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Research Article

Association of change in total cholesterol level with bloodshed: A population-based study

• Su-Min Jeong,
• Seulggie Choi,
• Kyuwoong Kim,
• Sung-Min Kim,
• Gyeongsil Lee,
• Joung Sik Son,
• Jae-Moon Yun,
• Sang Min Park

x

• Published: Apr 19, 2018
• https://doi.org/x.1371/journal.pone.0196030

Figures

Abstruse

Background

Hypercholesterolemia is a well-established risk factor for coronary heart illness, simply the clan between cholesterol level alter and mortality is non fully understood. We aimed to investigate the clan of 2 yr (2002–2003 to 2004–2005) change in cholesterol with all-cause and cause-specific mortality in a population-based cohort study.

Methods and findings

The study population consisted of 269,391 participants aged more than twoscore years who were costless of myocardial infarction, stroke and cancer using the Korean National Health Insurance Service—National Health Screening Cohort. Cholesterol levels were classified into 1st, 2nd and third tertiles during each of the first and second health examinations, respectively. The participants were followed-up for all-crusade and cause-specific bloodshed from 1 January 2006 to 31 December 2013. Compared to participants who stayed within the 2nd tertile group for cholesterol during both the first and second examinations, participants who became or maintained cholesterol levels to the 1st tertile during the second exam had increased gamble of all-cause mortality [adjusted hazard ratio (aHR) with 95% conviction interval (95% CI) = ane.28 (1.18–1.38) in 1st/1st, 1.xvi (1.07–1.26) in 2nd/1st and 1.47 (1.32–1.64) in tertiary/1st tertile levels, respectively]. In addition, increased or persistent high cholesterol levels to the tertiary tertile was associated with elevated risk for all-cause mortality [aHR (95% CI) = 1.10 (1.01–1.20) in 1st/2d, ane.xvi(1.03–1.31) in 1st/tertiary and i.15(1.05–i.25) in third/tertiary tertile levels].

Conclusions

Changes in cholesterol levels in either management to low cholesterol or persistently low cholesterol levels were associated with higher risk of mortality. Particularly, spontaneous decline in cholesterol levels may be a marker for worsening health conditions.

Commendation: Jeong S-M, Choi S, Kim K, Kim South-Thousand, Lee G, Son JS, et al. (2018) Clan of change in total cholesterol level with bloodshed: A population-based study. PLoS 1 13(iv): e0196030. https://doi.org/10.1371/periodical.pone.0196030

Editor: Katriina Aalto-Setala, University of Tampere, FINLAND

Received: November 2, 2017; Accepted: April 5, 2018; Published: April 19, 2018

Copyright: © 2018 Jeong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Information Availability: Data are from the Korea National Health Insurance service (NHIS). Interested researchers tin request access to the data from NHIS. The detailed data for data access of NHIS could be obtained from the NHIS website (world wide web.nhis.or.kr).

Funding: Seulggie Choi and Kyuwoong Kim received a scholarship from the BK21‐plus instruction programme provided past the National Research Foundation of Korea, outside of the submitted work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Hypercholesterolemia is a well-established take a chance factor for coronary heart affliction (CHD) [one, 2], indicating that cholesterol lowering therapy would exist beneficial for prevention of CHD [3]. However, previous studies on the association betwixt cholesterol levels and mortality have shown inconsistent results that vary according to historic period, cause of decease, and sex [4–eight]. Previous findings bespeak that that low cholesterol was associated with loftier mortality [6, 7]. For example, among the elderly, frailty or poor health status may have contributed to the increased gamble of decease among those with low cholesterol levels [9]. In addition, other previous studies take revealed a U-shaped relationship between cholesterol and mortality [10, 11]. Interestingly, the increased take chances of death amid those with low cholesterol was due to non-vascular disease, such as liver disease [12] or cancer [13], which is in contrast to the high contribution of cardiovascular illness (CVD) related mortality among those with loftier cholesterol levels [eleven].

A number of studies investigated the clan between the change in cholesterol levels and mortality [5, 8]. A study from the Honolulu Heart Program revealed a 30% increase in bloodshed amongst people who had decreased levels of cholesterol [5]. The almost common causes of deaths amid those with declines in cholesterol levels were malignancies of the hematopoietic organization, esophagus, and prostate and not-cancerous liver disease. Yet, this report was express to a relatively pocket-sized number of male subjects (n = 5,941). In a study using the Framingham data, those with decreasing cholesterol levels were associated with increased take chances of all-crusade and CVD mortality [8]. Spontaneous turn down in cholesterol of xiv mg/dL during xiv-years was associated with 11% increased risk of bloodshed, compared to those with stable or increased cholesterol levels. However, previous studies have been mainly performed in the Western population and the number of report population is relatively pocket-sized.

In this study, we aimed to elucidate the association between modify in cholesterol and all-crusade mortality too as crusade-specific mortality using a nationally representative cohort.

Methods

Data source

National Wellness Insurance Service (NHIS) in the Commonwealth of Korea covers approximately 97% of the Korean population and provides biennial health screening examinations called the National Health Screening Plan (NHSP) to all enrollees above 40 years quondam [fourteen]. The NHSP offers screening tests for several weather condition, including anemia, liver disease and kidney affliction as well equally cardiovascular risk factors including blood pressure, lipid profile and fasting glucose. The National Health Insurance Service—National Health Screening Accomplice (NHIS-HEALS) database is composed of demographic factors, results from the NHSP, utilization of medical facilities at outpatient and inpatient settings with the International Classification of Diseases, 10th revision (ICD-10) codes and the date and crusade of decease from the Korea National Statistical Office. In addition, NHIS-HEALS contains demographic information such every bit age, gender, health insurance premium, and disability. The NHIS database has been widely used in multiple epidemiological studies [15, 16] and its validity is described in detail elsewhere [17].

Study population

The NHIS-HEALS database consists of about 510,000 randomly selected participants amidst the general population over 40 years ages who underwent health screening examinations in 2002 or 2003 and followed-upward until 31 December 2013. We identified 334,058 participants who had cholesterol values in the first (2002–2003) and second (2004–2005) wellness examination periods. We excluded those who passed abroad (n = 1,032) before the index date of one Jan 2006. In addition, we also excluded those who were diagnosed with myocardial infarction (MI) or stroke (n = 38,748), reported a history of MI, stroke or cancer before the index date (north = 4,058) or had missing data on laboratory results and lifestyle variables (n = 12,689). Furthermore, nosotros excluded statin users (n = fifteen,140), who were divers as those with more than than 30 cumulative defined daily dose (cDDD) of statins during 2002 to 2005 to investigate the association between spontaneous change of cholesterol levels and mortality, since we assumed that decreased cholesterol with statins or without statins may exist differently associated with bloodshed [18]. Therefore, final study population consisted of 262,391 participants (Fig 1).

This study was approved by Seoul National University Hospital's institutional review lath (IRB number: 1703-039-863), and consent from individual patients was waived as NHIS-HEALS was anonymized according to strict confidentiality guidelines. This study was approved by NHIS (NHIS-2017-2-456)

Alter in cholesterol level

Total cholesterol levels were measured at each wellness examination later fasting for at least viii hours. Baseline (2002–2003) cholesterol levels were classified into 1st (< 182 mg/dL), 2nd (182–212 mg/dL) and third tertiles (≥ 212 mg/dL). In addition, follow-up (2004–2005) cholesterol levels were classified into 1st tertile (< 181 mg/dL), 2nd tertile (181–210 mg/dL) and 3rd tertile (≥ 211 mg/dL). Participants who stayed in the 2nd tertile group for both the initial and 2d health examination periods were considered the reference grouping.

Outcome assessment

Deaths from i January 2006 to 31 Dec 2013 were determined by using death certificates from the National Statistical Office of Korea. The causes of deaths were categorized into CVD (ICD-10 codes I00-I99) and cancer (ICD-x C00-C97) according to the ICD-10 codes.

Covariates

Body mass index (BMI) was calculated by weight (kg) divided by height (grand) squared and grouped into < 25 kg/m² and ≥ 25 kg/thousand² according to Asian-Pacific cut-off points [nineteen]. Smoking status was classified into never, former and current smokers. Alcohol consumption was divided into none or at least i drink per week. Insurance premium divided into quintiles was used to classify household income status. The presence of inability was based on National Registration for Disability. Comorbidities were summarized by the Charlson comorbidity index (CCI) [xx] using ICD-10 codes from 2002 to 2005. History of hypertension and diabetes were defined as having reported being previously diagnosed with or taking anti-hypertensive or anti-diabetic medications.

Statistical analyses

Analysis of variance (ANOVA) for continuous variables and Chi-squared test for categorical variables were used to compare baseline characteristics according to baseline cholesterol levels. Continuous variables are expressed as mean [standard deviation (SD)]. We used the Cox-regression hazard model to evaluate the risk of mortality according to the change in cholesterol levels. We adjusted for age and sex activity in model i. In model two, we additionally adjusted life style variables (BMI, smoking status and drinking condition), socioeconomic factors (household income and disability) and medical conditions (CCI, history of hypertension and diabetes, systolic blood pressure and fasting glucose level). We performed sensitivity analysis by excluding deaths that occurred within the first two years from the index date to account for the possibility of opposite-causality. All data processing and statistical analyses were carried out using SAS 9.four (SAS Establish, Cary, NC) and STATA 14.i (Stata Corp, College Station, TX, United states), respectively.

Results

Baseline characteristics

The hateful age of the full population was 54 (SD 8.eight) years and were composed of 153,759 (58.6%) male subjects (Table i). The mean cholesterol level at baseline was 198.0 (SD 36.1) mg/dL in 2002–2003 and 196.half dozen (SD 35.two) mg/dL in 2004–2005 with 0.57 (Standard error, 0.001) correlation coefficient for cholesterol. Subjects in the baseline 3rd tertile cholesterol levels were more probable to be old, female person, obese (≥ 25 kg/one thousand²) and to accept college systolic claret pressure and fasting blood glucose compared to those in the 1st and 2nd tertiles for cholesterol.

Alter in cholesterol and mortality

The mean follow-up period was 8.0 years and the mean time to expiry was 4.seven years. At that place was a U-shaped relationship between baseline cholesterol levels and all-cause mortality [adjusted HR (aHR) = 1.13; 95% confidence interval (CI) = one.06–1.20 in 1st tertile, aHR = 1.15; 95% CI = 1.08–1.22 in 3rd tertile], compared to 2nd tertile at baseline (S1 Table) (S1 Fig).

Subjects with persistent 1st tertile cholesterol levels and increasing cholesterol levels from the 1st tertile to the 2nd and tertiary tertile levels during the follow-up flow were associated with increased risk of all-cause bloodshed [aHR (95% CI) = 1.28 (1.18–1.38), 1.x (1.01–1.20) and 1.16 (1.03–one.31), respectively] compared to those with persistent 2nd tertile levels (Table ii). Subjects with decreasing cholesterol levels from tertiary tertile levels to 1st and 2d and persistent 3rd tertile levels were associated with increased risk of all-cause mortality [aHR (95% CI) = one.47 (one.32–1.64), 1.15 (i.05–1.26) and 1.15 (one.05–1.25), respectively] compared to those with persistent 2d tertile levels. Decreasing cholesterol from 2nd tertile to 1st tertile levels was associated with increased risk of all-crusade bloodshed [aHR (95% CI) = 1.sixteen (1.07–1.26)]. These associations were prominent in groups less than 65 years old or men (S2 Tabular array). Among statin users (n = xv,140), those with persistent 1st tertile cholesterol levels were associated with high all-cause mortality. (S3 Tabular array).

The risk of CVD mortality was elevated in those with persistent 3rd tertile levels and increasing cholesterol levels from 1st tertile to 3rd tertile levels [aHR (95% CI) = 1.30 (1.05–1.61) and ane.47 (1.10–1.98), respectively]. Subjects with persistent 1st tertile levels and decreasing cholesterol levels from 3rd tertile to 1st tertile levels were associated with high CVD bloodshed risk [aHR (95% CI) 1.37 (i.12–1.67) and 1.43 (1.08–1.89), respectively].

Increased risk of cancer mortality was observed those in persistent 1st tertile levels and decreasing cholesterol levels from third tertile to 1st tertile levels [aHR (95% CI) = 1.34 (1.19–1.l) and 1.26 (1.06–1.50)].

Sensitivity analysis

In the sensitivity analysis of excluding deaths within the first 2 years of follow-up (n = 2,069), increased risks of all-crusade mortality, CVD mortality and cancer bloodshed were consistently observed in subjects with persistent 1st tertile levels [aHR (95% CI) = 1.27 (1.17–ane.39), 1.36 (1.ten–one.69) and 1.35 (i.19–1.53)] compared to those with persistent 2nd tertile levels (Table 3). Moreover, decreasing cholesterol levels from 2d and 3rd tertile to 1st tertile levels were significantly associated with high all-cause mortality risk. On the other manus, increasing cholesterol levels from 1st tertile to 2d and 3rd tertile levels were associated with high all-crusade mortality [aHR (95% CI) = 1.xi (1.01–ane.22) and 1.xv (1.01–1.31)].

Give-and-take

Nosotros demonstrated that subjects with both decreasing cholesterol levels and persistently low cholesterol levels were significantly associated with an increased risk of all-cause bloodshed compared to those remaining at a stable middle cholesterol level. In add-on, subjects with increasing cholesterol levels and persistently high cholesterol were associated with high all-cause mortality risk. CVD mortality according to modify in cholesterol showed similar patterns with all-crusade mortality. On the other mitt, cancer mortality risk was elevated in those with persistently depression and decreasing cholesterol levels.

Contempo studies accept plant an inverse association between cholesterol level and mortality [9, 21–24]. However, it is uncertain whether low cholesterol level contributes to increased risk of mortality or is rather a surrogate marker for other serious illnesses. A longitudinal study in Denmark showed that severe diseases that could lower total cholesterol might increase mortality [21]. In addition, high cholesterol was associated with lower not-CVD bloodshed such as cancer mortality in subjects with age ≥ 65 years [23]. A study in patients with end phase renal disease suggested that systemic inflammation and malnutrition may explain this changed association through cytokines related to acute or chronic inflammation which contribute low cholesterol levels and higher mortality [25].

Pass up in cholesterol levels from high to depression tertile within 2 years might be related to atmospheric condition that can alter cholesterol homeostasis including uptake, synthesis and storage. Furthermore, refuse in cholesterol levels consequently can lead increased susceptibility to fatal diseases [9] past dysfunction in cellular functions [26]. In our study, cancer bloodshed was higher in those with sustained low tertile of cholesterol levels or steep reject (from 3rd to1st tertile levels) within 2 years. Increased lipid uptake in cancer cells may account for this steep decline. Cancer cells take an increasing requirement for lipids in gild to reduce the fluidity of cell membranes and increment chemotherapy resistance by saturating the cell membrane with lipid, thereby increasing their chances of survival [27].

Besides cancer bloodshed, low full cholesterol was associated with high CVD bloodshed in prospective cohort studies [10, 28, 29]. This study also showed that low cholesterol levels as well equally high cholesterol levels were associated with loftier CVD mortality. We could not verify the exact reasons for this result, but many previous studies have suggested that 1) this is due to take a chance findings or reverse epidemiology [ten]; 2) the effects of malnutrition, a risk cistron for non-ischemic heart illness [28]; 3) subfractions, peculiarly for low levels of high density lipoprotein-cholesterol (HDL-C) [29]. In patients with acute MI, significant decreases in full cholesterol, low density lipoprotein-cholesterol (LDL-C), and HDL-C levels were reported, although the causes were not clear [thirty].

At that place are several limitations in our study that demand to be considered. First, we could not evaluate lipoprotein subfractions such as HDL-C and LDL-C, due the lack of information [22]. Second, possibility of day-to mean solar day variability due to laboratory error or biologic variability may exist, as we used single cholesterol measurement. Repeated measurement would exist more accurate to allocate the subjects [31]. Furthermore, while at that place might be possibility of increasing or decreasing trends of cholesterol levels due to life style change in Korean population, such equally change of dietary patterns or increasing trends of obesity, we used classification of tertiles for first and second examination, separately and there was no substantial change in average cholesterol from 1998 to 2010 in Korean [32]. 3rd, we cannot dominion out the possibility of opposite causality. Although we have excluded deaths within first ii years from index appointment to resolve reverse causality, there might be other predisposing conditions that can cause steep refuse of cholesterol in short periods. Quaternary, the changes in cholesterol levels may reflect a 'regression to the mean' rather than any biologic upshot [33].

In determination, decreasing cholesterol levels or persistently low cholesterol levels were associated with college gamble of all-crusade, cancer and CVD mortality. In addition, increasing cholesterol levels or persistently loftier cholesterol levels was as well associated with loftier CVD mortality take chances. This suggests that decreased cholesterol and low cholesterol levels may be an indicator for poor wellness condition. The clinical implication of this report is that individuals with spontaneously decreased cholesterol or persistently low cholesterol levels are at increased adventure of mortality and may require careful attending for signs of deterioration of health [eight].

Supporting information

S1 Fig. The association between baseline cholesterol levels and bloodshed.

(a) All-cause mortality (b) Cardiovascular disease bloodshed and (C) Cancer bloodshed according to the tertiles of baseline cholesterol showed U-shaped association.

https://doi.org/x.1371/journal.pone.0196030.s004

(TIF)

References

1. i. Menotti A, Lanti 1000, Kromhout D, Kafatos A, Nedeljkovic South, Nissinen A. Curt and long term association of a single serum cholesterol measurement in 2d-aged men in prediction of fatal coronary and other cardiovascular events: a cross-cultural comparison through Europe. European journal of epidemiology. 2005;20(seven):597–604. Epub 2005/08/27. pmid:16119433.
   • View Commodity
   • PubMed/NCBI
   • Google Scholar
2. 2. Nagasawa SY, Okamura T, Iso H, Tamakoshi A, Yamada Grand, Watanabe M, et al. Relation between serum full cholesterol level and cardiovascular disease stratified past sex and historic period grouping: a pooled analysis of 65 594 individuals from 10 cohort studies in Nippon. J Am Centre Assoc. 2012;i(5):e001974. pmid:23316288.
   • View Article
   • PubMed/NCBI
   • Google Scholar
3. three. Chou R, Dana T, Blazina I, Daeges M, Jeanne TL. Statins for Prevention of Cardiovascular Disease in Adults: Evidence Study and Systematic Review for the US Preventive Services Job Force. JAMA. 2016;316(19):2008–24. pmid:27838722.
   • View Article
   • PubMed/NCBI
   • Google Scholar
4. 4. Sherwin RW, Wentworth DN, Cutler JA, Hulley SB, Kuller LH, Stamler J. Serum cholesterol levels and cancer mortality in 361662 men screened for the multiple take chances cistron intervention trial. JAMA. 1987;257(7):943–8. pmid:3806876
   • View Commodity
   • PubMed/NCBI
   • Google Scholar
5. 5. Iribarren C, Reed DM, Chen R, Yano K, Dwyer JH. 1st Serum Cholesterol and Mortality. Circulation. 1995;92:2396–403.
   • View Article
   • Google Scholar
6. half dozen. Tuikkala P, Hartikainen S, Korhonen MJ, Lavikainen P, Kettunen R, Sulkava R, et al. Serum total cholesterol levels and all-cause mortality in a home-domicile elderly population: a six-year follow-up. Scandinavian Journal of Primary Health Care. 2010;28(2):121–7. pmid:20470020
   • View Article
   • PubMed/NCBI
   • Google Scholar
7. 7. Weverling-Rijnsburger AWE, Blauw GJ, Lagaay AM, Knock DL, Meinders AE, Westendorp RGJ. Total cholesterol and risk of mortality in the oldest sometime. The Lancet. 1997;350(9085):1119–23.
   • View Article
   • Google Scholar
8. 8. Anderson KM, Castelli WP, Levy D. Cholesterol and mortality. 30 years of follow-up from the Framingham study. Jama. 1987;257(xvi):2176–80. Epub 1987/04/24. pmid:3560398.
   • View Commodity
   • PubMed/NCBI
   • Google Scholar
9. 9. Ravnskov U, Diamond DM, Hama R, Hamazaki T, Hammarskjold B, Hynes N, et al. Lack of an clan or an inverse association between 1st-density-lipoprotein cholesterol and mortality in the elderly: a systematic review. BMJ Open up. 2016;half dozen(six):e010401. pmid:27292972.
   • View Article
   • PubMed/NCBI
   • Google Scholar
10. 10. Bae JM, Yang YJ, Li ZM, Ahn YO. 1st cholesterol is associated with bloodshed from cardiovascular diseases: a dynamic cohort study in Korean adults. J Korean Med Sci. 2012;27(1):58–63.
    • View Article
    • Google Scholar
11. xi. Jacobs D, Blackburn H, Higgins M, Reed D, Iso H, McMillan G, et al. Report of the Briefing on 1st Blood Cholesterol: Mortality Associations. Circulation. 1992;86(three):1046. pmid:1355411
    • View Article
    • PubMed/NCBI
    • Google Scholar
12. 12. Ghadir MR, Riahin AA, Havaspour A, Nooranipour M, Habibinejad AA. The relationship between lipid profile and severity of liver damage in cirrhotic patients. Hepatitis Monthly. 2010;10(4):285–8. pmid:22312394
    • View Article
    • PubMed/NCBI
    • Google Scholar
13. 13. Sherwin RW, Wentworth DN, Cutler JA, Hulley SB, Kuller LH, Stamler J. Serum cholesterol levels and cancer mortality in 361,662 men screened for the Multiple Risk Factor Intervention Trial. Jama. 1987;257(7):943–8. Epub 1987/02/twenty. pmid:3806876.
    • View Article
    • PubMed/NCBI
    • Google Scholar
14. fourteen. Lee Due west-C, Lee S-Y. National Wellness Screening Program of Korea. J Korean Med Assoc. 2010;53(5):363–70.
    • View Article
    • Google Scholar
15. 15. Noh J. The Diabetes Epidemic in Korea. Endocrinol Metab (Seoul). 2016;31(three):349–53. pmid:27586447.
    • View Article
    • PubMed/NCBI
    • Google Scholar
16. 16. Lim DH, Kim YJ, Kim SO, Hong Due south, Lee CK, Yoo B, et al. The adventure of canker zoster in patients with ankylosing spondylitis: Analysis of the Korean National Health Insurance Service—Sample cohort database. Mod rheumatology. 2017:1–vi. Epub 2017/05/27. pmid:28548546.
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
17. 17. Cheol Seong S, Kim YY, Khang YH, Heon Park J, Kang HJ, Lee H, et al. Information Resource Profile: The National Health Data Database of the National Health Insurance Service in South Korea. Int J Epidemiol. 2016. pmid:27794523.
    • View Article
    • PubMed/NCBI
    • Google Scholar
18. eighteen. Collins R, Reith C, Emberson J, Armitage J, Baigent C, Blackwell 50, et al. Estimation of the evidence for the efficacy and condom of statin therapy. The Lancet. 388(10059):2532–61.
    • View Article
    • Google Scholar
19. 19. Appropriate trunk-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (London, England). 2004;363(9403):157–63. Epub 2004/01/17. pmid:14726171.
    • View Article
    • PubMed/NCBI
    • Google Scholar
20. twenty. Sundararajan Five, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity alphabetize predicted in-hospital mortality. Periodical of clinical epidemiology. 2004;57(12):1288–94. Epub 2004/12/25. pmid:15617955.
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
21. 21. Bathum Fifty, Depont Christensen R, Engers Pedersen Fifty, Lyngsie Pedersen P, Larsen J, Nexoe J. Association of lipoprotein levels with mortality in subjects aged 50 + without previous diabetes or cardiovascular illness: a population-based register written report. Scand J Prim Wellness Care. 2013;31(3):172–80. pmid:23941088.
    • View Article
    • PubMed/NCBI
    • Google Scholar
22. 22. Ghasemzadeh Z, Abdi H, Asgari S, Tohidi M, Khalili D, Valizadeh M, et al. Divergent pathway of lipid contour components for cardiovascular disease and bloodshed events: Results of over a decade follow-upwardly among Iranian population. Nutr Metab (Lond). 2016;13:43. pmid:27346994.
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
23. 23. Newson RS, Felix JF, Heeringa J, Hofman A, Witteman JC, Tiemeier H. Association betwixt serum cholesterol and noncardiovascular mortality in older age. J Am Geriatr Soc. 2011;59(10):1779–85. pmid:22091490.
    • View Article
    • PubMed/NCBI
    • Google Scholar
24. 24. Brescianini Southward, Maggi S, Farchi Grand, Mariotti Due south, Di Carlo A, Baldereschi Thou, et al. 1st total cholesterol and increased take a chance of dying: are 1st levels clinical warning signs in the elderly? Results from the Italian Longitudinal Written report on Aging. J Am Geriatr Soc. 2003;51(7):991–6. Epub 2003/07/02.
    • View Article
    • Google Scholar
25. 25. Liu Y, Coresh J, Eustace JA, et al. Clan between cholesterol level and mortality in dialysis patients: Role of inflammation and malnutrition. JAMA. 2004;291(4):451–9. pmid:14747502
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
26. 26. Maxfield FR, Tabas I. Role of cholesterol and lipid system in disease. Nature. 2005;438(7068):612–21. pmid:16319881.
    • View Article
    • PubMed/NCBI
    • Google Scholar
27. 27. Beloribi-Djefaflia S, Vasseur S, Guillaumond F. Lipid metabolic reprogramming in cancer cells. Oncogenesis. 2016;5:e189. pmid:26807644.
    • View Article
    • PubMed/NCBI
    • Google Scholar
28. 28. Nago N, Ishikawa S, Goto T, Kayaba K. 1st Cholesterol is Associated With Mortality From Stroke, Center Disease, and Cancer: The Jichi Medical School Cohort Study. Journal of Epidemiology. 2011;21(ane):67–74.
    • View Article
    • Google Scholar
29. 29. Kronmal RA, Kosinski Equally, Mock MB. The relationship between cholesterol level and myocardial infarction or bloodshed take chances in patients with coronary artery disease. A report from the Coronary Artery Surgery Report (CASS) registry. Annals of epidemiology. 1992;2(1–2):129–36. Epub 1992/01/01. pmid:1342254.
    • View Article
    • PubMed/NCBI
    • Google Scholar
30. xxx. Khan HA, Alhomida AS, Sobki SH. Lipid profile of patients with acute myocardial infarction and its correlation with systemic inflammation. Biomark Insights. 2013;eight:1–7. pmid:23400110.
    • View Article
    • PubMed/NCBI
    • Google Scholar
31. 31. Bookstein Fifty, Gidding SS, Donovan M, Smith FA. Day-to-mean solar day variability of serum cholesterol, triglyceride, and high-density lipoprotein cholesterol levels. Impact on the assessment of risk co-ordinate to the National Cholesterol Education Program guidelines. Archives of internal medicine. 1990;150(viii):1653–7. Epub 1990/08/01. pmid:2383160.
    • View Article
    • PubMed/NCBI
    • Google Scholar
32. 32. Roh East, Ko S-H, Kwon H-Due south, Kim NH, Kim JH, Kim CS, et al. Prevalence and Management of Dyslipidemia in Korea: Korea National Health and Nutrition Examination Survey during 1998 to 2010. Diabetes & Metabolism Journal. 2013;37(six):433–49. pmid:24404515
    • View Article
    • PubMed/NCBI
    • Google Scholar
33. 33. Barnett AG, van der Pols JC, Dobson AJ. Regression to the mean: what it is and how to deal with it. International Journal of Epidemiology. 2005;34(1):215–20. pmid:15333621
    • View Article
    • PubMed/NCBI
    • Google Scholar

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