The purpose of this study is to examine the association of individual, community, and health system factors on quality of life among inner-city African Americans with type 2 diabetes.
Methods
Primary data from a cross-sectional study with a community sample of 241 inner-city African Americans with type 2 diabetes were analyzed. Paper-based surveys were administered in which the SF-12 was used to capture the physical component (PCS) and mental component (MCS) of quality of life. Four regression approaches (sequential, stepwise with backward and forward selection, and all possible subsets regression) were used to examine the influence of individual, community, and health system factors on PCS and MCS after adjusting for relevant covariates using a conceptual framework.
Results
In fully adjusted models, having less than a high school education and having major depression were associated with lower quality-of-life scores for MCS across all 4 regression approaches. Being employed was positively associated with better quality-of-life scores for PCS across all 4 regression approaches. PCS was higher across all 4 regression approaches for those reporting a history of trauma. At the health systems level, usual source of care was associated with better PCS across 3 regression approaches.
Conclusions
These results highlight key factors that influence quality of life among inner-city African Americans with type 2 diabetes that could be targets for interventions in this population. However, additional research is needed to understand existing pathways that may be driving many of these relationships.
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References
1.
RoglicG. WHO Global report on diabetes: a summary. Int J Non Commun Dis. 2016;1(1):3.
2.
Centers for Disease Control and Prevention, US Department of Health and Human Services. National Diabetes Statistics Report, 2020. 2020.
3.
CannonAHandelsmanYHeileMShannonM. Burden of illness in type 2 diabetes mellitus. J Manag Care Spec Pharm. 2018;24(9-a suppl):S5-S13. doi:10.18553/jmcp.2018.24.9-a.s5
4.
BommerCHeesemannESagalovaV, et al. The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study. Lancet Diabetes Endocrinol. 2017;5(6):423-430. doi:10.1016/S2213-8587(17)30097-9
5.
BishuKGGebregziabherMDismukeCE, et al. Quantifying the incremental and aggregate cost of missed workdays in adults with diabetes. J Gen Intern Med. 2015;30(12):1773-1779. doi:10.1007/s11606-015-3338-y
6.
RubinRRPeyrotM. Quality of life and diabetes. Diabetes Metab Res Rev. 1999;15(3):205-218. doi:10.1002/(sici)1520-7560(1999 05/06)15:3<205::aid-dmrr29>3.0.co;2-o
7.
CampbellJABishuKGWalkerRJ, et al. Trends of medical expenditures and quality of life in US adults with diabetes: the medical expenditure panel survey, 2002-2011. Health Qual Life Outcomes. 2017;15(1):70. doi:10.1186/s12955-017-0651-7
8.
GlasgowREToobertDJGilletteCD. Psychosocial barriers to diabetes self-management and quality of life. Diabetes Spectr. 2001;14(1):33-41.
9.
CochranJConnVS. Meta-analysis of quality of life outcomes following diabetes self-management training. Diabetes Educ. 2008;34(5):815-823. doi:10.1177/0145721708323640
10.
American Diabetes Association. 5. Facilitating behavior change and well-being to improve health outcomes: standards of medical care in diabetes—2020. Diabetes Care. 43(suppl 1):S48-S65.
11.
CunninghamATCrittendonDRWhiteN, et al. The effect of diabetes self-management education on HbA1c and quality of life in African-Americans: a systematic review and meta-analysis. BMC Health Serv Res. 2018;18(1):367. doi:10.1186/s12913-018-3186-7
12.
GloverCMWangYFogelfeldL, et al. Stress and other determinants of diabetes-specific quality of life in low-income African Americans with uncontrolled type 2 diabetes mellitus. J Health Care Poor Underserved. 2016;27(3):1345-1356. doi:10.1353/hpu.2016.0142
13.
DawsonAZWalkerRJCampbellJA, et al. Effect of perceived racial discrimination on self-care behaviors, glycemic control, and quality of life in adults with type 2 diabetes. Endocrine. 2015;49(2):422-428. doi:10.1007/s12020-014-0482-9
14.
AchukoOWalkerRJCampbellJA, et al. Pathways between discrimination and quality of life in patients with type 2 diabetes. Diabetes Technol Ther. 2016;18(3):151-158. doi:10.1089/dia.2015.0305
15.
EgedeLEEllisC. The effects of depression on diabetes knowledge, diabetes self-management, and perceived control in indigent patients with type 2 diabetes. Diabetes Technol Ther. 2008;10(3):213-219. doi:10.1089/dia.2007.0278
16.
Diez RouxAV. Neighborhoods and health: what do we know? What should we do?Am J Public Health. 2016;106(3):430-431. doi:10.2105/AJPH.2016.303064
17.
CampbellJAYanAWalkerRE, et al. Relative contribution of individual, community, and health system factors on glycemic control among inner-city African Americans with type 2 diabetes. J Racial Ethn Health Disparities. doi:10.1007/s40615-020-00795-7
18.
TungELChinMH. Demographic influences and health disparities in adults with diabetes. In: DelamaterAMMarreroDG, eds. Behavioral Diabetes. Springer; 2020:441-461.
19.
HoogendoornCJShapiraARoyJ F, et al. Diabetes distress and quality of life in adults with diabetes. In: DelamaterAMMarreroDG, eds. Behavioral Diabetes. Springer; 2020:303-328.
20.
Hill-BriggsFGaryTLHillMN, et al. Health-related quality of life in urban African Americans with type 2 diabetes. J Gen Intern Med. 2002;17(6):412-419.
21.
CampbellJAEgedeLE. Individual-, community-, and health system-level barriers to optimal type 2 diabetes care for inner-city African Americans: an integrative review and model development. Diabetes Educ. 2020;46(1):11-27. doi:10.1177/0145721719889338
Centers for Disease Control and Prevention, US Department of Health and Human Services. Behavioral Risk Factor Surveillance System Questionnaire. 2014.
24.
UnderwoodLGTeresiJA. The daily spiritual experience scale: development, theoretical description, reliability, exploratory factor analysis, and preliminary construct validity using health-related data. Ann Behav Med. 2002;24(1):22-33.
25.
WamalaSPLynchJKaplanGAWomen’s exposure to early and later life socioeconomic disadvantage and coronary heart disease risk: the Stockholm Female Coronary Risk Study. Int J Epidemiol. 2001;30(2):275-284.
26.
CunninghamWEAndersenRMKatzMH, et al. The impact of competing subsistence needs and barriers on access to medical care for persons with human immunodeficiency virus receiving care in the United States. Med Care. 1999;37:1270-1281.
27.
Centers for Disease Control and Prevention, US Department of Health and Human Services. National Health and Nutrition Examination Survey, 2009-2010 Dietary Screener. 2014.
28.
BoothM. Assessment of physical activity: an international perspective. Res Q Exerc Sport. 2000;71(suppl 2):114-120.
29.
BrooksCMRichardsJMKohlerCL, et al. Assessing adherence to asthma medication and inhaler regimens: a psychometric analysis of adult self-report scales. Med Care. 1994;32:298-307.
30.
BushKKivlahanDRMcDonellMB, et al. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Arch Intern Med. 1998;158(16):1789-1795.
31.
StantonALKirkSBCameronCL, et al. Coping through emotional approach: scale construction and validation. J Pers Soc Psychol. 2000;78(6):1150.
32.
KesslerRCAndrewsGColpeLJ, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959-976.
33.
KroenkeKSpitzerRLWilliamsJB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9): 606-613.
34.
WagnildGMYoungH. Development and psychometric evaluation of the resilience scale. J Nurs Meas. 1993;1(2):165-178.
35.
WallhagenMILacsonM. Perceived control and psychosocial/physiological functioning in African American elders with type 2 diabetes. Diabetes Educ. 1999;25(4):568-575.
36.
AndreouEAlexopoulosECLionisC, et al. Perceived stress scale: reliability and validity study in Greece. Int J Environ Res Public Health. 2011;8(8):3287-3298.
37.
FelittiVJAndaRFNordenbergD, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 2019;56(6):774-786.
38.
BickelGNordMPriceC, et al. Guide to Measuring Household Food Security. Alexandria Department of Agriculture Food and Nutrition Service; 2000.
39.
EcheverriaSEDiez-RouxAVLinkBG. Reliability of self-reported neighborhood characteristics. J Urban Health. 2004;81(4):682-701.
40.
MoffetHHAdlerNSchillingerD, et al. Cohort profile: the diabetes study of Northern California (DISTANCE)—objectives and design of a survey follow-up study of social health disparities in a managed care population. Int J Epidemiol. 2009;38(1):38-47.
41.
SherbourneCDStewartAL. The MOS social support survey. Soc Sci Med. 1991;32(6):705-714.
42.
Centers for Disease Control and Prevention. National Health Interview Survey, 2017. www.cdc.gov/nchs/hdi.htm
43.
EgedeLEEllisC. Development and testing of the multidimensional trust in health care systems scale. J Gen Intern Med. 2008;23(6):808.
WangKChenZ. Stepwise regression and all possible subsets regression in education. Electronic International Journal of Education, Arts, and Science (EIJEAS). 2016; 2.
46.
BendelRBAfifiAA. Comparison of stopping rules in forward “stepwise” regression. J Am Stat Assoc. 1977;72(357):46-53.
47.
GreenlandSMickeyRM. Re: “The impact of confounder selection criteria on effect estimation.” Am J Epidemiol. 1989;130(5): 1066. doi:10.1093/oxfordjournals.aje.a115409
48.
HosmerDWLemeshowS. Applied Logistic Regression. John Wiley & Sons; 2000.
49.
WhittinghamMJStephensPABradburyRB, et al. Why do we still use stepwise modelling in ecology and behaviour?J Anim Ecol. 2006;75(5):1182-1189.
GoldneyRDPhillipsPJFisherLJ, et al. Diabetes, depression, and quality of life: a population study. Diabetes Care. 2004; 27(5):1066-1070. doi:10.2337/diacare.27.5.1066
52.
LewkoJMisiakB. Relationships between quality of life, anxiety, depression and diabetes. Ann Depress Anxiety. 2015;2(1):1040.
53.
BradshawBGRichardsonGEKumpferK, et al. Determining the efficacy of a resiliency training approach in adults with type 2 diabetes. Diabetes Educ. 2007;33(4):650-659.
54.
DeNiscoS. Exploring the relationship between resilience and diabetes outcomes in African Americans. J Am Acad Nurse Pract. 2011;23(11):602-610. doi:10.1111/j.1745-7599.2011.00648.x
55.
SteinhardtMAMamerowMMBrownSA, et al. A resilience intervention in African American adults with type 2 diabetes: a pilot study of efficacy. Diabetes Educ. 2009;35(2):274-284. doi:10.1177/0145721708329698
56.
BretonMCGuénetteLAmicheMA, et al. Burden of diabetes on the ability to work: a systematic review. Diabetes Care. 2013;36(3):740-749. doi:10.2337/dc12-0354
57.
CampbellJAWalkerRJEgedeLE. Associations between adverse childhood experiences, high-risk behaviors, and morbidity in adulthood. Am J Prev Med. 2016;50(3):344-352. doi:10.1016/j.amepre.2015.07.022
58.
CampbellJAWalkerRJSmallsBL, et al. Glucose control in diabetes: the impact of racial differences on monitoring and outcomes. Endocrine. 2012;42(3):471-482. doi:10.1007/s12020-012-9744-6
59.
WalkerRJSmallsBLBonilhaHS, et al. Behavioral interventions to improve glycemic control in African Americans with type 2 diabetes: a systematic review. Ethn Dis. 2013;23(4):401-408.
60.
WalkerRJSmallsBLCampbellJA, et al. Impact of social determinants of health on outcomes for type 2 diabetes: a systematic review. Endocrine. 2014;47(1):29-48. doi:10.1007/s12020-014-0195-0
