proportional hazards model as our analytical tools. A cohort of 5970 participants aged ≥ 50 years was followed for an average of 5.44 years. The results revealed a V-shaped correlation between selenium intake and T2D risk, with the lowest risk observed at approximately 45 µg/day. Below this level, the risk decreased with an increasing selenium intake, while the risk increased between 45 and 100 µg/day. No significant association was found beyond 100 µg/day. These findings suggest that both low and high selenium consumption may increase T2D risk, highlighting the importance of maintaining a balanced selenium intake for T2D prevention.

Sex- and age-specific associations of serum essential elements with diabetes among the Chinese adults: a community-based cross-sectional study

BACKGROUND

Although several studies have found the relationship between essential elements and diabetes, the studies about the association of essential elements with diabetes diagnosed according to an oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) in a sex- and age-specific manner were limited. To investigate the linear and nonlinear relationship of five essential elements including iron (Fe), copper (Cu), Zinc (Zn), magnesium (Mg), and calcium (Ca) with diabetes, fasting plasma glucose (FPG), 2-h postprandial plasma glucose (PPG), and HbA1c and to evaluate the sex- and age-specific heterogeneities in these relationships.

METHODS

A total of 8392 community-dwelling adults were recruited to complete a questionnaire and undergo checkups of anthropometric parameters and serum levels of five metals (Fe, Cu, Zn, Mg, and Ca). The multivariable logistic and linear regression, the restricted cubic spline (RCS) analysis, and subgroup analysis were applied to find the associations between the essential elements and the prevalence of diabetes as well as FPG, PPG, and HbA1c.

RESULTS

In the multivariable logistic regression and multivariable linear regression, serum Cu was positively associated with FPG, PPG, and HbA1c while serum Mg was significantly inversely correlated with FPG, PPG, HbA1c, and diabetes (all P < 0.001). In the RCS analysis, the non-linear relationship of Cu and diabetes (P < 0.001) was found. In the subgroup analysis, stronger positive associations of Cu with diabetes (P for interaction = 0.027) and PPG (P for interaction = 0.002) were found in younger women.

CONCLUSIONS

These findings may lead to more appropriate approaches to essential elements supplementation in people with diabetes of different ages and sexes. However, more prospective cohort and experimental studies are needed to probe the possible mechanism of sex- and age-specific associations between serum essential elements and diabetes.

Associations among diabetes medication use, serum magnesium, and insulin resistance in a cohort of older Puerto Rican adults

BACKGROUND

Hypomagnesemia is commonly observed in individuals with diabetes, but how diabetes medications alter magnesium (Mg) status remains unclear.

OBJECTIVES

We aimed to examine the association between diabetes medication and hypomagnesemia and evaluate whether serum Mg mediates the association between diabetes medication and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in a prospective cohort.

METHODS

Adults from the Boston Puerto Rican Health Study were included (n = 1106). Multivariable logistic regression models were used to estimate odds ratio (OR) and 95% confidence interval (CI) for cross-sectional association between diabetes medication and hypomagnesemia (serum Mg <0.75 mmol/L). Longitudinal mediation analysis was performed to evaluate the direct and indirect (via serum Mg) associations between diabetes medication and 4-y HOMA-IR in 341 participants with baseline hemoglobin A1c (HbA1c) of ≥6.5%.

RESULTS

Mean age at baseline was 59.0 ± 7.6 y, with 28.0% male and 45.8% with hypomagnesemia. Use of metformin [OR (95% CI) = 3.72 (2.53, 5.48)], sulfonylureas [OR (95% CI) = 1.68 (1.00, 2.83)], and glitazones [OR (95% CI) = 2.09 (1.10, 3.95)], but not insulin, was associated with higher odds of hypomagnesemia. Use of multiple diabetes medications and longer duration of use were associated with higher odds of hypomagnesemia. Serum Mg partially mediated the association between metformin and HOMA-IR [indirect association: β (95% CI) = 1.11 (0.15, 2.07)], which weakened the direct association [β (95% CI) = -5.16 (-9.02, -1.30)] by 22% [total association: β (95% CI) = -4.05 (-7.59, -0.51)]. Similarly, serum Mg mediated 17% of the association between sulfonylureas and elevated HOMA-IR. However, the mediation by serum Mg was weak for insulin and glitazones.

CONCLUSIONS

Diabetes medication, especially metformin, was associated with elevated odds of hypomagnesemia, which may weaken the association between metformin and lowering of HOMA-IR. The causal inference needs to be confirmed in further studies.

Association of serum magnesium with metabolic syndrome and the role of chronic kidney disease: A population-based cohort study with Mendelian randomization

OBJECTIVES

To assess the association of serum magnesium with prevalent and incident metabolic syndrome (MetS) and its individual components in the general population and to examine any effect modification by chronic kidney disease (CKD) status.

METHODS

We analysed longitudinal data from the population-based KORA F4/FF4 study, including 2996 participants (387 with CKD) for cross-sectional analysis and 1446 participants (88 with CKD) for longitudinal analysis. Associations with MetS, as well as single components of MetS, were assessed by adjusted regression models. Nonlinearity was tested by restricted cubic splines and analyses were stratified by CKD. Causality was evaluated by two-sample Mendelian randomization (MR).

RESULTS

Serum magnesium (1 SD) was inversely associated with prevalent MetS (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.83, 0.98). The association was more pronounced in individuals with CKD (OR 0.75, 95% CI 0.59, 0.94). Among MetS components, serum magnesium was negatively associated with elevated fasting glucose (OR 0.78, 95% CI 0.71, 0.88) and, again, this association was more pronounced in individuals with CKD (OR 0.67, 95% CI 0.53, 0.84). Serum magnesium was not associated with incident MetS or its components. Restricted cubic spline analysis revealed a significant nonlinear inverse relationship of serum magnesium with MetS and elevated fasting glucose. MR analysis suggested an inverse causal effect of serum magnesium on MetS (OR 0.91, 95% CI 0.85, 0.97).

CONCLUSION

Serum magnesium is associated with prevalent, but not incident MetS, and this effect is stronger in individuals with CKD. MR analysis implies a potential, albeit weak, causal role of magnesium in MetS.

Genome-wide association study of serum magnesium in type 2 diabetes

People with type 2 diabetes have a tenfold higher prevalence of hypomagnesemia, which is suggested to be caused by low dietary magnesium intake, medication use, and genetics. This study aims to identify the genetic loci that influence serum magnesium concentration in 3466 people with type 2 diabetes. The GWAS models were adjusted for age, sex, eGFR, and HbA1c. Associated traits were identified using publicly available data from GTEx consortium, a human kidney eQTL atlas, and the Open GWAS database. The GWAS identified a genome-wide significant locus in TAF3 (p = 2.9 × 10-9) in people with type 2 diabetes. In skeletal muscle, loci located in TAF3 demonstrate an eQTL link to ATP5F1C, a gene that is involved in the formation of Mg2+-ATP. Serum Mg2+ levels were associated with MUC1/TRIM46 (p = 2.9 × 10-7), SHROOM3 (p = 4.0 × 10-7), and SLC22A7 (p = 1.0 × 10-6) at nominal significance, which is in combination with the eQTL data suggesting that they are possible candidates for renal failure. Several genetic loci were in agreement with previous genomic studies which identified MUC1/TRIM46 (Pmeta = 6.9 × 10-29, PQ = 0.81) and SHROOM3 (Pmeta = 2.9 × 10-27, PQ = 0.04) to be associated with serum Mg2+ in the general population. In conclusion, serum magnesium concentrations are associated with genetic variability around the regions of TAF3, MUC1/TRIM46, SHROOM3, and SLC22A7 in type 2 diabetes.

Associations between multiple metals during early pregnancy and gestational diabetes mellitus under four statistical models

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. Metal exposure is an emerging factor affecting the risk of GDM. However, the effects of metal mixture on GDM and key metals within the mixture remain unclear. This study was aimed at investigating the association between metal mixture during early pregnancy and the risk of GDM using four statistical methods and further at identifying the key metals within the mixture associated with GDM. A nested case-control study including 128 GDM cases and 318 controls was conducted in Beijing, China. Urine samples were collected before 13 gestational weeks and the concentrations of 13 metals were measured. Single-metal analysis (unconditional logistic regression) and mixture analyses (Bayesian kernel machine regression (BKMR), quantile g-computation, and elastic-net regression (ENET) models) were applied to estimate the associations between exposure to multiple metals and GDM. Single-metal analysis showed that Ni was associated with lower risk of GDM, while positive associations of Sr and Sb with GDM were observed. Compared with the lowest quartile of Ni, the ORs of GDM in the highest quartiles were 0.49 (95% CI 0.24, 0.98). In mixture analyses, Ni and Mg showed negative associations with GDM, while Co and Sb were positively associated with GDM in BKMR and quantile g-computation models. No significant joint effect of metal mixture on GDM was observed. However, interestingly, Ni was identified as a key metal within the mixture associated with decreased risk of GDM by all three mixture methods. Our study emphasized that metal exposure during early pregnancy was associated with GDM, and Ni might have important association with decreased GDM risk.

Longitudinal plasma magnesium status during pregnancy and the risk of gestational diabetes mellitus: a prospective cohort study

Emerging evidence has shown that magnesium (Mg) was associated with type 2 diabetes while few focused on abnormal glucose metabolism during pregnancy. The study is aimed at investigating the association between longitudinal changes in plasma Mg during pregnancy and subsequent risk of gestational diabetes (GDM) and exploring the possible influence of iron supplementation on the changes of plasma Mg levels. One thousand seven hundred fifty-six pregnant women from Tongji Maternal and Child Health Cohort (TMCHC) were involved. Blood samples were collected at gestational weeks 17.0 ± 0.9 and later 26.2 ± 1.4. Plasma Mg was measured by inductively coupled plasma mass spectrometry (ICP-MS) with decline rates calculated. Information on general characteristics and iron supplementation was collected by questionnaires. Oral glucose tolerance test (OGTT) was conducted at 24-28 gestational weeks to diagnose GDM. Poisson regression with robust error variance was used to estimate relative risks (RR) of GDM. Median concentrations of plasma Mg were 0.69 mmol/L and 0.63 mmol/L respectively at two collections. The prevalence of hypomagnesemia at the first collection was 73% and associated with a 1.59 (95%CI: 1.07, 2.37) fold risk of GDM. Adjusted RRs were 1.74 (95%CI: 1.06, 2.83) and 2.44 (95%CI: 1.54, 3.85) for women with hypomagnesemia and followed more tertile (T2 and T3 vs. T1) of Mg decrement. Iron supplementation above 30 mg/day was found associated with more Mg decrement (25.5% and 27.5% in T2 and T3 vs. 19.5% in T1). In conclusion, hypomagnesemia during pregnancy is prevalent and associated with increased GDM risk, especially in women followed by more plasma Mg decrement during pregnancy. High-dose iron supplementation may involve more plasma Mg decrement.

Nutritional Support for Alcoholic Liver Disease

Malnutrition is a common finding in alcohol use disorders and is associated with the prognosis of patients with alcoholic liver disease (ALD). These patients also frequently show deficiencies in vitamins and trace elements, increasing the likelihood of anemia and altered cognitive status. The etiology of malnutrition in ALD patients is multifactorial and complex and includes inadequate dietary intake, abnormal absorption and digestion, increased skeletal and visceral protein catabolism, and abnormal interactions between ethanol and lipid metabolism. Most nutritional measures derive from general chronic liver disease recommendations. Recently, many patients with ALD have been diagnosed with metabolic syndrome, which requires individualized treatment via nutritional therapy to avoid overnutrition. As ALD progresses to cirrhosis, it is frequently complicated by protein–energy malnutrition and sarcopenia. Nutritional therapy is also important in the management of ascites and hepatic encephalopathy as liver failure progresses. The purpose of the review is to summarize important nutritional therapies for the treatment of ALD.

Exposure to proton pump inhibitors and risk of diabetes: A systematic review and meta-analysis

BACKGROUND

Exposure to proton pump inhibitors (PPIs) has been reported to have a potential role in the development of diabetes.

AIM

To determine the association between PPIs and diabetes.

METHODS

This meta-analysis is registered on PROSPERO (CRD42022352704). In August 2022, eligible studies were identified through a comprehensive literature search. In this study, odds ratios were combined with 95% confidence intervals using a random-effects model. The source of heterogeneity was assessed using sensitivity analysis and subgroup analysis. The publication bias was evaluated using Egger’s test and Begg’s test.

RESULTS

The meta-analysis included 9 studies with a total of 867185 participants. Results showed that the use of PPIs increased the risk of diabetes (odds ratio = 1.23, 95% confidence interval: 1.05-1.43, n = 9, I² = 96.3%). Subgroup analysis showed that geographic location and study type had significant effects on the overall results. Both Egger’s and Begg’s tests showed no publication bias (P > 0.05). Sensitivity analysis also confirmed the stability of the results.

CONCLUSION

The results of this study indicated that the use of PPIs was related to an increased risk of diabetes. However, more well-designed studies are needed to verify these results in the future.