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Published in: BMC Public Health 1/2012

Open Access 01-12-2012 | Study protocol

Effect of communicating genetic and phenotypic risk for type 2 diabetes in combination with lifestyle advice on objectively measured physical activity: protocol of a randomised controlled trial

Authors: Job G Godino, Esther MF van Sluijs, Theresa M Marteau, Stephen Sutton, Stephen J Sharp, Simon J Griffin

Published in: BMC Public Health | Issue 1/2012

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Abstract

Background

Type 2 diabetes (T2D) is associated with increased risk of morbidity and premature mortality. Among those at high risk, incidence can be halved through healthy changes in behaviour. Information about genetic and phenotypic risk of T2D is now widely available. Whether such information motivates behaviour change is unknown. We aim to assess the effects of communicating genetic and phenotypic risk of T2D on risk-reducing health behaviours, anxiety, and other cognitive and emotional theory-based antecedents of behaviour change.

Methods

In a parallel group, open randomised controlled trial, approximately 580 adults born between 1950 and 1975 will be recruited from the on-going population-based, observational Fenland Study (Cambridgeshire, UK). Eligible participants will have undergone clinical, anthropometric, and psychosocial measurements, been genotyped for 23 single-nucleotide polymorphisms associated with T2D, and worn a combined heart rate monitor and accelerometer (Actiheart®) continuously for six days and nights to assess physical activity. Participants are randomised to receive either standard lifestyle advice alone (control group), or in combination with a genetic or a phenotypic risk estimate for T2D (intervention groups). The primary outcome is objectively measured physical activity. Secondary outcomes include self-reported diet, self-reported weight, intention to be physically active and to engage in a healthy diet, anxiety, diabetes-related worry, self-rated health, and other cognitive and emotional outcomes. Follow-up occurs eight weeks post-intervention. Values at follow-up, adjusted for baseline, will be compared between randomised groups.

Discussion

This study will provide much needed evidence on the effects of providing information about the genetic and phenotypic risk of T2D. Importantly, it will be among the first to examine the impact of genetic risk information using a randomised controlled trial design, a population-based sample, and an objectively measured behavioural outcome. Results of this trial, along with recent evidence syntheses of similar studies, should inform policy concerning the availability and use of genetic risk information.

Trial registration

Current Controlled Trials ISRCTN09650496
Appendix
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Literature
1.
Petit WA, Adamec CA: The encyclopedia of diabetes. 2011, New York: Facts On File
2.
Ahmad LA, Crandall JP: Type 2 diabetes prevention: a review. Clin Diabetes. 2010, 28: 53-59. 10.2337/diaclin.28.2.53.CrossRef
3.
Qi L, Hu FB, Hu G: Genes, environment, and interactions in prevention of type 2 diabetes: a focus on physical activity and lifestyle changes. Curr Mol Med. 2008, 8: 519-532. 10.2174/156652408785747915.CrossRefPubMed
4.
5.
Bonnefond A, Froguel P, Vaxillaire M: The emerging genetics of type 2 diabetes. Trends Mol Med. 2010, 16: 407-416. 10.1016/j.molmed.2010.06.004.CrossRefPubMed
6.
Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, Wheeler E, Glazer NL, Bouatia-Naji N, Gloyn AL, et al: New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010, 42: 105-116. 10.1038/ng.520.CrossRefPubMedPubMedCentral
7.
Lyssenko V, Nagorny CLF, Erdos MR, Wierup N, Jonsson A, Spegel P, Bugliani M, Saxena R, Fex M, Pulizzi N, et al: Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet. 2009, 41: 82-88. 10.1038/ng.288.CrossRefPubMed
8.
Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PIW, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, et al: Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007, 316: 1331-1336.CrossRefPubMed
9.
Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benediktsson R, Jonsdottir T, Walters GB, Styrkarsdottir U, Gretarsdottir S, Emilsson V, Ghosh S, et al: A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007, 39: 770-775. 10.1038/ng2043.CrossRefPubMed
10.
Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, et al: Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010, 42: 579-589. 10.1038/ng.609.CrossRefPubMedPubMedCentral
11.
Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PIW, Abecasis GR, Almgren P, Andersen G, et al: Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008, 40: 638-645. 10.1038/ng.120.CrossRefPubMedPubMedCentral
12.
Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, Timpson NJ, Perry JRB, Rayner NW, Freathy RM, et al: Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007, 316: 1336-1341. 10.1126/science.1142364.CrossRefPubMedPubMedCentral
13.
Collins FS, Green ED, Guttmacher AE, Guyer MS: A vision for the future of genomics research: A blueprint for the genomic era. Nature. 2003, 422: 835-847. 10.1038/nature01626.CrossRefPubMed
14.
Grant RW, Moore AF, Florez JC: Genetic architecture of type 2 diabetes: Recent progress and clinical implications. Diabetes Care. 2009, 32: 1107-1114. 10.2337/dc08-2171.CrossRefPubMedPubMedCentral
15.
Majithia AR, Florez JC: Clinical translation of genetic predictors for type 2 diabetes. Curr Opin Endocrinol Diabetes and Obesity. 2009, 16: 100-106. 10.1097/MED.0b013e3283292354.CrossRef
16.
Stolerman ES, Florez JC: Genomics of type 2 diabetes mellitus: implications for the clinician. Nat Rev Endocrinol. 2009, 5: 429-436. 10.1038/nrendo.2009.129.CrossRefPubMed
17.
Buijsse B, Simmons RK, Griffin SJ, Schulze MB: Risk assessment tools for identifying individuals at risk of developing type 2 diabetes. Epidemiologic Rev. 2011, 33: 46-62. 10.1093/epirev/mxq019.CrossRef
18.
Noble D, Mathur R, Dent T, Meads C, Greenhalgh T: Risk models and scores for type 2 diabetes: systematic review. Br Med J. 2011, 343: d7163-10.1136/bmj.d7163.CrossRef
19.
Talmud PJ, Hingorani AD, Cooper JA, Marmot MG, Brunner EJ, Kumari M, Kivimäki M, Humphries SE: Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. Br Med J. 2010, 340: b4838-10.1136/bmj.b4838.CrossRef
20.
Edelman E, Eng C: A practical guide to interpretation and clinical application of personal genomic screening. Br Med J. 2009, 339: b4253-10.1136/bmj.b4253.CrossRef
21.
Wang C, Bowen DJ, Kardia SL: Research and practice opportunities at the intersection of health education, health behavior, and genomics. Health Educ Behav. 2005, 32: 686-701. 10.1177/1090198105278827.CrossRefPubMed
22.
Feero WG, Guttmacher AE, Collins FS: The Genome Gets Personal—Almost. JAMA. 2008, 299: 1351-1352. 10.1001/jama.299.11.1351.CrossRefPubMed
23.
Marteau TM: Communicating genetic risk information. Br Med Bull. 1999, 55: 414-428. 10.1258/0007142991902466.CrossRefPubMed
24.
Marteau TM, Weinman J: Self-regulation and the behavioural response to DNA risk information: A theoretical analysis and framework for future research. Social Sci Med. 2006, 62: 1360-1368. 10.1016/j.socscimed.2005.08.005.CrossRef
25.
Collins RE, Wright AJ, Marteau TM: Impact of communicating personalized genetic risk information on perceived control over the risk: a systematic review. Genet Med. 2011, 13: 273-10.1097/GIM.0b013e3181f710ca.CrossRefPubMed
26.
Bates BR, Templeton A, Achter PJ, Harris TM, Condit CM: What does "a gene for heart disease" mean? A focus group study of public understandings of genetic risk factors. Am J Med Genet A. 2003, 119A: 156-161. 10.1002/ajmg.a.20113.CrossRefPubMed
27.
Boer H, Seydel E: Protection motivation theory. Predicting Health Behavior 1st edition. Edited by: Connor M, Norman P. 1996, Buckingham: Open University Press, 95-118.
28.
Brewer N, Weinstein N, Cuite C, Herrington J: Risk perceptions and their relation to risk behavior. Ann Behav Med. 2004, 27: 125-130. 10.1207/s15324796abm2702_7.CrossRefPubMed
29.
Rothman AJ, Kiviniemi MT: Treating people with information: an analysis and review of approaches to communicating health risk information. J Natl Cancer Inst Monogr. 1999, 1999: 44-51. 10.1093/oxfordjournals.jncimonographs.a024207.CrossRef
30.
Weinstein ND: What does it mean to understand a risk? Evaluating risk comprehension. J Natl Cancer Inst Monogr. 1999, 1999: 15-20. 10.1093/oxfordjournals.jncimonographs.a024192.CrossRef
31.
Price H: Risk communication: Why, what and how?A discussion of the evidence regarding risk communication and how best to do it in practice. Diabetes and Primary Care. 2010, 12: 100-
32.
Sivell S, Elwyn G, Gaff CL, Clarke AJ, Iredale R, Shaw C, Dundon J, Thornton H, Edwards A: How risk is perceived, constructed and interpreted by clients in clinical genetics, and the effects on decision making: Systematic review. J Genet Couns. 2008, 17: 30-63. 10.1007/s10897-007-9132-1.CrossRefPubMed
33.
Edwards A, Elwyn G, Mulley A: Explaining risks: turning numerical data into meaningful pictures. Br Med J. 2002, 324: 827-830. 10.1136/bmj.324.7341.827.CrossRef
34.
Gigerenzer G, Edwards A: Simple tools for understanding risks: from innumeracy to insight. Br Med J. 2003, 327: 741-744. 10.1136/bmj.327.7417.741.CrossRef
35.
Cameron LD, Sherman KA, Marteau TM, Brown PM: Impact of genetic risk information and type of disease on perceived risk, anticipated affect, and expected consequences of genetic tests. Heal Psychol. 2009, 28: 307-CrossRef
36.
Leventhal H, Brissette I, Leventhal EA: The common-sense model of self-regulation of health and illness. The self-regulation of health and illness behaviour. Edited by: Cameron LD, Leventhal H. 2003, New York: Routledge, 42-65.
37.
Floyd D, Prentice-Dunn S: A meta-analysis of research on protection motivation theory. J Appl Soc Psychol. 2000, 30: 407-429. 10.1111/j.1559-1816.2000.tb02323.x.CrossRef
38.
Milne S, Sheeran P, Orbell S: Prediction and intervention in health-related behavior: A meta-analytic review of protection motivation theory. J Appl Soc Psychol. 2000, 30: 106-143. 10.1111/j.1559-1816.2000.tb02308.x.CrossRef
39.
Marteau TM, French DP, Griffin SJ, Prevost A, Sutton S, Watkinson C, Attwood S, Hollands GJ: Effects of communicating DNA-based disease risk estimates on risk-reducing behaviours. Annu Rev Public Health. 2010
40.
McBride CM, Koehly LM, Sanderson SC, Kaphingst KA: The behavioral response to personalized genetic information: Will genetic risk profiles motivate individuals and families to choose more healthful behaviors?. Annu Rev Public Health. 2010, 31: 89-103. 10.1146/annurev.publhealth.012809.103532.CrossRefPubMed
41.
Marteau TM, Lerman C: Genetic risk and behavioural change. Br Med J. 2001, 322: 1056-1059. 10.1136/bmj.322.7293.1056.CrossRef
42.
Beery TA, Williams JK: Risk reduction and health promotion behaviors following genetic testing for adult-onset disorders. Genet Test. 2007, 11: 111-123. 10.1089/gte.2006.0527.CrossRefPubMed
43.
Heshka JT, Palleschi C, Howley H, Wilson B, Wells PS: A systematic review of perceived risks, psychological and behavioral impacts of genetic testing. Genet Med. 2008, 10: 19-32. 10.1097/GIM.0b013e31815f524f.CrossRefPubMed
44.
Scheuner MT, Sieverding P, Shekelle PG: Delivery of genomic medicine for common chronic adult diseases: a systematic review. JAMA. 2008, 299: 1320-1334. 10.1001/jama.299.11.1320.CrossRefPubMed
45.
McBride CM, Brody LC: Point: genetic risk feedback for common disease time to test the waters. Cancer Epidemiol Biomarkers Prev. 2007, 16: 1724-1726. 10.1158/1055-9965.EPI-07-0102.CrossRefPubMed
46.
Khoury MJ, Gwinn M, Yoon PW, Dowling N, Moore CA, Bradley L: The continuum of translation research in genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention?. Genet Med. 2007, 9: 665-10.1097/GIM.0b013e31815699d0.CrossRefPubMed
47.
De Lucia Rolfe E, Loos RJF, Druet C, Stolk RP, Ekelund U, Griffin SJ, Forouhi NG, Wareham NJ, Ong KK: Association between birth weight and visceral fat in adults. Am J Clin Nutr. 2010, 92: 347-10.3945/ajcn.2010.29247.CrossRef
48.
Edwards A, Gray J, Clarke A, Dundon J, Elwyn G, Gaff C, Hood K, Iredale R, Sivell S, Shaw C, Thornton H: Interventions to improve risk communication in clinical genetics: Systematic review. Patient Educ Counseling. 2008, 71: 4-25. 10.1016/j.pec.2007.11.026.CrossRef
49.
Fagerlin A, Zikmund-Fisher BJ, Ubel PA: “If I’m better than average, then I’m ok?”: Comparative information influences beliefs about risk and benefits. Patient Educ Counseling. 2007, 69: 140-144. 10.1016/j.pec.2007.08.008.CrossRef
50.
Mason D, Prevost AT, Sutton S: Perceptions of absolute versus relative differences between personal and comparison health risk. Heal Psychol. 2008, 27: 87-CrossRef
51.
Cameron LD: Can our health behaviour models handle imagery-based processes and communications?. The Eur Health Psychologist. 2009, 11: 56-58.
52.
53.
54.
55.
Narayan KMV, Boyle JP, Thompson TJ, Sorensen SW, Williamson DF: Lifetime Risk for Diabetes Mellitus in the United States. JAMA. 2003, 290: 1884-1890. 10.1001/jama.290.14.1884.CrossRefPubMed
56.
NHLBI Obesity Education Initiative Expert Panel on the Identification Evaluation and Treatment of Obesity in Adults: Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults – The evidence report. 1998, Washington DC: National Institutes of Health
57.
Griffin S, Little P, Hales C, Kinmonth A, Wareham N: Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev. 2000, 16: 164-171. 10.1002/1520-7560(200005/06)16:3<164::AID-DMRR103>3.0.CO;2-R.CrossRefPubMed
58.
Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ: A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study. Fam Pract. 2008, 25: 191-196. 10.1093/fampra/cmn024.CrossRefPubMed
59.
DOH: At least five a week: Evidence on the impact of physical activity and its relationship to health. 2004, London: London Department of Health
60.
Cardiovascular Review Group Committee on Medical Aspects of Food Policy: Nutritional aspects of cardiovascular disease: Report on health and social subjects. 1994, London: HMSO
61.
Brage S, Brage N, Franks P, Ekelund U, Wareham N: Reliability and validity of the combined heart rate and movement sensor Actiheart. Eur J Clin Nutr. 2005, 59: 561-570. 10.1038/sj.ejcn.1602118.CrossRefPubMed
62.
Brage S, Ekelund U, Brage N, Hennings MA, Froberg K, Franks PW, Wareham NJ: Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J Appl Physiol. 2007, 103: 682-10.1152/japplphysiol.00092.2006.CrossRefPubMed
63.
Brage S, Brage N, Franks P, Ekelund U, Wong M, Andersen L, Froberg K, Wareham N: Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure. J Appl Physiol. 2004, 96: 343-CrossRefPubMed
64.
Thompson D, Batterham A, Bock S, Robson C, Stokes K: Assessment of low-to-moderate intensity physical activity thermogenesis in young adults using synchronized heart rate and accelerometry with branched-equation modeling. J Nutr. 2006, 136: 1037-PubMed
65.
Strath SJ, Brage S, Ekelund U: Integration of physiological and accelerometer data to improve physical activity assessment. Med Sci Sports Exercise. 2005, 37: S563-S571. 10.1249/01.mss.0000185650.68232.3f.CrossRef
66.
67.
Atlantis E, Barnes EH, Ball K: Weight status and perception barriers to healthy physical activity and diet behavior. Int J Obes. 2008, 32: 343-352. 10.1038/sj.ijo.0803707.CrossRef
68.
Maximova K, McGrath JJ, Barnett T, O'Loughlin J, Paradis G, Lambert M: Do you see what I see? Weight status misperception and exposure to obesity among children and adolescents. Int J Obes. 2008, 32: 1008-1015. 10.1038/ijo.2008.15.CrossRef
69.
Lechner L, Brug J, De Vries H: Misconceptions of fruit and vegetable consumption: Differences between objective and subjective estimation of intake. J Nutr Educ. 1997, 29: 313-320. 10.1016/S0022-3182(97)70245-0.CrossRef
70.
Lechner L, Brug J, De Vries H, van Assema P, Mudde A: Stages of change for fruit, vegetable and fat intake: consequences of misconception. Heal Educ Res. 1998, 13: 1-a-11.CrossRef
71.
Lechner L, Bolman C, Van Dijke M: Factors related to misperception of physical activity in The Netherlands and implications for health promotion programmes. Heal Promot Int. 2006, 21: 104-112. 10.1093/heapro/dal011.CrossRef
72.
van Sluijs E, Griffin S, van Poppel M: A cross-sectional study of awareness of physical activity: associations with personal, behavioral and psychosocial factors. Int J Behav Nutr Phys Act. 2007, 4: 53-10.1186/1479-5868-4-53.CrossRefPubMedPubMedCentral
73.
Broadbent E, Petrie KJ, Main J, Weinman J: The brief illness perception questionnaire. J Psychosom Res. 2006, 60: 631-637. 10.1016/j.jpsychores.2005.10.020.CrossRefPubMed
74.
Figueiras MJ, Alves NC: Lay perceptions of serious illnesses: An adapted version of the Revised Illness Perception Questionnaire (IPQ-R) for healthy people. Psychol Heal. 2007, 22: 143-158. 10.1080/14768320600774462.CrossRef
75.
Cameron LD: Illness risk representations and motivations to engage in protective behavior: The case of skin cancer risk. Psychol Heal. 2008, 23: 91-112. 10.1080/14768320701342383.CrossRef
76.
Ajzen I: The theory of planned behavior. Organ Behav Hum Decis Process. 1991, 50: 179-211. 10.1016/0749-5978(91)90020-T.CrossRef
77.
78.
Blue CL: Does the theory of planned behavior identify diabetes-related cognitions for intention to be physically active and eat a healthy diet?. Public Health Nursing. 2007, 24: 141-150. 10.1111/j.1525-1446.2007.00618.x.CrossRefPubMed
79.
Diefenbach MA, Weinstein ND, O'Reilly J: Scales for assessing perceptions of health hazard susceptibility. Heal Educ Res. 1993, 8: 181-192. 10.1093/her/8.2.181.CrossRef
80.
Lipkus IM, Kuchibhatla M, McBride CM, Bosworth HB, Pollak KI, Siegler IC, Rimer BK: Relationships among breast cancer perceived absolute risk, comparative risk, and worries. Cancer Epidemiol Biomarkers Prev. 2000, 9: 973-975.PubMed
81.
Fayers PM, Sprangers MAG: Understanding self-rated health. Lancet. 2002, 359: 187-188. 10.1016/S0140-6736(02)07466-4.CrossRefPubMed
82.
Watson M, Lloyd S, Davidson J, Meyer L, Eeles R, Ebbs S, Murday V: The impact of genetic counselling on risk perception and mental health in women with a family history of breast cancer. Br J Cancer. 1999, 79: 868-10.1038/sj.bjc.6690139.CrossRefPubMedPubMedCentral
83.
Rees G, Fry A, Cull A, Sutton S: Illness perceptions and distress in women at increased risk of breast cancer. Psychol Heal. 2004, 19: 749-765. 10.1080/08870440412331279764.CrossRef
84.
Marteau TM, Bekker H: The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol. 1992, 31: 301-306. 10.1111/j.2044-8260.1992.tb00997.x.CrossRefPubMed
85.
Park P, Simmons RK, Prevost AT, Griffin SJ: Screening for type 2 diabetes is feasible, acceptable, but associated with increased short-term anxiety: a randomised controlled trial in British general practice. BMC Publ Health. 2008, 8: 350-10.1186/1471-2458-8-350.CrossRef
86.
Gorber SC, Tremblay M, Moher D, Gorber B: A comparison of direct vs. self‐report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007, 8: 307-326. 10.1111/j.1467-789X.2007.00347.x.CrossRefPubMed
87.
McKeown NM, Day NE, Welch AA, Runswick SA, Luben RN, Mulligan AA, McTaggart A, Bingham SA: Use of biological markers to validate self-reported dietary intake in a random sample of the European Prospective Investigation into Cancer United Kingdom Norfolk cohort. Am J Clin Nutr. 2001, 74: 188-196.PubMed
88.
Bingham SA, Gill C, Welch A, Day K, Cassidy A, Khaw KT, Sneyd MJ, Key TJA, Roe L, Day NE: Comparison of dietary assessment methods in nutritional epidemiology: weighed records v. 24 h recalls, food-frequency questionnaires and estimated-diet records. Br J Nutr. 1994, 72: 619-643. 10.1079/BJN19940064.CrossRefPubMed
89.
Sterne JAC, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, Wood AM, Carpenter JR: Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. Br Med J. 2009, 338: b2393-10.1136/bmj.b2393.CrossRef
90.
White IR, Thompson SG: Adjusting for partially missing baseline measurements in randomized trials. Stat Med. 2005, 24: 993-1007. 10.1002/sim.1981.CrossRefPubMed
91.
Watkinson C, van Sluijs E, Sutton S, Marteau T, Griffin S: Randomised controlled trial of the effects of physical activity feedback on awareness and behaviour in UK adults: the FAB study protocol [ISRCTN92551397]. BMC Publ Health. 2010, 10: 144-10.1186/1471-2458-10-144.CrossRef
92.
93.
Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M: Developing and evaluating complex interventions: the new Medical Research Council guidance. Br Med J. 2008, 337: a1655-10.1136/bmj.a1655.CrossRef
94.
Yates T, Davies M, Khunti K: Preventing type 2 diabetes: can we make the evidence work?. Postgrad Med J. 2009, 85: 475-480. 10.1136/pgmj.2008.076166.CrossRefPubMed
Metadata
Title
Effect of communicating genetic and phenotypic risk for type 2 diabetes in combination with lifestyle advice on objectively measured physical activity: protocol of a randomised controlled trial
Authors
Job G Godino
Esther MF van Sluijs
Theresa M Marteau
Stephen Sutton
Stephen J Sharp
Simon J Griffin
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2012
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/1471-2458-12-444

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