Relationship between baseline and changed serum uric acid and the incidence of type 2 diabetes mellitus: a national cohort study

The link between hyperuricemia and diabetes: insights from a quantitative analysis of scientific literature

Background

Hyperuricemia (HUA) is a significant public health issue, ranking second only to diabetes in prevalence. While existing research demonstrates a robust correlation between these two conditions, the precise etiological mechanisms remain inadequately elucidated. This study utilized scientometric analysis to investigate the global association between HUA and diabetes.

Methods

Data on HUA and diabetes were retrieved from the Web of Science Core Collection database, encompassing the period from its inception until September 30, 2024. Collaboration networks were examined using VOSviewer, cluster analysis was executed with CiteSpace, and systematic mapping was conducted using Bibliometrix.

Results

By September 30, 2024, 1,464 studies indicated a consistent yearly increase in publications connecting HUA and diabetes despite some fluctuations. The lead authors were Richard J. Johnson, Miguel A. Lanaspa, and Masanari Kuwabara, with most contributors from China, the United States, and Japan. Key institutions include China Medical University, Shanghai Jiao Tong University, and Capital Medical University. The most published journal was Nutrition, Metabolism and Cardiovascular Diseases (CVDs), whereas the most cited journal was Diabetes Care. The reference network from 1987 to September 30, 2024, identified 19 clusters highlighting key research areas in HUA and diabetes, such as metabolic syndrome, uropathology, chronic kidney disease (CKD), and CVD. Exploring pathological mechanisms and pharmacological interventions linked to diabetes concomitant with HUA has emerged as a focal point of research and a burgeoning trend within the field.

Conclusion

This study is the first scientometric analysis to synthesize research trends on HUA and diabetes, revealing molecular mechanisms and treatment strategies and providing theoretical insights for future clinical use.

Association of homocysteine and uric acid with type 2 diabetes mellitus: a case-control study

The aim of this study was to examine the association between homocysteine (Hcy), uric acid (UA) and type 2 diabetes mellitus (T2DM), and to explore whether there was an interaction between Hcy and UA in the development of T2DM. A total of 1250 diabetic patients and 1250 non-diabetic controls were included in this case-control study. Binary logistic regression and interaction analysis were used to evaluate the association between Hcy, UA, and T2DM, and the combined effects of Hcy and UA on T2DM, respectively. Plasma Hcy and UA levels were significantly higher in diabetic patients compared to non-diabetic controls (p < 0.001, p = 0.002). Elevated Hcy and UA were risk factors for T2DM. Binary logistic regression analysis showed that compared with the lowest quartile of Hcy and UA, the highest quartile had a significantly increased risk of T2DM (OR = 1.629, 95% CI: 1.303, 2.035 for Hcy; OR = 1.596, 95% CI: 1.277, 1.995 for UA). Stratified analysis suggested a significant association between Hcy and T2DM for those aged < 65 years and males. A significant association between UA and T2DM was found in those aged ≥ 65 years, males, and BMI ≥ 24 kg/m2. No significant interaction was observed between Hcy and UA (p > 0.05). Hcy and UA were risk factors for T2DM. However, there was no interaction between Hcy and UA in the risk of T2DM.

The bidirectional relationship between activities of daily living and frailty during short-and long-term follow-up period among the middle-aged and older population: findings from the Chinese nationwide cohort study

Objective

Frailty and activities of daily living (ADL) disability are common conditions among older population. Studies on the bidirectional relationship between frailty and ADL are limited. The current study examined the cross-sectional and longitudinal associations between frailty and ADL in middle-aged and older Chinese individuals.

Methods

The data was collected through the China Health and Retirement Longitudinal Study (CHARLS), conducted in 2011, 2013, and 2015, encompassing 17,284 individuals aged ≥45 years. We excluded individuals without follow-up data. 2,631 participants finished the baseline survey. The definition of ADL disability encompasses difficulty in engaging in either basic activities of daily living (BADL) or instrumental activities of daily living (IADL). Frailty was assessed according to the Fried criteria. Logistic regression was utilized to examine odds ratios (ORs) and 95% confidence intervals (CIs) for assessing the cross-sectional relationships between ADL with frailty at baseline. The prediction effects were explored using Cox proportional hazards analysis, testing hazard ratios (HRs) and 95%CIs.

Results

In cross-sectional analysis, BADL [OR = 6.660 (4.519-9.815)], IADL [OR = 5.950 (4.490-7.866)], and ADL [OR = 5.658 (4.278-7.483)] exhibited significant associations with frailty; frailty demonstrated significant associations with BADL [OR = 6.741 (4.574-9.933)], IADL [OR = 6.042 (4.555-8.016)] and ADL [OR = 5.735 (4.333-7.591)]. In longitudinal analysis, IADL and ADL were significantly associated with frailty in participants without baseline frailty in the short-term period [IADL: HR = 1.971 (1.150-3.379), ADL: HR = 1.920 (1.146-3.215)], IADL exhibited a significant association with frailty in the long-term period [HR = 2.056 (1.085-3.895)]. There was no significant link observed between frailty and an elevated risk of disability onset in BADL, IADL and ADL during the short-term period. When considering the long-term perspective, frailty exhibited a significant association with an elevated risk of disability onset in BADL [HR= 1.820 (1.126-2.939)] and IADL [HR = 1.724 (1.103-2.694)].

Conclusion

In middle-aged and older adults, ADL and IADL disability predicted frailty after 2-year follow-up, IADL disability predicted frailty after 4-year follow-up. Moreover, frailty did not predict BADL, IADL and ADL disability after 2-year follow-up. However, frailty predicted BADL and IADL disability after 4-year follow-up.

Healthy lifestyle decreases the risk of the first incidence of non-communicable chronic disease and its progression to multimorbidity and its mediating roles of metabolic components: a prospective cohort study in China

OBJECTIVES

To identify the influence of healthy lifestyles on the incidence of the first NCD (FNCD), multiple chronic conditions (MCCs), and the progression from FNCD to MCCs.

DESIGN

cohort study.

SETTING

Zhejiang, China PARTICIPANTS: 10566 subjects (55.5 ± 13.5 years, 43.1% male) free of NCDs at baseline from the Zhejiang Metabolic Syndrome prospective cohort.

MEASUREMENTS

Healthy lifestyle score (HLS) was developed by 6 common healthy lifestyle factors as smoking, alcohol drinking, physical activity, body mass index (BMI) and waist-to-hip ratio (WHR). Healthy lifestyle data and metabolic biomarkers collected via a face-to-face questionnaire-based interview, clinical health examination and routine biochemical determination. Biochemical variables were determined using biochemical auto-analyzer. Participants were stratified into four group based on the levels of HLS as ≤2, 3, 4 and ≥5. Multiple Cox proportional hazards model was applied to examine the relationship between HLS and the risk of FNCD, MCCs and the progression from FNCD to MCCs. The population-attributable fractions (PAF) were used to assess the attributable role of HLS. Mediating effect was examined by mediation package in R.

RESULTS

After a median of 9.92 years of follow-up, 1572 participants (14.9%) developed FNCD, and 149 (1.4%) developed MCCs. In the fully adjusted model, the higher HLS group (≥5) was associated with lower risk of FNCD (HR = 0.68 and 95% CI: 0.56-0.82), MCCs (HR = 0.31 and 95%CI: 0.14-0.69); and the progression from FNCD to MCCs (HR = 0.39 and 95%CI: 0.18-0.85). Metabolic components (TC, TG, HDL-C, LDC-C, FPG, and UA) played the mediating roles with the proportion ranging from 5.02% to 22.2% for FNCD and 5.94% to 20.1% for MCCs. PAFs (95%CI) for poor adherence to the overall healthy lifestyle (HLS ≤ 3) were 17.5% (11.2%, 23.7%) for FNCD, 42.9% (23.4%, 61.0%) for MCCs, and 37.0% (15.5%, 56.3%) for the progression from FNCD to MCCs.

CONCLUSIONS

High HLS decreases the risk of FNCD, MCCs, and the progression from FNCD to MCCs. These effects are partially mediated by metabolic components. Maintaining healthy lifestyles might reduce the disease burden of common chronic diseases.