Dataset Information

Derivation and validation of 10-year all-cause and cardiovascular disease mortality prediction model for middle-aged and elderly community-dwelling adults in Taiwan.

ABSTRACT: Prediction model mainly focused on specific diseases, such as diabetes, hypertension, cardiovascular disease, or patients with cancer, or populations of Europe and America, thereby limiting its generalization. This study aimed to develop and validate a 10-year mortality risk score by using data from a population-representative sample of adults. Data were collected from 2,221 Taichung Community Health study participants aged ?40 years. The baseline period of the study was 2004, and all participants were followed up until death or in 2016. Cox's proportional hazards regression analyses were used to develop the prediction model. A total of 262 deaths were ascertained during the 10-year follow-up. The all-cause mortality prediction model calculated the significant risk factors, namely, age, sex, marital status, physical activity, tobacco use, estimated glomerular filtration rate, and albumin-to-creatinine ratio, among the baseline risk factors. The expanded cardiovascular disease (CVD) mortality prediction model consisted of six variables: age, sex, body mass index, heart disease plus heart disease medication use, stroke plus medication use, and ankle-brachial index. The areas under receiver operating curves of the 3-, 5- and 10-year predictive models varied between 0.97, 0.96, and 0.88 for all-cause mortality, and between 0.97, 0.98, and 0.84 for expanded CVD mortality. These mortality prediction models are valid and can be used as tools to identify the increased risk for mortality.

SUBMITTER: Li TC

PROVIDER: S-EPMC7489508 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Derivation and validation of 10-year all-cause and cardiovascular disease mortality prediction model for middle-aged and elderly community-dwelling adults in Taiwan.

Li Tsai-Chung TC Li Chia-Ing CI Liu Chiu-Shong CS Lin Wen-Yuan WY Lin Chih-Hsueh CH Yang Shing-Yu SY Lin Cheng-Chieh CC

PloS one 20200914 9

Prediction model mainly focused on specific diseases, such as diabetes, hypertension, cardiovascular disease, or patients with cancer, or populations of Europe and America, thereby limiting its generalization. This study aimed to develop and validate a 10-year mortality risk score by using data from a population-representative sample of adults. Data were collected from 2,221 Taichung Community Health study participants aged ≥40 years. The baseline period of the study was 2004, and all participan ...[more]

PMID: 32925948

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Project description:BackgroundCardiovascular disease (CVD) is one of the leading causes of mortality and loss of disability-adjusted life years in developed countries. This study derived a dietary pattern using an a priori method and additionally derived dietary patterns using a posteriori methods, and assessed the relationship with CVD risk factors in Taiwanese middle-aged and elderly adults.MethodsCross-sectional analyses of 62,965 subjects aged 40 years and above from the Mei Jau (MJ) database collected between 2003 and 2012 in Taiwan. Diet was assessed using a 22 item semi-quantitative food frequency questionnaire. Using this information, three dietary patterns were generated. The a priori diet was labeled the Taiwanese dietary pattern and was derived using hypothesized effect of 22 food groups, while two a posteriori dietary patterns, "vegi-fruits" and "meat-processed", were derived using principal component analysis. The association between dietary patterns and a range of CVD risk factors (i.e. blood lipids, blood glucose and C-reactive protein) was evaluated using linear regression.ResultsThe results showed that high intake (Q5, quintile 5) of Taiwanese diet was negatively associated with CVD risk factors at (p < 0.001, model 3), but not with triacylglycerol. In addition, high intake of vegi-fruit dietary pattern (Q5) was negatively associated with CVD risk factors (p < 0.001), but not with high-density lipoprotein, while high consumption of meat-processed dietary pattern (Q5) was positively associated with CVD risk factors (p < 0.001), but negatively related with triacylglycerol in Q3 level and no association with C-reactive protein.ConclusionA negative association was observed between Taiwanese or vegi-fruit dietary patterns and CVD risk factors, while a positive association was found between meat-processed dietary pattern and CVD risk factors. The findings suggested that a diet rich in vegetables and fruits has a beneficial effect in the management of CVD risk factors.

Project description:The predictive value of traditional cardiovascular risk estimators is limited, and young and elderly populations are particularly underrepresented. We aimed to investigate the urine metabolome and its association with cardiovascular risk to identify novel markers that might complement current estimators based on age. Urine samples were collected from 234 subjects categorized into three age-grouped cohorts: 30-50 years (cohort I, young), 50-70 years (cohort II, middle-aged), and > 70 years (cohort III, elderly). Each cohort was further classified into three groups: (a) control, (b) individuals with cardiovascular risk factors, and (c) those who had a previous cardiovascular event. Novel urinary metabolites linked to cardiovascular risk were identified by nuclear magnetic resonance in cohort I and then evaluated by target mass spectrometry quantification in all cohorts. A previously identified metabolic fingerprint associated with atherosclerosis was also analyzed and its potential risk estimation investigated in the three aged cohorts. Three different metabolic signatures were identified according to age: 2-hydroxybutyrate, gamma-aminobutyric acid, hypoxanthine, guanidoacetate, oxaloacetate, and serine in young adults; citrate, cyclohexanol, glutamine, lysine, pantothenate, pipecolate, threonine, and tyramine shared by middle-aged and elderly adults; and trimethylamine N-oxide and glucuronate associated with cardiovascular risk in all three cohorts. The urinary metabolome contains a metabolic signature of cardiovascular risk that differs across age groups. These signatures might serve to complement existing algorithms and improve the accuracy of cardiovascular risk prediction for personalized prevention. KEY MESSAGES: • Cardiovascular risk in the young and elderly is underestimated. • The urinary metabolome reflects cardiovascular risk across all age groups. • Six metabolites constitute a metabolic signature of cardiovascular risk in young adults. • Middle-aged and elderly adults share a cardiovascular risk metabolic signature. • TMAO and glucuronate levels reflect cardiovascular risk across all age groups.

Dataset Information

Derivation and validation of 10-year all-cause and cardiovascular disease mortality prediction model for middle-aged and elderly community-dwelling adults in Taiwan.

Publications

Derivation and validation of 10-year all-cause and cardiovascular disease mortality prediction model for middle-aged and elderly community-dwelling adults in Taiwan.

Similar Datasets

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