Journal of Diabetes and Its Complications xxx (2014) xxx–xxx

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Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups M. Schunk a, P. Reitmeir a, S. Schipf b, H. Völzke b, C. Meisinger c, K.-H. Ladwig c, A. Kluttig d, K.H. Greiser d, e, K. Berger f, G. Müller f, U. Ellert g, H. Neuhauser g, T. Tamayo h, W. Rathmann h, R. Holle a a

Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany Institute for Community Medicine, Ernst Moritz Arndt-University, Greifswald, Germany c Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany d Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany e German Cancer Research Centre, Division of Cancer Epidemiology, Heidelberg, Germany f Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany g Department of Epidemiology and Health Reporting, Robert-Koch-Institute, Berlin, Germany h Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University, Düsseldorf, Germany b

a r t i c l e

i n f o

Article history: Received 28 July 2014 Received in revised form 11 November 2014 Accepted 17 November 2014 Available online xxxx Keywords: T2DM HRQL Treatment Gender SF-12

a b s t r a c t Aim: This study compares health-related quality of life (HRQL) in patients with type 2 diabetes (T2DM) across treatment groups and explores gender differences. Methods: Four regional surveys (KORA, CARLA, SHIP, DHS) and a national survey (GNHIES98) were pooled at individual level. HRQL was assessed with the SF-12/-36v1. Linear regression models were used to assess the effect of T2DM by treatment type (no medication; oral; oral/insulin combination; insulin) on the physical (PCS-12) and mental summary score (MCS-12) and the SF-6D, controlling for age, sex, study and covariates. We also performed an explanatory analysis of single items. Results: PCS-12 scores and treatment type were associated (P-value 0.006), with lowest values for insulin treatment (–4.44 vs. oral; –4.41 vs. combination). MCS-12 scores were associated with treatment type and gender (P-value b0.012), with lower scores for women undergoing oral (–4.25 vs. men) and combination treatment (–6.99 vs. men). Similar results were observed for SF-6D utilities and single items, related to mental health, social functioning, vitality and role limitation (emotional). Comorbidities were predictors of lower PCS-12 and SF-6D scores. Conclusions: T2DM treatment impacts differently on physical and mental HRQL and on women and men. Further studies of gender-specific perceptions of T2DM treatment regimens are needed. © 2014 Elsevier Inc. All rights reserved.

1. Introduction Type 2 diabetes mellitus (T2DM) is a major chronic illness, which currently affects 8.3% of people of all ages worldwide with an expected increase in incidence over the next decades (IDF, 2011). The high prevalence of comorbidities, such as cardiovascular diseases and neuropathy, and late stage complications such as amputation, blindness and dialysis imposes large physical and psychological burdens for those with T2DM (Fisher, Thorpe, Devellis, & Devellis, 2007; Karlsen, Oftedal, & Bru, 2012). At all stages of the disease, treatment is coupled with a substantial amount of self-management tasks such as measuring blood glucose, monitoring of feet and weight, medication, regular medical check-ups as well as lifestyle changes to adopt healthy eating habits and increase physical activity (Funnell & Anderson, 2004; Nefs, Bot, Browne, Speight, & Pouwer, 2012). Onset of Conflict of interest: Competing Interests Nothing to declare.

diabetes-related secondary illness can be perceived as failure to perform well enough in these tasks (Peyrot et al., 2005). Health-related quality of life (HRQL) instruments are tools to measure patient-oriented outcomes in clinical epidemiology and health service research. Generic HRQL comprises the ability to function in everyday life, taking account of dimensions of physical and mental well-being that are considered to be relevant to all adults, irrespective of age, sex and health status. Psychometric instruments, such as the SF-36 (from which the SF-12 is derived), aim to assess generic HRQL as a multidimensional construct, generating a profile for each individual. Preference-based instruments, such as the EQ-5D or the SF-6D, draw on health states being valued using econometric methods and summarize HRQL as a single value, often referred to as an index. These index values offer the opportunity for economic evaluation to calculate quality-adjusted life–years (QALYs). Both types of instrument are widely used, but the instruments' heterogenic nature causes constraints for the

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Please cite this article as: Schunk, M., et al., Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups, Journal of Diabetes and Its Complications (2014), http://dx.doi.org/10.1016/j.jdiacomp.2014.11.010

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M. Schunk et al. / Journal of Diabetes and Its Complications xxx (2014) xxx–xxx

comparison of results across studies (Brazier, Yang, Tsuchiya, & Rowen, 2010; Valderas & Alonso, 2008). The loss of HRQL in T2DM patients has been quantified by a number of studies across different instruments in relation to both people without T2DM and other disease groups (Glasgow, Ruggiero, Eakin, Dryfoos, & Chobanian, 1997; Landman et al., 2010a; Maddigan, Feeny, Majumdar, Farris, & Johnson, 2006; UKPDS, 1999). We have previously analysed differences in HRQL in those with and without T2DM in a large population-based sample in Germany (aged 45–74 years). Measured using the SF-12 physical and mental health summary scores (PCS-12 and MCS-12), T2DM was associated with a decline in PCS-12 equal to a detriment of 20 years of age. In MCS-12, the T2DMassociated decline was only significant for women (Schunk et al., 2012). Restricting our sample to people with T2DM, this paper presents more detailed analysis to follow earlier findings. We compare the loss of HRQL in T2DM patients across treatment types which denote increasing treatment intensity (no medication, oral anti-diabetic agents (OAD) only, insulin treatment or a combination of OAD and insulin) and look at the results of both the psychometric scales (PCS-12 and MCS-12) and the econometric measure SF-6D in order to see whether the restriction of health states necessary for SF-6D valuation has compromised the sensitivity of the original profile instrument and to make our results comparable with a wider range of other studies. Comparisons of HRQL across different types of diabetes treatment have rarely been undertaken, although treatment types reflect different stages of the disease, differences in the risk of tolerability issues and in the complexity of treatment regimens. For example, there is a higher risk of hypoglycemic episodes with treatment regimens including insulin. Episodes of uncontrolled diabetes may also evolve from failure to adhere to complex medication regimes. Previous studies primarily focused either on the relationship between HRQL and one treatment type (or different drugs within one treatment type) (Mohamed et al., 2013; Pollack, Purayidathil, Bolge, & Williams, 2010) or on changes in HRQL following the switch to insulin treatment or intensified insulin therapy in patients with insufficiently controlled blood glucose (Anderson et al., 2011; Hajos et al., 2012; Reza, Taylor, Towse, Ward, & Hendra, 2002; Secnik Boye et al., 2006). Onset of medication (usually OADs as first line treatment) as well as switches to insulin therapy (either insulin only or in combination with OADs) may indicate that the disease is not well controlled and induce fears related to disease progression. Although some evidence pointed to an inverse association of increasing treatment intensity and HRQL, results have been mixed, and studies have used small clinical samples (Fisher et al., 2007; Rubin & Peyrot, 1999). Caution must be applied to control for the impact of comorbidities and complications when looking at effects of intensified treatment regimens on HRQL (Zhang, Norris, Chowdhury, Gregg, & Zhang, 2007). Our pooled analysis of five population-based studies across Germany has a sufficiently large sample size to compare treatment groups while controlling for variables such as cardiovascular comorbidities, clinical characteristics and socioeconomic and lifestyle factors associated with HRQL, delineated as HRQL determinants in respective models for the general population and for T2DM patients (Bakas et al., 2012; Ferrans, Zerwic, Wilbur, & Larson, 2005; Rubin & Peyrot, 1999). In addition, the potential effect modification of treatment effects on HRQL by gender has not been studied so far. Studies including our own have shown that the HRQL loss with T2DM is higher for women than for men, in particular with regard to the mental health domain (Rubin & Peyrot, 1999; Schunk et al., 2012). Studies have pointed at the vulnerability of women with regard to fears related to disease progression and weight gain (Kacerovsky-Bielesz et al., 2009; Whale, Gillison, & Smith, 2013). Thus, increasing treatment intensity may induce such fears and therefore affect women more than men. Furthermore, deficits have been found in the quality of diabetes care as well as in the control of cardiovascular risk factors regarding the treatment of women (Bird et al., 2007; Yu, Lyles,

Bent-Shaw, & Young, 2013). These may contribute to lower HRQL in women with T2DM because they enhance diabetes-related symptoms and deficits in functioning. We will assess these gender differences, using the descriptive breadth provided by all 12 single items, to show which health outcomes are particularly exposed to gender differences across different T2DM treatment groups. The objectives of this study are to: 1) compare HRQL, measured using the two SF-12 summary scales (PCS-12 and MCS-12) and SF-6D utility values, across different types of diabetes treatment; and 2) explore gender-associated differences in HRQL, as measured by SF-12 single items, across different types of diabetes treatment. We hypothesize that increasing treatment intensity leads to a higher loss of HRQL because of a higher likelihood of medication-related tolerability issues, adherence problems and fears with regard to disease progression. We further hypothesize that increasing treatment intensity leads to a higher loss of HRQL in women compared to men because of a lack of support to their specific needs, both on a societal level and on the level of the health care system. 2. Methods 2.1. Study design Drawing on data from national and regional population-based surveys, this analysis was part of the DIAB-CORE (Diabetes Collaborative Research of Epidemiological Studies) research consortium, which investigates T2DM in Germany. Four regional surveys (KORA, CARLA, SHIP and DHS) and a national survey (GNHIES98) were comparable in their assessment of HRQL and are included in the subsequent analysis. The studies were conducted between 1997 and 2006. Overall response proportions ranged between 61% and 69%. A detailed description of the study design and the included surveys is available elsewhere (Schunk et al., 2012). Ethical approval from designated research ethics committees was obtained for each study. The primary data from the studies were pooled at individual level, using a homogenized script for all basic variables to ensure a high degree of comparability. Only the age group 45–74 years was included, because this was covered by all studies. T2DM was defined based on self-reported physician diagnosis. Lacking information on the type of diabetes across all studies, people with an age at onset of diabetes of ≤ 30 years were excluded. Cases with any missing values in the SF-12 were excluded. 2.2. Definition of variables HRQL was assessed with the German version of the 12-item short form Health Survey (SF-12, version 1) in three of the studies. Two studies (GNHIES98, DHS) administered the SF-36 (version 1), from which the SF-12 was derived. All except one study (KORA), where it was part of the face-to-face interview, applied the SF-12/-36 as a selfadministered questionnaire at the study centre. We calculated the PCS12 and MCS-12 using a standard algorithm (Bullinger & Kirchberger, 1998). The scores are norm based (mean = 50; SD = 10) with higher values indicating better HRQL. The SF-6D draws on a subset of SF-12 items and provides a single index value for health status, using preference-based utility weights. Although health utilities theoretically range between 0 (health state similar to death) and 1 (‘perfect health’), possible values of the SF-6D index lie between 0.345 and 1 (Brazier, Roberts, & Deverill, 2002). Lacking the availability of respective German data, the valuation is based on a British population sample and can be used here only in an exploratory way. For the single item analysis, items were coded as follows: item 1 followed a five-answer scheme (‘good’, ‘very good’ and ‘excellent’ were coded as positive; ‘fair’ and ‘poor’ were coded as negative). Items 2 and 3 followed a three-answer scheme (‘yes, limited a lot’ and ‘yes, limited a little’ were coded as negative; ‘no, not limited at all’ was

Please cite this article as: Schunk, M., et al., Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups, Journal of Diabetes and Its Complications (2014), http://dx.doi.org/10.1016/j.jdiacomp.2014.11.010

(16.2) (21.1) (27.4) (16.4) (12.6) (17.4) 22 47 20 26 32 147 17 (12.5) 18 (8.1) 8 (11.0) 26 (16.4) 24 (9.5) 93 (11.0) (57.4) (46.2) (43.8) (48.4) (49.6) (49.2) 78 103 32 77 126 416 (14.0) (24.7) (17.8) (18.9) (28.4) (22.4) 19 55 13 30 72 189 8.5 (6.9) 9.1 (7) 7.5 (6.4) 8.9 (7.6) 8.1 (7.2) 8.5 (7.1) (6.8) (7.5) (8.5) (7.4) (6.7) (7.2) 63.1 62.6 64.1 63.4 62.6 63 (44.9) (50.9) (45.2) (43.4) (48.4) (47.3) 61 114 33 69 123 400 1999–2001 2000–2003 2003–2004 2002–2006 1997–1999 1997–2006 Cooperative Health Research in the Region of Augsburg Survey 4 (KORA S4) Study of Health in Pommerania (SHIP 0) Dortmund Health Study (DHS) Cardiovascular disease, Living and Ageing in Halle (CARLA) GNHIES 98: German National Health Interview and Examination Survey 1998 Total sample

136 (16.1) 224 (26.5) 73 (8.6) 159 (18.8) 254 (30.0) 846

Study period Study name

Table 1 Sample description.

T2DM (N, % of Women total sample) (N, %)

Age (years) at Diabetes duration No anti-diabetic Oral anti-diabetics OAD + insulin Insulin examination mean (SD) (years) mean (SD) medication (N, %) (OAD) (N, %) (N, %) (N, %)

M. Schunk et al. / Journal of Diabetes and Its Complications xxx (2014) xxx–xxx

3

coded as positive). Items 4–7 were dichotomized (yes was coded as negative; no was coded as positive). Item 8 followed a five-answer scheme (‘not at all’ and ‘a little bit’ were coded as positive; ‘moderately’, ‘quite a bit’ and ‘extremely’ were coded as negative). Items 9 and 10 followed a six-answer scheme (‘all of the time’, ‘most of the time’ and ‘a good bit of time’ were coded as positive; ‘some of the time’, ‘a little of the time’ and ‘none of the time’ were coded as negative). Items 11 and 12 followed the same answer scheme, but positive and negative were coded in the opposite way. Study participants were asked in the surveys' interview sections in which year they had been diagnosed (diabetes duration) and which type of treatment they were receiving at the moment. We combined the answers to treatment type into four categories: (1) no antidiabetic medication (‘no medication’); (2) OAD; (3) combination of OAD and insulin (‘combination’); and (4) insulin only. Socioeconomic information was assessed as years of schooling, income and household status. Education was treated as a categorical variable with three levels (primary, secondary and tertiary education). Income was transformed to equivalent income using a formula from the Luxembourg Income Study adapted for the DIAB-CORE studies (Maier et al., 2013). Living alone (yes vs. no) was based on information regarding household size. Information on comorbidities followed survey questions if myocardial infarction or stroke had ever been diagnosed or was being treated in hospital, and if a doctor had ever diagnosed hyperlipidaemia and hypertension. Weight and height were measured at the study centre and calculated as body mass index (BMI; weight in kg divided by the squared height in metres), classified in groups according to the WHO (normal weight: 18.5 ≤ BMI b 25; pre-obesity: 25 ≤ BMI b 30; moderate obesity (i.e. obesity class 1): 30 ≤ BMI b 35; severe obesity (i.e. obesity class 2): 35 ≤ BMI b 40; very severe obesity (i.e. obesity class 3): BMI ≥ 40 kg/m 2) (WHO, 2002). Lifestyle variables included physical activity (b 1 hour per week), alcohol (N40 g/day for men; N20 g/day for women) and smoking (current, former, never). 2.3. Statistical analysis Linear regression models were used to assess the effect of the exposure variable, T2DM by treatment type, on the PCS-12, MCS-12 and SF-6D scores, controlling for age, sex, study and covariates. Furthermore, to adjust for sex-dependent treatment effects, an interaction term for sex by treatment was added to all models. For categorical variables, only P-values for testing overall group differences are reported. For the single item analyses, binary outcome variables were coded as described, and logistic regression models were calculated for each item. Adjusted means and adjusted prevalence are reported for combined sex and treatment type groups. P-values b 0.05 are regarded as statistically significant. Analyses were performed using SAS statistical software 9.3. 3. Results Characteristics of the study population are shown in Table 1. Sample size was 846 people; 91 people were excluded because of missing values in the SF-12. Mean age at examination was 63 years, and mean diabetes duration was 8.5 years. Women accounted for 47% of the sample. With regard to treatment type, 22% reported no medication, 49% OAD only, 17% insulin treatment and 11% a combination of OAD and insulin. With longer diabetes duration, the numbers receiving no medication decreased from 37% (diabetes duration 0–2 years) to 12% (more than 16 years) and with OAD treatment from 59% to 28% (Fig. 1). Correspondingly, the proportion receiving insulin treatment increased from 3% (diabetes duration 0–2 years) to 34% (more than 16 years) and from 1% to 26% for the combination treatment.

Please cite this article as: Schunk, M., et al., Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups, Journal of Diabetes and Its Complications (2014), http://dx.doi.org/10.1016/j.jdiacomp.2014.11.010

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M. Schunk et al. / Journal of Diabetes and Its Complications xxx (2014) xxx–xxx

100% 90% No Antidiabetic

80%

Medication

70%

Oral

60% Oral+Insulin

50% Insulin

40% 30% 20% 10% 0% 0-2 years

3-5 years

6-10 years

11-15 years

+16 years

Fig. 1. Treatment type by diabetes duration (total sample).

The results from the regression analysis (Table 2) show that the PCS-12 was significantly associated with treatment type (P-value 0.006), with the lowest estimates for those on insulin treatment (–1.66 score points), compared with the group with no anti-diabetic

medication. Those with oral treatment and combination treatment had higher PCS-12 estimates (2.78 and 2.75 score points, respectively). Furthermore, myocardial infarction (–4.09 score points; P-value b 0.001), stroke (–4.41 score points; P-value 0.002) and hypertension

Table 2 Regression model—PCS-12, MCS-12 and SF6D scores.

Intercept Study (ref.: GNHIES98) § CARLA DOGS KORA SHIP Treatment type (ref.: no anti-diabetic medication) § Oral anti-diabetics (OADs) OAD/insulin combination Insulin Sex (ref.: men) § Sex and treatment (ref. men, no anti-diabetic medication) § Women and OADs Women and OAD/insulin combination Women and insulin Age Diabetes duration Education (ref.: ≥10 years) Equivalent income (ref.: more than 150% above median income) § Between median income and 150% above Between median income and 60% below Less than 60% of GNHIES 98 median income Living alone Myocardial infarction Stroke Hypertension Hyperlipidaemia BMI in groups (ref.: ≥18.5 and ≤24.9 kg/m2)§ BMI ≥25.0 and ≤29.9 kg/m2 BMI ≥30.0 and ≤34.9 kg/m2 BMI ≥35.0 and ≤39.9 kg/m2 BMI N =40.0 kg/m2 Alcohol (N40 g/day ♂; N20 g/day ♀) Low physical activity (less than 1 h/week) Smoking (ref.: never) § Current Former

Physical component score (PCS-12)

Mental component score (MCS-12)

SF-6D

Estimate

Estimate

Estimate

50.87

SE

P-value

3.97

43.85

SE

P-value

3.92

0.119 2.31 −1.30 1.27 1.93

1.12 2.57 1.20 1.00

2.78 2.75 −1.66 −0.48

1.23 1.82 1.70 1.54

−2.03 −2.71 0.11 −0.07 −0.05 −0.18

1.80 2.59 2.27 0.05 0.06 0.93

−0.82 0.03 −1.82 −1.42 −4.09 −4.41 −2.44 −1.40

1.37 1.39 1.59 0.93 1.15 1.40 0.81 0.77

−0.20 0.17 −2.13 −1.42 0.79 −2.28

1.31 1.35 1.58 1.87 1.55 0.85

0.08 −1.45

1.15 0.89

0.226 0.355 0.846 0.444

0.125 b.001 0.002 0.003 0.070 0.333

0.611 0.007 0.197

P-value

0.06

b.0001 0.023

0.04 −0.02 0.01 0.04

0.02 0.04 0.02 0.02

0.04 0.06 −0.01 −0.01

0.02 0.03 0.03 0.02

−0.05 −0.10 −0.01 0.00 0.00 0.00

0.03 0.04 0.04 0.00 0.00 0.01

0.00 0.00 −0.04 −0.03 −0.04 −0.04 −0.03 −0.03

0.02 0.02 0.02 0.01 0.02 0.02 0.01 0.01

0.01 0.02 −0.02 0.01 0.01 −0.01

0.02 0.02 0.02 0.03 0.02 0.01

0.01 −0.01

0.02 0.01

0.109 1.48 −0.63 −0.61 1.83

1.11 2.54 1.19 0.98

0.99 1.77 0.94 0.58

1.22 1.80 1.68 1.52

−4.83 −7.57 −3.91 0.14 −0.09 −0.35

1.78 2.56 2.25 0.05 0.06 0.92

0.42 −0.50 −2.88 −0.66 −0.32 0.40 −0.95 −1.05

1.36 1.38 1.57 0.91 1.14 1.38 0.80 0.76

0.80 1.79 0.28 1.11 1.69 0.06

1.30 1.34 1.56 1.85 1.53 0.84

1.20 0.77

1.14 0.88

0.006

0.087 0.491

SE

0.75

0.355

b.001 0.012

0.006 0.108 0.703 0.077

0.472 0.778 0.775 0.238 0.170 0.535

0.269 0.944 0.501

0.467

0.001 0.050

0.369 0.102 0.807 0.243

0.068 0.039 0.059 0.007 0.020 0.144

0.821 0.413 0.588

Estimates depend on reference group of interaction term—treatment groups by sex differences shown in Fig. 2 (adjusted LS means). § P-values for testing overall group differences.

Please cite this article as: Schunk, M., et al., Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups, Journal of Diabetes and Its Complications (2014), http://dx.doi.org/10.1016/j.jdiacomp.2014.11.010

M. Schunk et al. / Journal of Diabetes and Its Complications xxx (2014) xxx–xxx

49

58

PCS-12*

47

MCS-12*

56

45

54

43

52

41

50

39

48

37

46

35

44

33

42

31

5

40

No Antidiabetic Medication

Oral

Oral+Insulin

Insulin

Women Men

No Antidiabetic Medication

Oral

Oral+Insulin

Insulin

Women Men

*adjusted (least squares) LS means based on table 2 (adjusted for study, age, diabetes duration, education, equivalent income, living alone, myocardial infarction, stroke, hypertension, hyperlipidaemia, BMI, alcohol, physical activity, smoking) Fig. 2. a: PCS-12 scores (treatment type by sex). b: MCS-12 scores (treatment type by sex).

(–2.44 score points; P-value 0.003) were significantly associated with PCS-12. Of all the other covariates, only low physical activity was negatively related to PCS-12 (–2.28 score points; P-value 0.007). Adjusted means for treatment types by sex are shown in Fig. 2. Women and men have similar PCS-12 mean scores in the no medication and insulin groups. Men tend to have higher PCS-12 scores than women in the OAD and combination treatment groups, but these differences proved

General Health Status (Item 1) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Physical health limits certain work/activities 1 (Item 5)

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Performance of moderate activities of daily living (Item 2)a

Overall accomplishment related to emotional well being (Item 6)

Feeling calm and peaceful (Item 9) a

1

2

3

4

not to be significant (Fig. 2a). However, with regard to MCS-12 scores (Fig. 2b), differences between women and men associated with treatment type were significant (P-value b0.001). Compared with men receiving OAD and combination treatment, women had lower MCS-12 scores (49.0 vs. 53.3 for OAD treatment, 47.0 vs. 54.0 for combination treatment). The results from the regression analysis (Table 2) show likewise that estimates of MCS-12 scores exhibit detriments for women in the oral,

Mobility (climbing stairs) (Item 3)

Less careful performance limits certain work/activities (Item 7)a

Having a lot of energy (Item 10) a

1

2

3

4

Overall accomplishment related to physical health (Item 4)b

Interference of pain in activities of daily living (Item 8) a,b

Feeling downhearted and sad (Item 11)a

1

2

3

4

1: No anti-diabetic treatment 2: OAD only 3: OAD and insulin 4: insulin only *Adjusted for: study, age, diabetes duration, education, equivalent income, living alone, myocardial infarction, stroke, hypertension, hyperlipidaemia, BMI, alcohol, physical activity, smoking; asex: P-values