TY - JOUR
T1 - Longitudinal change in fasting blood glucose and myocardial infarction risk in a population without diabetes
AU - Jin, Cheng
AU - Chen, Shuohua
AU - Vaidya, Anand
AU - Wu, Yuntao
AU - Wu, Zhijun
AU - Hu, Frank B.
AU - Kris-Etherton, Penny
AU - Wu, Shouling
AU - Gao, Xiang
N1 - Publisher Copyright:
© 2017 by the American Diabetes Association.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - OBJECTIVE To examine the change in fasting blood glucose (FBG) during repeated assessments over time and its potential impact on the risk of developing myocardial infarction (MI). RESEARCH DESIGN AND METHODS This prospective cohort study included 68,297 participants without diabetes (mean age 49 years) whowere free ofMI, stroke, and cancer prior to or in 2010 (baseline of the current analysis). FBG concentrations were measured in 2006, 2008, and 2010. The FBG trajectories during 2006-2010, the primary exposure of the current study, were identified by latent mixture modeling. Incident MI cases were confirmed via review of medical records by cardiologists. RESULTS We identified five discrete FBG trajectories according to FBG range and changing pattern over time: elevated-stable (n = 3,877), elevated-decreasing (n = 7,060), moderate-increasing (n = 10,298), moderate-stable (n = 40,352), and low-stable (n = 6,710). During 4 years of follow-up, we documented 283 incident MI cases. Relative to the moderate-stable pattern (FBG ranged from 4.9 to 5.1 mmol/L), adjusted hazard ratios (HRs) were 1.53 (95% CI 1.04, 2.26) for the elevated-stable pattern (FBG ranged from 6.1 to 6.3 mmol/L) and HR 0.61 (95% CI 0.38, 0.98) for the elevated-decreasing pattern (FBG decreased from 6.0 to 5.4 mmol/L), after adjustment for potential confounders such as age, sex, lifestyle factors, obesity, medical history, blood pressure, blood lipids, and C-reactive protein. Consistently, cumulative average and increasing rate of FBG during 2006-2010, but not a single baseline FBG, predicted future risk of MI. CONCLUSIONS We found that discrete FBG trajectories were significantly associated with subsequent risk of MI in individuals without diabetes. These observations suggest that long-term trajectories of FBG may be important for risk prediction of MI and possibly other macrovascular diseases.
AB - OBJECTIVE To examine the change in fasting blood glucose (FBG) during repeated assessments over time and its potential impact on the risk of developing myocardial infarction (MI). RESEARCH DESIGN AND METHODS This prospective cohort study included 68,297 participants without diabetes (mean age 49 years) whowere free ofMI, stroke, and cancer prior to or in 2010 (baseline of the current analysis). FBG concentrations were measured in 2006, 2008, and 2010. The FBG trajectories during 2006-2010, the primary exposure of the current study, were identified by latent mixture modeling. Incident MI cases were confirmed via review of medical records by cardiologists. RESULTS We identified five discrete FBG trajectories according to FBG range and changing pattern over time: elevated-stable (n = 3,877), elevated-decreasing (n = 7,060), moderate-increasing (n = 10,298), moderate-stable (n = 40,352), and low-stable (n = 6,710). During 4 years of follow-up, we documented 283 incident MI cases. Relative to the moderate-stable pattern (FBG ranged from 4.9 to 5.1 mmol/L), adjusted hazard ratios (HRs) were 1.53 (95% CI 1.04, 2.26) for the elevated-stable pattern (FBG ranged from 6.1 to 6.3 mmol/L) and HR 0.61 (95% CI 0.38, 0.98) for the elevated-decreasing pattern (FBG decreased from 6.0 to 5.4 mmol/L), after adjustment for potential confounders such as age, sex, lifestyle factors, obesity, medical history, blood pressure, blood lipids, and C-reactive protein. Consistently, cumulative average and increasing rate of FBG during 2006-2010, but not a single baseline FBG, predicted future risk of MI. CONCLUSIONS We found that discrete FBG trajectories were significantly associated with subsequent risk of MI in individuals without diabetes. These observations suggest that long-term trajectories of FBG may be important for risk prediction of MI and possibly other macrovascular diseases.
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U2 - 10.2337/dc17-0610
DO - 10.2337/dc17-0610
M3 - Article
C2 - 28887409
AN - SCOPUS:85033221601
SN - 0149-5992
VL - 40
SP - 1565
EP - 1572
JO - Diabetes care
JF - Diabetes care
IS - 11
ER -