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Figure 1.
Hazard Ratios (HRs) for Mortality Associated With Isocaloric Substitution of 3% Energy From Plant Protein for Animal Protein From Various Sources
Hazard Ratios (HRs) for Mortality Associated With Isocaloric Substitution of 3% Energy From Plant Protein for Animal Protein From Various Sources

Model includes plant protein and the various sources of animal protein and is adjusted for total energy, percentage of energy from fats (saturated, monounsaturated, polyunsaturated, and other) and carbohydrates (all continuous), age (≤50, 51-55, 56-60, 61-65, 66-70, or >70 years), sex, body mass index (calculated as weight in kilograms divided by the height in meters squared; <22.5, 22.5 to <25.0, 25.0 to <27.5, or ≥27.5), smoking (never, past, or current with ≤20 or >20 cigarettes per day), alcohol use (none or occasional or regular ethanol consumption of <150, 150 to <300, or ≥300 g per day), physical activity (quartile category in metabolic equivalent hours per day), occupation status (agriculture/forestry/fishery, salaried/professional, self-employed, housework/unemployed, or other), and intake of green tea (never, <1, 1, 2-3, or ≥4 cups per day) and coffee (never, <1, 1, or ≥2 cups per day).

Figure 2.
Hazard Ratios (HRs) for Mortality Associated With Isocaloric Substitution of 3% Energy From Fish Protein for Other Animal Protein Sources
Hazard Ratios (HRs) for Mortality Associated With Isocaloric Substitution of 3% Energy From Fish Protein for Other Animal Protein Sources

Model includes animal protein from various sources and plant protein and is adjusted for total energy, percentage of energy from fats (saturated, monounsaturated, polyunsaturated, and other) and carbohydrates (all continuous), age (≤50, 51-55, 56-60, 61-65, 66-70, or >70 years), sex, body mass index (calculated as weight in kilograms divided by the height in meters squared; <22.5, 22.5 to <25.0, 25.0 to <27.5, or ≥27.5), smoking (never, past, or current with ≤20 and >20 cigarettes per day), alcohol use (none or occasional or regular consumption of ethanol of <150, 150 to <300, or ≥300 g per day), physical activity (quartile category in metabolic equivalent hours per day), occupation status (agriculture/forestry/fishery, salaried/professional, self-employed, housework/unemployed, or other) and intake of green tea (never, <1, 1, 2-3, or ≥4 cups per day) and coffee (never, <1, 1, or ≥2 cups per day).

Table 1.  
Distribution of Baseline Characteristic of Participants According to Quintile Category of Total, Animal, and Plant Protein Intake Expressed as Percentage of Total Energy
Distribution of Baseline Characteristic of Participants According to Quintile Category of Total, Animal, and Plant Protein Intake Expressed as Percentage of Total Energy
Table 2.  
Hazards for All-Cause and Cause-Specific Mortality According to Percentage of Energy From Total, Animal, and Plant Protein Intake
Hazards for All-Cause and Cause-Specific Mortality According to Percentage of Energy From Total, Animal, and Plant Protein Intake
1.
Rodriguez  NR.  Introduction to Protein Summit 2.0: continued exploration of the impact of high-quality protein on optimal health.  Am J Clin Nutr. 2015;101(6):1317S-1319S. doi:10.3945/ajcn.114.083980PubMedGoogle ScholarCrossref
2.
Millward  DJ, Layman  DK, Tomé  D, Schaafsma  G.  Protein quality assessment: impact of expanding understanding of protein and amino acid needs for optimal health.  Am J Clin Nutr. 2008;87(5):1576S-1581S. doi:10.1093/ajcn/87.5.1576SPubMedGoogle ScholarCrossref
3.
Moughan  PJ.  Dietary protein for human health.  Br J Nutr. 2012;108(suppl 2):S1-S2. doi:10.1017/S0007114512003509PubMedGoogle ScholarCrossref
4.
Phillips  SM, Chevalier  S, Leidy  HJ.  Protein “requirements” beyond the RDA: implications for optimizing health.  Appl Physiol Nutr Metab. 2016;41(5):565-572. doi:10.1139/apnm-2015-0550PubMedGoogle ScholarCrossref
5.
Westerterp-Plantenga  MS, Lemmens  SG, Westerterp  KR.  Dietary protein: its role in satiety, energetics, weight loss and health.  Br J Nutr. 2012;108(suppl 2):S105-S112. doi:10.1017/S0007114512002589PubMedGoogle ScholarCrossref
6.
Leidy  HJ, Clifton  PM, Astrup  A,  et al.  The role of protein in weight loss and maintenance.  Am J Clin Nutr. 2015;101(6):1320S-1329S. doi:10.3945/ajcn.114.084038PubMedGoogle ScholarCrossref
7.
Adams  SH.  Emerging perspectives on essential amino acid metabolism in obesity and the insulin-resistant state.  Adv Nutr. 2011;2(6):445-456. doi:10.3945/an.111.000737PubMedGoogle ScholarCrossref
8.
Lynch  CJ, Adams  SH.  Branched-chain amino acids in metabolic signalling and insulin resistance.  Nat Rev Endocrinol. 2014;10(12):723-736. doi:10.1038/nrendo.2014.171PubMedGoogle ScholarCrossref
9.
Santesso  N, Akl  EA, Bianchi  M,  et al.  Effects of higher- versus lower-protein diets on health outcomes: a systematic review and meta-analysis.  Eur J Clin Nutr. 2012;66(7):780-788. doi:10.1038/ejcn.2012.37PubMedGoogle ScholarCrossref
10.
Dong  JY, Zhang  ZL, Wang  PY, Qin  LQ.  Effects of high-protein diets on body weight, glycaemic control, blood lipids and blood pressure in type 2 diabetes: meta-analysis of randomised controlled trials.  Br J Nutr. 2013;110(5):781-789. doi:10.1017/S0007114513002055PubMedGoogle ScholarCrossref
11.
Wu  G.  Dietary protein intake and human health.  Food Funct. 2016;7(3):1251-1265. doi:10.1039/C5FO01530HPubMedGoogle ScholarCrossref
12.
Richter  CK, Skulas-Ray  AC, Champagne  CM, Kris-Etherton  PM.  Plant protein and animal proteins: do they differentially affect cardiovascular disease risk?  Adv Nutr. 2015;6(6):712-728. doi:10.3945/an.115.009654PubMedGoogle ScholarCrossref
13.
Carroll  KK.  Dietary protein in relation to plasma cholesterol levels and atherosclerosis.  Nutr Rev. 1978;36(1):1-5. doi:10.1111/j.1753-4887.1978.tb03670.xPubMedGoogle ScholarCrossref
14.
Tominaga  S, Kuroishi  T.  An ecological study on diet/nutrition and cancer in Japan.  Int J Cancer. 1997;(suppl 10):2-6. doi:10.1002/(SICI)1097-0215(1997)10+<2::AID-IJC2>3.0.CO;2-CPubMedGoogle Scholar
15.
Levine  ME, Suarez  JA, Brandhorst  S,  et al.  Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population.  Cell Metab. 2014;19(3):407-417. doi:10.1016/j.cmet.2014.02.006PubMedGoogle ScholarCrossref
16.
Kelemen  LE, Kushi  LH, Jacobs  DR  Jr, Cerhan  JR.  Associations of dietary protein with disease and mortality in a prospective study of postmenopausal women.  Am J Epidemiol. 2005;161(3):239-249. doi:10.1093/aje/kwi038PubMedGoogle ScholarCrossref
17.
Song  M, Fung  TT, Hu  FB,  et al.  Association of animal and plant protein intake with all-cause and cause-specific mortality.  JAMA Intern Med. 2016;176(10):1453-1463. doi:10.1001/jamainternmed.2016.4182PubMedGoogle ScholarCrossref
18.
Japan Ministry of Education. Culture, Sports, Science and Technology. Standard Tables of Food Composition in Japan. 5th ed, revised and enlarged. Tokyo: National Printing Bureau; 2005
19.
Ishihara  J, Sobue  T, Yamamoto  S,  et al; JPHC.  Validity and reproducibility of a self-administered food frequency questionnaire in the JPHC Study cohort II: study design, participant profile and results in comparison with cohort I.  J Epidemiol. 2003;13(1)(suppl):S134-S147. doi:10.2188/jea.13.1sup_134PubMedGoogle ScholarCrossref
20.
Tsugane  S, Kobayashi  M, Sasaki  S; JPHC.  Validity of the self-administered food frequency questionnaire used in the 5-year follow-up survey of the JPHC Study cohort I: comparison with dietary records for main nutrients.  J Epidemiol. 2003;13(1)(suppl):S51-S56. doi:10.2188/jea.13.1sup_51PubMedGoogle ScholarCrossref
21.
Nanri  A, Mizoue  T, Kurotani  K,  et al; Japan Public Health Center-Based Prospective Study Group.  Low-carbohydrate diet and type 2 diabetes risk in Japanese men and women: the Japan Public Health Center–Based Prospective Study.  PLoS One. 2015;10(2):e0118377. doi:10.1371/journal.pone.0118377PubMedGoogle ScholarCrossref
22.
Willett  W.  Nutritional Epidemiology. 3rd ed. New York, NY: Oxford University Press; 2013.
23.
Song  M, Giovannucci  E.  Substitution analysis in nutritional epidemiology: proceed with caution.  Eur J Epidemiol. 2018;33(2):137-140. doi:10.1007/s10654-018-0371-2PubMedGoogle ScholarCrossref
24.
Kurotani  K, Akter  S, Kashino  I,  et al; Japan Public Health Center based Prospective Study Group.  Quality of diet and mortality among Japanese men and women: Japan Public Health Center Based Prospective Study.  BMJ. 2016;352:i1209. doi:10.1136/bmj.i1209PubMedGoogle ScholarCrossref
25.
Tielemans  SM, Kromhout  D, Altorf-van der Kuil  W, Geleijnse  JM.  Associations of plant and animal protein intake with 5-year changes in blood pressure: the Zutphen Elderly Study.  Nutr Metab Cardiovasc Dis. 2014;24(11):1228-1233. doi:10.1016/j.numecd.2014.05.013PubMedGoogle ScholarCrossref
26.
Shang  X, Scott  D, Hodge  A,  et al.  Dietary protein from different food sources, incident metabolic syndrome and changes in its components: an 11-year longitudinal study in healthy community-dwelling adults.  Clin Nutr. 2017;36(6):1540-1548. doi:10.1016/j.clnu.2016.09.024PubMedGoogle ScholarCrossref
27.
Chalvon-Demersay  T, Azzout-Marniche  D, Arfsten  J,  et al.  A systematic review of the effects of plant compared with animal protein sources on features of metabolic syndrome.  J Nutr. 2017;147(3):281-292.PubMedGoogle Scholar
28.
Elliott  P, Stamler  J, Dyer  AR,  et al.  Association between protein intake and blood pressure: the INTERMAP Study.  Arch Intern Med. 2006;166(1):79-87. doi:10.1001/archinte.166.1.79PubMedGoogle ScholarCrossref
29.
Allen  NE, Appleby  PN, Davey  GK, Kaaks  R, Rinaldi  S, Key  TJ.  The associations of diet with serum insulin-like growth factor I and its main binding proteins in 292 women meat-eaters, vegetarians, and vegans.  Cancer Epidemiol Biomarkers Prev. 2002;11(11):1441-1448.PubMedGoogle Scholar
30.
Holmes  MD, Pollak  MN, Willett  WC, Hankinson  SE.  Dietary correlates of plasma insulin-like growth factor I and insulin-like growth factor binding protein 3 concentrations.  Cancer Epidemiol Biomarkers Prev. 2002;11(9):852-861.PubMedGoogle Scholar
31.
van Baak  MA, Larsen  TM, Jebb  SA,  et al.  Dietary intake of protein from different sources and weight regain, changes in body composition and cardiometabolic risk factors after weight loss: the DIOGenes Study.  Nutrients. 2017;9(12):E1326. doi:10.3390/nu9121326PubMedGoogle ScholarCrossref
32.
Shang  X, Scott  D, Hodge  AM,  et al.  Dietary protein intake and risk of type 2 diabetes: results from the Melbourne Collaborative Cohort Study and a meta-analysis of prospective studies.  Am J Clin Nutr. 2016;104(5):1352-1365. doi:10.3945/ajcn.116.140954PubMedGoogle ScholarCrossref
33.
Malik  VS, Li  Y, Tobias  DK, Pan  A, Hu  FB.  Dietary protein intake and risk of type 2 diabetes in US men and women.  Am J Epidemiol. 2016;183(8):715-728. doi:10.1093/aje/kwv268PubMedGoogle ScholarCrossref
34.
Papandreou  C, Becerra-Tomas  N, Bullo  M,  et al.  Legume consumption and risk of all-cause, cardiovascular, and cancer mortality in the PREDIMED study.  Clin Nutr. 2019;38(1):348-356. doi:10.1016/j.clnu.2017.12.019PubMedGoogle ScholarCrossref
35.
Aune  D, Keum  N, Giovannucci  E,  et al.  Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies.  BMJ. 2016;353:i2716. doi:10.1136/bmj.i2716PubMedGoogle ScholarCrossref
36.
Abete  I, Romaguera  D, Vieira  AR, Lopez de Munain  A, Norat  T.  Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies.  Br J Nutr. 2014;112(5):762-775. doi:10.1017/S000711451400124XPubMedGoogle ScholarCrossref
37.
Etemadi  A, Sinha  R, Ward  MH,  et al.  Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study.  BMJ. 2017;357:j1957. doi:10.1136/bmj.j1957PubMedGoogle ScholarCrossref
38.
Kurotani  K, Budhathoki  S, Joshi  AM,  et al.  Dietary patterns and colorectal cancer in a Japanese population: the Fukuoka Colorectal Cancer Study.  Br J Nutr. 2010;104(11):1703-1711. doi:10.1017/S0007114510002606PubMedGoogle ScholarCrossref
39.
Nanri  A, Shimazu  T, Takachi  R,  et al; Japan Public Health Center-based Prospective Study Group.  Dietary patterns and type 2 diabetes in Japanese men and women: the Japan Public Health Center–Based Prospective Study.  Eur J Clin Nutr. 2013;67(1):18-24. doi:10.1038/ejcn.2012.171PubMedGoogle ScholarCrossref
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    2 Comments for this article
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    Concerns about Misleading Interpretation and Incorrect Conclusion
    Angela Stanton, PhD | Stanton Migraine Protocol Inc.,
    The article by Budhathoki et al.,(1) is akin to the article  in 2016 by Song et al (2)l. A study of association is used to support causation without appropriate statistical proof.

    The article states in the abstract that “Intake of animal protein showed no clear association with total or cause-specific mortality” and then in the next sentence “In contrast, intake of plant protein was associated with lower total mortality.” If there is no clear association between meat protein and mortality, how can plant protein be associated with lower mortality? If there is no association, then there is no association.  />
    In my view, the authors main findings are incorrect, confusing, and misleading.

    This research is based on food frequency surveys for the previous year, completed once every five years. Food frequency questionnaires are questionable at best, particularly when a past year’s consumption has to be recalled.

    A frequent  error in a food frequency analysis is the substitution of plant protein for animal protein “on paper” with “isocaloric substitution interpretation,” without the subjects actually changing their diet. Such substitution cannot be used to conclude what would have happened had they actually changed their diet. So we cannot infer if their mortality changed.

    And finally, none of the hazard ratios shown meet the Bradford Criteria of 2 to suggest that the associations are significant enough to consider causation for even further analysis, let alone conclude any causal significance. This study shows no association of mortality with the type of protein consumed.

    1 Budhathoki, S. et al. Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality. JAMA Internal Medicine, doi:10.1001/jamainternmed.2019.2806 (2019).

    2 Song, M., Fung, T. T., Hu, F. B. & et al. Association of animal and plant protein intake with all-cause and cause-specific mortality. JAMA Internal Medicine 176, 1453-1463, doi:10.1001/jamainternmed.2016.4182 (2016).
    CONFLICT OF INTEREST: None Reported
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    This study is very well described by the title but no clear advice could be provided
    Guy Pelouze, MD MSc | Institut de Recherche Clinique, France
    The findings of this prospective observational study could be summarized differently: Animal protein is associated with no increase or decrease of mortality neither total nor from cancer or CVD. The null hypothesis is not rejected. The authors argue that plant protein could be associated with less mortality. Apart from the validity of testing this partial hypothesis as a secondary outcome, one must recognize that the results are mitigated and surprising. As total and animal protein consumption is not associated with any change in mortality, a decrease in total and CVD mortalities associated with plant protein is improbable. Plant protein is significantly associated with a 13% decrease in all-cause mortality. No difference in mortality due to cancer. An association with a 24% decrease in cardiovascular mortality, 25% for coronary heart disease and 28% for stroke. But confounding factors are so numerous that in such a model this assertion is backed by very weak evidence. We have listed some evidences of uncertainty in the design and the follow-up:
    - A single questionnaire at the beginning of the study that lasted several years and another questionnaire five years later with modalities for taking into account information that violates the basic rules. I quote: "Since the five-year follow-up survey questionnaire contained more complete information on food consumption than the original survey, we used the five-year follow-up survey data collected from January 1, 1995, to December 31, 1999, as the basis for this analysis."
    - Weak correlation and reproducibility of questionnaires as evaluated in one small group of verification and only once at the beginning of the study.
    - No clinical evaluation about T2D during the study (minimal duration 16 years)
    - A multivariate model 1 which does not equate smokers across groups while  deaths from cancer and CVD are dealt with.
    So using a bayesian approach, what does reconcile the different findings of this study?
    My answer is ethnicity, Japanese diet and lifestyle. Japanese do have a low prevalence of CVD. They eat less meat and much more fish and seafood that Westerners. It is the case in the study. In Japan as in the West people who don't eat plants do have a less healthy lifestyle as eating plants is a marker of less proportion of processed foods. And last but not least the statistical substitution of protein leads tp the same results (and better results for cancer) when fish instead of plant protein is substituted.
    CONFLICT OF INTEREST: None Reported
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    Original Investigation
    August 26, 2019

    Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality

    Author Affiliations
    • 1Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
    • 2Department of Food and Life Science, Azabu University, Kanagawa, Japan
    • 3Department of Food Science and Nutrition, Faculty of Human Life and Environment, Nara Women’s University, Nara, Japan
    • 4Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
    • 5Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan
    JAMA Intern Med. Published online August 26, 2019. doi:10.1001/jamainternmed.2019.2806
    Key Points

    Question  What is the long-term association between dietary protein intake and all-cause or cause-specific mortality in the Japanese population?

    Findings  In this cohort study of 70 696 Japanese adults followed up for a mean of 18 years, higher intake of plant protein was associated with lower total mortality. Moreover, substitution of plant protein for animal protein, mainly for red or processed meat protein, was associated with lower risk of total, cancer-related, and cardiovascular disease–related mortality.

    Meaning  A higher intake of plant-based proteins may contribute to long-term health and longevity.

    Abstract

    Importance  Epidemiological evidence regarding the long-term effects of higher dietary protein intake on mortality outcomes in the general population is not clear.

    Objective  To evaluate the associations between animal and plant protein intake and all-cause and cause-specific mortality.

    Design, Setting, and Participants  This prospective cohort study included 70 696 participants in the Japan Public Health Center–based Prospective Cohort who were aged 45 to 74 years and had no history of cancer, cerebrovascular disease, or ischemic heart disease at study baseline. Data were collected from January 1, 1995, through December 31, 1999, with follow-up completed December 31, 2016, during which 12 381 total deaths were documented. Dietary intake information was collected through a validated food frequency questionnaire and used to estimate protein intake in all participants. Participants were grouped into quintile categories based on their protein intake, expressed as a percentage of total energy. Data were analyzed from July 18, 2017, through April 10, 2019.

    Main Outcomes and Measures  Hazard ratios (HRs) and 95% CIs for all-cause and cause-specific mortality were estimated using Cox proportional hazards regression models with adjustment for potential confounding factors.

    Results  Among the 70 696 participants, 32 201 (45.5%) were men (mean [SD] age, 55.6 [7.6] years) and 38 495 (54.5%) were women (mean [SD] age, 55.8 [7.7] years). Intake of animal protein showed no clear association with total or cause-specific mortality. In contrast, intake of plant protein was associated with lower total mortality, with multivariable-adjusted HRs of 0.89 (95% CI, 0.83-0.95) for quintile 2; 0.88 (95% CI, 0.82-0.95) for quintile 3; 0.84 (95% CI, 0.77-0.92) for quintile 4; and 0.87 (95% CI, 0.78-0.96) for quintile 5, with quintile 1 as the reference category (P = .01 for trend). For cause-specific mortality, this association with plant protein intake was evident for cardiovascular disease (CVD)–related mortality (HRs, 0.84 [95% CI, 0.73-0.96] to 0.70 [95% CI, 0.59-0.83]; P = .002 for trend). Isocaloric substitution of 3% energy from plant protein for red meat protein was associated with lower total (HR, 0.66; 95% CI, 0.55-0.80), cancer-related (HR, 0.61; 95% CI, 0.45-0.82), and CVD-related (HR, 0.58; 95% CI, 0.39-0.86) mortality; substitution for processed meat protein was associated with lower total (HR, 0.54; 95% CI, 0.38-0.75) and cancer-related (HR, 0.50; 95% CI, 0.30-0.85) mortality.

    Conclusions and Relevance  In this large prospective study, higher plant protein intake was associated with lower total and CVD-related mortality. Although animal protein intake was not associated with mortality outcomes, replacement of red meat protein or processed meat protein with plant protein was associated with lower total, cancer-related, and CVD-related mortality.

    Introduction

    Exploration of the health effects of a high-protein diet have attracted substantial interest during recent years.1-4 In short-term trials, consumption of high-protein diets have been shown to produce greater weight loss, loss of fat mass, and preservation of lean mass compared with the consumption of normal-protein diets.5,6 These favorable effects of a high-protein diet in body weight management may be due to the modulation of amino acids in appetitive signaling, leading to increased satiety and hence reduced energy intake.7,8 High-protein diets are also linked to improvements in cardiovascular risk factors, including blood pressure, blood lipid and lipoprotein profiles, and glycemic regulation.9,10 Despite these benefits, the health effects of adherence to high dietary protein intake on long-term health and mortality remain to be clarified. Importantly, high consumption of dietary protein is unavoidably linked to a decrease in other foods, usually carbohydrates, and a decrease in carbohydrate foods with high fiber and other micronutrients may have a negative effect. Furthermore, among protein sources, proteins originating from animal and plant sources have different amino acid combinations,11 and the choices of dietary protein source also necessarily influence other macronutrients, micronutrients, and polyphenols in the diet,12 potentially leading to differential health effects. Thus, clarifying the association between high dietary protein intake and long-term health outcomes is essential; in particular, clarifying the association between specific sources of protein and mortality may help individuals increase longevity by substituting one type of protein for another.

    Earlier ecologic studies13,14 reported a positive correlation between overall animal protein intake and mortality due to cardiovascular disease (CVD) and cancer. However, only a few epidemiologic studies15-17 have evaluated the association between protein intake in association with mortality outcomes. An analysis using the US National Health and Nutrition Examination Survey (NHANES) reported a significant increase in the risk of death due to all causes associated with higher protein intake.15 However, that study was based on relatively few deaths. Two other US studies16,17 did not replicate this positive association of overall mortality with animal protein but did report a reduced risk of CVD-related mortality associated with higher plant protein. Moreover, no reports on this issue have yet appeared from an Asian population, despite the differences in dietary habits between Asian and western populations. The higher fish and soy product consumption in Japan than in western populations suggests that their sources of animal and plant proteins may differ. Herein, we evaluated the association between animal and plant protein intake and all-cause and cause-specific mortality in a Japanese population within the Japan Public Health Center–based Prospective Cohort (JPHC) Study.

    Methods
    Participants

    The JPHC Study commenced January 1, 1990, with the enrollment of 61 595 registered residents aged 40 to 59 years from 5 public health center (PHC) areas across Japan (cohort 1). A further 78 825 individuals aged 40 to 69 years from another 6 PHC areas were added starting January 1, 1993 (cohort 2). At baseline, enrolled participants were provided with self-administered survey questionnaires to assess diet and lifestyle factors. Completion of these questionnaires was considered to indicate consent to participate in the study. Follow-up survey questionnaires were readministered at 5-year intervals after the baseline survey. Because the questionnaire in the 5-year follow-up survey contained more comprehensive information on food intake than that in the baseline survey, we used the 5-year follow-up survey data collected from January 1, 1995, through December 31, 1999, as baseline data for this analysis. Informed consent was obtained from all participants per the study protocol, which was approved by the institution review board of the National Cancer Center, Tokyo, Japan (approval number: 2001-021, 2004-059). Although written informed consent was not required, all eligible individuals were given an explanation of the aim and design of the study when invited to participate. This study followed the American Association for Public Opinion Research (AAPOR) reporting guideline.

    After exclusion of 275 ineligible participants and 4803 participants who died or moved out of the study area before the 5-year follow-up survey, 103 428 eligible participants completed and returned questionnaires on demographics, medical and treatment history, and lifestyle and dietary habits. We further excluded 14 226 participants who reported a history of cancer, stroke, ischemic heart disease, or renal disease in the baseline or second survey; 5383 who reported extreme energy intake (<1001 or >4201 kcal/d for men or <844 or >3688 kcal/d for women); 172 in the top 0.1 percentile of protein intake variables; and 12 951 with missing covariate information (as detailed in eMethods in the Supplement). Finally, 70 696 participants were included in the analytic cohort.

    Dietary Assessment

    A semiquantitative food frequency questionnaire was used to assess usual intake of 138 food and beverage items during the previous year. For most foods, intake frequency ranged from rarely (<1 time per month) to at least 7 times per day in 9 categories. A standard portion size was prespecified for each food, and participants were asked to report their usual portion size relative to the standard portion size using 3 options (<0.5 times, standard, or >1.5 times). Daily food intake was calculated by multiplying intake frequency by standard portion and relative size for each food item in the food frequency questionnaire. The daily food intake data, with Standard Tables of Food Composition in Japan (Fifth Revised and Enlarged Edition),18 was then used to estimate nutrient intake. The dietary intake information estimated from the food frequency questionnaire was previously compared with dietary intake estimates from 14- or 28-day dietary records (validity) and with intake estimates computed from subsequent questionnaires administered 1 year apart (reproducibility) in a cohort subsample. Spearman correlation coefficients were 0.31 in men and 0.33 in women for validity and 0.57 in men and 0.54 in women for reproducibility.19,20 For the present analysis, we also estimated protein intake from animal and plant sources separately. Sources of animal protein were fish and shellfish, meat and processed meat, eggs, milk, and dairy products; sources of plant protein included foods other than animal foods. We expressed protein intake as a percentage of total energy consumption. Spearman correlation coefficients for validity for animal protein and plant protein were 0.21 and 0.59, respectively, in men and 0.26 and 0.49, respectively, in women.21 Corresponding values for reproducibility were 0.49 for animal protein and 0.60 for plant protein in men and 0.48 for animal protein and 0.58 for plant protein in women.

    Mortality Ascertainment

    Residential and vital statuses of cohort participants during follow-up were determined annually through the residential registry. Causes of death, coded according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, were obtained from death certificates with permission of the Ministry of Health, Labour and Welfare. For this analysis, we assessed all-cause mortality and deaths due to cancer (codes C00-C99), CVD (codes I00-I99), heart disease (codes I20-I52), and cerebrovascular disease (codes I60-I69).

    Statistical Analysis

    Data were analyzed from July 18, 2017, through April 10, 2019. Person-years of follow-up for each participant were calculated from the date of response to the 5-year survey questionnaire until the date of death, move out of Japan, or end of the follow-up period, whichever came first. The end of the follow-up period was December 31, 2016, for all PHCs except Tokyo and Osaka, which concluded on December 31, 2009, and December 31, 2012, respectively. Individuals lost to follow-up were censored at the last confirmed date of presence in the study area. Cox proportional hazards regression models were used to evaluate the association between protein intake and mortality outcomes (eMethods in the Supplement). We adjusted for covariates in 2 models: the first adjusted for age, sex, and percentage of energy from saturated, monounsaturated, polyunsaturated, and other fats, whereas the second further adjusted for body mass index, smoking status, alcohol intake, total physical activity, coffee consumption, green tea consumption, and total calorie intake while leaving out the percentage of energy from carbohydrates. Mutual adjustment for animal protein and plant protein in the respective analyses was performed. The latter model assumes isocaloric substitution interpretation, wherein the coefficient for protein represents the substitution effect of an equal amount of energy from protein for carbohydrates.22,23 Tests for trend were based on a Wald test for linear contrast of the model coefficients corresponding to variable categories. We conducted stratified analysis by lifestyle factors and tested the significance of interaction by the likelihood ratio test (eMethods in the Supplement). Next, we evaluated the isoenergic substitution effect within the protein group by protein food sources, wherein we estimated the hazard ratios (HRs) for replacement of 3% of energy from one source for the equivalent amount of energy from other sources. We used SAS, version 9.3 (SAS Institute, Inc), and R statistical software, version 3.5.3 (R Development Core Team, 2019) for analyses. All statistical tests were 2 sided, and P < .05 was considered statistically significant.

    Results

    Of the 70 696 participants, 32 201 (45.5%) were men (mean [SD] age, 55.6 [7.6] years) and 38 495 (54.5%) were women (mean [SD] age, 55.8 [7.7] years). During a mean follow-up of 18 years, we documented 12 381 deaths due to all causes, including 5055 due to cancer, 3025 due to CVD, 1528 due to heart disease, and 1198 due to cerebrovascular disease. Mean (SD) intakes, expressed as percentage of total energy, were 7.7% (2.7%) for animal protein and 6.7% (1.4%) for plant protein. Fish and seafood products (47.1%), red meats (19.4%), milk or dairy products (16.7%), and eggs (9.5%) were the major sources of animal protein intake compared with cereals (50.3%), pulses (24.1%), vegetables (7.8%), and fruits (3.8%) for plant protein intake (eFigure in the Supplement). Participants with higher intake of protein from animal and plant sources were less likely to be men (34.1% and 30.5%, respectively), less likely to smoke (23.5% and 21.5%, respectively) and consume alcohol (33.3% and 21.9%, respectively), and more likely to regularly drink green tea (50.7% and 57.2%, respectively) than participants with lower protein intake (Table 1). Compared with participants with lower intake, those with higher animal protein intake tended to consume more total energy (mean [SE], 2287 [4.9] kcal/d) and fat (mean [SE], 32.0% [0.04%]) but less carbohydrates (mean [SE], 47.1% [0.1%]), whereas those with higher plant protein intake tended to consume less total energy (mean [SE], 1914 [5.0] kcal/d) and fat (mean [SE], 22.9% [0.1%]) but more carbohydrates (mean [SE], 60.0% [0.1%]). As expected, compared with those in the lowest quintile of plant protein intake, participants in the highest quintile had higher intakes of soy foods (mean [SE], 144 [0.5] g/d), fruits (mean [SE], 237 [1.3] g/d), and vegetables (mean [SE], 253 [1.0] g/d) but lower intake of meat (mean [SE], 33.0 [0.3] g/d). Compared with those in the lowest quintile of animal protein intake, those in the highest quintiles had higher intake of meats (mean [SE], 60.6 [0.3] g/d) but lower intake of fruits (mean [SE], 180.8 [1.3] g/d), vegetables (mean [SE], 198.0 [1.0] g/d), and soy foods (mean [SE], 78.0 [0.6] g/d).

    Higher total and animal protein intake was not associated with risk of overall mortality or cause-specific mortality (Table 2). In contrast, plant protein intake was significantly inversely associated with the risk of overall mortality (HR for quintile 2, 0.89 [95% CI, 0.83-0.95]; HR for quintile 3, 0.88 [95% CI, 0.82-0.95]; HR for quintile 4, 0.84 [95% CI, 0.77-0.92]; HR for quintile 5, 0.87 [95% CI, 0.78-0.96]; with quintile 1 as the reference category) (P = .01 for trend). Among cause-specific mortality, this inverse association with plant protein intake was evident for CVD mortality (HR for quintile 5, 0.73; 95% CI, 0.59-0.91) and its subdivisions of heart disease (HR for quintile 5, 0.72; 95% CI, 0.54-0.97) and cerebrovascular disease mortality (HR for quintile 5, 0.72; 95% CI, 0.51-1.00), but not with cancer mortality (overall or site-specific) (Table 2 and eTable 1 in the Supplement). Repetition of the above analysis by including observations with missing information for covariates using multiple imputation produced similar HRs to that of complete case analysis (eTable 2 in the Supplement). In other sensitivity analyses, although we further adjusted for diet quality score24 and other dietary variables, including intake of vegetables, fruits, pulses or soy foods, red and processed meats, fish, polyunsaturated fatty acids, folate, fiber, and sodium, the observed results were not substantially changed. The observed association did not substantially change after further adjustment for history of hypertension, dyslipidemia, or type 2 diabetes or after exclusion of deaths occurring during the first 5 years of follow-up (n = 1644). In subgroup analysis, the association between plant protein and total mortality appeared to be stronger for participants who never smoked (HR for quintile 5, 0.80; 95% CI, 0.69-0.93), with regular alcohol consumption (HR for quintile 5, 0.84; 95% CI, 0.72-0.98), with lean body mass (HR for quintile 5, 0.86; 95% CI, 0.76-0.97), and less physically active (HR for quintile 5, 0.82; 95% CI, 0.70-0.96), although the interaction was significant only for alcohol use (P = .01) and body mass index (P = .02) and appeared not to differ by age (eTable 3 in the Supplement). Total and animal protein, however, showed no clear association in subgroup analysis by these factors.

    Next, we examined the association of substituting one protein source for another with the risk of mortality outcomes. In this analysis, isocaloric substitution of 3% energy from plant protein for red meat protein was associated with lower total (HR, 0.66; 95% CI, 0.55-0.80), cancer-related (HR, 0.61; 95% CI, 0.45-0.82), and CVD-related (HR, 0.58; 95% CI, 0.39-0.86) mortality, whereas substitution for processed meat was associated with lower total (HR, 0.54; 95% CI, 0.38-0.75) and cancer-related (HR, 0.50; 95% CI, 0.30-0.85) mortality (Figure 1). The estimated absolute risk reduction at 15 years for isocaloric substitution of 3% energy from plant protein for red meat protein was 3.60% (95% CI, 2.10%-4.86%) for total, 1.92% (95% CI, 0.87%-2.71%) for cancer-related, and 1.16% (95% CI, 0.39%-1.68%) for CVD-related mortality (eTable 4 in the Supplement). The corresponding value for substitution of plant protein for processed meat protein was 4.95% (95% CI, 2.62%-6.65%) for total and 2.45% (95% CI, 0.72%-3.48%) for cancer-related mortality, although the estimate was not significant for cardiovascular mortality. Among animal proteins, substitution of fish protein for red meat was associated with lower total (HR, 0.75; 95% CI, 0.65-0.87), cancer-related (HR, 0.67; 95% CI, 0.53-0.85), and CVD-related (HR, 0.67; 95% CI, 0.50-0.91) mortality; and substitution of fish protein for processed meat was associated with lower total (HR, 0.61; 95% CI, 0.44-0.84) and cancer-related (HR, 0.55; 95% CI, 0.34-0.91) mortality (Figure 2). Among plant proteins, no clear association was observed when vegetable and fruit protein were substituted for cereal or soy protein, which may indicate that all 3 sources are beneficial (eTable 5 in the Supplement).

    Discussion

    In this large prospective study, plant protein intake was associated with lower risk of all-cause and CVD-related mortality. Moreover, substitution of plant protein for animal protein was associated with lower risk of total, cancer-related, and CVD-related mortality. Our study suggests that plant protein may provide beneficial health effects and that replacement of red and processed meat protein with plant or fish protein may increase longevity.

    To date, only a few prospective studies16,17 have evaluated animal and plant protein intake separately in association with the risk of overall or cause-specific mortality. In a study of postmenopausal women in Iowa,16 higher vegetable protein intake was associated with 30% lower risk of coronary heart disease mortality compared with lower vegetable protein intake. More recently, in a combined analysis of the Nurses’ Health Study and the Health Professionals Follow-up Study, Song et al17 revealed a similar inverse association with plant protein intake, wherein a 3% increase in energy from plant protein was associated with 10% lower risk of overall mortality and 12% lower risk of cardiovascular mortality. We applied similar analysis methods to the above studies, and our findings for plant protein support their findings. Interestingly, the greatest change in HRs in our study was between the first and second quintiles, which might suggest the possibility that very low intake or deprivation of plant protein might also be a risk for increased mortality. In contrast to these findings for plant protein, our results for animal protein intake showed no clear association with mortality outcomes. This lack of association with animal protein does not accord with the above-mentioned US study,17 wherein higher animal protein intake was positively associated with CVD-related mortality. In another report from the NHANES III study,15 although higher total protein intake levels were linked with significantly increased risks of all-cause mortality (among participants younger than 65 years), this association was significantly attenuated when animal protein was controlled for, a finding that was also replicated in our study (eTable 6 in the Supplement), implicating the role of animal proteins in this association. This discrepancy in findings for animal protein between our present study and the US study17 may be attributable to the difference in percentage of energy from animal protein, which was higher in the US study (median intake, as expressed in percentage of energy, of 14%) than in the present study (7.7%). The discrepancy might also be attributable to a difference in the main dietary source of animal protein, which was red and processed meat in the US study vs fish intake in the present study. Collectively, these findings suggest that proteins from animal and plant sources may have differing effects on long-term health and that a preference for plant-based foods in obtaining the required protein may provide long-term health benefits.

    Indeed, intake of plant protein, but not animal protein, has been associated with favorable changes in blood pressure level, waist circumference, and weight.25-28 Plant protein, unlike animal protein, was not significantly associated with higher insulinlike growth factor 1 levels.29,30 A recent systematic review27 found that consumption of plant protein (soy protein with isoflavones) was more strongly linked to lower levels of total and low-density lipoprotein cholesterol than the consumption of animal protein, whereas another study31 found that substitution of nonmeat protein for meat protein was favorably associated with fasting insulin levels and insulin resistance. Other evidence suggests a null or even lower risk of type 2 diabetes associated with higher intake of plant protein vs increased risk associated with animal protein.32,33 Moreover, intake of nuts and grains or legumes, a rich source of plant protein, was associated with lower CVD-related and all-cause mortality,34,35 whereas higher intake of red or processed meat, major sources of animal protein, was associated with higher all-cause and CVD-related mortality, including cancer mortality.36,37

    Cereals, pulses, vegetables, and fruits were the major sources of plant protein intake and carbohydrates. Because these foods are also often represented in healthy dietary patterns,38,39 replacing them may have adverse health effects. Thus, we also conducted substitution analysis within protein groups by protein food source. In this analysis, substitution of plant protein for red and processed meat protein was associated with lower total mortality, a finding that accords with the US study.17 Furthermore, our study showed that substitution of 3% energy of plant protein instead of red meat protein would result in an absolute risk reduction of overall mortality at 15 years of 3.60% (95% CI, 2.10%-4.86%). For an average person with 2000 kcal/d of energy intake, 3% of energy from plant protein would be approximately 260 g for a protein-rich food such as soy.

    Strengths and Limitations

    Strengths of this study include its population-based design, prospective collection of lifestyle data, use of validated food frequency questionnaires, large sample size, and long follow-up. Our study also had some limitations. The correlation coefficient for validity for protein intake was moderate to low. Dietary information was also based on a single assessment at baseline, and dietary habits might have changed during follow-up. However, any such misclassification in exposure assessment is likely to have been nondifferential among study participants and would likely have attenuated the risk estimates associated with mortality outcomes toward null. Nevertheless, we were still able to see differential associations with mortality outcomes in our study. Although we excluded participants with a history of chronic diseases, the presence of subclinical diseases might have led to changes in dietary habits. Plant protein intake may represent a healthy eating behavior; although adjustment for several lifestyle factors showed little difference in the overall results, the possibility of residual confounding in the association between plant protein and mortality remains.

    Conclusions

    We found that plant protein intake was associated with lower risk of all-cause and CVD-related mortality. Furthermore, replacement of red or processed meat protein with plant protein was associated with a decreased risk of total, cancer-related, and CVD-related mortality. Our study suggests that encouraging diets with higher plant-based protein intake may contribute to long-term health and longevity.

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    Article Information

    Accepted for Publication: May 27, 2019.

    Corresponding Author: Norie Sawada, MD, PhD, Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan (nsawada@ncc.go.jp).

    Published Online: August 26, 2019. doi:10.1001/jamainternmed.2019.2806

    Author Contributions: Drs Budhathoki and Sawada had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Budhathoki, Iwasaki, Yamaji, Ishihara, Tsugane.

    Acquisition, analysis, or interpretation of data: Budhathoki, Sawada, Iwasaki, Yamaji, Goto, Kotemori, Ishihara, Takachi, Charvat, Mizoue, Iso, Tsugane.

    Drafting of the manuscript: Budhathoki.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Budhathoki, Goto, Kotemori, Charvat.

    Obtained funding: Tsugane.

    Administrative, technical, or material support: Sawada, Takachi, Iso, Tsugane.

    Supervision: Sawada, Iwasaki, Takachi, Iso, Tsugane.

    Conflict of Interest Disclosures: None reported.

    Funding/Support: This study was supported by grants 23-A-31[toku], 26-A-2, and 29-A-4 from the National Cancer Center Research and Development Fund (since 2011) and a Grant-in-Aid for Cancer Research from the Ministry of Health, Labour and Welfare of Japan (from 1989 to 2010).

    Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Group Members: Members of the Japan Public Health Center-based Prospective Study Group include the following: S. Tsugane (principal investigator), N. Sawada, M. Iwasaki, M. Inoue, T. Yamaji, A. Goto, T. Shimazu, H. Charvat, S. Budhathoki and M. Muto, National Cancer Center, Tokyo; H. Suzuki, Iwate Prefectural Ninohe Public Health Center, Iwate; T. Minamizono, Akita Prefectural Yokote Public Health Center, Akita; Y. Kobayashi, Nagano Prefectural Saku Public Health Center, Nagano; M. Irei, Okinawa Prefectural Chubu Public Health Center, Okinawa; M. Doi, Ibaraki Prefectural Mito Public Health Center, Ibaraki; M. Katagiri, Niigata Prefectural Nagaoka Public Health Center, Niigata; T. Tagami, Kochi Prefectural Chuo-higashi Public Health Center, Kochi; Y. Sou, Nagasaki Prefectural Kamigoto Public Health Center, Nagasaki; M. Uehara, Okinawa Prefectural Miyako Public Health Center, Okinawa; Y. Kokubo, National Cerebral and Cardiovascular Center, Osaka; K. Yamagishi, University of Tsukuba, Ibaraki; M. Noda and T. Mizoue, National Center for Global Health and Medicine, Tokyo; Y. Kawaguchi, Tokyo Medical and Dental University, Tokyo; K. Nakamura, Niigata University, Niigata; R. Takachi, Nara Women’s University, Nara; J. Ishihara, Azabu University, Kanagawa; H. Iso and T. Sobue, Osaka University, Osaka; I. Saito, Ehime University, Ehime; N. Yasuda, Kochi University, Kochi; M. Mimura, Keio University, Tokyo; and K. Sakata, Iwate Medical University, Iwate.

    Additional Contributions: We thank all members of the Japan Public Health Center–based Prospective Study Group for their valuable contributions.

    References
    1.
    Rodriguez  NR.  Introduction to Protein Summit 2.0: continued exploration of the impact of high-quality protein on optimal health.  Am J Clin Nutr. 2015;101(6):1317S-1319S. doi:10.3945/ajcn.114.083980PubMedGoogle ScholarCrossref
    2.
    Millward  DJ, Layman  DK, Tomé  D, Schaafsma  G.  Protein quality assessment: impact of expanding understanding of protein and amino acid needs for optimal health.  Am J Clin Nutr. 2008;87(5):1576S-1581S. doi:10.1093/ajcn/87.5.1576SPubMedGoogle ScholarCrossref
    3.
    Moughan  PJ.  Dietary protein for human health.  Br J Nutr. 2012;108(suppl 2):S1-S2. doi:10.1017/S0007114512003509PubMedGoogle ScholarCrossref
    4.
    Phillips  SM, Chevalier  S, Leidy  HJ.  Protein “requirements” beyond the RDA: implications for optimizing health.  Appl Physiol Nutr Metab. 2016;41(5):565-572. doi:10.1139/apnm-2015-0550PubMedGoogle ScholarCrossref
    5.
    Westerterp-Plantenga  MS, Lemmens  SG, Westerterp  KR.  Dietary protein: its role in satiety, energetics, weight loss and health.  Br J Nutr. 2012;108(suppl 2):S105-S112. doi:10.1017/S0007114512002589PubMedGoogle ScholarCrossref
    6.
    Leidy  HJ, Clifton  PM, Astrup  A,  et al.  The role of protein in weight loss and maintenance.  Am J Clin Nutr. 2015;101(6):1320S-1329S. doi:10.3945/ajcn.114.084038PubMedGoogle ScholarCrossref
    7.
    Adams  SH.  Emerging perspectives on essential amino acid metabolism in obesity and the insulin-resistant state.  Adv Nutr. 2011;2(6):445-456. doi:10.3945/an.111.000737PubMedGoogle ScholarCrossref
    8.
    Lynch  CJ, Adams  SH.  Branched-chain amino acids in metabolic signalling and insulin resistance.  Nat Rev Endocrinol. 2014;10(12):723-736. doi:10.1038/nrendo.2014.171PubMedGoogle ScholarCrossref
    9.
    Santesso  N, Akl  EA, Bianchi  M,  et al.  Effects of higher- versus lower-protein diets on health outcomes: a systematic review and meta-analysis.  Eur J Clin Nutr. 2012;66(7):780-788. doi:10.1038/ejcn.2012.37PubMedGoogle ScholarCrossref
    10.
    Dong  JY, Zhang  ZL, Wang  PY, Qin  LQ.  Effects of high-protein diets on body weight, glycaemic control, blood lipids and blood pressure in type 2 diabetes: meta-analysis of randomised controlled trials.  Br J Nutr. 2013;110(5):781-789. doi:10.1017/S0007114513002055PubMedGoogle ScholarCrossref
    11.
    Wu  G.  Dietary protein intake and human health.  Food Funct. 2016;7(3):1251-1265. doi:10.1039/C5FO01530HPubMedGoogle ScholarCrossref
    12.
    Richter  CK, Skulas-Ray  AC, Champagne  CM, Kris-Etherton  PM.  Plant protein and animal proteins: do they differentially affect cardiovascular disease risk?  Adv Nutr. 2015;6(6):712-728. doi:10.3945/an.115.009654PubMedGoogle ScholarCrossref
    13.
    Carroll  KK.  Dietary protein in relation to plasma cholesterol levels and atherosclerosis.  Nutr Rev. 1978;36(1):1-5. doi:10.1111/j.1753-4887.1978.tb03670.xPubMedGoogle ScholarCrossref
    14.
    Tominaga  S, Kuroishi  T.  An ecological study on diet/nutrition and cancer in Japan.  Int J Cancer. 1997;(suppl 10):2-6. doi:10.1002/(SICI)1097-0215(1997)10+<2::AID-IJC2>3.0.CO;2-CPubMedGoogle Scholar
    15.
    Levine  ME, Suarez  JA, Brandhorst  S,  et al.  Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population.  Cell Metab. 2014;19(3):407-417. doi:10.1016/j.cmet.2014.02.006PubMedGoogle ScholarCrossref
    16.
    Kelemen  LE, Kushi  LH, Jacobs  DR  Jr, Cerhan  JR.  Associations of dietary protein with disease and mortality in a prospective study of postmenopausal women.  Am J Epidemiol. 2005;161(3):239-249. doi:10.1093/aje/kwi038PubMedGoogle ScholarCrossref
    17.
    Song  M, Fung  TT, Hu  FB,  et al.  Association of animal and plant protein intake with all-cause and cause-specific mortality.  JAMA Intern Med. 2016;176(10):1453-1463. doi:10.1001/jamainternmed.2016.4182PubMedGoogle ScholarCrossref
    18.
    Japan Ministry of Education. Culture, Sports, Science and Technology. Standard Tables of Food Composition in Japan. 5th ed, revised and enlarged. Tokyo: National Printing Bureau; 2005
    19.
    Ishihara  J, Sobue  T, Yamamoto  S,  et al; JPHC.  Validity and reproducibility of a self-administered food frequency questionnaire in the JPHC Study cohort II: study design, participant profile and results in comparison with cohort I.  J Epidemiol. 2003;13(1)(suppl):S134-S147. doi:10.2188/jea.13.1sup_134PubMedGoogle ScholarCrossref
    20.
    Tsugane  S, Kobayashi  M, Sasaki  S; JPHC.  Validity of the self-administered food frequency questionnaire used in the 5-year follow-up survey of the JPHC Study cohort I: comparison with dietary records for main nutrients.  J Epidemiol. 2003;13(1)(suppl):S51-S56. doi:10.2188/jea.13.1sup_51PubMedGoogle ScholarCrossref
    21.
    Nanri  A, Mizoue  T, Kurotani  K,  et al; Japan Public Health Center-Based Prospective Study Group.  Low-carbohydrate diet and type 2 diabetes risk in Japanese men and women: the Japan Public Health Center–Based Prospective Study.  PLoS One. 2015;10(2):e0118377. doi:10.1371/journal.pone.0118377PubMedGoogle ScholarCrossref
    22.
    Willett  W.  Nutritional Epidemiology. 3rd ed. New York, NY: Oxford University Press; 2013.
    23.
    Song  M, Giovannucci  E.  Substitution analysis in nutritional epidemiology: proceed with caution.  Eur J Epidemiol. 2018;33(2):137-140. doi:10.1007/s10654-018-0371-2PubMedGoogle ScholarCrossref
    24.
    Kurotani  K, Akter  S, Kashino  I,  et al; Japan Public Health Center based Prospective Study Group.  Quality of diet and mortality among Japanese men and women: Japan Public Health Center Based Prospective Study.  BMJ. 2016;352:i1209. doi:10.1136/bmj.i1209PubMedGoogle ScholarCrossref
    25.
    Tielemans  SM, Kromhout  D, Altorf-van der Kuil  W, Geleijnse  JM.  Associations of plant and animal protein intake with 5-year changes in blood pressure: the Zutphen Elderly Study.  Nutr Metab Cardiovasc Dis. 2014;24(11):1228-1233. doi:10.1016/j.numecd.2014.05.013PubMedGoogle ScholarCrossref
    26.
    Shang  X, Scott  D, Hodge  A,  et al.  Dietary protein from different food sources, incident metabolic syndrome and changes in its components: an 11-year longitudinal study in healthy community-dwelling adults.  Clin Nutr. 2017;36(6):1540-1548. doi:10.1016/j.clnu.2016.09.024PubMedGoogle ScholarCrossref
    27.
    Chalvon-Demersay  T, Azzout-Marniche  D, Arfsten  J,  et al.  A systematic review of the effects of plant compared with animal protein sources on features of metabolic syndrome.  J Nutr. 2017;147(3):281-292.PubMedGoogle Scholar
    28.
    Elliott  P, Stamler  J, Dyer  AR,  et al.  Association between protein intake and blood pressure: the INTERMAP Study.  Arch Intern Med. 2006;166(1):79-87. doi:10.1001/archinte.166.1.79PubMedGoogle ScholarCrossref
    29.
    Allen  NE, Appleby  PN, Davey  GK, Kaaks  R, Rinaldi  S, Key  TJ.  The associations of diet with serum insulin-like growth factor I and its main binding proteins in 292 women meat-eaters, vegetarians, and vegans.  Cancer Epidemiol Biomarkers Prev. 2002;11(11):1441-1448.PubMedGoogle Scholar
    30.
    Holmes  MD, Pollak  MN, Willett  WC, Hankinson  SE.  Dietary correlates of plasma insulin-like growth factor I and insulin-like growth factor binding protein 3 concentrations.  Cancer Epidemiol Biomarkers Prev. 2002;11(9):852-861.PubMedGoogle Scholar
    31.
    van Baak  MA, Larsen  TM, Jebb  SA,  et al.  Dietary intake of protein from different sources and weight regain, changes in body composition and cardiometabolic risk factors after weight loss: the DIOGenes Study.  Nutrients. 2017;9(12):E1326. doi:10.3390/nu9121326PubMedGoogle ScholarCrossref
    32.
    Shang  X, Scott  D, Hodge  AM,  et al.  Dietary protein intake and risk of type 2 diabetes: results from the Melbourne Collaborative Cohort Study and a meta-analysis of prospective studies.  Am J Clin Nutr. 2016;104(5):1352-1365. doi:10.3945/ajcn.116.140954PubMedGoogle ScholarCrossref
    33.
    Malik  VS, Li  Y, Tobias  DK, Pan  A, Hu  FB.  Dietary protein intake and risk of type 2 diabetes in US men and women.  Am J Epidemiol. 2016;183(8):715-728. doi:10.1093/aje/kwv268PubMedGoogle ScholarCrossref
    34.
    Papandreou  C, Becerra-Tomas  N, Bullo  M,  et al.  Legume consumption and risk of all-cause, cardiovascular, and cancer mortality in the PREDIMED study.  Clin Nutr. 2019;38(1):348-356. doi:10.1016/j.clnu.2017.12.019PubMedGoogle ScholarCrossref
    35.
    Aune  D, Keum  N, Giovannucci  E,  et al.  Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies.  BMJ. 2016;353:i2716. doi:10.1136/bmj.i2716PubMedGoogle ScholarCrossref
    36.
    Abete  I, Romaguera  D, Vieira  AR, Lopez de Munain  A, Norat  T.  Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies.  Br J Nutr. 2014;112(5):762-775. doi:10.1017/S000711451400124XPubMedGoogle ScholarCrossref
    37.
    Etemadi  A, Sinha  R, Ward  MH,  et al.  Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study.  BMJ. 2017;357:j1957. doi:10.1136/bmj.j1957PubMedGoogle ScholarCrossref
    38.
    Kurotani  K, Budhathoki  S, Joshi  AM,  et al.  Dietary patterns and colorectal cancer in a Japanese population: the Fukuoka Colorectal Cancer Study.  Br J Nutr. 2010;104(11):1703-1711. doi:10.1017/S0007114510002606PubMedGoogle ScholarCrossref
    39.
    Nanri  A, Shimazu  T, Takachi  R,  et al; Japan Public Health Center-based Prospective Study Group.  Dietary patterns and type 2 diabetes in Japanese men and women: the Japan Public Health Center–Based Prospective Study.  Eur J Clin Nutr. 2013;67(1):18-24. doi:10.1038/ejcn.2012.171PubMedGoogle ScholarCrossref
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