Protein intake and the incidence of pre-diabetes and diabetes in 4 population-based studies: the PREVIEW project
Sluik, D. ; Brouwer, E.M. ; Berendsen, A.M. ; Mikkilä, V. ; Poppitt, Sally D. ; Silvestre, Marta P. ; Tremblay, A. ; Perusse, L. ; Bouchard, C. ; Raben, Anne ; Feskens, E.J.M. - \ 2019
American Journal of Clinical Nutrition 109 (2019)5. - ISSN 0002-9165 - p. 1310 - 1318.
Background:Data on the relationship between protein intake andthe risk of type 2 diabetes are conflicting.Objectives:We studied prospective associations between the intakeof total, plant-based, and animal protein and the risk of pre-diabetesand diabetes in 4 population-based studies included in the PREVIEWproject.Methods:Analyses were conducted with the use of data from 3 Eu-ropean cohorts and 1 Canadian cohort, including 78,851 participants.Protein intake was assessed through the use of harmonized datafrom food-frequency questionnaires or 3-d dietary records. Cohort-specific incidence ratios (IRs) were estimated for pre-diabetes anddiabetes, adjusting for general characteristics, lifestyle and dietaryfactors, disease history, and body mass index (BMI) and waistcircumference; results were pooled based on a random-effects meta-analysis.Results:Higher total protein intake (g·kg–1·d–1) was associatedwith lower incidences of pre-diabetes and diabetes (pooled IRs: 0.84;95% CI: 0.82, 0.87 and 0.49; 95% CI: 0.28, 0.83, respectively); plant-based protein intake was the main determinant (pooled IRs: 0.83;95% CI: 0.81, 0.86 and 0.53; 95% CI: 0.36, 0.76, respectively).Substituting 2 energy percentage (E%) protein at the expense ofcarbohydrates revealed increased risks of pre-diabetes and diabetes(pooled IRs: 1.04; 95% CI: 1.01, 1.07 and 1.09; 95% CI: 1.01, 1.18,respectively). Except for the associations between intakes of totalprotein and plant-based protein (g·kg–1·d–1) and diabetes, all otherassociations became nonsignificant after adjustment for BMI andwaist circumference.Conclusions:Higher protein intake (g·kg–1·d–1) was associatedwith a lower risk of pre-diabetes and diabetes. Associationswere substantially attenuated after adjustments for BMI and waistcircumference, which demonstrates a crucial role for adiposityand may account for previous conflicting findings. This study wasregistered at ISRCTN as ISRCTN31174892.
PREVIEW study—Influence of a behavior modification intervention (PREMIT) in over 2300 people with pre-diabetes : Intention, self-efficacy and outcome expectancies during the early phase of a lifestyle intervention
Huttunen-Lenz, Maija ; Hansen, Sylvia ; Christensen, Pia ; Larsen, Thomas Meinert ; Sandø-Pedersen, Finn ; Drummen, Mathijs ; Adam, Tanja C. ; Macdonald, Ian A. ; Taylor, Moira A. ; Martinez, J.A. ; Navas-Carretero, Santiago ; Handjiev, Svetoslav ; Poppitt, Sally D. ; Silvestre, Marta P. ; Fogelholm, Mikael ; Pietiläinen, Kirsi H. ; Brand-Miller, Jennie ; Berendsen, Agnes A.M. ; Raben, Anne ; Schlicht, Wolfgang - \ 2018
Psychology Research and Behavior Management 11 (2018). - ISSN 1179-1578 - p. 383 - 394.
Cognition - Diabetes mellitus - Goals - Habits - Weight loss
Purpose: Onset of type 2 diabetes (T2D) is often gradual and preceded by impaired glucose homeostasis. Lifestyle interventions including weight loss and physical activity may reduce the risk of developing T2D, but adherence to a lifestyle change is challenging. As part of an international T2D prevention trial (PREVIEW), a behavior change intervention supported participants in achieving a healthier diet and physically active lifestyle. Here, our aim was to explore the influence of this behavioral program (PREMIT) on social-cognitive variables during an 8-week weight loss phase. Methods: PREVIEW consisted of an initial weight loss, Phase I, followed by a weight-maintenance, Phase II, for those achieving the 8-week weight loss target of ≥ 8% from initial bodyweight. Overweight and obese (BMI ≥25 kg/m2) individuals aged 25 to 70 years with confirmed pre-diabetes were enrolled. Uni-and multivariate statistical methods were deployed to explore differences in intentions, self-efficacy, and outcome expectancies between those who achieved the target weight loss (“achievers”) and those who did not (“non-achievers”). Results: At the beginning of Phase I, no significant differences in intentions, self-efficacy and outcome expectancies between “achievers” (1,857) and “non-achievers” (163) were found. “Non-achievers” tended to be younger, live with child/ren, and attended the PREMIT sessions less frequently. At the end of Phase I, “achievers” reported higher intentions (healthy eating χ2 (1)=2.57; P <0.008, exercising χ2 (1)=0.66; P <0.008), self-efficacy (F(2; 1970)=10.27, P <0.005), and were more positive about the expected outcomes (F(4; 1968)=11.22, P <0.005). Conclusion: Although statistically significant, effect sizes observed between the two groups were small. Behavior change, however, is multi-determined. Over a period of time, even small differences may make a cumulative effect. Being successful in behavior change requires that the “new” behavior is implemented time after time until it becomes a habit. Therefore, having even slightly higher self-efficacy, positive outcome expectancies and intentions may over time result in considerably improved chances to achieve long-term lifestyle changes.
Demographic and Social-Cognitive Factors Associated with Weight Loss in Overweight, Pre-diabetic Participants of the PREVIEW Study
Hansen, Sylvia ; Huttunen-Lenz, Maija ; Sluik, Diewertje ; Brand-Miller, Jennie ; Drummen, Mathijs ; Fogelholm, Mikael ; Handjieva-Darlenska, Teodora ; Macdonald, Ian ; Martinez, Alfredo J. ; Larsen, Thomas Meinert ; Poppitt, Sally ; Raben, Anne ; Schlicht, Wolfgang - \ 2018
International Journal of Behavioral Medicine 25 (2018)6. - ISSN 1070-5503 - p. 682 - 692.
Behavioral determination - Lifestyle intervention - Social-cognitive factors - Weight loss
Purpose: Weight loss has been demonstrated to be a successful strategy in diabetes prevention. Although weight loss is greatly influenced by dietary behaviors, social-cognitive factors play an important role in behavioral determination. This study aimed to identify demographic and social-cognitive factors (intention, self-efficacy, outcome expectancies, social support, and motivation with regard to dietary behavior and goal adjustment) associated with weight loss in overweight and obese participants from the PREVIEW study who had pre-diabetes. Method: Prospective correlational data from 1973 adult participants were analyzed. The participants completed psychological questionnaires that assessed social-cognitive variables with regard to dietary behavior. Stepwise multiple regression analyses were performed to identify baseline demographic and social-cognitive factors associated with weight loss. Results: Overall, being male, having a higher baseline BMI, having a higher income, perceiving fewer disadvantages of a healthy diet (outcome expectancies), experiencing less discouragement for healthy eating by family and friends (social support), and lower education were independently linked to greater weight loss. When evaluating females and males separately, education was no longer associated with weight loss. Conclusion: The results indicate that a supportive environment in which family members and friends avoid discouraging healthy eating, with the application of a strategy that uses specific behavior change techniques to emphasize the benefits of outcomes, i.e., the benefits of a healthy diet, may support weight loss efforts. Weight loss programs should therefore always address the social environment of persons who try to lose body weight because family members and friends can be important supporters in reaching a weight loss goal.
Objectively measured physical activity and sedentary time are associated with cardiometabolic risk factors in adults with prediabetes : The PREVIEW study
Swindell, Nils ; Mackintosh, Kelly ; Mcnarry, Melitta ; Stephens, Jeffrey W. ; Sluik, Diewertje ; Fogelholm, Mikael ; Drummen, Mathijs ; Macdonald, Ian ; Martinez, J.A. ; Handjieva-Darlenska, Teodora ; Poppitt, Sally D. ; Brand-Miller, Jennie ; Larsen, Thomas M. ; Raben, Anne ; Stratton, Gareth - \ 2018
Diabetes Care 41 (2018)3. - ISSN 0149-5992 - p. 562 - 569.
OBJECTIVE The aim of the present cross-sectional study was to examine the association among physical activity (PA), sedentary time (ST), and cardiometabolic risk in adults with prediabetes. RESEARCH DESIGN AND METHODS Participants (n = 2,326; 25-70 years old, 67% female) from eight countries, with a BMI >25 kg · m22 and impaired fasting glucose (5.6-6.9 mmol · L21) or impaired glucose tolerance (7.8-11.0 mmol · L21 at 2 h), participated. Seven-day accelerometry objectively assessed PA levels and ST. RESULTS Multiple linear regression revealed that moderate-To-vigorous PA (MVPA) was negatively associated withHOMAof insulin resistance (HOMA-IR) (standardizedb =20.078 [95% CI20.128,20.027]), waist circumference (WC) (b =20.177 [20.122,20.134]), fasting insulin (b = 20.115 [20.158, 20.072]), 2-h glucose (b = 20.069 [20.112, 20.025]), triglycerides (b = 20.091 [20.138, 20.044]), and CRP (b = 20.086 [20.127, 20.045]). ST was positively associated with HOMA-IR (b = 0.175 [0.114, 0.236]), WC (b = 0.215 [0.026, 0.131]), fasting insulin (b = 0.155 [0.092, 0.219]), triglycerides (b = 0.106 [0.052, 0.16]), CRP (b = 0.106 [0.39, 0.172]), systolic blood pressure (BP) (b = 0.078 [0.026, 0.131]), and diastolic BP (b = 0.106 [0.39, 20.172]). Associations reported between total PA (counts · min21), and all risk factors were comparable or stronger than for MVPA: HOMA-IR (b = 20.151 [20.194, 20.107]), WC (b = 20.179 [20.224, 20.134]), fasting insulin (b = 20.139 [20.183, 20.096]), 2-h glucose (b = 20.088 [20.131, 20.045]), triglycerides (b = 20.117 [20.162, 20.071]), and CRP (b = 20.104 [20.146, 20.062]). CONCLUSIONS In adults with prediabetes, objectively measured PA and ST were associated with cardiometabolic risk markers. Total PA was at least as strongly associated with cardiometabolic risk markers as MVPA, which may imply that the accumulation of total PA over the day is as important as achieving the intensity of MVPA.
|Energy requirements of pregnant and lactating women.
Prentice, A.M. ; Spaaij, C.J.K. ; Poppitt, S.D. ; Raaij, J.M.A. van; Totton, M. ; Swann, D. ; Black, A.E. - \ 1996
European Journal of Clinical Nutrition 50 (1996). - ISSN 0954-3007 - p. S82 - S111.