Correlates of health-related quality of life in French people with type 2 diabetes

diabetes research and clinical practice 101 (2013) 226–235

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Diabetes Research and Clinical Practice jou rnal hom ep ag e: w ww.e l s e v i er . c om/ loca te / d i ab r es

Correlates of health-related quality of life in French people with type 2 diabetes I. Bourdel-Marchasson a,b,c,*, C. Druet d, C. Helmer e,f, E. Eschwege g, P. Lecomte h, M. Le-Goff e,f, A.J. Sinclair i, A. Fagot-Campagna j a

Pole de ge´rontologie clinique, CHU Bordeaux, F-33000 Bordeaux, France Univ Bordeaux Segalen, RMSB, UMR 5536, F-33000 Bordeaux, France c CNRS, RMSB, UMR 5536, F-33000 Bordeaux, France d Institut de Veille Sanitaire, programme Diabe`te, De´partement des Maladies Chroniques et Traumatismes, Saint-Maurice, France e INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France f Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France g Centre de recherche en e´pide´miologie Inserm UMR-S 1018, Villejuif, France h Unite´ Endocrinologie, Nutrition, Diabe´tologie END, CHRU Bretonneau et Universite´ Franc¸ois Rabelais, Tours, France i Institute of Diabetes for Older People (IDOP), University of Bedfordshire, UK j National Health Insurance Service (CnamTS), Paris, France b

article info

abstract

Article history:

Aim: Diabetes is known to impair health-related quality of life (HrQol). Our aim was to

Received 26 November 2012

analyse a comprehensive set of potential determinants of HrQol in a large sample of patients

Received in revised form

with diabetes.

4 April 2013

Methods: This study is based on the ENTRED 2007 study, a representative sample of adults

Accepted 30 May 2013

(18 years and older) with diabetes. Data were extracted from postal self-reported ques-

Available online 5 July 2013

tionnaires (from patients and medical practitioners) and from reimbursements from the

Keywords:

(MCS) and physical (PCS) component summaries. Multivariate linear regression models

National health insurance data system. HrQol was assessed with the MOS SF-12 for mental Diabetes

were used to analyse the variables associated with HrQol.

Health related quality of life

Results: SF-12 MCS and PCS were available in 2832 patients with T2DM, with a mean age 64

Social support

years (1715 males, 56%). Lower income, severe hypoglycaemic episodes, hospitalisation 24 h, instrumental daily living (IADL) restriction, low satisfaction for social support and an HbA1c within the 8.1–10.0% range were associated with lower MCS rating, whereas an older age and male gender were associated with higher MCS. Older age, female sex, higher BMI, lower income, insulin treatment, macrovascular complications, severe hypoglycaemic episodes, hospitalisation 24 h, and IADL restriction were associated with lower PCS values whereas having no need for social support was associated with higher PCS values. Discussion: HrQol associated factors are multiple but mainly linked with socio-demographic factors, diabetes complications and satisfaction for social support. A patient centred approach should be tested to prevent impairment of HrQol and thus to decrease the burden of diabetes. Assessment of social support should be included. # 2013 Elsevier Ireland Ltd. All rights reserved.

* Corresponding author at: Centre Henri Choussat, Hopital Xavier Arnozan, 33604 Pessac cedex, France. Tel.: +33 5 57 65 65 71; fax: +33 5 57 65 65 60. E-mail address: [email protected] (I. Bourdel-Marchasson). 0168-8227/$ – see front matter # 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.diabres.2013.05.011

diabetes research and clinical practice 101 (2013) 226–235

1.

Introduction

Type 2 diabetes (T2D) is one of the most frequent chronic diseases in adults reaching 3.2% in French people older than 18 years and 11% in those older than 65 years [1]. The burden of diabetes is known to be heavy, as it involves high rates of disability, participation restrictions and decreased life expectancy. The health burden of diabetes is associated with an increasing economic burden, particularly in the oldest [2]. Effective interventions are thus needed to decrease these negative impacts in various populations with diabetes. Patient’s perception of his/her own quality of life is considered as a valuable basis to identify targets for improvement. Health-related quality of life (HrQoL) is therefore one of the major end-points of recent clinical trials in people with diabetes [3,4]. HrQoL assessment with the generic instrument SF-36 or its shorter version SF-12 has been used in people in T2D along with diabetes-specific instruments. The SF12 questionnaire is an instrument used to measure overall physical and mental health. Using a generic instrument allows comparisons with the general population. In France, in 2003, a previous large cross-sectional study obtained SF-36 scores in 22,743 community dwellers aged 18–84 years old including 3.4% patients with diabetes [5]. Diabetes was shown to be a predictor of lower scores in all of the 8 subscales independently of socio-economic status and diseases such as ischaemic heart disease, heart failure, cancer and hypertension. Similar results have been shown in German [6] or Korean populations [7]. However, in people with T2D and with diverse co-morbidities, the impact of diabetes on HrQoL is not easily distinguishable from that of other diseases or disabilities [8,9]. Previous studies investigating HrQoL in populations with T2D may have been of limited power due to limited sample sizes [10–13], or may have addressed only specific populations [14–16]. In a study focused on 7606 people with chronic diseases, including 14% people with diabetes, factors associated with lower HrQoL scores were not limited to the disease and its consequences but depended strongly on socio-economic factors [17]. Thus, although it has been shown that HrQol was associated with the characteristics of the diabetes disease [18], estimating the respective contribution of diverse factors on HrQol is necessary to better evaluate any intervention. For this purpose, a high power study is needed to assess the relative influences of multiple factors on HrQol. Using the large ENTRED 2007 cross-sectional study (E´chantillon national te´moin repre´sentatif des personnes diabe´tiques), based on a representative of adults with diabetes living in metropolitan France in 2007 [19], the aim of our analysis was to assess HrQol in people with T2D and to estimate the relative contributions of socio-demographic factors, diabetes characteristics, complications and treatment, social support and functional impairment in daily living, in mental and physical components of HrQol.

2.

Methods

2.1.

Population

The ENTRED 2007 study is based on a representative sample of 8926 adults with diabetes, aged 18 years and over, treated for

227

diabetes and living in metropolitan France. This sample was randomly extracted from the database of two National Health Insurance Services: The health insurance for employers and their relatives, CNAMTS (Caisse Nationale d’Assurance Maladie, 75% of people living in France) and the health insurance of independent workers (RSI, 5% of people living in France) from all patients who claimed reimbursement for oral hypoglycaemic agents (OHA) or insulin at least three times during the previous 12 months. To classify the different types of diabetes, we used an epidemiological algorithm validated by a scientific committee. People diagnosed before the age of 45 years and treated with insulin within two years of diagnosis were classified as having type 1 diabetes. The French National Ethics Authority approved the study protocol.

2.2.

General design of the survey

Health questionnaires were mailed to all selected patients (patient’s questionnaire, PQ). Respondents provided the address of their medical-care provider and a follow-up questionnaire was then mailed to physicians to obtain the patient’s biological data during previous year (medical questionnaire, MQ). A third source of data came from reimbursements for medical care by the national health insurance database: drugs, hospitalisations and medical visits. These data were available for all patients.

2.3.

Quality of life assessment

The French version of the generic scale MOS SF-12 was used through self-assessment in the PQ [20]. The SF-12 measures 8 health domains: functioning and physical limitations, emotional limitation, mental health, energy and fatigue, pain, social functioning and general health perception. The responses were scored according to two summary measures, the Mental (MCS) and Physical (PCS) Component Summaries. Summaries are scored from 0 to 100, 100 being associated with the best quality of life. The scoring was constructed to obtain in a given general population the mean of 50 for each summary. SF-12 summaries were calculated only when all the 12 items were addressed. Furthermore, people were asked in the PQ to score their own view of future with the diabetes disease (great confidence, confidence, concern, great concern). Medical care providers were also asked to score the burden of diabetes for the patient’s daily life (very important, important, not so important and minimal). These questions were drawn for this study.

2.4.

Characteristics

The socio-demographic characteristics were self-reported in the PQ. Income was self-scored as follows: comfortable, fine, fair, difficult to achieve daily living, debts are necessary to achieve daily living. Education was recorded using five levels: no schooling or less than 4 years of schooling, primary school level (equivalent to 5 years of schooling, reference category), short secondary school level (equivalent to 6–9 years of schooling), long secondary school level (equivalent to 10–12 years of schooling), and university level (over 12 years of schooling). Current or past occupational activities were

228

diabetes research and clinical practice 101 (2013) 226–235

ranked in the following classes – 1: farmers, skilled workmen, store keepers and company managers, 2: executive and intellectual professions; 3: intermediary professions (reference category); 4: employees; 5: workers; 6: housewife (or men) or people who had never worked. Weight and height were selfreported and BMI (Body Mass Index) (kg/m2) was divided according to three classes: <25 kg/m2 (reference category), 25– 29 and 30 kg/m2. Diabetes duration (4 years, 5–9 years, 10–19 years, and 20 years) was self-reported, as were complications. Macrovascular complications were defined by a history of angina, myocardial infarction, coronary revascularisation, foot ulcer or amputation. Microvascular complications were defined by a history of ophthalmological laser treatment, loss of sight of one eye, foot ulcer, amputation, and dialysis or renal transplantation. Occurrences of severe hypoglycaemia were identified by the question: ‘‘Last year, have you experienced severe hypoglycaemia, which required the help of someone to raise your blood glucose level?’’ The HbA1c level was reported by care providers (MQ). Diabetes treatment was obtained from the national health insurance data system and was classified as oral hypoglycemic agent (OHA), OHA combined with insulin, and insulin alone. Instrumental activities of daily living (IADLs) autonomy were self-reported (PQ) using the Lawton and Brody scale [21]. In the study only six of the eight IADLs were recorded: the ability to use the telephone, the mode of transportation, the responsibility for his/her own medications, the ability to handle financial and administrative tasks, or shopping, or cooking. Cooking was considered only in women. For each activity, participants were considered to be non-restricted if they were able to perform the activity at the highest level of performance. Otherwise, they were considered to be restricted. Autonomy was defined when the patient was non-restricted for any of the 5 (for men) or 6 (for women) activities. The occurrence of one or more hospital stays during the previous year was found in the national health insurance data system and was here considered as a factor restricting participation in daily activities. We have categorised hospitalisation in 3 classes: none, day-hospital (stay shorter than 24 h) and conventional or overnight hospitalisation. Finally, patients were asked in the mailed questionnaire (PQ) to rate their satisfaction towards social support: very satisfied, rather satisfied, not really satisfied, not satisfied at all, or do not need help.

2.5.

Analysis

Descriptive procedures included frequencies, percentage and their 95% confidence intervals (CI) for categorical variables, and means and standard deviations (SD) for continuous variables. Chi square tests were used to compare frequencies between responders and non-responders. Student t tests were used to compare MCS and PCS according to age and sex. We applied a stepwise backward variables selection in linear regression models to determine the factors associated with lower summary scores of quality of life (MCS and PCS). For each characteristic, beta coefficients represent the mean variation of MCS (or PCS) score for a given category compared to the reference category. A first block of variables included socio-demographic data (self-scored income, age, gender,

educational level, professional activity) and BMI, a second one added diabetes-related health-status data (macrovascular and microvascular complications, diabetes duration, type of hypoglycaemic treatment, history of severe hypoglycaemia), and a third one added IADL autonomy, history of hospitalisation and self-rated social support to build the first final model. The variable ‘‘last HbA1c’’ reported by the medical-care provider was analysed in the sample of patients in whom medical questionnaire is available in the second and final model. All models were adjusted for age and gender. P-values less than 0.05 were considered as statistically significant. All analyses were performed using SAS 9.1.

3.

Results

PQ were available in 48% of the sample (among those with type 2 diabetes: n = 3894 or 2282 males, 1612 females). MQ were obtained for 57% of the responders with type 2 diabetes (N = 2232). SF-12 MCS and PCS were available in 2832 patients with T2D (Fig. 1). Missing responses in the PQ led to missing SF12 summaries in 1062 patients. Non respondents to PQ and those with missing SF12 were older than the respondents (65.4 years (SD 14.3) vs. 63.8 years (SD 10.8), p < 0.0001), and more often women (48.1% vs. 39.4%, p < 0.0001) and had a lower rate of treatment of insulin alone (14.7% vs. 7.4%) mainly due to the exclusion of subjects with type 1 diabetes. A full-filled MQ was available in 1670 (59%) patients. These latter were more often men ( p < 0.001) and of similar age than those without a fullfilled MQ (type 1 excluded). The main characteristics of the ENTRED patients with type 2 diabetes and with completed SF summaries are presented in Table 1. Among them, 41% were obese, diabetes duration was longer than 20 years in 17%, 21% were on insulin, alone or in combination with OHA; severe hypoglycaemia were reported by 8%, HbA1c was higher than 8% in 17% according to practitioners. Twelve percent of the patients reported to be not really or not at all satisfied about their social support. In the 2832 assessed patients mean MCS was 42.9/100 (SD 10.8, 95%CI [42.5–43.3]) and mean PCS was 40.9/100 (SD 10.5, 95%CI [40.5–41.3]). With older age, PCS decreased from 43.7 (10.3) in patients younger than 65 years to 33.9 (9.4) in those older than 80 years ( p < 0.001); on the contrary MCS were unchanged across ages. PCS and MCS were both lower in women than in men at any age (PCS: 38.8 (10.6) in women and 43.0 (10.1) in men, p < 0.001; MCS: 40.8 (10.8) in women and 44.8 (10.5) in men, p < 0.001). In the ENTRED type 2 diabetes population with available PQ, 31.5% reported they saw their own future with regards to diabetes with concern or great concern. More patients reported to be confident or very confident about they own future with diabetes when older than 80 years (74.2%) compared to those younger than 65 years (62.9%, p < 0.0001). Medical practitioners assessed their patient’s burden as very important or important in 31.6% of the cases. A non-significant trend of lower burden estimation by practitioners was seen according to increased patient’s age (MQ, n = 2232). They estimated as very important or important this burden in 33.2% of patients younger than 65 years and in 29.2% of those older than 80 years.

diabetes research and clinical practice 101 (2013) 226–235

229

8 926 adults Treated for diabetes in metropolitan France Mean age: 65y (SD 13.31)

Sex ratio M/F 1.21

N=4277 Patient Questionnaire Mean age: 64y (SD 12.66)

Sex ratio M/F 1.37 13.19% with insulin alone

N=4649 Non-respondents Mean age: 66y (SD 13.75)

Sex ratio M/F 1.08 11.59% with insulin alone

N=3894 Type 2 Diabetes Mean age: 65y (SD 11.07)

Sex ratio M/F 1.42 10.4% with insulin alone

N=2832 Subjects with completed SF12 Mean age: 64y (SD 10.83)

Sex ratio M/F 1.54 10.1% with insulin alone

N=275 Type 1 Diabetes

N=1062 Other subjects Mean age: 69y (SD 10.85)

Sex ratio M/F 1.14 11.3% with insulin alone

Fig. 1 – Flow chart of the subjects included in ENTRED 2007 study and participation to the assessment of HrQol.

3.1. Relationships between patients’ characteristics and SF-12 MCS and PCS Factors associated with lower MCS with adjustment for age and sex only, were income perceived as fair or low, inferior occupational categories, lower educational level, insulin treatment, longer diabetes duration, an history of severe hypoglycaemia, the response ‘‘don’t know’’ at the question of severe hypoglycaemia during the previous year, existing complications (macro or microvascular), IADL restriction, hospitalisation > 24 h during the previous year, HbA1c higher than 10%, and finally dissatisfaction for social support were found after adjustment on age and gender (Table 1). The same variables were associated with lower PCS plus BMI higher than 25 kg/m2 and HbA1c above 8%. Table 2 includes the results of 2 multivariate linear regression models for MCS associated factors. Model 1 and

Model 2 (with HbA1c classes within the subgroups of patients with MQ) confirmed the strong associations of lower rating of MCS with lower income, severe hypoglycaemic episodes, hospitalisation 24 h, IADL restriction, and low satisfaction for social support. Older age was associated with higher MCS but the relationship was weak. HbA1c 8.1–10.0% range was associated with weaker MCS values. The list of factors associated with lower value of PCS summaries is different (Table 3). Older age, female sex, higher BMI, lower income, insulin treatment, macrovascular complications, severe hypoglycaemic episodes, hospitalisation 24 h, IADL restriction were associated with lower PCS values and no need for social support with higher PCS values. In the Model 2, no relationship appeared between PCS and HbA1c. The strongest association was found for perceived income and for IADL autonomy.

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diabetes research and clinical practice 101 (2013) 226–235

Table 1 – Characteristics of patients with type 2 diabetes with completed SF-12 summaries and linear regression adjusted on age and sex for the influence of each factor on MCS and PCS scores. ENTRED metropolitan France 2007 (n = 2832). n

(%)

MCS beta

Age mean (SD) Male sex Education levela No schooling or less than 4 years Primary school level (reference) Short secondary school level Long secondary school level University level Incomea Comfortable Fine (reference) Fair Difficult to achieve Debts are necessary to achieve Occupational activitya Farmers, skilled workmen, store keepers and company managers Executive and superior intellectual professions Intermediary professions (reference) Employees Workers Housewife (or men) or who had never work Body Mass Index mean (SD)a

1715

p

beta

(13.8) (29.3) (32.4) (10.3) (14.2)

2.11 0.00 1.76 2.55 3.04

264 1066 842 495 117

(9.5) (38.3) (30.2) (17.8) (4.2)

2.36 0.00 3.51 7.77 11.31

(12.3) (10.2) (20.3) (23.3) (27.7) (6.2)

0.68 0.84 0.00 1.59 2.11 2.00

511 1093 1137

(18.6) (39.9) (41.5)

0.00 0.27 0.57

814 651 773 463

(30.1) (24.1) (28.6) (17.1)

0.00 0.68 1.24 2.40

2245 302 285

(79.3) (10.7) (10.0)

0.00 2.36 3.51

235 2533 35 7.1  1.2

(8.4) (90.4) (1.2)

6.21 0.00 7.36

543 343 434 224 46 754 703

(34.1) (21.6) (27.3) (14.1) (2.9) (27.4) (26.1)

0.00 1.00 1.36 0.65 6.70 3.83 3.02

1974 224 624 2492

(70.0) (7.9) (22.1) (66.2)

0.00 1.15 3.48 8.72

1498 634 236 92 275

(54.8) (23.2) (8.6) (3.4) (10.0)

3.82 0.00 2.51 8.50 4.86

<.0001 0.0013 0.0009 0.0005 <.0001 <0.0001 0.0007 <.0001 <.0001 <.0001 0.0006 0.3709 0.2982 0.0208 0.0005 0.0539

2.63 0.00 0.98 2.07 3.74 1.87 0.00 3.78 7.73 10.83 0.96 1.07 0.00 2.15 3.34 3.71

0.5802 <25 kg/m2 (reference) 25–29 kg/m 2 30 kg/m 2 Diabetes durationa 4 years (reference) 5–9 years 10–19 years 20 years Diabetes treatment during the previous 3 monthsc Oral Hypoglycaemic Agents (OHA) (reference) Insulin and OHA Insulin At least one severe hypoglycaemic episode during previous yeara Yes No Don’t know Last HbA1c (mean  SD)b

0.6323 0.3151 0.0026 0.2220 0.0231 0.0002 <.0001 0.0003 <.0001 <.0001 <.0001 <.0001

a b c

Data issued from the patient questionnaire. Data issued from the medical questionnaire. Data issued from the national health insurance database.

0.1670 0.0449 0.4368 <.0001 <.0001 <.0001 <.0001 0.1218 <.0001 <.0001 <.0001 <.0001 0.0014 <.0001 <.0001

<.0001 <.0001 0.04 0.002 <.0001 <.0001 0.004 <.0001 <.0001 <.0001 <.0001 <.0001 0.17 0.15 0.0007 <.0001 0.0001 <.0001

0.00 1.23 4.34 0.00 1.28 1.16 2.98 0.00 4.39 4.38 6.91 0.00 6.83

0.02 <.0001 <.0001 0.0135 0.0217 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.02

0.0008 6.5% (reference) 6.6–7% 7.1–8% 8.1–10% >10% Macrovascular complications (yes)a Microvascular complications (yes)a Hospitalisation during the previous yearc None (reference) Stay < 24 h Stay  24 h IADL autonomy (yes)a Satisfaction with social supporta Very satisfied Rather satisfied (reference) Not really satisfied Not satisfied at all Don’t need help

p

63.8 (10.8) 60.6

383 812 896 284 393

317 263 524 601 716 159 29.6 (5.4)

PCS

0.00 1.09 0.78 1.88 3.92 6.00 4.35 0.00 1.94 5.12 11.56 2.96 0.00 0.54 3.88 4.64

0.10 0.21 0.01 0.009 <.0001 <.0001 <.0001 0.005 <.0001 <.0001 <.0001 <.0001 0.5 0.0004 <.0001

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diabetes research and clinical practice 101 (2013) 226–235

Table 2 – Factors associated with quality of life MOS SF-12 mental component summary scores (MCS) in patients with type 2 diabetes. Multivariate analysis. ENTRED metropolitan France 2007. Model 1 n = 2336

Intercept Age Female sex Education levela No schooling or less than 4 years Primary school level (reference) Short secondary school level Long secondary school level University level Incomea Comfortable Fine (reference) Fair Difficult to achieve daily living Debts are necessary to achieve daily living Diabetes durationa 4 years 5–9 years 10–19 years 20 years Diabetes treatment during the previous 3 monthsc

beta

p

beta

p

38.62 0.04 0.95

<0.0001 0.04 0.03 0.08 0.6 – 0.015 0.04 0.04 <0.0001 0.09 – <0.0001 <0.0001 <0.0001 0.80 – 0.47 0.78 0.40

38.05 0.07 0.78

0.00 1.58 0.95 1.48

<0.0001 0.01 0.17 0.2 0.7 – 0.03 0.2 0.10 <0.0001 0.5 – <0.0001 <0.0001 <0.0001 0.12 – 0.0245 0.19 0.09

0.00 0.2 0.7

0.77 – 0.8 0.5

0.37 0.00 1.25 1.49 1.34 1.22 0.00 2.37 4.57 7.65 0.00 0.39 0.15 0.54

0.13 – 0.5 0.09

0.00 Oral hypoglycaemic agents (OHA) (reference) 0.48 Insulin and OHA Insulin 1.18 At least one severe hypoglycaemic episode during the previous yeara Yes No (reference) Don’t know Macrovascular complications (yes)a Microvascular complications (yes)a Hospitalisation during the previous yearc None (reference) One stay < 24 h At least one stay  24 h IADL autonomy (yes)a Satisfaction with social supporta Very satisfied Rather satisfied (reference) Not really satisfied Not satisfied at all Don’t need help HbA1cb 6.5% (reference) 6.6–7% 7.1–8% 8.1–10% >10% R2 (%)

Model 2 n = 1329

0.002 0.0022 – 0.05 0.1 0.7 0.009 – 0.9 0.002 <0.0001 <0.0001 <0.0001 – 0.003 <0.0001 <0.0001

2.24 0.00 3.39 0.76 0.20 0.00 0.06 1.51 5.45 3.13 0.00 2.29 5.84 2.97

0.29 0.00 1.49 1.19 1.43 0.70 0.00 2.95 3.81 8.47

1.95 0.00 4.41 1.39 0.03 0.00 0.06 1.78 5.12 2.96 0.00 2.30 5.53 3.14 0.00 0.70 0.12 1.70 2.78 23.6

25.4

0.03 0.0409 – 0.08 0.03 1.0 0.02 – 0.9 0.007 <0.0001 <0.0001 <0.0001 – 0.02 0.0005 0.002 0.03 – 0.3 0.9 0.04 0.11

Non significant variables remain in the model if they are confusing factors. a Data issued from the patient questionnaire. b Data issued from the medical questionnaire. c Data issued from the national health insurance database.

4.

Discussion

The factors associated with lower scores of HrQol summaries in French patients with type 2 diabetes are multiple, in relation

with socio-economic conditions, social support, diabetes complications, disability and social participation restriction. The effect of current blood poor glucose control is somewhat weak and seen only for mental and not physical HrQol, and diabetes duration had no impact on HrQol after adjustment.

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diabetes research and clinical practice 101 (2013) 226–235

Table 3 – Models of multivariate analysis of factors associated to with quality of life MOS SF-12 physical component summary scores (PCS) in patients with type 2 diabetes. ENTRED metropolitan France 2007. Model 1 n = 2175

Intercept Age Female sex Body Mass Indexa <25 kg/m2 (reference) 25–29 kg/m 2 30 kg/m 2 Education levela No schooling or less than 4 years Primary school level (reference) Short secondary school level Long secondary school level University level Occupational activitya Farmers, skilled workmen, store keepers and company managers Executive and superior intellectual professions Intermediary professions (reference) Employees Workers Housewife (or men) or who had never work Incomea Comfortable Fine (reference) Fair Difficult to achieve daily living Debts are necessary to achieve daily living Diabetes treatment during the previous 3 monthsc Oral hypoglycaemic agents (OHA) (reference) Insulin & OHA Insulin At least one severe hypoglycaemic episode during the previous yeara Yes No (reference) Don’t know Macrovascular complications (yes)a Microvascular complications (yes)a Hospitalisation during the previous yearc None (reference) One stay < 24 h At least one stay  24 h IADL autonomy (yes)a Satisfaction with social supporta Very satisfied Rather satisfied (reference) Not really satisfied Not satisfied at all Don’t need help HbA1cb 6.5% (reference) 6.6–7% 7.1–8% 8.1–10% >10% R2 (%) Non significant variables remain in the model if they are confusing factors. Data issued from the patient questionnaire. b Data issued from the medical questionnaire. c Data issued from the national health insurance database. a

Model 2 n = 1231

beta

p

beta

p

53.41 0.20 1.59

<.0001 <.0001 0.0005 <.0001 – 0.13 <.0001 0.2 0.9 – 0.5 0.8 0.02 0.6 0.6 0.3 – 0.5 0.5 0.6 <.0001 0.1 – <.0001 <.0001 <.0001 0.01 – 0.03 0.02

53.23 0.19 2.33

<0.0001 <0.0001 0.0001 0.0002 – 0.4 0.0006 0.1 0.8 – 0.8 0.5 0.05 0.8 1.0 0.1 – 0.8 0.2 0.5 <0.0001 0.4 – 0.0009 <0.0001 0.002 0.03 – 0.09 0.02

0.00 0.74 2.61 0.04 0.00 0.34 0.17 1.65 0.32 0.77 0.00 0.39 0.35 0.49 1.01 0.00 1.79 2.97 5.19 0.00 1.28 1.45

2.26 0.00 3.21 2.56 0.36 0.00 0.97 2.00 8.65 1.84 0.00 0.90 0.95 1.72

41.7

0.0006 0.0006 – 0.05 <.0001 0.4 <.0001 – 0.1 <.0001 <.0001 <.0001 <.0001 – 0.2 0.3 0.01

0.00 0.53 2.29 0.20 0.00 0.16 0.59 1.77 0.20 1.27 0.00 0.22 1.04 0.51 0.76 0.00 1.90 3.62 4.20 0.00 1.29 2.02

1.69 0.00 0.02 2.76 0.12 0.00 0.14 1.97 8.62 1.38 0.00 1.08 1.47 2.59 0.00 0.63 0.04 0.52 1.05 40.0

0.15 0.05 – 1.0 <0.0001 0.8 0.0023 – 0.9 0.0007 <0.0001 0.0007 0.02 – 0.2 0.30 0.004 0.6 – 0.3 0.9 0.5 0.5

diabetes research and clinical practice 101 (2013) 226–235

According to age and sex, trends for SF-12 summaries in ENTRED are similar than in general French population: age has a strong effect on physically oriented items; women have at any age lower scores than men for mental and physical summaries. Audureau and colleagues [5] have shown a decrease in mental health in people older than 65 years compared with the youngest, which is not seen in our sample. In T2DM people from ENTRED, few were younger than 45 years and thus, our population is not comparable to the general population of age 18–65 years. Diabetes disease seems to have a premature ageing effect, particularly on physical related items [22]. Our results confirm that the negative impact of diabetes and disease-associated factors such as obesity occurs mainly on the physical domain of HrQol [6]. This study has some limitations, however. This study is cross-sectional and causality links cannot be ascertained here. The response rate to the patient questionnaire may have selected patients with characteristics linked to the HrQol. In particular, the oldest and the women were less represented in the SF-12 responders than in the ENTRED responders. ENTRED responders were also younger and more often men than ENTRED non-responders. It is also likely that non-responders to the ENTRED study were more often disabled or with less social support than responders because the more disabled patients may have needed help to fill the questionnaire or have not answered. A specific tool for HrQol assessment in older and disabled populations with diabetes may be preferentially used [23]. The response rate of practitioners was also lower in women. It is thus probable that we have overestimated the HrQoL of ENTRED study participants. The SF-12 reproduces the eight-scale profile with fewer levels than SF-36 scales and yields less precise scores, as would be expected for single-item and two-item scales. For large group studies, these differences are not as important, because confidence intervals for group averages in health scores are largely determined by sample size. However, ENTRED included a large number of patients and despite the attrition rate, the final number of patients with full HrQol measures remains high and allows powerful analysis. We recognise that socio-economic factors are important modulators of HrQol. Population-based studies have shown that people with diabetes have a lower educational level and lower income than other patients [24,25]. The perception of income was related to MCS summaries with equivalent strength (beta coefficients) as IADL disability and satisfaction for social support. The figure for PCS summaries showed also a similar strength of income perceived as fair (beta 1.90) than factors such as severe hypoglycaemia (beta 1.69), and macrovascular complications (beta 2.76). Thus, people with T2DM are particularly at risk to have impaired HrQol in part due to these socio-economic factors which are not modifiable by medical intervention. IADL autonomy is a very important factor in quality of life, in both mental and physical domain with the highest beta coefficient of the analysed variables along with the income category ‘‘debts are necessary to achieve’’. The diabetes-related items are also determinant factors of HrQol. Occurrence of hypoglycaemia is associated with impairment of HrQol but is usually associated to other factors of impaired HrQol [26,27]. Diabetes complications and

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hypoglycaemia had a greater impact than treatment itself on mental or physical domains in the ENTRED study similarly to the observations made in UKPDS cross-sectional or longitudinal study [15]. We have recently observed in older people that hypoglycaemia occurred more often in people with complications and in the highest and lowest ranges of HbA1c independently of treatment [28]. However, in the ENTRED study, the impact of hypoglycaemic episodes on mental and physical health remained strong after adjustment on complications. HbA1c in the 8.1–10.0% range was associated with low mental quality of life after multiple adjustments, suggesting that lowering blood glucose can lead to a beneficial effect. A longitudinal study has shown in subjects with uncontrolled diabetes (HbA1c > 7%, mean 8.8%) an association between improvement of HbA1c using insulin therapy and emotional well-being [29] encouraging efforts to improve blood glucose control. A multifactorial combined 12 month intervention in a young population with diabetes in 85% of them and/or coronary heart disease was able to decrease the rate of disability and to improve quality of life. This intervention was not blind and focused on blood pressure, blood glucose, LDL cholesterol correction and on the treatment of depression [30]. On the other hand, another interventional study has shown that decreasing the level of HbA1c had no impact on HrQoL after adjustment on other diabetes related characteristics [31]. Physical activity also seems efficient in the prevention of hospitalisation and in improving the quality of life in both domains as previously shown [32–35]. The position that the patient takes when faced with the condition of diabetes and the health system may also be determining factors. Better HrQol, in physical and mental domains may be associated with the feeling of being able to manage one’s life by oneself [36]. The older participants of ENTRED did not consider diabetes as associated with a great burden, in accordance with practitioners’ perception. This was in line with better MCS scores associated with older age in our participants. A study has shown similar results and subsequently less aggressive treatment in those with lower life expectancy [37]. Patients’ trust in their physician was shown to be associated with better self-efficacy and outcomes expectations, themselves associated with better HrQol and with objective health outcomes in relation with diabetes, but with less strength [38]. The participation of the patient in the choice of goals for treatment may improve their HrQol particularly in frail and older patients with diabetes [16]. A diabetes case manager may also improve the efficiency of complications and disability prevention. He/she may take on the responsibility of the medical practitioner for therapeutic education and then improve blood glucose control [39]. Correspondingly, disease management programmes in primary care have been associated with better HrQol, particularly in subjects with comorbid conditions [3]. Patients requiring social support in the ENTRED study had lower mental HrQol scores. In contrast, carers of older subjects with diabetes are likely to experience stress which is related to the needs of their relatives [40]. They lack knowledge and may respond positively to diabetes educational programme devoted to carers. It is recommended that clinicians adapt goals of management to important factors as life expectancy, patient’s

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diabetes research and clinical practice 101 (2013) 226–235

motivation, comorbidity and complications, hypoglycaemia risk, resources and diabetes duration [41]. There is also a large consensus to assess older people for frailty in order to provide efficient and safer treatments [42–44]. The results of this patient-centred strategy on HrQol should be tested in patients with diabetes on the basis of the spectrum of HrQol-associated factors shown in this work.

Scientific committee ENTRED C. Attali, C. Avril, M. Besnier, J. Bloch, I. Bourdel-Marchasson, M. Chantry, B. Detournay, E. Eschwe`ge, A. Fagot-Campagna, S. Fosse, A. Fontbonne, C. Fournier, A. Gautier, S. Halimi, P. Lecomte, A. Paumier, A. Penfornis, N. Poutignat, I. Romon, C. Roudier, A. Rudnichi, D. Simon, M. Varroud-Vidal, P. Vexiau, A. Weill.

Funding The analysis of HrQol in the ENTRED study has been funded by French Institute of Health Monitoring, (Institut de veille sanitaire, InVS).

Conflict of interest The authors declare that they have no conflict of interest.

Author contribution I. Bourdel-Marchasson has participated in the ENTRED study questionnaire construction, has planned the HrQoL analysis and has written the paper. C. Druet is the head of the diabetes department of InVs and has contributed to the interpretation of data and to the writing of the paper. C. Helmer has monitored the statistical analysis and has contributed to the interpretation of data and to the writing of the paper. E. Eschwege, P. Lecomte and A.J. Sinclair have contributed to the interpretation of data and to the writing of the paper. M. LeGoff has realised the statistical analysis. A. Fagot-Campagna is the head of ENTRED study, has contributed to the interpretation of data and to the writing of the paper.

Acknowledgements Fundings of Entred 2007 study came from the French Institute of Health Monitoring, (Institut de veille sanitaire, InVS), The French National Health Insurance service (Caisse Nationale de l’Assurance Maladie CnamTS), the Health Insurance System for independent workers (Re´gime des Salarie´s Inde´pendants, RSI), the French National Institut for Prevention and Health Education (Institut national de pre´vention et d’e´ducation pour la sante´, Inpes), and the French Health Authority (Haute Autorite´ de Sante´ HAS). The people with diabetes and their medical practitioners are here warmly thanked.

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