Date Presented 4/20/2018
Lower activity and participation levels in daily occupations contribute to overly high health care utilization (HCU) in adults with Type 2 diabetes mellitus (T2DM). Adults with T2DM who are younger, are a member of a minority group, and have many comorbidities are also at increased risk for higher HCU.
Primary Author and Speaker: Matt P. Malcolm
Additional Authors and Speakers: Arlene A. Schmid, Laura A. Grimm, Tara C. Klinedinst, Karen E. Atler
PURPOSE AND BACKGROUND: The purpose of this study was to determine how activity and participation levels in daily occupations relate to blood glucose (A1c) management and health care utilization (HCU) in adults with Type 2 diabetes mellitus (T2DM). A 2013 American Diabetes Association report indicated that people with diabetes annually spend 2.3 times more on HCU than people without diabetes. Much emphasis has been placed on improving patients’ ability to self-manage blood glucose with the hope of reducing HCU. However, recent research indicates that the long-standing focus on diet, exercise, and medication self-management does not facilitate sustainable lifestyle changes to normalize A1c and reduce high HCU.
METHOD: For this cross-sectional study of people with T2DM and low socioeconomic status (SES), 93 participants were recruited from a large primary care center who met the following inclusion criteria: T2DM diagnosis, age >17 yr, and literate. Following consent, participants completed the following activity and participation questionnaires, administered at the primary care center by an occupational therapist: International Physical Activity Questionnaire (IPAQ), Michigan Diabetes Knowledge Test (DKT), Frenchay Activities Index (FAI), and Community Integration Questionnaire (CIQ). Demographic (age, gender, race and ethnicity, comorbidities) and HCU (number of emergency department [ED] visits, hospital nights, doctor visits, and medications) data were also collected.
We conducted means comparisons (analyses of variance or chi-square tests) of A1c category across each demographic, HCU, and activity and participation independent variable (IV). Multivariate linear regression determined how these IVs predicted A1c value. We conducted means comparisons of the same IVs across dependent variables of having an ED visit or hospitalization in the past 6 mo. Separate multivariate linear regressions determined how these IVs predicted the number of ED visits and hospital nights.
RESULTS: Participants were 48 women and 45 men (M age = 58.6; 38% minority; M comorbidities = 3.1). More minorities had A1c values in the diabetic range than nonminorities (p = .04). The regression was not significant for predicting A1c values. Those who visited the ED (vs. those who did not) had lower age (M = 53.3 vs. 62.7, p < .01), more comorbidities (M = 3.7 vs. 2.7, p = .01), more doctor visits (M = 7.2 vs. 4.1, p < .01), and lower FAI scores (M = 25.7 vs. 29.7, p = .02). Younger age, being a minority, more comorbidities, more hospital nights, higher DKT score, and higher CIQ home score significantly predicted more ED visits. Participants with a hospitalization (vs. those without) had lower age (M = 51.9 vs. 61.0, p < .01), more comorbidities (M = 4.4 vs. 2.7, p < .01), more doctor visits (M = 8.4 vs. 4.4, p < .01), more ED visits (M = 3.8 vs. 0.5, p < .01), more sedentary time (IPAQ; M = 570.0 vs. 329.1 min/wk, p = .004), and lower FAI scores (M = 23.7 vs. 29.5, p < .01). Younger age, more comorbidities, more ED visits, and more sedentary time significantly predicted more hospital nights.
CONCLUSION: People with T2DM and lower SES are at increased risk for higher ED and hospital utilization if they are younger, are a minority, have many comorbidities, and engage less in domestic, leisure, work, and outside-the-home occupations.
IMPACT STATEMENT: These findings are salient to occupational therapy because they demonstrate a link between lower activity and participation and higher HCU for people with T2DM. Impaired activity and participation levels could be critical research and intervention targets for occupational therapy scholars and practitioners.
References
American Diabetes Association. (2013). Economic costs of diabetes in the US in 2012. Diabetes Care, 36, 1033–1046. https://doi.org/10.2337/dc12-2625
Baptista, D. R., Wiens, A., Pontarolo, R., Regis, L., Reis, W. C. T., & Correr, C. J. (2016). The chronic care model for Type 2 diabetes: A systematic review. Diabetology and Metabolic Syndrome, 8, 7. https://doi.org/10.1186/s13098-015-0119-z
Khunti, K., Gray, L. J., Skinner, T., Carey, M. E., Realf, K., Dallosso, H., . . . Davies, M. J. (2012). Effectiveness of a diabetes education and self management programme (DESMOND) for people with newly diagnosed Type 2 diabetes mellitus: Three year follow-up of a cluster randomised controlled trial in primary care. BMJ, 344, e2333. https://doi.org/10.1136/bmj.e2333