Stressors May Compromise Medication Adherence Among Adults With Diabetes and Low Socioeconomic Status

Abstract

Studies examining the impact of stressors on diabetes self-care have been limited by focusing on a single stressor or have been largely qualitative. Therefore, we assessed the stressors experienced by a high-risk population with type 2 diabetes, and tested whether having more stressors was associated with less adherence to multiple self-care behaviors. Participants were recruited from a Federally Qualified Health Center and 192 completed a stressors checklist. Experiencing more stressors was associated with less adherence to diet recommendations and medications among participants who were trying to be adherent, but was not associated with adherence to other self-care behaviors. Because having more stressors was also associated with more depressive symptoms, we further adjusted for depressive symptoms; stressors remained associated with less adherence to medications, but not to diet recommendations. For adults engaged in adherence, experiencing numerous chronic stressors presents barriers to adherence that are distinct from associated depressive symptoms.

Stress, depression and medication nonadherence in diabetes: test of the exacerbating and buffering effects of family support

“…Participants are asked “In the past year (12 months), have any of the following family issues been stressful for you?” with 1=yes and 0=no as response options. Example items include “lack of affordable local transport for my family or myself” and “living in an unsafe neighborhood.” The TAPS score is calculated by summing the “yes” responses across items for a possible range of 0–20 (Osborn et al, 2014). Although the checklist nature of the TAPS precludes examination of internal consistency reliability, the stressors most commonly reported on the TAPS have been similar across samples of patients from FQHCs (Rothberg et al, 2011; Welch et al, 2011).…”

“…Although the checklist nature of the TAPS precludes examination of internal consistency reliability, the stressors most commonly reported on the TAPS have been similar across samples of patients from FQHCs (Rothberg et al, 2011; Welch et al, 2011). This instrument was developed based on extensive input from healthcare providers and diabetes educators who treat patients at FQHCs (Osborn et al, 2014), enhancing its content and face validity.…”

“…Stressors and depressive symptoms are related (Fisher et al, 2001; Naranjo et al, 2011) but independent (Osborn et al, 2014) predictors of medication nonadherence (Billimek & Sorkin, 2012a, 2012b; DiMatteo et al, 2000; Gonzalez et al, 2007; Ngo-Metzger et al, 2012; Osborn et al, 2014) which disproportionately affect minorities and socioeconomically disadvantaged patients (Fisher et al, 2001; Jeon et al, 2009; Jiang et al, 2008; Mendenhall et al, 2012; Spencer et al, 2006). However, not all patients who experience these overlapping vulnerabilities are suboptimally adherent.…”

A dyadic multiple mediation model of patient and spouse stressors predicting patient dietary and exercise adherence via depression symptoms and diabetes self-efficacy

“…Other studies, however, have not found associations between stress and adherence (for a review see Morris et al, 2011). Finally, a recent study found that an accumulation of multiple stressors was associated with dietary adherence, but this relationship became non-significant when they controlled for depression (Osborn et al, 2014). …”

Measuring insulin adherence among adults with type 2 diabetes

“…Certain populations have higher rates of non-adherence to diabetes treatment, including racial/ethnic minorities (Osborn, Cavanaugh, et al, 2011), populations with low socioeconomic status (SES; defined as having a limited income, education, or lack of health insurance), and/or persons with more social stressors (Osborn et al, 2014), limited health literacy (Osborn, Cavanaugh, et al, 2011), and depression (Gonzalez et al, 2007; Osborn, Patel, et al, 2011). Factors associated with non-adherence to insulin, specifically, include older age (Egede et al, 2011), being female (Egede et al, 2011; Peyrot et al, 2010), being a racial/ethnic minority (Cramer et al, 2005), having low SES and a T2DM diagnosis (versus type 1 diabetes) (Peyrot et al, 2010), among other factors (Davies et al, 2013).…”