The Effects of Nutritional Supplements and Dietary Interventions on All-Cause Mortality and Cardiovascular Outcomes

The Effects of Nutritional Supplements and Dietary Interventions on All-Cause Mortality and Cardiovascular Outcomes

By Aly Becraft, MS and Kevin C Maki, PhD

 

Despite scientific uncertainty surrounding the benefits of dietary supplements, many U.S. adults use them, along with various dietary interventions, with the belief that they will improve their overall health (1).  Khan et al. (2) recently published a systematic review to assess the effect of various nutritional supplements and dietary interventions on cardiovascular outcomes.  The criteria for inclusion were randomized controlled trials (RCTs) and meta-analyses of RCTs that assessed the effect of nutritional supplements (vitamins, minerals, dietary supplements) or dietary interventions on all-cause mortality and cardiovascular outcomes in adults and written in English.  The main outcome of interest was all-cause mortality and secondary outcomes included cardiovascular mortality, myocardial infarction (MI), stroke, and coronary heart disease (CHD).  From these criteria, 942 articles were identified, and after initial title and abstract screening, 140 full-text articles remained to be reviewed for eligibility.  Ultimately, 9 systematic reviews and 4 new RCTs were included, comprising a total of 105 meta-analyses, 24 interventions (16 types of nutritional supplements and 8 dietary interventions), 277 RCTs and 922,129 participants.  A list of these interventions is shown in Table 1 and the significant findings from the present analysis are summarized in Table 2.

 

Table 1. List of interventions analyzed in Khan et al. (2)

Nutritional Supplements

Dietary Interventions

Antioxidants

Mediterranean diet

Vitamin B6

Reduced dietary fat

Vitamin B3 or niacin

Modified dietary fat

Vitamin B complex

Reduced saturated fat

Carotene

Reduced salt (hypertensive)

Selenium

Reduced salt (normotensive)

Vitamin E

Increased omega-3 α-linolenic acid

Vitamin A

Increased omega-6 PUFA

Vitamin C

 

Vitamin D

 

Calcium and calcium plus vitamin D

 

Folic acid

 

Iron

 

Omega-3 long-chain PUFA

 

Multivitamins

 

Abbreviation: PUFA, polyunsaturated fatty acids

 

 

 

Table 2. Summary of statistically significant findings from Khan et al. (2)

 

Intervention

RR (95% CI)

P-value

Certainty

All-cause mortality

Reduced salt intake in normotensive patients

0.90 (0.85 to 0.95)

0.01

Moderate

Cardiovascular mortality

Reduced salt intake in hypertensive patients

0.67 (0.46 to 0.99)

0.04

Moderate

MI

Omega-3 LC-PUFA

0.92 (0.85 to 0.99)

0.03

Low

CHD

Omega-3 LC-PUFA

0.93 (0.89 to 0.98)

0.01

Low

Stroke

Folic acid

0.80 (0.67 to 0.96)

0.02

Low

Stroke

Calcium plus vitamin D

1.17 (1.05 to 1.30)

0.01

Moderate

Abbreviations: CHD, coronary heart disease; CI, confidence interval; LC-PUFA, long-chain polyunsaturated fatty acids; MI, myocardial infarction; RR, risk ratio

 

Comment.  Overall, the researchers found little evidence for nutritional supplements or dietary interventions to significantly reduce risk for all-cause mortality or cardiovascular outcomes, with some exceptions as outlined in Table 2.  Interventions associated with lower risks included reduced salt intake and lower total (normotensives) or cardiovascular mortality (hypertensives), omega-3 fatty acid supplementation and reduced risks for CHD and MI, and folic acid supplementation associated with lower risk for stroke. 

 

Of note, calcium plus vitamin D intake was associated with increased risk for stroke.  This finding could be related to hypercalcemia-mediated vascular calcification and/or effects on coagulation, although additional research is needed to more firmly establish causality and mechanistic explanations (3-5).

 

Certainty of evidence from this systematic review was low for most interventions due to low precision of estimates, qualitative and quantitative heterogeneity, and publication bias.  Regardless, these findings can be a useful resource for healthcare professionals who would like to recommend evidence-based nutritional interventions and provide a basis for future studies to explore the gaps in the currently available evidence base. 

 

References:

  1. Gahche JJ, Bailey RL, Potischman N, et al. Dietary supplement use was very high among older adults in the United States in 2011-2014. J Nutr. 2017;147:1968-76.
  2. Khan SU, Khan MU, Riaz H, et al. Effects of nutritional supplements and dietary interventions on cardiovascular outcomes: an umbrella review and evidence map. Ann Intern. 2019;E-pub ahead of print
  3. Chin K, Appel LJ, Michos ED. Vitamin D, calcium, and cardiovascular disease: A”D”vantageous or “D”etrimental? An era of uncertainty. Curr Atheroscler Rep. 2017;19(1):5.
  4. Anderson JJ, Kruszka B, Delaney JA, et al. Calcium intake from diet and supplements and the risk of coronary artery calcification and its progression among older adults: 10-year follow-up of the Multi-Ethnic Study of Atherosclerosis (MESA). J Am Heart Assoc. 2016;5(10).
  5. Heaney RP, Kopecky S, Maki KC, Hathcock J, MacKay D, Wallace TC. A review of calcium supplements and cardiovascular disease risk. Adv Nutr. 2012;3:763-771.

 

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Serum Markers of Oxidative Stress to Assess Mortality Risk in Patients with Type 2 Diabetes

Serum Markers of Oxidative Stress to Assess Mortality Risk in Patients with Type 2 Diabetes

By Aly Becraft, MS and Kevin C Maki, PhD

Hyperglycemia is thought to result in increased reactive oxygen species (ROS) production and weakened antioxidant capacity,1 which can make patients with type 2 diabetes (T2D) susceptible to elevated oxidative stress. Current research relating diabetes complications and oxidative stress is lacking because ROS are difficult to measure directly;2 however, methods that indirectly quantify oxidative stress by measuring derivatives of reactive oxygen metabolites (d-ROMs) as a proxy for ROS production3 and total thiol levels (TTLs) as a proxy for reduction-oxidation (redox) status of blood4 are also available.

Xuan et al. recently published pooled results from two cohort studies in a meta-analysis to investigate the association of these oxidative stress biomarkers with incident major cardiovascular events, total cancer incidence, and cause-specific and all-cause mortality in patients with T2D.5 Diabetes sub-cohorts of the ESTHER and DIANA studies, conducted in Germany, were included. In the ongoing ESTHER cohort, to date, patient follow up visits have been conducted after 2, 5, 8, 11 and 14 years. Follow up in the DIANA study occurred after 4 and 7 years. For this meta-analysis, the 8-year follow-up data from the ESTHER cohort was used as baseline and the 11-year follow-up for repeated biomarker measurements. For the DIANA study, baseline and the 4-year follow-up data were used. Biomarker measurements were conducted on 1029 patients from the ESTHER cohort, of which 720 had repeated measurements. In the DIANA study, measurements of both biomarkers were performed for 1096 baseline study participants, and repeated measurement of d-ROMs was done for 738 participants.

In both cohorts, significantly increased d-ROMs levels were observed in females, current smokers, patients with T2D who had body mass index (BMI) ≥40 kg/m2, those not taking any antidiabetic medication, with insulin therapy, without lipid-lowering medication, with high total cholesterol levels, or with high C-reactive protein (CRP) levels. In addition, significantly lower TTLs in both cohorts were observed in females, alcohol abstainers, and patients with T2DM with BMI ≥40 kg/m2, without any antidiabetic medication, with insulin therapy, with antihypertensive therapy, with anticoagulant medication, with high CRP levels, with estimated glomerular filtration rate (eGFR), or with a history of myocardial infarction, heart failure, or hypertension. Both biomarkers were significantly associated with all-cause mortality in each of the cohorts; however, the associations with cancer mortality and major cardiovascular events were not statistically significant. Adjustment for disease and CRP concentration attenuated observed effect estimates. Subgroup analysis of all-cause mortality demonstrated strong associations with d-ROM levels among males and among patients with T2D with glycated hemoglobin <7%, age <70 years, BMI <30 kg/m2, and a history of coronary heart disease.

 

The results of this study support the notion that an imbalanced redox system may play a role in increasing premature mortality in patients with T2D. Other evidence supports such a role for oxidative stress,6-8 but it remains to be determined if oxidative stress is also involved in the development of cardiovascular disease and cancer in patients with T2D. Although this study was observational, and thus, the possibility of residual confounding cannot be disregarded, the results demonstrate the potential need for oxidative stress interventions in patients with T2D and illustrate the usefulness of using d-ROMs and TTLs as biomarkers to identify individuals with T2D who may be at increased risk for premature death.

 

References:

 

  1. Dincer A, Onal S, Timur S, et al. Differentially displayed proteins as a tool for the development of type 2 diabetes. Ann Clin Biochem. 2009;46:306–310.

 

  1. Stephens JW, Khanolkar MP, Bain SC. The biological relevance and measurement of plasma markers of oxidative stress in diabetes and cardiovascular disease. Atherosclerosis. 2009;202:321–329.

 

  1. Kotani K, Sakane N. C-reactive protein and reactive oxygen metabolites in subjects with metabolic syndrome. J Int Med Res. 2012;40:1074–1081.

 

  1. Marrocco I, Altieri F, Peluso I. Measurement and clinical significance of biomarkers of oxidative stress in humans. Oxid Med Cell Longev. 2017;2017:6501046.

 

  1. Xuan Y, Gào X, Anusruti A, Holleczek B, Jansen EH, Muhlack DC, Brenner H, Schöttker B. Association of serum markers of oxidative stress with incident major cardiovascular events, cancer incidence and all-Cause mortality in type 2 diabetes patients: pooled results from two cohort studies. Diabetes Care. 2019;Epub ahead of print.

 

  1. Broedbaek K, Siersma V, Henriksen T, et al. Urinary markers of nucleic acid oxidation and long-term mortality of newly diagnosed type 2 diabetic patients. Diabetes Care. 2011;34:2594– 2596.

 

  1. Kjaer LK, Oellgaard J, Henriksen T, et al. Indicator of RNA oxidation in urine for the prediction of mortality in patients with type 2 diabetes and microalbuminuria: a post-hoc analysis of the Steno-2 trial. Free Radic Biol Med. 2018;129:247–255.

 

  1. Kjær LK, Cejvanovic V, Henriksen T, et al. Cardiovascular and all-cause mortality risk associated with urinary excretion of 8-oxoGuo, a biomarker for RNA oxidation, in patients with type 2 diabetes: a prospective cohort study. Diabetes Care. 2017;40:1771–1778.

 

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Associations of Dietary Cholesterol and Egg Consumption with Incident Cardiovascular Disease and Total Mortality

Associations of Dietary Cholesterol and Egg Consumption with Incident Cardiovascular Disease and Total Mortality

Associations of Dietary Cholesterol and Egg Consumption with Incident Cardiovascular Disease and Total Mortality

 

By Kevin C. Maki, PhD and Heather Nelson Cortes, PhD

 

Despite decades of research, the association between dietary cholesterol consumption, cardiovascular disease (CVD) and mortality remains controversial.  Adding to this controversy are the confusing recommendations in the 2015-2020 Dietary Guidelines for Americans.1,2  The Guidelines state that cholesterol is not a nutrient of concern for overconsumption, but also recommend that individuals should consume as little dietary cholesterol as possible while following a healthy eating pattern.  A meta-analysis of prospective cohort studies published in 2015 did not show statistically significant associations between dietary cholesterol consumption and incident CVD, coronary artery disease or stroke, although higher dietary cholesterol intake was associated with an increased level of low-density-lipoprotein cholesterol (LDL-C).3  Because a large chicken egg (~50 g) contains roughly 186 mg of cholesterol,4 limiting egg consumption has been recommended as a way to decrease dietary cholesterol and to possibly reduce the risk of CVD.

 

Zhong et al. recently published an analysis of the associations between intakes of dietary cholesterol and eggs with incident CVD and total mortality from the Lifetime Risk Pooling Project.5  The Lifetime Risk Pooling Project contains data from 6 cohorts in which usual dietary intake, fatal and nonfatal coronary heart disease, stroke, heart failure and CVD from other causes were assessed. The 6 cohorts were the Atherosclerosis Risk in Communities (ARIC) Study,6 Coronary Artery Risk Development in Young Adults (CARDIA) Study,7 Framingham Heart Study (FHS),8  Framingham Offspring Study (FOS),9 Jackson Heart Study (JHS)10 and the Multi-Ethnic Study of Atherosclerosis (MESA).11  The analysis included 29,615 participants (mean [standard deviation] age at baseline, 51.6 [13.5] years).5  There were 13,299 (44.9%) men and 9,204 (31.1%) subjects were black.  The median follow-up was 17.5 years (interquartile limits, 13.0-21.7; maximum, 31.3) during which there were 5,400 incident CVD events and 6,132 all-cause deaths. 

 

Dietary cholesterol and egg consumption showed linear associations with incident CVD and all-cause mortality (all P values for nonlinear terms, 0.19-0.83).  The addition of each 300 mg of dietary cholesterol per day was associated with higher risk of incident CVD (adjusted hazard ratio [HR] 1.17, 95% confidence interval [CI], 1.09-1.26 and adjusted absolute risk difference [ARD] 3.24%, 95% CI 1.39%-5.08%).  The same increment of dietary cholesterol per day was also associated with higher risk of all-cause mortality (adjusted HR 1.18, 95% CI 1.10-1.26 and adjusted ARD 4.43%, 95% CI 2.51%-6.36%). Consumption of each additional half egg per day was associated with higher risk of incident CVD:  adjusted HR 1.06, 95% CI 1.03-1.10; adjusted ARD 1.11%, 95% CI 0.32%-1.89% and all-cause mortality:  adjusted HR 1.08, 95% CI 1.04-1.11; adjusted ARD 1.93%, 95% CI 1.10%-2.76%.

 

The associations between egg consumption and incident CVD (adjusted HR 0.99, 95% CI 0.93-1.05) and all-cause mortality (adjusted HR 1.03, 95% CI 0.97-1.09) were no longer significant after adjusting for dietary cholesterol consumption.  The associations between dietary cholesterol intake and incident CVD, as well as mortality, remained statistically significant after adjusting for traditional CVD risk factors (including non-high-density lipoprotein cholesterol [non-HDL-C] concentration), various nutrient intakes and measures of diet quality.

 

Comment.  This new analysis by Zhong et al. has several strengths, including a long follow-up period and the availability and analysis of a great deal of dietary information, such as indices of diet quality, including the Alternative Healthy Eating Index, a Dietary Approaches to Stop Hypertension score and a Mediterranean Diet index.  The supplemental material for the paper includes extensive information from sensitivity analyses.

 

Despite these strengths, the results are difficult to interpret, in our view, for several reasons.  First, adjustment for non-HDL-C level did not materially alter the association between dietary cholesterol intake and incident CVD.  This is curious because the presumed mechanistic link between dietary cholesterol intake and incident CVD is through the effect of dietary cholesterol to raise the circulating concentrations of LDL-C and non-HDL-C, which are well-established major CVD risk factors that are believed to be causally related to CVD incidence.  In a communication with the authors, we were told that adjustment for non-HDL-C and HDL-C levels had virtually no impact on the point estimates for CVD risk.  Data were missing for LDL-C for 900 subjects, so this was not assessed separately.  Given the lack of effect of adjustment for lipid levels, if the association between dietary cholesterol intake and CVD risk is causal, one must hypothesize mechanisms other than the effect of dietary cholesterol to raise atherogenic cholesterol (LDL-C and non-HDL-C) levels.

 

A second issue is that within the range of typical cholesterol intakes in the United States (<300 mg/d), no significant increases in risk for incident CVD or all-cause mortality were observed.  For example, for intakes of 200 to <300 mg/d compared to <100 mg/d, the HR for CVD in model 3 (adjusted for CVD risk factors and medication use) was 0.99, 95% CI 0.87-1.12 and for mortality was 0.95, 95% CI 0.84-1.06.  Therefore, the traditional recommendation to limit dietary cholesterol intake to <300 mg/d is supported by these analyses.

 

Finally, the relationship between cholesterol intake and non-CVD mortality is similar to that for all-cause mortality, with model 3 HR for all-cause mortality of 1.15 (95% CI 1.07-1.23) compared with 1.13 (95% CI 1.04-1.22) for non-CVD mortality (eFigure 5 in the supplemental material).  We are not aware of biologically plausible mechanisms that would explain an increase in non-CVD mortality as a consequence of higher dietary cholesterol intake.  Therefore, the possibility of residual confounding must be considered.

 

It is also notable that two other recent publications have reported on the association between egg consumption and incident CVD.  In the EPIC-Norfolk cohort,12 the top quintile of egg consumption (median 40 g/d) was associated with a non-significantly lower adjusted incidence of ischemic heart disease compared with the lowest quintile (HR 0.93, 95% CI 0.86-1.01), with a p-value for trend across quintiles of 0.37.  Also, in a large study in China with nearly 500,000 participants,13 those who consumed eggs daily had lower risks for incident CVD (HR 0.89, 95% CI 0.87-0.92) and ischemic heart disease (HR 0.88, 95% CI 0.84-0.93) than those who rarely or never consumed eggs, with significant inverse trends (p < 0.001) over the range of egg intake categories.  So, within the space of one year we have seen publications from observational studies reporting associations ranging from a significant inverse association, to no significant relationship, to a significant positive association of egg intake with incident CVD and/or ischemic heart disease.

 

Our view is that the available data show convincingly that higher dietary cholesterol intake modestly raises the level of LDL-C, a major CVD risk factor, with linear models indicating a rise of ~2 mg/dL of LDL-C for each increment of 100 mg/d of dietary cholesterol.3,14,15  The results from the Zhong et al. study do not suggest elevations in CVD incidence or mortality risk for intakes of dietary cholesterol below the traditional recommendation of <300 mg/d (i.e., for intake of 200-299 mg/d compared with <100 mg/d).5  Their results also showed that the relationship between egg consumption and CVD and mortality risk could be accounted for by the cholesterol content of eggs.  Therefore, we believe it is reasonable to suggest that whole eggs can be a part of a healthy dietary pattern, provided that total dietary cholesterol intake is not excessive, with the traditional recommendation being not to exceed 300 mg/d.  For those with hypercholesterolemia, it may be reasonable to further restrict dietary cholesterol intake.  The National Lipid Association recommendations for management of dyslipidemia suggest that dietary cholesterol be limited to <200 mg/d for those with hypercholesterolemia, and further restriction may be prudent for those who are known to be hyperresponders, i.e., those who have a larger than average increase in LDL-C in response to an increase in dietary cholesterol.16  Additional research will be needed to determine whether a dietary cholesterol intake >300 mg/d is causally related to adverse health outcomes, and, if so, what mechanisms account for these relationships.

 

References

  1. US Department of Health and Human Services and US Department of Agriculture. 2015-2020 Dietary Guidelines for Americans. 8th Edition. December 2015. https://health.gov/dietary guidelines/2015/guidelines/.
  2. Dietary Guidelines Advisory Committee. Scientific Report of the 2015 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of Health and Human Services and the Secretary of Agriculture. Washington, DC: US Dept of Agriculture, Agricultural Research Service; 2015.
  3. Berger S, Raman G, Vishwanathan R, et al. Dietary cholesterol and cardiovascular disease. Am J Clin Nutr. 2015;102:276-294.
  4. US Department of Agriculture. Agricultural Research Service, Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference, Release 28. Version Current: September 2015. https://ndb.nal.usda.gov/ndb/.
  5. Zhong VW, Van Horn L, Cornelis MC, et al. Associations of dietary cholesterol or egg consumption with incident cardiovascular disease and mortality. JAMA. 2019;321:1081-1095.
  6. The ARIC Investigators. The Atherosclerosis Risk in Communities (ARIC) study: design and objectives. Am J Epidemiol. 1989;129:687-702.
  7. Friedman GD, Cutter GR, Donahue RP, et al. CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol. 1988;41:1105-1116.
  8. Wong ND, Levy D. Legacy of the Framingham Heart Study: rationale, design, initial findings, and implications. Glob Heart. 2013;8:3-9.
  9. Feinleib M, Kannel WB, Garrison RJ, et al. The Framingham Offspring Study: design and preliminary data. Prev Med. 1975;4:518-525.
  10. Taylor HA Jr, Wilson JG, Jones DW, et al. Toward resolution of cardiovascular health disparities in African Americans. Ethn Dis. 2005;15(suppl 6):4-17.
  11. Bild DE, Bluemke DA, Burke GL, et al. Multi-Ethnic Study of Atherosclerosis: objectives and design. Am J Epidemiol. 2002;156:871-881.
  12. Key TJ, Appleby PN, Bradbury KE, et al. Consumption of meat, fish, dairy products, eggs and risk of ischemic heart disease: a prospective study of 7198 incident cases among 409,885 participants in the Pan-European EPIC cohort. Circulation. 2019; Epub ahead of print.
  13. Qin C, Lv J, Bian Z, et al. Associations of egg consumption with cardiovascular disease in a cohort study of 0.5 million Chinese adults. Heart. 2018;104:1756-1763.
  14. Vincent MJ, Allen B, Palacios OM, Haber LT, Maki KC. Meta-regression analysis of the effects of dietary cholesterol intake on LDL and HDL cholesterol. Am J Clin Nutr. 2019;109:7-
  15. Clarke R, Frost C, Collins R, Appleby P, Peto R. Dietary lipids and blood cholesterol: quantitative meta-analysis of metabolic ward studies. BMJ. 1997;314:112-117.
  16. Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 2. J Clin Lipidol. 2015;9(6 Suppl):S1-S122.e1.

 

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Association of Long-term Consumption of Sugar-Sweetened and Artificially Sweetened Beverages with Total and Cause-specific Mortality

Association of Long-term Consumption of Sugar-Sweetened and Artificially Sweetened Beverages with Total and Cause-specific Mortality

By Heather Nelson Cortes, PhD and Kevin C Maki, PhD

In the United States, sugar sweetened beverages (SSBs) account for the largest source of added sugar in the diet 1,2.  These types of drinks (e.g., carbonated, noncarbonated, fruit, sports) have added caloric sweeteners like high fructose corn syrup, sucrose, or fruit juice concentrates.  Currently it is recommended that adults consume no more than 10% of their total energy intake from added sugar 3.

While consumption rates of SSBs had been declining in the US over the past 10 years, recent research has suggested a reversal in that trend, with increased consumption among adults of all ages averaging around 145 kcal/day (6% of energy)4.  In younger adults, SSBs are responsible for 9.3% of daily calories in men and 8.2% of daily calories in women 5-7.

Studies have shown a positive association between intake of SSBs and weight gain, as well as higher risks of type 2 diabetes, coronary heart disease and stroke 8-11.  Artificially sweetened beverages (ASBs) are used as alternatives to the calorically heavy SSBs, yet there has been little research on the long-term health effects of ASBs or on the relationship between SSB consumption and total mortality.

In an analysis of two ongoing prospective cohort studies, Malik et al. examined the association between intakes of SSBs and ASBs with total and cause-specific mortality 12.  The analysis included data from the Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS).  The NHS study has been collecting data since 1976 and includes 121,700 female nurses, age 30-55 years at study entry.  The HPFS began in 1986 and includes 51,529 male health professionals, age 40-75 years at entry. 

Mean consumption of SSBs decreased in both cohorts over the follow-up periods, which were 34 years in the NHS and 28 years in the HPFS.  Intakes of SSBs and ASBs were inversely correlated in both the NHS (r = −0.06, P < 0.001) and the HPFS (r = −0.16, P < 0.001).  Overall, there were 36,436 deaths, including 7,896 from cardiovascular disease (CVD) and 12,380 from cancer during a total of 3,415,564 person-years of follow-up.

After adjusting for major diet and lifestyle factors, consumption of SSBs was associated with a higher risk of total mortality (Table).  SSBs were also associated with increased CVD mortality (hazard ratio comparing extreme categories of 1.31 [95% confidence interval, 1.15-1.50], P trend < 0.0001) and cancer mortality (1.16 [1.04-1.29], P trend = 0.0004).  ASB intake was associated with increased risk for total and CVD mortality only in the highest intake group (Table).  Interestingly, intake of ASBs was associated with total mortality in the NHS, but not the HPFS (P interaction = 0.01).  ASBs were not associated with cancer mortality in either cohort.

 

 

Table:  SSB and ASB Consumption and Mortality Risk (Total, CVD, Cancer)

Pooled Hazard Ratios (95% confidence intervals) from NHS and HPFS

 

<1/month

1-4/month

2-6/week

1-<2/d

>2/d

P trend

Total Mortality

SSB

1.0

 

1.01

(0.98, 1.04)

1.06

(1.03, 1.09)

1.14

(1.09, 1.19)

1.21

(1.13, 1.28)

<0.0001

ASB

1.0

 

0.96

(0.93, 0.99)

0.97

(0.95, 1.00)

0.98

(0.94, 1.03)

1.04

(1.02, 1.12)

0.01

CVD Mortality

SSB

1.0

1.06

(1.00, 1.12)

1.10

(1.04, 1.17)

1.19

(1.08, 1.31)

1.31

(1.15, 1.50)

<0.0001

ASB

1.0

0.93

(0.87, 1.00)

0.95

(0.89, 1.00)

1.02

(0.94, 1.12)

1.13

(1.02, 1.25)

0.02

Cancer Mortality

SSB

1.0

1.03 

(0.98, 1.08)

1.06

(1.01, 1.11)

1.12

(1.03, 1.21)

1.16

(1.04, 1.29)

0.0004

ASB

1.0

1.01

(0.96, 1.07)

0.99

(0.94, 1.04)

1.00

(0.93, 1.07)

1.04

(0.96, 1.12)

0.58

 

Comment.  Results from this study highlight the importance of minimizing SSB intake because consumption of SSBs has been consistently associated with adverse health outcomes and a less favorable cardiometabolic risk factor profile.8-11  Substituting ASBs for SSBs will help decrease added sugar intake, but it is important to note that the possible health impacts of long-term consumption have not been well documented.  It is uncertain whether the modest increases in total (4%) and CVD (13%) mortality associated with consuming ≥2 ASBs per day represent causal relationships.  Nevertheless, it is reasonable to recommend moderation in the consumption of these products.

 

References

  1. Hu FB, Malik VS. Sugar-sweetened beverages and risk of obesity and type 2 diabetes: epidemiologic evidence. Physiol Behav. 2010;100:47–54.
  2. National Cancer Institute: Division of Cancer Control & Population Sciences. Epidemiology and Genomics Research Program. Sources of Calories from Added Sugars among the US population, 2005–2006. Updated April 20, 2018. http://riskfactor.cancer.gov/diet/foodsources/added_sugars/.
  3. S. Department of Health and Human Services and U.S. Department of 
Agriculture. 2015–2020 Dietary Guidelines for Americans. 8th Edition. December 2015. http://health.gov/dietaryguidelines/2015/guidelines/.
  4. Welsh JA, Sharma AJ, Grellinger L, Vos MB. Consumption of added sugars is decreasing in the United States. Am J Clin Nutr. 2011;94:726–734.
  5. Ogden CL, Kit BK, Carroll MD, Park S. Consumption of sugar drinks in the United States, 2005–2008. NCHS Data Brief. 2011:1–8. 

  6. Rosinger A, Herrick K, Gahche J, Park S. Sugar-sweetened beverage consumption among U.S. adults, 2011–2014. NCHS Data Brief. 2017:1–8. 

  7. Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013;98:1084–1102.
  8. Malik VS, Popkin BM, Bray GA, Després JP, Willett WC, Hu FB. Sugar- sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33:2477–2483.
  9. Fung TT, Malik V, Rexrode KM, Manson JE, Willett WC, Hu FB. Sweetened beverage consumption and risk of coronary heart disease in women. Am J Clin Nutr. 2009;89:1037–1042.
  10. de Koning L, Malik VS, Kellogg MD, Rimm EB, Willett WC, Hu FB. Sweetened beverage consumption, incident coronary heart disease, and biomarkers of risk in men. Circulation. 2012;125:1735–41, S1.
  11. Bernstein AM, de Koning L, Flint AJ, Rexrode KM, Willett WC. Soda consumption and the risk of stroke in men and women. Am J Clin Nutr. 2012;95:1190–1199.
  12. Malik VS, Li Y, Pan A, De Koning L, Schernhammer E, Willett WC, Hu FB. Long-term consumption of sugar-sweetened and artificially sweetened beverages and risk of mortality in US adults.  2019;139: doi: 10.1161/circulationaha.118.037401.

 

 

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Association of Statin Adherence with Mortality in Patients with Atherosclerotic Cardiovascular Disease

Association of Statin Adherence with Mortality in Patients with Atherosclerotic Cardiovascular Disease

By Heather Nelson Cortes, PhD and Kevin C Maki, PhD

 

There is little doubt of the role that statins play in the reduction of mortality risk, mainly attributable to a benefit on death from cardiovascular causes.  A meta-analysis of statin clinical trials reported a 12% proportional reduction in all-cause mortality per mmol/L reduction in low-density lipoprotein cholesterol (LDL-C) with the use of statins (rate ratio [RR] 0.88, 95% confidence interval [CI] 0.84-0.91; p < 0.0001).1  In a systematic review, De Vera et al. reported an increased risk of adverse outcomes with poor statin therapy adherence.2  With such a strong link between statin adherence and decreased mortality, it is unclear why so many patients stop taking their statins or what the long-term effects on health and healthcare costs will be.  Results from surveys of statin adherence suggest that as many as 50% of patients for whom statin therapy is prescribed stop taking the medication within 12 months.3,4  Rates of discontinuation and poor adherence are high even among those with known atherosclerotic cardiovascular disease (ASCVD).3,4

 

To further assess the association between statin adherence and all-cause mortality, Rodriguez et al. conducted a retrospective cohort analysis of patients between the ages of 21-85 years with one or more International Classification of Diseases, Ninth Revision, Clinical Modification codes for ASCVD on two or more dates in the previous two years without intensity changes to their statin prescription.5  All patients were treated within the Veterans Affairs Health System between January 1, 2013 and April 2014.

 

The primary outcome was death from all causes adjusted for demographic and clinical characteristics, and adherence to other cardiac medications.  Secondary outcomes included 1-year mortality, 1-year hospitalization for ischemic heart disease or ischemic stroke.  A sensitivity analysis was also conducted to investigate an association between statin adherence and hospitalization for gastrointestinal bleeding and pneumonia.  Finally, the researchers sought to determine if the association between statin adherence and mortality was modified by statin intensity (low, medium, high) or by patient-level or system-level characteristics.

 

The medication possession ratio (MPR) was used to measure patient medication adherence.  The MPR is the number of days of outpatient statin supplied during a 12- month period divided by the number of days the patient was not hospitalized and alive in the same 12-month time frame.  Medication adherence was categorized as <50% MPR, 50-69% MPR, 70-89% MPR and ≥90% MPR.

 

The study included 347,104 patients with ASCVD on stable statin prescriptions.  The overall mean statin adherence in this population was ~88%; ~6% had a MPR of <50% and ~64% had a MPR of ≥90%.  Overall, women were less adherent than men (odds ratio, 0.89; 95% CI, 0.84-0.94), as were minority groups, while younger and older patients were less likely to be adherent compared with those aged 65-74 years.  During a mean (standard deviation) follow up of 2.9 (0.8) years there were 85,930 deaths (24.8%).  Compared to the most adherent patients (MPR ≥90%), patients with a MPR <50% had a hazard ratio (HR) adjusted for clinical characteristics and adherence to other cardiac medications of 1.30 (95% CI, 1.27-1.34), while those with a MPR of 50-69% had a HR of 1.21 (95% CI, 1.18-1.24), and those with an MPR of 70-89% had a HR of 1.08 (95% CI, 1.06-1.09).

 

After one year, hospitalizations for ischemic heart disease and stroke were more frequent in patients who were less adherent to their statin therapy.  The proportion of patients with a hospitalization for ischemic heart disease or ischemic stroke was 13.4% (n = 2653) for an MPR<50%, 13.1% (n = 4018) for an MPR of 50-69%, 11.5% (n = 8729) for an MPR of 70-89%, and 11.5% (n = 25434) for an MPR of ≥90% (p < 0.001).  This association remained even after adjusting for baseline characteristics.  There was no association between MPR and hospitalization for gastrointestinal bleeding or pneumonia.

 

Finally, in this cohort 42,010 (12%) patients were on low-intensity therapy, 217,570 (63%) were on moderate-intensity therapy, and 87,524 (25%) were on high-intensity treatment.  Patients on moderate-intensity statin therapy were more likely to adhere to statin therapy compared to patients in the low- and high-intensity therapy groups.  Patients with the highest MPR had lower LDL-C values (77.2 mg/dL for MPR ≥90% compared with 92.1 mg/dL for MPR <50%).

 

Comment.  The role that statins play in the reduction of mortality is not surprising.  When a patient consistently takes the statin as prescribed, their risk of cardiovascular mortality will likely decrease.  What is surprising is the lack of adherence by patients, especially over time, given the evidence supporting statin effectiveness.  Further research should focus on how to improve patient adherence to statin therapy.6

 

Another important consideration that is illustrated by the present study is that it is important to consider the effects of healthy and unhealthy user bias in observational studies.  Ann Marie Navar makes this point in an editorial accompanying the paper.6  Those with the poorest adherence to statin therapy (MPR <50%) had a 30% increase in mortality.  Adjustment for follow-up LDL-C levels reduced the mortality hazard by 10%.  Thus, only one third of the effect appears to be attributable to the main pathway through which statins alter risk.  This suggests the presence of residual confounding by other factors.  People who are adherent to therapy recommendations differ in numerous ways relevant to health outcomes from those who do not.  It is difficult, if not impossible, to fully account for differences in potential confounders through statistical modeling.  Thus, while a portion of the higher mortality risk among those with poor adherence is likely due to less impact of the drug itself, other factors also likely contribute to a similar or even larger degree.

 

This concept was recently illustrated in an analysis from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.7,8  Healthy 55- to74-year old participants were randomly assigned to receive usual care or a more intensive screening program.  Among those randomized to more intensive screening, 10.8% did not complete any of the recommended screening tests.  After 10 years, those non-adherent subjects had 50% higher mortality compared to those with full adherence who completed all recommended tests.  However, the increased mortality was not attributable only to cancers, but to a wide range of causes.  Thus, non-adherence to recommended screening (or to prescribed medication) is likely a marker for an array of behaviors associated with increased mortality risk.  This unhealthy or healthy user bias should be kept in mind when evaluating the results from observational studies of behaviors associated with health outcomes.  Those who choose to engage in a behavior they view as health-promoting, such as taking prescribed medication, undergoing recommended screening tests, following a diet or exercise program, or taking a dietary supplement, may differ in important ways from those who choose not to engage in the behavior, resulting in healthy user bias.  Conversely, those who engage in behaviors they know are unhealthy, such as cigarette smoking, may also engage in other unhealthy behaviors (unhealthy user bias).  Thus, estimates of the effects of behavioral exposures from observational studies should be interpreted with caution and should ideally be verified in prospective, randomized, controlled trials.

 

References

 

  1. Baigent C, Keech A, Kearney PM, et al. Cholesterol Treatment Trialists’ (CTT) Collaborators. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005;366:1267-1278.
  2. DeVera MA, Bhole V, Burns LC, Lacaille D. Impact of statin adherence on cardiovascular disease and mortality outcomes: a systematic review. Br J Clin Pharmacol. 2014;78:684-698.
  3. Maddox TM, Chan PS, Spertus JA, et al. Variations in coronary artery disease secondary prevention prescriptions among outpatient cardiology practices: insights from the NCDR (National Cardiovascular Data Registry). J Am Coll Cardiol. 2014;63:539-546.
  4. Hirsh BJ, Smilowitz NR, Rosenson RS, et al. Utilization of and adherence to guideline-recommended lipid-lowering therapy after acute coronary syndrome: opportunities for improvement. J Am Coll Cardiol. 2015;66:184-192.
  5. Rodriguez F, Maron DJ, Knowles JW, et al. Association of statin adherence with mortality in patients with atherosclerotic cardiovascular disease. JAMA Cardiol. 2019; Epub ahead of print.
  6. Navar AM. Statins work, but only in people who take them. JAMA Cardiol. 2019; Epub ahead of print.
  7. Pierre-Victor D, Pinsky PF. Association of nonadherence to cancer screening examinations with mortality from unrelated causes: a secondary analysis of the PLCO Cancer Screening trial. JAMA Intern Med. 2019;179:196-203.
  8. Grady D. Why is nonadherence to cancer screening associated with increased mortality? JAMA Intern Med. 2018; Epub ahead of print.

 

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Changes in Diet Quality and Mortality

Changes in Diet Quality and Mortality

Changes in Diet Quality and Mortality

By Kevin C Maki, PhD

Background
Sotos-Prieto and colleagues from the Departments of Nutrition and Epidemiology at Harvard University published an analysis of the relationships between changes in diet quality scores and mortality [all-cause, cardiovascular (CV), and cancer] in a recent issue of the New England Journal of Medicine.1  These relationships were examined in two large cohorts of health professionals, the US Nurses’ Health Study (women) and the US Health Professionals Follow-up Study (men).

Previous studies have shown that higher diet quality scores are associated with lower mortality.  Of course, the potential problem with observational evidence is that it is difficult to know whether it is higher diet quality per se that is responsible for the relationship to lower mortality, or other differences between those with lower and higher diet quality scores.  People who consume diets that conform to recommendations from health authorities often have other characteristics that might contribute to better outcomes.  They tend to be more health conscious, have higher educational attainment, exercise more regularly, have lower body mass index, and be less likely to smoke, use illicit substances and consume alcohol to excess, just to name a few of the differences.

Epidemiologists attempt to adjust for these differences using statistical techniques to reduce the potential for bias and confounding by differences other than the exposure of interest; in this case diet quality score.  It is often impossible to identify and adjust for all of the variables that may be relevant.  The ultimate goal is to identify exposures that are causally related to disease status and modifiable, which can serve as the basis for public health actions, including recommendations for the characteristics of a healthy diet.

While far from perfect, it is useful to investigate the relationships between changes in exposure variables over time and disease risk.  For example, it bolstered the case for a causal relationship between cigarette smoking and risks for lung cancer and heart disease when it was shown that risks declined over time in those who quit smoking, but did not in those who continued to smoke.  Similarly, the Harvard group sought to assess whether changes in diet quality scores over time predicted risks for all-cause and cause-specific mortality.

Methods
In order to address this question, the researchers calculated changes over time in three scores:  the Alternative Healthy Eating Index (aHEI), the Alternative Mediterranean Diet (aMED) score, and the Dietary Approaches to Stop Hypertension (DASH) score.  Scores were calculated based on responses to the Willett Food Frequency Questionnaire that was administered every 4 years over long periods in both cohorts.  For the main analysis, changes in diet quality were calculated from 1986 to 1998 and follow-up was through 2010 (12 years).  The analysis included data from 73,739 participants (65% women).

The aHEI used scores from 0-10 for 11 food components selected on the basis of their relationships with chronic diseases.  Thus, the score could be from 0 to 110.  The aMED score included 9 components and were scored as 0 or 1 according to whether intake was above or below the cohort-specific median, allowing a score from 0 to 9.  The DASH score included 8 components, each scored 1-5, thus producing scores ranging from 8 to 40.  For all, a higher score indicated higher diet quality.

Results
Participants who increased their diet quality scores reported increased intakes of whole grains, vegetables and omega-3 fatty acids, as well as reduced intakes of sodium.  Compared to participants with relatively stable scores (middle quintile for change), those in the top 20% for increases (roughly 15-16 points for aHEI, 2-3 points for aMED, and 5-6 points for DASH), had 9-14% lower mortality risk, all p < 0.05 for the fifth vs. the third quintile in multivariable-adjusted models.  Similar results were obtained when a 20-percentile increase in score was modeled (8-17% lower risk for mortality).

Results were somewhat less consistent for deaths from CV causes and cancer.  A 20-percentile increase in aHEI was associated with 15% lower CV mortality (p < 0.05), while the same increase in aMED was associated with a 7% lower CV mortality (p < 0.05), and a 20-percentile increase in DASH score was associated with a non-significant 4% reduction in mortality.  For cancer mortality, a 20-percentile increase was associated with 6-9% lower mortality, which was only statistically significant (p < 0.05) for the DASH score (9%).

Having constant high diet quality score was associated with reductions of 9-14% in all-cause mortality over 12 years compared to those with constant low scores.  The investigators also looked at 8-year and 16-year changes.  In general, the effect became more pronounced with longer periods.  This was particularly evident for the aHEI, although that may be due to the greater range of values possible, which increases the variation in the populations studied.

Comment
This study adds support for the healthy eating patterns recommended in the Dietary Guidelines for Americans (2015-2020).2  Although confounding by unmeasured, or crudely measured, factors cannot be ruled out, the available data are consistent with a causal association between a healthy diet pattern and reduced risks for all-cause and CV mortality.  The evidence for a reduction in cancer mortality with a healthy dietary pattern is less convincing.  These results particularly support the recommendations for increased consumption of whole grains, fruits, vegetables, and fish/omega-3 fatty acids, compared with the average American diet, since these were the foods that were primarily responsible for changes in diet quality scores over time.

As I have stated repeatedly, public policy recommendations regarding diet often have to be based on evidence from observational studies assessing disease risk and intervention studies of biomarkers for disease risk, because few randomized, controlled dietary intervention studies have been completed to assess effects on disease incidence.  The strongest recommendations should be reserved for those areas where we have alignment between results from all three types of studies.

The results from the Prevención con Dieta Mediterránea (PREDIMED) study support health benefits, including reduced incidence of CV events (particularly stroke) and diabetes associated with advice to consume a Mediterranean diet pattern supplemented with nuts or olive oil, compared to low-fat diet advice.3 PREDIMED was not a perfect trial.  More randomized, controlled dietary intervention trials with outcomes of disease incidence are badly needed to answer questions about risks and benefits of various types of dietary advice.  PREDIMED demonstrates the feasibility of completing such studies.

For now, despite a number of caveats and uncertainties, the best available evidence suggests that the dietary patterns recommended in the Dietary Guidelines for Americans (healthy US diet, Mediterranean diet, DASH diet) are associated with a variety of favorable outcomes, including reduced total and CV mortality.

References:

  1. Sotos-Prieto M, Bhupathiraju SN, Mattei J, et al. Association of changes in diet quality with total and cause-specific mortality. N Engl J Med. 2017;377:143-153.
  2. US Department of Health and Human Services and US Department of Agriculture. Dietary Guidelines for Americans 2015-2020. 8th December 2016. Available at https://health.gov/dietaryguidelines/2015/resources/2015-2020_Dietary_Guidelines.pdf.
  3. Estruch R, Martínez-González MA, Corella D, et al.; PREDIMED Study Investigators. Effects of a Mediterranean-style diet on cardiovascular risk factors: a randomized trial. Ann Intern Med. 2006;145:1-11.

 

 

Changes in Diet Quality and Mortality