Low-density lipoprotein cholesterol was inversely associated with 3-year all-cause mortality among Chinese oldest old: data from the Chinese Longitudinal Healthy Longevity Survey.
Abstract
<h4>Objective</h4>Low-density lipoprotein cholesterol (LDL-C) is a risk factor for
survival in middle-aged individuals, but conflicting evidence exists on the relationship
between LDL-C and all-cause mortality among the elderly. The goal of this study was
to assess the relationship between LDL-C and all-cause mortality among Chinese oldest
old (aged 80 and older) in a prospective cohort study.<h4>Methods</h4>LDL-C concentration
was measured at baseline and all-cause mortality was calculated over a 3-year period.
Multiple statistical models were used to adjust for demographic and biological covariates.<h4>Results</h4>During
three years of follow-up, 447 of 935 participants died, and the overall all-cause
mortality was 49.8%. Each 1 mmol/L increase of LDL-C concentration corresponded to
a 19% decrease in 3-year all-cause mortality (hazard ratio [HR] 0.81, 95% confidence
interval [CI] 0.71-0.92). The crude HR for abnormally higher LDL-C concentration (≥3.37 mmol/L)
was 0.65 (0.41-1.03); and the adjusted HR was statistically significant around 0.60
(0.37-0.95) when adjusted for different sets of confounding factors. Results of sensitivity
analysis also showed a significant association between higher LDL-C and lower mortality
risk.<h4>Conclusions</h4>Among the Chinese oldest old, higher LDL-C level was associated
with lower risk of all-cause mortality. Our findings suggested the necessity of re-evaluating
the optimal level of LDL-C among the oldest old.
Type
Journal articleSubject
HumansTreatment Outcome
Mortality
Risk Factors
Sensitivity and Specificity
Longitudinal Studies
Follow-Up Studies
Prospective Studies
Longevity
Aged
Aged, 80 and over
China
Female
Male
Cholesterol, LDL
Biomarkers
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https://hdl.handle.net/10161/22876Published Version (Please cite this version)
10.1016/j.atherosclerosis.2015.01.002Publication Info
Lv, Yue-Bin; Yin, Zhao-Xue; Chei, Choy-Lye; Qian, Han-Zhu; Kraus, Virginia Byers;
Zhang, Juan; ... Zeng, Yi (2015). Low-density lipoprotein cholesterol was inversely associated with 3-year all-cause
mortality among Chinese oldest old: data from the Chinese Longitudinal Healthy Longevity
Survey. Atherosclerosis, 239(1). pp. 137-142. 10.1016/j.atherosclerosis.2015.01.002. Retrieved from https://hdl.handle.net/10161/22876.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Virginia Byers Kraus
Mary Bernheim Distinguished Professor of Medicine
Virginia Byers Kraus, MD, PhD, is the Mary Bernheim Distinguished Professor of Medicine,
Professor of Orthopaedic Surgery, Professor of Pathology and a faculty member of the
Duke Molecular Physiology Institute in the Duke University School of Medicine. She
is a practicing Rheumatologist with over 30 years’ experience in translational musculoskeletal
research focusing on osteoarthritis, the most common of all arthritides. She trained
at Brown University (ScB 1979), Duke University (MD 19
David Bruce Matchar
Professor of Medicine
My research relates to clinical practice improvement - from the development of clinical
policies to their implementation in real world clinical settings. Most recently my
major content focus has been cerebrovascular disease. Other major clinical areas in
which I work include the range of disabling neurological conditions, cardiovascular
disease, and cancer prevention. Notable features of my work are: (1) reliance on
analytic strategies such as meta-analysis, simulation, decision analy
Yi Zeng
Professor in Medicine
(1) Socioeconomic, behavior, environmental and genetic determinants of healthy aging
and healthy longevity; (2) Factors related to elderly disability and mental health;
(3) Methods of family households and elderly living arrangements forecasting/analysis
and their applications in health services and socioeconomic planning, and market studies;
(4) Policy analysis in population aging, social welfare, retirement, and fertility
transitions.
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