Bryna Shatenstein

Dr. Bryna Shatenstein


Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2007 in Journal of the American Dietetic Association
Verified
Journal Article
Closed access
BSBryna Shatenstein
Bryna Shatenstein
MKMarie-Jeanne Kergoat
Marie-Jeanne Kergoat
IRIsabelle Reid
Isabelle Reid

1 May 2012 in Experimental Gerontology
Verified
Journal Article
Closed access
BSBryna Shatenstein
Bryna Shatenstein
GFGuylaine Ferland
Guylaine Ferland
SBSylvie Belleville
Sylvie Belleville
KGKatherine Gray-Donald
Katherine Gray-Donald
MKMarie-Jeanne Kergoat
Marie-Jeanne Kergoat
CGCarol Greenwood
Carol Greenwood

1 August 2005 in Journal of the American Dietetic Association
Verified
Journal Article
Closed access
BSBryna Shatenstein
Bryna Shatenstein
SNSylvie Nadon
Sylvie Nadon
CGCatherine Godin
Catherine Godin
GFGuylaine Ferland
Guylaine Ferland

19 February 2013 in The Journal of nutrition, health and aging
Verified
Journal Article
Open access
PDF file
BSBryna Shatenstein
Bryna Shatenstein
Lise GauvinLise Gauvin
Lise Gauvin
HKH. Keller
H. Keller
LRL. Richard
L. Richard
PGP. Gaudreau
P. Gaudreau
HPH. Payette
H. Payette
Judicious food choices are of prime importance during aging.

4 August 2015 in Nutrients
Verified
Journal Article
Open access
PDF file
BSBryna Shatenstein
Bryna Shatenstein
HPHélène Payette
Hélène Payette
A 36-item Short Diet Questionnaire (SDQ) was developed to assess usual consumption frequencies of foods providing fats, fibre, calcium, vitamin D, in addition to fruits and vegetables. It was pretested among 30 community-dwelling participants from the Québec Longitudinal Study on Nutrition and Successful Aging, “NuAge” (n = 1793, 52.4% women), recruited in three age groups (70 ± 2 years; 75 ± 2 years; 80 ± 2 years). Following revision, the SDQ was administered to 527 NuAge participants (55% female), distributed among the three age groups, both sexes and languages (French, English) prior to the second of three non-consecutive 24 h diet recalls (24HR) and validated relative to the mean of three 24HR. Full data were available for 396 participants. Most SDQ nutrients and fruit and vegetable servings were lower than 24HR estimates (p < 0.05) except calcium, vitamin D, and saturated and trans fats. Spearman correlations between the SDQ and 24HR were modest and significant (p < 0.01), ranging from 0.19 (cholesterol) to 0.45 (fruits and vegetables). Cross-classification into quartiles showed 33% of items were jointly classified into identical quartiles of the distribution, 73% into identical and contiguous quartiles, and only 7% were frankly misclassified. The SDQ is a reasonably accurate, rapid approach for ranking usual frequencies of selected nutrients and foods. Further testing is needed in a broader age range.

1 March 2014 in The Journal of Nutrition
Verified
Journal Article
Open access
PDF file
KGKatherine Gray-Donald
Katherine Gray-Donald
DADanielle St- Arnaud-McKenzie
Danielle St- Arnaud-McKenzie
PGPierrette Gaudreau
Pierrette Gaudreau
JMJosé A. Morais
José A. Morais
BSBryna Shatenstein
Bryna Shatenstein
HPHélène Payette
Hélène Payette
Weight loss is prevalent in the elderly population, with deleterious health consequences, notably loss of lean body mass and subsequent functional decline. Protein intake below the current RDA [0.8 g/(kg · d)] is also common in older adults; however, the link between the 2 has received little attention. Our objective was to assess the relation between protein intake and incident 1-y weight loss ≥5% in community-dwelling older adults. We conducted a nested, prospective, case-control study in 1793 community-living elderly participants of the Quebec Longitudinal Study of Nutrition as a Determinant of Successful Aging (NuAge). We studied 211 incident cases of 1-y weight loss (≥5%) and 211 weight-stable controls (±2%) matched by sex and age category (70 ± 2, 75 ± 2, and 80 ± 2 y). Diet was measured by 3 nonconsecutive 24-h recalls. ORs (95% CIs) for the association between protein intake and weight loss were computed by using conditional logistic regression. After adjustment for body mass index, energy intake, appetite, smoking status, physical activity level, physical function, chronic diseases and medications, depressive symptoms, and serum albumin and ultrasensitive C-reactive protein, the ORs of weight loss in participants with low protein intakes [<0.8 g/(kg · d)] were 2.56 (95% CI: 1.01, 6.50) compared with participants with very high protein intakes [≥1.2 g/(kg · d)]. Corresponding numbers were 2.15 (95% CI: 1.02, 4.56) in participants with moderate protein intakes [0.8–1.0 g/(kg · d) are protective against weight loss in healthy older adults. These findings add epidemiologic evidence in support of higher optimal protein intakes than the current guidelines for healthy older adults.