Kosuke Inoue1, Roch Nianogo1, Donatello Telesca2, Atsushi Goto3, Vahe Khachadourian4, Yusuke Tsugawa5,6, Takehiro Sugiyama7,8, Elizabeth Rose Mayeda1, Beate Ritz1,9,10. 1. Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 2. Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 3. Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan. 4. Gerald & Patricia Turpanjian School of Public Health, American University of Armenia, Yerevan, Armenia. 5. Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. 6. Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 7. Diabetes and Metabolism Information Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan. 8. Department of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan. 9. Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 10. Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.
Abstract
OBJECTIVE: It is unclear whether relatively low glycated haemoglobin (HbA1c) levels are beneficial or harmful for the long-term health outcomes among people without diabetes. We aimed to investigate the association between low HbA1c levels and mortality among the US general population. METHODS: This study includes a nationally representative sample of 39 453 US adults from the National Health and Nutrition Examination Surveys 1999-2014, linked to mortality data through 2015. We employed the parametric g-formula with pooled logistic regression models and the ensemble machine learning algorithms to estimate the time-varying risk of all-cause and cardiovascular mortality by HbA1c categories (low, 4.0 to <5.0%; mid-level, 5.0 to <5.7%; prediabetes, 5.7 to <6.5%; and diabetes, ≥6.5% or taking antidiabetic medication), adjusting for 72 potential confounders including demographic characteristics, lifestyle, biomarkers, comorbidities and medications. RESULTS: Over a median follow-up of 7.5 years, 5118 (13%) all-cause deaths, and 1116 (3%) cardiovascular deaths were observed. Logistic regression models and machine learning algorithms showed nearly identical predictive performance of death and risk estimates. Compared with mid-level HbA1c, low HbA1c was associated with a 30% (95% CI, 16 to 48) and a 12% (95% CI, 3 to 22) increased risk of all-cause mortality at 5 years and 10 years of follow-up, respectively. We found no evidence that low HbA1c levels were associated with cardiovascular mortality risk. The diabetes group, but not the prediabetes group, also showed an increased risk of all-cause mortality. CONCLUSIONS: Using the US national database and adjusting for an extensive set of potential confounders with flexible modelling, we found that adults with low HbA1c were at increased risk of all-cause mortality. Further evaluation and careful monitoring of low HbA1c levels need to be considered.
OBJECTIVE: It is unclear whether relatively low glycated haemoglobin (HbA1c) levels are beneficial or harmful for the long-term health outcomes among people without diabetes. We aimed to investigate the association between low HbA1c levels and mortality among the US general population. METHODS: This study includes a nationally representative sample of 39 453 US adults from the National Health and Nutrition Examination Surveys 1999-2014, linked to mortality data through 2015. We employed the parametric g-formula with pooled logistic regression models and the ensemble machine learning algorithms to estimate the time-varying risk of all-cause and cardiovascular mortality by HbA1c categories (low, 4.0 to <5.0%; mid-level, 5.0 to <5.7%; prediabetes, 5.7 to <6.5%; and diabetes, ≥6.5% or taking antidiabetic medication), adjusting for 72 potential confounders including demographic characteristics, lifestyle, biomarkers, comorbidities and medications. RESULTS: Over a median follow-up of 7.5 years, 5118 (13%) all-cause deaths, and 1116 (3%) cardiovascular deaths were observed. Logistic regression models and machine learning algorithms showed nearly identical predictive performance of death and risk estimates. Compared with mid-level HbA1c, low HbA1c was associated with a 30% (95% CI, 16 to 48) and a 12% (95% CI, 3 to 22) increased risk of all-cause mortality at 5 years and 10 years of follow-up, respectively. We found no evidence that low HbA1c levels were associated with cardiovascular mortality risk. The diabetes group, but not the prediabetes group, also showed an increased risk of all-cause mortality. CONCLUSIONS: Using the US national database and adjusting for an extensive set of potential confounders with flexible modelling, we found that adults with low HbA1c were at increased risk of all-cause mortality. Further evaluation and careful monitoring of low HbA1c levels need to be considered.
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