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Journal of Diabetes 8 (2016) 269 – 278

O R I G I N A L A RT I C L E

Gender differences in the association between lifestyle behaviors and diabetes distress in a community sample of adults with type 2 diabetes Carla LIPSCOMBE,1,2 Kimberley J. SMITH,3,4 Geneviève GARIEPY1,2 and Norbert SCHMITZ1,2,5,6 Departments of 1Epidemiology and Biostatistics and 5Psychiatry, McGill University, 2Douglas Mental Health University Institute and 6 Montréal Diabetes Research Centre, Montreal, Quebec, Canada, 3Department of Life Sciences and 4Institute of Environment Health and Societies, Healthy Ageing, Brunel University, Uxbridge, UK

Correspondence Norbert Schmitz, Douglas Mental Health University Institute, McGill University, 6875 LaSalle Boulevard, Montréal, Québec, Canada H4H 1R3. Tel: +1514 761 6131 extn 3379 Fax: +1514 888 4064 Email: [email protected] Received: 28 November 2014; revised 13 March 2015; accepted 30 March 2015. doi: 10.1111/1753-0407.12298

Abstract Background: The present study examined the association between moderate and severe diabetes distress (DD) and lifestyle behaviors (physical activity, smoking, alcohol consumption) in a community sample of adults with type 2 diabetes mellitus (T2DM). Methods: A total of 1971 adults with T2DM were recruited using mixed methods sampling. Participants were considered eligible if they had a doctor diagnosis of T2DM (≤10 years), were insulin naïve, aged 40–75 years, and were from Quebec, Canada. Participants provided information on DD, lifestyle behaviors, sociodemographic, and diabetes-related factors. Multinomial logistic regressions examined the association between moderate and severe DD and each lifestyle behavior, according to gender. Effect estimates can be interpreted as probability ratios (PR). Results: In females, physical inactivity was associated with an increased likelihood of moderate distress (PR 2.2; 95% confidence interval [CI] 1.49– 3.24) and severe distress (PR 1.80; 95% CI 1.00–3.24). In males, only severe distress was associated with physical inactivity (PR 1.92; 95% CI 1.00–3.66). Current smoking was associated with a greater probability of severe distress in males (PR 3.0; 95% CI 1.54–5.84) and females (PR 1.32; 95% CI 0.67–2.60); however this effect was stronger in males. No association was found between alcohol consumption and DD in females. In males, frequent alcohol consumption was associated with a reduced probability of moderate (PR 0.56; 95% CI 0.34–0.91) and severe distress (PR 0.47; 95% CI 0.21–1.06). Conclusions: The findings of this study suggest important gender differences in the association between DD and lifestyle behaviors. Keywords: alcohol drinking, exercise, mental health, smoking, type 2 diabetes mellitus.

Significant findings of the study: In females, physical inactivity was associated with a greater probability of moderate and severe DD. In males, smoking was associated with greater probability of severe DD. In males only, alcohol consumption was associated with a reduced probability of moderate and severe distress. What this study adds: This is the first study to investigate the association between smoking, alcohol consumption, and DD in a community sample of adults with T2DM. The findings highlight the role of gender in the relationship between DD and diabetes-related health behaviors. © 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd

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Introduction Type 2 diabetes mellitus (T2DM) is a progressive and chronic metabolic disorder affecting roughly 6% of Canadians.1 Standard treatment for T2DM is focused on glucose regulation and includes a combination of pharmacological (e.g. insulin therapy) and nonpharmacological approaches.2 Daily self-care and lifestyle modifications are important components of the T2DM treatment regimen and have been shown to delay the progression of diabetes complications and improve diabetes-related health outcomes.3 The Canadian Diabetes Association (CDA) recommends that people with T2DM engage in regular physical activity, limit their alcohol consumption, and quit smoking.2 Poor mental health is a common comorbidity among people with T2DM, and has been shown to interfere with regimen compliance and is associated with poorer diabetes-related health outcomes.4–6 Most studies on mental health in people with diabetes examine depression; however, researchers are increasingly interested in a form of distress specific to living with diabetes called “diabetes distress” (DD). Diabetes distress is a multidimensional construct characterized by negative emotions, worries, and fears relating to four major diabetes-related problem areas. Subdomains of DD include: (i) emotional distress, characterized by feelings of anger, frustration, and worry regarding living with the demands of diabetes or future diabetes-related complications; (ii) physician distress, relating to the quality of care provided by healthcare professionals; (iii) regimen-related distress, pertaining to fears and concerns regarding diabetes treatment regimens; and (iv) interpersonal distress, relating to the level of social support received from family members and friends.7 In people with diabetes, DD appears to be more common than major depression (MD). Recent point estimates in community samples have found the prevalence of moderate to severe DD to be as high as 18%.8 In addition, DD appears to be more strongly associated with poorer glycemic control than MD,6,9–11 and is associated with poorer disease management, including worse medication adherence,6,10,12 poor dietary habits,6,10,12,13 and lower levels of physical activity.6,10,12,13 Despite considerable symptom overlap between DD and MD, particularly with regard to somatic symptoms (e.g. feeling tired, having low energy), evidence suggests that DD is a separate and distinct condition from MD.9,14 Lifestyle behaviors such as smoking, excessive alcohol consumption, and physical inactivity are associated with a wide range of physical and mental health consequences in people with T2DM.2,15–18 However, little is known about the relationship between smoking, alcohol consumption, and DD in this population. Several studies 270

have examined the relationship between physical activity levels and DD;6–8,10,12,13 however, the large majority of these studies have used clinical samples or samples identified through medical groups or diabetes education centers, rendering conclusions about how this relationship may manifest in the general population difficult to make. The relationship between lifestyle behaviors and DD is also likely to vary by sex. Females tend to evidence higher average levels of DD than males,12,19,20 and this pattern appears to hold cross-culturally.21,22 In addition, longitudinal studies find females have a greater odds of developing DD13 and experience greater persistence of DD symptoms over time.11 Similarly, lifestyle behaviors such as smoking, physical activity, and alcohol consumption tend to differ according to gender.1,23 To date, few studies have examined how smoking, physical activity, and alcohol consumption relate to total DD, and the multiple dimensions of DD in a representative sample of adults living with T2DM. As such, the main objectives of the present study were to describe and examine the association between physical activity, smoking, and alcohol consumption according to individual DD subscales and total DD. In addition, given the existence of gender differences in the development, severity, and persistence of DD, as well as in the prevalence and performance of these lifestyle behaviors, all analyses were stratified by gender.

Methods Subjects Data for the present study were derived from the Evaluation of Diabetes Treatment study (EDIT), a longitudinal community-based survey of adults with T2DM (for more information, see Smith et al.24). Participant recruitment involved mixed method sampling techniques including random digit dialing and mail-out surveys. Eligibility criteria included being a resident of Quebec (Canada), aged 40–75 years, having a doctor diagnosis of T2DM within the previous 10 years, and being insulin naïve. A total of 2028 subjects met the inclusion criteria and underwent the interview process. Participants who did not provide information on questions relating to DD, smoking levels, alcohol consumption, or physical activity levels were excluded from the analyses. In all, 1971 participants were included in the final sample. The present study uses baseline data collected in 2011. The study protocol was reviewed and approved by the Research Ethics Committee of the Douglas Mental Health University Institute. All participants provided informed consent.

© 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd

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Diabetes distress Diabetes distress was assessed with the 17-item Diabetes Distress Scale (DDS-17).7 The DDS-17 measures distress associated with four major areas that are pertinent to living with diabetes. Participants are asked to rate the degree to which various problem areas have caused them distress during the previous month using a six-point Likert-scale (1 = no problem; 6 = very serious problem). Subdomains of DD include: (i) emotional distress (ED; five items); (ii) physician-related distress (PD; four items); (iii) interpersonal distress (ID; three items); and (iv) regimen-related distress (RD; five items). The DDS-17 allows for the calculation of a global composite DD score and a score for each subscale. A recent validation study provided evidence supporting the use of three categories of distress to more accurately depict subgroups of DD.8 As such, participants’ global DD scores were categorized to reflect three levels of distress: (i) little to no DD (0.0–1.0); (ii) moderate DD (2.0–2.9); and (iii) severe DD (≥3.0). Given that there is no evidence to support a similar categorization scheme for DD subscales, scores on each of the four DD subdomains were tabulated and are presented as the mean ± SD. Physical inactivity Physical inactivity was determined by asking participants to report the amount of days over the past month spent engaged in sports or exercise for at least 15 min. Participants were classified according to two categories reflecting either low activity levels (“inactive”) if they reported 0–11 days of physical activity a month (this would roughly translate into being active less than three times a week) or high activity levels (“active”) if they reported at least 12 days of physical activity a month (this would roughly translate into at least 3 days of physical activity a week). This particular categorization scheme was selected based on its approximation to weekly physical activity guidelines recommended by the CDA.2 Drinking patterns Alcohol consumption was assessed with the three-item Alcohol Use and Disorders Identification Test (AUDITC).25 To determine past year drinking patterns, we used the first two questions of the AUDIT-C and adapted a classification scheme used in the Canadian Alcohol and Drug Use Monitoring Survey.23 Participants were classified according to the following three categories: (i) nondrinkers: participants who reported, at the time of the interview, abstention from alcohol during the previous 12 months; (ii) infrequent drinkers: participants report-

Lifestyle behaviors and diabetes distress

ing drinking less often than once a week; and (iii) frequent drinkers: participants reporting drinking once a week or more. Smoking Questions pertaining to smoking status and frequency were derived from the Canadian Community Health Survey (CCHS) Cycle 1.2.26 Participants were categorized according to the following scheme: (i) non-smokers included participants who reported smoking less than 100 total cigarettes in their lifetime (i.e. never smokers) or participants who reported smoking more than 100 total cigarettes in their lifetime but who, at the time of the interview, did not smoke (i.e. former smokers); and (ii) current smokers, consisting of participants reporting being a current smoker. This classification scheme was selected for consistency with the Canadian Tobacco Use Monitoring Survey.27 Covariates Participants provided information on characteristics including age, gender, education (less than secondary school, secondary school, post-secondary school), marital status (married or partnered; widowed, separated, or divorced; never married), and major depression (MD) (assessed with the nine-item Patient Health Questionnaire28). Diabetes complications were assessed with the 17-item Diabetes Complications Index (DCI).29 The DCI assesses past diagnoses and current symptoms of six of the most common complications of T2DM, namely coronary artery disease, cerebrovascular disease, peripheral vascular disease, neuropathy, foot problems, and eye problems. Scores on the DCI can range from 0 to 6, with higher scores indicating the presence of more diabetes complications. We cross-tabulated DD and MD to assess the degree of overlap between these two conditions and found a small degree of comorbidity (25% of those with moderate–severe distress had comorbid MD). Based on this finding and evidence from the literature suggesting that DD and MD are likely separate constructs describing largely distinct mental health states,9,14 the role of MD in the relationship between DD and lifestyle was not considered further. Data analysis Chi-squared analyses (for categorical data), one-way ANOVA’s or t-tests (for continuous data) were used to test for differences between lifestyle factors according to DD, DD subscales, and gender. When more than two group means were being compared (i.e. subscale scores according to alcohol consumption), significant

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ANOVAs were followed up with Bonferroni post hoc analyses. To further examine the association between each lifestyle factor (smoking status, alcohol consumption, physical activity level) and DD, three separate multinomial logistic regression models were developed. In all three regression models, a stepwise approach was applied. Step 1 assessed the unadjusted association between the exposure variable and the outcome. In Step 2, sociodemographic factors were entered into the model (age, education, marital status). Step 3 further adjusted for diabetes complications and physical activity and/or smoking and/or alcohol consumption. All analyses were conducted separately for males and females. Given the use of a multinomial logistic regression, effect measures should be interpreted as a ratio of probability ratios (PR) comparing (i) the respective level of distress (moderate or severe) to the reference level of distress (little to no distress) given a particular level of the lifestyle behavior in question with (ii) the respective level of distress (moderate or severe) to the reference level of distress (little to no distress) given the reference level of the lifestyle behavior in question. Data were analyzed using Stata version 12.0 software (Stata Corp., College Station, TX, USA). Sensitivity analyses Sensitivity analyses were performed to verify the robustness of the observed effects. Participants physical activity scores were re-classified into: (i) physically inactive, reflecting 0 days of physical activity in the previous month; and (ii) some physical activity, reflecting “1” day or more of physical activity in the previous month. Using the total AUDIT-C score (range 0–12), alcohol consumption was recategorized to reflect: (i) non-drinkers (AUDIT score of 0); (ii) moderate drinkers (AUDIT-C score of >0 to 0 to 1, indicating a consistent effect across steps (PRStep3 1.35; 95% CI 0.71–2.56; Table 3). In males, physical inactivity was associated with a greater probability of severe distress in unadjusted (Step 1) and partially adjusted models (Step 2). In fully adjusted models (Step 3), the association was no longer significant; however, the point estimate remained >1, indicating a consistent effect across steps (PRStep3 1.51; 95% CI 0.75– 3.01; Table 4). Compared with non-smokers, current smoking was associated with an increased probability of severe distress for both males and females. In males, this effect was of large magnitude and was significant even after controlling for sociodemographic, lifestyle, and diabetesrelated factors (Table 4). In females, the association between smoking and severe DD was no longer significant once lifestyle and diabetes-related factors were entered into the model; however, it should be noted that the point estimate for this comparison remained >1, indicating a consistent effect across steps of the analysis (PRStep3 1.32; 95% CI 0.67–2.60; Table 3). Alcohol consumption was not associated with DD in females (Table 3). However, in males alcohol consump-

© 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd

C. LIPSCOMBE et al. Table 1

Lifestyle behaviors and diabetes distress

Sample characteristics and lifestyle behaviors according to gender Female

No. subjects Age (years; n = 1971) Highest level of education (n = 1945) Less than secondary school graduation Secondary school graduation Post-secondary school Marital status (n = 1965) Married or partnered Widowed, separated, or divorced Never married Mean no. diabetes complications (n = 1865) DD summary score* (n = 1971) DD categories (n = 1971) Little to no distress Moderate distress Severe distress Physical activity* (days; n = 1971) Physical activity (n = 1971) Inactive Active Smoking (n = 1971) Non-smokers Current smokers Alcohol consumption* (n = 1971) Non-drinkers Infrequent Frequent

987 61 ± 8

Male 984 59.8 ± 8.3

45.23% 29.44% 25.33%

35.88% 32.37% 31.75%

60.14% 29.46% 10.40% 0.95 ± 0.83 1.64 ± 0.71

71.04% 15.65% 13.31% 0.92 ± 0.82 1.54 ± 0.64

75.38% 18.54% 6.08% 11.0 ± 0.36

78.96% 16.16% 4.88% 12.2 ± 0.36

59.88% 40.12%

55.28% 44.72%

79.64% 20.36%

79.07% 20.93%

45.39% 40.83% 13.78%

23.78% 38.41% 37.80%

The percentage of participants within each categorical variable according to gender is shown. Continuous variables are given as the mean ± SD. Asterisks indicate lifestyle behaviors that had a significant association with gender using either Chi-squared analyses (categorical variables) or t-tests (continuous variables). DD, diabetes distress.

tion was associated with a reduced likelihood of moderate and severe distress. More specifically, compared with non-drinkers, male frequent drinkers were less likely to report moderate distress. This effect was of large magnitude (nearly 50% less likely) and remained stable across steps of the analysis. Similarly, infrequent and frequent drinking were associated with a reduced likelihood of severe distress. Although this association was no longer significant in fully adjusted models, point estimates for infrequent drinking (PRStep3 0.47; 95% CI 0.21–1.03) and frequent drinking (PRStep3 0.47; 95% CI 0.21–1.06) remained highly stable, changing minimally across steps of the analysis (Table 4).

Sensitivity analyses Changes to the parameters used to describe physical activity level and alcohol consumption did not alter the pattern of observed effects. The results of a series of

linear regressions with DD as a continuous variable (log transformed) supported the pattern of results in Tables 3 and 4 (data not shown).

Discussion The main finding of the present study is an association between three lifestyle behaviors (physical activity, smoking, alcohol consumption) and moderate and severe DD in a community sample of people with T2DM. In addition, separate analyses for males and females revealed important gender differences in the relationship between lifestyle and DD. This study contributes to the literature by being the first to investigate smoking and alcohol consumption as additional factors associated with DD. Furthermore, this is the first study to identify associations between lifestyle factors according to DD categories and DD subscales, specifically by gender.

© 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd

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Lifestyle behaviors and diabetes distress Table 2

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Sample characteristics and lifestyle behaviors according to diabetes distress categories, separated by gender

Female No. subjects Age (years; n = 986) Education Less than secondary school (n = 441) Secondary school (n = 287) Post-secondary school (n = 247) Marital status Married or partnered (n = 590) Widowed, separated, or divorced (n = 289) Never married (n = 102) Diabetes complications (n = 934) Physical activity* Inactive (n = 591) Active (n = 396) Smoking* Non-smokers (n = 786) Current smokers (n = 201) Alcohol consumption Non-drinkers (n = 448) Infrequent (n = 403) Frequent (n = 136) Male No. subjects Age (years; n = 983) Education Less than secondary school (n = 348) Secondary school (n = 314) Post-secondary school (n = 308) Marital status Married or partner (n = 699) Widowed, separated, or divorced (n = 154) Never married (n = 131) Diabetes complications (n = 929) Physical activity Inactive (n = 544) Active (n = 440) Smoking* Non-smokers (n = 778) Current smokers (n = 206) Alcohol consumption* Non-drinkers (n = 234) Infrequent (n = 378) Frequent (n = 372)

Little to no distress

Moderate distress

Severe distress

744 61.58 ± 8.24

183 59.10 ± 8.74

60 57 ± 8

46% 28.90% 25.10%

41.90% 32.40% 25.70%

45.76% 27.12% 27.12%

62.89% 28.34% 8.77% 0.997 ± 1.090

55% 32.22% 12.78% 1.44 ± 1.24

41.67% 35% 23.33% 1.82 ± 1.37

55.91% 44.09%

72.68% 27.32%

70.00% 30.00%

81.32% 18.68%

77.05% 22.95%

66.67% 33.33%

44.22% 42.20% 13.58%

49.73% 37.16% 13.11%

46.67% 35.00% 18.33%

P-value

0.000

0.016

0.488

777 60.4 ± 8.2

159 58.08 ± 8.68

48 55.88 ± 7.38

37.12% 31.90% 30.98%

31.85% 33.76% 34.39%

29.17% 35.42% 35.42%

72.72% 15.44% 11.84% 0.96 ± 1.05

64.78% 15.72% 19.50% 1.60 ± 1.39

64.58% 18.75% 16.67% 1.53 ± 1.35

54.18% 45.82%

55.97% 44.03%

70.83% 29.17%

80.57% 19.43%

79.87% 20.13%

52.08% 47.92%

21.75% 38.61% 39.54%

29.56% 40.25% 30.19%

37.50% 29.17% 33.33%

0.078

0.000

0.017

The percentage of participants within each categorical variable according to gender is shown. Continuous variables are given as the mean ± SD. Asterisks indicate lifestyle behaviors that had a significant association with gender using either Chi-squared analyses (categorical variables) or one-way ANOVA (continuous variables). P-values indicating the results of significance tests are presented in the final column.

Our findings for physical activity parallel previous results in the literature6–8,10,12,13 of a negative association between activity levels and DD. However, the results from the present study suggest that this association may differ depending on the level of DD examined and according to gender. For example, although a strong association between physical activity and moderate and 274

severe DD was found for females, no association was found for males and moderate DD. Although there was some evidence of an association between physical activity and distress in males, this association was restricted to the severe distress category. One implication of these results is that the relationship between distress and physical activity may be stronger for females than for males.

© 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd

C. LIPSCOMBE et al. Table 3

Lifestyle behaviors and diabetes distress

Multinomial logistic regression predicting the probability of moderate and severe diabetes distress from lifestyle behaviors in females

Model 1: Physical activity Moderate distress Inactive versus active Severe distress Inactive versus active Model 2: Smoking Moderate distress Current versus non-smoker Severe distress Current versus non-smoker Model 3: Alcohol consumption Moderate distress Infrequent versus non-drinker Frequent versus non-drinker Severe distress Infrequent versus non-drinker Frequent versus non-drinker

Step 1: Unadjusted PR (95% CI)

Step 2: Adjusted PR (95% CI)

Step 3: Fully adjusted PR (95% CI)

2.10 (1.47–2.99)***

2.14 (1.48–3.08)***

2.20 (1.49–3.24)***

1.84 (1.04–3.26)*

1.80 (1.00–3.24)*

1.35 (0.71–2.56)

1.30 (0.88–1.92)

1.20 (0.80–1.79)

0.90 (0.58–1.41)

2.18 (1.23–3.84)**

1.83 (1.01–3.29)*

1.32 (0.67–2.60)

0.78 (0.55–1.11) 0.86 (0.52–1.42)

0.77 (0.54–1.11) 0.86 (0.51–1.45)

0.89 (0.61–1.31) 0.97 (0.56–1.67)

0.79 (0.44–1.41) 1.28 (0.62–2.66)

0.71 (0.39–1.31) 1.43 (0.66–3.06)

1.04 (0.53–2.07) 1.92 (0.85–4.36)

Diabetes distress reference category: little to no distress. Step 1, unadjusted association; Step 2, adjusted for age, marital status, and education; Step 3, further adjusted for diabetes complications and lifestyle behaviors (smoking and/or alcohol consumption and/or physical activity). Missing due to incomplete datasets: n = 57 (0.03% of dataset). *P < 0.05, **P < 0.01, ***P < 0.001. PR, probability ratio; CI, confidence interval.

Table 4

Multinomial logistic regression predicting the probability of moderate and severe diabetes distress from lifestyle behaviors in males

Model 1: Physical activity Moderate distress Inactive versus active Severe distress Inactive versus active Model 2: Smoking Moderate distress Current versus non-smoker Severe distress Current versus non-smoker Model 3: Alcohol consumption Moderate distress Infrequent versus non-drinker Frequent versus non-drinker Severe distress Infrequent versus non-drinker Frequent versus non-drinker

Step 1: Unadjusted PR (95% CI)

Step 2: Adjusted PR (95% CI)

Step 3: Fully adjusted PR (95% CI)

1.08 (0.76–1.52)

1.03 (0.72–1.46)

0.96 (0.66–1.40)

1.92 (1.00–3.66)*

1.51 (0.75–3.01)

1.04 (0.68–1.60)

0.88 (0.56–1.37)

0.84 (0.53–1.33)

3.81 (2.10–6.90)***

3.30 (1.77–6.11)***

3.00 (1.54–5.84)**

0.77 (0.50–1.17) 0.56 (0.36–0.87)*

0.71 (0.46–1.10) 0.54 (0.34–0.86)**

0.73 (0.46–1.15) 0.56 (0.34–0.91)*

0.44 (0.21–0.90)* 0.49 (0.24–0.98)*

0.39 (0.18–0.83)* 0.47 (0.23–0.98)*

0.47 (0.21–1.03) 0.47 (0.21–1.06)

2.05 (1.08–3.89)

*

Diabetes distress reference category: little to no distress. Step 1, unadjusted association; Step 2, adjusted for age, marital status, and education; Step 3, further adjusted for diabetes complications and lifestyle behaviors (smoking and/or alcohol consumption and/or physical activity). Missing due to incomplete datasets: n = 57 (0.03% of dataset). *P < 0.05, **P < 0.01, ***P < 0.001. PR, probability ratio; CI, confidence interval.

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For example, females may be more susceptible to the presence of moderate amounts of distress than males, or inactivity may lead to measurably greater amounts of distress in females than in males. Given the crosssectional nature of the present study, the direction of causality between these variables cannot be determined. It is also possible that the shape of the relationship between DD and physical activity differs depending on gender and the level of DD experienced (i.e. curvilinear in females, threshold or straight line relationship in males). Partial support for a non-linear relationship between these variables is provided by the recent work of Fisher et al.8 Alternatively, the types of physical activity that men and women engage in may be qualitatively different and, as a result, associate differently with DD (i.e. physical labor versus leisure-type physical activities). Current smoking was associated with a greater probability of severe distress; however, this association appeared to be stronger in male than female smokers. Although this result supports evidence from the literature of an association between smoking and mental health comorbidities in adults with T2DM,31–33 it also highlights a potentially important role of DD severity and gender in this relationship. Interestingly, this finding is somewhat at odds with the results of a large, nationally representative study that found a stronger association between smoking and general psychological distress in females compared with males.34 One possible explanation for this discrepancy is that the association between smoking, gender, and distress may manifest differently depending on the subpopulation under investigation and the measure of psychological distress used. The findings from the present study suggest that, among adults with T2DM, smoking may be a better indicator of diabetesspecific distress in males than in females. This result may also reflect true differences in coping styles between the sexes. For example, it has been suggested that males are more likely than females to turn to alcohol and other drugs as a coping mechanism when faced with difficult life situations.35 Given the strong medical evidence supporting the importance of smoking cessation in people with T2DM,36,37 future studies may consider examining the role of DD in smoking cessation attempts or the propensity for relapse in this population. Although it cannot be determined from the present study whether smokers are more likely to develop severe distress or whether severe distress leads to more frequent smoking, this finding does highlight a potentially critical role for severe distress in the performance of an unhealthy lifestyle behavior, particularly in men. In females, there was little statistical support for an association between alcohol consumption and DD. However, in males, alcohol consumption was associ276

ated with a reduced likelihood of moderate and severe distress. Although several lines of evidence in the literature point to a beneficial effect of moderate alcohol consumption on diabetes health outcomes,38–41 including a reduced likelihood of anxiety and depression symptoms,42 this finding should be interpreted with some caution. Non-drinkers (the reference category) may be a group comprised of both healthy individuals choosing not to drink out of personal preference and individuals in poorer health who do not drink as a result of their health status or contraindication with certain medications. Comparatively, the group of infrequent and/or frequent drinkers may be comprised of people who are well enough to be able to drink in the first place. In the present study, male non-drinkers tended to have more overall distress than both infrequent and frequent male drinkers. As such, the relationship between lower DD and alcohol consumption seen in the present study may be explained by a third factor, such as “general health”, and not alcohol consumption per se. However, one possible implication of this result is that men in this sample that drink are using alcohol as a means by which to dampen or quell feelings of distress. Thus, the relative reduction in distress seen among drinkers may reflect a form of self-medication on the part of males. It has been shown that males are more likely than females to engage in problem drinking,23 and may be more likely than females to use alcohol as a coping mechanism35 or as self-medication.43 Although it cannot be determined from the present study whether frequent drinking leads to a reduced likelihood of being distressed or whether the contrary is true, the possibility of abuse or misuse of alcohol in males with moderate or severe DD should be considered in future studies. Limitations Because of the cross-sectional nature of the present study and the a posteriori decision to use subgroup analyses, interpretation of the data must be done with care. For example, it is not possible to comment on the direction of causality between the lifestyle behaviors examined and DD. In addition, despite efforts to control for possible confounds, alternative explanations for the observed relationships are possible (e.g. Hba1c levels, diet). We excluded household income as a potential covariate due to a high level of missing data on this variable (15%). However, it should be noted that sensitivity analyses with income included as a covariate revealed no differences in the pattern of results. Physical activity was measured using a single question that assessed frequency of activity during the previous month. As a result, we were unable to examine the association between duration,

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intensity, or type of physical activity performed and DD. Finally, given the possibility for misclassification of DD and MD cases, further research is needed to better understand the role of depression in the association between DD and lifestyle behaviors. Conclusion The findings of the present study add to the growing body of evidence suggesting an important role for DD in diabetes-related health behaviors. In addition, this study highlights the need to consider DD as an important component of diabetes disease management in people with T2DM. From a clinical standpoint, this study provides support for DD screening by health professionals during routine medical visits in patients presenting with T2DM and a history of unhealthy lifestyle behaviors. For example, smoking may be a good proxy for distress in males, whereas inactivity a good proxy for distress in females. Future studies are needed to delineate the direction of causality between DD and these lifestyle factors. An understanding of the causal relationship could benefit interventional studies aimed at eliminating unhealthy lifestyle habits or reducing DD. As an example, it may be important to screen for and treat DD symptoms prior to interventions designed to encourage smoking cessation or increase physical activity levels in people with T2DM. Finally, the evidence from the present study suggests that future research examining the role of DD in diabetes health may consider the role of severe distress and gender more closely. Acknowledgements Funding for this study was provided by an operating grant from the Canadian Institutes of Health Research. Disclosure None declared. References 1. Pelletier C, Dai S, Roberts KC, Bienek A, Onysko J, Pelletier L. Report summary. Diabetes in Canada: Facts and figures from a public health perspective. Chronic Dis Inj Can. 2012; 33: 53–4. 2. Cheng AY. Canadian Diabetes Association 2013 clinical practice guidelines for the prevention and management of diabetes in Canada. Introduction. Can J Diabetes. 2013; 37 (Suppl. 1): S1–3. 3. Gonder-Frederick LA, Cox DJ, Ritterband LM. Diabetes and behavioral medicine: The second decade. J Consult Clin Psychol. 2002; 70: 611–25.

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Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher’s web-site: Table S1 Association between diabetes distress subscales, total distress, and physical activity status in males and females. Table S2 Association between diabetes distress subscales, total distress, and smoking in males and females. Table S3 Association between diabetes distress subscale, total distress, and alcohol consumption in males and females.

© 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd