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NUTR 305: NUTRITIONAL EPIDEMIOLOGY Fall 2018
Course Syllabus Time and location of the course: Mondays 1:30-4:30PM Location: Dental School, Rachel’s Amphitheater Rm 1414 (Except October 9th lecture, to be held in Sackler 108) Instructor : Fang Fang Zhang, MD, PhD Associate Professor, Friedman School of Nutrition Science and Policy 150 Harrison Ave, Boston, MA 02111
Email : [email protected] | Phone : 617-636-3704 Teaching Assistant: Silvia Berciano, MS.
PhD Candidate, Biochemical and Molecular Nutrition Friedman School of Nutrition Science and Policy Email : [email protected]
Office Hours: Flexible. Email anytime to set up an appointment Tufts Graduate Credit: 1.0 (3 credit hours) Prerequisites for taking this course: Required prerequisites for this course are the following:
1) Introductory Human Nutrition (e.g., NUTR 201 or 202) 2) Introductory Epidemiology (e.g., NUTR 204 or MPH 201) 3) Biostatistics (e.g., NUTR 209/309 A&B or MPH 205)
Course Description: This course is designed for graduate students who are interested in conducting or better interpreting epidemiological studies relating diet and nutritional status to disease and health. There is an increasing awareness that various aspects of diet and nutrition may be important contributing factors in chronic disease. There are many important problems, however, in the implementation and interpretation of these studies. The purpose of this course is to examine methodologies used in nutritional epidemiological studies, and to review the current state of knowledge regarding diet and other nutritional indicators as etiologic factors in disease.
Course Objectives: At the conclusion of the course, students should be able to:
1. Describe the utility and limitations of different epidemiological study designs for research in nutritional epidemiology.
2. Describe the strengths and limitations of different methods of measuring diet and identify when specific dietary methods may be most appropriate.
3. Explain the statistical methods commonly used in nutritional epidemiology
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to analyze diet-disease associations. 4. Describe strategies that can be used to evaluate or adjust for other dietary
and lifestyle factors that may explain or influence relationships of diet and disease.
5. Describe the current state of epidemiological evidence for relationships of diet to the development of selected diseases.
6. Describe the issues in studying gene-nutrient interactions and discuss the influence of genetics on data collected in nutritional epidemiological studies.
7. Critically evaluate nutritional epidemiology research publications. Course texts and Materials (for the course as a whole): Required: Willett W. Nutritional Epidemiology (3rd edition). New York: Oxford
University Press, 2012. Recommended: Hu F. Obesity Epidemiology. New York: Oxford University Press, 2008
Margetts BM, Nelson M. Design Concepts in Nutritional Epidemiology. New York: Oxford University Press, 1997.
Readings To further understand the material, a selection of classic and contemporary research articles are assigned. The majorities are assigned as required reading and others are recommended readings to enhance learning. All additional readings are posted online on CANVAS. Please note that all students are responsible for doing the readings. All students are expected to complete the required readings prior to the class (e.g., the instructors may ask questions in class about required readings). Both required and recommended readings are assigned to help students prepare for each lecture. Participating in class discussions counts towards 5% of your final course grade. Workshops: There will be weekly workshops for students to practice the key concepts learned in each lecture. Each workshop will consist in two exercises. Students may discuss the exercises with their peers and instructors, but the answers submitted must be your own work. Weekly workshops account for 20% of the final course grade. Assignments: There will be two assignments for students to work on independently. Your grades on Assignments 1 and 2 each account for 10% of your final course grade. Practica: There will be three practica during the semester. These classes are intended to reinforce important concepts covered in the lectures and are designed to help students critically evaluate and interpret the findings from nutritional epidemiological studies. The three practica will be instructor-led and will require students to interpret SAS statistical output and published data. Final project: There will be one final project on a Brief Critical Review, to be outlined later in the semester, contributing 20% of your final course grade.
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Summary of Grade Contribution: 1) Assignment 1: Dietary Assessment Methods 10% 2) Assignment 2: Energy Adjustment & Measurement Error 10% 3) Midterm Exam (in-class, closed book exam) 35% 4) Weekly workshops 20% 5) Class Participation 5% 6) Final Project: Brief Critical Review 20% Class Policies and Expectations: Students will be expected to complete all required readings (textbook and assigned research articles) prior to each lecture. All students will be required to read the articles before class in order to be able to participate in the class discussion. Students will have only one opportunity to complete each assignment, and all assignments are due on the date/time specified. Late submissions will not be accepted. There will be no exceptions unless permission has been granted by the instructor in advance. Students will have only one opportunity to complete the midterm exam and final project. The exam and final project must be completed and successfully submitted within the specified time period. There will be no exceptions unless an extension is granted prior to the deadline by the instructor. If students anticipate missing a lecture, arriving late to lecture, or need to leave early, they must notify the instructor beforehand. It is preferable for students who arrive more than 10 minutes late to not disrupt the class or disrespect the lecturer and fellow students by entering the classroom. They can join the second session of the class after the break. Academic Conduct Academic integrity, including avoiding plagiarism, is critically important. Each student is responsible for being familiar with the standards and policies outlined in the Friedman School’s Policies and Procedures manual (http://nutrition.tufts.edu/student/documents). It is the responsibility of the student to be aware of, and comply with, these policies and standards. In accordance with Tufts University’s policy on academic misconduct, violations of standards of academic conduct will be sanctioned by penalties ranging from grade reduction or failure on an assignment; grade reduction or failure of a course; up to dismissal from the school, depending on the nature and context of any infraction (http://uss.tufts.edu/studentaffairs/judicialaffairs/Academic%20Integrity.pdf). Accommodations of Disabilities Tufts University is committed to providing equal access and support to all students through the provision of reasonable accommodations so that each student may access their curricula and achieve their personal and academic potential. If you have a disability that requires reasonable accommodations, please contact the Friedman School Assistant Dean of Student Affairs at 617-636-6719 to make arrangements for determination of appropriate
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accommodations. Please be aware that accommodations cannot be enacted retroactively, making timeliness a critical aspect for their provision.
Course Schedule
*** Class 1: Overview of Nutritional Epidemiology
Learning Objectives for class 1: Upon completion of this class, students will be able to: 1. Define and describe the objectives of nutritional epidemiology research 2. Discuss different types of study designs are used in nutritional epidemiological research 3. Understand the types of measures of nutritional exposure and outcome 4. List some of the key issues/challenges in nutritional epidemiology
Required Readings for class 1: Willett, Chapter 1: Overview of Nutritional Epidemiology Willett, Chapter 2: Foods and Nutrients Freudenheim JL. Study design and hypothesis testing: Issues in the evaluation of evidence from research in nutritional epidemiology. Am J Clin. Nutr. 1999;69:1315S–1321S.
***
Class 2: Dietary Assessment Methods: Food Frequency Questionnaires
Learning Objectives for class 2: Upon completion of this class, students will be able to: 1. Explain how FFQs are developed for collecting dietary intake data 2. Describe the basic assumption behind FFQs and the rationale behind the selection of foods included 3. Discuss how calibration and validation studies are designed, and the different factors that may influence the results of a validation study 4. Understand the strengths and limitations of different methods used to measure diet in epidemiological studies
Required Readings for class 2: Chapter 5: Food Frequency Methods Chapter 6: Reproducibility & Validity of Food Frequency Questionnaires Kristal AR, Peters U, Potter JD. Is it time to abandon the food frequency questionnaire? Cancer Epidemiol Biomarkers Prev. 2005 Dec;14(12):2826-8. Willett WC, Hu FB. Not the time to abandon the food frequency questionnaire: point. Cancer Epidemiol Biomarkers Prev. 2006 Oct;15(10):1757-8.
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Kristal AR, Potter JD. Not the time to abandon the food frequency questionnaire: counterpoint. Cancer Epidemiol Biomarkers Prev. 2006 Oct;15(10):1759-60. Recommended: Tucker KL, Bianchi LA, Maras J, Bermudez OI. Adaptation of a food frequency questionnaire to assess diets of Puerto Rican and non-Hispanic adults. Am J Epi. 1998;148:507–518. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study. Am J Epi. 2001;154:1089–1099.
***
Class 3: Dietary Assessment Methods: Records and Recalls
Learning Objectives for class 3: Upon completion of this class, students will be able to: 1. Understand the sources of variability in dietary assessments and how variations affect the validity and reliability of the method 2. Explain how 24-hour diet recalls and food records are conducted, as well as their respective advantages and disadvantages in assessing diet 3. Discuss recent developments and new methods for the administration of diet recalls and records
Required Readings for class 3: Chapter 3: Nature of Variation in Diet Chapter 4: 24 hour recall and Food Record Methods Stote KS, Radecki SV, Moshfegh AJ, Ingwersen LA, Baer DJ. The number of 24 h dietary recalls using the US Department of Agriculture’s automated multiple-pass method required to estimate nutrient intake in overweight and obese adults. Public Health Nutr, 2011;14:1736-1742. Kirkpatrick SI, Gilsing AM, Hobin E, et al. Lessons from studies to evaluate an online 24-hour recall for use with children and adults in Canada. Nutrients 2017, 9, 100; doi:10.3390/nu9020100 Recommended: Schoeller DA, et al. Letter to the Editor: Self-report-based estimates of energy intake offer an inadequate basis for scientific conclusions. AJCN, 2013;87:1413-1415.
***
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Class 4: Measurement Error: Effects and Remedies
Learning Objectives for class 4: Upon completion of this class, students will be able to: 1. Understand the different types of measurement error and the statistical approaches can be used to correct measures of association 2. Discuss the different statistical corrections can be used for measurement error in confounding variables 3. Be able to interpret studies applying measurement error correction techniques
Required Readings for class 4: Chapter 12: Correction for the effects of measurement error Freedman LS, Schatzkin A, Midthune D, Kipnis V. Dealing with Dietary Measurement Error in Nutritional Cohort Studies. J Natl Cancer Inst 2011;103:1–7. Kipnis V, Subar AF, Midthune D, Freedman LS, Ballard-Barbash R, Troiano RP, Bingham S, Schoeller DA, Schatzkin A, Carroll RJ. Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol. 2003;158(1):14–21; and discussion 22–26. Thiébaut AC, Freedman LS, Carroll RJ, Kipnis V. [Editorial] Is it necessary to correct for measurement error in nutritional epidemiology? Ann Intern Med. 2007 Jan 2;146(1):65–67.
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Class 5: Energy Adjustment
Learning Objectives for class 5: Upon completion of this class, students will be able to: 1. Understand why energy intake is measured and when energy adjustment is necessary 2. Explain the components of total energy expenditure 3. Compare and contrast the different energy adjustment methods 4. Understand the factors that must be considered when energy adjusting nutrient data 5. Interpret the meaning of regression coefficients in statistical models
Required Readings for class 5: Chapter 11: Implications of Total Energy For Epidemiologic Analyses
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Hu FB, Stampfer MJ, Rimm E, Ascherio A, Rosner BA, Spiegelman D, Willett WC. Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol. 1999;149:531–540. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J ClinNutr 1997, 65(4 Suppl): 1220S-1228S Mackerras D. Energy adjustment: the concepts underlying the debate. J ClinEpidemiol. 1996;49:957–962.
***
Class 6: Practicum 1: Energy Adjustment
*** Class 7: Dietary Patterns: Empirical
Learning Objectives for class 7: Upon completion of this class, students will be able to: 1. Explain why empirically derived dietary patterns are used 2. Differentiate between factor analysis and cluster analysis 3. Discuss the validity of these pattern analysis techniques 4. List the advantages and disadvantages of empirically derived patterns 5. Identify the limitations of dietary pattern approaches
Required Readings for class 7:
Smith AD, Emmett PM, Newby PK, Northstone K. A comparison of dietary patterns derived by cluster and principal components analysis in a UK cohort of children. Eur J ClinNutr 2011 May 25.
Reedy J, Wirfalt E, Flood A, Mitrou PN, Krebs-Smith SM, Kipnis V, et al. Comparing 3 dietary pattern methods--cluster analysis, factor analysis, and index analysis--With colorectal cancer risk: The NIH-AARP Diet and Health Study. Am J Epidemiol. 2010;171(4):479-87.
Moeller SM, Reedy J, Millen AE, Dixon LB, Newby PK, Tucker KL, Krebs-Smith SM, Guenther PM. Dietary patterns: challenges and opportunities in dietary patterns research an Experimental Biology workshop, April 1, 2006. J Am Diet Assoc. 2007 Jul;107(7):1233–1239.
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Brunner EJ, Mosdol AM, Witte DR, et al. Dietary patterns and 15-y risk of major coronary events, diabetes, and mortality. Am J ClinNutr. 2008;87:1414–1421.
*** Class 8: Practicum 2: Diet Pattern Analysis
***
Class 9: Methodological considerations in study design
Learning Objectives for class 9: Upon completion of this class, students will be able to:
1. Understand the difference between categorized versus continuous presentation of independent variables
2. Explain the issues of missing data and outliers 3. Discuss the approaches used for handling repeated dietary assessments
and related hypotheses 4. Explain the need for subgroup analyses and interactions 5. Understand the importance of selection of confounders
Required Readings for class 9: Chapter 13: Issues in Analysis and Presentation of Dietary Data Satija A, Yu E, Willett WC, Hu FB. Understanding nutritional epidemiology and its role in policy. Adv Nutr. 2015;6:5-18. Bernstein AM, Rosner BA, Willett WC. Cereal fiber and coronary heart disease: a comparison of modeling approaches for repeated dietary measurements, intermediate outcomes, and long follow-up. Eur J Epidemiol. 2011, 26(11): 877-86 Mozaffarian et al. Changes in diet and lifestyle and long-term weight gain in women and men. NEJM, 2011. 364(25): 2392-404.
***
Class 10: Nutrient-Gene Interactions and Epigenetics
Learning Objectives for class 10: Upon completion of this class, students will be able to:
1. Define nutrient-gene interaction
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2. Understand the role of nutrient-gene interactions in human disease 3. Know how to evaluate nutrient-gene interactions in epidemiologic
studies 4. Understand the concept of Mendelian Randomization 5. Discuss the role of epigenetic mechanisms in the relationship between
diet and disease
Required Readings for class 10:
Hunter DJ. Gene-environment interactions in human diseases. Nature reviews. Genetics. Apr 2005;6(4):287-298. Ulrich CM, Kampman E, Bigler J, et al. Colorectal adenomas and the C677T MTHFR polymorphism: evidence for gene-environment interaction? Cancer Epidemiol Biomarkers Prev. Aug 1999;8(8):659-668. Recommended:
Heianza Y1, Qi L. Gene-Diet Interaction and Precision Nutrition in Obesity. Int J Mol Sci. 2017 Apr 7;18(4).
Friso S1, Choi SW. Gene-nutrient interactions and DNA methylation. J Nutr. 2002 Aug;132(8 Suppl):2382S-2387S.
Young AI, Wauthier F, Donnelly P. Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index. Nat Commun. 2016 Sep 6;7:12724.
Lichtenstein P, Holm NV, Verkasalo PK, et al. Environmental and heritable factors in the causation of cancer--analyses of cohorts of twins from Sweden, Denmark, and Finland. The New England journal of medicine. Jul 13 2000;343(2):78-85.
Graff M, Scott RA, Justice AE, et al. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults. PLoS Genet. 2017 Apr 27;13(4): e1006528.
Zheng J, Baird D, Borges MC, et al. Recent Developments in Mendelian Randomization Studies. Curr Epidemiol Rep. 2017;4(4):330-345.
***
Class 11: Nutrition Biomarkers
Learning Objectives for class 11: Upon completion of this class, students will be able to:
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1. Explain the advantages of using biomarkers in nutritional epidemiology 2. Differentiate between a direct and surrogate biomarker of exposure 3. Define validity, relative validity, calibration & reproducibility 4. Explain the principle behind the trial comparison methods of evaluating a FFQ 6. Identify the most important considerations relating to the use of nutritional biomarkers 7. List the most common surrogate biomarkers used in epidemiological studies 8. Discuss the underlying assumptions on the use of biomarkers in epidemiological studies 9. Understand how metabolomics approaches are used to identify novel biomarkers of intake
Required Readings for class 11: Chapter 8: Biochemical Indicators of dietary intake Marklund, M., Leander, K., Vikstrom, M., Laguzzi, F., Gigagnte, B. et al. Polyunsaturated fat intake estimated by circulating biomarkers and risk of cardiovascular disease and all-cause mortality in a population-based cohort of 60-year-old men and women. Circulation. 2015;132:586-594.
O’Sullivan, Aifric., Gibney, MJ., Brennan, L. Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies. Am J Clin Nutr. 2011;93:314-21.
Potischman N. Biologic and methodologic issues for nutritional biomarkers. J Nutr. 2003 Mar;133Suppl 3:875S-880S.
***
Class 12: Controversies in Epidemiology: Observational studies vs. RCT
Learning Objectives for class 12: Upon completion of this class, students will be able to:
1. Explain the inherent differences between intervention and observational studies
2. Differentiate the paradigms of treatment (secondary prevention) and primary prevention studies
3. Discuss the optimal way to model nutritional exposures in a primary prevention study
4. Explain the main reasons why nutritional intervention studies do not always replicate findings from epidemiologic studies
Required Readings for class 12:
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Frieden TR. Evidence for Health Decision Making - Beyond Randomized, Controlled Trials. N Engl J Med. 2017 Aug 3;377(5):465-475. doi: 10.1056/NEJMra1614394. Recommended: Anglemyer A, Horvath HT, Bero L. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database Syst Rev. 2014 Apr 29; Review. Morris MC, Tangney CC. A potential design flaw of randomized trials of vitamin supplements. JAMA. 2011;305(13):1348-9. Mozaffarian D, Aro A, Willett WC. Health effects of trans-fatty acids: experimental and observational evidence. European Journal of Clinical Nutrition. 2009 63: S5-S21
***
Class 13: Advances in Nutritional Genomics and Multi-omic integration
Learning Objectives for class 13:
1. Understand how Nutrient-Gene Interactions are identified 2. Learn about the most recent advances in Nutritional Genomics 3. Know how to use Gene-Environment interaction databases and other
publicly available tools 4. Understand how multi-omic integration studies can provide
mechanistic insights into the nature of Nutrient-Gene Interactions
Required Readings for class 13:
TBD
Recommended:
Parnell LD, Blokker BA, Dashti HS, Nesbeth PD, Cooper BE, Ma Y, Lee YC, Hou R, Lai CQ, Richardson K, Ordovás JM. CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits. BioData Min. 2014 Oct 26;7:21. doi: 10.1186/1756-0381-7-21.
Cornelis MC, Hu FB. Systems Epidemiology: A New Direction in Nutrition and Metabolic Disease Research. Curr Nutr Rep. 2013 Dec;2(4).
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Lai CQ, Smith CE, Parnell LD, Lee YC, Corella D, Hopkins P, Hidalgo BA, Aslibekyan S, Province MA, Absher D, Arnett DK, Tucker KL, Ordovas JM. Epigenomics and metabolomics reveal the mechanism of the APOA2-saturated fat intake interaction affecting obesity. Am J Clin Nutr. 2018 Jul 1;108(1):188-200.
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Class 14: Energy Intake Validation and the Microbiota
Learning Objectives for class 14: Upon completion of this class, students will be able to: 1. Explain why validity is an issue when measuring energy intake 2. List the different factors that affect the validity of reported energy intake 3. Explain the methods used to assess validity of energy intake assessed 4. Discuss the effects of poor validity of energy intake in epidemiological studies 5. Understand the role of the gut microbiota in energy metabolism and health, and the factors that modulate microbiota composition.
Required Readings for class 14: Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard-Barbash R, Sunshine J, Schatzkin A. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol. 2003;158(1):1–13. Livingstone MBE and Black AE. Markers of the Validity of Reported Energy Intake. J Nutr. 2003, 133: 895S-920S. Recommended: Schoeller DA, Thomas D, Archer E, Heymsfield SB, Blair SN, Goran MI, Hill JO, Atkinson RL, Corkey BE, Foreyt J, Dhurandhar NV, Kral JG, Hall KD, Hansen BC, Heitmann BL, Ravussin E, Allison DB. Self-report-based estimates of energy intake offer an inadequate basis for scientific conclusions. Am J Clin Nutr. 2013 Jun;97(6):1413-5. Black AE. Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J ObesRelatMetabDisord. 2000 Sep;24(9):1119–1130.
Mendez, M.A., Popkin, B.M., Buckland, G., Schroder, H., Amiano, P. et al. Alternative methods for accounting for underreporting and overreporting when measuring dietary intake-obesity relations. Am J Epid. 2010.
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***
Class 15: Dietary Patterns: Theoretical
Learning Objectives for class 15: Upon completion of this class, students will be able to: 1. Understand why diet quality indices are used to assess dietary patterns 2. List common diet quality indices used in nutritional epidemiology 3. Discuss the most important considerations in creating a diet index score 4. Discuss the advantages and disadvantages of theoretical derived patterns 5. Interpret the results of studies using theoretically derived dietary patterns
Required Readings for class 15:
Chiuve SE, Fung TT, Rimm EB, Hu FB, McCullough ML, Wang M, Stampfer MJ, Willett WC. Alternative dietary indices both strongly predict risk of chronic disease. J Nutr 2012. 142(6): 1009-18.
George SM, Ballard-Barbash R, Manson JE, Reedy J, Shikany JM, Subar AF, et al. Comparing indices of diet quality with chronic disease mortality risk in postmenopausal women in the Women's Health Initiative Observational Study: evidence to inform national dietary guidance. Am J Epidemiol. 2014;180(6):616-25.
Harmon BE, Boushey CJ, Shvetsov YB, Ettienne R, Reedy J, Wilkens LR, et al. Associations of key diet-quality indexes with mortality in the Multiethnic Cohort: the Dietary Patterns Methods Project. The American journal of clinical nutrition. 2015;101(3):587-97.
Kant AK, Schatzkin A, Graubard BI, Schairer C. A prospective study of diet quality and mortality in women. JAMA : the journal of the American Medical Association. 2000;283(16):2109-15.
Bhupathiraju SN, Lichtenstein AH, Dawson-Hughes B, Tucker K. Adherence Index Based on the AHA 2006 Diet and Lifestyle Recommendations Is Associated with Select Cardiovascular Disease Risk Factors in Older Puerto Ricans. J Nutr. 2011 Mar;141(3):460-9.
Rehm CD, Penalvo JL, Afshin A, Mozaffarian D. Dietary Intake Among US Adults, 1999-2012. JAMA. 2016;315(23):2542-2553.
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Class 16: Practicum 3: Diet Quality Indices
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***
November 5, 2018: Mid-term Exam
*** Class 17: Nutrition and Musculoskeletal Health
Learning Objectives for class 17: Upon completion of this class, students will be able to:
1. Understand the epidemiology and public health burden of osteoporosis and fracture
2. Discuss the role of calcium and vitamin D in age-related bone loss and fracture
3. Explain the controversy surrounding evidence that calcium and vitamin D have a detrimental effect on cardiovascular health
Required Readings for class 17: Bolland MJ, Leung W, Tai V, Bastin S, Gamble GD, Grey A, Reid IR. Calcium intake and risk of fracture: systematic review. The British Medical Journal. 2015 Sept.; 351:h4580. Weaver CM, Alexander DD, Boushey CJ, Dawson-Hughes B, Lappe JM, LeBoff MS, Liu S, Looker AC, Wallace TC, Wang DD. Calcium plus vitamin D supplementation and risk of fractures: an updated meta-analysis from the National Osteoporosis Foundation. Osteoporosis International. 2016; 27: 367-376. Chung M, Tang AM, Fu Z, Wang DD, Newberry SJ. Calcium Intake and Cardiovascular Disease Risk: An Updated Systematic Review and Meta-analysis. Ann Intern Med. 2016 Dec 20;165(12):856-866. Recommended: Lewis JR et al. The Effects of Calcium Supplementation on Verified Coronary Heart Disease Hospitalization and Death in Postmenopausal Women: A Collaborative Meta‐Analysis of Randomized Controlled Trials. Journal of Bone and Mineral Research. 2015 January; 30(1): 165-75. Bolland MJ et al. Effect of Calcium Supplements on Risk of Myocardial Infarction and Cardiovascular Events: Meta-analysis. The British Medical Journal. 2010 July; 341:c3691. Ensrud KE. Epidemiology of Fracture Risk with Advancing Age. Journal of Gerontology: Medical Sciences. 2013 October; 68(10):1236-42.
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Cauley JA. Public Health Impact of Osteoporosis. Journal of Gerontology: Medical Sciences. 2013 October; 68(10):1243-51
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Class 18: Nutrition and Infectious Disease
Learning Objectives for class 18: Upon completion of this class, students will be able to:
1. Recognize the importance of nutritional status in relation to immune function in people living with HIV (PLHIV)
2. Identify methods of nutritional assessment to address issues related to nutritional status, dietary quality, and food security in PLHIV.
3. Develop awareness of the complex relationships between nutrition and metabolic status, food insecurity, and adherence to medications among PLHIV
Required Readings for class 18: Sarah J. Fielden, Aranka Anema, Pamela Fergusson, Katherine Muldoon, Nils Grede, Saskia de Pee. Measuring Food and Nutrition Security: Tools and Considerations for Use Among People Living with HIV. AIDS Behav. Published Online: 03 Dec 2013 Saskia de Pee and Richard D. Semba. Role of nutrition in HIV infection: Review of evidence for more effective programming in resource-limited settings. Food and Nutrition bulletin. 2010 Vol 31, No. 4 Nutrition Requirements for People Living with HIV/AIDSReport of a technical consultation, 13-15 May 2003, Geneva, Switzerland
***
Class 19: Epidemiology of Obesity
Learning Objectives for class 19: Upon completion of this class, students will be able to:
1. Explain how obesity is assessed in children and adults 2. List different sources of misclassification of obesity in each group 3. Understand how the prevalence of obesity varies by age, race/ethnicity,
sex, SES, place and time 4. Propose a useful way to characterize obesity risk factors
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5. Discuss obesity as an exposure with respect to psychosocial and physical health outcomes
Required Readings for class 19:
Chapter 20 of Frank Hu's Book Obesity Epidemiology Predictors and consequences of childhood obesity
Must A, Anderson SE. Body mass index in children and adolescents: considerations for population-based applications. Int J Obes (Lond) 2006;30:590–594.
Freedman DS, Butte NF, Taveras EM, et al. BMI z-scores are a poor indicator of adiposity among 2- to 19-year-olds with very high BMIs, NHANES 1900-2000 to 2013-2014. Obesity 2017;25:739–746
Anderson SE et al. Bedtime in Preschool-Aged Children and Risk for Adolescent Obesity. The Journal of Pediatrics, September 2016; 176:17-22
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Class 20: The role of meta-analysis in Nutritional Epidemiology
Learning Objectives for class 20: Upon completion of this class, students will be able to:
1. Understand the utility of meta-analysis in nutrition epidemiology, including strengths and limitations.
2. Evaluate, summarize and interpret findings from meta-analyses while considering prior and new evidence.
3. Discuss how findings from meta-analysis can be used to shape dietary recommendations and policy and be communicated to the public.
Required Readings for class 20: Swart KM, Lips P, Brouwer IA, Jorde R, Heymans MW, Grimnes G, Grübler MR, Gaksch M, Tomaschitz A, Pilz S, Eiriksdottir G, Gudnason V, Wamberg L, Rejnmark L, Sempos CT, Durazo-Arvizu RA, Dowling KG, Hull G, Škrabáková Z, Kiely M, Cashman KD, van Schoor NM. Effects of vitamin D supplementation on markers for cardiovascular disease and type 2 diabetes: an individual participant data meta-analysis of randomized controlled trials. Am J Clin Nutr. 2018 Jun 1;107(6):1043-1053. Egger M, Schneider M, Davey Smith G. Spurious precision? Meta-analysis of observational studies. BMJ. 1998 Jan 10;316(7125):140-4.
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Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000 Apr 19;283(15):2008-12 Recommended: Merino J, Dashti HS, Li SX, Sarnowski C, Justice AE, Graff M, Papoutsakis C, Smith CE, Dedoussis GV, Lemaitre RN, Wojczynski MK, Männistö S, Ngwa JS, Kho M, Ahluwalia TS, Pervjakova N, Houston DK, Bouchard C, Huang T, Orho-Melander M, Frazier-Wood AC, Mook-Kanamori DO, Pérusse L, Pennell CE, de Vries PS, Voortman T, Li O, Kanoni S, Rose LM, Lehtimäki T, Zhao JH, Feitosa MF, Luan J, McKeown NM, Smith JA, Hansen T, Eklund N, Nalls MA, Rankinen T, Huang J, Hernandez DG, Schulz CA, Manichaikul A, Li-Gao R, Vohl MC, Wang CA, van Rooij FJA, Shin J, Kalafati IP, Day F, Ridker PM, Kähönen M, Siscovick DS, Langenberg C, Zhao W, Astrup A, Knekt P, Garcia M, Rao DC, Qi Q, Ferrucci L, Ericson U, Blangero J, Hofman A, Pausova Z, Mikkilä V, Wareham NJ, Kardia SLR, Pedersen O, Jula A, Curran JE, Zillikens MC, Viikari JS, Forouhi NG, Ordovás JM, Lieske JC, Rissanen H, Uitterlinden AG, Raitakari OT, Kiefte-de Jong JC, Dupuis J, Rotter JI, North KE, Scott RA, Province MA, Perola M, Cupples LA, Turner ST, Sørensen TIA, Salomaa V, Liu Y, Sung YJ, Qi L, Bandinelli S, Rich SS, de Mutsert R, Tremblay A, Oddy WH, Franco OH, Paus T, Florez JC, Deloukas P, Lyytikäinen LP, Chasman DI, Chu AY, Tanaka T. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium. Mol Psychiatry. 2018 Jul 9. doi: 10.1038/s41380-018-0079-4. Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013 Jan 2;309(1):71-82.
O'Connor LE, Kim JE, Campbell WW. Total red meat intake of ≥0.5 servings/d does not negatively influence cardiovascular disease risk factors: a systemically searched meta-analysis of randomized controlled trials. Am J Clin Nutr. 2017 Jan;105(1):57-69. doi: 10.3945/ajcn.116.142521. Epub 2016 Nov 23. Review. PubMed PMID: 27881394;
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Class 21: Nutrition and Global Burden of Disease
Learning Objectives for class 21: Upon completion of this class, students will be able to:
1. Explain the background and rationale for the study of the Global Burden of Disease
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2. Understand the data sources and methodology used in modeling dietary burdens of disease
3. Discuss the main findings on the impacts of diet on disease burdens. Required Readings for class 21: Singh GM, Micha R, Khatibzadeh S, Lim S, Ezzati M, Mozaffarian D, Global Burden of Diseases Nutrition and Chronic Diseases Expert Group. Estimated global, regional, and national disease burdens related to sugar-sweetened beverage consumption in 2010. (2015) Circulation, 132(8): 639-66. Afshin A, Micha R, Khatibzadeh S, Fahimi S, Shi P, Powles J, et al.; 2010 Global Burden of Diseases, Injuries, and Risk Factors Study: NUTRItrition and ChrOnic Diseases Expert Group (NUTRICODE), and Metabolic Risk Factors of ChrOnic Diseases Collaborating Group. The impact of dietary habits and metabolic risk factors on cardiovascular and diabetes mortality in countries of the Middle East and North Africa in 2010: a comparative risk assessment analysis. BMJ Open. 2015 May 20;5(5):e006385.
*** Class 22: Diet, Lifestyle, and Diabetes
Learning Objectives for class 22: Upon completion of this class, students will be able to:
1. Discuss the population diabetes trends in US adults 2. Explain the metabolic consequences of diabetes 3. Understand the relationship between diet and diabetes 4. List the most important methodological issues in analyzing the
relationship between diet and diabetes
Required Readings for class 22:
Hu FB, Manson JE, Stampfer MJ, Colditz G, Liu S, Solomon CG, Willett WC. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001 Sep 13;345(11):790–797.
Hu FB. Globalization of diabetes: the role of diet, lifestyle, and genes. Diabetes Care. 2011 Jun;34(6):1249-57. doi: 10.2337/dc11-0442.
Chan JC, Malik V, Jia W, Kadowaki T, Yajnik CS, Yoon KH, Hu FB. Diabetes in Asia: epidemiology, risk factors, and pathophysiology. JAMA. 2009 May 27;301(20):2129-40. doi: 10.1001/jama.2009.726. Review.
Recommended:
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Curbing the Diabetes Pandemic: The Need for Global Policy Solutions. Hu FB, Satija A, Manson JE. JAMA. 2015 Jun 16;313(23):2319-20. doi: 10.1001/jama.2015.5287 Understanding nutritional epidemiology and its role in policy. Satija A, Yu E, Willett WC, Hu FB. Adv Nutr. 2015 Jan 15;6(1):5-18. doi: 10.3945/an.114.007492. Print 2015 Jan. Hu FB, Willett WC, Li T, Stampfer MJ, Colditz GA, Manson JE. Adiposity as compared with physical activity in predicting mortality among women. N Engl J Med 2004;351(26):2694–2703.
deKoning L, Malik VS, Rimm EB, Willett WC, Hu FB. Sugar-sweetened and artificially sweetened beverage consumption and risk of type 2 diabetes in men. Am J ClinNutr. 2011 Jun;93(6):1321–1327. Epub 2011 Mar 23.
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Class 23: Nutrition Interventions and Health Disparities
Learning Objectives for class 23: Upon completion of this class, students will be able to:
1. Understand the epidemiology of health disparities and the importance of disparities research
2. Learn about different analysis and visualization tools used to monitor and report health disparities
3. Describe key considerations of planning a dietary intervention. 4. Discuss the challenges and rewarding aspects of community-based
intervention studies
Required Readings for class 23: TBC
***
Class 24: Nutrition and Cancer
Learning Objectives for class 24: Upon completion of this class, students will be able to
1. Summarize the current state of the science for diet and human cancer. 2. Discuss major methodological challenges (specific to the study of
cancer) that have slowed down our understanding of the relation of diet to cancer.
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3. Understand important questions that remain unanswered in the relation of diet to cancer.
Required Readings for class 24: Willett, W. Nutrition and Cancer: the search continues. Nutr Cancer. 2008;60(5):557-9. Chan DS, Lau R, Aune D, Vieira R, Greenwood DC, Kampman E, Norat T. Red and processed meat and colorectal cancer incidence: meta-analysis of prospective studies. PLoS One. 2011;6(6):e20456. Prentice RL, Caan B, Chlebowski RT, Patterson R, Kuller LH, Ockene JK, et al. Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. Prentice RL1
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This schedule and assigned readings are subject to modifications at the discretion of the instructor.
Session #
Monday Date
Location Time Lecture Topic Lecturer Assignments
1 Sept 10 RA 1414 1:30-3:00pm Nutritional Epidemiology: An overview Fang Fang Zhang Assignment 1 assigned
2 RA 1414 3:00-4:30pm Dietary Assessment Methods I: FFQs Fang Fang Zhang
3 Sept 17 RA 1414 1:30-3:00pm Dietary Assessment Methods II: Records and Recalls Cheryl Gilhooly FFQ and 24HR due
4 RA 1414 3:00-4:30pm Measurement Error: Effects and Remedies Fang Fang Zhang
5 Sept 24 RA 1414 1:30-3:00pm Energy Adjustment Fang Fang Zhang FFQ/24HR data returned
6 TBD 3:00-4:30pm Practicum 1: Energy adjustment Fang Fang Zhang
7 Oct 1 RA 1414 1:30-3:00pm Dietary Patterns: Empirical approaches Fang Fang Zhang Assignment 1 due
8 TBD 3:00-4:30pm Practicum 2: Diet Pattern Analysis Fang Fang Zhang Assignment 2 assigned
9 Oct 9 S 108 1:30-3:00pm Methodological considerations in Study Design Fang Fang Zhang
10 S 108 3:00-4:30pm Gene-Nutrient Interactions and Epigenetics Jiantao Ma
11 Oct 15 RA 1414 1:30-3:00pm Nutrition Biomarkers and Metabolomics Shilpa Bhupathiraju Assignment 2 due
12 RA 1414 3:00-4:30pm Controversies in Epidemiology: Observational studies vs. RCTs Dariush Mozaffarian
13 Oct 22 RA 1414 1:30-3:00pm Advances in Nutritional Genomics and Multi-omic Integration Laurence Parnell
14 RA 1414 3:00-4:30pm Energy Intake Validation and Microbiota Carlota Dao 15 Oct 29 RA 1414 1:30-3:00pm Dietary Patterns: Theoretical approaches Fang Fang Zhang
16 TBD 3:00-4:30pm Practicum 3: Diet Quality Indices Fang Fang Zhang
Nov 5 RA 1414 1:30-4:30pm Midterm Examination Final Critique assigned
Nov 12 RA 1414 1:30-4:30pm No class (Veteran’s day)
17 Nov 19 RA 1414 1:30-3:00pm Nutrition and Musculoskeletal Health Kyla Shea
18 RA 1414 3:00-4:30pm Nutrition and Infectious Disease Alice Tang 19 Nov 26 RA 1414 1:30-3:00pm Epidemiology of Obesity Erin Hennessy
20 RA 1414 3:00-4:30pm The role of meta-analysis in Nutritional Epidemiology Hassan Dashti 21 Dec 3 RA 1414 1:30-3:00pm Nutrition and the Global Burden of Disease Gitanjali Singh
22 RA 1414 3:00-4:30pm Diet, Lifestyle and Diabetes Frank Hu
23 Dec 10 RA 1414 1:30-3:00pm Nutrition Interventions and Health Disparities Sabrina Noel
24 RA 1414 3:00-4:30pm Nutrition and Cancer Fang Fang Zhang Dec 17 1:30-4:30pm Final Critique Due
