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The Characteristics of Diabetic Residents in European Nursing Homes: Results from the SHELTER Study
JAMDA 16 (2015) 334e340
JAMDA journal homepage: www.jamda.com
Original Study
The Characteristics of Diabetic Residents in European Nursing Homes: Results from the SHELTER Study ska MD, PhD a, *, Eva Topinková MD, PhD b, Piotr Brzyski PhD a, Katarzyna Szczerbin Henriëtte G. van der Roest PhD c, Tomás Richter MD, PhD b, Harriet Finne-Soveri MD, PhD d, Michael D. Denkinger MD e, Jacob Gindin MD f, Graziano Onder MD, PhD g, Roberto Bernabei MD g a Department of Sociology of Medicine, Epidemiology and Preventive Medicine Chair, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland b Department of Geriatrics, 1st Faculty of Medicine, Charles University, Prague, Czech Republic c EMGO Institute for Health and Care Research, Department of General Practice and Elderly Care, VU University Medical Centre, Amsterdam, The Netherlands d Unit for Ageing and Services, National Institute for Health and Welfare, Helsinki, Finland e Agaplesion Bethesda Clinic, Geriatric Centre Ulm/Alb-Donau, University of Ulm, Ulm, Germany f The Centre for Standards in Health and Disability, Research Authority, University of Haifa, Haifa, Israel g Centro Medicina dell’Invecchiamento, Università Cattolica Sacro Cuore, Rome, Italy
a b s t r a c t Keywords: Diabetes mellitus nursing home older adults
Objectives: The objectives of this study were to describe the prevalence of diabetes mellitus (DM) in European nursing homes (NHs), and the health and functional characteristics of diabetic residents (DMR) aged 60 years and older. Design: Between 2009 and 2011, the Services and Health for Elderly in Long TERm care (SHELTER) project, a 12-month prospective cohort study, was conducted to assess NH residents across different health care systems in 7 European countries and Israel. Methods: The study included 59 NHs in 8 countries with a total of 4037 residents living in or admitted to a NH during the 3-month enrollment period. The multidimensional InterRAI instrument for Long-Term Care Facilities (InterRAI-LTCF) was used to assess health and functional status among residents. Descriptive statistics and linear, ordinal, and logistic regression were used to perform the analyses. Results: We found a 21.8% prevalence of DM among NH residents. Residents with DM (DMRs) were significantly younger compared with non-DMRs (82.3, SD 7.7; 84.6, SD 8.4; P < .001). DMRs were more frequently overweight or obese, and presented more often with ischemic heart disease, congestive heart failure, hypertension, and stroke than residents without DM. DMRs also took more drugs, had pressure ulcers (PU) or other wounds more often, and more frequently had urinary incontinence (UI); they also reported worse self-perceived health. DM independently of other factors increased risk of PU occurrence (odds ratio 1.38; 95% confidence interval [CI] 1.02e1.86; P ¼ .036) and decreased probability of higher pain scores (B ¼ 0.28; 95% CI 0.41 to 0.14; P < .001). DM was not associated with ADL dependency, cognitive impairment, and depression in NH residents. Conclusion: Prevalence of DM in European NH residents is comparable to US national NH surveys, and to UK and German NH data based on glucose-level testing. DMRs compared with non-DMRs have more comorbid conditions, and a particularly higher incidence of cardiovascular diseases and obesity, PU, and severe UI. DMRs should be regarded as a specific group of residents who require an interdisciplinary approach in medical and nursing care. Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
KS, ET, HFS, JG, and RB are members of InterRAI. The other authors declare no conflicts of interest. The SHELTER study was funded by the European Union’s Seventh Framework Programme for Research, European Commission Grant 223115. The work of ET and
http://dx.doi.org/10.1016/j.jamda.2014.11.009 1525-8610/Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
TR was partly supported by FP7 European Commission Grant 278803 “The MIDFRAIL Study.” ska, MD, PhD, Jagiellonian * Address correspondence to Katarzyna Szczerbin University Medical College, ul. Kopernika 7a, 31e034 Kraków, Poland. ska). E-mail address: [email protected] (K. Szczerbin
ska et al. / JAMDA 16 (2015) 334e340 K. Szczerbin
According to the International Diabetes Federation (IDF), the prevalence of diabetes mellitus (DM) in European adults aged 20 to 79 years is 8.5% (11.0% in North America).1 It rises with age, reaching the peak in older adults aged 75 to 80.2 The highest prevalence of diabetes was found in nursing home (NH) populations. Studies conducted in the United States among large samples of NH residents showed a prevalence of 33.3% in a general sample of 1,361,406 NH residents,3 with 26% of patients found to be men and 23% women older than 65.4 Another cross-sectional study conducted in 1995 and 2004 found that the increase in prevalence of DM in US NH residents older than 55 years was steeper among men, from 16.9% to 26.4%, than among women, from 16.1% to 22.2%.5 DM thus seems to be an emerging challenge in the NH population. In comparison with the United States, there is definitely less information in published literature about prevalence of DM in European NHs.6 The existing data are based on significantly smaller convenience samples. Strikingly, a very low prevalence of DM was found in one study from France (8.7% in 4896 residents)7 and in 2 British studies (5.8% and 13.0%), depending on the type of long-term care facility (residential homes or NHs; for older people or for mentally ill older adults)8 and study method used (eg, postal survey or measurement of fasting glucose).8,9 Yet, Sinclair et al10 indicated that many cases of DM may remain unrecognized, and studies may underestimate the true prevalence rate in NHs when laboratory measurements of blood glucose are not included in the study protocol. Based on patient file information Sinclair et al10 reported a 12% prevalence of previously diagnosed DM in NH residents. However, as a result of blood glucose measurements taken during the study, another 14.7% of the study population was newly diagnosed with DM. Thus, the overall DM prevalence in Birmingham NHs in the United Kingdom was found to be 26.7%. These findings are supported by another study from Germany reporting 26.2% prevalence of DM in NHs based on glucose-level testing.11 The lack of standard blood glucose measurement in NHs was seen as an indicator of substandard quality and incomplete diagnostics.10 The latest European guidelines therefore recommend routine laboratory screening for DM in NH residents at admission and at 2-year intervals.12 Timely recognition of DM may prevent or slow down potential complications and diabetes-related conditions. Known diagnosis of DM should draw attention to symptoms that are often underreported, undetected, and undertreated in diabetic patients. NH professionals’ awareness of the high prevalence rate of DM in NHs is therefore a key factor that should drive them to perform regular screening for DM in NH residents so as to provide appropriate care, bearing in mind the clinical complexity of diabetic patients. The aim of our study thus was to detect the prevalence of DM in a large sample of European NHs. Further, to describe clinical characteristics of diabetic residents (DMRs) aged 60 years and older based on data collected in 59 NHs in 7 European countries and Israel from the SHELTER study (the Services and Health for Elderly in Long TERm care study) database. The third aim was to compare health and functional status of DMRs and nondiabetic residents (nonDMRs), while focusing on health problems that are typical for patients with DM. Methods The SHELTER study, a project funded by the Seventh Framework Program of the EU, was conducted from 2009 to 2011.13 The sample consisted of 4156 residents in 59 NHs located in 7 European countries (Czech Republic: 10 NHs, England: 9, Finland: 6, France: 4, Germany: 9, Italy: 10, The Netherlands: 4), and Israel: 7 NHs. NHs were selected based on their willingness to participate in the SHELTER study and
335
were not intended to be representative of all NHs in each participating country. Adults residing in participating NHs at the beginning of the study and those admitted in the 3-month enrollment period were assessed. To meet the goal of our current analysis, we excluded NH residents younger than 60 years (n ¼ 96) because of possible differences of characteristics in younger adults with DM. We also excluded residents (n ¼ 23) with missing data about their concomitant diseases (empty checklist of diseases), because it was not clear whether they had DM or not. The final sample was composed of 4037 persons. Residents were invited to take part in the study and were free to decline participation. Ethical approval for the study was obtained in all countries according to local regulations. The interRAI instrument for Long-Term Care Facilities (interRAILTCF) was used. This is a comprehensive standardized instrument to assess care needs, health, and functional status of NH residents. The interRAI-LTCF has been validated in several European countries and has proved to be a reliable instrument.13,14 It contains more than 350 variables, including sociodemographic items, numerous clinical diagnoses, symptoms, geriatric syndromes, care programs, and treatments. A diagnosis of DM and other clinical diagnoses were derived from the interRAI diagnoses section and a list of International Classification of Diseases, Ninth Revision (ICD-9) coded diseases. Several validated scales can be generated from the interRAI-LTCF items. For this study, the 7-point Cognitive Performance Scale (CPS) was used to assess cognitive status.15,16 Intact or nearly intact cognitive function was represented by a CPS score of 0 to 1, moderate impairment by a CPS score of 2 to 3, and severe impairment by a CPS score of 4 to 6. Functional status was represented by the 7-point scale of Activities of Daily Living Hierarchy (ADLh)17 categorizing physical functioning as independent (ADLh ¼ 0e1), moderately dependent (ADLh ¼ 2e3), and severely dependent (ADLh ¼ 4e6). The 7-point Depression Rating Scale (DRS)18 was used to indicate the presence of symptoms of depression (DRS ¼ 3 or more). Pressure ulcer (PU) stage was coded as follows: 0, no PU; 1, any area of persistent skin redness; 2, partial loss of skin layers; 3, deep craters in the skin; 4, breaks in skin exposing muscle or bone; 5, not codeable (eg, necrotic eschar predominant). Pain was coded based on frequency (pain experienced daily vs less than daily or no pain), on intensity (moderate, severe, or unbearable pain vs mild or no pain), and on occurrence of breakthrough pain within the past 3 days (yes vs no). A 5-point Pain Scale presenting level of pain starting from 0 (no pain) through 2 (daily pain) up to 4 (daily excruciating pain) was applied in regression models. The World Health Organization classification based on body mass index (BMI) was used to stratify for nutritional status. Four answers to a question concerning self-perceived health were divided into 3 categories: “excellent” (due to very low number of answers) and “good” were put in one category, and “fair” and “poor” were treated as 2 other separate categories. In line with previous publications, polypharmacy was categorized into 3 groups: nonpolypharmacy (concurrent use of 0e4 drugs), polypharmacy (concurrent use of 5e9 drugs), and excessive polypharmacy (concurrent use of 10 drugs or more).19 Urinary incontinence (UI) was defined as “severe” if the patient was frequently (daily but with some control present) or permanently incontinent (not controlled) or needed bladder catheterization versus “occasionally or infrequently incontinent” (incontinence episodes less than daily or did not occur over past 3 days), or “continent” (no incontinence problem). Bunions, hammertoes, overlapping toes or other structural foot problems, infections, and ulcers were all defined as “any foot problems.” Coding of other variables is described in Table 2 presenting results. Distributions of qualitative variables were described as frequencies (n) and percentages (%), whereas quantitative variables were described as means with SDs if they had normal distribution or as medians and quartiles otherwise. The distributions of categorical
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Table 1 Clinical Characteristics of DMRs and non-DMRs in 59 European Nursing Homes: The SHELTER Study Characteristics of NH Residents
Age, mean (SD) Age, y, % (n) 60e75 76e85 >85 Female gender Self-perceived health, % (n) Excellent and Good Fair Poor Selected diseases, % (n) Coronary heart disease Congestive heart failure Hypertension Stroke/transient ischemic attack Hemiplegia Alzheimer disease Other dementia Urinary tract infection Chronic kidney disease Cancer Chronic obstructive pulmonary disease No. of diseases, mean (SD) No. of drugs, mean (SD) No. of drugs, % (n) 0e4 5e9 10
Diabetic
Nondiabetic
All
21.8% (n ¼ 879)
78.2% (n ¼ 3158)
100.0% (n ¼ 4037)
82.3 ( 7.7)
84.6 ( 8.4)
84.1 ( 8.3)
17.7 40.8 41.4 73.8
13.6 33.6 52.8 73.7
14.5 35.2 50.3 73.7
(156) (359) (364) (649)
(428) (1062) (1668) (2327)
(584) (1421) (2032) (2976)
34.4 (224) 45.1 (294) 20.6 (134)
41.7 (917) 40.1 (882) 18.1 (398)
40.0 (1141) 41.3 (1176) 18.7 (134)
37.0 21.2 40.5 29.4 13.2 17.0 37.8 7.9 4.6 12.5 11.7 4.1 8.2
24.0 17.2 22.7 21.8 10.5 21.2 36.4 6.0 2.8 11.1 9.6 2.5 6.8
26.8 18.1 26.6 23.5 11.1 20.3 36.7 6.4 3.2 11.4 10.1 2.9 7.1
(325) (186) (356) (258) (116) (149) (332) (69) (40) (110) (103) (1.8)* (3.5)
17.0 (145) 49.9 (452) 33.0 (281)
(756) (543) (716) (689) (330) (669) (1145) (188) (90) (352) (304) (1.6) (3.3)
27.9 (855) 50.3 (1540) 21.8 (668)
(1081) (729) (1072) (947) (446) (818) (1477) (257) (130) (462) (40.7) (1.8) (3.6)
n
P
4037 4037
<.001 <.001
4037 2849
.930 .003
4028 4032 4037 4033 4031 4030 4028 4028 4037 4037 4037 4037 3914 3914
<.001 .007 <.001 <.001 .022 .005 .443 .042 .012 .370 .053 <.001 <.001 <.001
36.0 (1408) 39.8 (1557) 24.2 (949)
Bold values are statistically significant P < .05. *Including diabetes mellitus in DMRs.
variables were compared with c2 test. For normally distributed variables, the means were compared between 2 groups with t-test for independent samples, and for other variables, distributions were compared between 2 groups using the Mann-Whitney U test for interval variables and Ko1mogorov-Smirnov test for ordinal ones. Moreover, univariate and multivariate linear, logistic, and ordinal regression models were estimated using the Generalized Estimating Equations procedure, to assess the independent influence of DM on cognitive impairment (CPS), physical disability (ADLh), symptoms of depression (DRS), level of pain (Pain Scale), and PU occurrence. The differences were considered statistically significant if P value was less than .05. The analysis was conducted using IBM SPSS Statistics 21 for Windows (IBM SPSS Statistics, IBM Corporation, Chicago, IL). Results The study sample consisted of 4037 NH residents aged 60 years or older: 879 diabetic (21.8%) and 3158 nondiabetic individuals (78.2%). The findings presented in Table 1 show that DMRs were younger, they more frequently reported worse self-perceived health, used more drugs (one-third of DMRs were on excessive polypharmacy regimen), and suffered from more comorbidities. Cardiovascular diseases, such as coronary heart disease (CHD), congestive heart failure (CHF), hypertension, and stroke, were more frequently present in DMRs. The prevalence of urinary tract infections and chronic kidney disease (CKD) was low in both groups, but significantly higher than in nonDMRs. No significant differences between the prevalence rates of other chronic diseases were found. Not surprisingly, prevalence of BMI values over 25.0 kg/m2 was higher in DMRs. Meanwhile, DMRs suffered less frequently from dehydration, mouth pain, and gum inflammation, and these conditions were rare in both groups of residents (Table 2). Prevalence of PU was higher in DMRs than in non-DMRs. Moreover, higher probability of developing PU among DMRs was confirmed in the univariate
logistic regression model (odds ratio [OR] 1.58; 95% confidence interval [CI] 1.27e1.97; P < .001). This influence remained significant after adjustment for potential risk factors of PU occurrence, such as BMI, ADLh, admission to hospital in the past 90 days, difficulty chewing, and dehydration. However, due to the presence of an interaction between DM and depression in the model, this relationship occurred to be slightly weaker in strength (than estimated in univariate model) in nondepressed patients (OR 1.38; 95% CI 1.02e1.86; P ¼ .036), while being even stronger in patients with depression (OR 1.90; 95% CI 1.14e3.18; P ¼ .015) (Annex: Table 1). UI was highly prevalent in both groups, yet severe UI was significantly more frequent in DMRs (Table 2). Foot problems were equally frequent (20.2%) in both groups. No differences were found in the frequency and intensity of pain; with the exception of breakthrough pain (acute flare-ups of pain appearing one or more times in the past 3 days of observation), which was reported less frequently by DMRs (Table 2). In fact, application of a univariate ordinal regression showed that DM decreased the probability of higher pain scores measured using the Pain Scale (B ¼ 0.13; 95% CI 0.26 to 0.01; P ¼ .038). This relationship was even stronger after adjustment for several other clinical factors associated with pain (B ¼ 0.28; 95% CI 0.41 to 0.14; P < .001), such as cancer, PU, depression, weight loss, cognitive impairment, polypharmacy, and history of recent hospitalization (Annex: Table 2). About 31.1% of all studied NH residents were moderately, and 50.6% were severely impaired in ADLs. The functional status in terms of ADLs did not differ significantly between DMRs and non-DMRs. Univariate ordinal regression model did not show significant influence of DM on ADL impairment (B ¼ 0.02; 95% CI 0.06 to 0.10; P ¼ .600). We confirmed this finding after adjustment for other factors related to impaired ADL (stroke, hemiplegia, severe cognitive impairment, weight loss, BMI less than 18.5 kg/m2, and recent hospitalization) (B ¼ 0.07; 95% CI 0.02 to 0.16; P ¼ .110) (Annex: Table 3).
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Table 2 The Conditions That Influence Functional Status of DMRs and non-DMRs in 59 European Nursing Homes: The SHELTER Study Characteristics of NH Residents
Physical, cognitive, and psychological status, % (n) Moderately physically dependent (ADLh) Severely physically dependent (ADLh) Moderate cognitive impairment (CPS) Severe cognitive impairment (CPS) Symptoms of depression (DRS) Nutritional status Weight, median (quartiles), kg BMI, median (quartiles), kg/m2 Residents acc. BMI, % (n) BMI 30.0 kg/m2 BMI 25.0e29.9 kg/m2 BMI 18.5e24.9 kg/m2 BMI < 18.5 kg/m2 Dehydrated Oral health, % (n) Mouth pain Gum inflammation Dentures Skin problems, % (n) Pressure ulcer Other chronic wound Other major skin problems UI, % (n) Continent Infrequently or occasionally incontinent Severely incontinent Foot problems, % (n) Any foot problems Pain, % (n) Frequency: daily pain Intensity: moderate, severe or horrible and excruciating pain Breakthrough pain (acute flare-ups of pain in past 3 d)
Diabetic
Nondiabetic
All
21.8% (n ¼ 879)
78.2% (n ¼ 3158)
100.0% (n ¼ 4037)
34.0 49.7 32.8 33.0 32.8
30.3 50.8 32.7 37.7 32.4
31.1 50.6 32.7 36.7 32.5
(299) (437) (285) (287) (285)
(954) (1602) (1020) (1176) (1009)
n
(1253) (2039) (1305) (1463) (1294)
4032
.051
3989
.011
3983
.826
3993 3922 3883
<.001 <.001 <.001
(553) (1064) (1831) (435) (188)
4032
<.001
67 (57e79) 25.2 (22.2e29.3)
61 (52e72) 23.6 (20.4e27.1)
63 (53e74) 24.0 (20.8e27.6)
21.8 30.3 40.3 7.6 2.3
12.1 26.6 49.1 12.2 5.3
14.2 27.4 47.2 11.2 4.7
(183) (260) (345) (65) (20)
(366) (804) (1486) (370) (168)
P
2.8 (25) 1.7 (15) 58.0 (509)
4.4 (140) 3.2 (102) 51.8 (1636)
4.1 (165) 2.9 (117) 53.2 (2145)
4033 4034 4034
.035 .017 <.001
13.7 (120) 5.8 (51) 3.5 (31)
9.1 (286) 2.7 (86) 2.2 (68)
10.1 (406) 3.4 (137) 2.5 (99)
4036 4033 4037 4030
<.001 <.001 .020 .048
18 (158) 12.7 (111) 69.3 (608)
20.7 (653) 14.4 (455) 64.9 (2045)
20.1 (811) 14.0 (566) 65.9 (2653)
19.7 (173)
20.4 (641)
20.2 (814)
4027
.454
13.1 (112) 20.9 (178) 2.6 (22)
14.4 (418) 22.7 (657) 4.4 (127)
14.1 (530) 22.3 (835) 4.0 (149)
3748 3748 3740
.343 .269 .018
Acc, residents by BMI value. Bold values are statistically significant P .05.
Clinically significant symptoms of depression had resembling frequencies in both groups, and no difference between DMRs and non-DMRs was found both in the univariate (B ¼ 0.12; 95% CI 0.12 to 0.35; P ¼ .334) and the multivariate regression model, after adjustment for sex, age, polypharmacy, pain, and severe ADL impairment (B ¼ 0.02; 95% CI 0.45 to 0.41; P ¼ .923) (Annex: Table 4). In the descriptive analysis we found that there was no significant difference between DMRs and non-DMRs in prevalence of moderate cognitive impairment (32.7% vs 32.8%); however, presence of severe cognitive impairment (33.0% vs 37.7%) was lower in DMRs, attributing to significant difference in distribution of cognitive impairment between analyzed groups (P ¼ .011). Also, the prevalence of Alzheimer disease (17.0%) was lower in DMRs (P < .005) (Table 2). The univariate ordinal regression model showed that DM decreased probability of severe cognitive impairment (B ¼ 0.13; 95% CI 0.21 to 0.04; P ¼ .003). However, adjustment for sex, age, BMI, polypharmacy, level of depression symptoms, functional status, and weight loss, revealed that DM had no longer, independent of previously mentioned factors, influence on cognitive impairment (B ¼ 0.02; 95% CI 0.11 to 0.07; P ¼ .657) (Annex: Table 5). Discussion This is the first large-scale multinational observational study in the European region analyzing the prevalence of DM and the health and functional characteristics of DMR. In contrast to lower reported prevalence rates of DM in several European studies, which did not include laboratory testing of blood glucose levels, our findings of 21.8% diabetic individuals among a European NH population is in
accordance with the prevalence rate found in British and German studies, in which diagnosis of DM was based on laboratory test.10,11 This figure is somewhat lower than data found in the largest US study,3 but close to the recent national US National Nursing Home Survey (NNHS) reporting a diagnosis of DM based on ICD-9eClinical Modification in approximately one-fifth of NH residents.4 The analysis of the characteristics of NH residents in the SHELTER study provided results comparable to US studies. According to Dybicz et al,20 DMRs were younger than non-DMRs (34.3% of DMRs vs 53.1% of non-DMRs were 85 and older). This ratio in our study was 41.4% to 52.8%. A reason for this may be the medical complexity and disability of the diabetic population, which is institutionalized at a younger age than non-DMRs. Another cause can be a higher mortality among diabetic individuals due to cardiovascular diseases,21 which limits number of long-lived diabetic individuals in NHs. Both of these possibilities should thus urge NH staff to pay more attention to screening for DM, early detection, and effective control. Analysis of trends in the prevalence of DM and its comorbidities in US NHs showed that the frequency rate of cardiovascular diseases increased in diabetic residents between 1995 and 2004 and was strongly related to DM.5 In accordance with the studies from the United States, we confirm that also European DMRs are clinically complex, with a high frequency of comorbidities (such as hypertension, CHD, CHF, and stroke) and use more drugs.20,22 Obesity and overweight were common in US DMRs (59.4% vs 40.6% non-DMRs) as well as in our study, although respective rates were slightly lower in the European sample (52.1% DMRs vs 38.7% non-DMRs). We also found a greater prevalence of other illnesses contributing to multimorbidity and clinical complexity of DMRs. It is of note that the rates
338
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of CHF, stroke, PU, and CKD in the SHELTER population were very close to those found in the previously mentioned studies. DM has been often reported as a condition associated with PU.23 According to the 2004 NNHS, DMRs had 56% higher odds of having a PU compared with non-DMRs.24 Interestingly, in a study by Brandeis et al,25 DM was found to be a significant factor associated with the occurrence of PU in high-incidence NHs as opposed to lowincidence NHs. Our findings thus confirm significance of DM for the development of PU. The DMRs in our study had a significantly better nutritional status (lower prevalence of low BMI and dehydration) and fewer oral problems (dentures present more often, less gum disease and mouth pain). These findings and the other SHELTER study data led us to assume that NH staff caring for residents with a diagnosis of diabetes paid careful attention in areas such as following a diabetic diet and regular assessment and monitoring of nutritional status, including evaluation of the oral cavity. Interestingly, we confirmed neither a higher frequency nor increased intensity of pain reported by DMRs. Moreover, approximately 59% of them did not report any issue of pain and DM was associated with lower probability of severe pain. As a result of diabetic neuropathy, the demonstration of pain in diabetic patients may be lower (when it is demonstrated by the loss of pinprick, vibration, and temperature sensation) or higher (in case of painful neuropathy symptoms). The first type is presented in approximately half of diabetic patients, the second type in one-third of community-dwelling diabetic patients.26 Thus, a lower probability of severe pain in our DMR sample may have its origin in neuropathic impairment of sensation. In some cases, somatic pain may be less pronounced or even “silent.”27 The absence of association between DM and pain intensity was also presented in another article based on the SHELTER study.28 Obesity and DM are known risk factors for the development of physical disability among older adults. A growing body of evidence suggests that metabolic dysregulation associated with obesity and DM accelerates the progression of sarcopenia, and subsequently functional decline in older adults. Although both conditions are often interrelated, DM independently of obesity has a negative impact on physical functioning.29 Yet, in our cohort, there was no significant difference in ADL disability between DMRs and non-DMRs. The influence of DM on disability in our sample is mitigated by the fact that most residents admitted to European NHs suffer from a significant level of disability in ADLs and/or cognitive impairment at the time of admission, as these conditions are commonly used as the basic eligibility criteria for admission to a NH. Disability and age remain important drivers of long-term care use.30 In our study, more than 80% of both DMRs and non-DMRs were moderately to severely physically dependent. It is worth mentioning that we did not confirm a typical relation between age and ADL impairment in our study group. Researchers should thus be aware that prevalence of some characteristics and relation between them appear different on studying the NH population compared with findings of epidemiological studies on a community-dwelling population. The relation between DM and cognitive impairment is even more complex. During the past 20 years, this has been extensively studied and discussed in a context of interrelation with obesity and metabolic syndrome31 to formulate the hypothesis of a “metabolic-cognitive syndrome,”32 in which hyperglycemia is an important player in vascular change, and insulin resistance is associated with amyloid pathology in Alzheimer’s disease. In our sample, we did not find a negative effect of DM on cognitive performance (as shown in the regression model presented in Table 5 in the Annex). Also, Alzheimer disease was recognized in DMRs less
frequently than in other NH residents. In light of well-documented evidence, we do not attempt to propose that there is no relation between DM and cognitive impairment; however, our results are consistent with findings from other studies of NH populations. The Canadian Study on Health and Aging found no evidence that DM increases the risk of Alzheimer disease.33 The American study conducted by Dybicz et al20 showed that cognitive impairment was not more frequent in DMRs than in other NH residents. The possible explanation, again, may lie in admission criteria to NHs, which include cognitive impairment. To support this thesis, it should be noted that in our sample approximately two-thirds of residents, both DMRs and non-DMRs, had moderately to severely impaired cognition. Yet, the regression analysis conducted on data collected in our study provided another possible clarification. It showed that BMI higher than 25.0 kg/m2 reduced the probability of cognitive impairment, whereas weight loss of 10% in 6 months increased it (regression model in Annex: Table 5). The results of some prospective cohort studies suggest that the late-life metabolic syndrome (in which DM and obesity are considered among other diagnostic criteria) is associated with reduced risk of cognitive decline among older people.34,35 Also, a scientific debate about the relation between BMI and dementia36,37 leads us to the conclusion that weight loss might be a predominant independent risk factor for generalized decline in cognition and physical performance (frailty, sarcopenia, malnutrition) in NH residents, much stronger than other conditions or diseases, including diabetes. Our opinion is in accordance with the discussion raised by other researchers.38 In summary, the relation among DM, obesity, and cognitive impairment seems to be complex and needs explanation in further studies. Yet, there is no doubt that early recognition of cognitive impairment among DMRs is important, because it may influence DM management. Improved DM control (in terms of meeting the HbAc1 target) has been shown to delay global cognitive decline in older individuals with DM type 2.39 Among patients with chronic medical illnesses, the annual prevalence rate of depression is higher than in the general population. Rates of depression may be particularly high in diseases of the central nervous system (eg, stroke, traumatic brain injury, Parkinson disease), cardiovascular disorders, cancer, and conditions involving immune and inflammatory mechanisms.40 In LTC populations, the previously mentioned chronic diseases and comorbidities, and some other conditions, such as pain and functional disability, also were reported to increase the prevalence of depression. However, independent influence of DM on depression is not well described. McCusker et al41 found DM, delirium, and pain as factors independently associated with a higher prevalence of depression diagnosed during admission to LTCFs. However, in the same study, other diseases (heart disease, hypertension, stroke, cancer, and dementia) were found to have no such influence. Prevalence of depression symptoms in our study group was approximately 32%, and we did not find any statistically significant difference between DMRs and non-DMRs. It seems that comorbid conditions and the effect of overlapping of different chronic diseases may mask an individual potential impact of diabetes on depression. The SHELTER study, to our knowledge, is the largest study including the European and Israeli NH population. The application of standardized methodology and the interRAI-LTCF tool enabled a comprehensive and comparable assessment that provided data on prevalence and health characteristics of residents with DM in 59 NHs across Europe. Many similarities in older DMRs, both in US and European NHs, provide encouraging evidence and therefore a starting point to design care recommendations for DMRs that may be applied to LTCFs in different countries. Our study has several limitations. First, the SHELTER study was not primarily intended to focus on DM in the NH population. The
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diagnosis of DM was not obtained based on direct laboratory testing as part of the study protocol. However, the design of this study involved using clinical data, including diagnosis of DM, made by physicians based on previous laboratory data recorded in the patient’s medical file. Furthermore, in 71.2% of NHs (42 of 59 recruited into the SHELTER study), a physician was available daily, and, overall, 96.6% facilities had a physician visiting at least once a week. However, some cases of previously unknown diagnosis of diabetes may have been missed and the true prevalence may have been underestimated. Second, the SHELTER sample of countries was not strictly selected as representative of all NHs in the respective countries, as described by Onder et al.13 Bearing this in mind, we hope that our findings will contribute to enhance NH staff awareness of the high prevalence of DM in patients of LTCFs. Recently, guidelines have been published to underline the importance of screening for detection of DM in NH residents, recognition of symptoms and risks, and appropriately adjusted management.6,12,42,43 They continue to remain a challenge, as diagnostic and treatment recommendations have been only partially met so far.44,45 Based on our findings, the following key issues should be addressed in light of new IDF guidelines: better recognition and managing a late-life metabolic syndrome; regular weight monitoring to prevent its loss and malnutrition, which seem to be the independent risk factors for both cognitive and physical decline; better management of pain with recognition of possible underlying neuropathy; and PU risk assessment, early prevention, and treatment. Conclusions The prevalence of DM in European NH residents is found to be 21.8% and is very similar to the US research data, as well as to data from the United Kingdom and Germany based on glucoselevel testing. It is much higher than known prevalence rates in community-dwelling older people, and should thus receive greater attention of care professionals aiming for early detection and treatment. DMRs, as compared with other NH residents, have more comorbid conditions, especially higher rate of cardiovascular diseases and obesity, PU, and severe UI. In spite of their younger age, their functional status in terms of ADLs, cognitive impairment, and mood does not differ from older non-DMRs. Moreover, we found that DM enhances the probability of PU, and reduces probability of severe pain. DMRs should be regarded as a specific group of residents who require an interdisciplinary approach in medical and nursing care. Our findings complement the recently developed IDF global guidelines for managing older people with type 2 DM, and underline the complexity of DM management, particularly the assessment of comorbidities, functional (physical, psychological, cognitive, and nutritional) status, and detection of the specific diabetic complications (foot problems, sensory deficits, PU, UI) in NH residents.43 Supplementary Data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jamda.2014.11.009. References 1. International Diabetes Federation. IDF Diabetes Atlas. 6th ed. Brussels, Belgium: International Diabetes Federation. Available at: http://www.idf.org/dia betesatlas; 2013. Accessed June 30, 2014. 2. Fagot-Campagna A, Bourdel-Marchasson I, Simon D. Burden of diabetes in an aging population: Prevalence, incidence, mortality, characteristics and quality of care. Diabetes Metab 2005;31:5S35e5S52.
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3. Centers for Medicare and Medicaid Services. MDS active resident information report: Third quarter 2010. Available at: http://www.cms.gov/ResearchStatistics-Data-and-Systems/Computer-Data-and-Systems/MDSPubQIandRes Rep/activeresreport.html. Accessed August 6, 2013. 4. Moore KL, Boscardin WJ, Steinman MA, Schwartz JB. Age and sex variation in prevalence of chronic medical conditions in older residents of US nursing homes. J Am Geriatr Soc 2012;60:756e764. 5. Zhang X, Decker FH, Luo H, et al. Trends in the prevalence and comorbidities of diabetes mellitus in nursing home residents in the United States: 1995e2004. J Am Geriatr Soc 2010;58:724e730. 6. Benetos A, Novella JL, Guerci B, et al. Pragmatic diabetes management in nursing homes: Individual care plan. J Am Med Dir Assoc 2013;14:791e800. 7. Rolland Y, Abellan van Kan G, Hermabessiere S, et al. Descriptive study of nursing home residents from the REHPA network. J Nutr Health Aging 2009;13: 679e683. 8. Aspray TJ, Nesbit K, Cassidy TP, et al. Diabetes in British nursing and residential homes: A pragmatic screening study. Diabetes Care 2006;29:707e708. 9. Taylor CD, Hendra TJ. The prevalence of diabetes mellitus and quality of diabetic care in residential and nursing homes. A postal survey. Age Ageing 2000; 29:447e450. 10. Sinclair AJ, Gadsby R, Penfold S, et al. Prevalence of diabetes in care home residents. Diabetes Care 2001;24:1066e1068. 11. Hauner H, Kurnaz AA, Haastert B, et al. Undiagnosed diabetes mellitus and metabolic control assessed by HbA(1c) among residents of nursing homes. Exp Clin Endocrinol Diabetes 2001;109:326e329. 12. Sinclair AJ, Task and Finish Group of Diabetes UK. Good clinical practice guidelines for care home residents with diabetes: An executive summary. Diabet Med 2011;28:772e777. 13. Onder G, Carpenter I, Finne-Soveri H, et al. Assessment of nursing home residents in Europe: The services and health for elderly in long TERm care (SHELTER) study. BMC Health Serv Res 2012;12:5. 14. Hirdes JP, Ljunggren G, Morris JN, et al. Reliability of the interRAI suite of assessment instruments: A 12-country study of an integrated health information system. BMC Health Serv Res 2008;8:277. 15. Landi F, Tua E, Onder G, et al. Minimum data set for home care: A valid instrument to assess frail older people living in the community. Med Care 2000; 38:1184e1190. 16. Morris JN, Fries BE, Mehr DR, et al. MDS cognitive performance scale. J Gerontol 1994;49:M174eM182. 17. Morris JN, Fries BE, Morris SA. Scaling ADLs within the MDS. J Gerontol A Biol Sci Med Sci 1999;54:M546eM553. 18. Burrows AB, Morris JN, Simon SE, et al. Development of a minimum data setbased depression rating scale for use in nursing homes. Age Ageing 2000;29: 165e172. 19. Onder G, Liperoti R, Fialova D, et al. Polypharmacy in nursing home in Europe: Results from the SHELTER study. J Gerontol A Biol Sci Med Sci 2012;67: 698e704. 20. Dybicz SB, Thompson S, Molotsky S, Stuart B. Prevalence of diabetes and the burden of comorbid conditions among elderly nursing home residents. Am J Geriatr Pharmacother 2011;9:212e223. 21. Danaei G, Lawes CM, Vander Hoorn S, et al. Global and regional mortality from ischaemic heart disease and stroke attributable to higher-than-optimum blood glucose concentration: Comparative risk assessment. Lancet 2006;368: 1651e1659. 22. Travis SS, Buchanan RJ, Wang S, Kim M. Analyses of nursing home residents with diabetes at admission. J Am Med Dir Assoc 2004;5:320e327. 23. Berlowitz DR, Brandeis GH, Morris JN, et al. Deriving a risk-adjustment model for pressure ulcer development using the minimum data set. J Am Geriatr Soc 2001;49:866e871. 24. Resnick HE, Heineman J, Stone R, Shorr RI. Diabetes in US nursing homes, 2004. Diabetes Care 2008;31:287e288. 25. Brandeis GH, Ooi WL, Hossain M, et al. A longitudinal study of risk factors associated with the formation of pressure ulcers in nursing homes. J Am Geriatr Soc 1994;42:388e393. 26. Abbott CA, Malik RA, van Ross ER, et al. Prevalence and characteristics of painful diabetic neuropathy in a large community-based diabetic population in the U.K. Diabetes Care 2011;34:2220e2224. 27. Ieda M, Fukuda K. Cardiac innervation and sudden cardiac death. Curr Cardiol Rev 2009;5:289e295. 28. Lukas A, Mayer B, Fialova D, et al. Treatment of pain in European nursing homes: Results from the services and health for elderly in long TERm care (SHELTER) study. J Am Med Dir Assoc 2013;14:821e831. 29. Anton SD, Karabetian C, Naugle K, Buford TW. Obesity and diabetes as accelerators of functional decline: Can lifestyle interventions maintain functional status in high risk older adults? Exp Gerontol 2013;48:888e897. 30. de Meijer CA, Koopmanschap MA, Koolman XH, van Doorslaer EK. The role of disability in explaining long-term care utilization. Med Care 2009;47:1156e1163. 31. Frisardi V, Solfrizzi V, Seripa D, et al. Metabolic-cognitive syndrome: A crosstalk between metabolic syndrome and Alzheimer’s disease. Ageing Res Rev 2010;9:399e417. 32. Luchsinger JA, Gustafson DR. Adiposity, type 2 diabetes, and Alzheimer’s disease. J Alzheimers Dis 2009;16:693e704. 33. MacKnight C, Rockwood K, Awalt E, McDowell I. Diabetes mellitus and the risk of dementia, Alzheimer’s disease and vascular cognitive impairment in the
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ska et al. / JAMDA 16 (2015) 334e340 K. Szczerbin Canadian Study of Health and Aging. Dement Geriatr Cogn Disord 2002;14: 77e83. Liu CL, Lin MH, Peng LN, et al. Late-life metabolic syndrome prevents cognitive decline among older men aged 75 years and over: One-year prospective cohort study. J Nutr Health Aging 2013;17:523e526. van den Berg E, Biessels GJ, de Craen AJ, et al. The metabolic syndrome is associated with decelerated cognitive decline in the oldest old. Neurology 2007;69:979e985. Hughes TF, Borenstein AR, Schofield E, et al. Association between late-life body mass index and dementia: The KAME project. Neurology 2009;72:1741e1746. Dahl AK, Lopponen M, Isoaho R, et al. Overweight and obesity in old age are not associated with greater dementia risk. J Am Geriatr Soc 2008;56:2261e2266. Knopman DS. When being thin is not a virtue. J Am Geriatr Soc 2008;56: 2349e2350. Luchsinger JA, Palmas W, Teresi JA, et al. Improved diabetes control in the elderly delays global cognitive decline. J Nutr Health Aging 2011;15:445e449. Birrer RB, Vemuri SP. Depression in later life: A diagnostic and therapeutic challenge. Am Fam Physician 2004;69:2375e2382.
41. McCusker J, Cole MG, Voyer P, et al. Observer-rated depression in longterm care: Frequency and risk factors. Arch Gerontol Geriatr 2014;58: 332e338. 42. Sinclair A, Morley JE, Rodriguez-Manas L, et al. Diabetes mellitus in older people: Position statement on behalf of the International Association of Gerontology and Geriatrics (IAGG), the European Diabetes Working Party for Older People (EDWPOP), and the International Task Force of Experts in Diabetes. J Am Med Dir Assoc 2012;13:497e502. 43. International Diabetes Federation. Global guideline for managing older people with type 2 diabetes. Updated 2013. Available at: http://www.idf. org/guidelines/managing-older-people-type-2-diabetes. Accessed September 14, 2014. 44. Feldman SM, Rosen R, DeStasio J. Status of diabetes management in the nursing home setting in 2008: A retrospective chart review and epidemiology study of diabetic nursing home residents and nursing home initiatives in diabetes management. J Am Med Dir Assoc 2009;10:354e360. 45. Garcia TJ, Brown SA. Diabetes management in the nursing home: A systematic review of the literature. Diabetes Educ 2011;37:167e187.
JAMDA journal homepage: www.jamda.com
Original Study
The Characteristics of Diabetic Residents in European Nursing Homes: Results from the SHELTER Study ska MD, PhD a, *, Eva Topinková MD, PhD b, Piotr Brzyski PhD a, Katarzyna Szczerbin Henriëtte G. van der Roest PhD c, Tomás Richter MD, PhD b, Harriet Finne-Soveri MD, PhD d, Michael D. Denkinger MD e, Jacob Gindin MD f, Graziano Onder MD, PhD g, Roberto Bernabei MD g a Department of Sociology of Medicine, Epidemiology and Preventive Medicine Chair, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland b Department of Geriatrics, 1st Faculty of Medicine, Charles University, Prague, Czech Republic c EMGO Institute for Health and Care Research, Department of General Practice and Elderly Care, VU University Medical Centre, Amsterdam, The Netherlands d Unit for Ageing and Services, National Institute for Health and Welfare, Helsinki, Finland e Agaplesion Bethesda Clinic, Geriatric Centre Ulm/Alb-Donau, University of Ulm, Ulm, Germany f The Centre for Standards in Health and Disability, Research Authority, University of Haifa, Haifa, Israel g Centro Medicina dell’Invecchiamento, Università Cattolica Sacro Cuore, Rome, Italy
a b s t r a c t Keywords: Diabetes mellitus nursing home older adults
Objectives: The objectives of this study were to describe the prevalence of diabetes mellitus (DM) in European nursing homes (NHs), and the health and functional characteristics of diabetic residents (DMR) aged 60 years and older. Design: Between 2009 and 2011, the Services and Health for Elderly in Long TERm care (SHELTER) project, a 12-month prospective cohort study, was conducted to assess NH residents across different health care systems in 7 European countries and Israel. Methods: The study included 59 NHs in 8 countries with a total of 4037 residents living in or admitted to a NH during the 3-month enrollment period. The multidimensional InterRAI instrument for Long-Term Care Facilities (InterRAI-LTCF) was used to assess health and functional status among residents. Descriptive statistics and linear, ordinal, and logistic regression were used to perform the analyses. Results: We found a 21.8% prevalence of DM among NH residents. Residents with DM (DMRs) were significantly younger compared with non-DMRs (82.3, SD 7.7; 84.6, SD 8.4; P < .001). DMRs were more frequently overweight or obese, and presented more often with ischemic heart disease, congestive heart failure, hypertension, and stroke than residents without DM. DMRs also took more drugs, had pressure ulcers (PU) or other wounds more often, and more frequently had urinary incontinence (UI); they also reported worse self-perceived health. DM independently of other factors increased risk of PU occurrence (odds ratio 1.38; 95% confidence interval [CI] 1.02e1.86; P ¼ .036) and decreased probability of higher pain scores (B ¼ 0.28; 95% CI 0.41 to 0.14; P < .001). DM was not associated with ADL dependency, cognitive impairment, and depression in NH residents. Conclusion: Prevalence of DM in European NH residents is comparable to US national NH surveys, and to UK and German NH data based on glucose-level testing. DMRs compared with non-DMRs have more comorbid conditions, and a particularly higher incidence of cardiovascular diseases and obesity, PU, and severe UI. DMRs should be regarded as a specific group of residents who require an interdisciplinary approach in medical and nursing care. Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
KS, ET, HFS, JG, and RB are members of InterRAI. The other authors declare no conflicts of interest. The SHELTER study was funded by the European Union’s Seventh Framework Programme for Research, European Commission Grant 223115. The work of ET and
http://dx.doi.org/10.1016/j.jamda.2014.11.009 1525-8610/Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
TR was partly supported by FP7 European Commission Grant 278803 “The MIDFRAIL Study.” ska, MD, PhD, Jagiellonian * Address correspondence to Katarzyna Szczerbin University Medical College, ul. Kopernika 7a, 31e034 Kraków, Poland. ska). E-mail address: [email protected] (K. Szczerbin
ska et al. / JAMDA 16 (2015) 334e340 K. Szczerbin
According to the International Diabetes Federation (IDF), the prevalence of diabetes mellitus (DM) in European adults aged 20 to 79 years is 8.5% (11.0% in North America).1 It rises with age, reaching the peak in older adults aged 75 to 80.2 The highest prevalence of diabetes was found in nursing home (NH) populations. Studies conducted in the United States among large samples of NH residents showed a prevalence of 33.3% in a general sample of 1,361,406 NH residents,3 with 26% of patients found to be men and 23% women older than 65.4 Another cross-sectional study conducted in 1995 and 2004 found that the increase in prevalence of DM in US NH residents older than 55 years was steeper among men, from 16.9% to 26.4%, than among women, from 16.1% to 22.2%.5 DM thus seems to be an emerging challenge in the NH population. In comparison with the United States, there is definitely less information in published literature about prevalence of DM in European NHs.6 The existing data are based on significantly smaller convenience samples. Strikingly, a very low prevalence of DM was found in one study from France (8.7% in 4896 residents)7 and in 2 British studies (5.8% and 13.0%), depending on the type of long-term care facility (residential homes or NHs; for older people or for mentally ill older adults)8 and study method used (eg, postal survey or measurement of fasting glucose).8,9 Yet, Sinclair et al10 indicated that many cases of DM may remain unrecognized, and studies may underestimate the true prevalence rate in NHs when laboratory measurements of blood glucose are not included in the study protocol. Based on patient file information Sinclair et al10 reported a 12% prevalence of previously diagnosed DM in NH residents. However, as a result of blood glucose measurements taken during the study, another 14.7% of the study population was newly diagnosed with DM. Thus, the overall DM prevalence in Birmingham NHs in the United Kingdom was found to be 26.7%. These findings are supported by another study from Germany reporting 26.2% prevalence of DM in NHs based on glucose-level testing.11 The lack of standard blood glucose measurement in NHs was seen as an indicator of substandard quality and incomplete diagnostics.10 The latest European guidelines therefore recommend routine laboratory screening for DM in NH residents at admission and at 2-year intervals.12 Timely recognition of DM may prevent or slow down potential complications and diabetes-related conditions. Known diagnosis of DM should draw attention to symptoms that are often underreported, undetected, and undertreated in diabetic patients. NH professionals’ awareness of the high prevalence rate of DM in NHs is therefore a key factor that should drive them to perform regular screening for DM in NH residents so as to provide appropriate care, bearing in mind the clinical complexity of diabetic patients. The aim of our study thus was to detect the prevalence of DM in a large sample of European NHs. Further, to describe clinical characteristics of diabetic residents (DMRs) aged 60 years and older based on data collected in 59 NHs in 7 European countries and Israel from the SHELTER study (the Services and Health for Elderly in Long TERm care study) database. The third aim was to compare health and functional status of DMRs and nondiabetic residents (nonDMRs), while focusing on health problems that are typical for patients with DM. Methods The SHELTER study, a project funded by the Seventh Framework Program of the EU, was conducted from 2009 to 2011.13 The sample consisted of 4156 residents in 59 NHs located in 7 European countries (Czech Republic: 10 NHs, England: 9, Finland: 6, France: 4, Germany: 9, Italy: 10, The Netherlands: 4), and Israel: 7 NHs. NHs were selected based on their willingness to participate in the SHELTER study and
335
were not intended to be representative of all NHs in each participating country. Adults residing in participating NHs at the beginning of the study and those admitted in the 3-month enrollment period were assessed. To meet the goal of our current analysis, we excluded NH residents younger than 60 years (n ¼ 96) because of possible differences of characteristics in younger adults with DM. We also excluded residents (n ¼ 23) with missing data about their concomitant diseases (empty checklist of diseases), because it was not clear whether they had DM or not. The final sample was composed of 4037 persons. Residents were invited to take part in the study and were free to decline participation. Ethical approval for the study was obtained in all countries according to local regulations. The interRAI instrument for Long-Term Care Facilities (interRAILTCF) was used. This is a comprehensive standardized instrument to assess care needs, health, and functional status of NH residents. The interRAI-LTCF has been validated in several European countries and has proved to be a reliable instrument.13,14 It contains more than 350 variables, including sociodemographic items, numerous clinical diagnoses, symptoms, geriatric syndromes, care programs, and treatments. A diagnosis of DM and other clinical diagnoses were derived from the interRAI diagnoses section and a list of International Classification of Diseases, Ninth Revision (ICD-9) coded diseases. Several validated scales can be generated from the interRAI-LTCF items. For this study, the 7-point Cognitive Performance Scale (CPS) was used to assess cognitive status.15,16 Intact or nearly intact cognitive function was represented by a CPS score of 0 to 1, moderate impairment by a CPS score of 2 to 3, and severe impairment by a CPS score of 4 to 6. Functional status was represented by the 7-point scale of Activities of Daily Living Hierarchy (ADLh)17 categorizing physical functioning as independent (ADLh ¼ 0e1), moderately dependent (ADLh ¼ 2e3), and severely dependent (ADLh ¼ 4e6). The 7-point Depression Rating Scale (DRS)18 was used to indicate the presence of symptoms of depression (DRS ¼ 3 or more). Pressure ulcer (PU) stage was coded as follows: 0, no PU; 1, any area of persistent skin redness; 2, partial loss of skin layers; 3, deep craters in the skin; 4, breaks in skin exposing muscle or bone; 5, not codeable (eg, necrotic eschar predominant). Pain was coded based on frequency (pain experienced daily vs less than daily or no pain), on intensity (moderate, severe, or unbearable pain vs mild or no pain), and on occurrence of breakthrough pain within the past 3 days (yes vs no). A 5-point Pain Scale presenting level of pain starting from 0 (no pain) through 2 (daily pain) up to 4 (daily excruciating pain) was applied in regression models. The World Health Organization classification based on body mass index (BMI) was used to stratify for nutritional status. Four answers to a question concerning self-perceived health were divided into 3 categories: “excellent” (due to very low number of answers) and “good” were put in one category, and “fair” and “poor” were treated as 2 other separate categories. In line with previous publications, polypharmacy was categorized into 3 groups: nonpolypharmacy (concurrent use of 0e4 drugs), polypharmacy (concurrent use of 5e9 drugs), and excessive polypharmacy (concurrent use of 10 drugs or more).19 Urinary incontinence (UI) was defined as “severe” if the patient was frequently (daily but with some control present) or permanently incontinent (not controlled) or needed bladder catheterization versus “occasionally or infrequently incontinent” (incontinence episodes less than daily or did not occur over past 3 days), or “continent” (no incontinence problem). Bunions, hammertoes, overlapping toes or other structural foot problems, infections, and ulcers were all defined as “any foot problems.” Coding of other variables is described in Table 2 presenting results. Distributions of qualitative variables were described as frequencies (n) and percentages (%), whereas quantitative variables were described as means with SDs if they had normal distribution or as medians and quartiles otherwise. The distributions of categorical
ska et al. / JAMDA 16 (2015) 334e340 K. Szczerbin
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Table 1 Clinical Characteristics of DMRs and non-DMRs in 59 European Nursing Homes: The SHELTER Study Characteristics of NH Residents
Age, mean (SD) Age, y, % (n) 60e75 76e85 >85 Female gender Self-perceived health, % (n) Excellent and Good Fair Poor Selected diseases, % (n) Coronary heart disease Congestive heart failure Hypertension Stroke/transient ischemic attack Hemiplegia Alzheimer disease Other dementia Urinary tract infection Chronic kidney disease Cancer Chronic obstructive pulmonary disease No. of diseases, mean (SD) No. of drugs, mean (SD) No. of drugs, % (n) 0e4 5e9 10
Diabetic
Nondiabetic
All
21.8% (n ¼ 879)
78.2% (n ¼ 3158)
100.0% (n ¼ 4037)
82.3 ( 7.7)
84.6 ( 8.4)
84.1 ( 8.3)
17.7 40.8 41.4 73.8
13.6 33.6 52.8 73.7
14.5 35.2 50.3 73.7
(156) (359) (364) (649)
(428) (1062) (1668) (2327)
(584) (1421) (2032) (2976)
34.4 (224) 45.1 (294) 20.6 (134)
41.7 (917) 40.1 (882) 18.1 (398)
40.0 (1141) 41.3 (1176) 18.7 (134)
37.0 21.2 40.5 29.4 13.2 17.0 37.8 7.9 4.6 12.5 11.7 4.1 8.2
24.0 17.2 22.7 21.8 10.5 21.2 36.4 6.0 2.8 11.1 9.6 2.5 6.8
26.8 18.1 26.6 23.5 11.1 20.3 36.7 6.4 3.2 11.4 10.1 2.9 7.1
(325) (186) (356) (258) (116) (149) (332) (69) (40) (110) (103) (1.8)* (3.5)
17.0 (145) 49.9 (452) 33.0 (281)
(756) (543) (716) (689) (330) (669) (1145) (188) (90) (352) (304) (1.6) (3.3)
27.9 (855) 50.3 (1540) 21.8 (668)
(1081) (729) (1072) (947) (446) (818) (1477) (257) (130) (462) (40.7) (1.8) (3.6)
n
P
4037 4037
<.001 <.001
4037 2849
.930 .003
4028 4032 4037 4033 4031 4030 4028 4028 4037 4037 4037 4037 3914 3914
<.001 .007 <.001 <.001 .022 .005 .443 .042 .012 .370 .053 <.001 <.001 <.001
36.0 (1408) 39.8 (1557) 24.2 (949)
Bold values are statistically significant P < .05. *Including diabetes mellitus in DMRs.
variables were compared with c2 test. For normally distributed variables, the means were compared between 2 groups with t-test for independent samples, and for other variables, distributions were compared between 2 groups using the Mann-Whitney U test for interval variables and Ko1mogorov-Smirnov test for ordinal ones. Moreover, univariate and multivariate linear, logistic, and ordinal regression models were estimated using the Generalized Estimating Equations procedure, to assess the independent influence of DM on cognitive impairment (CPS), physical disability (ADLh), symptoms of depression (DRS), level of pain (Pain Scale), and PU occurrence. The differences were considered statistically significant if P value was less than .05. The analysis was conducted using IBM SPSS Statistics 21 for Windows (IBM SPSS Statistics, IBM Corporation, Chicago, IL). Results The study sample consisted of 4037 NH residents aged 60 years or older: 879 diabetic (21.8%) and 3158 nondiabetic individuals (78.2%). The findings presented in Table 1 show that DMRs were younger, they more frequently reported worse self-perceived health, used more drugs (one-third of DMRs were on excessive polypharmacy regimen), and suffered from more comorbidities. Cardiovascular diseases, such as coronary heart disease (CHD), congestive heart failure (CHF), hypertension, and stroke, were more frequently present in DMRs. The prevalence of urinary tract infections and chronic kidney disease (CKD) was low in both groups, but significantly higher than in nonDMRs. No significant differences between the prevalence rates of other chronic diseases were found. Not surprisingly, prevalence of BMI values over 25.0 kg/m2 was higher in DMRs. Meanwhile, DMRs suffered less frequently from dehydration, mouth pain, and gum inflammation, and these conditions were rare in both groups of residents (Table 2). Prevalence of PU was higher in DMRs than in non-DMRs. Moreover, higher probability of developing PU among DMRs was confirmed in the univariate
logistic regression model (odds ratio [OR] 1.58; 95% confidence interval [CI] 1.27e1.97; P < .001). This influence remained significant after adjustment for potential risk factors of PU occurrence, such as BMI, ADLh, admission to hospital in the past 90 days, difficulty chewing, and dehydration. However, due to the presence of an interaction between DM and depression in the model, this relationship occurred to be slightly weaker in strength (than estimated in univariate model) in nondepressed patients (OR 1.38; 95% CI 1.02e1.86; P ¼ .036), while being even stronger in patients with depression (OR 1.90; 95% CI 1.14e3.18; P ¼ .015) (Annex: Table 1). UI was highly prevalent in both groups, yet severe UI was significantly more frequent in DMRs (Table 2). Foot problems were equally frequent (20.2%) in both groups. No differences were found in the frequency and intensity of pain; with the exception of breakthrough pain (acute flare-ups of pain appearing one or more times in the past 3 days of observation), which was reported less frequently by DMRs (Table 2). In fact, application of a univariate ordinal regression showed that DM decreased the probability of higher pain scores measured using the Pain Scale (B ¼ 0.13; 95% CI 0.26 to 0.01; P ¼ .038). This relationship was even stronger after adjustment for several other clinical factors associated with pain (B ¼ 0.28; 95% CI 0.41 to 0.14; P < .001), such as cancer, PU, depression, weight loss, cognitive impairment, polypharmacy, and history of recent hospitalization (Annex: Table 2). About 31.1% of all studied NH residents were moderately, and 50.6% were severely impaired in ADLs. The functional status in terms of ADLs did not differ significantly between DMRs and non-DMRs. Univariate ordinal regression model did not show significant influence of DM on ADL impairment (B ¼ 0.02; 95% CI 0.06 to 0.10; P ¼ .600). We confirmed this finding after adjustment for other factors related to impaired ADL (stroke, hemiplegia, severe cognitive impairment, weight loss, BMI less than 18.5 kg/m2, and recent hospitalization) (B ¼ 0.07; 95% CI 0.02 to 0.16; P ¼ .110) (Annex: Table 3).
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337
Table 2 The Conditions That Influence Functional Status of DMRs and non-DMRs in 59 European Nursing Homes: The SHELTER Study Characteristics of NH Residents
Physical, cognitive, and psychological status, % (n) Moderately physically dependent (ADLh) Severely physically dependent (ADLh) Moderate cognitive impairment (CPS) Severe cognitive impairment (CPS) Symptoms of depression (DRS) Nutritional status Weight, median (quartiles), kg BMI, median (quartiles), kg/m2 Residents acc. BMI, % (n) BMI 30.0 kg/m2 BMI 25.0e29.9 kg/m2 BMI 18.5e24.9 kg/m2 BMI < 18.5 kg/m2 Dehydrated Oral health, % (n) Mouth pain Gum inflammation Dentures Skin problems, % (n) Pressure ulcer Other chronic wound Other major skin problems UI, % (n) Continent Infrequently or occasionally incontinent Severely incontinent Foot problems, % (n) Any foot problems Pain, % (n) Frequency: daily pain Intensity: moderate, severe or horrible and excruciating pain Breakthrough pain (acute flare-ups of pain in past 3 d)
Diabetic
Nondiabetic
All
21.8% (n ¼ 879)
78.2% (n ¼ 3158)
100.0% (n ¼ 4037)
34.0 49.7 32.8 33.0 32.8
30.3 50.8 32.7 37.7 32.4
31.1 50.6 32.7 36.7 32.5
(299) (437) (285) (287) (285)
(954) (1602) (1020) (1176) (1009)
n
(1253) (2039) (1305) (1463) (1294)
4032
.051
3989
.011
3983
.826
3993 3922 3883
<.001 <.001 <.001
(553) (1064) (1831) (435) (188)
4032
<.001
67 (57e79) 25.2 (22.2e29.3)
61 (52e72) 23.6 (20.4e27.1)
63 (53e74) 24.0 (20.8e27.6)
21.8 30.3 40.3 7.6 2.3
12.1 26.6 49.1 12.2 5.3
14.2 27.4 47.2 11.2 4.7
(183) (260) (345) (65) (20)
(366) (804) (1486) (370) (168)
P
2.8 (25) 1.7 (15) 58.0 (509)
4.4 (140) 3.2 (102) 51.8 (1636)
4.1 (165) 2.9 (117) 53.2 (2145)
4033 4034 4034
.035 .017 <.001
13.7 (120) 5.8 (51) 3.5 (31)
9.1 (286) 2.7 (86) 2.2 (68)
10.1 (406) 3.4 (137) 2.5 (99)
4036 4033 4037 4030
<.001 <.001 .020 .048
18 (158) 12.7 (111) 69.3 (608)
20.7 (653) 14.4 (455) 64.9 (2045)
20.1 (811) 14.0 (566) 65.9 (2653)
19.7 (173)
20.4 (641)
20.2 (814)
4027
.454
13.1 (112) 20.9 (178) 2.6 (22)
14.4 (418) 22.7 (657) 4.4 (127)
14.1 (530) 22.3 (835) 4.0 (149)
3748 3748 3740
.343 .269 .018
Acc, residents by BMI value. Bold values are statistically significant P .05.
Clinically significant symptoms of depression had resembling frequencies in both groups, and no difference between DMRs and non-DMRs was found both in the univariate (B ¼ 0.12; 95% CI 0.12 to 0.35; P ¼ .334) and the multivariate regression model, after adjustment for sex, age, polypharmacy, pain, and severe ADL impairment (B ¼ 0.02; 95% CI 0.45 to 0.41; P ¼ .923) (Annex: Table 4). In the descriptive analysis we found that there was no significant difference between DMRs and non-DMRs in prevalence of moderate cognitive impairment (32.7% vs 32.8%); however, presence of severe cognitive impairment (33.0% vs 37.7%) was lower in DMRs, attributing to significant difference in distribution of cognitive impairment between analyzed groups (P ¼ .011). Also, the prevalence of Alzheimer disease (17.0%) was lower in DMRs (P < .005) (Table 2). The univariate ordinal regression model showed that DM decreased probability of severe cognitive impairment (B ¼ 0.13; 95% CI 0.21 to 0.04; P ¼ .003). However, adjustment for sex, age, BMI, polypharmacy, level of depression symptoms, functional status, and weight loss, revealed that DM had no longer, independent of previously mentioned factors, influence on cognitive impairment (B ¼ 0.02; 95% CI 0.11 to 0.07; P ¼ .657) (Annex: Table 5). Discussion This is the first large-scale multinational observational study in the European region analyzing the prevalence of DM and the health and functional characteristics of DMR. In contrast to lower reported prevalence rates of DM in several European studies, which did not include laboratory testing of blood glucose levels, our findings of 21.8% diabetic individuals among a European NH population is in
accordance with the prevalence rate found in British and German studies, in which diagnosis of DM was based on laboratory test.10,11 This figure is somewhat lower than data found in the largest US study,3 but close to the recent national US National Nursing Home Survey (NNHS) reporting a diagnosis of DM based on ICD-9eClinical Modification in approximately one-fifth of NH residents.4 The analysis of the characteristics of NH residents in the SHELTER study provided results comparable to US studies. According to Dybicz et al,20 DMRs were younger than non-DMRs (34.3% of DMRs vs 53.1% of non-DMRs were 85 and older). This ratio in our study was 41.4% to 52.8%. A reason for this may be the medical complexity and disability of the diabetic population, which is institutionalized at a younger age than non-DMRs. Another cause can be a higher mortality among diabetic individuals due to cardiovascular diseases,21 which limits number of long-lived diabetic individuals in NHs. Both of these possibilities should thus urge NH staff to pay more attention to screening for DM, early detection, and effective control. Analysis of trends in the prevalence of DM and its comorbidities in US NHs showed that the frequency rate of cardiovascular diseases increased in diabetic residents between 1995 and 2004 and was strongly related to DM.5 In accordance with the studies from the United States, we confirm that also European DMRs are clinically complex, with a high frequency of comorbidities (such as hypertension, CHD, CHF, and stroke) and use more drugs.20,22 Obesity and overweight were common in US DMRs (59.4% vs 40.6% non-DMRs) as well as in our study, although respective rates were slightly lower in the European sample (52.1% DMRs vs 38.7% non-DMRs). We also found a greater prevalence of other illnesses contributing to multimorbidity and clinical complexity of DMRs. It is of note that the rates
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of CHF, stroke, PU, and CKD in the SHELTER population were very close to those found in the previously mentioned studies. DM has been often reported as a condition associated with PU.23 According to the 2004 NNHS, DMRs had 56% higher odds of having a PU compared with non-DMRs.24 Interestingly, in a study by Brandeis et al,25 DM was found to be a significant factor associated with the occurrence of PU in high-incidence NHs as opposed to lowincidence NHs. Our findings thus confirm significance of DM for the development of PU. The DMRs in our study had a significantly better nutritional status (lower prevalence of low BMI and dehydration) and fewer oral problems (dentures present more often, less gum disease and mouth pain). These findings and the other SHELTER study data led us to assume that NH staff caring for residents with a diagnosis of diabetes paid careful attention in areas such as following a diabetic diet and regular assessment and monitoring of nutritional status, including evaluation of the oral cavity. Interestingly, we confirmed neither a higher frequency nor increased intensity of pain reported by DMRs. Moreover, approximately 59% of them did not report any issue of pain and DM was associated with lower probability of severe pain. As a result of diabetic neuropathy, the demonstration of pain in diabetic patients may be lower (when it is demonstrated by the loss of pinprick, vibration, and temperature sensation) or higher (in case of painful neuropathy symptoms). The first type is presented in approximately half of diabetic patients, the second type in one-third of community-dwelling diabetic patients.26 Thus, a lower probability of severe pain in our DMR sample may have its origin in neuropathic impairment of sensation. In some cases, somatic pain may be less pronounced or even “silent.”27 The absence of association between DM and pain intensity was also presented in another article based on the SHELTER study.28 Obesity and DM are known risk factors for the development of physical disability among older adults. A growing body of evidence suggests that metabolic dysregulation associated with obesity and DM accelerates the progression of sarcopenia, and subsequently functional decline in older adults. Although both conditions are often interrelated, DM independently of obesity has a negative impact on physical functioning.29 Yet, in our cohort, there was no significant difference in ADL disability between DMRs and non-DMRs. The influence of DM on disability in our sample is mitigated by the fact that most residents admitted to European NHs suffer from a significant level of disability in ADLs and/or cognitive impairment at the time of admission, as these conditions are commonly used as the basic eligibility criteria for admission to a NH. Disability and age remain important drivers of long-term care use.30 In our study, more than 80% of both DMRs and non-DMRs were moderately to severely physically dependent. It is worth mentioning that we did not confirm a typical relation between age and ADL impairment in our study group. Researchers should thus be aware that prevalence of some characteristics and relation between them appear different on studying the NH population compared with findings of epidemiological studies on a community-dwelling population. The relation between DM and cognitive impairment is even more complex. During the past 20 years, this has been extensively studied and discussed in a context of interrelation with obesity and metabolic syndrome31 to formulate the hypothesis of a “metabolic-cognitive syndrome,”32 in which hyperglycemia is an important player in vascular change, and insulin resistance is associated with amyloid pathology in Alzheimer’s disease. In our sample, we did not find a negative effect of DM on cognitive performance (as shown in the regression model presented in Table 5 in the Annex). Also, Alzheimer disease was recognized in DMRs less
frequently than in other NH residents. In light of well-documented evidence, we do not attempt to propose that there is no relation between DM and cognitive impairment; however, our results are consistent with findings from other studies of NH populations. The Canadian Study on Health and Aging found no evidence that DM increases the risk of Alzheimer disease.33 The American study conducted by Dybicz et al20 showed that cognitive impairment was not more frequent in DMRs than in other NH residents. The possible explanation, again, may lie in admission criteria to NHs, which include cognitive impairment. To support this thesis, it should be noted that in our sample approximately two-thirds of residents, both DMRs and non-DMRs, had moderately to severely impaired cognition. Yet, the regression analysis conducted on data collected in our study provided another possible clarification. It showed that BMI higher than 25.0 kg/m2 reduced the probability of cognitive impairment, whereas weight loss of 10% in 6 months increased it (regression model in Annex: Table 5). The results of some prospective cohort studies suggest that the late-life metabolic syndrome (in which DM and obesity are considered among other diagnostic criteria) is associated with reduced risk of cognitive decline among older people.34,35 Also, a scientific debate about the relation between BMI and dementia36,37 leads us to the conclusion that weight loss might be a predominant independent risk factor for generalized decline in cognition and physical performance (frailty, sarcopenia, malnutrition) in NH residents, much stronger than other conditions or diseases, including diabetes. Our opinion is in accordance with the discussion raised by other researchers.38 In summary, the relation among DM, obesity, and cognitive impairment seems to be complex and needs explanation in further studies. Yet, there is no doubt that early recognition of cognitive impairment among DMRs is important, because it may influence DM management. Improved DM control (in terms of meeting the HbAc1 target) has been shown to delay global cognitive decline in older individuals with DM type 2.39 Among patients with chronic medical illnesses, the annual prevalence rate of depression is higher than in the general population. Rates of depression may be particularly high in diseases of the central nervous system (eg, stroke, traumatic brain injury, Parkinson disease), cardiovascular disorders, cancer, and conditions involving immune and inflammatory mechanisms.40 In LTC populations, the previously mentioned chronic diseases and comorbidities, and some other conditions, such as pain and functional disability, also were reported to increase the prevalence of depression. However, independent influence of DM on depression is not well described. McCusker et al41 found DM, delirium, and pain as factors independently associated with a higher prevalence of depression diagnosed during admission to LTCFs. However, in the same study, other diseases (heart disease, hypertension, stroke, cancer, and dementia) were found to have no such influence. Prevalence of depression symptoms in our study group was approximately 32%, and we did not find any statistically significant difference between DMRs and non-DMRs. It seems that comorbid conditions and the effect of overlapping of different chronic diseases may mask an individual potential impact of diabetes on depression. The SHELTER study, to our knowledge, is the largest study including the European and Israeli NH population. The application of standardized methodology and the interRAI-LTCF tool enabled a comprehensive and comparable assessment that provided data on prevalence and health characteristics of residents with DM in 59 NHs across Europe. Many similarities in older DMRs, both in US and European NHs, provide encouraging evidence and therefore a starting point to design care recommendations for DMRs that may be applied to LTCFs in different countries. Our study has several limitations. First, the SHELTER study was not primarily intended to focus on DM in the NH population. The
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diagnosis of DM was not obtained based on direct laboratory testing as part of the study protocol. However, the design of this study involved using clinical data, including diagnosis of DM, made by physicians based on previous laboratory data recorded in the patient’s medical file. Furthermore, in 71.2% of NHs (42 of 59 recruited into the SHELTER study), a physician was available daily, and, overall, 96.6% facilities had a physician visiting at least once a week. However, some cases of previously unknown diagnosis of diabetes may have been missed and the true prevalence may have been underestimated. Second, the SHELTER sample of countries was not strictly selected as representative of all NHs in the respective countries, as described by Onder et al.13 Bearing this in mind, we hope that our findings will contribute to enhance NH staff awareness of the high prevalence of DM in patients of LTCFs. Recently, guidelines have been published to underline the importance of screening for detection of DM in NH residents, recognition of symptoms and risks, and appropriately adjusted management.6,12,42,43 They continue to remain a challenge, as diagnostic and treatment recommendations have been only partially met so far.44,45 Based on our findings, the following key issues should be addressed in light of new IDF guidelines: better recognition and managing a late-life metabolic syndrome; regular weight monitoring to prevent its loss and malnutrition, which seem to be the independent risk factors for both cognitive and physical decline; better management of pain with recognition of possible underlying neuropathy; and PU risk assessment, early prevention, and treatment. Conclusions The prevalence of DM in European NH residents is found to be 21.8% and is very similar to the US research data, as well as to data from the United Kingdom and Germany based on glucoselevel testing. It is much higher than known prevalence rates in community-dwelling older people, and should thus receive greater attention of care professionals aiming for early detection and treatment. DMRs, as compared with other NH residents, have more comorbid conditions, especially higher rate of cardiovascular diseases and obesity, PU, and severe UI. In spite of their younger age, their functional status in terms of ADLs, cognitive impairment, and mood does not differ from older non-DMRs. Moreover, we found that DM enhances the probability of PU, and reduces probability of severe pain. DMRs should be regarded as a specific group of residents who require an interdisciplinary approach in medical and nursing care. Our findings complement the recently developed IDF global guidelines for managing older people with type 2 DM, and underline the complexity of DM management, particularly the assessment of comorbidities, functional (physical, psychological, cognitive, and nutritional) status, and detection of the specific diabetic complications (foot problems, sensory deficits, PU, UI) in NH residents.43 Supplementary Data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jamda.2014.11.009. References 1. International Diabetes Federation. IDF Diabetes Atlas. 6th ed. Brussels, Belgium: International Diabetes Federation. Available at: http://www.idf.org/dia betesatlas; 2013. Accessed June 30, 2014. 2. Fagot-Campagna A, Bourdel-Marchasson I, Simon D. Burden of diabetes in an aging population: Prevalence, incidence, mortality, characteristics and quality of care. Diabetes Metab 2005;31:5S35e5S52.
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