Diet-disease relationships: Recent advances in nutritional epidemiology

Raul Zamora-Ros, Carlos Alberto González

Abstract


Nutritional epidemiology currently studies the diet-disease relationships. In order to evaluate these associations, an accurate estimation of nutritional exposure is essential. Traditional dietary questionnaires are being complemented with the measurement of nutritional biomarkers. New methodologies, including the use of new dietary assessments, metabolomics for increasing the quantity and quality of biomarkers, and statistical approaches to combine both techniques, are required to move forward in this field. In this review, we have selected five of the more relevant accomplishments in this field as examples of the importance of dietary factors in the prevention of non-communicable diseases. This theoretical knowledge needs to be finally translated by public health experts into dietary recommendations to the general population.

Keywords


nutritional epidemiology; fruits and vegetables; red and processed meat; sugar-sweetened beverages; Mediterranean diet

Full Text: PDF

DOI: https://doi.org/10.7203/metode.11.16205

References


Aune, D., Giovannucci, E., Boffetta, P., Fadnes, L. T., Keum, N. N., Norat, T., Greenwood, D. C., Riboli, E., Vatten, L. J., & Tonstad, S. (2017). Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. International Journal of Epidemiology, 46(3), 1029–1056. https://doi.org/10.1093/ije/dyw319

Boeing, H. (2013). Nutritional epidemiology: New perspectives for understanding the diet-disease relationship? European Journal of Clinical Nutrition, 67(5), 424–429. https://doi.org/10.1038/ejcn.2013.47

Bouvard, V., Loomis, D., Guyton, K. Z., Grosse, Y., Ghissassi, F. E., Benbrahim-Tallaa, L., Guha, N., Mattock, H., & Straif, K. (2015). Carcinogenicity of consumption of red and processed meat. Lancet Oncology, 16(16), 1599–1600. https://doi.org/10.1016/S1470-2045(15)00444-1

Brandolini-Bunlon, M., Pétéra, M., Gaudreau, P., Comte, B., Bougeard, S., & Pujos-Guillot, E. (2019). Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10), 134. https://doi.org/10.1007/s11306-019-1598-y

Estruch, R., Ros, E., Salas-Salvadó, J., Covas, M.-I., Corella, D., Arós, F., Gómez-Gracia, E., Ruiz-Gutiérrez, V., Fiol, M., Lapetra, J., Lamuela-Raventos, R. M., Serra-Majem, L., Pintó, X., Basora, J., Muñoz, M. A., Sorlí, J. V., Martínez, J. A., Fitó, M., Gea, A., … Martínez-González, M. A. (2018). Primary prevention of cardiovascular disease with a mediterranean diet supplemented with extra-virgin olive oil or nuts. New England Journal of Medicine, 378(25), e34. https://doi.org/10.1056/NEJMoa1800389

Forouhi, N. G., & Unwin, N. (2019). Global diet and health: Old questions, fresh evidence, and new horizons. Lancet, 393(10184), 1916–1918. https://doi.org/10.1016/S0140-6736(19)30500-8

Freedman, L. S., Tasevska, N., Kipnis, V., Schatzkin, A., Mares, J., Tinker, L., & Potischman, N. (2010). Gains in statistical power from using a dietary biomarker in combination with self-reported intake to strengthen the analysis of a diet-disease association: An example from CAREDS. American Journal of Epidemiology, 172(7), 836−842. https://doi.org/10.1093/aje/kwq194

Galbete, C., Schwingshackl, L., Schwedhelm, C., Boeing, H., & Schulze, M. B. (2018). Evaluating mediterranean diet and risk of chronic disease in cohort studies: An umbrella review of meta-analyses. European Journal of Epidemiology, 33(10), 909–931. https://doi.org/10.1007/s10654-018-0427-3

GBD 2017 Diet Collaborators. (2019). Health effects of dietary risks in 195 countries, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 393(10184), 1958–1972. https://doi.org/10.1016/S0140-6736(19)30041-8

Gormley, I. C., Bai, Y., & Brennan, L. (2020). Combining biomarker and self-reported dietary intake data: A review of the state of the art and an exposition of concepts. Statistical Methods in Medical Research, 29(2), 617–635. https://doi.org/10.1177/0962280219837698

Hu, F. B. (2013). Resolved: There is sufficient scientific evidence that decreasing sugar-sweetened beverage consumption will reduce the prevalence of obesity and obesity-related diseases. Obesity Reviews, 14(8), 606–619. https://doi.org/10.1111/obr.12040

Illner, A.-K., Freisling, H., Boeing, H., Huybrechts, I., Crispim, S., & Slimani, N. (2012). Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. International Journal of Epidemiology, 41, 1187–1203. https://doi.org/10.1093/ije/dys105

Johnston, B. C., Zeraatkar, D., Han, M. A., Vernooij, R. W. M., Valli, C., El Dib, R., Marshall, C., Stover, P. J., Fairweather-Taitt, S., Wójcik, G., Bhatia, F., de Souza, R., Brotons, C., Meerpohl, J. J., Patel, C. J., Djulbegovic, B., Alonso-Coello, P., Bala, M. M., & Guyatt, G. H. (2019). Unprocessed red meat and processed meat consumption: Dietary guideline recommendations from the nutritional recommendations (NutriRECS) Consortium. Annals Internal of Medicine, 171(10), 756–764. https://doi.org/10.7326/M19-1621

Li, J., Guasch-Ferré, M., Chung, W., Ruiz-Canela, M., Toledo, E., Corella, D., Bhupathiraju, S. N., Tobias, D. K., Tabung, F. K., Hu, J., Zhao, T., Turman, C., Feng, Y.-C. A., Clish, C. B., Mucci, L., Eliassen, A. H., Costenbader, K. H., Karlson, E. W., Wolpin, B. M., … Liang, L. (2020). The mediterranean diet, plasma metabolome, and cardiovascular disease risk. European Heart Journal, ehaa209. https://doi.org/10.1093/eurheartj/ehaa209

NCD Risk Factor Collaboration. (NCD-RisC). (2016). Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19·2 million participants. The Lancet, 387(10026), 1377–1396. https://doi.org/10.1016/S0140-6736(16)30054-X

Potischman, N. (2003). Biologic and methodologic issues for nutritional biomarkers. Journal of Nutrition, 133(3), 875S–880S. https://doi.org/10.1093/jn/133.3.875S

Shaw, P. A., Deffner, V., Keogh, R. H., Tooze, J. A., Dodd, K. W., Küchenhoff, H., Kipnis, V., Freedman, L. S., Measurement Error and Misclassification Topic Group (TG4) of the STRATOS Initiative. (2018). Epidemiologic analyses with error-prone exposures: Review of current practice and recommendations. Annals of Epidemiology, 28(11), 821–828. https://doi.org/10.1016/j.annepidem.2018.09.001

Singh, G. M., Micha, R., Khatibzadeh, S., Lim, S., Ezzati, M., Mozaffarian, D., & Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). (2015). Estimated global, regional, and national disease burdens related to sugar-sweetened beverage consumption in 2010. Circulation, 132(8), 639–666. http://doi.org/10.1161/CIRCULATIONAHA.114.010636

Ulaszewska, M. M., Weinert, C. H., Trimigno, A., Portmann, R., Andres Lacueva, C., Badertscher, R., Brennan, L., Brunius, C., Bub, A., Capozzi, F., Cialiè Rosso, M., Cordero, C. E., Daniel, H., Durand, S., Egert, B., Ferrario, P. G., Feskens, E. J. M., Franceschi, P., Garcia-Aloy, M., … Vergères, G. (2018). Nutrimetabolomics: An integrative action for metabolomic analyses in human nutritional studies. Molecular Nutrition & Food Research, 63(1), e1800384. https://doi.org/10.1002/mnfr.201800384

Vieira, A. R., Abar, L., Chan, D. S. M., Vingeliene, S., Polemiti, E., Stevens, C., Greenwood, D., & Norat, T. (2017). Foods and beverages and colorectal cancer risk: A systematic review and meta-analysis of cohort studies, an update of the evidence of the WCRF-AICR Continuous Update Project. Annals of Oncology, 28(8), 1788–1802. https://doi.org/10.1093/annonc/mdx171


Refbacks

  • There are currently no refbacks.