Changes in frailty and incident cardiovascular disease in three prospective cohorts.

BACKGROUND AND AIMS: Previous studies found that frailty was an important risk factor for cardiovascular disease (CVD). However, previous studies only focused on baseline frailty status, not taking into consideration the changes in frailty status during follow-up. The aim of this study was to investigate the associations of changes in frailty status with incident CVD. METHODS: This study used data of three prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), and Health and Retirement Study (HRS). Frailty status was evaluated by the Rockwood frailty index and classified as robust, pre-frail, or frail. Changes in frailty status were assessed by frailty status at baseline and the second survey which was two years after the baseline. Cardiovascular disease was ascertained by self-reported physician-diagnosed heart disease (including angina, heart attack, congestive heart failure, and other heart problems) or stroke. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders. RESULTS: A total of 7116 participants from CHARLS (female: 48.6%, mean age: 57.4 years), 5303 from ELSA (female: 57.7%, mean age: 63.7 years), and 7266 from HRS (female: 64.9%, mean age: 65.1 years) were included according to inclusion and exclusion criteria. The median follow-up periods were 5.0 years in the CHARLS, 10.7 years in the ELSA, and 9.5 years in the HRS. Compared with stable robust participants, robust participants who progressed to pre-frail or frail status had increased risks of incident CVD (CHARLS, HR = 1.84, 95% CI: 1.54-2.21; ELSA, HR = 1.53, 95% CI: 1.25-1.86; HRS, HR = 1.59, 95% CI: 1.31-1.92). In contrast, frail participants who recovered to robust or pre-frail status presented decreased risks of incident CVD (CHARLS, HR = 0.62, 95% CI: 0.47-0.81; ELSA, HR = 0.49, 95% CI: 0.34-0.69; HRS, HR = 0.70, 95% CI: 0.55-0.89) when compared with stable frail participants. These decreased risks of incident CVD were also observed in pre-frail participants who recovered to robust status (CHARLS, HR = 0.66, 95% CI: 0.52-0.83; ELSA, HR = 0.65, 95% CI: 0.49-0.85; HRS, HR = 0.71, 95% CI: 0.56-0.91) when compared with stable pre-frail participants. CONCLUSIONS: Different changes in frailty status are associated with different risks of incident CVD. Progression of frailty status increases incident CVD risks, while recovery of frailty status decreases incident CVD risks.

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.

Internal blood lead exposure levels in permanent residents of Jiangxi Province and its effects on routine hematological and biochemical indices.

Background: Lead exposure levels are closely linked to human health and can cause damage to multiple organ systems, including the blood system and liver. However, due to insufficient evidence, the effects of lead exposure on hematological and biochemical indices have not been fully established. Objective: This study aims to explore the blood lead levels of permanent residents in Jiangxi Province and analyze the factors affecting blood lead levels and the impact of blood lead levels on hematological and biochemical indices. Methods: We conducted a cross-sectional study including questionnaires, health examinations, and blood sample examinations on 720 randomly selected permanent residents (3-79 years) in Jiangxi Province in 2018. The blood lead levels were measured using inductively coupled plasma mass spectrometry. Routine hematological and biochemical tests were determined by qualified medical institutions using automated hematology analyzers and biochemistry analyzers. Results: The geometric mean of blood lead concentration in permanent residents of Jiangxi Province was 20.45 µg/L. Gender, age, annual household income, smoking, and hypertension were the influencing factors for blood lead levels. For each 1 µg/L increase in blood lead, the risks of elevated red blood cell count (from low to high), platelet volume distribution width, alkaline phosphatase (from low to high), and cholesterol increased by 2.4, 1.6, 3.6, and 2.3%, respectively, whereas the risks of elevation of direct bilirubin and total bilirubin both decreased by 1.7%. Conclusion: The blood lead level in permanent residents of Jiangxi Province is higher than the national average. Higher blood lead levels were found in men than in women; blood lead levels were positively correlated with age but negatively correlated with annual household income; smoking and hypertension are risk factors for elevated blood lead; and blood lead levels affect routine hematological and biochemical markers such as red blood cell count, platelet volume distribution width, direct bilirubin, total bilirubin, alkaline phosphatase, and cholesterol.