View Item 

Show simple item record

New research directions on disparities in obesity and type 2 diabetes
dc.contributor.authorThornton, Pamela L.
dc.contributor.authorKumanyika, Shiriki K.
dc.contributor.authorGregg, Edward W.
dc.contributor.authorAraneta, Maria R.
dc.contributor.authorBaskin, Monica L.
dc.contributor.authorChin, Marshall H.
dc.contributor.authorCrespo, Carlos J.
dc.contributor.authorGroot, Mary
dc.contributor.authorGarcia, David O.
dc.contributor.authorHaire‐joshu, Debra
dc.contributor.authorHeisler, Michele
dc.contributor.authorHill‐briggs, Felicia
dc.contributor.authorLadapo, Joseph A.
dc.contributor.authorLindberg, Nangel M.
dc.contributor.authorManson, Spero M.
dc.contributor.authorMarrero, David G.
dc.contributor.authorPeek, Monica E.
dc.contributor.authorShields, Alexandra E.
dc.contributor.authorTate, Deborah F.
dc.contributor.authorMangione, Carol M.
dc.date.accessioned2020-03-17T18:34:29Z
dc.date.availableWITHHELD_12_MONTHS
dc.date.available2020-03-17T18:34:29Z
dc.date.issued2020-02
dc.identifier.citationThornton, Pamela L.; Kumanyika, Shiriki K.; Gregg, Edward W.; Araneta, Maria R.; Baskin, Monica L.; Chin, Marshall H.; Crespo, Carlos J.; Groot, Mary; Garcia, David O.; Haire‐joshu, Debra ; Heisler, Michele; Hill‐briggs, Felicia ; Ladapo, Joseph A.; Lindberg, Nangel M.; Manson, Spero M.; Marrero, David G.; Peek, Monica E.; Shields, Alexandra E.; Tate, Deborah F.; Mangione, Carol M. (2020). "New research directions on disparities in obesity and type 2 diabetes." Annals of the New York Academy of Sciences 1461(1): 5-24.
dc.identifier.issn0077-8923
dc.identifier.issn1749-6632
dc.identifier.urihttps://hdl.handle.net/2027.42/154507
dc.description.abstractObesity and type 2 diabetes disproportionately impact U.S. racial and ethnic minority communities and lowâ income populations. Improvements in implementing efficacious interventions to reduce the incidence of type 2 diabetes are underway (i.e., the National Diabetes Prevention Program), but challenges in effectively scalingâ up successful interventions and reaching atâ risk populations remain. In October 2017, the National Institutes of Health convened a workshop to understand how to (1) address socioeconomic and other environmental conditions that perpetuate disparities in the burden of obesity and type 2 diabetes; (2) design effective prevention and treatment strategies that are accessible, feasible, culturally relevant, and acceptable to diverse population groups; and (3) achieve sustainable health improvement approaches in communities with the greatest burden of these diseases. Common features of guiding frameworks to understand and address disparities and promote health equity were described. Promising research directions were identified in numerous areas, including study design, methodology, and core metrics; program implementation and scalability; the integration of medical care and social services; strategies to enhance patient empowerment; and understanding and addressing the impact of psychosocial stress on disease onset and progression in addition to factors that support resiliency and health.This report discusses a workshop convened by the National Institutes of Health to understand how to (1) address socioeconomic and other environmental conditions that perpetuate disparities in the burden of obesity and type 2 diabetes; (2) design effective prevention and treatment strategies that are accessible, feasible, culturally relevant, and acceptable to diverse population groups; and (3) achieve sustainable health improvement approaches in communities with the greatest burden of these diseases.
dc.publisherWiley Periodicals, Inc.
dc.publisherNational Academies Press
dc.subject.otherNIH
dc.subject.otherobesity
dc.subject.otherdiabetes
dc.subject.otherdisparities
dc.subject.othersocial determinants
dc.subject.otherNIDDK
dc.titleNew research directions on disparities in obesity and type 2 diabetes
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelScience (General)
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154507/1/nyas14270_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154507/2/nyas14270.pdf
dc.identifier.doi10.1111/nyas.14270
dc.identifier.sourceAnnals of the New York Academy of Sciences
dc.identifier.citedreferenceArgentieri, M.A., S. Nagarajan, B. Seddighzadeh, et al. 2017. Epigenetic pathways in human disease: the impact of DNA methylation on stressâ related pathogenesis and current challenges in biomarker development. EBioMedicine 18: 327 â 350.
dc.identifier.citedreferenceAmerican Psychological Association APA Working Group on Stress and Health Disparities. 2017. Stress and health disparities report: contexts, mechanisms, and interventions among racial/ethnic minority and low socioeconomic status populations. Accessed October 3, 2019. https://www.apa.org/pi/health-disparities/resources/stress-report.
dc.identifier.citedreferenceShields, A.E. 2017. Epigenetic signals of how social disadvantage â gets under the skinâ : a challenge to the public health community. Epigenomics 9: 223 â 229.
dc.identifier.citedreferenceBrotman, D.J., S.H. Golden & I.S. Wittstein. 2007. The cardiovascular toll of stress. Lancet 370: 1089 â 1100.
dc.identifier.citedreferenceEpel, E.S., E.H. Blackburn, J. Lin, et al. 2004. Accelerated telomere shortening in response to life stress. Proc. Natl. Acad. Sci. USA 101: 17312 â 17315.
dc.identifier.citedreferenceBhasin, M.K., J.A. Dusek, B.H. Chang, et al. 2013. Relaxation response induces temporal transcriptome changes in energy metabolism, insulin secretion and inflammatory pathways. PLoS One 8: e62817.
dc.identifier.citedreferenceDusek, J.A., H.H. Otu, A.L. Wohlhueter, et al. 2008. Genomic counterâ stress changes induced by the relaxation response. PLoS One 3: e2576.
dc.identifier.citedreferenceLevine, G.N., R.A. Lange, C.N. Baireyâ Merz, et al. 2017. Meditation and cardiovascular risk reduction: a scientific statement from the American Heart Association. J. Am. Heart Assoc. 6. https://doi.org/10.1161/JAHA.117.002218.
dc.identifier.citedreferenceRay, I.B., A.R. Menezes, P. Malur, et al. 2014. Meditation and coronary heart disease: a review of the current clinical evidence. Ochsner J. 14: 696 â 703.
dc.identifier.citedreferenceVanderWeele, T.J., J. Yu, Y.C. Cozier, et al. 2017. Attendance at religious services, prayer, religious coping, and religious/spiritual identity as predictors of allâ cause mortality in the Black Women’s Health Study. Am. J. Epidemiol. 185: 515 â 522.
dc.identifier.citedreferencePew Research Center. 2014. Religious landscape study. Accessed October 3, 2019. https://www.pewforum.org/religious-landscape-study/.
dc.identifier.citedreferenceCozier, Y.C., J. Yu, L.A. Wise, et al. 2018. Religious and spiritual coping and risk of incident hypertension in the Black Women’s Health Study. Ann. Behav. Med. 52: 989 â 998.
dc.identifier.citedreferenceSpence, N., M. Farvid, E. Warner, et al. 2019. Religious service attendance, religious coping, and risk of hypertension in women participating in the Nurses’ Health Study II. Am. J. Epidemiol. https://doi.org/10.1093/aje/kwz222.
dc.identifier.citedreferencevan Dam, H.A., F.G. van der Horst, L. Knoops, et al. 2005. Social support in diabetes: a systematic review of controlled intervention studies. Patient Educ. Couns. 59: 1 â 12.
dc.identifier.citedreferenceCohen, S. 2004. Social relationships and health. Am. Psychol. 59: 676 â 684.
dc.identifier.citedreferenceBerkman, L.F., T. Glass, I. Brissette, et al. 2000. From social integration to health: Durkheim in the new millennium. Soc. Sci. Med. 51: 843 â 857.
dc.identifier.citedreferenceYoungâ Hyman, D., M. de Groot, F. Hillâ Briggs, et al. 2016. Psychosocial care for people with diabetes: a position statement of the American Diabetes Association. Diabetes Care 39: 2126 â 2140.
dc.identifier.citedreferenceNoordam, R., N. Aarts, R.P. Peeters, et al. 2016. Selective serotonin reuptake inhibitors decrease pancreatic insulin secretion in older adults and increase the risk of insulin dependence in type 2 diabetes patients. J. Clin. Psychiatry 77: e1124â e1129.
dc.identifier.citedreferenceAnderson, R.J., K.E. Freedland, R.E. Clouse, et al. 2001. The prevalence of comorbid depression in adults with diabetes: a metaâ analysis. Diabetes Care 24: 1069 â 1078.
dc.identifier.citedreferenceAli, S., M.A. Stone, J.L. Peters, et al. 2006. The prevalence of coâ morbid depression in adults with Type 2 diabetes: a systematic review and metaâ analysis. Diabet. Med. 23: 1165 â 1173.
dc.identifier.citedreferencede Groot, M., R. Anderson, K.E. Freedland, et al. 2001. Association of depression and diabetes complications: a metaâ analysis. Psychosom. Med. 63: 619 â 630.
dc.identifier.citedreferenceGoldney, R.D., P.J. Phillips, L.J. Fisher, et al. 2004. Diabetes, depression, and quality of life: a population study. Diabetes Care 27: 1066 â 1070.
dc.identifier.citedreferenceKaton, W.J., C. Rutter, G. Simon, et al. 2005. The association of comorbid depression with mortality in patients with type 2 diabetes. Diabetes Care 28: 2668 â 2672.
dc.identifier.citedreferenceZhang, X., S.L. Norris, E.W. Gregg, et al. 2005. Depressive symptoms and mortality among persons with and without diabetes. Am. J. Epidemiol. 161: 652 â 660.
dc.identifier.citedreferenceLlorente, M.D. & V. Urrutia. 2006. Diabetes, psychiatric disorders, and the metabolic effects of antipsychotic medications. Clin. Diabetes 24: 18 â 24.
dc.identifier.citedreferenceBurcu, M., J.M. Zito, D.J. Safer, et al. 2017. Concomitant use of atypical antipsychotics with other psychotropic medication classes and the risk of type 2 diabetes mellitus. J. Am. Acad. Child Adolesc. Psychiatry 56: 642 â 651.
dc.identifier.citedreferenceU.S. Department of Health and Human Services. 2001. Mental health: culture, race, and ethnicity. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration.
dc.identifier.citedreferenceGonzalez, J.S., L. Fisher & W.H. Polonsky. 2011. Depression in diabetes: have we been missing something important? Diabetes Care 34: 236 â 239.
dc.identifier.citedreferenceFisher, L., D.M. Hessler, W.H. Polonsky, et al. 2012. When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale. Diabetes Care 35: 259 â 264.
dc.identifier.citedreferenceNaranjo, D., D.M. Hessler, R. Deol, et al. 2012. Health and psychosocial outcomes in U.S. adult patients with diabetes from diverse ethnicities. Curr. Diab. Rep. 12: 729 â 738.
dc.identifier.citedreferenceHilliard, M.E., J.P. Yiâ Frazier, D. Hessler, et al. 2016. Stress and A1c among people with diabetes across the lifespan. Curr. Diab. Rep. 16: 67.
dc.identifier.citedreferenceFisher, L., M.M. Skaff, J.T. Mullan, et al. 2007. Clinical depression versus distress among patients with type 2 diabetes: not just a question of semantics. Diabetes Care 30: 542 â 548.
dc.identifier.citedreferenceKoh, H.K., S.C. Oppenheimer, S.B. Massinâ Short, et al. 2010. Translating research evidence into practice to reduce health disparities: a social determinants approach. Am. J. Public Health 100 ( Suppl. 1 ): S72 â S80.
dc.identifier.citedreferenceWharam, J.F., F. Zhang, E.M. Eggleston, et al. 2018. Effect of highâ deductible insurance on highâ acuity outcomes in diabetes: a Natural Experiment for Translation in Diabetes (NEXTâ D) Study. Diabetes Care 41: 940 â 948.
dc.identifier.citedreferenceNational Academies of Sciences, Engineering & Medicine. 2018. Immigration as a Social Determinant of Health: Proceedings of a Workshop. Washington, DC: National Academies Press.
dc.identifier.citedreferenceHaireâ Joshu, D., C.D. Schwarz, K. Stegerâ May, et al. 2018. A randomized trial of weight change in a national home visiting program. Am. J. Prev. Med. 54: 341 â 351.
dc.identifier.citedreferenceCahill, A.G., D. Haireâ Joshu, W.T. Cade, et al. 2018. Weight control program and gestational weight gain in disadvantaged women with overweight or obesity: a randomized clinical trial. Obesity (Silver Spring) 26: 485 â 491.
dc.identifier.citedreferenceHaireâ Joshu, D., A.G. Cahill, R.I. Stein, et al. 2019. Randomized controlled trial of homeâ based lifestyle therapy on postpartum weight in underserved women with overweight or obesity. Obesity (Silver Spring) 27: 535 â 541.
dc.identifier.citedreferencePew Research Center. 2019. Mobile fact sheet. Accessed July 30, 2019. https://www.pewinternet.org/fact-sheet/mobile/.
dc.identifier.citedreferencePew Research Center. 2019. Digital gap between rural and nonrural America persists. Accessed July 30, 2019. https://www.pewresearch.org/fact-tank/2019/05/31/digital-gap-between-rural-and-nonrural-america-persists/.
dc.identifier.citedreferenceChin et al. 2014. Components of the intervention to improve diabetes care and outcomes on the south side. Health Promot. Pract. 15: 29S â 39S.
dc.identifier.citedreferenceBullard, K.M., C.C. Cowie, S.E. Lessem, et al. 2018. Prevalence of diagnosed diabetes in adults by diabetes typeâ United States, 2016. MMWR Morb. Mortal. Wkly. Rep. 67: 359 â 361.
dc.identifier.citedreferenceHales, C.M., C.D. Fryar, M.D. Carroll, et al. 2018. Differences in obesity prevalence by demographic characteristics and urbanization level among adults in the United States, 2013â 2016. JAMA. 319: 2419 â 2429.
dc.identifier.citedreferenceDilley, J.A., K.W. Simmons, M.J. Boysun, et al. 2010. Demonstrating the importance and feasibility of including sexual orientation in public health surveys: health disparities in the Pacific Northwest. Am. J. Public Health 100: 460 â 467.
dc.identifier.citedreferenceKnowler, W.C., E. Barrettâ Connor, S.E. Fowler, et al. 2002. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N. Engl. J. Med. 346: 393 â 403.
dc.identifier.citedreferenceCenters for Disease Control and Prevention, U.S. Department of Health and Human Services. 2018. National Diabetes Prevention Program. Accessed January 10, 2019. https://www.cdc.gov/diabetes/prevention/index.html.
dc.identifier.citedreferenceHaireâ Joshu, D. & F. Hillâ Briggs. 2019. The next generation of diabetes translation: a path to health equity. Annu. Rev. Public Health 40: 391 â 410.
dc.identifier.citedreferenceGregg, E. 2019. Prevalence of total diabetes (diagnosed diabetes and undiagnosed diabetes) in the U.S. adult population, age â ¥ 20, 2011â 2016 (PIR = poverty income ratio). Unpublished data, National Health and Nutrition Examination Survey.
dc.identifier.citedreferenceCenters for Disease Control and Prevention, U.S. Department of Health and Human Services. 2017. National Diabetes Statistics Report, 2017. Accessed February 15, 2019. https://www.cdc.gov/features/diabetes-statistic-report/index.html.
dc.identifier.citedreferenceCunningham, S.A., S.A. Patel, G.L. Beckles, et al. 2018. Countyâ level contextual factors associated with diabetes incidence in the United States. Ann. Epidemiol. 28: 20 â 25.e22.
dc.identifier.citedreferenceSiegel, K.R., K.M. Bullard, G. Imperatore, et al. 2018. Prevalence of major behavioral risk factors for type 2 diabetes. Diabetes Care 41: 1032 â 1039.
dc.identifier.citedreferenceLovasi, G.S., M.A. Hutson, M. Guerra, et al. 2009. Built environments and obesity in disadvantaged populations. Epidemiol. Rev. 31: 7 â 20.
dc.identifier.citedreferenceNelson, M.C., N.I. Larson, D. Barrâ Anderson, et al. 2009. Disparities in dietary intake, meal patterning, and home food environments among young adult nonstudents and 2â and 4â year college students. Am. J. Public Health 99: 1216 â 1219.
dc.identifier.citedreferencePetrovic, D., C. de Mestral, M. Bochud, et al. 2018. The contribution of health behaviors to socioeconomic inequalities in health: a systematic review. Prev. Med. 113: 15 â 31.
dc.identifier.citedreferenceBijlsmaâ Rutte, A., F. Rutters, P.J.M. Elders, et al. 2018. Socioâ economic status and HbA1c in type 2 diabetes: a systematic review and metaâ analysis. Diabetes Metab. Res. Rev. 34: e3008.
dc.identifier.citedreferenceAli, M.K., K. McKeever Bullard, G. Imperatore, et al. 2012. Characteristics associated with poor glycemic control among adults with selfâ reported diagnosed diabetesâ National Health and Nutrition Examination Survey, United States, 2007â 2010. MMWR Suppl. 61: 32 â 37.
dc.identifier.citedreferenceMayberry, L.S., E.M. Bergner, R.J. Chakkalakal, et al. 2016. Selfâ care disparities among adults with type 2 diabetes in the USA. Curr. Diab. Rep. 16: 113.
dc.identifier.citedreferenceBrown, A.F., R.B. Gerzoff, A.J. Karter, et al. 2003. Health behaviors and quality of care among Latinos with diabetes in managed care. Am. J. Public Health 93: 1694 â 1698.
dc.identifier.citedreferenceMosen, D.M., A. Feldstein & A. Borin. 2015. Disparities in glycemic control among Hispanic adults with diabetes. J. Patient Cent. Res. Rev. 2: 114.
dc.identifier.citedreferenceMuntner, P., M. Abdalla, A. Correa, et al. 2017. Hypertension in Blacks: unanswered questions and future directions for the JHS (Jackson Heart Study). Hypertension 69: 761 â 769.
dc.identifier.citedreferenceGregg, E.W., Y. Li, J. Wang, et al. 2014. Changes in diabetesâ related complications in the United States, 1990â 2010. N. Engl. J. Med. 370: 1514 â 1523.
dc.identifier.citedreferenceDesai, N., C.M. Lora, J.P. Lash, et al. 2019. CKD and ESRD in US Hispanics. Am. J. Kidney Dis. 73: 102 â 111.
dc.identifier.citedreferenceZheng, Y., S.H. Ley & F.B. Hu. 2018. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat. Rev. Endocrinol. 14: 88 â 98.
dc.identifier.citedreferenceFord, E.S., U.A. Ajani, J.B. Croft, et al. 2007. Explaining the decrease in U.S. deaths from coronary disease, 1980â 2000. N. Engl. J. Med. 356: 2388 â 2398.
dc.identifier.citedreferenceAli, M.K., K.M. Bullard & E.W. Gregg. 2013. Achievement of goals in U.S. Diabetes Care, 1999â 2010. N. Engl. J. Med. 369: 287 â 288.
dc.identifier.citedreferenceWorld Health Organization. 2019. Health equity. Accessed May 27, 2019. https://www.who.int/topics/health_equity/en/.
dc.identifier.citedreferenceOffice of Disease Prevention and Health Promotion, U.S. Dept of Health and Human Services. 2019. Healthy people 2020. Accessed January 15, 2019. https://www.healthypeople.gov/.
dc.identifier.citedreferenceMarmot, M. 2005. Social determinants of health inequalities. Lancet 365: 1099 â 1104.
dc.identifier.citedreferenceChin, M.H., P.T. King, R.G. Jones, et al. 2018. Lessons for achieving health equity comparing Aotearoa/New Zealand and the United States. Health Policy 122: 837 â 853.
dc.identifier.citedreferenceChin, M.H., A.R. Clarke, R.S. Nocon, et al. 2012. A roadmap and best practices for organizations to reduce racial and ethnic disparities in health care. J. Gen. Intern. Med. 27: 992 â 1000.
dc.identifier.citedreferenceKumanyika, S. 2017. Getting to equity in obesity prevention: a new framework. Accessed January 3, 2018. https://nam.edu/getting-to-equity-in-obesity-prevention-a-new-framework/.
dc.identifier.citedreferenceTung, E.L., K.A. Cagney, M.E. Peek, et al. 2017. Spatial context and health inequity: reconfiguring race, place, and poverty. J. Urban Health 94: 757 â 763.
dc.identifier.citedreferenceDamschroder, L.J., D.C. Aron, R.E. Keith, et al. 2009. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement. Sci. 4: 50.
dc.identifier.citedreferenceKao, A.C. 2015. Driven to care: aligning external motivators with intrinsic motivation. Health Serv. Res. 50 ( Suppl. 2 ): 2216â 2222.
dc.identifier.citedreferencePeek, M.E., M.J. Ferguson, T.P. Roberson, et al. 2014. Putting theory into practice: a case study of diabetesâ related behavioral change interventions on Chicago’s South Side. Health Promot. Pract. 15: 40S â 50S.
dc.identifier.citedreferenceNational Institute on Minority Health and Health Disparities. 2017. NIMHD research framework. Accessed January 3, 2019. https://www.nimhd.nih.gov/about/overview/research-framework.html.
dc.identifier.citedreferenceAlley, D.E., C.N. Asomugha, P.H. Conway, et al. 2016. Accountable health communitiesâ addressing social needs through Medicare and Medicaid. N. Engl. J. Med. 374: 8 â 11.
dc.identifier.citedreferenceCooper, L.A., D.L. Roter, K.A. Carson, et al. 2012. The associations of clinicians’ implicit attitudes about race with medical visit communication and patient ratings of interpersonal care. Am. J. Public Health 102: 979 â 987.
dc.identifier.citedreferenceBen, J., D. Cormack, R. Harris, et al. 2017. Racism and health service utilisation: a systematic review and metaâ analysis. PLoS One 12: e0189900.
dc.identifier.citedreferenceBerwick, D.M., T.W. Nolan & J. Whittington. 2008. The triple aim: care, health, and cost. Health Aff. (Millwood) 27: 759 â 769.
dc.identifier.citedreferenceChen, A.H., M.K. Youdelman & J. Brooks. 2007. The legal framework for language access in healthcare settings: title VI and beyond. J. Gen. Intern. Med. 22 ( Suppl. 2 ): 362 â 367.
dc.identifier.citedreferencePeek, M.E., A. Odomsâ Young, M.T. Quinn, et al. 2010. Race and shared decisionâ making: perspectives of Africanâ Americans with diabetes. Soc. Sci. Med. 71: 1 â 9.
dc.identifier.citedreferenceWilkes, A.E., K. Bordenave, L. Vinci, et al. 2011. Addressing diabetes racial and ethnic disparities: lessons learned from quality improvement collaboratives. Diabetes Manag. (Lond.) 1: 653 â 660.
dc.identifier.citedreferencePeek, M.E., A.E. Wilkes, T.S. Roberson, et al. 2012. Early lessons from an initiative on Chicago’s South Side to reduce disparities in diabetes care and outcomes. Health Aff. (Millwood) 31: 177 â 186.
dc.identifier.citedreferencePeek, M.E., S.A. Harmon, S.J. Scott, et al. 2012. Culturally tailoring patient education and communication skills training to empower Africanâ Americans with diabetes. Transl. Behav. Med. 2: 296 â 308.
dc.identifier.citedreferenceNundy, S., J.J. Dick, M.C. Solomon, et al. 2013. Developing a behavioral model for mobile phoneâ based diabetes interventions. Patient Educ. Couns. 90: 125 â 132.
dc.identifier.citedreferenceNundy, S., C.Y. Lu, P. Hogan, et al. 2014. Using patientâ generated health data from mobile technologies for diabetes selfâ management support: provider perspectives from an academic medical center. J. Diabetes Sci. Technol. 8: 74 â 82.
dc.identifier.citedreferenceGoddu, A.P., T.S. Roberson, K.E. Raffel, et al. 2015. Food Rx: a communityâ university partnership to prescribe healthy eating on the South Side of Chicago. J. Prev. Interv. Community 43: 148 â 162.
dc.identifier.citedreferenceNundy, S., J.J. Dick, A.P. Goddu, et al. 2012. Using mobile health to support the chronic care model: developing an institutional initiative. Int. J. Telemed. Appl. 2012: 871925.
dc.identifier.citedreferencePeek, M.E., M. Ferguson, N. Bergeron, et al. 2014. Integrated communityâ healthcare diabetes interventions to reduce disparities. Curr. Diab. Rep. 14: 467.
dc.identifier.citedreferenceChin, M.H., A.P. Goddu, M.J. Ferguson, et al. 2014. Expanding and sustaining integrated health careâ community efforts to reduce diabetes disparities. Health Promot. Pract. 15: 29S â 39S.
dc.identifier.citedreferenceGoddu, A.P., K.E. Raffel & M.E. Peek. 2015. A story of change: the influence of narrative on Africanâ Americans with diabetes. Patient Educ. Couns. 98: 1017 â 1024.
dc.identifier.citedreferenceNundy, S., A. Mishra, P. Hogan, et al. 2014. How do mobile phone diabetes programs drive behavior change? Evidence from a mixed methods observational cohort study. Diabetes Educ. 40: 806 â 819.
dc.identifier.citedreferenceNundy, S., J.J. Dick, C.H. Chou, et al. 2014. Mobile phone diabetes project led to improved glycemic control and net savings for Chicago plan participants. Health Aff. (Millwood) 33: 265 â 272.
dc.identifier.citedreferenceChin, M.H. & D. Goldmann. 2011. Meaningful disparities reduction through research and translation programs. JAMA 305: 404 â 405.
dc.identifier.citedreferenceLeatherman, S., D. Berwick, D. Iles, et al. 2003. The business case for quality: case studies and an analysis. Health Aff. (Millwood) 22: 17 â 30.
dc.identifier.citedreferenceMarmot, M. & Commission on Social Determinants of Health. 2007. Achieving health equity: from root causes to fair outcomes. Lancet 370: 1153 â 1163.
dc.identifier.citedreferenceKim, K., J.S. Choi, E. Choi, et al. 2016. Effects of communityâ based health worker interventions to improve chronic disease management and care among vulnerable populations: a systematic review. Am. J. Public Health 106: e3â e28.
dc.identifier.citedreferenceGary, T.L., M. Battsâ Turner, L.R. Bone, et al. 2004. A randomized controlled trial of the effects of nurse case manager and community health worker team interventions in urban Africanâ Americans with type 2 diabetes. Control. Clin. Trials 25: 53 â 66.
dc.identifier.citedreferenceGary, T.L., M. Battsâ Turner, H.C. Yeh, et al. 2009. The effects of a nurse case manager and a community health worker team on diabetic control, emergency department visits, and hospitalizations among urban African Americans with type 2 diabetes mellitus: a randomized controlled trial. Arch. Intern. Med. 169: 1788 â 1794.
dc.identifier.citedreferenceGuide to Community Preventive Services. Diabetes prevention: interventions engaging community health workers. Accessed January 10, 2019. https://www.thecommunityguide.org/findings/diabetes-prevention-interventions-engaging-community-health-workers.
dc.identifier.citedreferenceCenters for Disease Control and Prevention. 2018. Centers for Disease Control and Prevention Diabetes Prevention Recognition Program: Standards and Operating Procedures. Accessed January 10, 2019. https://www.cdc.gov/diabetes/prevention/pdf/dprp-standards.pdf.
dc.identifier.citedreferenceCho, Y.M., S. Lee, S.M.S. Islam, et al. 2018. Theories applied to mâ Health interventions for behavior change in lowâ and middleâ income countries: a systematic review. Telemed. J. E Health 24: 727 â 741.
dc.identifier.citedreferenceBennett, G.G., D.M. Steinberg, C. Stoute, et al. 2014. Electronic health (eHealth) interventions for weight management among racial/ethnic minority adults: a systematic review. Obes. Rev. 15 ( Suppl. 4 ): 146 â 158.
dc.identifier.citedreferenceTate, D.F., C.G. Valle, M.M. Crane, et al. 2017. Randomized trial comparing group size of periodic inâ person sessions in a remotely delivered weight loss intervention. Int. J. Behav. Nutr. Phys. Act. 14: 144.
dc.identifier.citedreferencePhelan, S., T. Hagobian, A. Brannen, et al. 2017. Effect of an internetâ based program on weight loss for lowâ income postpartum women: a randomized clinical trial. JAMA 317: 2381 â 2391.
dc.identifier.citedreferenceLudwig, J., L. Sanbonmatsu, L. Gennetian, et al. 2011. Neighborhoods, obesity, and diabetesâ a randomized social experiment. N. Engl. J. Med. 365: 1509 â 1519.
dc.identifier.citedreferenceResnicow, K., T. Baranowski, J.S. Ahluwalia, et al. 1999. Cultural sensitivity in public health: defined and demystified. Ethn. Dis. 9: 10 â 21.
dc.identifier.citedreferenceKreuter, M.W., S.N. Lukwago, R.D. Bucholtz, et al. 2003. Achieving cultural appropriateness in health promotion programs: targeted and tailored approaches. Health Educ. Behav. 30: 133 â 146.
dc.identifier.citedreferenceAllan, D. & D. Cornes. 1998. The impact of management of change projects on practice: a description of the contribution that one educational programme made to the quality of health care. J. Adv. Nurs. 27: 865 â 869.
dc.identifier.citedreferenceShikany, J.M., T.L. Carson, C.M. Hardy, et al. 2018. Assessment of the nutrition environment in rural counties in the Deep South. J. Nutr. Sci. 7: e27.
dc.identifier.citedreferenceArd, J.D., T.L. Carson, J.M. Shikany, et al. 2017. Weight loss and improved metabolic outcomes amongst rural African American women in the Deep South: sixâ month outcomes from a communityâ based randomized trial. J. Intern. Med. 282: 102 â 113.
dc.identifier.citedreferenceMenke, A., S. Casagrande, L. Geiss, et al. 2015. Prevalence of and trends in diabetes among adults in the United States, 1988â 2012. JAMA 314: 1021 â 1029.
dc.identifier.citedreferenceAmerican Diabetes Association. 2015. (2) Classification and diagnosis of diabetes. Diabetes Care 38 (Suppl.): S8 â S16.
dc.identifier.citedreferenceHsu, W.C., M.R. Araneta, A.M. Kanaya, et al. 2015. BMI cut points to identify atâ risk Asian Americans for type 2 diabetes screening. Diabetes Care 38: 150 â 158.
dc.identifier.citedreferenceAraneta, M.R. & E. Barrettâ Connor. 2005. Ethnic differences in visceral adipose tissue and type 2 diabetes: Filipino, Africanâ American, and white women. Obes. Res. 13: 1458 â 1465.
dc.identifier.citedreferenceShah, A.D., N.R. Kandula, F. Lin, et al. 2016. Less favorable body composition and adipokines in South Asians compared with other US ethnic groups: results from the MASALA and MESA studies. Int. J. Obes. (Lond.) 40: 639 â 645.
dc.identifier.citedreferenceKarter, A.J., D. Schillinger, A.S. Adams, et al. 2013. Elevated rates of diabetes in Pacific Islanders and Asian subgroups: the Diabetes Study of Northern California (DISTANCE). Diabetes Care 36: 574 â 579.
dc.identifier.citedreferencePhillips, E.G., M.T. Wells, G. Winston, et al. 2017. Innovative approaches to weight loss in a highâ risk population: the small changes and lasting effects (SCALE) trial. Obesity (Silver Spring) 25: 833 â 841.
dc.identifier.citedreferenceLindberg, N.M., V.J. Stevens, S. Vegaâ Lopez, et al. 2012. A weightâ loss intervention program designed for Mexicanâ American women: cultural adaptations and results. J. Immigr. Minor. Health 14: 1030 â 1039.
dc.identifier.citedreferenceJiang, L., S.M. Manson, J. Beals, et al. 2013. Translating the Diabetes Prevention Program into American Indian and Alaska Native communities: results from the Special Diabetes Program for Indians Diabetes Prevention demonstration project. Diabetes Care 36: 2027 â 2034.
dc.identifier.citedreferenceJiang, L., A. Johnson, K. Pratte, et al. 2018. Longâ term Outcomes of Lifestyle Intervention to Prevent Diabetes in American Indian and Alaska Native Communities: the Special Diabetes Program for Indians Diabetes Prevention Program. Diabetes Care 41: 1462 â 1470.
dc.identifier.citedreferenceLewis, T.T., H.M. Kravitz, I. Janssen, et al. 2011. Selfâ reported experiences of discrimination and visceral fat in middleâ aged Africanâ American and Caucasian women. Am. J. Epidemiol. 173: 1223 â 1231.
dc.identifier.citedreferenceAndersohn, F., R. Schade, S. Suissa, et al. 2009. Longâ term use of antidepressants for depressive disorders and the risk of diabetes mellitus. Am. J. Psychiatry 166: 591 â 598.
dc.identifier.citedreferenceWhitaker, K.M., S.A. Eversonâ Rose, J.S. Pankow, et al. 2017. Experiences of discrimination and incident type 2 diabetes mellitus: the Multiâ Ethnic Study of Atherosclerosis (MESA). Am. J. Epidemiol. 186: 445 â 455.
dc.identifier.citedreferenceRosengren, A., S. Hawken, S. Ounpuu, et al. 2004. Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): caseâ control study. Lancet 364: 953 â 962.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
nyas14270_am.pdf
Size:
993.9KB
Format:
PDF
View/Open
Name:
nyas14270.pdf
Size:
788.4KB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.