Fatty acids play an essential role in health. Studies have shown that diets high in omega-3 fatty acids found in foods like fish, fish oil, flaxseed and walnuts may be beneficial. Yet some studies have raised concern that too many omega-6 fatty acids in Western diets rich in vegetable oils may be harmful. Some scientists have proposed that the balance of omega-3 and omega-6 in diets is vital to health. They hypothesize that a higher omega-6 to omega-3 fatty acids ratio is detrimental.

But, proving that a higher ratio of omega-6 to omega-3 fatty acids is harmful has been difficult. Many studies have found conflicting results. Scientists have struggled to accurately measure fatty acid intake as tracking an individual’s dietary intake is challenging and self-reported dietary intake may be incorrect. Additionally, scientists must follow individuals for many years to determine if a high ratio of omega-6 to omega-3 is linked with cancer, heart disease, or death. But, measuring circulating fatty acids in an individual’s blood may offer an easier and more reliable approach to studying the health impacts of these vital nutrients.

Zhang et al. show that people with higher ratios of omega-6 to omega-3 fatty acids in their blood are at greater risk of dying from cancer, heart disease, or any cause than those with lower ratios. The experiments measured omega-6 and omega-3 fatty acid levels in more than 85,000 participants in the UK Biobank who scientists followed for an average of about 13 years. Participants with the highest ratios of omega-6 to omega-3 fatty acids were 26% more likely to die of any cause, 14% more likely to die of cancer, and 31% more likely to die of heart disease than individuals with the lowest ratios. Individually, high levels of omega-6 fatty acids and high levels of omega-3 fatty acids were both associated with a lower risk of dying. But the protective effects of omega-3 were greater. For example, individuals with the highest levels of omega-6 fatty acids were 23% less likely to die of any cause. By comparison, those with the highest levels of omega-3s were 31% less likely to die. The stronger protection offered by high levels of omega-3s likely explains why having a high ratio of omega-6s to omega-3s was linked to harm. Both are protective. But the protection provided by omega-3s is more robust.

The experiments support dietary interventions to raise omega-3 fatty acid levels and maintain a low omega-6 to omega-3 fatty acid ratio to prevent early deaths from cancer, heart disease or other causes. More research is needed to understand the impact of dietary fatty acid intake on other diseases and how genetics may influence the health impact of fatty acids.

Cancer and cardiovascular disease (CVD) are the two leading causes of non-communicable disease mortality globally (Vos et al., 2020). Substantial epidemiologic evidence has linked the dietary or circulating levels of omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) to the risk of all-cause, cancer, and CVD mortality (Supplementary file 1 Table S1). However, the results are inconsistent, especially for omega-6 PUFAs. Most large observational studies support the inverse associations between omega-3 PUFAs and mortality. In addition to total and individual omega-3 PUFAs, the omega-3 index, defined as the percentage of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in total fatty acids in red blood cells, was shown to be a validated biomarker of the dietary intake and tissue levels of long-chain omega-3 PUFAs, and was proposed to be a risk factor for CVD and related mortality (Harris, 2009; Harris and Von Schacky, 2004). While the omega-3 index has been observed to be inversely associated with all cause-mortality, its association patterns with CVD and cancer mortality are less clear (Harris et al., 2017; Harris et al., 2018; Kleber et al., 2016). Most importantly, results from clinical trials of omega-3 PUFA supplementation have been inconsistent (Bhatt et al., 2019; Nicholls et al., 2020). On the other hand, while some studies revealed inverse associations of omega-6 PUFAs with all-cause mortality (Delgado et al., 2017; Marklund et al., 2019; Wu et al., 2014), others reported null results (Harris et al., 2017; Harris et al., 2020; Miura et al., 2016; Otsuka et al., 2019; Zhuang et al., 2019). The role of omega-6 PUFAs in cancer and CVD mortality is less studied, and the patterns are similarly conflicting (Harris et al., 2017; Delgado et al., 2017; Marklund et al., 2019; Wu et al., 2014). Interpreting previous observational results is challenging due to the limitations of small sample sizes, insufficient adjustments for confounding, and unique sample characteristics. Moreover, many studies rely on self-reported dietary intake or fish oil supplementation status, which are subject to large variability and reporting bias (Shim et al., 2014). Despite the tremendous interest and research effort, the roles of omega-3 and omega-6 PUFAs in all-cause and cause-specific mortality remain uncertain.

It has been suggested that the high omega-6/omega-3 ratio in Western diets, 20:1 or even higher, as compared to an estimated 1:1 during the most time of human evolution, contributes to many chronic diseases, including CVD, cancer, and autoimmune disorders (Simopoulos, 2001; Simopoulos, 2008). However, while many previous studies have examined total or individual omega-3 and omega-6 PUFAs, fewer investigated the role of their imbalance, as measured by the omega-6/omega-3 ratio, in mortality (Harris et al., 2017; Otsuka et al., 2019; Zhuang et al., 2019; Noori et al., 2011). In a prospective cohort study of postmenopausal women, the omega-6/omega-3 ratio in red blood cells was associated with an increased risk of all-cause mortality but not with cancer or CVD mortality (Harris et al., 2017). Similar positive associations with all-cause mortality were observed in smaller cohorts investigating the ratio in serum or dietary intake (Otsuka et al., 2019; Noori et al., 2011). However, prospective studies in two independent cohorts from China and US did not find a linear positive association between the omega-6/omega-3 ratio in diet and all-cause mortality (Zhuang et al., 2019). To address these gaps in our understanding of the roles of omega-3 and omega-6 PUFAs and their imbalance in all-cause and cause-specific mortality, we perform a prospective study in a large population-based cohort (N=85,425) from UK Biobank, using objective measurements of PUFA levels in plasma.

In this prospective population-based study of UK individuals, we showed that a higher ratio of plasma omega-6/omega-3 fatty acids was positively associated with the risk of all-cause, cancer, and CVD mortality. These associations were independent of most risk factors examined, including age, sex, TDI, BMI, comorbidities, and physical activity, but they were stronger in current smokers. These relationships were linear for cancer mortality but not for all-cause and CVD mortality. For those two outcomes, the risk of mortality first decreased at lower ratios and then increased, with an inflection point around the ratio of 8. Moreover, omega-3 and omega-6 PUFAs in plasma were consistently and inversely associated with all-cause, cancer, and CVD mortality, with omega-3 showing stronger effects.

To date, studies that examined the relationship between the ratio of omega-6/omega-3 PUFAs and mortality in the general population are sparse (Harris et al., 2017; Otsuka et al., 2019; Zhuang et al., 2019; Noori et al., 2011). Similar to our finding, in a 2017 report from a prospective women cohort study (n=6501; 1875 all-cause deaths, 617 CVD deaths, 462 cancer deaths) (Harris et al., 2017), the adjusted HR for all-cause mortality was 1.10 (1.02–1.19) per 1-SD increase of omega-6/omega-3 ratio in red blood cells; however, the effects were not significant for cancer and CVD deaths. Another study supporting our results was conducted on elderly Japanese individuals (n=1054; 422 deaths). It found that the ratio of an omega-3 fatty acid, EPA, to an omega-6 fatty acid, arachidonic acid (ARA), is inversely associated with all-cause mortality, with an HR of 0.71 (95% 0.53–0.96) comparing the highest to the lowest tertile (Otsuka et al., 2019). Findings of previous studies based on dietary intake were null (Zhuang et al., 2019; Noori et al., 2011). A prospective cohort involving 145 hemodialysis patients enrolled in Southern California during 2001–2007 (42 all-cause deaths) showed that the estimated HR (95% CI) for all-cause mortality among those in the lowest relative to the highest quartiles of dietary omega-6/omega-3 ratio was 0.37 (0.14–1.08) (Noori et al., 2011). Although the effect was not significant, it still shows the protective trend of a lower omega-6/omega-3 ratio against premature death, when taking the sample size and study population into consideration. In a 2019 report based on two population-based prospective cohorts in China (n=14,117, 1007 all-cause deaths) and the US (n=36,032, 4826 all-cause deaths), the effect of the omega-6/omega-3 ratio intake was not significant (HR (95% CI) is 0.95 (0.80–1.14) for China and 0.99 (0.89–1.11) for US, respectively) (Zhuang et al., 2019). These discrepancies may be explained by the usage of circulating biomarkers or dietary intakes for calculating the omega-6/omega-3 ratio. Indeed, we performed the same association analyses for dietary PUFAs and found that their associations with mortality have smaller effect sizes and are less statistically significant, although maintaining the same effect directions as plasma PUFAs. The estimated dietary intakes may be inaccurate due to recall bias or outdated food databases (Shim et al., 2014). The circulating level is a more objective measurement of PUFA status and thus provides a more reliable picture of the effects of omega-3 and omega-6 PUFAs on mortality. Additionally, we observed that the omega-6/omega-3 ratio tends to have stronger effects on mortality outcomes in current smokers. This is consistent with a previous observation that the association between habitual fish oil supplementation and a lower risk of all-cause mortality is stronger in current smokers (Li et al., 2020). Moreover, we found that current smokers in UK Biobank tend to have higher omega-6/omega-3 ratios. Similarly, prior studies reported that current smokers have lower circulating omega-3 PUFAs than non-smokers but similar circulating levels of omega-6 PUFAs (Murff et al., 2016; Scaglia et al., 2016). It is likely that omega-3 PUFAs play more important roles in current smokers, resulting in a stronger effect of the omega-6/omega-3 ratio on mortality. However, the underlying mechanism awaits future investigations.

A large number of existing observational studies documented the inverse association of circulating levels and intake of omega-3 PUFAs with mortality (Harris et al., 2018; Kleber et al., 2016; Zhang et al., 2018; Chen et al., 2016; Eide et al., 2016; Harris et al., 2021; Lee et al., 2009; Lindberg et al., 2008; Pertiwi et al., 2021), which is in line with our finding that individuals in the highest quintile of the plasma omega-3% had approximately 30% lower risk for all-cause and CVD mortality and 25% lower risk for cancer mortality, when compared to those in the lowest quintile. Our analysis of dietary omega-3% also revealed inverse associations with all-cause and cancer mortality, with 9% and 18% lower risk, respectively. Few previous studies have examined the association in generally healthy populations (Harris et al., 2018; Zhang et al., 2018; Chen et al., 2016; Harris et al., 2021). In a 2016 meta-analysis (Chen et al., 2016) of seven epidemiologic studies for dietary omega-3 PUFAs intake and four studies for circulating levels, the estimated relative risk for all-cause mortality was 0.91 (95% CI: 0.84–0.98) when comparing the highest to the lowest categories of omega-3 PUFA intake. In two 2018 reports of population-based studies in the US, the circulating level and dietary intake of omega-3 PUFAs were significantly associated with lower total mortality (Harris et al., 2018; Zhang et al., 2018). In a 2021 meta-analysis of 17 epidemiologic studies, comparing the highest to the lowest quintiles of circulating EPA and DHA, the estimated HRs for all-cause, CVD, and cancer mortality were 0.84 (0.79–0.89), 0.80 (0.73–0.88), and 0.87 (0.78–0.96), respectively (Harris et al., 2021). Moreover, inverse associations of omega-3 PUFAs biomarkers with total mortality were found in patients with myocardial infarction (Lee et al., 2009; Pertiwi et al., 2021), type 2 diabetes (Harris et al., 2020), and other diseases (Kleber et al., 2016; Eide et al., 2016; Lindberg et al., 2008; Pottala et al., 2010); inverse associations of omega-3 PUFAs with CVD mortality were also reported in these patient groups (Kleber et al., 2016; Harris et al., 2020; Pertiwi et al., 2021). However, there are also reports of a null relationship between omega-3 PUFAs and mortality (Miura et al., 2016; Otsuka et al., 2019; Miura et al., 2018). One possible explanation for the discrepancies could be the limited statistical power due to the small sample size and the small number of events. Moreover, the inconsistency may be due to unique sample characteristics; one study only involved elder patients (Otsuka et al., 2019), and one only involved women (Miura et al., 2018).

A smaller number of studies have evaluated the associations of omega-6 PUFAs with mortality. Our findings in the large UK prospective cohort are in accordance with the results of several previous studies that increased circulating levels of omega-6 PUFAs were associated with decreased all-cause mortality (Delgado et al., 2017; Wu et al., 2014; Zhuang et al., 2019; Warensjö et al., 2008). Moreover, a 2019 meta-analysis involving 18 cohort studies and 12 case-control studies showed that an omega-6 PUFA, linoleic acid, was inversely associated with CVD mortality; the HR per interquintile range was 0.78 (95% CI, 0.70–0.85) (Marklund et al., 2019). Other studies, however, did not support such inverse associations (Harris et al., 2017; Harris et al., 2020; Miura et al., 2016; Otsuka et al., 2019; Miura et al., 2018). Although the findings were inconsistent, no previous studies reported harmful effects of omega-6 PUFAs on mortality (Harris et al., 2017; Wu et al., 2014; Harris et al., 2020; Miura et al., 2016; Otsuka et al., 2019; Zhuang et al., 2019; Miura et al., 2018; Warensjö et al., 2008; de Lorgeril et al., 1994; Petrone et al., 2013). Our studies support the inverse associations between omega-6 PUFAs and all-cause and cause-specific mortality. Further research is needed to investigate the health impacts of omega-6 PUFAs in laboratory studies, epidemiological investigations, and clinical trials.

We observed that the omega-6/omega-3 ratio is positively, while both of its numerator and denominator, omega-6% and omega-3%, are negatively associated with mortality. Our findings support that both omega-6 and omega-3 PUFAs are protective against death and that the positive associations of the omega-6/omega-3 ratio with mortality outcomes are likely due to the stronger effects of omega-3 than omega-6 PUFAs. Our mediation analysis with clinical biomarkers for CVD and cancer revealed that CRP and SHBG partially medicated the effects of the omega-6/omega-3 ratio on all-cause mortality. However, the proportions mediated are relatively small (~5%), suggesting the presence of direct effects or unexamined factors. Our findings call for future studies that evaluate the utility and investigate the mechanisms of the omega-6/omega-3 ratio.

Strengths of our current study include the use of objective PUFA biomarkers in plasma instead of the estimated intakes from dietary questionnaires, which increases the accuracy of exposure assessment. Moreover, the prospective population-based study design, large sample size, long duration of follow-up, and detailed information on potential confounding variables, substantially mitigate the possible complications from reverse causality and confounding bias. In several sensitivity analyses, most of the documented associations remain materially unchanged, indicating the robustness of our results.

Several potential limitations deserve attention. First, plasma omega-3 and omega-6 PUFAs were measured only once at baseline. Their levels may vary with diet or other lifestyle factors, which could cause misclassification over follow-up. However, some studies demonstrated that multiple measurements of omega-3 PUFAs have been consistent for a 6-month period (Kobayashi et al., 2001). Moreover, the 13 year within-person correlation for circulating omega-6 PUFAs was comparable to such correlations for other major CVD risk factors (Clarke et al., 1999) Thus, the single measurement of PUFAs at baseline, although not perfect, provides us with adequate information to investigate the relative long-term effects. Second, although we adjusted for many potential confounders in the model, we cannot rule out the imprecisely measured and unmeasured factors. Third, we acknowledged that the cohort did not mirror the broader UK demographic in terms of socioeconomic and health profiles. Participants in the UK Biobank generally exhibited better health and higher socioeconomic status than the average UK resident, potentially influencing the disease prevalence and incidence rates. Nonetheless, the UK Biobank’s extensive sample size and comprehensive exposure data enable the generation of valuable estimates for exposure-disease associations. These estimates have been corroborated by findings from more demographically representative cohorts (Batty et al., 2020; Fry et al., 2017). Last, although we included individuals of different ancestries in the analysis, over 90% of the participants were of European ancestry. The generalizability of our findings across ancestries requires future verification.

The datasets analyzed during the current study are available from the UK Biobank through an application process (http://www.ukbiobank.ac.uk/). R scripts were deposited on GitHub (copy archived at Zhang, 2024).

1. 1. Batty GD
   2. Gale CR
   3. Kivimäki M
   4. Deary IJ
   5. Bell S

   (2020) Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

   BMJ 368:m131.

   https://doi.org/10.1136/bmj.m131

   • PubMed
   • Google Scholar
2. 1. Bhatt DL
   2. Steg PG
   3. Miller M
   4. Brinton EA
   5. Jacobson TA
   6. Ketchum SB
   7. Doyle RT
   8. Juliano RA
   9. Jiao L
   10. Granowitz C
   11. Tardif JC
   12. Ballantyne CM
   13. REDUCE-IT Investigators

   (2019) Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia

   The New England Journal of Medicine 380:11–22.

   https://doi.org/10.1056/NEJMoa1812792

   • PubMed
   • Google Scholar
3. 1. Chen GC
   2. Yang J
   3. Eggersdorfer M
   4. Zhang W
   5. Qin LQ

   (2016) N-3 long-chain polyunsaturated fatty acids and risk of all-cause mortality among general populations: a meta-analysis

   Scientific Reports 6:28165.

   https://doi.org/10.1038/srep28165

   • PubMed
   • Google Scholar
4. 1. Chua ME
   2. Sio MCD
   3. Sorongon MC
   4. Dy JS

   (2012) Relationship of dietary intake of omega-3 and omega-6 Fatty acids with risk of prostate cancer development: a meta-analysis of prospective studies and review of literature

   Prostate Cancer 2012:826254.

   https://doi.org/10.1155/2012/826254

   • PubMed
   • Google Scholar
5. 1. Clarke R
   2. Shipley M
   3. Lewington S
   4. Youngman L
   5. Collins R
   6. Marmot M
   7. Peto R

   (1999) Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies

   American Journal of Epidemiology 150:341–353.

   https://doi.org/10.1093/oxfordjournals.aje.a010013

   • PubMed
   • Google Scholar
6. 1. Delgado GE
   2. März W
   3. Lorkowski S
   4. von Schacky C
   5. Kleber ME

   (2017) Omega-6 fatty acids: Opposing associations with risk-The Ludwigshafen Risk and Cardiovascular Health Study

   Journal of Clinical Lipidology 11:1082–1090.

   https://doi.org/10.1016/j.jacl.2017.05.003

   • PubMed
   • Google Scholar
7. 1. de Lorgeril M
   2. Renaud S
   3. Mamelle N
   4. Salen P
   5. Martin JL
   6. Monjaud I
   7. Guidollet J
   8. Touboul P
   9. Delaye J

   (1994) Mediterranean alpha-linolenic acid-rich diet in secondary prevention of coronary heart disease

   Lancet 343:1454–1459.

   https://doi.org/10.1016/s0140-6736(94)92580-1

   • PubMed
   • Google Scholar
8. 1. Durrleman S
   2. Simon R

   (1989) Flexible regression models with cubic splines

   Statistics in Medicine 8:551–561.

   https://doi.org/10.1002/sim.4780080504

   • PubMed
   • Google Scholar
9. 1. Eide IA
   2. Dahle DO
   3. Svensson M
   4. Hartmann A
   5. Åsberg A
   6. Bjerve KS
   7. Christensen JH
   8. Schmidt EB
   9. Lauritsen ME
   10. Lund K
   11. Jenssen T

   (2016) Plasma levels of marine n-3 fatty acids and cardiovascular risk markers in renal transplant recipients

   European Journal of Clinical Nutrition 70:824–830.

   https://doi.org/10.1038/ejcn.2016.14

   • PubMed
   • Google Scholar
10. 1. Fry A
    2. Littlejohns TJ
    3. Sudlow C
    4. Doherty N
    5. Adamska L
    6. Sprosen T
    7. Collins R
    8. Allen NE

    (2017) Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population

    American Journal of Epidemiology 186:1026–1034.

    https://doi.org/10.1093/aje/kwx246

    • PubMed
    • Google Scholar
11. 1. Groothuis-Oudshoorn K

    (2011) mice: multivariate imputation by chained equations in R

    Journal of Statistical Software 45:1–67.

    https://doi.org/10.18637/jss.v045.i03

    • Google Scholar
12. 1. Harris WS
    2. Von Schacky C

    (2004) The Omega-3 Index: a new risk factor for death from coronary heart disease?

    Preventive Medicine 39:212–220.

    https://doi.org/10.1016/j.ypmed.2004.02.030

    • PubMed
    • Google Scholar
13. 1. Harris WS

    (2009) The omega-3 index: from biomarker to risk marker to risk factor

    Current Atherosclerosis Reports 11:411–417.

    https://doi.org/10.1007/s11883-009-0062-2

    • PubMed
    • Google Scholar
14. 1. Harris WS
    2. Luo J
    3. Pottala JV
    4. Espeland MA
    5. Margolis KL
    6. Manson JE
    7. Wang L
    8. Brasky TM
    9. Robinson JG

    (2017) Red blood cell polyunsaturated fatty acids and mortality in the Women’s Health Initiative Memory Study

    Journal of Clinical Lipidology 11:250–259.

    https://doi.org/10.1016/j.jacl.2016.12.013

    • PubMed
    • Google Scholar
15. 1. Harris WS
    2. Tintle NL
    3. Etherton MR
    4. Vasan RS

    (2018) Erythrocyte long-chain omega-3 fatty acid levels are inversely associated with mortality and with incident cardiovascular disease: The Framingham Heart Study

    Journal of Clinical Lipidology 12:718–727.

    https://doi.org/10.1016/j.jacl.2018.02.010

    • PubMed
    • Google Scholar
16. 1. Harris K
    2. Oshima M
    3. Sattar N
    4. Würtz P
    5. Jun M
    6. Welsh P
    7. Hamet P
    8. Harrap S
    9. Poulter N
    10. Chalmers J
    11. Woodward M

    (2020) Plasma fatty acids and the risk of vascular disease and mortality outcomes in individuals with type 2 diabetes: results from the ADVANCE study

    Diabetologia 63:1637–1647.

    https://doi.org/10.1007/s00125-020-05162-z

    • PubMed
    • Google Scholar
17. 1. Harris WS
    2. Tintle NL
    3. Imamura F
    4. Qian F
    5. Korat AVA
    6. Marklund M
    7. Djoussé L
    8. Bassett JK
    9. Carmichael PH
    10. Chen YY
    11. Hirakawa Y
    12. Küpers LK
    13. Laguzzi F
    14. Lankinen M
    15. Murphy RA
    16. Samieri C
    17. Senn MK
    18. Shi P
    19. Virtanen JK
    20. Brouwer IA
    21. Chien KL
    22. Eiriksdottir G
    23. Forouhi NG
    24. Geleijnse JM
    25. Giles GG
    26. Gudnason V
    27. Helmer C
    28. Hodge A
    29. Jackson R
    30. Khaw KT
    31. Laakso M
    32. Lai H
    33. Laurin D
    34. Leander K
    35. Lindsay J
    36. Micha R
    37. Mursu J
    38. Ninomiya T
    39. Post W
    40. Psaty BM
    41. Risérus U
    42. Robinson JG
    43. Shadyab AH
    44. Snetselaar L
    45. Sala-Vila A
    46. Sun Y
    47. Steffen LM
    48. Tsai MY
    49. Wareham NJ
    50. Wood AC
    51. Wu JHY
    52. Hu F
    53. Sun Q
    54. Siscovick DS
    55. Lemaitre RN
    56. Mozaffarian D
    57. Fatty Acids and Outcomes Research Consortium (FORCE)

    (2021) Blood n-3 fatty acid levels and total and cause-specific mortality from 17 prospective studies

    Nature Communications 12:2329.

    https://doi.org/10.1038/s41467-021-22370-2

    • PubMed
    • Google Scholar
18. 1. Julkunen H
    2. Cichońska A
    3. Tiainen M
    4. Koskela H
    5. Nybo K
    6. Mäkelä V
    7. Nokso-Koivisto J
    8. Kristiansson K
    9. Perola M
    10. Salomaa V
    11. Jousilahti P
    12. Lundqvist A
    13. Kangas AJ
    14. Soininen P
    15. Barrett JC
    16. Würtz P

    (2023) Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank

    Nature Communications 14:604.

    https://doi.org/10.1038/s41467-023-36231-7

    • PubMed
    • Google Scholar
19. 1. Kleber ME
    2. Delgado GE
    3. Lorkowski S
    4. März W
    5. von C

    (2016) Omega-3 fatty acids and mortality in patients referred for coronary angiography

    The Ludwigshafen Risk and Cardiovascular Health Study. Atherosclerosis 252:175–181.

    https://doi.org/10.1016/j.atherosclerosis.2016.06.049

    • PubMed
    • Google Scholar
20. 1. Kobayashi M
    2. Sasaki S
    3. Kawabata T
    4. Hasegawa K
    5. Akabane M
    6. Tsugane S

    (2001) Single measurement of serum phospholipid fatty acid as a biomarker of specific fatty acid intake in middle-aged Japanese men

    European Journal of Clinical Nutrition 55:643–650.

    https://doi.org/10.1038/sj.ejcn.1601194

    • PubMed
    • Google Scholar
21. 1. Lapointe-Shaw L
    2. Bouck Z
    3. Howell NA
    4. Lange T
    5. Orchanian-Cheff A
    6. Austin PC
    7. Ivers NM
    8. Redelmeier DA
    9. Bell CM

    (2018) Mediation analysis with a time-to-event outcome: a review of use and reporting in healthcare research

    BMC Medical Research Methodology 18:118.

    https://doi.org/10.1186/s12874-018-0578-7

    • PubMed
    • Google Scholar
22. 1. Lee S-H
    2. Shin M-J
    3. Kim J-S
    4. Ko Y-G
    5. Kang S-M
    6. Choi D
    7. Jang Y
    8. Chung N
    9. Shim W-H
    10. Cho S-Y
    11. Manabe I
    12. Ha J-W

    (2009) Blood eicosapentaenoic acid and docosahexaenoic acid as predictors of all-cause mortality in patients with acute myocardial infarction--data from Infarction Prognosis Study (IPS) Registry

    Circulation Journal 73:2250–2257.

    https://doi.org/10.1253/circj.cj-09-0327

    • PubMed
    • Google Scholar
23. 1. Li Z-H
    2. Zhong W-F
    3. Liu S
    4. Kraus VB
    5. Zhang Y-J
    6. Gao X
    7. Lv Y-B
    8. Shen D
    9. Zhang X-R
    10. Zhang P-D
    11. Huang Q-M
    12. Chen Q
    13. Wu X-B
    14. Shi X-M
    15. Wang D
    16. Mao C

    (2020) Associations of habitual fish oil supplementation with cardiovascular outcomes and all cause mortality: evidence from a large population based cohort study

    BMJ 368:m456.

    https://doi.org/10.1136/bmj.m456

    • PubMed
    • Google Scholar
24. 1. Lindberg M
    2. Saltvedt I
    3. Sletvold O
    4. Bjerve KS

    (2008) Long-chain n-3 fatty acids and mortality in elderly patients

    The American Journal of Clinical Nutrition 88:722–729.

    https://doi.org/10.1093/ajcn/88.3.722

    • PubMed
    • Google Scholar
25. 1. Marklund M
    2. Wu JHY
    3. Imamura F
    4. Del Gobbo LC
    5. Fretts A
    6. de Goede J
    7. Shi P
    8. Tintle N
    9. Wennberg M
    10. Aslibekyan S
    11. Chen T-A
    12. de Oliveira Otto MC
    13. Hirakawa Y
    14. Eriksen HH
    15. Kröger J
    16. Laguzzi F
    17. Lankinen M
    18. Murphy RA
    19. Prem K
    20. Samieri C
    21. Virtanen J
    22. Wood AC
    23. Wong K
    24. Yang W-S
    25. Zhou X
    26. Baylin A
    27. Boer JMA
    28. Brouwer IA
    29. Campos H
    30. Chaves PHM
    31. Chien K-L
    32. de Faire U
    33. Djoussé L
    34. Eiriksdottir G
    35. El-Abbadi N
    36. Forouhi NG
    37. Michael Gaziano J
    38. Geleijnse JM
    39. Gigante B
    40. Giles G
    41. Guallar E
    42. Gudnason V
    43. Harris T
    44. Harris WS
    45. Helmer C
    46. Hellenius M-L
    47. Hodge A
    48. Hu FB
    49. Jacques PF
    50. Jansson J-H
    51. Kalsbeek A
    52. Khaw K-T
    53. Koh W-P
    54. Laakso M
    55. Leander K
    56. Lin H-J
    57. Lind L
    58. Luben R
    59. Luo J
    60. McKnight B
    61. Mursu J
    62. Ninomiya T
    63. Overvad K
    64. Psaty BM
    65. Rimm E
    66. Schulze MB
    67. Siscovick D
    68. Skjelbo Nielsen M
    69. Smith AV
    70. Steffen BT
    71. Steffen L
    72. Sun Q
    73. Sundström J
    74. Tsai MY
    75. Tunstall-Pedoe H
    76. Uusitupa MIJ
    77. van Dam RM
    78. Veenstra J
    79. Monique Verschuren WM
    80. Wareham N
    81. Willett W
    82. Woodward M
    83. Yuan J-M
    84. Micha R
    85. Lemaitre RN
    86. Mozaffarian D
    87. Risérus U
    88. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Fatty Acids and Outcomes Research Consortium (FORCE)

    (2019) Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality

    Circulation 139:2422–2436.

    https://doi.org/10.1161/CIRCULATIONAHA.118.038908

    • PubMed
    • Google Scholar
26. 1. Miura K
    2. Hughes MCB
    3. Ungerer JP
    4. Green AC

    (2016) Plasma eicosapentaenoic acid is negatively associated with all-cause mortality among men and women in a population-based prospective study

    Nutrition Research 36:1202–1209.

    https://doi.org/10.1016/j.nutres.2016.09.006

    • PubMed
    • Google Scholar
27. 1. Miura K
    2. Hughes MCB
    3. Ungerer JPJ
    4. Smith DD
    5. Green AC

    (2018) Absolute versus relative measures of plasma fatty acids and health outcomes: example of phospholipid omega-3 and omega-6 fatty acids and all-cause mortality in women

    European Journal of Nutrition 57:713–722.

    https://doi.org/10.1007/s00394-016-1358-y

    • PubMed
    • Google Scholar
28. 1. Murff HJ
    2. Tindle HA
    3. Shrubsole MJ
    4. Cai Q
    5. Smalley W
    6. Milne GL
    7. Swift LL
    8. Ness RM
    9. Zheng W

    (2016) Smoking and red blood cell phospholipid membrane fatty acids

    Prostaglandins, Leukotrienes, and Essential Fatty Acids 112:24–31.

    https://doi.org/10.1016/j.plefa.2016.08.004

    • PubMed
    • Google Scholar
29. 1. Nicholls SJ
    2. Lincoff AM
    3. Garcia M
    4. Bash D
    5. Ballantyne CM
    6. Barter PJ
    7. Davidson MH
    8. Kastelein JJP
    9. Koenig W
    10. McGuire DK
    11. Mozaffarian D
    12. Ridker PM
    13. Ray KK
    14. Katona BG
    15. Himmelmann A
    16. Loss LE
    17. Rensfeldt M
    18. Lundström T
    19. Agrawal R
    20. Menon V
    21. Wolski K
    22. Nissen SE

    (2020) Effect of High-Dose Omega-3 Fatty Acids vs Corn Oil on Major Adverse Cardiovascular Events in Patients at High Cardiovascular Risk: The STRENGTH Randomized Clinical Trial

    JAMA 324:2268–2280.

    https://doi.org/10.1001/jama.2020.22258

    • PubMed
    • Google Scholar
30. 1. Noori N
    2. Dukkipati R
    3. Kovesdy CP
    4. Sim JJ
    5. Feroze U
    6. Murali SB
    7. Bross R
    8. Benner D
    9. Kopple JD
    10. Kalantar-Zadeh K

    (2011) Dietary Omega-3 Fatty Acid, Ratio of Omega-6 to Omega-3 Intake, Inflammation, and Survival in Long-term Hemodialysis Patients

    American Journal of Kidney Diseases 58:248–256.

    https://doi.org/10.1053/j.ajkd.2011.03.017

    • Google Scholar
31. 1. Otsuka R
    2. Tange C
    3. Nishita Y
    4. Tomida M
    5. Kato Y
    6. Imai T
    7. Ando F
    8. Shimokata H

    (2019) Fish and Meat Intake, Serum Eicosapentaenoic Acid and Docosahexaenoic Acid Levels, and Mortality in Community-Dwelling Japanese Older Persons

    International Journal of Environmental Research and Public Health 16:10.

    https://doi.org/10.3390/ijerph16101806

    • PubMed
    • Google Scholar
32. 1. Perez-Cornago A
    2. Pollard Z
    3. Young H
    4. van Uden M
    5. Andrews C
    6. Piernas C
    7. Key TJ
    8. Mulligan A
    9. Lentjes M

    (2021) Description of the updated nutrition calculation of the Oxford WebQ questionnaire and comparison with the previous version among 207,144 participants in UK Biobank

    European Journal of Nutrition 60:4019–4030.

    https://doi.org/10.1007/s00394-021-02558-4

    • PubMed
    • Google Scholar
33. 1. Pertiwi K
    2. Küpers LK
    3. de Goede J
    4. Zock PL
    5. Kromhout D
    6. Geleijnse JM

    (2021) Dietary and Circulating Long-Chain Omega-3 Polyunsaturated Fatty Acids and Mortality Risk After Myocardial Infarction: A Long-Term Follow-Up of the Alpha Omega Cohort

    Journal of the American Heart Association 10:e022617.

    https://doi.org/10.1161/JAHA.121.022617

    • PubMed
    • Google Scholar
34. 1. Petrone AB
    2. Weir N
    3. Hanson NQ
    4. Glynn R
    5. Tsai MY
    6. Gaziano JM
    7. Djoussé L

    (2013) Omega-6 fatty acids and risk of heart failure in the Physicians’ Health Study

    The American Journal of Clinical Nutrition 97:66–71.

    https://doi.org/10.3945/ajcn.112.048991

    • PubMed
    • Google Scholar
35. 1. Pottala JV
    2. Garg S
    3. Cohen BE
    4. Whooley MA
    5. Harris WS

    (2010) Blood eicosapentaenoic and docosahexaenoic acids predict all-cause mortality in patients with stable coronary heart disease: the Heart and Soul study

    Circulation. Cardiovascular Quality and Outcomes 3:406–412.

    https://doi.org/10.1161/CIRCOUTCOMES.109.896159

    • PubMed
    • Google Scholar
36. 1. Scaglia N
    2. Chatkin J
    3. Chapman KR
    4. Ferreira I
    5. Wagner M
    6. Selby P
    7. Allard J
    8. Zamel N

    (2016) The relationship between omega-3 and smoking habit: a cross-sectional study

    Lipids in Health and Disease 15:61.

    https://doi.org/10.1186/s12944-016-0220-9

    • PubMed
    • Google Scholar
37. 1. Shim JS
    2. Oh K
    3. Kim HC

    (2014) Dietary assessment methods in epidemiologic studies

    Epidemiology and Health 36:e2014009.

    https://doi.org/10.4178/epih/e2014009

    • PubMed
    • Google Scholar
38. 1. Simopoulos AP

    (2001) Evolutionary aspects of diet and essential fatty acids

    World Review of Nutrition and Dietetics 88:18–27.

    https://doi.org/10.1159/000059742

    • PubMed
    • Google Scholar
39. 1. Simopoulos AP

    (2008) The Importance of the Omega-6/Omega-3 fatty acid ratio in cardiovascular disease and other chronic diseases

    Experimental Biology and Medicine 233:674–688.

    https://doi.org/10.3181/0711-MR-311

    • Google Scholar
40. 1. Sudlow C
    2. Gallacher J
    3. Allen N
    4. Beral V
    5. Burton P
    6. Danesh J
    7. Downey P
    8. Elliott P
    9. Green J
    10. Landray M
    11. Liu B
    12. Matthews P
    13. Ong G
    14. Pell J
    15. Silman A
    16. Young A
    17. Sprosen T
    18. Peakman T
    19. Collins R

    (2015) UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age

    PLOS Medicine 12:e1001779.

    https://doi.org/10.1371/journal.pmed.1001779

    • PubMed
    • Google Scholar
41. 1. Valeri L
    2. VanderWeele TJ

    (2015) SAS macro for causal mediation analysis with survival data

    Epidemiology 26:e23–e24.

    https://doi.org/10.1097/EDE.0000000000000253

    • PubMed
    • Google Scholar
42. 1. VanderWeele TJ

    (2011) Causal mediation analysis with survival data

    Epidemiology 22:582–585.

    https://doi.org/10.1097/EDE.0b013e31821db37e

    • PubMed
    • Google Scholar
43. 1. Vos T
    2. Lim SS
    3. Abbafati C
    4. Abbas KM
    5. Abbasi M
    6. Abbasifard M
    7. Abbasi-Kangevari M
    8. Abbastabar H
    9. Abd-Allah F
    10. Abdelalim A
    11. Abdollahi M
    12. Abdollahpour I
    13. Abolhassani H
    14. Aboyans V
    15. Abrams EM
    16. Abreu LG
    17. Abrigo MRM
    18. Abu-Raddad LJ
    19. Abushouk AI
    20. Acebedo A
    21. Ackerman IN
    22. Adabi M
    23. Adamu AA
    24. Adebayo OM
    25. Adekanmbi V
    26. Adelson JD
    27. Adetokunboh OO
    28. Adham D
    29. Afshari M
    30. Afshin A
    31. Agardh EE
    32. Agarwal G
    33. Agesa KM
    34. Aghaali M
    35. Aghamir SMK
    36. Agrawal A
    37. Ahmad T
    38. Ahmadi A
    39. Ahmadi M
    40. Ahmadieh H
    41. Ahmadpour E
    42. Akalu TY
    43. Akinyemi RO
    44. Akinyemiju T
    45. Akombi B
    46. Al-Aly Z
    47. Alam K
    48. Alam N
    49. Alam S
    50. Alam T
    51. Alanzi TM
    52. Albertson SB
    53. Alcalde-Rabanal JE
    54. Alema NM
    55. Ali M
    56. Ali S
    57. Alicandro G
    58. Alijanzadeh M
    59. Alinia C
    60. Alipour V
    61. Aljunid SM
    62. Alla F
    63. Allebeck P
    64. Almasi-Hashiani A
    65. Alonso J
    66. Al-Raddadi RM
    67. Altirkawi KA
    68. Alvis-Guzman N
    69. Alvis-Zakzuk NJ
    70. Amini S
    71. Amini-Rarani M
    72. Aminorroaya A
    73. Amiri F
    74. Amit AML
    75. Amugsi DA
    76. Amul GGH
    77. Anderlini D
    78. Andrei CL
    79. Andrei T
    80. Anjomshoa M
    81. Ansari F
    82. Ansari I
    83. Ansari-Moghaddam A
    84. Antonio CAT
    85. Antony CM
    86. Antriyandarti E
    87. Anvari D
    88. Anwer R
    89. Arabloo J
    90. Arab-Zozani M
    91. Aravkin AY
    92. Ariani F
    93. Ärnlöv J
    94. Aryal KK
    95. Arzani A
    96. Asadi-Aliabadi M
    97. Asadi-Pooya AA
    98. Asghari B
    99. Ashbaugh C
    100. Atnafu DD
    101. Atre SR
    102. Ausloos F
    103. Ausloos M
    104. Ayala Quintanilla BP
    105. Ayano G
    106. Ayanore MA
    107. Aynalem YA
    108. Azari S
    109. Azarian G
    110. Azene ZN
    111. Babaee E
    112. Badawi A
    113. Bagherzadeh M
    114. Bakhshaei MH
    115. Bakhtiari A
    116. Balakrishnan S
    117. Balalla S
    118. Balassyano S
    119. Banach M
    120. Banik PC
    121. Bannick MS
    122. Bante AB
    123. Baraki AG
    124. Barboza MA
    125. Barker-Collo SL
    126. Barthelemy CM
    127. Barua L
    128. Barzegar A
    129. Basu S
    130. Baune BT
    131. Bayati M
    132. Bazmandegan G
    133. Bedi N
    134. Beghi E
    135. Béjot Y
    136. Bello AK
    137. Bender RG
    138. Bennett DA
    139. Bennitt FB
    140. Bensenor IM
    141. Benziger CP
    142. Berhe K
    143. Bernabe E
    144. Bertolacci GJ
    145. Bhageerathy R
    146. Bhala N
    147. Bhandari D
    148. Bhardwaj P
    149. Bhattacharyya K
    150. Bhutta ZA
    151. Bibi S
    152. Biehl MH
    153. Bikbov B
    154. Bin Sayeed MS
    155. Biondi A
    156. Birihane BM
    157. Bisanzio D
    158. Bisignano C
    159. Biswas RK
    160. Bohlouli S
    161. Bohluli M
    162. Bolla SRR
    163. Boloor A
    164. Boon-Dooley AS
    165. Borges G
    166. Borzì AM
    167. Bourne R
    168. Brady OJ
    169. Brauer M
    170. Brayne C
    171. Breitborde NJK
    172. Brenner H
    173. Briant PS
    174. Briggs AM
    175. Briko NI
    176. Britton GB
    177. Bryazka D
    178. Buchbinder R
    179. Bumgarner BR
    180. Busse R
    181. Butt ZA
    182. Caetano dos Santos FL
    183. Cámera LLA
    184. Campos-Nonato IR
    185. Car J
    186. Cárdenas R
    187. Carreras G
    188. Carrero JJ
    189. Carvalho F
    190. Castaldelli-Maia JM
    191. Castañeda-Orjuela CA
    192. Castelpietra G
    193. Castle CD
    194. Castro F
    195. Catalá-López F
    196. Causey K
    197. Cederroth CR
    198. Cercy KM
    199. Cerin E
    200. Chandan JS
    201. Chang AR
    202. Charlson FJ
    203. Chattu VK
    204. Chaturvedi S
    205. Chimed-Ochir O
    206. Chin KL
    207. Cho DY
    208. Christensen H
    209. Chu DT
    210. Chung MT
    211. Cicuttini FM
    212. Ciobanu LG
    213. Cirillo M
    214. Collins EL
    215. Compton K
    216. Conti S
    217. Cortesi PA
    218. Costa VM
    219. Cousin E
    220. Cowden RG
    221. Cowie BC
    222. Cromwell EA
    223. Cross DH
    224. Crowe CS
    225. Cruz JA
    226. Cunningham M
    227. Dahlawi SMA
    228. Damiani G
    229. Dandona L
    230. Dandona R
    231. Darwesh AM
    232. Daryani A
    233. Das JK
    234. Das Gupta R
    235. das Neves J
    236. Dávila-Cervantes CA
    237. Davletov K
    238. De Leo D
    239. Dean FE
    240. DeCleene NK
    241. Deen A
    242. Degenhardt L
    243. Dellavalle RP
    244. Demeke FM
    245. Demsie DG
    246. Denova-Gutiérrez E
    247. Dereje ND
    248. Dervenis N
    249. Desai R
    250. Desalew A
    251. Dessie GA
    252. Dharmaratne SD
    253. Dhungana GP
    254. Dianatinasab M
    255. Diaz D
    256. Dibaji Forooshani ZS
    257. Dingels ZV
    258. Dirac MA
    259. Djalalinia S
    260. Do HT
    261. Dokova K
    262. Dorostkar F
    263. Doshi CP
    264. Doshmangir L
    265. Douiri A
    266. Doxey MC
    267. Driscoll TR
    268. Dunachie SJ
    269. Duncan BB
    270. Duraes AR
    271. Eagan AW
    272. Ebrahimi Kalan M
    273. Edvardsson D
    274. Ehrlich JR
    275. El Nahas N
    276. El Sayed I
    277. El Tantawi M
    278. Elbarazi I
    279. Elgendy IY
    280. Elhabashy HR
    281. El-Jaafary SI
    282. Elyazar IR
    283. Emamian MH
    284. Emmons-Bell S
    285. Erskine HE
    286. Eshrati B
    287. Eskandarieh S
    288. Esmaeilnejad S
    289. Esmaeilzadeh F
    290. Esteghamati A
    291. Estep K
    292. Etemadi A
    293. Etisso AE
    294. Farahmand M
    295. Faraj A
    296. Fareed M
    297. Faridnia R
    298. Farinha CES
    299. Farioli A
    300. Faro A
    301. Faruque M
    302. Farzadfar F
    303. Fattahi N
    304. Fazlzadeh M
    305. Feigin VL
    306. Feldman R
    307. Fereshtehnejad SM
    308. Fernandes E
    309. Ferrari AJ
    310. Ferreira ML
    311. Filip I
    312. Fischer F
    313. Fisher JL
    314. Fitzgerald R
    315. Flohr C
    316. Flor LS
    317. Foigt NA
    318. Folayan MO
    319. Force LM
    320. Fornari C
    321. Foroutan M
    322. Fox JT
    323. Freitas M
    324. Fu W
    325. Fukumoto T
    326. Furtado JM
    327. Gad MM
    328. Gakidou E
    329. Galles NC
    330. Gallus S
    331. Gamkrelidze A
    332. Garcia-Basteiro AL
    333. Gardner WM
    334. Geberemariyam BS
    335. Gebrehiwot AM
    336. Gebremedhin KB
    337. Gebreslassie A
    338. Gershberg Hayoon A
    339. Gething PW
    340. Ghadimi M
    341. Ghadiri K
    342. Ghafourifard M
    343. Ghajar A
    344. Ghamari F
    345. Ghashghaee A
    346. Ghiasvand H
    347. Ghith N
    348. Gholamian A
    349. Gilani SA
    350. Gill PS
    351. Gitimoghaddam M
    352. Giussani G
    353. Goli S
    354. Gomez RS
    355. Gopalani SV
    356. Gorini G
    357. Gorman TM
    358. Gottlich HC
    359. Goudarzi H
    360. Goulart AC
    361. Goulart BNG
    362. Grada A
    363. Grivna M
    364. Grosso G
    365. Gubari MIM
    366. Gugnani HC
    367. Guimaraes ALS
    368. Guimarães RA
    369. Guled RA
    370. Guo G
    371. Guo Y
    372. Gupta R
    373. Haagsma JA
    374. Haddock B
    375. Hafezi-Nejad N
    376. Hafiz A
    377. Hagins H
    378. Haile LM
    379. Hall BJ
    380. Halvaei I
    381. Hamadeh RR
    382. Hamagharib Abdullah K
    383. Hamilton EB
    384. Han C
    385. Han H
    386. Hankey GJ
    387. Haro JM
    388. Harvey JD
    389. Hasaballah AI
    390. Hasanzadeh A
    391. Hashemian M
    392. Hassanipour S
    393. Hassankhani H
    394. Havmoeller RJ
    395. Hay RJ
    396. Hay SI
    397. Hayat K
    398. Heidari B
    399. Heidari G
    400. Heidari-Soureshjani R
    401. Hendrie D
    402. Henrikson HJ
    403. Henry NJ
    404. Herteliu C
    405. Heydarpour F
    406. Hird TR
    407. Hoek HW
    408. Hole MK
    409. Holla R
    410. Hoogar P
    411. Hosgood HD
    412. Hosseinzadeh M
    413. Hostiuc M
    414. Hostiuc S
    415. Househ M
    416. Hoy DG
    417. Hsairi M
    418. Hsieh VC
    419. Hu G
    420. Huda TM
    421. Hugo FN
    422. Huynh CK
    423. Hwang BF
    424. Iannucci VC
    425. Ibitoye SE
    426. Ikuta KS
    427. Ilesanmi OS
    428. Ilic IM
    429. Ilic MD
    430. Inbaraj LR
    431. Ippolito H
    432. Irvani SSN
    433. Islam MM
    434. Islam M
    435. Islam SMS
    436. Islami F
    437. Iso H
    438. Ivers RQ
    439. Iwu CCD
    440. Iyamu IO
    441. Jaafari J
    442. Jacobsen KH
    443. Jadidi-Niaragh F
    444. Jafari H
    445. Jafarinia M
    446. Jahagirdar D
    447. Jahani MA
    448. Jahanmehr N
    449. Jakovljevic M
    450. Jalali A
    451. Jalilian F
    452. James SL
    453. Janjani H
    454. Janodia MD
    455. Jayatilleke AU
    456. Jeemon P
    457. Jenabi E
    458. Jha RP
    459. Jha V
    460. Ji JS
    461. Jia P
    462. John O
    463. John-Akinola YO
    464. Johnson CO
    465. Johnson SC
    466. Jonas JB
    467. Joo T
    468. Joshi A
    469. Jozwiak JJ
    470. Jürisson M
    471. Kabir A
    472. Kabir Z
    473. Kalani H
    474. Kalani R
    475. Kalankesh LR
    476. Kalhor R
    477. Kamiab Z
    478. Kanchan T
    479. Karami Matin B
    480. Karch A
    481. Karim MA
    482. Karimi SE
    483. Kassa GM
    484. Kassebaum NJ
    485. Katikireddi SV
    486. Kawakami N
    487. Kayode GA
    488. Keddie SH
    489. Keller C
    490. Kereselidze M
    491. Khafaie MA
    492. Khalid N
    493. Khan M
    494. Khatab K
    495. Khater MM
    496. Khatib MN
    497. Khayamzadeh M
    498. Khodayari MT
    499. Khundkar R
    500. Kianipour N
    501. Kieling C
    502. Kim D
    503. Kim YE
    504. Kim YJ
    505. Kimokoti RW
    506. Kisa A
    507. Kisa S
    508. Kissimova-Skarbek K
    509. Kivimäki M
    510. Kneib CJ
    511. Knudsen AKS
    512. Kocarnik JM
    513. Kolola T
    514. Kopec JA
    515. Kosen S
    516. Koul PA
    517. Koyanagi A
    518. Kravchenko MA
    519. Krishan K
    520. Krohn KJ
    521. Kuate Defo B
    522. Kucuk Bicer B
    523. Kumar GA
    524. Kumar M
    525. Kumar P
    526. Kumar V
    527. Kumaresh G
    528. Kurmi OP
    529. Kusuma D
    530. Kyu HH
    531. La Vecchia C
    532. Lacey B
    533. Lal DK
    534. Lalloo R
    535. Lam JO
    536. Lami FH
    537. Landires I
    538. Lang JJ
    539. Lansingh VC
    540. Larson SL
    541. Larsson AO
    542. Lasrado S
    543. Lassi ZS
    544. Lau KMM
    545. Lavados PM
    546. Lazarus JV
    547. Ledesma JR
    548. Lee PH
    549. Lee SWH
    550. LeGrand KE
    551. Leigh J
    552. Leonardi M
    553. Lescinsky H
    554. Leung J
    555. Levi M
    556. Lewington S
    557. Li S
    558. Lim LL
    559. Lin C
    560. Lin RT
    561. Linehan C
    562. Linn S
    563. Liu HC
    564. Liu S
    565. Liu Z
    566. Looker KJ
    567. Lopez AD
    568. Lopukhov PD
    569. Lorkowski S
    570. Lotufo PA
    571. Lucas TCD
    572. Lugo A
    573. Lunevicius R
    574. Lyons RA
    575. Ma J
    576. MacLachlan JH
    577. Maddison ER
    578. Maddison R
    579. Madotto F
    580. Mahasha PW
    581. Mai HT
    582. Majeed A
    583. Maled V
    584. Maleki S
    585. Malekzadeh R
    586. Malta DC
    587. Mamun AA
    588. Manafi A
    589. Manafi N
    590. Manguerra H
    591. Mansouri B
    592. Mansournia MA
    593. Mantilla Herrera AM
    594. Maravilla JC
    595. Marks A
    596. Martins-Melo FR
    597. Martopullo I
    598. Masoumi SZ
    599. Massano J
    600. Massenburg BB
    601. Mathur MR
    602. Maulik PK
    603. McAlinden C
    604. McGrath JJ
    605. McKee M
    606. Mehndiratta MM
    607. Mehri F
    608. Mehta KM
    609. Meitei WB
    610. Memiah PTN
    611. Mendoza W
    612. Menezes RG
    613. Mengesha EW
    614. Mengesha MB
    615. Mereke A
    616. Meretoja A
    617. Meretoja TJ
    618. Mestrovic T
    619. Miazgowski B
    620. Miazgowski T
    621. Michalek IM
    622. Mihretie KM
    623. Miller TR
    624. Mills EJ
    625. Mirica A
    626. Mirrakhimov EM
    627. Mirzaei H
    628. Mirzaei M
    629. Mirzaei-Alavijeh M
    630. Misganaw AT
    631. Mithra P
    632. Moazen B
    633. Moghadaszadeh M
    634. Mohamadi E
    635. Mohammad DK
    636. Mohammad Y
    637. Mohammad Gholi Mezerji N
    638. Mohammadian-Hafshejani A
    639. Mohammadifard N
    640. Mohammadpourhodki R
    641. Mohammed S
    642. Mokdad AH
    643. Molokhia M
    644. Momen NC
    645. Monasta L
    646. Mondello S
    647. Mooney MD
    648. Moosazadeh M
    649. Moradi G
    650. Moradi M
    651. Moradi-Lakeh M
    652. Moradzadeh R
    653. Moraga P
    654. Morales L
    655. Morawska L
    656. Moreno Velásquez I
    657. Morgado-da-Costa J
    658. Morrison SD
    659. Mosser JF
    660. Mouodi S
    661. Mousavi SM
    662. Mousavi Khaneghah A
    663. Mueller UO
    664. Munro SB
    665. Muriithi MK
    666. Musa KI
    667. Muthupandian S
    668. Naderi M
    669. Nagarajan AJ
    670. Nagel G
    671. Naghshtabrizi B
    672. Nair S
    673. Nandi AK
    674. Nangia V
    675. Nansseu JR
    676. Nayak VC
    677. Nazari J
    678. Negoi I
    679. Negoi RI
    680. Netsere HBN
    681. Ngunjiri JW
    682. Nguyen CT
    683. Nguyen J
    684. Nguyen M
    685. Nguyen M
    686. Nichols E
    687. Nigatu D
    688. Nigatu YT
    689. Nikbakhsh R
    690. Nixon MR
    691. Nnaji CA
    692. Nomura S
    693. Norrving B
    694. Noubiap JJ
    695. Nowak C
    696. Nunez-Samudio V
    697. Oţoiu A
    698. Oancea B
    699. Odell CM
    700. Ogbo FA
    701. Oh IH
    702. Okunga EW
    703. Oladnabi M
    704. Olagunju AT
    705. Olusanya BO
    706. Olusanya JO
    707. Oluwasanu MM
    708. Omar Bali A
    709. Omer MO
    710. Ong KL
    711. Onwujekwe OE
    712. Orji AU
    713. Orpana HM
    714. Ortiz A
    715. Ostroff SM
    716. Otstavnov N
    717. Otstavnov SS
    718. Øverland S
    719. Owolabi MO
    720. P A M
    721. Padubidri JR
    722. Pakhare AP
    723. Palladino R
    724. Pana A
    725. Panda-Jonas S
    726. Pandey A
    727. Park EK
    728. Parmar PGK
    729. Pasupula DK
    730. Patel SK
    731. Paternina-Caicedo AJ
    732. Pathak A
    733. Pathak M
    734. Patten SB
    735. Patton GC
    736. Paudel D
    737. Pazoki Toroudi H
    738. Peden AE
    739. Pennini A
    740. Pepito VCF
    741. Peprah EK
    742. Pereira A
    743. Pereira DM
    744. Perico N
    745. Pham HQ
    746. Phillips MR
    747. Pigott DM
    748. Pilgrim T
    749. Pilz TM
    750. Pirsaheb M
    751. Plana-Ripoll O
    752. Plass D
    753. Pokhrel KN
    754. Polibin RV
    755. Polinder S
    756. Polkinghorne KR
    757. Postma MJ
    758. Pourjafar H
    759. Pourmalek F
    760. Pourmirza Kalhori R
    761. Pourshams A
    762. Poznańska A
    763. Prada SI
    764. Prakash V
    765. Pribadi DRA
    766. Pupillo E
    767. Quazi Syed Z
    768. Rabiee M
    769. Rabiee N
    770. Radfar A
    771. Rafiee A
    772. Rafiei A
    773. Raggi A
    774. Rahimi-Movaghar A
    775. Rahman MA
    776. Rajabpour-Sanati A
    777. Rajati F
    778. Ramezanzadeh K
    779. Ranabhat CL
    780. Rao PC
    781. Rao SJ
    782. Rasella D
    783. Rastogi P
    784. Rathi P
    785. Rawaf DL
    786. Rawaf S
    787. Rawal L
    788. Razo C
    789. Redford SB
    790. Reiner RC
    791. Reinig N
    792. Reitsma MB
    793. Remuzzi G
    794. Renjith V
    795. Renzaho AMN
    796. Resnikoff S
    797. Rezaei N
    798. Rezai MS
    799. Rezapour A
    800. Rhinehart PA
    801. Riahi SM
    802. Ribeiro ALP
    803. Ribeiro DC
    804. Ribeiro D
    805. Rickard J
    806. Roberts NLS
    807. Roberts S
    808. Robinson SR
    809. Roever L
    810. Rolfe S
    811. Ronfani L
    812. Roshandel G
    813. Roth GA
    814. Rubagotti E
    815. Rumisha SF
    816. Sabour S
    817. Sachdev PS
    818. Saddik B
    819. Sadeghi E
    820. Sadeghi M
    821. Saeidi S
    822. Safi S
    823. Safiri S
    824. Sagar R
    825. Sahebkar A
    826. Sahraian MA
    827. Sajadi SM
    828. Salahshoor MR
    829. Salamati P
    830. Salehi Zahabi S
    831. Salem H
    832. Salem MRR
    833. Salimzadeh H
    834. Salomon JA
    835. Salz I
    836. Samad Z
    837. Samy AM
    838. Sanabria J
    839. Santomauro DF
    840. Santos IS
    841. Santos JV
    842. Santric-Milicevic MM
    843. Saraswathy SYI
    844. Sarmiento-Suárez R
    845. Sarrafzadegan N
    846. Sartorius B
    847. Sarveazad A
    848. Sathian B
    849. Sathish T
    850. Sattin D
    851. Sbarra AN
    852. Schaeffer LE
    853. Schiavolin S
    854. Schmidt MI
    855. Schutte AE
    856. Schwebel DC
    857. Schwendicke F
    858. Senbeta AM
    859. Senthilkumaran S
    860. Sepanlou SG
    861. Shackelford KA
    862. Shadid J
    863. Shahabi S
    864. Shaheen AA
    865. Shaikh MA
    866. Shalash AS
    867. Shams-Beyranvand M
    868. Shamsizadeh M
    869. Shannawaz M
    870. Sharafi K
    871. Sharara F
    872. Sheena BS
    873. Sheikhtaheri A
    874. Shetty RS
    875. Shibuya K
    876. Shiferaw WS
    877. Shigematsu M
    878. Shin JI
    879. Shiri R
    880. Shirkoohi R
    881. Shrime MG
    882. Shuval K
    883. Siabani S
    884. Sigfusdottir ID
    885. Sigurvinsdottir R
    886. Silva JP
    887. Simpson KE
    888. Singh A
    889. Singh JA
    890. Skiadaresi E
    891. Skou ST
    892. Skryabin VY
    893. Sobngwi E
    894. Sokhan A
    895. Soltani S
    896. Sorensen RJD
    897. Soriano JB
    898. Sorrie MB
    899. Soyiri IN
    900. Sreeramareddy CT
    901. Stanaway JD
    902. Stark BA
    903. Ştefan SC
    904. Stein C
    905. Steiner C
    906. Steiner TJ
    907. Stokes MA
    908. Stovner LJ
    909. Stubbs JL
    910. Sudaryanto A
    911. Sufiyan MB
    912. Sulo G
    913. Sultan I
    914. Sykes BL
    915. Sylte DO
    916. Szócska M
    917. Tabarés-Seisdedos R
    918. Tabb KM
    919. Tadakamadla SK
    920. Taherkhani A
    921. Tajdini M
    922. Takahashi K
    923. Taveira N
    924. Teagle WL
    925. Teame H
    926. Tehrani-Banihashemi A
    927. Teklehaimanot BF
    928. Terrason S
    929. Tessema ZT
    930. Thankappan KR
    931. Thomson AM
    932. Tohidinik HR
    933. Tonelli M
    934. Topor-Madry R
    935. Torre AE
    936. Touvier M
    937. Tovani-Palone MRR
    938. Tran BX
    939. Travillian R
    940. Troeger CE
    941. Truelsen TC
    942. Tsai AC
    943. Tsatsakis A
    944. Tudor Car L
    945. Tyrovolas S
    946. Uddin R
    947. Ullah S
    948. Undurraga EA
    949. Unnikrishnan B
    950. Vacante M
    951. Vakilian A
    952. Valdez PR
    953. Varughese S
    954. Vasankari TJ
    955. Vasseghian Y
    956. Venketasubramanian N
    957. Violante FS
    958. Vlassov V
    959. Vollset SE
    960. Vongpradith A
    961. Vukovic A
    962. Vukovic R
    963. Waheed Y
    964. Walters MK
    965. Wang J
    966. Wang Y
    967. Wang YP
    968. Ward JL
    969. Watson A
    970. Wei J
    971. Weintraub RG
    972. Weiss DJ
    973. Weiss J
    974. Westerman R
    975. Whisnant JL
    976. Whiteford HA
    977. Wiangkham T
    978. Wiens KE
    979. Wijeratne T
    980. Wilner LB
    981. Wilson S
    982. Wojtyniak B
    983. Wolfe CDA
    984. Wool EE
    985. Wu AM
    986. Wulf Hanson S
    987. Wunrow HY
    988. Xu G
    989. Xu R
    990. Yadgir S
    991. Yahyazadeh Jabbari SH
    992. Yamagishi K
    993. Yaminfirooz M
    994. Yano Y
    995. Yaya S
    996. Yazdi-Feyzabadi V
    997. Yearwood JA
    998. Yeheyis TY
    999. Yeshitila YG
    1000. Yip P
    1001. Yonemoto N
    1002. Yoon SJ
    1003. Yoosefi Lebni J
    1004. Younis MZ
    1005. Younker TP
    1006. Yousefi Z
    1007. Yousefifard M
    1008. Yousefinezhadi T
    1009. Yousuf AY
    1010. Yu C
    1011. Yusefzadeh H
    1012. Zahirian Moghadam T
    1013. Zaki L
    1014. Zaman SB
    1015. Zamani M
    1016. Zamanian M
    1017. Zandian H
    1018. Zangeneh A
    1019. Zastrozhin MS
    1020. Zewdie KA
    1021. Zhang Y
    1022. Zhang ZJ
    1023. Zhao JT
    1024. Zhao Y
    1025. Zheng P
    1026. Zhou M
    1027. Ziapour A
    1028. Zimsen SRM
    1029. Naghavi M
    1030. Murray CJL

    (2020) Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019

    Lancet 396:1204–1222.

    https://doi.org/10.1016/S0140-6736(20)30925-9

    • PubMed
    • Google Scholar
44. 1. Warensjö E
    2. Sundström J
    3. Vessby B
    4. Cederholm T
    5. Risérus U

    (2008) Markers of dietary fat quality and fatty acid desaturation as predictors of total and cardiovascular mortality: a population-based prospective study

    The American Journal of Clinical Nutrition 88:203–209.

    https://doi.org/10.1093/ajcn/88.1.203

    • PubMed
    • Google Scholar
45. 1. Wu JHY
    2. Lemaitre RN
    3. King IB
    4. Song X
    5. Psaty BM
    6. Siscovick DS
    7. Mozaffarian D

    (2014) Circulating omega-6 polyunsaturated fatty acids and total and cause-specific mortality: the Cardiovascular Health Study

    Circulation 130:1245–1253.

    https://doi.org/10.1161/CIRCULATIONAHA.114.011590

    • PubMed
    • Google Scholar
46. 1. Würtz P
    2. Kangas AJ
    3. Soininen P
    4. Lawlor DA
    5. Davey Smith G
    6. Ala-Korpela M

    (2017) Quantitative serum nuclear magnetic resonance metabolomics in large-scale epidemiology: a primer on -omic technologies

    American Journal of Epidemiology 186:1084–1096.

    https://doi.org/10.1093/aje/kwx016

    • PubMed
    • Google Scholar
47. 1. Zhang Y
    2. Zhuang P
    3. He W
    4. Chen JN
    5. Wang WQ
    6. Freedman ND
    7. Abnet CC
    8. Wang JB
    9. Jiao JJ

    (2018) Association of fish and long-chain omega-3 fatty acids intakes with total and cause-specific mortality: prospective analysis of 421 309 individuals

    Journal of Internal Medicine 284:399–417.

    https://doi.org/10.1111/joim.12786

    • PubMed
    • Google Scholar
48. Software

    1. Zhang Y

    (2024) PUFA-mortality, version swh:1:rev:70f744aa2ee75c84ee2c4173fd4ab7515f6243e2

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:dir:463e2491ba636b7163e737aa0997d94b105c020d;origin=https://github.com/YuchenZhang585/PUFA-mortality;visit=swh:1:snp:9832ebd549990fcb403827d4f41cabcd3f36dd3a;anchor=swh:1:rev:70f744aa2ee75c84ee2c4173fd4ab7515f6243e2
49. 1. Zhuang P
    2. Wang W
    3. Wang J
    4. Zhang Y
    5. Jiao J

    (2019) Polyunsaturated fatty acids intake, omega-6/omega-3 ratio and mortality: Findings from two independent nationwide cohorts

    Clinical Nutrition 38:848–855.

    https://doi.org/10.1016/j.clnu.2018.02.019

    • PubMed
    • Google Scholar

Author details

1. Yuchen Zhang

   Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8992-5258

2. Yitang Sun

   Department of Genetics, University of Georgia, Athens, Georgia, United States

   Contribution

   Data curation, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6564-8815

3. Qi Yu

   Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, United States

   Contribution

   Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0007-7585-1183

4. Suhang Song

   Department of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, United States

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1934-632X

5. J Thomas Brenna

   1. Division of Nutritional Sciences, Cornell University, Ithaca, New York, United States
   2. Dell Pediatric Research Institute and the Depts of Pediatrics, of Nutrition, and of Chemistry, University of Texas at Austin, Austin, Texas, United States

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9494-4245

6. Ye Shen

   Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States

   Contribution

   Conceptualization, Supervision, Investigation, Project administration, Writing – review and editing

   For correspondence

   yeshen@uga.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6662-0048

7. Kaixiong Ye

   1. Department of Genetics, University of Georgia, Athens, Georgia, United States
   2. Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Project administration, Writing – review and editing

   For correspondence

   kaixiong.ye@uga.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4658-7292

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