Liver cancer remains a global health challenge, and while infection by hepatitis B virus and hepatitis C virus are the main risk factors for hepatocellular carcinoma (HCC) development, non-alcoholic steatohepatitis is associated with metabolic syndrome or diabetes mellitus is becoming a more frequent risk factor [1].
Author, Year of Publication (Ref) | Study Design Cohort Study/Meta-Analysis of Cohort Studies |
Study Population and Sample Size | Nutrient/Food Group | Adjusted HR/RR (CI) of Highest Category vs. Lowest Category | Nutrient/Food Intake Categories Which Were Compared (Highest Category vs. Reference Category) |
---|---|---|---|---|---|
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 [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 [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 [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 [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 [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 [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 [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 [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 [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 [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 [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 [17] | Meta-analysis (9 cohorts) | 1,326,176 participants | Vegetable | 0.96 (0.95–0.97) | Per 100 gr/d |
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 [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) [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 [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 [22] | Meta-analysis (3 cohorts) | Mixed populations, 693,274 participants | Fish | 0.73 (0.56–0.90) | Highest vs. lowest consumption |
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 [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, [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 [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 [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 [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 [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 |
This entry is adapted from the peer-reviewed paper 10.3390/cancers14010103