Journal of Affective Disorders 179 (2015) 6–13

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Research report

Associations between depression, chronic physical health conditions, and disability in a community sample: A focus on the persistence of depression Sonya S. Deschênes a,b,n, Rachel J. Burns a,b, Norbert Schmitz a,b,c a

Department of Psychiatry, McGill University, Montreal, Quebec, Canada Douglas Mental Health University Institute, Montreal, Quebec, Canada c Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada b

art ic l e i nf o

a b s t r a c t

Article history: Received 26 February 2015 Received in revised form 9 March 2015 Accepted 12 March 2015 Available online 20 March 2015

Background: Previous research has demonstrated that comorbid depression and chronic physical health conditions are associated with disability. The distinction between persistent and transient depression in the relationship between physical health conditions and disability, however, is poorly understood. The present study examined the interactive effects of major depressive disorder (MDD) and chronic physical health conditions on disability in a community sample; the effects of persistent or transient depression on disability were also examined. Methods: Participants were from the Epidemiological Catchment Area of Montreal South-West Study (total N¼ 2202). Past 12-month MDD, chronic physical conditions, functional disability, and disability days experienced within the past month were concurrently assessed. A subsample (n ¼1226) was used to examine the persistence of depression across three waves of data collection over approximately six years. Results: Individuals with comorbid MDD and chronic physical health conditions were approximately thirteen times more likely to have moderate to severe functional disability and had the highest mean number of disability days compared to those without MDD or a chronic physical health condition. Persistent MDD was most strongly associated with functional disability and disability days, and persistence of MDD interacted with physical health conditions to increase likelihood of concurrent disability. Limitations: Our study is limited by a single assessment point for disability and chronic health conditions and by the use of self-report. Conclusions: Our findings suggest that MDD, particularly when persistent, is associated with disability among individuals with a broad range of chronic physical health conditions. & 2015 Elsevier B.V. All rights reserved.

Keywords: Chronic health conditions Persistent depression Disability Major depressive disorder

1. Introduction Major depressive disorder (MDD) and symptoms of depression are highly prevalent in the general population (Kessler et al., 2009, 2005) and are particularly prevalent in individuals with chronic physical health conditions (Barnett et al., 2012; Clarke and Currie, 2009; Gunn et al., 2012; Moussavi et al., 2007). The independent associations between chronic physical health conditions (Stewart et al., 1989) and depression (Hays et al., 1995; Kroenke et al., 2007) with disability are well-documented in the literature. Though chronic physical health conditions and depression are uniquely

n Correspondence to: Douglas Mental Health University Institute, 6875 Boul. Lasalle, Frank B. Common Pavilion, F2117.2, Montreal, QC, Canada H4H 1R3. Tel.: þ 1 514 761 6131x3334. E-mail address: [email protected] (S.S. Deschênes).

http://dx.doi.org/10.1016/j.jad.2015.03.020 0165-0327/& 2015 Elsevier B.V. All rights reserved.

disabling, comorbid depression in individuals with chronic physical health conditions may increase the likelihood of disability. Many studies have indeed demonstrated that symptoms of depression are associated with reduced functioning (Gili et al., 2013; Ormel et al., 1994), and that individuals with physical health conditions and comorbid depression have an even greater likelihood of functional disability and more disability days than those with neither a physical health condition nor depression (Egede, 2007; Joshi et al., 2014; Katon and Ciechanowski, 2002; Schmitz et al., 2007). The interactive effect of depression and chronic physical health conditions, such as diabetes, heart diseases, migraine headaches, asthma, and back problems, on disability appears to be synergistic (Schmitz et al., 2007), suggesting that the joint effect of depression and chronic health conditions on disability is beyond that of an additive effect. Chronic or persistent depression may be associated with even higher odds of disability and poor functioning. Chronic depression

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is a common form of depression that consists of depressed mood for at least two years (Klein, 2010). Chronic depression accounts for approximately 26.8% of depression cases in Canada (Satyanarayana et al., 2009), and similar prevalence rates of chronic depression amongst individuals who are depressed have been reported internationally (e.g., Angst et al., 2009; Eaton et al., 2008; Spijker et al., 2002). Chronic depression is associated with a higher number of medical comorbidities and incapacitating medical diseases, greater health service use, and greater disability than nonchronic depression (Akiskal, 1982; Campayo et al., 2010; Satyanarayana et al., 2009). Similarly, recurrent sub-threshold depressive symptoms are associated with greater disability among individuals with type 2 diabetes compared to individuals with low depressive symptoms (Schmitz et al., 2014). Recurrent subthreshold depressive symptoms following treatment are also associated with more severe and enduring future depressive episodes over the course of 12 years (Judd et al., 2000). However, to our knowledge, chronic/recurrent and nonchronic/nonrecurrent major depressive disorder (MDD) has not been distinguished in studies of the associations between depression, physical health conditions, and disability among individuals with a broad range of chronic health conditions. In addition, previous research on chronic MDD and comorbid physical health conditions has relied on self-reported duration of the current depressive episode (e.g., Satyanarayana et al., 2009). This assessment may be subject to recall bias, and therefore converging evidence using different methods of assessing chronicity of depressive symptoms, such as the use of repeated assessments of depression, could be informative for the study of the association between depression, chronic illness, and disability. The aims of the present study were twofold. First, using data from the Epidemiological Catchment Area of Montreal South-West Study, we sought to replicate previous findings by comparing the prevalence of functional disability and disability days in individuals with or without MDD and with or without chronic physical health conditions. We expected that the joint effect of MDD and chronic physical health on functional disability would be synergistic, such that it would exceed the additive effect of MDD and chronic physical health conditions. Second, we aimed to examine the associations between the persistence of depression over three time points and disability, while accounting for chronic health conditions, by identifying individuals who had either persistent depression (MDD present at multiple assessment waves), transient depression (MDD present at one assessment wave), or no depression (MDD criteria not met at any assessment wave). We also examined the interactions between the persistence of depression and comorbid chronic physical health conditions on functional disability and disability days.

2. Methods 2.1. Sample Data for this study were obtained from the Epidemiological Catchment Area of Montreal South-West Study, an ongoing study that examines the prevalence of mental disorders and their interactions with individual and environmental characteristics over time. Data were collected in-person either at the respondent's home or at the Douglas Mental Health University Institute by trained interviewers. Institutional ethical approval was obtained for the study and all participants provided informed consent. Detailed procedures are described elsewhere (Caron et al., 2012; Fleury et al., 2014). Data on sociodemographic characteristics and chronic health conditions come from the third and most recent wave of data collection because assessments of chronic health

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conditions were introduced at this time. To assess persistence of depression, data from all three waves were used. Wave 1 data were collected between May 2007 and November 2008 (n ¼2433), wave 2 data were collected between July 2009 and November 2010 (n ¼1823), and wave 3 data were collected between January 2012 and July 2013 (n ¼1303). A new cohort of participants was additionally recruited and participated at wave 3 (additional n ¼1029), and therefore the sample size at wave 3 was larger than at waves 1 and 2. For analyses examining the interactions between MDD (persistent or transient) and chronic physical health conditions, our sample consisted of 2202 adults who participated in the third wave of data collection, were between the ages of 18–73, and had complete data on depression, chronic health conditions, and disability. For analyses examining the associations between the persistence of depression and disability, our subsample consisted of 1226 adults who participated at all three waves. 2.2. Measures Chronic physical health conditions were assessed via selfreported items that queried whether diagnoses had ever been made by health care professionals for the most common chronic physical health conditions: diabetes, asthma, high blood pressure, heart disease, stomach or intestinal ulcers, arthritis/rheumatism, migraine headaches, cancer, kidney disease, and back problems. MDD was assessed with the World Mental Health – Composite International Diagnostic Interview 3.0 (Kessler and Üstün, 2004), a standardized instrument for the assessment of mental disorders according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (American Psychiatric Association, 2000) criteria. Diagnostic algorithms identified respondents who had a major depressive episode within the past 12 months. Persistence of depression was determined by the number of positive diagnoses of MDD, based on a structured interview, over three waves of assessment during an approximately six-year period (May 2007–July 2013). Persistent depression was considered if MDD criteria were met at two or three of the waves, whereas transient depression was considered if MDD criteria were met at only one of the three waves. Similar operational definitions of depression persistence have been used in previous research (e.g., Peyrot and Rubin, 1999; Schmitz et al., 2014). Functional disability was assessed with the World Health Organization Disability Assessment Schedule 2.0 (WHODAS-2.0; Üstün, 2010). The WHODAS-2.0 is a 12 item measure that assesses the degree of difficulty experienced with a number of daily activities in the last 30 days, such as standing for long periods, taking care of household responsibilities, learning new tasks, getting dressed, day to day work or school activities, or maintaining friendships. Responses to each item can range from 0 (“None”) to 4 (“Extreme/ cannot do”). The measure was developed to assess the following domains: understanding and communication, self-care, mobility, interpersonal relationships, work and household roles, and community and civic participation. Raw scores were transformed to a standardized scale of 0–100, and a score of 21 or above was used to identify moderate to severe levels disability. Research has demonstrated that a score of 21 on the 0–100 scale (i.e., a raw score of 10) represents the top 10% of the population distribution of the WHODAS 2.0 and likely reflects clinically significant disability (Andrews et al., 2009). Disability days were assessed with the Healthy Days Measures (Hennessy et al., 1994; Taylor, 2000). The Healthy Days Measures is a brief instrument developed by the United States Centers for Disease Control and Prevention that measures perceived physical and mental health over time. To assess number of disability days in the past month, three Healthy Days questions were administered

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in the present study: the number of days with poor physical health (“thinking about your physical health, which includes physical health conditions and injury, for how many days during the past 30 days was your physical health not good?”), the number of days with poor mental health (“thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?”), and the number of days with activity limitations (“during the past 30 days, for about how many days did poor physical or mental health keep you from doing your usual activities, such as self-care, work, or recreation?”). The three Healthy Days Measures were significantly moderately correlated with one another and with the WHODAS 2.0 (rs between .36 and .57, ps o.01). Covariates included age (grouped as 18–29, 30–44, 45–59, and 60–74), gender (male or female), highest education level attained (less than secondary school graduation, secondary school graduation, some postsecondary education, postsecondary school graduation), marital status (married, separated, common-law union, divorced, widowed, single/never married), smoking frequency (daily, occasionally, or not at all), alcohol consumption frequency (regular drinker, occasional drinker, former drinker, or never drank), and body mass index (kg/m2) category based on World Health Organization recommendations (normal weight [18.5– 24.9]/underweight [18.4 or less]/overweight [25.0–29.9]/obese [30 or more]).

To examine the associations between wave 3 MDD and chronic physical health conditions comorbidity with disability days, a series of one-way factorial analyses of covariance (ANCOVAs) adjusted for covariates were conducted with comorbidity group from data at wave 3 as the between-groups factor and the number of days when physical health was not good, the number of days when mental health was not good, and the number of days inactive as the outcome variables. Unadjusted analysis of variance (ANOVA) results are also presented. Similar analyses were conducted to address the second study goal of examining the effects of the persistence of depression on functional disability and disability days. Crude models, models adjusted for sociodemographic covariates, and models additionally adjusted for chronic physical health conditions are presented. Finally, to examine the interactions between the persistence of depression and chronic physical health conditions, similar analyses were conducted with the following six mutually-exclusive groups: (a) without MDD, without chronic physical health conditions; (b) with transient MDD, without chronic physical health conditions; (c) with persistent MDD, without chronic physical health conditions; (d) without MDD, with chronic physical health conditions; (e) with transient MDD, with chronic physical health conditions; (f) with persistent MDD, with chronic physical health conditions. Analyses were conducted in SPSS version 20.0 and significance tests reflect two-tailed tests.

2.3. Statistical analysis

3. Results

To address the first study goal of comparing the prevalence of functional disability and disability days in individuals with or without MDD and with or without chronic physical health conditions, functional disability and disability days were compared across four mutually-exclusive groups from wave 3 data: (a) without MDD and without chronic physical health conditions; (b) without MDD and with chronic physical health conditions; (c) with MDD and without chronic physical health conditions; (d) with comorbid MDD and chronic physical health conditions. Descriptive statistics were calculated to determine the percentage of the sample with MDD and/or chronic physical health conditions, functional disability, and socio-demographic and health behaviors within each group. The average number of disability days was also computed for each group. Binary logistic regression analyses were conducted to assess the likelihood of moderate to severe disability among those with MDD only, those with chronic physical health conditions only, or those with comorbid MDD and chronic physical health conditions (compared to the reference group with neither MDD nor chronic physical health conditions), and odds ratios (ORs) with 95% confidence intervals (CIs) are reported. Crude models and models adjusted for covariates are presented. To further understand the interactions between wave 3 MDD and chronic physical conditions on disability, we tested an additive interaction OR model by calculating the synergy index (SI) and associated confidence intervals, based on the recommendations of Andersson et al. (2005), for ORs unadjusted and adjusted for covariates. The SI represents the excess risk of functional disability from the interaction of both chronic physical health and MDD, relative to the risk of functional disability from either condition without an interaction. The SI was calculated as follows: SI¼ [ORpm  1]/([ORp  1] þ[ORm  1]), where ORpm is the OR for comorbid chronic physical health conditions and MDD, ORp is the OR for chronic physical health conditions only, and ORm is the OR for MDD only. The presence of an additive interaction effect is indicated by a SI greater than 1, and the 95% confidence intervals for the SI was computed based on the recommended formulas (Andersson et al., 2005).

Table 1 describes functional disability prevalence, demographic characteristics, and health and lifestyle-related characteristics stratified by MDD/chronic physical health condition comorbidity group (wave 3). Of the total sample included in the present study, 58.6% (n¼ 1290) reported having been diagnosed with a chronic physical health condition by a health care professional. Of those with a chronic physical health condition, 12.6% had diabetes (7.4% of total sample), 27.6% had asthma (16.2% of total sample), 28.6% had high blood pressure (16.8% of total sample), 10.4% had heart disease (6.1% of total sample), 13.4% had stomach or intestinal ulcers (7.9% of total sample), 25.6% had arthritis / rheumatism (15% of total sample), 22.5% had migraine headaches (13.2% of total sample), 9.6% had cancer (5.6% of total sample), 4.8% had kidney disease (2.8% of total sample), and 37.4% had back problems (21.9% of total sample). Prevalence of MDD was 4.5% at wave 1, 4.4% at wave 2, and 7.3% at wave 3. 3.1. Associations between MDD, chronic physical health conditions, and disability Table 2 presents data from the binary logistic regression models for crude analyses and analyses adjusted for covariates, testing the associations between MDD at wave 3 and chronic physical health conditions comorbidity with functional disability. Of the total sample, 12.1% had moderate to severe disability. The proportion of individuals with moderate to severe disability was greatest for those with comorbid MDD and chronic physical health conditions (46.2%), followed by 15.9% for those with MDD only, 14.7% for those with chronic physical health conditions only, and 3.9% for those with neither MDD nor a chronic physical health condition. After accounting for covariates, results of binary logistic regression analyses indicated that the likelihood of functional disability among those with comorbid MDD and chronic physical health conditions was significantly greater than those with neither MDD nor a chronic physical health condition. Individuals with MDD only or a chronic physical health condition only also had greater odds of disability than those with neither condition, albeit

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Table 1 Demographic characteristics for groups based on the presence or absence of major depressive disorder and chronic physical health conditions (wave 3). Comorbid MDD and chronic physical health conditions n¼ 117 (5.3% of total sample) n Functional disability No Yes

MDD only

Control

n ¼44 (2.0% of total sample)

Chronic physical health conditions Only n¼ 1173 (53.3% of total sample)

%

n

%

n

%

n

%

63 54

53.8 46.2

37 7

81.4 15.9

1001 172

85.3 14.7

834 34

96.1 3.9

Age 18–29 30–44 45–59 60–73

17 37 43 20

14.5 31.6 36.8 17.1

15 23 6 15

34.1 52.3 13.6 34.1

139 321 438 275

11.8 27.4 37.3 23.4

223 350 239 56

25.7 40.3 27.5 6.5

Gender Male Female

38 79

32.5 67.5

19 25

43.2 56.8

449 724

38.3 61.7

380 488

43.8 56.2

Medication use No Yes

40 77

34.2 65.8

28 16

63.6 36.4

834 330

71.1 28.1

727 137

83.8 15.8

Marital status Married Common-law union Separated Divorced Widowed Single/never married

21 14 7 21 5 49

17.9 12.0 6.0 17.9 4.3 41.9

9 11 1 2 21 9

20.5 25.0 2.3 4.5 47.7 20.5

355 198 33 188 32 367

30.3 16.9 2.8 16.0 2.7 31.3

264 171 19 69 8 337

30.4 19.7 2.2 7.9 .9 38.8

Education o Than secondary school graduation Secondary school graduation Some postsecondary Postsecondary school graduation

17 16 9 74

14.5 13.7 7.7 63.2

8 6 2 28

18.2 13.6 4.5 63.6

146 116 93 816

12.4 9.9 7.9 69.6

51 57 59 699

5.9 6.6 6.8 80.5

Smoking status Daily Occasionally Not at all

44 7 27

37.6 6.0 23.1

22 4 6

50.0 9.1 13.6

299 56 343

25.5 4.8 29.2

147 62 188

16.9 7.1 21.7

Alcohol use frequency Regular drinker Occasional drinker Former drinker Never drank

74 15 26 2

63.2 12.8 22.2 1.7

25 9 8 2

56.8 20.5 18.2 4.5

738 221 167 46

62.9 18.8 14.2 3.9

596 143 80 47

68.7 16.5 9.2 5.4

Body mass index Normal weight Underweight Overweight Obese

46 3 37 31

39.3 2.6 31.6 26.5

20 18 6 20

45.5 40.9 13.6 45.5

446 24 363 319

38.0 2.0 30.9 27.2

466 18 254 118

53.7 2.1 29.3 13.6

n¼ 868 (39.4% of total sample)

Table 2 Results of binary logistic regression analyses for associations between MDD and chronic physical health conditions with functional disability (outcome) at wave 3. B

SE (B)

OR

[95% CI]

P value

Synergy index [95% CI]

Crude model Chronic physical health condition only MDD only Comorbidity

1.44 1.54 3.05

.19 .45 .26

4.22 4.64 21.03

[2.89, 6.16] [1.93, 11.16] [12.76, 34.65]

o.001 .001 o.001

2.92 [1.49, 5.74]

Adjusted model Chronic physical health condition only MDD only Comorbidity

1.12 1.07 2.60

.30 .50 .38

3.07 2.92 13.49

[1.71, 5.52] [.92, 9.29] [6.43, 28.33]

o.001 .070 o.001

3.13 [1.20, 8.14]

Note: Reference¼no MDD and no chronic physical health condition (i.e., control group). MDD ¼Major depressive disorder. Model 1¼unadjusted; Model 2¼ adjusted for covariates (age, gender, education, marital status, smoking status, alcohol use, medication use, and BMI).

with smaller effect sizes. Comorbidity increased the adjusted OR for disability from approximately 2.92 for those with MDD only and 3.07 for those with chronic physical health conditions only, to

approximately 13.49 for those with comorbid MDD and chronic physical health conditions. The SI was calculated to examine the interactive effects of chronic physical health and MDD on

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Table 3 Means and standard deviations number for disability days by groups based on the presence or absence of MDD and chronic physical health conditions at wave 3. Number of days in past 30 days n

Comorbidity group Comorbid MDD only Chronic physical health conditions only Control

117 44 1173 868

Of poor physical health

Of poor mental health

Inactive

M

SD

M

SD

M

SD

11.53 8.07 5.47 2.22

11.07 11.09 8.81 5.16

12.93 11.61 2.58 2.09

11.02 11.83 5.52 4.79

10.55 7.57 2.65 1.12

10.65 9.84 6.24 3.61

Note: MDD¼ Major depressive disorder.

functional disability. The adjusted SI was 3.13 (95% CI ¼1.20, 8.14), indicating a strong positive interaction, even when accounting for potentially confounding socio-demographic factors and healthrelated behaviors. Table 3 presents the unadjusted means and standard deviations for the number of disability days in the past 30 days (i.e., number of days with poor physical health, number of days with poor mental health, and number of days with activity limitations), per group. Of the total sample, 50.5% had one or more days of poor physical health, 41.1% had one or more days of poor mental health, and 32.7% had one or more days of inactivity, within the past 30 days. An ANCOVA adjusted for covariates demonstrated a main effect of group on the mean number of days with poor physical health, F(3, 1165) ¼26.12, p o.001, η2p ¼.06, the mean number of days with poor mental health, F(3, 1165) ¼ 73.91, p o.001, η2p ¼ .16, and the mean number of days inactive, F(3, 1165) ¼40.06, p o.001, η2p ¼ .09. Bonferroni-corrected post-hoc analyses indicated that those with comorbid MDD and chronic physical health conditions had a significantly greater mean number of days with poor physical health condition than those with MDD only, those with chronic physical health conditions only, and those with neither MDD nor chronic physical health conditions (ps o.01). Those with comorbid MDD and chronic physical health conditions also had a significantly greater mean number of days with poor mental health and of days inactive than those with chronic physical health conditions only group and those with neither MDD nor chronic physical health conditions (ps o .001). 3.2. Persistence of MDD Of the total sample with depression data available at the three time points (N ¼1226), 46.6% (n ¼1027) did not meet criteria for MDD at any assessment point, 6.6% (n ¼145) met criteria for MDD at one of the three assessment points, and 2.5% (n ¼54) of the sample met criteria for MDD at two or three of the three assessment points. Of those with MDD at any wave, 72.9% had transient MDD (i.e., symptoms present at only one assessment point) and 27.1% had persistent MDD (i.e., symptoms present at two or three assessment points). Table 4 presents data from binary logistic regression models testing the associations between the persistence of depression and disability, and includes crude analyses, analyses adjusted for covariates, and analyses additionally adjusted for the presence or absence of chronic health conditions. Compared to those without MDD, those with transient MDD were approximately 2.71 times more likely to have disability and those with persistent MDD were approximately 5.32 times more likely to have disability, after accounting for covariates and the presence or absence of a chronic physical health condition. To examine the effect of persistent and transient MDD on disability days, and to examine whether associations are independent of comorbid chronic physical health conditions, a series of

Table 4 Results of binary logistic regression analyses for associations between persistent and transient MDD (longitudinal assessments) with functional disability (outcome; wave 3). n

B

SE (B)

OR

[95% CI]

P value

Crude model Transient MDD Persistent MDD

145 54

1.12 2.05

.22 .29

3.07 7.73

[2.01, 4.70] [4.36, 13.71]

o .001 o .001

Model 1 Transient MDD Persistent MDD

143 54

.87 1.60

.25 .35

2.38 4.93

[1.47, 3.86] [2.50, 9.70]

o .001 o .001

Model 2 Transient MDD Persistent MDD

143 54

1.00 1.67

.24 .32

2.71 5.32

[1.71, 4.31] [2.82, 10.03]

o .001 o .001

Note: Reference¼no major depressive episode at any assessment point (n¼ 1027 crude, 1021 adjusted models). Model 1 adjusted for age, sex, and medication use. Model 2 additionally adjusts for chronic health conditions (presence or absence). MDD¼ major depressive disorder.

ANCOVAs were conducted controlling for age, sex, medication use, and the presence or absence of chronic health conditions (Table 5 presents the unadjusted means and standard deviations for disability days by group). Overall there was a main effect of MDD persistence on the number of days with poor physical health, F(2, 1211) ¼24.59, p o.001, η2p ¼.04, the number of days with poor mental health, F(2, 1211) ¼88.53, po .001, η2p ¼.13, and the number of days inactive, F(2, 1211) ¼33.02, p o.001, η2p ¼.05. Bonferronicorrected post-hoc analyses indicated that those with persistent and transient MDD reported a greater number of days with poor physical health than those without MDD (ps o .001), but did not significantly differ from each other, and that those with persistent MDD reported a greater number of days with poor mental health and days inactive than those with transient MDD and those without MDD (ps o.001). To further understand the interaction between the persistence of MDD and chronic physical health conditions on functional disability and disability days, six groups were additionally compared based on the presence or absence of a chronic physical health condition and MDD persistence. A binary logistic regression model adjusted for covariates demonstrated that, although most groups were more likely than the group without MDD and without chronic physical health conditions to have disability, those with comorbid persistent MDD and chronic physical health conditions had the highest odds ratio for disability. This group was approximately 18.89 times more likely to have disability than the group without MDD and without chronic physical health conditions (see Table 6). In addition, ANCOVAs adjusted for covariates demonstrated a main effect of group on the number of days with poor physical health F(5, 1209)¼ 36.00, p o.001, η2p ¼.13, the number of days

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Table 5 Means and standard deviations for number of disability days (wave 3) by groups based on the presence or absence of persistent, transient, or no MDD (longitudinal assessments) and by groups based on the presence or absence of chronic, transient, or no MDD and chronic physical health conditions. Number of days in past 30 days n

Major depressive disorder (MDD) No MDD Transient MDD Persistent MDD Interactions with chronic physical health conditions No MDD/no chronic physical health conditions Transient MDD/no chronic physical health conditions Persistent MDD/no chronic physical health conditions No MDD/with chronic physical health conditions Transient MDD/with chronic physical health conditions Persistent MDD/with chronic physical health conditions

Of poor physical health

Of poor mental health

Of inactivity

M

SD

M

SD

M

SD

1027 145 54

4.06 8.17 11.96

7.67 10.35 12.03

1.75 6.35 11.83

4.33 8.97 11.43

1.87 4.82 8.98

5.22 8.16 10.07

393 45 7 634 100 47

1.94 4.69 5.00 5.38 9.73 13.00

4.84 7.52 11.09 8.74 11.08 11.93

1.64 5.82 10.57 1.82 6.59 12.02

3.84 8.72 12.75 4.61 9.11 11.36

.92 2.96 6.71 2.46 5.66 9.32

3.34 6.03 8.06 6.04 8.86 10.37

Note: MDD¼ major depressive disorder. Table 6 Results of binary logistic regression analyses for associations between chronic, transient, or No MDD (longitudinal assessments) and chronic physical health conditions with functional disability (outcome; wave 3). N

B

SE (B)

OR

[95% CI] Lower

Upper

P value

Crude model Transient MDD/no chronic physical health conditions Persistent MDD/no chronic physical health conditions No MDD/with chronic physical health conditions Transient MDD/with chronic physical health conditions Persistent MDD/with chronic physical health conditions

45 7 634 100 47

1.84 1.58 1.58 2.48 3.42

.48 1.12 .30 .36 .41

6.32 4.87 4.84 11.94 30.50

2.46 .55 2.66 5.92 13.77

16.23 43.44 8.78 24.08 67.57

o .001 .156 o .001 o .001 o .001

Adjusted model Transient MDD/no chronic physical health conditions Persistent MDD/no chronic physical health conditions No MDD/with chronic physical health conditions Transient MDD/with chronic physical health conditions

45 7 629 98

1.79 1.06 1.23 2.02

.50 1.13 .31 .37

6.00 2.90 3.40 7.56

2.25 .32 1.84 3.64

15.97 26.65 6.28 15.71

o .001 .347 o .001 o .001

Persistent MDD/with chronic physical health conditions

47

2.94

.43

18.89

8.14

43.81

o .001

Reference¼ No MDD/No chronic physical health conditions (n¼ 393 in crude model, n¼392 in adjusted model). Covariates include age, sex, and medication use.

with poor mental health F(5, 1209)¼19.97, po.001, η2p ¼ .08, and the number of days with activity limitations, F(5, 1209) ¼17.14, p o.001, η2p ¼.07. Bonferroni-corrected post-hoc analyses indicated that those with persistent MDD and comorbid chronic physical health conditions reported the highest mean number of days with poor physical health, which differed significantly from those without MDD and without chronic physical health conditions, those with transient MDD without chronic physical health conditions, and those without MDD and with chronic physical health conditions (ps o .001). In addition, those with persistent MDD and comorbid chronic physical health conditions reported the highest mean number of days with poor mental health, which differed significantly from those without MDD and without chronic physical health conditions, those with transient MDD without chronic physical health conditions, those without MDD and with chronic physical health conditions, and those with transient MDD and with chronic physical health conditions (ps o.001). Those with persistent MDD and comorbid chronic physical health conditions also reported the highest mean number of days with activity limitations, which differed significantly from those without MDD and without chronic physical health conditions, those with transient MDD without chronic physical health conditions, those without MDD and with chronic physical health conditions, and those with transient MDD and with chronic physical health conditions (ps o .03) (see Table 5).

4. Discussion This study examined the interactive effects of MDD and chronic physical health conditions on functional disability and disability days. The results provide support for a synergistic interaction between MDD and chronic physical health conditions on disability, and suggest that having MDD in addition to a chronic physical health condition increases the likelihood of disability. Specifically, those with comorbid MDD and chronic physical health conditions were approximately thirteen times more likely to have moderate to severe disability than those with those without MDD or a chronic physical health condition. The interactive effect of MDD and chronic physical health conditions seems to be synergistic. The co-occurrence of MDD and chronic physical health conditions was also associated with a higher mean number of disability days than those without MDD or chronic physical health conditions. In addition, we found that persistent MDD was most strongly associated with functional disability and a greater number of disability days compared to transient MDD or no MDD, even after accounting for socio-demographic and health-related factors, including chronic physical health conditions. We also found that the interaction between the persistence of MDD and physical health conditions was associated with greater functional disability and disability days. The findings of this study are consistent with previous accounts of elevated disability in individuals with comorbid physical and mental

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health conditions (Deschênes et al., 2015; Egede, 2004, 2007; Kessler et al., 2003; Patten, 2001; Schmitz et al., 2007; Sherbourne et al., 1996; Smith and Schmitz, 2014), as well as with previous studies on chronic/ recurrent and nonchronic/nonrecurrent depression and disability in community samples (Satyanarayana et al., 2009) and in individuals with type 2 diabetes (Schmitz et al., 2014). Satyanarayana et al. (2009) found that relative to nonchronic depression, chronic depression was associated with more severe health consequences and disabilityrelated variables such as unemployment and disability days. Schmitz et al. (2014) found that in individuals with type 2 diabetes, those with recurrent sub-threshold depressive symptoms were more likely to report functional disability and disability days than those with no or low depressive symptoms or to those with a single episode of subthreshold depressive symptoms. In keeping, we found that persistent depression, assessed via structured interview, among individuals with a chronic physical illness is associated with an almost 19-fold increase in the likelihood of concurrent disability. Together, these findings suggest that depressive symptoms and MDD, especially when persistent, should be an important consideration in those with a broad range of chronic health conditions. One possibility for the higher likelihood of disability among those with comorbid MDD and chronic physical health conditions could be a greater severity of physical symptoms. In keeping, Katon et al. (2007) conducted a systematic review of the literature and found that chronically ill primary care patients with depression or anxiety symptoms reported a greater number of medical symptoms than those without depression or anxiety. Another possibility is that depression may reduce the frequency of selfcare behaviors (e.g., Ciechanowski et al., 2003) and thus worsen physical health conditions symptoms and increase disability. Collaborative care that simultaneously targets mental health and chronic physical health conditions may be a promising avenue for reducing medical symptom severity and ultimately reducing disability. For instance, a randomized control trial study of collaborative care for depression in patients with diabetes and/or coronary heart disease demonstrated that the management of both depression and the chronic health conditions led to symptom reductions and improved quality of life (Katon et al., 2010). Future research on interventions targeting depression in individuals with a broad range of chronic health conditions could be a promising avenue. The present study had several limitations. First, although the persistence of MDD was evaluated across three waves of data collection, chronic physical health conditions and disability were measured concurrently with the final MDD assessment. Therefore, the main findings reported here are cross-sectional and no causal conclusions can be drawn. We tested the synergistic interactions between mental health and chronic physical health conditions on disability; however an alternative pathway may be that physical health conditions and disability interact to produce poor mental health, or that disability in those with chronic physical health conditions may worsen mental health. Repeated assessments of health conditions and disability should be included in future longitudinal research to better understand the temporal dynamics of the associations between depression and disability in individuals with chronic physical health conditions. Second, information related to the duration of the chronic physical health condition was not included, though it is possible that longer durations of symptoms are more disabling. Third, the presence of chronic physical health conditions was based on participant self-report; participants with undiagnosed health conditions were not included in the present study. Fourth, our study focused on MDD; however other mental health conditions, such as anxiety disorders have also been shown to be elevated in chronically ill individuals (e.g., Clarke and Currie, 2009) and may also interact with chronic health conditions to produce greater disability. Fifth, we assessed the persistence of depression via the presence or

absence of MDD over repeated assessments; although this method can be advantageous (e.g., lower risk of recall bias), this method does not consider DSM-5 subtypes of MDD such as dysthymic disorder or major depressive episode, chronic type. Finally our measures of disability, which included the WHODAS 2.0 and the Healthy Days Measure, were limited by self-report. In conclusion, we found that MDD and chronic physical health conditions interacted synergistically in the association with functional disability, even when accounting for potentially confounding socio-demographic and health-related variables. Notably, individuals from the community who had MDD and a chronic physical health condition were more than 13 times more likely to have concurrent disability than individuals without MDD or a chronic physical health condition, and the odds of disability were increased to more than 18-fold when persistent depression was considered. MDD and chronic physical health condition comorbidity, particularly with persistent depression, was also associated with a greater number of disability days. Targeting persistent depression in individuals with chronic physical health conditions might help to minimize disability, although further clinical research is needed.

Role of funding source The study was funded by the Canadian Institutes of Health Research (CTP79839).

Conflict of interest None.

Acknowledgments We would like to thank the CIHR Team in Social and Psychiatric Epidemiology at the Douglas Mental Health University Institute for providing access to the study data.

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Associations between depression, chronic physical health conditions, and disability in a community sample: A focus on the persistence of depression.

Previous research has demonstrated that comorbid depression and chronic physical health conditions are associated with disability. The distinction bet...
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