Objective:To investigate the effect of changes in metabolic syndrome status and persistence on carotid plaque risk.Methods:This retrospective cohort study analyzed individuals who underwent routine health check-ups at the health management center of the Second Affiliated Hospital of Dalian Medical University from 2014 to 2023. Participants with at least three carotid ultrasound records meeting the inclusion criteria were classified into 4 groups based on changes in metabolic status: persistently metabolic health, transitioning from metabolic health to unhealth, transitioning from metabolic unhealth to health, and persistently metabolic unhealth. The cumulative incidence of carotid plaque in these groups was compared. A Cox proportional risk model was used to evaluate the relationship between changes in metabolic syndrome status, the number of metabolic syndrome components, and the risk of carotid plaque development. Restricted cubic spline analysis was applied to explore the association between changes in individual metabolic syndrome components and carotid plaque risk.Results:Compared to the persistently metabolic health group, the persistent unhealth group had the highest risk of developing carotid plaque( HR=1.35, 95% CI 1.05-1.74, P=0.021), followed by those who transitioned from metabolic health to unhealth and those who improved from metabolic unhealth to health. Furthermore, the risk of carotid plaque increased progressively with the number of metabolic syndrome components. Restricted cubic spline analysis revealed a nonlinear relationship between fasting blood glucose change and carotid plaque risk, while systolic blood pressure, diastolic blood pressure, waist circumference, triglycerides, and high-density lipoprotein-cholesterol showed a linear dose-response relationship with carotid plaque. Conclusions:The change of metabolic syndrome is associated with the risk of developing carotid plaque, and maintaining metabolic health, recovering from metabolic syndrome, or minimizing the number of metabolic syndrome components may be effective strategies to prevent carotid plaque formation.

Objective:To explore the relationship between thyroid hormone sensitivity and metabolic dysfunction-associated steatotic liver disease(MASLD) in a population with normal thyroid function, with a particular focus on sex-specific differences.Methods:This retrospective study included 41 355 euthyroid cases who underwent routine health examinations at the Health Management Centre of the Second Affiliated Hospital of Dalian Medical University from January 2014 to December 2023 were included. The free triiodothyronine(FT 3) to free thyroxine(FT 4) ratio(FT 3/FT 4) was calculated in order to reflect the peripheral sensitivity of the thyroid gland. Similarly, thyroid feedback quantile-based index(TFQI), thyrotrophic thyroxine resistance index(TT 4RI), and the FT 3-based TFQI-derived index(TFQI-FT 3) were calculated in order to reflect the central sensitivity of the thyroid gland. A Logistic regression was employed to analyse the effect of sex-specific thyroid hormone sensitivity indices on the prevalence of MASLD. The restricted cubic spline was used to analyse the non-linear relationship between the thyroid sensitivity hormone indices and MASLD. Furthermore, the correlation between the thyroid hormone sensitivity indices and MASLD in different subgroups was also analysed. Results:The prevalence of MASLD in the study population was 28.8%. After adjusting the model for confounders, the risk of MASLD increased by 7%, 3%, 10%, and 5% for each standard deviation increase in FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI in the total population, respectively. The risk of MASLD increased by 6% and 5% for each standard deviation increase in FT 3/FT 4 and TFQI-FT 3 in men, respectively. For each standard deviation increase in FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI in women, the risk of MASLD increased by 6%, 5%, 11%, and 5%, respectively. Higher FT 3/FT 4 and TFQI-FT 3 were positively associated with the risk of developing MASLD in men, and higher FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI were positively associated with the risk of developing MASLD in women. There was a non-linear, inverted U-shaped relationship between TFQI and risk of MASLD in women. Subgroup analyses showed positive associations between FT 3/FT 4, TFQI, TFQI-FT 3, and MASLD. Conclusions:The thyroid hormone sensitivity indices may provide a basis for clinical prevention and management of MASLD in individuals with normal thyroid function. Additionally, FT 3/FT 4 and TFQI-FT 3 may indicate the risk of MASLD in the general population, while TFQI and TT 4RI are more suitable for assessing the risk of MASLD in women.

Objective:To explore the correlation between serum ferritin (SF) and risk of lean non-alcoholic fatty liver disease (NAFLD), so as to provide the basis for the prevention and treatment of lean NAFLD.Methods:A total of 7 187 people without NAFLD at baseline who took at least 2 physical examinations in the Health Management Center of the Second Hospital of Dalian Medical University from January 2014 to December 2023 and met the selection criteria were selected as the research subjects, and all the subjects had no NAFLD at baseline. Subjects were divided into four groups according to baseline SF quartiles: 1 797 cases in the first quartile ( Q1) group, 1 797 cases in the second quartile ( Q2) group, 1 797 cases in the third quartile ( Q3) group, and 1 796 cases in the fourth quartile ( Q4) group. The incidence of lean NAFLD in each group were observed. Kaplan-Meier curve was plotted to calculate the cumulative incidence of lean NAFLD which compared by log-rank test. Cox proportional hazard regression model was used to analyze the correlation between SF and new-onset lean NAFLD, Q1, Q2, Q3 and Q4 of SF were taken as continuous variables into the model for trend test.The stability of the results was verified by two item sensitivity analyses. Time-dependent receiver operating characteristic curve (ROC) was plotted to evaluate the predictive value of SF for the onset of lean NAFLD. Results:The cumulative follow-up were 25 076 person-years. There were 230 new cases of lean NAFLD, and the incidence density was 9.172/1 000 person-years. The incidence densities of lean NAFLD in Q1, Q2, Q3 and Q4 groups were 6.915/1 000 person-years, 8.552/1 000 person-years, 9.641/1 000 person-years, 12.003/1 000 person-years, respectively. Kaplan-Meier curve indicated that the incidence of lean NAFLD was increased with the increment of SF, and the difference was statistically significant (log-rank test, χ2=9.92, P=0.019). Cox proportional hazard regression model results showed that the risk of developing lean NAFLD in Q4 group increased by 72.8% ( HR=1.728, 95% confidence interval (95% CI): 1.059 to 2.820) compared with Q1 group. Trend analysis revealed that the risk of lean NAFLD increased by 18.9% for each one-quartile increase of SF( HR=1.189, 95% CI: 1.012 to 1.396). Two sensitivity analyses indicated that the risk of NAFLD in Q4 group was 1.795 times ( HR=1.795, 95% CI: 1.083 to 2.975) or 1.654 times ( HR=1.654, 95% CI: 1.022 to 2.678) higher than that in Q1 group. The area under the curve (95% CI) of SF for predicting the incidence of lean NAFLD at 2-, 3-, 7- and 8-year follow-up based on time-dependent ROC were 0.645 (0.593 to 0.698), 0.652 (0.603 to 0.700), 0.605 (0.539 to 0.672) and 0.716 (0.597 to 0.836), respectively. Conclusion:SF is an independent risk factor for lean NAFLD and has predictive value for the new-onset of lean NAFLD.

Objective:To investigate the effect of changes in metabolic syndrome status and persistence on carotid plaque risk.Methods:This retrospective cohort study analyzed individuals who underwent routine health check-ups at the health management center of the Second Affiliated Hospital of Dalian Medical University from 2014 to 2023. Participants with at least three carotid ultrasound records meeting the inclusion criteria were classified into 4 groups based on changes in metabolic status: persistently metabolic health, transitioning from metabolic health to unhealth, transitioning from metabolic unhealth to health, and persistently metabolic unhealth. The cumulative incidence of carotid plaque in these groups was compared. A Cox proportional risk model was used to evaluate the relationship between changes in metabolic syndrome status, the number of metabolic syndrome components, and the risk of carotid plaque development. Restricted cubic spline analysis was applied to explore the association between changes in individual metabolic syndrome components and carotid plaque risk.Results:Compared to the persistently metabolic health group, the persistent unhealth group had the highest risk of developing carotid plaque( HR=1.35, 95% CI 1.05-1.74, P=0.021), followed by those who transitioned from metabolic health to unhealth and those who improved from metabolic unhealth to health. Furthermore, the risk of carotid plaque increased progressively with the number of metabolic syndrome components. Restricted cubic spline analysis revealed a nonlinear relationship between fasting blood glucose change and carotid plaque risk, while systolic blood pressure, diastolic blood pressure, waist circumference, triglycerides, and high-density lipoprotein-cholesterol showed a linear dose-response relationship with carotid plaque. Conclusions:The change of metabolic syndrome is associated with the risk of developing carotid plaque, and maintaining metabolic health, recovering from metabolic syndrome, or minimizing the number of metabolic syndrome components may be effective strategies to prevent carotid plaque formation.

Objective:To explore the relationship between thyroid hormone sensitivity and metabolic dysfunction-associated steatotic liver disease(MASLD) in a population with normal thyroid function, with a particular focus on sex-specific differences.Methods:This retrospective study included 41 355 euthyroid cases who underwent routine health examinations at the Health Management Centre of the Second Affiliated Hospital of Dalian Medical University from January 2014 to December 2023 were included. The free triiodothyronine(FT 3) to free thyroxine(FT 4) ratio(FT 3/FT 4) was calculated in order to reflect the peripheral sensitivity of the thyroid gland. Similarly, thyroid feedback quantile-based index(TFQI), thyrotrophic thyroxine resistance index(TT 4RI), and the FT 3-based TFQI-derived index(TFQI-FT 3) were calculated in order to reflect the central sensitivity of the thyroid gland. A Logistic regression was employed to analyse the effect of sex-specific thyroid hormone sensitivity indices on the prevalence of MASLD. The restricted cubic spline was used to analyse the non-linear relationship between the thyroid sensitivity hormone indices and MASLD. Furthermore, the correlation between the thyroid hormone sensitivity indices and MASLD in different subgroups was also analysed. Results:The prevalence of MASLD in the study population was 28.8%. After adjusting the model for confounders, the risk of MASLD increased by 7%, 3%, 10%, and 5% for each standard deviation increase in FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI in the total population, respectively. The risk of MASLD increased by 6% and 5% for each standard deviation increase in FT 3/FT 4 and TFQI-FT 3 in men, respectively. For each standard deviation increase in FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI in women, the risk of MASLD increased by 6%, 5%, 11%, and 5%, respectively. Higher FT 3/FT 4 and TFQI-FT 3 were positively associated with the risk of developing MASLD in men, and higher FT 3/FT 4, TFQI, TFQI-FT 3, and TT 4RI were positively associated with the risk of developing MASLD in women. There was a non-linear, inverted U-shaped relationship between TFQI and risk of MASLD in women. Subgroup analyses showed positive associations between FT 3/FT 4, TFQI, TFQI-FT 3, and MASLD. Conclusions:The thyroid hormone sensitivity indices may provide a basis for clinical prevention and management of MASLD in individuals with normal thyroid function. Additionally, FT 3/FT 4 and TFQI-FT 3 may indicate the risk of MASLD in the general population, while TFQI and TT 4RI are more suitable for assessing the risk of MASLD in women.

Objective:To explore the correlation between serum ferritin (SF) and risk of lean non-alcoholic fatty liver disease (NAFLD), so as to provide the basis for the prevention and treatment of lean NAFLD.Methods:A total of 7 187 people without NAFLD at baseline who took at least 2 physical examinations in the Health Management Center of the Second Hospital of Dalian Medical University from January 2014 to December 2023 and met the selection criteria were selected as the research subjects, and all the subjects had no NAFLD at baseline. Subjects were divided into four groups according to baseline SF quartiles: 1 797 cases in the first quartile ( Q1) group, 1 797 cases in the second quartile ( Q2) group, 1 797 cases in the third quartile ( Q3) group, and 1 796 cases in the fourth quartile ( Q4) group. The incidence of lean NAFLD in each group were observed. Kaplan-Meier curve was plotted to calculate the cumulative incidence of lean NAFLD which compared by log-rank test. Cox proportional hazard regression model was used to analyze the correlation between SF and new-onset lean NAFLD, Q1, Q2, Q3 and Q4 of SF were taken as continuous variables into the model for trend test.The stability of the results was verified by two item sensitivity analyses. Time-dependent receiver operating characteristic curve (ROC) was plotted to evaluate the predictive value of SF for the onset of lean NAFLD. Results:The cumulative follow-up were 25 076 person-years. There were 230 new cases of lean NAFLD, and the incidence density was 9.172/1 000 person-years. The incidence densities of lean NAFLD in Q1, Q2, Q3 and Q4 groups were 6.915/1 000 person-years, 8.552/1 000 person-years, 9.641/1 000 person-years, 12.003/1 000 person-years, respectively. Kaplan-Meier curve indicated that the incidence of lean NAFLD was increased with the increment of SF, and the difference was statistically significant (log-rank test, χ2=9.92, P=0.019). Cox proportional hazard regression model results showed that the risk of developing lean NAFLD in Q4 group increased by 72.8% ( HR=1.728, 95% confidence interval (95% CI): 1.059 to 2.820) compared with Q1 group. Trend analysis revealed that the risk of lean NAFLD increased by 18.9% for each one-quartile increase of SF( HR=1.189, 95% CI: 1.012 to 1.396). Two sensitivity analyses indicated that the risk of NAFLD in Q4 group was 1.795 times ( HR=1.795, 95% CI: 1.083 to 2.975) or 1.654 times ( HR=1.654, 95% CI: 1.022 to 2.678) higher than that in Q1 group. The area under the curve (95% CI) of SF for predicting the incidence of lean NAFLD at 2-, 3-, 7- and 8-year follow-up based on time-dependent ROC were 0.645 (0.593 to 0.698), 0.652 (0.603 to 0.700), 0.605 (0.539 to 0.672) and 0.716 (0.597 to 0.836), respectively. Conclusion:SF is an independent risk factor for lean NAFLD and has predictive value for the new-onset of lean NAFLD.

Objective:To investigate the association between different dietary patterns and subtypes of metabolic associated fatty liver disease(MAFLD).Methods:A total of 6 022 check-ups at the health management center of the Second Hospital of Dalian Medical University from January 2022 to March 2023 were selected as study subjects. MAFLD was categorised into three subtypes: overweight/obese type, metabolic disorder type, and diabetic type. Factor analysis was used to extract dietary patterns. Logistic regression was used to assess the impact of dietary patterns on MAFLD occurrence, constructing interaction models between dietary patterns intake and age, gender, and physical exercise levels. Results:Four dietary patterns were extracted based on feature sorting after factor analysis and were named as the high-quality protein pattern, the fruit-vegetable pattern, egg-aquatic pattern, and the processed meat pattern. Regression analysis of the unadjusted model showed that overweight/obese and diabetic types of MAFLD were negatively associated with the high-quality protein mode, while model-adjusted regression analysis showed that the processed meat pattern was positively associated with the risk of MAFLD, and fruit-vegetable pattern was positively associated with overweight/obese MAFLD( P<0.05). The results of subgroup analyses suggested that female( OR=1.55, 95% CI 1.14-2.15) with a high intake of pickle pattern had a higher risk of overweight/obese MAFLD than male( OR=1.18, 95% CI 1.02-1.49). Conclusion:High-quality protein pattern was negatively correlated with MAFLD, whereas fruit-vegetable pattern and processed meat pattern were positively correlated with MAFLD. Female with high consumption of processed meat pattern are more likely to develop overweight/obesity MAFLD compared with male. It is recommended that people with MAFLD reduce their intake of processed products and high-fructose food, and consume adequate amounts of high-quality protein food to maintain a balanced diet.

Objective:To investigate the relationship between obesity and incident chronic kidney disease(CKD) in a population undergoing health check-ups.Methods:This is a retrospective cohort study. A total of 31 251 participants who had at least 2 health physical examinations in the Health Management Center of the Second Affiliated Hospital of Dalian Medical University from January 2017 to December 2022 and met the inclusion criteria were selected. The participants were divided into normal body weight group, overweight group, and obese group according to baseline body mass index. Cox proportional hazard regression model was used to analyze the relationship between obesity and new-onset CKD, and the dose-response relationship between body mass index and CKD was analyzed with restricted cubic splines.Results:Multivariate Cox regression analysis showed that the risk of developing CKD increased by 13%( HR=1.13, 95% CI 1.01-1.25) and 55%( HR=1.55, 95% CI 1.36-1.76) in the overweight and obese group compared to the normal weight group. Subgroup analysis indicated that obese women had a higher risk of developing CKD compared to men. There was a " U-shaped" correlation between body mass index and CKD in male population, with the lowest risk of CKD occurring at body mass index of 19.6-24.2 kg/m 2. In women, the relationship between body mass index and CKD was approximately linear, with the risk of CKD gradually increasing when body mass index exceeded 22.5 kg/m 2. Conclusions:Obesity is an independent risk factor for new-onset CKD, and obese women have a higher risk of developing CKD than men. Regarding CKD prevention, men are advised to maintain a higher level of body weight within the normal range of body mass index, while women are encouraged to control their weight to a lower level within the normal body mass index range.

Objective:To explore the correlation between systemic immunity-inflammation index(SII) and hyperuricemia(HUA).Methods:Participants who had at least 3 health checkups in the Health Management Center of the Second Affiliated Hospital of Dalian Medical University from January 2014 to December 2022 were selected to construct a dynamic cohort. The SII, reflecting the inflammatory state of the body, was constructed using neutrophil, platelet, and lymphocyte counts. A Cox proportional hazard regression model was used to explore the association between SII and HUA in the overall population and different subgroups of the population, and sensitivity analysis was performed twice. Results:A total of 20 022 subjects were included, and the mean follow-up time was 3.67 years. After adjusting for confounding factors, each unit increase in the natural logarithm of SII(lnSII) was associated with a 24% increased risk of hyperuricemia( HR=1.24, 95% CI 1.16-1.32, P<0.001). As a categorical variable, compared with the lowest quartile array( Q1), the risk of HUA in the total population increased by 12%( HR=1.12, 95% CI 1.03-1.21, P=0.006), 14%( HR=1.14, 95% CI 1.06-1.24, P=0.001), 27%( HR=1.27, 95% CI 1.17-1.37, P<0.001) in Q2, Q3 and Q4 groups within the general population, respectively. All subgroup analysis and sensitivity analysis showed that SII was positively correlated with HUA. Conclusions:Elevated levels of SII significantly increase the risk of HUA. Assessing the body′s inflammatory status using SII can aid in risk screening and preventive management for individuals at high risk of HUA.

Objective:To analyze the trajectory of residual cholesterol(RC) in a healthy check-up cohort and explore its correlation with the incidence of non-alcoholic fatty liver disease(NAFLD).Methods:A total of 2 477 participants who met the inclusion criteria in the Health Management Center of the Second Hospital of Dalian Medical University from January 2016 to December 2020 were retrospectively selected to establish a four-year RC trajectory model using the group-based trajectory model(GBTM), and the risk of NAFLD in the RC group was analyzed using Cox proportional hazards regression model. The predictive value of the Cox model was evaluated with a receiver operating characteristic(ROC) curve, and the reliability of the association between RC and NAFLD was verified through sensitivity analysis.Results:Three RC trajectory subgroups were identified low-level RC(79.21%), medium-level RC(19.86%), and high-level RC(0.93%). After 4 years of follow-up, the incidence rate of NAFLD in this cohort was 11.99%, and the incidences of NAFLD in the low-, medium-, and high-RC groups were 10.55%, 16.46%, and 39.13%, respectively. The cumulative incidence of NAFLD increased with follow-up with the highest rate observed in the high-level RC group( χ2=68.026, P<0.001). The results of Cox proportional hazards regression model indicated that the risk of NAFLD incidence in both the high-level and medium-level RC groups was greater than that in the low-level RC group. The areas under ROC curve at the 2nd, 3rd, and 4th years of follow-up were 0.777, 0.778, and 0.720, respectively, suggesting that RC has certain predictive value for new-onset NAFLD. The results were consistent after excluding 166 individuals with diabetes, hypertension, or dyslipidemia. In another sensitivity analysis, higher RC quartiles( Q2, Q3, Q4) were associated with greater NAFLD risk compared to the lowest quartile( Q1). Conclusions:The trajectory of high-level RC is a risk factor for the onset of NAFLD, and the continuous increase of high-level RC value may be an early signal of NAFLD, and timely intervention is recommended to achieve the goal of early prevention of NAFLD.