NutriQuébec: a unique web-based prospective cohort study to monitor the population's eating and other lifestyle behaviours in the province of Québec

Annie Lapointe, Catherine Laramée, Ariane Belanger-Gravel, David L Buckeridge, Sophie Desroches, Didier Garriguet, Lise Gauvin, Simone Lemieux, Céline Plante, Benoit Lamarche, Annie Lapointe, Catherine Laramée, Ariane Belanger-Gravel, David L Buckeridge, Sophie Desroches, Didier Garriguet, Lise Gauvin, Simone Lemieux, Céline Plante, Benoit Lamarche

Abstract

Introduction: The epidemic of non-communicable diseases including cardiovascular diseases and type 2 diabetes is attributable in large part to unhealthy eating and physical inactivity. In the fall of 2016, the Québec government launched its first-ever Government Health Prevention Policy (Politique gouvernementale de prévention en santé (PGPS)) to influence factors that lead to improved health status and quality of life as well as reduced social inequalities in health in the population of Québec. NutriQuébec is a web-based prospective open cohort study whose primary aim is to provide essential data for the evaluation of the PGPS on the Québec population's eating and other lifestyle behaviours over time.

Methods and analysis: Over a first phase of 3 years, NutriQuébec will enrol 20 000 adults living in the province of Québec in Canada through a multimedia campaign designed to reach different segments of the population, including subgroups with lower socioeconomic status. Participants will be invited to complete on a web platform nine core questionnaires on a yearly basis. Questionnaires will assess several dimensions related to lifestyle, including eating and physical activity behaviours, as well as a large number of personal characteristics and global health status. Temporal trends in eating and lifestyle behaviours will be analysed in relation to the implementation of the PGPS to provide essential data for its evaluation at a population level. Data analyses will use sociodemographic weights to adjust responses of participants to achieve, so far as is possible, representativeness of the adult Québec population.

Ethics and dissemination: Université Laval Research Ethics Board approved the NutriQuébec project. Data analysis, presentations in conferences and publication of manuscripts are scheduled to start in 2020.

Trial registration number: NCT04140071.

Keywords: nutrition & dietetics; public health; world wide web technology.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

References

    1. Institut national de santé publique du Québec Prévalence dsu diabète pour la population d’un an et plus, années financières 2000-2001 2016-2017. Système intégré de surveillance des maladies chroniques du Québec (SISMACQ). Rapport de l’onglet plan national de surveillance produit par l’Infocentre de santé publique l’Institut national de santé publique du Québec, 2019.
    1. GBD 2017 Diet Collaborators Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the global burden of disease study 2017. Lancet 2019;393:1958–72. 10.1016/S0140-6736(19)30041-8
    1. Loucks EB, Lynch JW, Pilote L, et al. . Life-Course socioeconomic position and incidence of coronary heart disease: the Framingham offspring study. Am J Epidemiol 2009;169:829–36. 10.1093/aje/kwn403
    1. Bird Y, Lemstra M, Rogers M, et al. . The relationship between socioeconomic status/income and prevalence of diabetes and associated conditions: a cross-sectional population-based study in Saskatchewan, Canada. Int J Equity Health 2015;14:93. 10.1186/s12939-015-0237-0
    1. Gershon AS, Dolmage TE, Stephenson A, et al. . Chronic obstructive pulmonary disease and socioeconomic status: a systematic review. COPD 2012;9:216–26. 10.3109/15412555.2011.648030
    1. Marmot M, Friel S, Bell R, et al. . Closing the gap in a generation: health equity through action on the social determinants of health. Lancet 2008;372:1661–9. 10.1016/S0140-6736(08)61690-6
    1. World Health Organization Preventing chronic diseases a vital investment. Available:
    1. Brassard D, Laramée C, Corneau L, et al. . Poor adherence to dietary guidelines among French-speaking adults in the province of Quebec, Canada: the PREDISE study. Can J Cardiol 2018;34:1665–73. 10.1016/j.cjca.2018.09.006
    1. Ministère de la santé et des services sociaux Politique gouvernementale de prévention en santé. La direction des communications du ministère de la santé et des services sociaux. Québec: Gouvernement du Québec, 2016.
    1. Ministère de la santé et services sociaux du Québec Plan d’action interministériel 2017-2021 de la Politique gouvernementale de Prévention en santé, 2017. Available:
    1. Institut de la statistique du Québec Québec population health survey (QPHS) 2008 and 2014-2015. version current 2015 [online]. Available: [Accessed 13 Jul 2020].
    1. Statistics Canada Canadian community health survey (CCHS). version current 27 November 2019 [online]. Available: [Accessed 13 Jul 2020].
    1. Bonevski B, Randell M, Paul C, et al. . Reaching the hard-to-reach: a systematic review of strategies for improving health and medical research with socially disadvantaged groups. BMC Med Res Methodol 2014;14:42. 10.1186/1471-2288-14-42
    1. NutriQuébec team NutriQuébec Facebook page. Available:
    1. Lemieux V. Pour qu’on se comprenne: guide de littératie en santé. Available:
    1. Lafrenière J, Laramée C, Robitaille J, et al. . Assessing the relative validity of a new, web-based, self-administered 24 H dietary recall in a French-Canadian population. Public Health Nutr 2018;21:2744–52. 10.1017/S1368980018001611
    1. Jacques S, Lemieux S, Lamarche B, et al. . Development of a web-based 24-h dietary recall for a French-Canadian population. Nutrients 2016;810.3390/nu8110724
    1. Lafrenière J, Laramée C, Robitaille J, et al. . Relative validity of a web-based, self-administered, 24-h dietary recall to evaluate adherence to Canadian dietary guidelines. Nutrition 2019;57:252–6. 10.1016/j.nut.2018.04.016
    1. Savard C, Lemieux S, Lafrenière J, et al. . Validation of a self-administered web-based 24-hour dietary recall among pregnant women. BMC Pregnancy Childbirth 2018;18:112. 10.1186/s12884-018-1741-1
    1. Lafrenière J, Couillard C, Lamarche B, et al. . Associations between self-reported vegetable and fruit intake assessed with a new web-based 24-h dietary recall and serum carotenoids in free-living adults: a relative validation study. J Nutr Sci 2019;8:1–9. 10.1017/jns.2019.23
    1. Lafrenière J, Lamarche B, Laramée C, et al. . Validation of a newly automated web-based 24-hour dietary recall using fully controlled feeding studies. BMC Nutr 2017;3:34. 10.1186/s40795-017-0153-3
    1. Moshfegh AJ, Rhodes DG, Baer DJ, et al. . The US department of agriculture automated Multiple-Pass method reduces bias in the collection of energy intakes. Am J Clin Nutr 2008;88:324–32. 10.1093/ajcn/88.2.324
    1. Garriguet D. Diet quality in Canada. Health Rep 2009;20:41–52.
    1. Carbonneau E, Lamarche B, Lafrenière J, et al. . Are French Canadians able to accurately self-rate the quality of their diet? insights from the PREDISE study. Appl Physiol Nutr Metab 2019;44:293–300. 10.1139/apnm-2018-0293
    1. Bradette-Laplante M, Carbonneau Élise, Provencher V, et al. . Development and validation of a nutrition knowledge questionnaire for a Canadian population. Public Health Nutr 2017;20:1184–92. 10.1017/S1368980016003372
    1. Carbonneau E, Bradette-Laplante M, Lamarche B, et al. . Development and validation of the food liking questionnaire in a French-Canadian population. Nutrients 2017;9:1337 10.3390/nu9121337
    1. Carbonneau E, Bradette-Laplante M, Lamarche B, et al. . Social support for healthy eating: development and validation of a questionnaire for the French-Canadian population. Public Health Nutr 2018;21:2360–6. 10.1017/S1368980018001209
    1. Carbonneau E, Carbonneau N, Lamarche B, et al. . Validation of a French-Canadian adaptation of the intuitive eating Scale-2 for the adult population. Appetite 2016;105:37–45. 10.1016/j.appet.2016.05.001
    1. Carbonneau E, Robitaille J, Lamarche B, et al. . Development and validation of the perceived food environment questionnaire in a French-Canadian population. Public Health Nutr 2017;20:1914–20. 10.1017/S1368980017000581
    1. Côté M, Harrison S, Lapointe A, et al. . A cross-sectional survey examining motivation and beliefs to participating in a web-based prospective cohort study on nutrition and health among individuals with a low socioeconomic status. BMC Public Health 2020;20:348. 10.1186/s12889-020-08467-1
    1. Côté M, Lapointe A, Laramée C, et al. . Beliefs related to participation in a large web-based prospective survey on diet and health among individuals with a low socioeconomic status: qualitative study. JMIR Form Res 2019;3:e13854. 10.2196/13854
    1. NutriQuébec team NutriQuébec website. Available:
    1. PULSAR PULSAR, 2019. Available:
    1. Garratt AM, Ruta DA, Abdalla MI, et al. . The SF36 health survey questionnaire: an outcome measure suitable for routine use within the NHS? BMJ 1993;306:1440–4. 10.1136/bmj.306.6890.1440
    1. Godin G, Bélanger-Gravel A, Paradis A-marie, et al. . A simple method to assess fruit and vegetable intake among obese and non-obese individuals. Can J Public Health 2008;99:494–8. 10.1007/BF03403784
    1. Vézina-Im L-A, Godin G, Couillard C, et al. . Validity and reliability of a brief self-reported questionnaire assessing fruit and vegetable consumption among pregnant women. BMC Public Health 2016;16:982. 10.1186/s12889-016-3656-y
    1. Blais FC, Gendron L, Mimeault V, et al. . [Evaluation of insomnia: validity of 3 questionnaires]. Encephale 1997;23:447–53.
    1. Buysse DJ, Reynolds CF, Monk TH, et al. . The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193–213. 10.1016/0165-1781(89)90047-4
    1. Statistics Canada Census program. version current 9 June 2020 [online]. Available: [Accessed 13 Jul 2020].
    1. Statistics Canada Canadian health measures survey. version current 4 Mars 2020 [online]. Available: [Accessed 13 Jul 2020].
    1. Godin G, Shephard R. Godin leisure-time exercise questionnaire. Med Sci Sports Exerc 1997;26:S36–8.
    1. Amireault S, Godin G. The Godin-Shephard leisure-time physical activity questionnaire: validity evidence supporting its use for classifying healthy adults into active and insufficiently active categories. Percept Mot Skills 2015;120:604–22. 10.2466/03.27.PMS.120v19x7
    1. Wareham NJ, Jakes RW, Rennie KL, et al. . Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European prospective investigation into cancer and nutrition (EPIC) study. Public Health Nutr 2003;6:407–13. 10.1079/PHN2002439
    1. Khaw K-T, Jakes R, Bingham S, et al. . Work and leisure time physical activity assessed using a simple, pragmatic, validated questionnaire and incident cardiovascular disease and all-cause mortality in men and women: the European prospective investigation into cancer in Norfolk prospective population study. Int J Epidemiol 2006;35:1034–43. 10.1093/ije/dyl079
    1. Perneger TV, Leplège A, Etter JF, et al. . Validation of a French-language version of the mos 36-Item short form health survey (SF-36) in young healthy adults. J Clin Epidemiol 1995;48:1051–60. 10.1016/0895-4356(94)00227-h
    1. Kelly MP, Barker M. Why is changing health-related behaviour so difficult? Public Health 2016;136:109–16. 10.1016/j.puhe.2016.03.030
    1. Carroll R, Ruppert D, Stefanski L, et al. . Measurement error in nonlinear models. New York: Chapman and Hall/CRC 2006.
    1. Tooze JA, Kipnis V, Buckman DW, et al. . A mixed-effects model approach for estimating the distribution of usual intake of nutrients: the NCI method. Stat Med 2010;29:2857–68. 10.1002/sim.4063
    1. Tooze JA, Midthune D, Dodd KW, et al. . A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc 2006;106:1575–87. 10.1016/j.jada.2006.07.003
    1. National Cancer Institute Usual dietary intakes: the NCI method, 2020. Available:
    1. Cefrio Portrait numérique des foyers québécois, 2018. Available:
    1. Cefrio Les plus vieux babyboomers et leurs parents 65 ans et plus (1954 et avant), 2018. Available:
    1. Cefrio Génération Z (18-24 ans), 2018. Available:
    1. Bernier M. L’utilisation d’Internet chez les Québécois, 2017. Available:
    1. Côté M, Lapointe A, Laramée C, et al. . Participation NutriQuébec : croyances des personnes issues de milieux défavorisés. Poster presented to the 2019 annual meeting of the Société Québécoise de Lipidologie, Nutrition et Métabolisme (SQLNM), du Réseau de recherche en santé CardioMétabolique, Diabète et Obésité (CMDO) et de COLosSUS, 2018.
    1. Kesse-Guyot E, Assmann K, Andreeva V, et al. . Lessons learned from methodological validation research in E-Epidemiology. JMIR Public Health Surveill 2016;2:e160 10.2196/publichealth.5880
    1. Kesse-Guyot E, Andreeva V, Castetbon K, et al. . Participant profiles according to recruitment source in a large web-based prospective study: experience from the Nutrinet-Santé study. J Med Internet Res 2013;15:e205. 10.2196/jmir.2488
    1. Whitaker C, Stevelink S, Fear N. The use of Facebook in recruiting participants for health research purposes: a systematic review. J Med Internet Res 2017;19:e290. 10.2196/jmir.7071
    1. Topolovec-Vranic J, Natarajan K. The use of social media in recruitment for medical research studies: a scoping review. J Med Internet Res 2016;18:e286. 10.2196/jmir.5698
    1. Clarity group - McMaster University Tool to assess risk of bias in cohort studies, 2018. Available:

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi