Chiu-Shong Liu

This study aimed to investigate the relationships between visit-to-visit variability in HbA1c and fasting plasma glucose (FPG) and atherosclerotic markers in persons with type 2 diabetes mellitus (T2DM), employing epidemiological analyses and Mendelian randomization (MR) techniques. Between January 2001 and December 2020, 2290 persons with T2DM (1307 men and 983 women) who underwent evaluation for atherosclerosis screening were enrolled in a management program at a medical center in Taiwan. To assess potential causal relationships among the coefficient of variation (CV) of HbA1c (HbA1c-CV), FPG-CV, and markers of atherosclerosis, we conducted a 2-stage multivariable regression analysis using 22 and 21 single nucleotide polymorphisms as instrumental variables for HbA1c and FPG, respectively. A total of 2290 individuals with T2DM were included, with a mean age of 61.79 years, and 57% were male. In the epidemiological analysis, after multivariable adjustment, the odds ratios for an ankle–brachial index (ABI) < 0.9 in the third and fourth quartiles compared with the first quartile were 3.15 (95% confidence interval [CI]: 1.80–5.50) and 4.29 (95% CI: 2.44–7.56), respectively, for FPG-CV, and 1.67 (95% CI: 1.06–2.62) and 1.65 (95% CI: 1.01–2.70), respectively, for HbA1c-CV. In the MR analysis, comparing the fourth quartile with the first quartile, the odds ratios for ABI < 0.9 and brachial–ankle pulse wave velocity (baPWV) ≥ 1800 cm/s were 2.78 (95% CI: 1.84–4.19) and 1.58 (95% CI: 1.23–2.02), respectively, for the unweighted genetic risk score predicting FPG-CV. Epidemiological and MR analyses provide evidence that FPG variability is significantly associated with atherosclerosis, as indicated by the ABI.

This study aimed to identify three-year trajectories of body mass index (BMI), a body shape index (ABSI), waist circumference (WC), waist-to-hip ratio (WHR

Depression is linked to a high risk of mortality from any causes in older adults. However, the role of frailty or quality of life (QOL) as a mediator in th

Background: This study aimed to explore trends, in 3 periods, in the intake of energy and macronutrients among Taiwanese older adults. Methods: Study subjects were those aged ≥65 years in the Nutrition and Health Survey in Taiwan 1999–2000 as well as the surveys in 2005–2008 and 2013–2016. Twenty-four-hour dietary recall data were obtained. This study used the 3 nutrition survey datasets for 1999–2000, 2005–2008, and 2013–2016, including data on the questionnaire, physical examination, and dietary intakes. Each nutrition survey involved the face-to-face household interview, and individual’s dietary intake of carbohydrate, fat, and protein (% of energy) was estimated. Subsequently, intake statuses of the three macronutrients were classified into below, meeting, and above intake categories. Results: In the 2013–2016 survey, approximately 40% of the older adults had a low intake of energy. The prevalence of older adults with a meeting intake of carbohydrate, fat, and protein have increased from the 1999–2000 to 2013–2016 periods. The prevalence of people having a low intake of carbohydrate declined from the 1999–2000 period to the 2013–2016 period. The prevalence of high fat intake in 2013–2016 was approximately 5% higher than that in 1999–2000. In the 2013–2016 period, the prevalence of low intake of carbohydrate, fat, and protein were 25.9, 24.5, and 4.9%, respectively; moreover, the prevalence of high intake of the aforementioned macronutrients were 38.7, 36.2, and 17.6%, respectively. Conclusions: Our study provides important evidence on the dietary patterns, as well as their changes over time among Taiwanese older adults. Such information would be useful for health policy makers about the burden of unbalanced diet and for nutrition educators on planning nutrition promotion interventions about well-balanced dietary for the older persons.

Background: Obesity and cognitive impairment prevalence increases as age increases. Recent growing evidence finds links between obesity and cognitive impairment in older adults. However, the association between the two is controversial. This study aims to identify obesity marker trajectory patterns, and to assess whether these patterns are associated with cognitive impairment and cognitive decline during a 10-year follow-up period among community-dwelling older adults. Methods: A total of 626 older adults aged 65 and older were involved in the study, with at least two repeated measurements at baseline, one-year or 10-year follow-up. Cognitive function was measured through the Mini Mental State Examination. Obesity markers included body mass index, waist circumference, waist-to-hip (WHR), fat mass (FM), and abdominal fat (AF) measured by dual-energy X-ray absorptiometry. Multivariate logistic regression analyses were performed to estimate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of cognitive impairment and cognitive decline for obesity marker trajectory patterns. Results: After a 10-year follow-up, 168 older adults with incident cognitive impairment and 156 with rapid cognitive decline were defined as the top 25th percentile of cognitive decline. Four distinct trajectory groups of obesity markers were identified. In multivariate logistic regression analyses, a low likelihood of cognitive impairment was observed in the consistently high-level group from FM trajectory (ORs = 0.41, 95% CI = 0.20–0.85); the high-level U-shaped group from WHR trajectory (0.43, 0.22–0.84); and the median-level flat inverse U-shaped, consistently high-level, and low-level flat U-shaped groups from AF trajectory (0.44, 0.26–0.77; 0.33, 0.18–0.61; 0.39, 0.18–0.82). In addition, a low likelihood of rapid decline was found in the low-level, slightly increasing trend group from WHR trajectory (0.43, 0.22–0.85). Conclusion: FM and AF trajectories with consistent high levels and WHR trajectory with high level with U-shaped group are associated with low risks of incident cognitive impairment in older adults. Similarly, WHR trajectory with a low but slowly increasing trend is associated with a decreased risk of cognitive decline.

The role of serum uric acid (SUA) in the role of advanced fibrosis is not fully explored. The study assesses the risk of advanced fibrosis according to SUA in an Asian population with a total of 3612 subjects enrolled in one health management center between 2006 and 2008. The fibrosis-4 score was used for the prediction of the high risk of advanced fibrosis. SUA scores higher than 7.6 mg/dL in men and 6.6 mg/dL in women were defined as hyperuricemia. A proportional odds model was used to assess cumulative risks of advanced fibrosis. The prevalence of high risk of advanced fibrosis was 2.5% in the hyperuricemia group and 0.6% in the normal SUA group (p < 0.001). After adjustment for confounding factors, the odds ratios (OR) for more severe advanced fibrosis were 1.37 (95% confidence interval [CI]: 1.07–1.78) in the hyperuricemia group. Hyperuricemia only increased the risk of advanced fibrosis in the non-T2DM group (OR, 1.29; 95% CI, 1.04 to 1.74) instead of T2DM group (OR, 1.85; 95% CI, 0.97 to 3.53). SUA is a risk factor for a higher risk of advanced fibrosis, with the disease likely progressing from a steatotic to a fibrotic picture. The focus should be more emphasized in non-T2DM groups.

Background: Decreased skeletal muscle mass and low physical performance are independently associated with increased mortality in elderly individuals. However, little is known about the effects of skeletal muscle mass combined with physical performance on the prediction of mortality risk among community-dwelling older adults. This study aimed to determine the combined effects of skeletal muscle mass and physical performance on total mortality. Methods: A community-based prospective cohort study was conducted among 641 participants aged 65 and older in 2009. The height-adjusted skeletal muscle index (hSMI) and the weight-adjusted SMI (wSMI) were determined by dual-energy X-ray absorptiometry examination. Physical performance tests measured at baseline included gait speed (GS), timed up-and-go (TUG) test, timed chair stand (TCS), weight-adjusted leg press (WaLP), and handgrip strength (HS). Cox proportional hazards regression models were applied to determine the adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (95% CIs) for baseline skeletal muscle mass, physical performance, and traditional risk factors. Results: During the follow-up of 12 years, 198 (30.89%) participants died. Low hSMI, low GS, high TUG, high TCS, low WaLP, and low HS were associated with high risks of mortality after the adjustment for confounders. The results of receiver operating characteristic (ROC) curve analyses revealed the values of ROC for models with additional consideration for TUG or all indicators significantly improved the discriminatory ability of mortality compared with the model with traditional factors (all P < 0.05). Elders with low hSMI and low GS (HRs = 4.33, 95% CI: 2.76–6.78), high TUG (4.11, 2.60–6.48), high TCS (2.97, 1.92–4.59), low WaLP (3.19, 2.13–4.79), and low HS (4.08, 2.70–6.17) were associated with high risks of mortality compared with those with high hSMI and their corresponding counterparts. Conclusion: The hSMI and physical performance are significantly associated with increased risks of all-cause mortality. The combined use of hSMI and physical performance can provide improved risk stratification, which may be appropriately used as a screening tool targeting high-risk elders for the effective prevention of sarcopenia-related mortality.

Background: Sleep duration is associated with mortality. However, prior studies exploring whether sleep duration predicts subsequent long-term mortality in patients with diabetes are limited. This study aims to examine whether metabolic factors affect the associations between baseline sleep duration and subsequent risks of all-cause, expanded, and non-expanded cardiovascular disease (CVD) mortalities among patients with type 2 diabetes (T2D). Methods: A total of 12,526 T2D patients aged 30 years and older, with a follow-up period ≥ 3 years, were identified from the Diabetes Case Management Program of a medical center in Taiwan. Sleep duration was measured using computerized questionnaires by case managers, and the time frame for this question was 1 month prior to the interview date. Sleep duration in relation to subsequent mortality from all causes, expanded CVD, and non-expanded CVD was examined using Cox proportional hazard models. Results: Within 10 years of follow-up, 2918 deaths (1328 CVD deaths and 1590 non-CVD deaths) were recorded. A J-shaped association was observed for all-cause, expanded CVD, and non-expanded CVD mortalities, and the lowest risks were observed for patients with 5–7 h of sleep. The significant joint effects included sleep duration of more or less than 7 h with age ≥ 65 years [adjusted HRs: 4.00 (3.49–4.60)], diabetes duration ≥ 5 years [1.60 (1.40–1.84)], age at diabetes diagnosis ≤ 45 years [1.69 (1.38–2.07)], insulin use [1.76 (1.54–2.03)], systolic blood pressure/diastolic blood pressure > 130/85 mmHg [1.24 (1.07–1.43)], triglyceride ≥ 150 mg/dL [1.38 (1.22–1.56)], HbA1c ≥ 7% [1.31 (1.13–1.52)], and body mass index < 27 kg/m² [1.31 (1.17–1.45)] for all-cause mortality. Conclusion: A J-shaped association was observed between sleep duration and all-cause and expanded CVD mortality, and a sleep duration of 5–7 h had the lowest mortality risk. Sleep duration also showed significant synergistic interactions with diabetes duration but shared an antagonistic interaction with age and obesity.

Background: Dyslipidemia is a major cardiovascular risk factor and common in diabetes patients. Most guidelines focus on optimal lipid levels, while variation of lipid profiles is far less discussed. This study aims to investigate the association of visit-to-visit variability in blood lipids with all-cause, cardiovascular, and non-cardiovascular mortality in patients with type 2 diabetes.Methods: We identified 10,583 type 2 diabetes patients aged ≥ 30 years with follow-up ≥ 3 years and who participated in the Diabetes Care Management Program at a medical center in Taiwan. Variability in lipid profiles within 3 years after entry was calculated using coefficient of variation. Cox proportional hazard models were used to evaluate lipid variability in relation to subsequent mortality.Results: Over a mean follow-up of 6.4 years, 1838 all-cause deaths (809 cardiovascular deaths) were observed. For each 10% increase in variability in high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol, the hazard ratios (95% confidence intervals) of all-cause mortality were 1.30 (1.22–1.37), 1.05 (1.01–1.09), and 1.10 (1.03–1.16), respectively; those of cardiovascular mortality were 1.27 (1.16–1.39), 1.08 (1.02–1.15), and 1.16 (1.07–1.27), respectively. Each 10% increase in high-density lipoprotein cholesterol variability conveyed 31% greater risk of non-cardiovascular mortality. High variability in total cholesterol and low-density lipoprotein cholesterol increased all-cause mortality in subgroups of nonsmoking, regular exercising, non-dyslipidemia, and more severe status of diabetes at baseline.Conclusions: Blood lipid variability except for triglyceride variability was associated with all-cause and cardiovascular mortality in patients with type 2 diabetes.

Background: Renal function is a key factor of cardiovascular disease. Carotid intima-media thickness (IMT) has been widely used as a marker of early subclinical atherosclerosis. The determinants of cystatin C, a novel marker of renal function, have not been extensively studied in the Asian population. This study aimed to assess the determinants of cystatin C and explore whether carotid thickening was associated with urinary albumin-creatinine ratio and cystatin C in community-living Taiwanese adults. Methods: A cross-sectional study was conducted on participants from Taichung City, Taiwan. All the participants underwent carotid ultrasonography. Carotid IMT-mean and IMT-maximum were derived. Kidney biomarkers were measured on the basis of urinary albumin-to-creatinine ratio (ACR) and cystatin C. Multiple linear regression analysis was used. Results: A total of 1032 individuals were recruited, and 469 (45.44%) of them were men. An increased cystatin C level was significantly associated with older age, male gender, lack of physical activity, low HDL cholesterol, abdominal obesity, high hs-CRP, and high ACR. The multivariate-adjusted mean carotid IMT-mean and IMT-maximum values significantly increased by 80.49 and 195.23 μm for every one unit of increase in cystatin C level and by 0.07 and 0.14 μm for every one unit of increase in ACR, respectively (all p < 0.001 except ACR on IMT-maximum with p < 0.01). Lack of physical activity, low HDL, abdominal obesity, high hs-CRP, and high ACR were the determinants of cystatin C. Conclusion: Cystatin C and ACR were strongly and linearly associated with carotid thickening, a marker of subclinical atherosclerosis.