| Literature DB >> 28635680 |
Michelle A Briggs1, Kristina S Petersen2, Penny M Kris-Etherton3.
Abstract
Dietary recommendations to decrease the risk of cardiovascular disease (CVD) have focused on reducing intake of saturated fatty acids (SFA) for more than 50 years. While the 2015-2020 Dietary Guidelines for Americans advise substituting both monounsaturated and polyunsaturated fatty acids for SFA, evidence supports other nutrient substitutions that will also reduce CVD risk. For example, replacing SFA with whole grains, but not refined carbohydrates, reduces CVD risk. Replacing SFA with protein, especially plant protein, may also reduce CVD risk. While dairy fat (milk, cheese) is associated with a slightly lower CVD risk compared to meat, dairy fat results in a significantly greater CVD risk relative to unsaturated fatty acids. As research continues, we will refine our understanding of dietary patterns associated with lower CVD risk.Entities:
Keywords: CVD; dairy fat; dietary substitution; monounsaturated fatty acids; polyunsaturated fatty acids; protein; refined carbohydrates; saturated fatty acids; whole grains
Year: 2017 PMID: 28635680 PMCID: PMC5492032 DOI: 10.3390/healthcare5020029
Source DB: PubMed Journal: Healthcare (Basel) ISSN: 2227-9032
The effect of replacing SFA with other dietary macronutrients on cardiovascular outcomes.
| Study | Design | Mean Follow-Up Time (Years) | Outcome | Substitution | Result | Effect Size (95% CI) | Covariates Included in Analyses | |
|---|---|---|---|---|---|---|---|---|
| Jakobsen 2009 [ | Pooled analysis of prospective cohort studies | 11 studies ( | Range 4 to 10 | Coronary events | 5% of energy from SFA → MUFA | ↔ | HR 1.19 (1.00–1.42) | Age; BMI; year survey completed; percentage of energy from MUFA, PUFA, |
| Coronary deaths | ↔ | HR 1.01 (0.73–1.41) | ||||||
| Guasch-Ferré 2015 [ | Prospective cohort | 7038 | 6 | CVD | 5% of energy from SFA → MUFA | ↓ | HR 0.63 (0.43–0.94) | Age; sex; BMI; intake of subtypes of fat, protein, and carbohydrates; energy intake; smoking; physical activity; education; alcohol intake; fiber intake; cholesterol intake; hypertension; intervention group; diabetes; hyper-cholesterolemia; family history of CHD; antihypertensive medication; oral antidiabetic agents; lipid lowering drugs |
| All-cause death | ↔ | HR 0.91 (0.65–1.26) | ||||||
| Li 2015 [ | Prospective cohort | 127,536 | Range 24–30 | CHD | 5% of energy from SFA → MUFA | ↓ | HR 0.85 (0.74–0.97) | BMI, percentage of energy from protein; energy intake; smoking; physical activity; alcohol intake; cholesterol intake; hypertension at baseline; hypercholesterolemia at baseline; family history of myocardial infarction and diabetes; use of vitamins and aspirin |
| Praagman 2016 [ | Prospective cohort | 35,597 | 12 | IHD | 5% of energy from SFA → | ↑ | HR 1.30 (1.02–1.65) | Age, sex, BMI, waist circumference; intake of carbohydrate, |
| Wang 2016 [ | Prospective cohort | 126,233 | NHS ≤ 32; HPFS ≤ 26 | CVD mortality | 5% of energy from SFA → MUFA | ↔ | HR 0.96 (0.84–1.09) | Age; BMI, percentage of energy intake from protein, remaining fatty acids (saturated fat, PUFA, MUFA, |
| Total mortality | ↓ | HR 0.87 (0.82–0.93) | ||||||
| Zong 2016 [ | Prospective cohort | 115,782 | NHS 25.8; HPFS 21.2 | CHD | 1% of energy from 12:0–18:0 SFA → MUFA | ↔ | HR 0.95 (0.90, 1.01) | Age; BMI; ethnicity; total energy; energy from |
| Hooper 2015 [ | Meta-analysis of randomized controlled trials | 15 studies ( | >2 | CVD events | SFA → MUFA | ↔ | RR 1.00 (0.53–1.89) | Aggregate meta-analysis—no overall adjustment |
| Mozaffarian 2010 [ | Meta-analysis of randomized controlled trials | 8 studies ( | Median of all trials 4.25 | CHD | 5% of energy from SFA → total PUFA | ↓ | RR 0.90 (0.83–0.97) | Aggregate meta-analysis—no overall adjustment |
| Jakobsen 2009 [ | Pooled analysis of prospective cohort studies | 11 studies ( | Range 4 to 10 | Coronary events | 5% of energy from SFA → total PUFA | ↓ | HR 0.87 (0.77–0.97) | Age; BMI; year survey completed; percentage of energy from MUFA, PUFA, |
| Coronary deaths | ↓ | HR 0.74 (0.61–0.89) | ||||||
| Farvid 2014 [ | Meta-analysis of prospective cohort studies | 13 studies ( | Range 5.3 to 30 | Coronary events | 5% of energy from SFA → linoleic acid | ↓ | RR 0.91 (0.87–0.96) | Aggregate meta-analysis—analyses in the individuals studies adjusted but no overall adjustment |
| Coronary deaths | ↓ | RR 0.87 (0.82–0.94) | ||||||
| Li 2015 [ | Prospective cohort | 127,536 | Range 24–30 | CHD | 5% of energy from SFA → total PUFA | ↓ | HR 0.75 (0.67–0.84) | BMI, percentage of energy from protein; energy intake; smoking; physical activity; alcohol intake; cholesterol intake; hypertension at baseline; hypercholesterolemia at baseline; family history of myocardial infarction and diabetes; use of vitamins and aspirin |
| Guasch-Ferré 2015 [ | Prospective cohort | 7038 | 6 | CVD | 5% of energy from SFA → PUFA | ↓ | HR 0.67 (0.45–0.98) | Age; sex; BMI; intake of subtypes of fat, protein, and carbohydrates; energy intake; smoking; physical activity; education; alcohol intake; fiber intake; cholesterol intake; hypertension; intervention group; diabetes; hyper-cholesterolemia; family history of CHD; antihypertensive medication; oral antidiabetic agents; lipid lowering drugs |
| All-cause mortality | ↓ | HR 0.61 (0.39–0.97) | ||||||
| Chen 2016 [ | Prospective cohort | 134,327 | NHS ≤ 32; NHS II ≤; HPFS ≤ 24 | CVD | 5% of energy from dairy fat → total PUFA | ↓ | HR 0.76 (0.71–0.81) | Age, BMI, intake of protein; energy intake; smoking; physical activity; intake of fruit, vegetables, coffee; alcohol intake; baseline hypertension; baseline hyper-cholesterolemia; race; menopausal status and menopausal hormone use (NHS and NHS II); oral contraceptive use (NHS II only) |
| CHD | ↓ | HR 0.74 (0.68–0.81) | ||||||
| Stroke | ↓ | HR 0.78 (0.70–0.88) | ||||||
| CVD | 5% of energy from dairy fat → | ↓ | HR 0.75 (0.70–0.81) | |||||
| CHD | ↓ | HR 0.75 (0.69–0.82) | ||||||
| Stroke | ↓ | HR 0.76 (0.68–0.86) | ||||||
| CVD | 0.3% of energy from dairy fat → α-linolenic acid | ↓ | HR 0.86 (0.82–0.90) | |||||
| CHD | ↓ | HR 0.83 (0.78–0.88) | ||||||
| Stroke | ↓ | HR 0.89 (0.83–0.96) | ||||||
| CVD | 0.3% of energy from dairy fat → marine | ↓ | HR 0.89 (0.84–0.94) | |||||
| CHD | ↓ | HR 0.87 (0.81–0.93) | ||||||
| Stroke | ↔ | HR 0.92 (0.84–1.01) | ||||||
| Praagman 2016 [ | Prospective cohort | 35,597 | 12 | IHD | 5% of energy from SFA → PUFA | ↑ | HR 1.35 (1.14–1.61) | Age, sex, BMI, waist circumference; intake of carbohydrate, |
| Wang 2016 [ | Prospective cohort | 126,233 | NHS ≤ 32; HPFS ≤ 26 | CVD mortality | 5% of energy from SFA → total PUFA | ↓ | HR 0.72 (0.65–0.80) | Age; BMI, percentage of energy intake from protein, remaining fatty acids (saturated fat, PUFA, MUFA, |
| Total mortality | ↓ | HR 0.73 (0.70–0.77) | ||||||
| CVD mortality | 2% of energy from SFA → | ↓ | HR 0.89 (0.85–0.94) | |||||
| Total mortality | ↓ | HR 0.93 (0.91–0.96) | ||||||
| CVD mortality | 0.3% of energy from SFA → | ↔ | HR 1.01 (0.97–1.05) | |||||
| Total mortality | ↓ | HR 0.95 (0.93-0.96) | ||||||
| Zong 2016 [ | Prospective cohort | 115,782 | NHS 25.8; HPFS 21.2 | CHD | 1% of energy from 12:0–18:0 SFA → PUFA | ↓ | HR 0.92 (0.89, 0.96) | Age; BMI; ethnicity; total energy; energy from |
| Hooper 2015 [ | Meta-analysis of randomized controlled trials | 15 studies ( | >2 | CVD events | SFA → PUFA | ↓ | RR 0.73 (0.58–0.92) | Aggregate meta-analysis—no overall adjustment |
| Jakobsen 2009 [ | Pooled analysis of prospective cohort studies | 11 studies ( | Range 4 to 10 | Coronary events | 5% of energy from SFA → total carbohydrate | ↑ | HR 1.07 (1.01–1.14) | Age; BMI; year survey completed; percentage of energy from MUFA, PUFA, |
| Coronary deaths | 5% of energy from SFA → total carbohydrate | ↔ | HR 0.96 (0.82–1.13) | |||||
| Jakobsen 2010 [ | Prospective cohort | 53,644 | Median 12 | MI | 5% of energy from SFA → total carbohydrates | ↔ | HR 1.04 (0.92–1.17) | Age, sex, BMI; percentage of energy from glycemic carbohydrates, proteins, MUFA, PUFA; energy intake; smoking; physical activity; education; alcohol consumer; intake of alcohol; hypertension |
| 5% of energy from SFA → carbohydrates with low-GI (median GI 82) | ↔ | HR 0.88 (0.72–1.07) | ||||||
| 5% of energy from SFA → carbohydrates with medium-GI (median GI 88) | ↔ | HR 0.98 (0.80–1.21) | ||||||
| 5% of energy from SFA → carbohydrates with high-GI (median GI 93) | ↑ | HR 1.33 (1.08–1.64) | ||||||
| Guasch-Ferré 2015 [ | Prospective cohort | 7038 | 6 | CVD | 5% of energy from SFA→ total carbohydrate | ↔ | HR 0.83 (0.63–1.10) | Age; sex; BMI; intake of subtypes of fat, protein, and carbohydrates; energy intake; smoking; physical activity; education; alcohol intake; fiber intake; cholesterol intake; hypertension; intervention group; diabetes; hyper-cholesterolemia; family history of CHD; antihypertensive medication; oral antidiabetic agents; lipid lowering drugs |
| All-cause death | ↔ | HR 1.04 (0.81–1.33) | ||||||
| Li 2015 [ | Prospective cohort | 127,536 | Range 24–30 | CHD | 5% of energy from SFA → whole grains | ↓ | HR 0.91 (0.85–0.98) | BMI, percentage of energy from protein; energy intake; smoking; physical activity; alcohol intake; cholesterol intake; hypertension at baseline; hypercholesterolemia at baseline; family history of myocardial infarction and diabetes; use of vitamins and aspirin |
| 5% of energy from SFA → refined starches/added sugar | ↔ | Not reported | ||||||
| Zong 2016 [ | Prospective cohort | 115,782 | NHS 25.8; HPFS 21.2 | CHD | 1% of energy from 12:0–18:0 SFA → whole grains | ↓ | HR 0.94 (0.91, 0.97) | Age; BMI; ethnicity; total energy; energy from |
| Chen 2016 [ | Prospective cohort | 134,327 | NHS ≤ 32; NHS II ≤ 20; HPFS ≤ 24 | CVD | 5% of energy from dairy fat → carbohydrate from whole grains | ↓ | HR 0.72 (0.69–0.75) | Age, BMI, intake of protein; energy intake; smoking; physical activity; intake of fruit, vegetables, coffee; alcohol intake; baseline hypertension; baseline hyper-cholesterolemia; race; menopausal status and menopausal hormone use (NHS and NHS II); oral contraceptive use (NHS II only) |
| CHD | ↓ | HR 0.66 (0.62–0.70) | ||||||
| Stroke | ↓ | HR 0.84 (0.78–0.91) | ||||||
| CVD | 5% of energy from dairy fat → carbohydrate from refined starch and added sugar | ↔ | HR 0.97 (0.94–1.00) | |||||
| CHD | ↔ | HR 0.96 (0.93–1.00) | ||||||
| Stroke | ↔ | HR 0.98 (0.94–1.03) | ||||||
| Praagman 2016 [ | Prospective cohort | 35,597 | 12 | IHD | 5% of energy from SFA → total carbohydrates | ↑ | HR (1.23 (1.09–1.40) | Age, sex, BMI, waist circumference; intake of carbohydrate, |
| 5% of energy from SFA → carbohydrates with low GI (GI < 53) | ↔ | HR 1.14 (0.91–1.43) | ||||||
| 5% of energy from SFA → carbohydrates with medium GI | ↑ | HR 1.35 (1.05–1.73) | ||||||
| 5% of energy from SFA → carbohydrates with high GI (GI > 56) | ↑ | HR 1.27 (1.03–1.56) | ||||||
| Hooper 2015 [ | Meta-analysis of randomized controlled trials | 15 studies ( | >2 | CVD events | SFA → carbohydrate | ↔ | RR 0.93 (0.79–1.08) | Aggregate meta-analysis—no overall adjustment |
| Larsson 2012 [ | Prospective cohort | 34,670 | Median 10.4 | Stroke | 5% of energy from SFA → protein | ↓ | 13% lower risk (0–26%) | Age, BMI; intake of fat; energy intake; smoking status and smoking pack years; physical activity; education; alcohol intake; intake of cholesterol, calcium, fruits and vegetables; hypertension; diabetes; aspirin use; family history of myocardial infarction |
| Praagman 2016 [ | Prospective cohort | 35,597 | 12 | IHD | 5% of energy from SFA → total protein | ↑ | HR 1.29 (1.08–1.54) | Age, sex, BMI, waist circumference; intake of carbohydrate, |
| 5% of energy from SFA → animal protein | ↑ | HR 1.37 (1.14–1.65) | ||||||
| 5% of energy from SFA → vegetable protein | ↔ | HR 0.81 (0.57–1.17) | ||||||
| Zong 2016 [ | Prospective cohort | 115,782 | NHS 25.8; HPFS 21.2 | CHD | 1% of energy from 12:0–18:0 SFA → plant protein | ↓ | HR 0.93 (0.89, 0.97) | Age; BMI; ethnicity; total energy; energy from |
| Hooper 2015 [ | Meta-analysis of randomized controlled trials | 15 studies ( | >2 | CVD events | SFA → protein | ↔ | RR 0.98 (0.90–1.06) | Aggregate meta-analysis—no overall adjustment |
The effect of macronutrient substitutions of blood lipid levels as reported by Mensink 2016 [4].
| Study | Design | Follow-Up Time | Outcome | Substitution | Result | Effect Size | Covariates Included in Analyses | |
|---|---|---|---|---|---|---|---|---|
| Mensink 2016 [ | Systematic review and meta-analysis of randomized controlled trials | 74 studies | Range 13–91 days | Total cholesterol | 1% of energy from SFA → | −0.046 mmol/L (−0.051 to−0.040; | ↓ | No adjustment |
| 69 studies | LDL cholesterol | −0.042 mmol/L (−0.047 to −0.037; | ↓ | |||||
| 68 studies | HDL cholesterol | −0.002 mmol/L (−0.00 to 0.000; | ↓ | |||||
| 72 studies | Triglycerides | −0.004 mmol/L (−0.007 to −0.001; | ↓ | |||||
| Mensink 2016 [ | Systematic review and meta-analysis of randomized controlled trials | 74 studies | Range 13–91 days | Total cholesterol | 1% of energy from SFA → | −0.064 mmol/L (−0.070 to −0.058; | ↓ | No adjustment |
| 69 studies | LDL cholesterol | −0.055 mmol/L (−0.061 to −0.050; p < 0.001) | ↓ | |||||
| 68 studies | HDL cholesterol | −0.005 mmol/L (−0.006 to −0.003; | ↓ | |||||
| 72 studies | Triglycerides | −0.010 mmol/L (−0.014 to −0.007; | ↓ | |||||
| Mensink 2016 [ | Systematic review and meta-analysis of randomized controlled trials | 74 studies | Range 13–91 days | Total cholesterol | 1% of energy from SFA → carbohydrates | −0.041 mmol/L (−0.047 to −0.035; | ↓ | No adjustment |
| 69 studies | LDL cholesterol | −0.033 mmol/L (−0.039 to −0.027; | ↓ | |||||
| 68 studies | HDL cholesterol | −0.010 mmol/L (−0.012 to −0.008; | ↓ | |||||
| 72 studies | Triglycerides | 0.011 mmol/L (0.007 to 0.014; | ↔ | |||||