139CLINICAL DIABETES • Volume 29, Number 4, 2011 B R I D G E S T O E X C E L L E N C E Impact of Activity Participation and Depression on Glycemic Control in Older Adults With Diabetes: Glycemic Control in Nursing Homes Julie L. Bellissimo, OMS IV, BS, Rachel M. Holt, DO, Stephanie M. Maus, OMS IV, BS, Tracy L. Marx, DO, Frank L. Schwartz, MD, and Jay H. Shubrook, DO I n the United States, 23.1% of adults ≥ 60 years of age have diabetes.1 This population is also burdened with an increased cumula- tive risk of multiple complications.2 The risk of these complications may be reduced with a reduction in A1C level.3 However, the risks of intensive glycemic control, such as hypogly- cemia, may outweigh the benefits in elderly patients with diabetes.2 Glycemic control in this population with diabetes is often complicated by the presence of comorbidities and a potential inabil- ity to adhere to treatment regimens.4 According to Ciechanowski et al.,5 “diabetes is considered to be the most psychologically and behav- iorally demanding of the chronic medical illnesses.” Typically, 95% of diabetes management is per- formed by patients. As patients age, cognitive dysfunction, functional disabilities, polypharmacy, and depression all may prevent them from adhering to treatment plans.4 A diagnosis of depression in the elderly may decrease adherence to exercise, diet, and medication regimens.5 In a study by Rush et al.,6 people with diabetes and depression were less likely to achieve their blood glucose goals. Thus, a diagnosis of depression appears to negatively affect glycemic control.5–9 In elderly adults with diabetes, depression can reduce quality of life, increase health care expenditures, and decrease adherence to medica- tion and diet regimens.4 Katon et al.10 found there to be a significantly higher mortality among depressed patients with type 2 diabetes than among nondepressed patients. Furthermore, Rubin and Peyrot11 have stated that “psychosocial variables [such as depression] are often stronger predictors of medi- cal outcome such as hospitalization and mortality than are physiologic and metabolic measures [such as the presence of complications, BMI, and A1C].” Elderly adults with diabetes have double the normal risk for depression.4 There is evidence that, at admittance to extended care facilities, the incidence of depres- sion increases.12 In a pilot study by Holt et al.,13 52% of people with diabetes in extended care facilities also suffered from depression. This emphasizes the importance of diag- nosis and treatment of depression in elderly people with diabetes, espe- cially in light of the increased risk. The American Diabetes Association recommends that psy- chosocial assessment be a routine component of the medical manage- ment of people with diabetes and that a change in the medical regimen should prompt screening for psycho- social problems such as depression.14 Symptoms of depression in older adults can be reduced effectively with pharmacological and psycho- logical treatments. Antidepressant medications are the most common treatment for depression in older adults.2 This trend is also seen in extended-care residents with diabetes. Holt et al.13 found that 58% of residents with diabetes received pharmacological treatment for depression. Although antidepressant medi- cations may reduce depressive symptoms in elderly adults, it has been suggested that this may not be an ideal treatment for depressed resi- dents.15 The frailty of this population may make them more susceptible to the side effects of these medica- tions.15 Thapa et al.16 found that nursing home residents who began therapy with tricyclic antidepres- sants had a rate of falls twice that of nonusers. Furthermore, residents started on selective serotonin- reuptake inhibitors had a rate of falls 80% higher than nonusers.16 Therefore, in addition to pharmaco- logical and psychosocial treatment, it is also important to consider the benefits of behavioral interventions in the treatment of depression. Behavioral intervention is based on a theory that depressed individu- als are unable to perceive positivity in their environment. The treatment focuses on increasing the number of positive activities. Increasing 140 Volume 29, Number 4, 2011 • CLINICAL DIABETES B R I D G E S T O E X C E L L E N C E positive events as a means of behav- ioral intervention has been shown to improve symptoms of depression in elderly adults.12 Furthermore, Meeks et al.12 found that, as nursing home residents increased their participa- tion in activities, they experienced a clinical reduction in the symptoms of depression. However, this study is not specific to older adults with diabetes. Many extended-care facili- ties recognize the impact activity participation can have on the health of their residents and offer a variety of activities. However, as Meeks et al. summarized, “general one-size- fits-all programming that is often found in nursing homes may not be an effective means of engaging the majority of residents in mean- ingful activities to improve their quality of life. Instead, efforts to tailor programming and especially to tailor individual interventions for depressed residents may be needed.”12 The purpose of this study was to determine whether residents of extended-care facilities with diabetes and a concurrent diag- nosis of depression have poorer glycemic control than those who are not depressed. This study also investigated the impact that activ- ity participation has on glycemic control. Research Design and Methods This project was approved by the Ohio University Institutional Review Board, and a letter of agreement was obtained from each of the participat- ing extended-care facilities. Site recruitment The investigators contacted extended- care facilities throughout Ohio and West Virginia. Facilities that expressed interest in participating in the study completed an agreement to be enrolled. Once completed, each facility’s director of nursing was sent all of the documents used for the study. These included a nursing home diabetes care protocol, a hypoglyce- mia/hyperglycemia reporting form, a nutritional reporting form, and a chart face sheet. These documents were reviewed with each director of nursing to clarify any questions. Table 1. Abstracted Data and Classification of Activities Category Parameter Collected General Age, type of diabetes Lab tests and general care Number of fingersticks per day, incidence of hypoglycemia and hyperglycemia per month, percent- age of target glucose levels reached per month, A1C goal reached (yes/no), lowest A1C reached in past month, number of A1C measurements per year, electrocardiogram in past year (yes/no), blood pres- sure recorded (yes/no), blood pressure at goal (yes/no), lipids checked annually (yes/no), lipids at goal (yes/no), microalbumin checked in past year (yes/no), weight checked monthly (yes/no) Exams and consultations Foot exam in past year (yes/no), podiatrist consultation (yes/no), annual eye exam (yes/no), psycholo- gist consultation (yes/no) Medications and vaccinations Flu and/or pneumococcal vaccine (yes/no), ACE inhibitor/angiotensin II receptor blocker (yes/no), aspirin (yes/no), oral antidiabetic medications (yes/no), insulin (yes/no), analog insulin (yes/no), non- analog insulin (yes/no), sliding-scale insulin regimen (yes/no), all antidiabetic medications, treatment for depression Other Hypo- and hyperglycemic protocols, physician type, diagnosis of depression Skills activities Arts and crafts, cooking group, current events, educational speakers, gardening, homemaking, intel- lectual residents’ council, music, reading/writing, sensory awareness/stimulation, word games/puzzles Spiritual activities Bible study, church-related spiritual activity Social activities 1-on-1 visits, beauty shop, bingo, card games, family visits, movies, outdoors, parties, patio chats, rem- iniscing, smoking, snack-and-chat, socializing, talking/phone, theater group, trip/shopping, visitors Physical activities Exercise/sports, parachute, physical therapy, walking Other activities Bird watching/feeding, hand rub/lotion, therapy, helping others, nail painting, people-watching, pet therapy, spa day, special programs/TV, van ride 141CLINICAL DIABETES • Volume 29, Number 4, 2011 B R I D G E S T O E X C E L L E N C E Patient inclusion and exclusion criteria The facility residents had to have had diabetes for at least 1 year and to have been a resident of the facility for at least 3 months to be included in the study. Residents with type 1 or type 2 diabetes were included regardless of their treatment plans. A diagnosis of depression was based on a docu- mented diagnosis in residents’ charts. Chart review/data abstraction Each director of nursing provided a list of eligible residents. All eligible skilled-nursing and assisted-living residents had their charts reviewed. A key code was developed for the facili- ties and qualifying residents. The key code was documented on a Microsoft Excel spreadsheet and kept on a sepa- rate password-protected computer. Activity participation was recorded as the number of activities each resident attended in a 1-month period and was then converted into hours/month. Unless otherwise spec- ified by the facility, each activity was considered to take 30 minutes. This assigned duration was used because most of the activities at the facili- ties with recorded times were 20–30 minutes in length. It is possible that some activities may have taken more or less time, thus skewing the results. At some facilities, records were only received for a period of 1 week. When this occurred, the hours/ month estimate was extrapolated from residents’ weekly activity participation. Activity participation was recorded in five separate categories: spiritual, skills, physical, social, and other (Table 1). Any recorded religious activity was considered a spiritual activity. An activity was categorized as a skills activity if it required cognitive ability. A social activity was any non-skills or non-physical activity that involved interaction with other residents, family members, nurses, or staff. If an activity did not fit into any of the other four categories, it was classified as “other.” Additionally, baseline information concerning care of each resident (Table 1) and demographic information, includ- ing sex, race, and age, were also obtained from eligible charts. Statistical analysis Statistical analysis was completed using SPSS version 17 (SPSS Inc., Chicago, Ill.). Pearson χ2 was used to test the significance between A1C goal and diagnosis of depression. The t tests were used to assess whether there was a difference in the subjects’ percentage of glucose control for those with or without a diagnosis of depression. The t tests were also run to determine if there was a statistical difference between the mean total activity of those residents who met A1C goals and those who did not and for activity subcategories. Levene’s test of equality of variances and the t test for equality of means were also used to analyze the data. Statistical significance was determined at P ≤ 0.05. Study Results Descriptive data A total of 187 charts were reviewed, including 49 males (26%) and 138 females (74%). The majority (177) of subjects were white (94.7%). Subjects’ ages ranged from 49 to 97 years, with a mean of 79.7 years. Most subjects (174) had a diagnosis of type 2 dia- betes (93%), whereas only eight (4%) were diagnosed with type 1 diabetes, and five (3%) had an unspecified dia- betes diagnosis. Eighty-five subjects (46%) had a diagnosis of depression, and of those, 70 residents (37%) received pharmacological treatment for depression (Table 2). Glucose control Blood glucose was monitored for 167 subjects (89%). The number of fingersticks per day ranged from 0 to 6. Nineteen subjects (10%) received one fingerstick daily, 109 subjects (58%) received two to four fingersticks daily, and two subjects (1%) received six fingersticks daily. Thirty-five subjects (19%) received less than one fingerstick daily. For those who had their glucose monitored, 45 subjects (27%) had a total of 192 hypoglycemic episodes, 163 of which were considered mild (blood glucose 50–69 mg/dl) and 29 of which were severe (blood glu- cose < 50 mg/dl). The range of these events was 14–68 mg/dl. Twelve residents had severe hypoglycemic reports, and 33 reported mild hypo- glycemic events. Forty-one of the residents who experienced a hypoglycemic epi- sode were on insulin (91%), whereas the other four residents (9%) were not on insulin. Furthermore, 26 of the residents who experienced a hypoglycemic episode did not have a diagnosis of depression, whereas 19 were depressed. The mean low- est A1C for those who experienced a hypoglycemic event was 6.6%, whereas for those who did not expe- rience a hypoglycemic event, it was 6.8%. Only 59 subjects (32%) had a written hypoglycemic protocol in their orders. However, 117 subjects (63%) had a hyperglycemic proto- col (Table 2). Ninety-one subjects (49%) had recorded hyperglycemic incidences. For this study, we used a liberal- ized blood glucose goal of 70–250 mg/dl. Most of the glucose read- ings (88%) were at this goal, with a range of 20–100% for a 1-month period. One hundred and thirty-nine subjects (74%) met the liberalized extended-care A1C goal of < 8.0%, with a lowest A1C mean of 6.75% for residents without depression and 6.73% for those with depression. There was no significant difference between the mean percentage of glu- 142 Volume 29, Number 4, 2011 • CLINICAL DIABETES B R I D G E S T O E X C E L L E N C E cose control by 1) fingerstick glucose readings (t df = 164 = −1.500, P = 0.138, 95% CI −9.06 to 1.239) or 2) A1C goal achievement (χ2 df = 1 = 0.266, P = 0.606, odds ratio = 0.799, 95% CI 0.340–1.876) in those with or without depression. Activity participation Total activity participation ranged from 0 to 235 hours/month. Subjects participated in a mean of 64 hours of activity in 1 month. Subjects partici- pated in more social activities than any other activity subcategory, with an average of 28.7 hours/month. Skill activities had the second-highest par- ticipation at an average of 15.8 hours/ month (range 0–149 hours). Subjects participated in physical activities on average 6.1 hours/month and in spiritual activities 2.1 hours/month. The mean time spent in the “other” subcategory was 15.3 hours/month (Table 3). Subjects who participated in more total activity hours were significantly more likely to achieve A1C goals (t df = 23.52 = −2.995, P < 0.01, 95% CI −30.465 to −5.391). However, no individual activity subcategory was significantly related to A1C level. Furthermore, there was no significant correlation between total activity participation (r = 0, n = 187, P = 0.994), or any of the subcategory activities and percentage of blood glucose at goal. Finally, there was no significant relationship between the total number of activity hours or any of the activity subcategories and hypoglycemic events. Discussion and Conclusions In this study, a diagnosis of depres- sion did not appear to result in poorer glucose control for adults with diabetes in extended-care facilities. Previous research has shown that a diagnosis of depression is associ- ated with poorer glucose control.5–7,9 However, these studies did not explain the mechanisms through which depression caused an increase in A1C. Depression is associated with decreased compliance with medica- tions, decreased physical activity, and increased inflammatory cyto- kines, which interfere with insulin action and result in hyperglycemia. Medication compliance was not an issue in these elderly adults, who depended on the care of nurses and staff at the facilities. Although a diagnosis of depres- sion did not affect A1C levels, residents who participated in more hours of activity were more likely to be at A1C target levels. If it is assumed that the hours of activity participation recorded is representa- tive of patients’ activity participation in previous months, it can be concluded that subjects who par- ticipated in more hours of activity were more likely to obtain an A1C level at goal. Recognizing that A1C Table 2. Participant and Hypoglycemic/Hyperglycemic Event Data Frequency Percentage (%) Total charts 187 Male 49 26 Female 138 74 Caucasian 177 94.7 Other race 10 5.3 Type 2 diabetes 174 93 Type 1 diabetes 8 4 Unspecified diabetes type 5 3 Diagnosis of depression 85 46 Pharmacological depression treatment 70 37 Residents with at least one blood glucose reading < 70 mg/dl 45 27* Residents with mild hypoglycemia (blood glucose 50–69 mg/dl) 33 20* Residents with severe hypoglycemia (blood glucose < 50 mg/dl) 12 7* Total number of hypoglycemic events/ month 192 — Total number of mild hypoglycemic events/ month 163 — Total number of severe hypoglycemic events/month 29 — Residents with hypoglycemia protocols 59 32* Residents with at least one blood glucose level > 250 mg/dl 91 49* Residents with hyperglycemia protocol 117 63* Residents with an A1C < 8% 139 74* *Percentage of subjects who had their blood glucose monitored. 143CLINICAL DIABETES • Volume 29, Number 4, 2011 B R I D G E S T O E X C E L L E N C E is an estimated average, people who experience hypoglycemic or hyperglycemic episodes may have an acceptable A1C, but still be in poor glycemic control. None of the subcategories of activity had a significant relationship with subjects’ A1C or percentage of blood glucose readings at goal. Recently it was reported that a combination behavioral approach for depression in adults with type 2 diabetes not only was effective in treating depression, but also sig- nificantly reduced A1C levels and fasting glucose levels from baseline to post-treatment and from base- line to the 3-month follow-up.8 Participants in that study engaged in 150 minutes of aerobic activity each week along with cognitive behavioral therapy.8 Although it appears from the study mentioned above on combina- tion therapy that physical activity does have an effect on glucose con- trol, our study suggests there may be a more complex relationship. Because none of the subcategories had any significant relationship with A1C levels at goal, this may imply that participation in any activity, not only physical activity, has positive effects. Our study showed that the quantity of activity participation may be more important than the type of activity. The application of this information may be helpful when nurses and family members encourage residents to participate in facility activities. Because it does not appear to matter what type of activity is involved but rather the quantity of activity in which patients participate, it may be advantageous to encourage residents to participate in activities they enjoy rather than focusing on one specific type of activity. One of the most significant find- ings in our study was the number of subjects in these facilities with hypoglycemic events (blood glucose < 70 mg/dl). Twenty-seven percent of subjects in this study had at least one hypoglycemic event in a 1-month period, and 7% had at least one severe hypoglycemic event. Despite the high incidence and danger of hypoglycemic events, only 33% of subjects had a hypoglycemic proto- col ordered. The results found in this study suggest that hypoglycemic events were not related to the amount or type of activity in which patients participated. However, they sug- gest that all residents with diabetes in extended-care facilities who are on medications that can cause hypoglycemia should have specific hypoglycemia management proto- cols to prevent significant cognitive injury, falls, and rebound hypergly- cemia from inappropriate correction of hypoglycemia. The results of this study are limited by several factors. Primarily, the number and heterogeneity of subjects may not be representative of all extended-care facility residents with diabetes. A larger poll of data may have yielded different relation- ships among depression, amount of activity participation, and glucose control. Most of the facilities had standard activity sheets used to record residents’ activity participa- tion. In the facilities that did not use these sheets, it appeared that either fewer activities were offered or the activities were not recorded. However, even in facilities that used standardized sheets, the recording of activities varied greatly. Some facili- ties had detailed descriptions of each activity, whereas others simply had a checklist. Furthermore, many activities could have fallen into more than one category. For example, garden- ing was considered to be a skills activity. However, if done in a group environment, it could have also been considered a social activity. To address this, the authors developed pre-specified categories for this study (Table 1). Despite these limitations, this study yielded important results that may be used in the future to improve the care of extended-care residents with diabetes. First, the amount of activity in which residents partici- pate may have more impact on their health than the type of activity. Second, a diagnosis of depression was not related to glycemic control in this select population. Finally, this study showed an unacceptable high incidence of hypoglycemic events in this population, and national requirements for standard hypogly- Table 3. Activity Participation Activity Frequency Maximum Participation (hours) Average Participation (hours) Total 187* 235 64.24 Social 174 112 28.73 Skills 173 149 15.82 Other 174 50 15.27 Physical 174 26 6.13 Spiritual 174 17 2.12 *Type of activity was not reported for 13 residents. 144 Volume 29, Number 4, 2011 • CLINICAL DIABETES B R I D G E S T O E X C E L L E N C E cemic protocols for all residents with diabetes should be adopted. ACKNOWLEDGMENTS The authors would like to acknowl- edge the Ohio University Heritage College of Osteopathic Medicine (OUCOM) Research and Scholarly Advancement Fellowship and the Centers for Osteopathic Research and Education research office for fund- ing and specifically Godwin Dogbey, PhD, at OUCOM for statistical support. REFERENCES 1American Diabetes Association: Diabetes statistics [article online]. Available from www.diabetes.org. Accessed 12 June 2009 2California Healthcare Foundation/ American Geriatrics Society Panel on Improving Care for Elders with Diabetes: Guidelines for improving the care of the older person with diabetes mellitus. J Am Geriatr Soc 51:5265–5280, 2003 3Stratton I, Adler A, Neil H, Matthews D, Manley S, Cull C, Hadden D, Turner R, Holman R: Association of glycaemia with macrovascular and microvascular complica- tions of type 2 diabetes (UKPDS 35). BMJ 321:405–412, 2000 4Munshi M: Managing the “geriatric syndrome” in patients with type 2 diabetes. 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J Clin Nurs 17:2524–2530, 2008 10Katon W, Rutter C, Simon G, Lin E, Ludman E, Ciechanowski P, Kinder L, Young B, von Korff M: The association of comorbid depression with mortality in patients with type 2 diabetes. Diabetes Care 28:2668–2672, 2005 11Rubin R, Peyrot M: Quality of life and diabetes. Diabetes Metab Res Rev 15:205–218, 1999 12Meeks S, Young C, Looney S: Activity participation and affect among nursing home residents: support for a behavioral model of depression. Aging Mental Health 11:751–760, 2007 13Holt R, Schwartz F, Shubrook J: Diabetes care in extended-care facilities. Diabetes Care 30:1454–1458, 2007 14American Diabetes Association: Executive summary: standards of medical care in diabetes—2011. Diabetes Care 34 (Suppl. 1):S4–S10, 2011 15Meeks S, Looney S, Van Haitsma K, Ten L: BE-ACTIV: a staff-assisted behavioral intervention for depression in nursing homes. Gerontologist 48:105–114, 2008 16Thapa P, Gideon P, Cost T, Milam A, Ray W: Antidepressants and the risk of falls among nursing home residents. N Engl J Med 339:875–882, 1998 Julie L. Bellissimo, OMS IV, BS, and Stephanie M. Maus, OMS IV, BS, are medical students at Ohio University Heritage College of Osteopathic Medicine (OUCOM) in Athens, Ohio. Rachel M. Holt, DO, is a resident in the Department of Emergency Medicine at Wright State University Boonshoft School of Medicine in Dayton, Ohio. Tracy L. Marx, DO, and Jay H. Shubrook, DO, are associ- ate professors of family medicine in the Department of Family Medicine at OUCOM. Frank L. Schwartz, MD, is a professor of specialty medicine in the Department of Specialty Medicine at OUCOM.