Night Sleep Duration and Risk of Incident Anemia in a Chinese Population: A Prospective Cohort Study

Abstract

The purpose was to study the association between sleep duration and the prevalence of anemia in Chinese people. There were 84,791 participants (men: 79.1%; women: 20.9%) aged 18–98 years in the prospective study. We divided the participants into five categories based on the individual sleep duration: ≤5 h, 6 h, 7 h(reference), 8 h, and ≥9 h. Anemia was defined based on hemoglobin <12 g/dL for men and <11 g/dL for women. The Cox proportional hazards model was used to assess the association between sleep duration and anemia. During median follow-up of 7.9 years, 2698 cases of anemia had occurred. The HRand (95% CI) of anemia (7 h as the reference group) for individuals reporting ≤5 h, 6 h, 8 h, and ≥9 h were 1.23(1.04–1.45), 1.26(1.11–1.44), 1.04(0.92–1.16) and 1.42(1.08–1.86), respectively. It showed that there was a significant interaction on the risk of anemia between sleep duration and sex in the secondary analysis (p < 0.001).The significant association between long sleepduration and anemia was found in women (HR, 2.29; 95% CI, 1.56–3.37), not in men(HR, 0.90; 95% CI, 0.60–1.34). Both short and long night sleep duration were associated with increased risk of anemia.

Introduction

Anemia has been linked to cardiovascular disease and mortality1,2,3,4,5,6. Similar with the common cardiovascular risk factors, such as smoking, diabetes, hypertension and hypercholesterolemia, anemia can also increase the risk of mortality, morbidity and hospitalization1,2,3,4,5,6. Consequently, anemia has lately been characterized as another cardiovascular risk factor7,8,9. Thus, it is necessary to identify anemia-related risk factors so that. we can take effective prevention and management strategies as early as possible. In addition to the traditional risk factors including age10, malnutrition, chronic kidney disease11, and poor glycemic control12,13, we have found some new risk factors for anemia, such as sleep14,15.

Recently, many epidemiological studies have reported that either a long or a short sleep duration is independently associated with cardiovascular disease16,17,18,19,20,21,22.Both sleep duration and anemia are recognized as strong, independent risk factors for ischemia and mortality events23,24.However, only a few studies to date have examined the association between sleep alterations and risk of iron deficiency anemia in infancy14,15. Another study evaluated the association between self-reported sleep duration and anemia on British people over 50 years old. The result showed that short sleep time could lead to low hemoglobin concentration, and disturbed sleep also increased the risk of anemia25. It is limited on the association between night sleep duration and risk for anemia in the general population. Alternatively, considering that a women-specific associations of short sleep duration with hypertension were reported in British population26,27, we further conducted a longitudinal analysis focusing primarily on the association between sleep duration and anemia, using the comprehensive data from the Kailuan Study28 stratified by age and sex.

Results

The percent of participants who reported sleeping for ≤5 h, 6 h, 7 h, 8 h, and ≥9 h per night were 7.1%, 17.3%, 17.8%, 60.0%, and 1.8%, respectively. The baseline characteristics by sleep duration was shown in Table 1. There were significant associations between sleep duration and age, sex, education level, smoking status, drinking status, physical activity, body mass index, blood pressure level, fasting blood glucose, total cholesterol, hypertension, diabetes mellitus, dyslipidemia, snoring status, and high sensitive C-reactive protein. The similar result was also found in our previous paper29.

Table 1 Baseline characteristics according to sleep duration.

Age, the percentage of women, education level, and the level of sensitivity C-reactive protein among participants with anemia were higher than those without anemia. In contrast, the prevalence of hypertension, the prevalence of obesity and snoring prevalence were lower among participants with anemia than without anemia (all p < 0.001).(Table 2)

Table 2 Comparisons between patients with and without anemia among Kailuan study.

As shown in Table 3, we can observe the hazard ratios for anemia according to sleep duration in total population and stratified by sex. Out of all the 84791 individuals, 2,698 participants developed anemia (men: 1,770; women: 928). The incidence per 1000 person years of anemia was 3.8 in men, and 7.2 in women. In the COX regression analysis, with adjustment for all variables (model 3), the multivariable adjusted hazard ratios of anemia among the participants were 1.23 (95% CI, 1.04–1.45) for a ≤ 5 h sleep duration, 1.26 (95% CI, 1.11–1.44) for 6 h, 1.04(95% CI, 0.92–1.16) for 8 h and 1.42 (95% CI, 1.08–1.86) for ≥9 h compared with the participants with 7 h of sleep. The risk of anemia in women with more than 8 hours of sleep (HR, 2.29; 95% CI, 1.56–3.37) was higher, but not in men (HR, 0.90; 95% CI, 0.60–1.34), a formal test for difference by sex also found statistical significance (p-interaction for long sleep duration <0.001; P-interaction for short sleep duration >0.05). In addition, the association between sleep duration and anemia was still significant in participants excluding the individuals who have myocardial infarction, stroke and cancer.

Table 3 Hazard ratios (95% CI) for anemia according to sleep duration in the Kailuan Study.

Further study stratified by different age groups was analysed in Table 4. Participants aged <60 years and who slept ≤5 hours (HR, 1.24; 95% CI, 1.01–1.53) or ≥9 hours (HR, 1.40; 95% CI, 1.04–1.90) were found likely to develop anemia. The older participants (ages ≥ 60) who slept ≤5 h (HR, 1.16; 95% CI, 0.86–1.56) or ≥9 hours(HR, 1.04; 95% CI, 0.57–1.89) were less likely to develop anemia. The interaction of sleep duration with age on the incident anemia is not significant (p > 0.05).

Table 4 Hazard ratios (95% CI) for anemia according to sleep duration stratified by age in the Kailuan Study.

Discussion

In the present study, both long and short sleep durations independently predicted an increased risk for incident anemia, after a follow-up of median 7.9 years, as shown during a median 7.9 years of follow-up. These relationships persist even after adjusting other known major risk factors, such as smoking, drinking, diabetes, hypertension, dyslipidemia, obesity, and high-sensitivity C-reactive protein. Sensitivity analyses further confirmed these findings.

The English Longitudinal Study of Ageing (ELSA)25, with participants of 6465 men and women aged 50–99 years, found that there was significant influence of short and disturbed sleep on low hemoglobin concentrations. Results of this study further found that the disturbed sleep was a risk factor of anemia.Our results are partly consistent with this study25.But the difference is that we also demonstrated that a long sleep duration was an independent predictor for incident anemia. Additionally, in the previous studies, traditional predictors for anemia had no significant difference between men and women.25. However, we found that the risk of anemia in women with long sleep duration was higher. But the difference was not significant among men. We have not found the exact cause of the result yet. The reason for the gender difference in the relationship between the sleep time and the anemia may be due to the differences in hormonal secretion and psychological factors in gender. Unfortunately, we did not collect sufficient data on the pre- or post-menopause status of women participants, which appeared to be an important determinant of anemia risk in women. In addition, considering that this connection might be affected by different sleep behaviors in different age groups, we performed a stratified analysis based on age. Participants aged <60 years and sleepping ≥9 hours were found to be more likely to develop anemia.However, there was no interaction between sleep duration and age in the risk of anemia (p-interaction >0.05).The above results stratified by age and sex further endorsed the possibility that the associations observed may be driven entirely by younger women.However, the lack of information on biological differences among different groupslimits us to further investigate whether the association could be modified or mediated by these factors.

Previous studies found that sleep apnea might be another pathway mediating long sleep duration with chronic diseases30. Evidence also have showed that sleep apnea may be an important anemia predictor31,32,33,34. A cohort study conducted in children also showed that children with sickle cell anemia had a high prevalence of sleep apnea with typical symptoms31. Unfortunately, sleep apnea was not measured in our study, but snoring status was used as a confounder instead of sleep apnea. After adjusting snoring status, sleep duration in our study was persistently associated with incident anemia.

We have not found the underlying mechanism for sleep duration and incident anemia. Inflammation is one of the most important biological pathways, because the long sleep time can lead to the increasing of inflammatory markers. In addition, the result that sleep deprivation could cause an increase in inflammatory response has been shown by a recent study35. And in this study, individuals who reported short(≤5 h) or long sleep duration (≥9 h)were more likely to be engaged in higher level of sensitivity C-reactive protein group than those who slept 7 h. We also found that the level of sensitivity C-reactive protein in participants with anemia was higher than those without anemia.

Limitations

First, we collect the data of sleep duration through self-reported questionnaires. In contrast, the polysomnography is a more valid and reliable measurement of sleep. Information on Chinese midday naps and sleep quality were not collected in current study. Participants with sleep apnea were not excluded, which is associated with high risk of anemia31,32. However, we adjusted for snoring status as an alternative confounder. In addition, the full model in our study was adjusted for corresponding risk factors for sleep apnea, such as body mass index, age, and smoking36. Second, anemia in our study was only diagnosed using the hemoglobin content without employing red cell hematocrit, mean cellular volume, and bone marrow iron staining. Therefore, we could not distinguish different types of anemia (including sickle cell anemia, iron deficiency anemia or renal anemia) in this study. Third, we only investigated the sleep duration at the baseline, without taking the sleep duration changes into consideration. Indeed, any subsequent alterations in sleep may lead to a non-differential misclassification and potentially underestimate the sleep–anemia association14. Fourth, there was not a rationale forthe analysis in our studyusing 60 years as a cut-off value. Alternatively, we used the same cut-off valueof 60 in our previous publications20,37. Finally, we only investigated employees of the Kailuan Coal Company, which most of them were men. Therefore, the results may not be applicable to the general population.

In conclusion, our study suggest that both long and short sleep durations may cause an increased risk of anemia in a Chinese population. In addition to nutritional deficiencies, malignant tumor or other chronic illnesses, inappropriate sleep might be taken in this condition.

Methods

Ethics statement

The protocol for the present study was approved by the Ethics Committee of Kailuan General Hospital in compliance with the Declaration of Helsinki, and all participants provided written informed consent.29,38.

Study design and participants

The Kailuan study was a prospective cohort study involving 101510 participants (men: 81110; women: 20400, aged 18–98 years) in Kailuan community from June 2006 to October 200729. This study enrolled 84791 participants, excluding someone who had history of anemia (3703), incomplete sleep data (3986), and incomplete hemoglobin data (9030). We carried out questionnaire surveys and investigated clinical and laboratory indicators among all the participants. Before the study, all doctors and nurses received rigorous unified training.

Assessment of sleep duration

Sleep duration data was collected through a self-reported answer to the question “How many hours of sleep have you had on an average night in the preceding 3 months?”We divided sleep durations into five groups according to the responses: ≤5 hours, 6 hours, 7 hours, 8 hours, and ≥9 hours. Additionally, participants were asked to answer “yes” or “no” to the question “Do you generally snore when you sleep?”29.

Assessment of potential covariates

We collected the data of demographic and clinical characteristics self-reported questionnaires, including age, sex, alcohol use, education, and disease history. Educational status was divided into “illiterate or primary school”, “middle school”, or “high school or above”. Physical activity was divided into “ ≥80 minutes every week(active)”, “1 to 79 minutes every week (intermediate)”, or “none”.29,38. Smoking status and drinking status were divided into “never”, “former”, or “current”. Body mass index (BMI) was calculated as the weight (kg) divided by the square of height (meters2). Blood pressure was measured three times using a standardized sphygmometer in the seated position. We used the average at last.

We measured the levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting blood-glucose (FBG), and high-sensitivity C-reactive protein (HCRP),. All these blood samples were analyzed by using a Hitachi 747 auto-analyzer (Hitachi; Tokyo, Japan)29 Diabetes was defined as having a history of diabetes, the use of glucose-lowering agents, or a fasting blood glucose ≥7 mmol/l. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, having a history of hypertension and/or the use of antihypertensive agents. Dyslipidemia was defined as having a history of dyslipidemia or the use of anti-lipidemic agents, TC ≥6.2 mmol/l, TG ≥2.3 mmol/l, LDL-C ≥ 4.1 mmol/l, or HDL-C < 1.0 mmol/l39.

Follow-up and anemia assessment

Participants were followed up by face-to-face interviews at every 2-year routine medical examination until December 31, 2015, or until the event of interest or death29.Person-years were calculated from the date the 2006 interview was conducted to the date when anemia was detected, date of death, or date of the last attended interview in this analysis, whichever came first29. Anemia status (no/yes) was defined based on hemoglobin <12 g/ dL for men and <11 g/dL for women40.

Statistical analyses

The statistical analysis was performed using SAS 9.4. We described continuous variables by their means ± standard deviations, and compared groups using one-way analysis of variance (ANOVA). Categorical variables were described as percentages and compared by the Chi-square test. We used Cox proportional hazards regression to estimate the risk of anemia by HR with 95% confidence intervals (CIs). Model 1 adjusted for age and sex. Model 2 further adjusted for level of education, smoking, alcohol, physical activity, and snoring. Model 3 further adjusted for hypertension, diabetes mellitus, dyslipidemia, body mass index, and high-sensitivity C-reactive protein.We assessed the association between sleep duration and age/sex in the secondary analyses. In addition, the robustness of our findings also be tested by a sensitivity analysis. Because major chronic illnesses including history of myocardial infarction, stroke and cancer can affect sleep behavior and future anemia risk, we repeated our analysis after excluding individuals with these conditions. Because 11 hospitals participated in the study, we used a Cox proportional hazards model with a sandwich covariance matrix as a random effect to account for the potential confounding effect of multiple hospitals participating in the study29. All statistical tests were two-sided, and the significance level was set at 0.05.

References

  1. 1.

    Coresh, J., Astor, B. & Sarnak, M. J. Evidence for increased cardiovascular disease risk in patients with chronic kidney disease. Current opinion in nephrology and hypertension 13, 73–81 (2004).

    Article  PubMed  Google Scholar 

  2. 2.

    Culleton, B. F. et al. Impact of anemia on hospitalization and mortality in older adults. Blood 107, 3841–3846, https://doi.org/10.1182/blood-2005-10-4308 (2006).

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Dong, X. et al. A population-based study of hemoglobin, race, and mortality in elderly persons. The journals of gerontology. Series A, Biological sciences and medical sciences 63, 873–878 (2008).

    Article  Google Scholar 

  4. 4.

    Penninx, B. W., Pahor, M., Woodman, R. C. & Guralnik, J. M. Anemia in old age is associated with increased mortality and hospitalization. The journals of gerontology. Series A, Biological sciences and medical sciences 61, 474–479 (2006).

    Article  Google Scholar 

  5. 5.

    Zakai, N. A. et al. A prospective study of anemia status, hemoglobin concentration, and mortality in an elderly cohort: the Cardiovascular Health Study. Archives of internal medicine 165, 2214–2220, https://doi.org/10.1001/archinte.165.19.2214 (2005).

    ADS  Article  PubMed  Google Scholar 

  6. 6.

    Anand, I. et al. Anemia and its relationship to clinical outcome in heart failure. Circulation 110, 149–154, https://doi.org/10.1161/01.CIR.0000134279.79571.73 (2004).

    Article  PubMed  Google Scholar 

  7. 7.

    Lee, W. C. et al. Anemia: A significant cardiovascular mortality risk after ST-segment elevation myocardial infarction complicated by the comorbidities of hypertension and kidney disease. PloS one 12, e0180165, https://doi.org/10.1371/journal.pone.0180165 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Spence, R. K. The economic burden of anemia in heart failure. Heart failure clinics 6, 373–383, https://doi.org/10.1016/j.hfc.2010.02.003 (2010).

    Article  PubMed  Google Scholar 

  9. 9.

    Tanimura, M. et al. Effect of Anemia on Cardiovascular Hemodynamics, Therapeutic Strategy and Clinical Outcomes in Patients With Heart Failure and Hemodynamic Congestion. Circulation journal: official journal of the Japanese Circulation Society 81, 1670–1677, https://doi.org/10.1253/circj.CJ-17-0171 (2017).

    Article  Google Scholar 

  10. 10.

    Stauffer, M. E. & Fan, T. Prevalence of anemia in chronic kidney disease in the United States. PloS one 9, e84943, https://doi.org/10.1371/journal.pone.0084943 (2014).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Portoles, J. et al. The development of anemia is associated to poor prognosis in NKF/KDOQI stage 3 chronic kidney disease. BMC nephrology 14, 2, https://doi.org/10.1186/1471-2369-14-2 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Gauci, R., Hunter, M., Bruce, D. G., Davis, W. A. & Davis, T. M. E. Anemia complicating type 2 diabetes: Prevalence, risk factors and prognosis. Journal of diabetes and its complications 31, 1169–1174, https://doi.org/10.1016/j.jdiacomp.2017.04.002 (2017).

    Article  PubMed  Google Scholar 

  13. 13.

    Gu, L., Lou, Q., Wu, H., Ouyang, X. & Bian, R. Lack of association between anemia and renal disease progression in Chinese patients with type 2 diabetes. Journal of diabetes investigation 7, 42–47, https://doi.org/10.1111/jdi.12368 (2016).

    Article  PubMed  Google Scholar 

  14. 14.

    Peirano, P. D. et al. Sleep alterations and iron deficiency anemia in infancy. Sleep medicine 11, 637–642, https://doi.org/10.1016/j.sleep.2010.03.014 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Peirano, P., Algarin, C., Garrido, M., Algarin, D. & Lozoff, B. Iron-deficiency anemia is associated with altered characteristics of sleep spindles in NREM sleep in infancy. Neurochemical research 32, 1665–1672, https://doi.org/10.1007/s11064-007-9396-8 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Ferrie, J. E. et al. A prospective study of change in sleep duration: associations with mortality in the Whitehall II cohort. Sleep 30, 1659–1666 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Gangwisch, J. E. et al. Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey. Hypertension 47, 833–839, https://doi.org/10.1161/01.HYP.0000217362.34748.e0 (2006).

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Ikehara, S. et al. Association of sleep duration with mortality from cardiovascular disease and other causes for Japanese men and women: the JACC study. Sleep 32, 295–301 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Patel, S. R. et al. A prospective study of sleep duration and mortality risk in women. Sleep 27, 440–444 (2004).

    Article  PubMed  Google Scholar 

  20. 20.

    Song, Q. et al. Long Sleep Duration and Risk of Ischemic Stroke and Hemorrhagic Stroke: the Kailuan Prospective Study. Scientific reports 6, 33664, https://doi.org/10.1038/srep33664 (2016).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Song, Q., Liu, X., Zhou, W., Wang, X. & Wu, S. Changes in sleep duration and risk of metabolic syndrome: the Kailuan prospective study. Scientific reports 6, 36861, https://doi.org/10.1038/srep36861 (2016).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Wang, X., Liu, X., Song, Q. & Wu, S. Sleep duration and risk of myocardial infarction and all-cause death in a Chinese population: the Kailuan study. Sleep medicine 19, 13–16, https://doi.org/10.1016/j.sleep.2015.09.027 (2016).

    Article  PubMed  Google Scholar 

  23. 23.

    Lipsic, E. et al. Hemoglobin levels and 30-day mortality in patients after myocardial infarction. International journal of cardiology 100, 289–292, https://doi.org/10.1016/j.ijcard.2004.10.043 (2005).

    Article  PubMed  Google Scholar 

  24. 24.

    Sabatine, M. S. et al. Association of hemoglobin levels with clinical outcomes in acute coronary syndromes. Circulation 111, 2042–2049, https://doi.org/10.1161/01.CIR.0000162477.70955.5F (2005).

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Jackowska, M., Kumari, M. & Steptoe, A. Sleep and biomarkers in the English Longitudinal Study of Ageing: associations with C-reactive protein, fibrinogen, dehydroepiandrosterone sulfate and hemoglobin. Psychoneuroendocrinology 38, 1484–1493, https://doi.org/10.1016/j.psyneuen.2012.12.015 (2013).

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Cappuccio, F. P. et al. Gender-specific associations of short sleep duration with prevalent and incident hypertension: the Whitehall II Study. Hypertension 50, 693–700, https://doi.org/10.1161/HYPERTENSIONAHA.107.095471 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Kim, S. J. et al. Genetic association of short sleep duration with hypertension incidence–a 6-year follow-up in the Korean genome and epidemiology study. Circulation journal: official journal of the Japanese Circulation Society 76, 907–913, JST.JSTAGE/circj/CJ-11-0713 (2012).

  28. 28.

    Wu, S. et al. Prevalence of ideal cardiovascular health and its relationship with the 4-year cardiovascular events in a northern Chinese industrial city. Circulation. Cardiovascular quality and outcomes 5, 487–493, https://doi.org/10.1161/CIRCOUTCOMES.111.963694 (2012).

    Article  PubMed  Google Scholar 

  29. 29.

    Song, Q. et al. Long Sleep Duration Is an Independent Risk Factor for Incident Atrial Fibrillation in a Chinese Population: A Prospective Cohort Study. Scientific reports 7, 3679, https://doi.org/10.1038/s41598-017-04034-8 (2017).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Foley, D. J. An epidemiological perspective on one tale of a two-tailed hypothesis. Sleep medicine reviews 8, 155–157; discussion 175–156, https://doi.org/10.1016/j.smrv.2004.02.002 (2004).

  31. 31.

    Rosen, C. L. et al. Obstructive sleep apnea and sickle cell anemia. Pediatrics 134, 273–281, https://doi.org/10.1542/peds.2013-4223 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Khan, A. M., Ashizawa, S., Hlebowicz, V. & Appel, D. W. Anemia of aging and obstructive sleep apnea. Sleep & breathing = Schlaf & Atmung 15, 29–34, https://doi.org/10.1007/s11325-010-0326-7 (2011).

    Article  Google Scholar 

  33. 33.

    Grandner, M. A. et al. Extreme sleep durations and increased C-reactive protein: effects of sex and ethnoracial group. Sleep 36, 769–779E, https://doi.org/10.5665/sleep.2646 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Patel, S. R. et al. Sleep duration and biomarkers of inflammation. Sleep 32, 200–204 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Meier-Ewert, H. K. et al. Effect of sleep loss on C-reactive protein, an inflammatory marker of cardiovascular risk. Journal of the American College of Cardiology 43, 678–683, https://doi.org/10.1016/j.jacc.2003.07.050 (2004).

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Punjabi, N. M. The epidemiology of adult obstructive sleep apnea. Proceedings of the American Thoracic Society 5, 136–143, https://doi.org/10.1513/pats.200709-155MG (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Song, Q., Liu, X., Wang, X. & Wu, S. Age- and gender-specific associations between sleep duration and incident hypertension in a Chinese population: the Kailuan study. Journal of human hypertension 30, 503–507, https://doi.org/10.1038/jhh.2015.118 (2016).

    CAS  Article  PubMed  Google Scholar 

  38. 38.

    Zhang, Q. et al. Ideal cardiovascular health metrics and the risks of ischemic and intracerebral hemorrhagic stroke. Stroke 44, 2451–2456, https://doi.org/10.1161/STROKEAHA.113.678839 (2013).

    Article  PubMed  Google Scholar 

  39. 39.

    Zhu, J. et al. 2016 update of the Chinese Guideline on the Prevention and Treatment of Dyslipidemia in Adults. Chinese Circulation Journal 31, 937–953 (2016).

    Google Scholar 

  40. 40.

    Cai, J. et al. Evaluation of the Efficiency of the Reticulocyte Hemoglobin Content on Diagnosis for Iron Deficiency Anemia in Chinese Adults. Nutrients 9, https://doi.org/10.3390/nu9050450 (2017).

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Acknowledgements

We thank the project development and management teams at the Kailuan Group.

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X.W. and S.W. conceived and designed this study, X.L. directed dataanalysis, Q.S. and X.L. writing the paper. W.H., X.H., J.G. and X.Z. prepared the database and reviewed thepaper. X.W. and S.W. conducted the quality assurance, reviewed and edited the paper. All authorsreviewed the manuscript.

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Correspondence to Xizhu Wang or Shouling Wu.

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Liu, X., Song, Q., Hu, W. et al. Night Sleep Duration and Risk of Incident Anemia in a Chinese Population: A Prospective Cohort Study. Sci Rep 8, 3975 (2018). https://doi.org/10.1038/s41598-018-22407-5

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