Liu Y., 2021 [4] | Liu Y., 2021 [5] |
Prospective cohort |
Nurses’ Health Study ( | n | = 88,770 women). The Health Professionals
Follow-up Study ( | n | = 48,197 men) |
Plant based low-carbohydrate diet |
0.83 (0.70–0.98) |
Per 1 standard deviation increase |
Carbohydrates from refined grains |
1.18 (1.00–1.39) |
Per 1 standard deviation increase |
Plant fat |
0.78 (0.65–0.95) |
Per 1 standard deviation increase |
Shah SC., 2021 [5] | Shah SC., 2021 [6] |
Prospective cohort |
The NIH-American Association of Retired Persons (NIH-AARP) Diet and Health Study ( | n | = 536,359) |
Magnesium (diet + supplements) |
0.65 (0.48–0.87) |
4th vs. 1st quartile |
Luu HN., 2021 [6] | Luu HN., 2021 [7] |
Prospective cohort |
Singapore Chinese Health
Study ( | n | = 63,2570) |
Alternative Health Eating Index-2010 (AHEI-2010) |
0.69 (0.53–0.89) |
4th vs. 1st quartile |
Alternate
Mediterranean Diet (aMED) |
0.70 (0.52–0.95) |
4th vs. 1st quartile |
Dietary Approaches to Stop Hypertension (DASH) |
0.67 (0.51–0.87) |
4th vs. 1st quartile |
Yang W., 2021 [7] | Yang W., 2021 [8] |
Prospective cohort |
Nurses’ Health Study ( | n | =70,055 women). Health Professionals Follow-up Study ( | n | = 49,261 men) |
Empirical
lifestyle pattern score for hyperinsulinemia (ELIH) |
1.89 (1.25–2.87) |
3rd vs. 1st tertile |
Empirical
lifestyle pattern score for insulin
resistance (ELIR) |
2.05 (1.34–3.14) |
3rd vs. 1st tertile |
Empirical dietary inflammatory pattern (EDIP) |
2.03 (1.31–3.16) |
3rd vs. 1st tertile |
Ji XW., 2021 [8] | Ji XW., 2021 [9] |
Prospective cohort |
Chinese men ( | n | = 59 998) |
Total fat |
1.33 (1.01–1.75) |
4th vs. 1st quartile |
Saturated fat |
1.50 (1.13–1.97) |
4th vs. 1st quartile |
Monounsaturated fat |
1.26 (0.96–1.65) |
4th vs. 1st quartile |
Polyunsaturated fat |
1.41 (1.07–1.86) |
4th vs. 1st quartile |
Luo Y., 2020 [9] | Luo Y., 2020 [10] |
Prospective cohort |
Patients with new HCC enrolled in the Guangdong Liver Cancer Cohort ( | n | = 887) |
Chinese Healthy Eating Index (CHEI-2016) |
0.74 (0.56–0.98)
Outcome: HCC specific mortality |
3rd vs. 1st tertile |
Healthy Eating Index-2015 (HEI-2015) |
0.93 (0.71–1.21)
Outcome: HCC specific mortality |
3rd vs. 1st tertile |
Zhong GC., 2020 [10] | Zhong GC., 2020 [11] |
Prospective cohort |
American adults from the prostate, lung, colorectal and ovarian
cancer screening trial ( | n | = 103,902) |
Dietary inflammatory index (DII) from food and supplements |
2.05 (1.23–3.41)
Outcome: PLC incidence |
3rd vs. 1st tertile |
Dietary inflammatory index (DII) from food and supplements |
1.97 (1.13–3.41)
Outcome: PLC mortality ( | n | = 102) |
3rd vs. 1st tertile |
Dietary inflammatory index (DII) from food only |
2.57 (1.44–4.60)
Outcome: PLC incidence |
3rd vs. 1st tertile |
Jayedi A., 2020 [11] | Jayedi A., 2020 [12] |
Umbrella Review of Meta-Analyses of Prospective Cohort Studies (5 Meta-analyses) |
Mixed populations |
Fish |
0.65 (0.48–0.87) |
per 100 gr/day |
Zhong GC., 2020 [12] | Zhong GC., 2020 [13] |
Prospective cohort |
American adults from the prostate, lung, colorectal and ovarian
cancer screening trial ( | n | = 104,025) |
Magnesium (diet + supplements) |
0.44 (0.24–0.80)
Outcome: PLC incidence |
3rd vs. 1st tertile |
Magnesium (diet + supplements) |
0.83 (0.67–1.01)
Outcome: PLC incidence |
Per 100 mg/d |
Dietary magnesium |
0.41 (0.22–0.76)
Outcome: PLC incidence |
3rd vs. 1st tertile |
Dietary magnesium |
0.65 (0.51–0.82)
Outcome: PLC incidence |
Per 100 mg/d |
Magnesium (diet + supplements) |
0.37 (0.19–0.71)
Outcome: PLC mortality |
3rd vs. 1st tertile |
Yang W., 2020 [13] | Yang W., 2020 [14] |
Prospective cohort |
Nurses’ Health Study ( | n | =88,657 women). Health Professionals Follow-up Study ( | n | = 49,826 men) |
Vegetable fats |
0.61 (0.39–0.96) |
17.7 vs. 8.7 (% energy) |
n-3 PUFA |
0.63 (0.41–0.96) |
0.8 vs. 0.5 (% energy) |
n-6 PUFA |
0.54 (0.34–0.86) |
6.5 vs. 3.7 (% energy) |
Yang W., 2020 [14] | Yang W., 2020 [15] |
Prospective cohort |
Nurses’ Health Study ( | n | = 93,427 women). Health Professionals Follow-up Study ( | n | = 51,418 men) |
High-fat dairy |
1.81 (1.19–2.76) |
2.0 vs. 0.4 serving/day |
Low-fat dairy |
1.18 (0.78, 1.78) |
1.9 vs. 0.2 serving/day |
Butter |
1.58 (1.06–2.36) |
0.7 vs. 0 serving/day |
Yogurt |
0.72 (0.49–1.05) |
0.2 vs. 0 serving/day |
Kim TL., 2020 [15] | Kim TL., 2020 [16] |
Umbrella Review of Meta-analyses of observational studies (2) |
Mixed populations |
Green tea |
0.87 (0.78–0.98) |
High vs. low |
Guo XF., 2019 [16] | Guo XF., 2019 [17] |
Meta-analysis (9 cohorts) |
1,326,176 participants |
Vegetable |
0.96 (0.95–0.97) |
Per 100 gr/d |
Ma Y., 2019 [17] | Ma Y., 2019 [18] |
Prospective cohort |
Nurses’ Health Study ( | n | = 92,389 women). Health Professionals Follow-up Study ( | n | = 50,468 men). |
Processed red meat |
1.84 (1.16–2.92) |
3rd vs. 1st tertile |
Total white meat |
0.61 (0.40–0.91) |
3rd vs. 1st tertile |
Unprocessed red meat |
1.06 (0.68–1.63) |
3rd vs. 1st tertile |
Poultry |
0.60 (0.40–0.90) |
3rd vs. 1st tertile |
Fish |
0.70 (0.47–1.05) |
3rd vs. 1st tertile |
Ma Y., 2019 [18] | Ma Y., 2019 [19] |
Prospective cohort |
Nurses’ Health Study ( | n | = 121,700 women). Health Professionals Follow-up Study ( | n | = 51,529 men) |
Alternative Healthy Eating Index-2010 (AHEI-2010) |
0.61 (0.39–0.95) |
3rd vs. 1st tertile |
Tran KT., (2019) [19] | Tran KT., (2019) [20] |
Prospective cohort |
UK Biobank population ( | n | = 471,779) |
Coffee |
0.50 (0.29–0.87) |
Any consumption vs. none |
Instant coffee |
0.51 (0.28–0.93) |
Any consumption vs. none |
Ground coffee |
0.47 (0.20–1.08) |
Any consumption vs. none |
Kennedy OJ., 2017 [20] | Kennedy OJ., 2017 [21] |
Meta-analysis (18 cohorts) |
Mixed populations, 2,272,642 participants |
Coffee |
0.71 (0.65–0.77) |
An extra two cups per day |
2 cohorts |
Approximately 850,000 participants |
Caffeinated coffee |
0.73 (0.63–0.85) |
An extra two cups per day |
3 cohorts |
Approximately 750,000 participants |
Decaffeinated coffee |
0.86 (0.74–1.00) |
An extra two cups per day |
Gao M., 2015 [21] | Gao M., 2015 [22] |
Meta-analysis (3 cohorts) |
Mixed populations, 693,274 participants |
Fish |
0.73 (0.56–0.90) |
Highest vs. lowest consumption |
Yang Y., 2014 [22] | Yang Y., 2014 [23] |
Meta-analysis (9 cohorts) |
Mixed populations, 1,474,309 participants |
Vegetables |
0.66 (0.51–0.86) |
Highest vs. lowest consumption |
Luo J., 2014 [23] | Luo J., 2014 [24] |
Meta-analysis
(7 cohorts) |
Mixed populations, 2,677,514 participants |
Red meat |
1.43 (1.08–1.90) |
Highest vs. lowest consumption |
White meat |
0.70 (0.57–0.86) |
Highest vs. lowest consumption |
Fish |
0.74 (0.61–0.91) |
Highest vs. lowest consumption |
Bravi F., 2013, [24] | Bravi F., 2013, [25] |
Meta-analysis (8 cohorts) |
Mixed populations, 378,392 participants |
Coffee |
0.64 (0.52–0.7) |
No consumption vs. any consumption |
Fedirko V., 2013 [25] | Fedirko V., 2013 [26] |
Cohort |
European Prospective Investigation into Cancer and
Nutrition cohort ( | n | = 477,206) |
Total sugar |
1.43 (1.17–1.74) |
Per 50 gr/day |
Total dietary fiber |
0.70 (0.52–0.93) |
Per 10 gr/day |
Sawada N., 2012 [26] | Sawada N., 2012 [27] |
Prospective cohort |
Population-based prospective cohort of Japanese subjects
( | n | = 90,296) |
Fish (rich in n-3 PUFA) |
0.64 (0.42–0.96) |
70.6 vs. 9.6 gr/day |
EPA |
0.56 (0.36–0.85) |
0.74 vs. 0.14 g/day |
DHA |
0.56 (0.35–0.87) |
1.19 vs. 0.28 g/day |
Freedman ND., 2010 [27] | Freedman ND., 2010 [28] |
Cohort |
Men and women of the National Institutes of Health–AARP Diet and Health Study ( | n | = 495,006) |
White meat |
0.52 (0.36–0.77) |
65.8 vs. 9.7 g/1000 kcal |
Red meat |
1.74 (1.16–2.61) |
64.8 vs. 10 g/1000 kcal |
Ioannou GN., 2009 [28] | Ioannou GN., 2009 [29] |
Cohort |
General US population from the first National Health and Nutrition Examination Survey ( | n | = 9221) |
Cholesterol |
2.45 (1.3–4.7) |
≥511 vs. <156 mg/d |