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English LK, Raghavan R, Obbagy JE, Callahan EH, Fultz AK, Nevins JEH, Scinto-Madonich S, Reigh NA, Stoody EE. Dietary Patterns and Health: Insights From NESR Systematic Reviews to Inform the Dietary Guidelines for Americans. JOURNAL OF NUTRITION EDUCATION AND BEHAVIOR 2024; 56:75-87. [PMID: 38185492 DOI: 10.1016/j.jneb.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 09/16/2023] [Accepted: 10/03/2023] [Indexed: 01/09/2024]
Abstract
This perspective article shares unique insights from the extensive experience of the US Department of Agriculture Nutrition Evidence Systematic Review branch in conducting systematic reviews on dietary patterns and health outcomes to inform the Dietary Guidelines for Americans. Methodological approaches for reviewing dietary patterns research are described, including approaches to operationalizing definitions and analyzing labeled dietary patterns. The review also describes techniques for synthesizing dietary patterns research across life stages in systematic reviews that inform food-based, federal dietary guidance. Current research activities and recommendations for how to improve or address gaps in dietary patterns research in the future are also discussed.
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Affiliation(s)
- Laural K English
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA.
| | - Ramkripa Raghavan
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Julie E Obbagy
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Emily H Callahan
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Amanda K Fultz
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Julie E H Nevins
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Sara Scinto-Madonich
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
| | - Nicole A Reigh
- Nutrition Evidence Systematic Review Branch, Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA; Panum Group, Bethesda, MD
| | - Eve E Stoody
- Nutrition Guidance and Analysis Division, Center for Nutrition Policy and Promotion, Food and Nutrition Service, US Department of Agriculture, Alexandria, VA
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The technique 'joint and individual variance explained' highlights persistent aspects of the diet using longitudinal food frequency data. Br J Nutr 2022; 128:2054-2062. [PMID: 34915946 DOI: 10.1017/s0007114521004955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Dietary pattern analysis is typically based on dimension reduction and summarises the diet with a small number of scores. We assess 'joint and individual variance explained' (JIVE) as a method for extracting dietary patterns from longitudinal data that highlights elements of the diet that are associated over time. The Auckland Birthweight Collaborative Study, in which participants completed an FFQ at ages 3·5 (n 549), 7 (n 591) and 11 (n 617), is used as an example. Data from each time point are projected onto the directions of shared variability produced by JIVE to yield dietary patterns and scores. We assess the ability of the scores to predict future BMI and blood pressure measurements of the participants and make a comparison with principal component analysis (PCA) performed separately at each time point. The diet could be summarised with three JIVE patterns. The patterns were interpretable, with the same interpretation across age groups: a vegetable and whole grain pattern, a sweets and meats pattern and a cereal v. sweet drinks pattern. The first two PCA-derived patterns were similar across age groups and similar to the first two JIVE patterns. The interpretation of the third PCA pattern changed across age groups. Scores produced by the two techniques were similarly effective in predicting future BMI and blood pressure. We conclude that when data from the same participants at multiple ages are available, JIVE provides an advantage over PCA by extracting patterns with a common interpretation across age groups.
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Coura AGL, de Arruda Neta ADCP, de Lima RLFC, Bersch-Ferreira ÂC, Weber B, Vianna RPDT. Tracking of Dietary Patterns in the Secondary Prevention of Cardiovascular Disease after a Nutritional Intervention Program-A Randomized Clinical Trial. Nutrients 2022; 14:nu14224716. [PMID: 36432401 PMCID: PMC9695891 DOI: 10.3390/nu14224716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/24/2022] [Accepted: 11/01/2022] [Indexed: 11/11/2022] Open
Abstract
Individuals with a history of previous cardiovascular events have an increased risk of mortality and morbidity, so adherence to a healthy dietary pattern is essential. We aimed to evaluate and compare dietary patterns between the control and the experimental group from the BALANCE Program. A total of 2360 individuals aged 45 years or older with previous cardiovascular disease were included. The individuals were randomized into two groups: intervention (dietary prescription with nutritional recommendations, nutritional education program based on playful strategies, suggestions of typical and accessible Brazilian foods and intensive monitoring) and control (conventional nutritional counseling). The dietary patterns were identified using factor analysis with the principal component extraction method, and the t-Student tests and ANOVA test were performed to evaluate the associated factors. Four dietary patterns were identified for both groups: "Traditional", "Snack", "Western", "Cardioprotective". There was an increase in the variances of the "Cardioprotective" pattern in both groups. Regarding the "Western" pattern, there was a significant reduction in the variances of the experimental group (10.63% vs. 8.14%). Both groups had improvements in eating habits, especially in the first year of follow-up. The greater increase in adherence to the traditional and cardioprotective pattern in the experimental group justifies the initiative of the BALANCE program.
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Affiliation(s)
- Amanda Gonçalves Lopes Coura
- Postgraduate Program in Nutrition Sciences, Federal University of Paraíba, João Pessoa 58059-900, Brazil
- Correspondence:
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Lee YQ, Colega M, Sugianto R, Lai JS, Godfrey KM, Tan KH, Shek LPC, Loy SL, Müller-Riemenschneider F, Padmapriya N, Chong YS, Eriksson JG, Chan JKY, Chan SY, Tai BC, Chong MFF. Tracking of dietary patterns between pregnancy and 6 years post-pregnancy in a multiethnic Asian cohort: the Growing Up in Singapore Towards healthy Outcomes (GUSTO) study. Eur J Nutr 2022; 61:985-1001. [PMID: 34686887 PMCID: PMC7612407 DOI: 10.1007/s00394-021-02703-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 10/06/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE Few studies have described adherence to dietary patterns over time in women of childbearing age. This study aims to describe, examine the stability and changes in dietary patterns between pregnancy and 6 years post-pregnancy and the sociodemographic and lifestyle factors influencing the adherence over time. METHODS During pregnancy and at 6 years post-pregnancy, 24-h recalls and food frequency questionnaires were collected, respectively, from 709 women. Data on sociodemographic and lifestyle factors were collected via questionnaires. Dietary patterns were identified using principal component analysis and stability assessed using Pearson's correlation coefficients (r) and Cohen's weighted kappa (κ). Associations with sociodemographic characteristics were assessed by multiple logistic regression. RESULTS The 'Fruits, Vegetables and Legumes' (FVL) and 'Seafood, Noodle, Soup' (SNS) patterns were identified at both time points, with low correlation for the dietary pattern z scores (r 0.2 and 0.3, respectively) and modest agreement in tertile assignment, suggesting poor stability. An 'unhealthy' pattern was only observed at 6 years post-pregnancy. Women who showed increased adherence to FVL pattern had higher educational attainment and exhibited healthy lifestyle behaviours. Women who had gestational diabetes during pregnancy were less likely to decrease adherence to FVL pattern over time. Women who adhered more closely to the 'unhealthy' pattern at 6 years post-pregnancy tended to be younger, of Malay ethnicity, had lower socioeconomic status, were less physically active and had additional pregnancies. CONCLUSIONS Dietary habits of women became less healthy during the transition from pregnancy to 6 years post-pregnancy. However, results should be interpreted with caution due to the different dietary assessment tools used at the two time points.
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Affiliation(s)
- Yu Qi Lee
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore.
| | - Marjorelee Colega
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
| | - Ray Sugianto
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore
| | - Jun Shi Lai
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
| | - Keith M Godfrey
- Medical Research Council Lifecourse Epidemiology Unit and National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service Foundation Trust, Southampton, SO16 6YD, UK
| | - Kok Hian Tan
- Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, 229899, Singapore
- Graduate Medical School, Duke-National University of Singapore, Singapore, 169857, Singapore
| | - Lynette Pei-Chi Shek
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, 119228, Singapore
| | - See Ling Loy
- Graduate Medical School, Duke-National University of Singapore, Singapore, 169857, Singapore
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, 229899, Singapore
| | - Falk Müller-Riemenschneider
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore
- Digital Health Center, Berlin Institute of Health, Charite University Medical Centre, Berlin, Germany
| | - Natarajan Padmapriya
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, 117597, Singapore
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, 117597, Singapore
| | - Johan Gunnar Eriksson
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, 117597, Singapore
- Folkhälsan Research Center, 00250, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, 00014, Helsinki, Finland
| | - Jerry Kok Yen Chan
- Graduate Medical School, Duke-National University of Singapore, Singapore, 169857, Singapore
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, 229899, Singapore
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, 117597, Singapore
| | - Bee Choo Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore
| | - Mary Foong-Fong Chong
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #09-01Q, Singapore, 117549, Singapore
- Singapore Institute for Clinical Sciences (SICS), Brenner Centre for Molecular Medicine, Agency for Science, Technology, and Research (A*STAR), Singapore, 117609, Singapore
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Ng A(P, Jessri M, L’Abbe MR. Using partial least squares to identify a dietary pattern associated with obesity in a nationally-representative sample of Canadian adults: Results from the Canadian Community Health Survey-Nutrition 2015. PLoS One 2021; 16:e0255415. [PMID: 34351952 PMCID: PMC8341606 DOI: 10.1371/journal.pone.0255415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 07/16/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Hybrid methods of dietary patterns analysis have emerged as a unique and informative way to study diet-disease relationships in nutritional epidemiology research. OBJECTIVE To identify an obesogenic dietary pattern using weighted partial least squares (wPLS) in nationally representative Canadian survey data, and to identify key foods and/or beverages associated with the defined dietary pattern. DESIGN Data from one 24-hr dietary recall data from the cross-sectional Canadian Community Health Survey-Nutrition (CCHS) 2015 (n = 12,049) were used. wPLS was used to identify an obesogenic dietary pattern from 40 standardized food and beverage categories using the variables energy density, fibre density, and total fat as outcomes. The association between the derived dietary pattern and likelihood of obesity was examined using weighted multivariate logistic regression. Key dietary components highly associated with the derived pattern were identified. RESULTS Compared to quartile one (i.e. those least adherent to an obesogenic dietary pattern), those in quartile four had 2.40-fold increased odds of being obese (OR = 2.40, 95% CI = 1.91, 3.02, P-trend< 0.0001) with a monotonically increasing trend. Using a factor loading significance cut-off of ≥|0.17|, three food/beverage categories loaded positively for the derived obesogenic dietary pattern: fast food (+0.32), carbonated drinks (including energy drinks, sports drinks and vitamin water) (+0.30), and salty snacks (+0.19). Seven categories loaded negatively (i.e. in the protective direction): whole fruits (-0.40), orange vegetables (-0.32), "other" vegetables (-0.32), whole grains (-0.26), dark green vegetables (-0.22), legumes and soy (-0.18) and pasta and rice (-0.17). CONCLUSION This is the first study to apply weighted partial least squares to CCHS 2015 data to derive a dietary pattern associated with obesity. The results from this study pinpoint key dietary components that are associated with obesity and consumed among a nationally representative sample of Canadians adults.
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Affiliation(s)
- Alena (Praneet) Ng
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mahsa Jessri
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- Health Analysis Division, Statistics Canada, Government of Canada, Ottawa, Ontario, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Mary R. L’Abbe
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
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Movassagh EZ, Baxter-Jones ADG, Kontulainen S, Whiting SJ, Vatanparast H. Tracking Dietary Patterns over 20 Years from Childhood through Adolescence into Young Adulthood: The Saskatchewan Pediatric Bone Mineral Accrual Study. Nutrients 2017; 9:nu9090990. [PMID: 28885565 PMCID: PMC5622750 DOI: 10.3390/nu9090990] [Citation(s) in RCA: 147] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 08/31/2017] [Accepted: 09/05/2017] [Indexed: 02/06/2023] Open
Abstract
Dietary patterns established during adolescence might play a role in adulthood disease. We examined the stability of dietary patterns (DPs) from childhood through adolescence and into young adulthood (from age 8 to 34 years). Data from 130 participants (53 females) of Saskatchewan Pediatric Bone Mineral Accrual Study (aged 8–15 years, at baseline) were included. Multiple 24-h recalls were collected annually from 1991 to 1997, 2002 to 2005, and 2010 and 2011. Using principal component analysis, “Vegetarian-style”, “Western-like”, “High-fat, high-protein”, “Mixed”, and “Snack” DPs were derived at baseline. Applied DP scores for all annual measurements were calculated using factor loading of baseline DPs and energy-adjusted food group intakes. We analyzed data using generalized estimating equations. The tracking coefficient represents correlation between baseline dietary pattern scores and all other follow-up dietary pattern scores. We found a moderate tracking for the “Vegetarian-style” (β = 0.44, p < 0.001) and “High-fat, high-protein” (β = 0.39, p < 0.001) DPs in females and “Vegetarian-style” DP (β = 0.30, p < 0.001) in males. The remaining DPs showed poor-to-fair tracking in both sexes. No tracking for “Western-like” DP in females was observed. Assessing overall change in DP scores from childhood to young adulthood showed an increasing trend in adherence to “Vegetarian-style” DP and decreasing trend in adherence to “High-fat, high-protein” DP by age in both sexes (p < 0.001), while “Western-like” and “Mixed” DP scores increased only in males (p < 0.001). These findings suggest that healthy dietary habits established during childhood and adolescence moderately continue into adulthood.
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Affiliation(s)
- Elham Z Movassagh
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 2Z4, Canada.
| | | | - Saija Kontulainen
- College of Kinesiology, University of Saskatchewan, Saskatoon, SK S7N5B2, Canada.
| | - Susan J Whiting
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 2Z4, Canada.
| | - Hassanali Vatanparast
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 2Z4, Canada.
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Prepregnancy Dietary Patterns Are Associated with Blood Lipid Level Changes During Pregnancy: A Prospective Cohort Study in Rio de Janeiro, Brazil. J Acad Nutr Diet 2017; 117:1066-1079.e1. [DOI: 10.1016/j.jand.2016.12.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Accepted: 12/06/2016] [Indexed: 01/13/2023]
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Jessri M, Wolfinger RD, Lou WY, L'Abbé MR. Identification of dietary patterns associated with obesity in a nationally representative survey of Canadian adults: application of a priori, hybrid, and simplified dietary pattern techniques. Am J Clin Nutr 2017; 105:669-684. [PMID: 28148504 DOI: 10.3945/ajcn.116.134684] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Accepted: 12/21/2016] [Indexed: 11/14/2022] Open
Abstract
Background: Analyzing the effects of dietary patterns is an important approach for examining the complex role of nutrition in the etiology of obesity and chronic diseases.Objectives: The objectives of this study were to characterize the dietary patterns of Canadians with the use of a priori, hybrid, and simplified dietary pattern techniques, and to compare the associations of these patterns with obesity risk in individuals with and without chronic diseases (unhealthy and healthy obesity).Design: Dietary recalls from 11,748 participants (≥18 y of age) in the cross-sectional, nationally representative Canadian Community Health Survey 2.2 were used. A priori dietary pattern was characterized with the use of the previously validated 2015 Dietary Guidelines for Americans Adherence Index (DGAI). Weighted partial least squares (hybrid method) was used to derive an energy-dense (ED), high-fat (HF), low-fiber density (LFD) dietary pattern with the use of 38 food groups. The associations of derived dietary patterns with disease outcomes were then tested with the use of multinomial logistic regression.Results: An ED, HF, and LFD dietary pattern had high positive loadings for fast foods, carbonated drinks, and refined grains, and high negative loadings for whole fruits and vegetables (≥|0.17|). Food groups with a high loading were summed to form a simplified dietary pattern score. Moving from the first (healthiest) to the fourth (least healthy) quartiles of the ED, HF, and LFD pattern and the simplified dietary pattern scores was associated with increasingly elevated ORs for unhealthy obesity, with individuals in quartile 4 having an OR of 2.57 (95% CI: 1.75, 3.76) and 2.73 (95% CI: 1.88, 3.98), respectively (P-trend < 0.0001). Individuals who adhered the most to the 2015 DGAI recommendations (quartile 4) had a 53% lower OR of unhealthy obesity (P-trend < 0.0001). The associations of dietary patterns with healthy obesity and unhealthy nonobesity were weaker, albeit significant.Conclusions: Consuming an ED, HF, and LFD dietary pattern and lack of adherence to the recommendations of the 2015 DGAI were associated with a significantly higher risk of obesity with and without accompanying chronic diseases.
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Affiliation(s)
- Mahsa Jessri
- Department of Nutritional Sciences, Faculty of Medicine, and
| | - Russell D Wolfinger
- Department of Statistics, North Carolina State University, Raleigh, NC; and.,Scientific Discovery and Genomics, SAS Institute, Cary, NC
| | - Wendy Y Lou
- Biostatistics Division, Canada Research Chair in Statistical Methods for Health Care, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Mary R L'Abbé
- Department of Nutritional Sciences, Faculty of Medicine, and
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Johns DJ, Lindroos AK, Jebb SA, Sjöström L, Carlsson LMS, Ambrosini GL. Dietary patterns, cardiometabolic risk factors, and the incidence of cardiovascular disease in severe obesity. Obesity (Silver Spring) 2015; 23:1063-70. [PMID: 25865622 PMCID: PMC6680188 DOI: 10.1002/oby.20920] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Accepted: 09/16/2014] [Indexed: 12/29/2022]
Abstract
OBJECTIVE The longitudinal associations between a dietary pattern (DP) and cardiometabolic risk factors and cardiovascular disease (CVD) incidence were investigated in a cohort of adults with severe obesity. METHODS The analysis included 2,037 individuals with severe obesity (>34 and >38 kg/m(2) for men and women, respectively) from the Swedish Obese Subjects study repeatedly followed up for 10 years. Reduced rank regression was used to identify a DP characterized by dietary energy density, saturated fat intake, and fiber density. Mixed models examined relationships between repeated measures of DP z-scores and cardiometabolic risk factors. Cox proportional hazards models assessed relationships between DP scores and CVD incidence. RESULTS An energy-dense, high-saturated-fat, and low-fiber DP was derived. A one-unit increase in the DP z-score between follow-ups was associated with an increase in weight [β (SE)] (1.71 ± 0.10 kg), waist circumference (1.49 ± 0.07 cm), BMI (0.60 ± 0.34 kg/m2), serum cholesterol (0.06 ± 0.01 mmol/l), and serum insulin (1.22 ± 0.17 mmol/l; all P < 0.0001), as well as in serum triglycerides (0.05 ± 0.02 mmol/l; P < 0.05), systolic blood pressure (1.05 ± 0.27 mmHg; P < 0.001), and diastolic blood pressure (0.55 ± 0.16 mmHg; P < 0.05). No significant association was observed between repeated measures of the DP z-scores and CVD incidence (HR = 0.96; 95% CI = 0.83-1.12). CONCLUSIONS An energy-dense, high-saturated-fat, and low-fiber DP was longitudinally associated with increases in cardiometabolic risk factors in severe obesity but not with CVD incidence.
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Affiliation(s)
- David J Johns
- Diet and Obesity Research, Medical Research Council, Human Nutrition Research, Elsie Widdowson Laboratory, Cambridge, UK
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