Bidirectional Association between Depression and Type 2 Diabetes in Women (original) (raw)

. Author manuscript; available in PMC: 2011 Nov 22.

Abstract

Background

Although it has been hypothesized that the diabetes-depression relation is bidirectional, few studies have addressed this hypothesis in a prospective setting.

Methods

A total of 65381 women aged 50–75 years in 1996 were followed until 2006. Clinical depression was defined as having diagnosed depression or using antidepressants, and depressed mood was defined as having clinical depression or severe depressive symptomatology, i.e., a Mental Health Index (MHI-5) score ≤52. Self-reported type 2 diabetes was confirmed using a supplementary questionnaire validated by medical record review.

Results

During 10-year follow-up (531097 person-years), 2844 incident cases of type 2 diabetes were documented. Compared to referents (MHI-5 score 86–100) who had the least depressive symptomatology, participants with increased severity of symptoms (MHI-5 score 76–85, 53–75, depressed mood) showed a monotonic elevated risk of developing type 2 diabetes (P for trend = 0.002). The relative risk (RR) for individuals with depressed mood was 1.17 (95% confidence interval [CI], 1.05–1.30) after adjustment for various covariates, and participants using antidepressants were at a particularly higher risk (RR, 1.25; 95% CI, 1.10–1.41). In a parallel analysis, 7415 incident clinical depression were documented (474722 person-years). Compared to non-diabetics, the RRs of developing clinical depression after controlling for all covariates were 1.29 (95% CI, 1.18–1.40) for diabetic patients, and 1.25, 1.24, 1.53 in diabetics without medications, with oral hypoglycemic agents, and insulin therapy, respectively (all P<0.01). These associations remained significant after adjustment for diabetes-related comorbidities.

Conclusions

Our results provide compelling evidence that the diabetes-depression association is bidirectional.

INTRODUCTION

Depression and diabetes are highly prevalent in the US population. Over 10% (23.5 million) of the US adults have diabetes, and the prevalence is much higher in the elderly (23% in those aged 60+ years).1 Major depressive disorder (MDD) affects approximately 14.8 million American adults, or about 6.7 percent of the US population age 18 and older in a given year,2 and it has been estimated that the lifetime incidence of depression is more than 20% in women compared to 12% in men.3 Therefore, association between diabetes and depression in middle-aged and elderly individuals, especially among women, deserves careful examination.

The comorbidity of depression in type 2 diabetic patients has been observed in several studies. Anderson et al4 summarized 20 cross-sectional reports and found that the odds of depression in the diabetic group were twice that of the nondiabetic comparison group. Nevertheless, this could be explained by two scenarios that depression may occur as a consequence of having diabetes or as a risk factor for the onset of type 2 diabetes. Therefore, temporal relationship has attracted much attention in the past few years. A meta-analysis of cohort studies found that depression was associated with a 60% increased risk of type 2 diabetes, while the evidence supporting the opposite direction was less convincing.5 To our knowledge, only a few studies have simultaneously investigated the bidirectional association between type 2 diabetes and depression, but the results are inconsistent.6–8 Therefore, we took advantage of repeated measurements of lifestyle risk factors and disease occurrences (including depression and diabetes) during 10 years of follow-up in a large prospective cohort to address the bidirectional relationship between diabetes and depression.

SUBJECTS AND METHODS

Study Setting and Population

The Nurses’ Health Study cohort was established in 1976 when 121700 female registered nurses aged 30 –55 years residing in 11 states of the United States (US) responded to a mailed questionnaire regarding their medical history and health practices. The cohort has been followed every 2 years with mailed questionnaires that update exposure information and inquire about newly diagnosed medical illnesses. Details have been published elsewhere.9–10 Up to 2006, the follow-up rate of the entire cohort was greater than 94%. The study protocol was approved by the institutional review boards of the Brigham and Women’s Hospital and Harvard School of Public Health.

We used 1996 questionnaire cycle as baseline when clinical depression related questions were first asked (n=100939). Participants with no information on depression status at baseline (antidepressant medication use: n=10866; physician-diagnosed depression: n=6131), with a prior history of type 1 (n=266) or gestational diabetes (n=285), cancer (n=9941), coronary heart disease (n=6180), and stroke (n=845) at baseline were excluded from the analysis. We further excluded participants with secondary diabetes (n=323), unknown or uncertain diabetes cases or diagnose date (n=721) at baseline and during the follow-up. Therefore, 65381 participants were left for the current analyses.

Depression Measurement

Self-reported symptoms of depression, use of antidepressant medication and doctor diagnosed depression were used as measures of depression. Depressive symptoms were assessed in 1992, 1996, and 2000 with the Mental Health Index (MHI-5), a five-item subscale of the Short-Form 36 Health Status Survey designed to capture psychological distress versus well-being.11–13 The participants were asked how much of the time over the past month (all, most, good bit, some, little, or none) they 1) felt nervous, 2) felt so down that nothing could cheer them up, 3) felt calm and peaceful, 4) felt down and blue, or 5) felt happy. The scale was scored from 0 to 100, with lower scores indicating more severe depressive symptomatology (SDS). The MHI-5 has been shown to have high sensitivity and specificity for major depression, with an area under the receiver-operating characteristic curve of 0.88 to 0.91 for the detection of major depressive disorder (MDD).14 In accordance with our prior study using this scale, we divided the participants into 4 categories of depressive symptoms according to their MHI-5 score (86–100, 76–85, 53–75, 0–52).10

Participants were first asked to report regular antidepressant medication use in 1996, and this was utilized as the baseline year for these analyses. This information was updated biennially through 2006. The type of antidepressant use was first inquired in 2000, when participants were asked to specifically report their regular use during the past 2 years of selective serotonin reuptake inhibitors (SSRIs, including fluoxetine, sertraline, paroxetine, citalopram), or other antidepressants, of which the tricyclic antidepressants (TCAs) amitriptyline, imipramine, and nortriptyline were provided as examples. This information was updated every two years thereafter. The nurses were first asked whether they ever (1996 or before, 1997–1998, 1999, 2000) had physician-diagnosed depression in 2000. This information was also updated biennially. Therefore, clinical depression was defined as reported a physician-diagnosed depression or antidepressant use.

For the analysis of whether depression increased the risk of developing diabetes, we created a proxy measure for depressive symptoms severity utilizing the MHI-5 score and clinical depression information. The participants were categorized into four groups: MHI-5 score 86–100 (reference group), 76–85, 53–75, depressed mood (defined as the score ≤52 or with clinical depression).

Assessment of Diabetes

A supplementary questionnaire regarding symptoms, diagnostic tests, and hypoglycemic therapy was mailed to women who indicated on any biennial questionnaire that they had been diagnosed as having diabetes. Several repeated mailings were sent to non-respondents, and these were followed by telephone interviews. A case of diabetes was considered confirmed if at least one of the following was reported on the supplementary questionnaire according to the National Diabetes Data Group criteria:15 (1) one or more classic symptoms (excessive thirst, polyuria, weight loss, hunger) plus fasting plasma glucose levels of at least 7.8 mmol/L (140 mg/dL ) or random plasma glucose levels of at least 11.1 mmol/L (200 mg/dL); (2) at least two elevated plasma glucose concentrations on different occasions (fasting levels of at least 7.8 mmol/L, random plasma glucose levels of at least 11.1 mmol/L, and/or concentrations of at least 11.1 mmol/L after two hours or more shown by oral glucose tolerance testing) in the absence of symptoms; or (3) treatment with hypoglycemic medication (insulin or oral hypoglycemic agent). For cases of type 2 diabetes identified after June 1996, we lowered the cut-off point to 7.0 mmol/L (126 mg/dL ) for fasting plasma glucose concentrations according to the American Diabetes Association criteria.16 The self-reported type 2 diabetes diagnosis through supplemental questionnaire confirmation has been demonstrated to be highly accurate in a validation study conducted in a subsample of NHS participants and consisted of comparisons with medical record review by an endocrinologist.17 In addition, another validation study assessing the prevalence of undiagnosed diabetes suggested a very low rate of false-negative results.18

Covariates

Covariates were assessed using the standardized questionnaires mailed to the nurses biennially. Height and weight were ascertained on the 1976 enrollment questionnaire, and weight was further requested every two years thereafter. Self-reported weight was highly correlated with actual weight in a validation study (r=0.96).19 Body mass index was calculated as weight in kilograms divided by the square of height in meters. The questionnaire also updated the information on cigarette smoking (non-smokers, past smokers and current smokers). The presence of a family history of diabetes (in first-degree relatives) was assessed in 1982, 1988 and 1992. Marital status was inquired in 1996, 2000 and 2004. Physical activity was measured biennially (except 2002) with the use of a validated questionnaire. Participants were asked to report the hours spent per week on moderate (e.g., brisk walking) and vigorous (e.g., strenuous sports and jogging) exercise, then the total Metabolic Equivalent-hours per week (MET-hrs/wk) were estimated based on the MET score assigned to each activity.20 Dietary information (including alcohol intake) was assessed in 1994, 1998 and 2002 using a semi-quantitative food frequency questionnaire. We asked how often, on average, a participant had consumed a particular amount of a specific type of food during the previous year. Whole grain, red and processed meat, soft drinks and coffee consumptions were included in the present analysis, since they were all shown to be associated with diabetes risk in our previous analyses.21–24 Alcohol consumption was measured in grams per day, and standard drinks of alcoholic beverages were specified as a can/bottle or glass for beer, 4-oz glass for wine, and one drink or shot for liquor. The self-reported information on physical activity, alcohol consumption and food frequency questionnaire was quite reliable in the cohort and detailed information on the validity and reproducibility has been reported elsewhere.25–27

Statistical Analysis

Because our two objectives required different population samples, we hereby described analysis samples and procedures separately.

Depression Status and Incident Diabetes (Analysis 1)

In addition to the above-mentioned exclusion criteria, participants who had prevalent type 2 diabetes at baseline (n=3298), or had missing data on the depressive symptoms status at baseline (n=4203) were also excluded, and thus a total of 57880 participants were included in the analysis. Person-years for each participant was calculated from the date of return of the 1996 questionnaire to the diagnose date of confirmed type 2 diabetes, death from any cause, or June 2006, whichever came first. Cox proportional hazards models were used to estimate age- and multivariable-adjusted relative risks (RRs) of developing type 2 diabetes in participants with depressed mood compared to those without. The basic model included age in five-year category, marital status (currently having spouse or not) and family history of diabetes (yes/no); model 2 included the terms in model 1 plus lifestyle factors, including alcohol consumption (never, 0–4.9 g/d, 5+ g/d), smoking status (never/past/current), physical activity level (<9, ≥9 MET-hrs/wk), and dietary information (coffee, whole grain, soft drinks and meat consumptions, all in three categories); model 3 included the terms in model 2 and body mass index categories (<25, 25.0–29.9, ≥30 kg/m2. We selected these factors a prior because of their previous reported associations with diabetes or depression.6–8 Depression exposure was treated as a time-dependent variable, and multivariable models included the updated time-dependent covariates as used in our previous analyses.10 A complementary analysis using data from 2000 and 2006 was performed to explore the effects of different types of antidepressant medications and risk of incident diabetes.

Diabetes Severity and Incident Clinical Depression (Analysis 2)

In the 65381 participants, individuals were excluded if they had physician-diagnosed depression at baseline (n=3710), used antidepressant medications at baseline (n=2077), provided no information on antidepressant medication use in 1998 (n=2714), or had inconsistent data on diabetes medication use (n=23) in 1996, leaving 56857 participants for this analysis. Depressive symptoms (MHI-5) were only assessed in 2000 during the follow-up; hence, clinical depression was used as the end point. Since there is no exact diagnosis date for depression, the diagnosis date was estimated to be in the middle of the 2-year cycle when clinical depression was first reported. Person-years for each participant was calculated from the date of return of the 1996 questionnaire to depression diagnosis date, death from any cause, or returning date of the 2006 questionnaire, whichever came first. Cox proportional hazards models with time-varying variables were used to estimate age- and multivariable-adjusted RRs of developing clinical depression in participants with type 2 diabetes compared to those without. We again used a same series of multivariable models as to Analysis 1. Further analyses were performed to investigate the effects of different diabetes management strategies (without medications, with oral hypoglycemic agents, with insulin therapy) on incident clinical depression.

For both analyses, we first compared means or proportions of covariates across categories of depressive symptomatology (analysis 1) and diabetes severity (analysis 2) reported in 1996. For these comparisons, we used Mantel-Haenszel chi-square tests for categorical variables and analysis of variance for continuous variables. All reported P values were 2-sided, and statistical analysis was performed with SAS statistical software version 9.1 (SAS Institute Inc., Cary, North Carolina).

RESULTS

Depression Status and Incident Diabetes

TABLE 1 summarizes the characteristics of the participants without prevalent type 2 diabetes by baseline depression status. Compared to the referents (MHI-5 score 86–100), women with higher depressive symptomatology were more likely to be younger, have no spouse and smoke cigarettes, and less likely to consume alcohol and be physical active. Participants with depressed mood had elevated BMI levels than those least depressed.

Table 1.

Characteristics of women without prevalent diabetes by depressive symptomatology status in the Nurses’ Health Study in 1996 (n=57880)a

During 10-year follow-up (531097 person-years), 2844 incident cases of type 2 diabetes were documented (TABLE 2). Compared to the referents (MHI-5 score 86–100), age-adjusted RRs of developing type 2 diabetes for women with MHI-5 score 76–85, 53–75, and depressed mood were 1.07 (95% CI, 0.97–1.17), 1.24 (95% CI, 1.11–1.38), and 1.42 (95% CI, 1.28–1.58), respectively (P for trend <0.001). The RRs were slightly attenuated by including marital status and family history of diabetes in the model, and remarkably attenuated after controlling for lifestyle factors (particularly physical activity) and BMI categories, but remained significant with RRs 1.17 (95% CI, 1.05–1.30) for those with depressed mood (P for trend = 0.002).

Table 2.

Relative risk (95% CI) of incident diabetes according to the depressive symptomatology status between 1996 and 2006.

We further categorized the participants with depressed mood into three groups: women with only SDS (MHI-5 score ≤52), with physician-diagnosed depression but not with antidepressants, and with antidepressant medications. In the fully adjusted Cox model, only women using antidepressant medications had a significant increased risk of incident type 2 diabetes compared to those with MHI-5 score 86–100 (RR, 1.25; 95% CI, 1.10–1.41), whereas individuals with only SDS or diagnosed depression were not at increased risk (Table 2). A complementary analysis using data from 2000 and 2006 revealed that those using SSRIs had 15% increased risk of incident diabetes (RR, 1.15; 95% CI, 1.01–1.31), while using other antidepressants (mainly TCAs) was not significantly associated with risk of developing diabetes (RR, 1.10; 95% CI, 0.91–1.33). However, multiple antidepressants use was associated with a much higher risk (RR, 1.51; 95% CI, 1.09–2.11; data not shown in tables).

Diabetes Severity and Incident Clinical Depression

The characteristics of the participants without prevalent depressed mood by diabetes status are depicted in TABLE 3. Compared to non-diabetic women, those with diabetes were more likely to be older, and have no spouse, and less likely to consume alcohol and be physical active. Participants with diabetes had elevated BMI levels than non-diabetic individuals.

Table 3.

Characteristics of women without depressed mood by diabetes status in the Nurses’ Health Study in 1996 (n=56857)a

During 10 years of follow-up (474722 person-years), 7415 incident cases of clinical depression were documented. As shown in TABLE 4, compared to non-diabetics, the RRs of developing clinical depression in participants with type 2 diabetes were 1.44 (95% CI, 1.33–1.57) in the age-adjusted model. The RR decreased to 1.29 (95% CI, 1.18–1.40) after adjustment for the covariates. Controlling for some major comorbidities (hypertension, hypercholesterolemia, coronary heart disease, and cancer) attenuated the association but it remained significant (RR, 1.20; 95% CI, 1.10–1.31, data not shown). Similar results were found in the sensitivity analysis which excluded those with other antidepressant medication use while free of SSRIs use or self-reported physician-diagnosed depression (data not shown).

Table 4.

Relative risk (95% CI) of incident clinical depression according to diabetes status between 1996 and 2006

We then further divided the diabetic participants into three groups (without any medications, only with oral hypoglycemic agents and with insulin therapy) to reflect the severity and management of the disease. Age-adjusted RR of developing clinical depression was 1.36 (95% CI, 1.19–1.55), 1.42 (95% CI, 1.25–1.60), and 1.78 (95% CI, 1.47–2.15) for diabetic women without medications, with oral hypoglycemic agents, and with insulin therapy, respectively (P for trend <.001). These associations remained significant with adjustment for the covariates (RR, 1.25; 95% CI, 1.09–1.42; RR, 1.24; 95% CI, 1.09–1.41; RR, 1.53; 95% CI, 1.26–1.85, respectively). Incorporation of major comorbidities markedly dropped the RRs but they remained statistically significant.

COMMENT

The findings from this well characterized cohort of more than 55000 US women with 10 years’ follow-up add to the growing evidence that depression and diabetes are closely related to each other, and this reciprocal association also depends on the severity or treatment of each condition. All the associations were independent of sociodemographic, diet, and lifestyle factors.

Depression status and incident type 2 diabetes

In the present study, depressed mood (SDS or clinical depression) was moderately associated with increase of developing type 2 diabetes after adjustment for various covariates. These results are consistent with accumulating evidence that depression is a significant risk factor for developing type 2 diabetes.5, 28–29 In addition, we found that adjustment for BMI and lifestyle factors (particularly physical activity) substantially decreased the RR, indicating that BMI and physical activity could be the major mediating factors. However, the association remained significant after controlling for BMI and lifestyle factors in our models, suggesting that depression has effects on incident diabetes independent of adiposity and inactivity. Furthermore, our results showed that women with antidepressant medications were at higher risk of developing type 2 diabetes compared to those with only SDS or physician-diagnosed depression. This is consistent with the observations in the Diabetes Prevention Program study,30 in which Rubin et al reported a strong and statistically significant association between antidepressant use and diabetes risk in the intensive lifestyle and placebo treatment arms. This could be attributed to two reasons: first, antidepressant use may be a marker of more severe or a history of chronic or recurrent depression;30 second, antidepressant itself may increase the diabetes risk. Previous studies also suggested that antidepressants may exert some clinical effects on glucose homeostasis,31 but the results are inconsistent. Besides, antidepressant use is shown to be associated with weight gain.32 Although the results remained significant after adjustment for current BMI (or baseline BMI plus weight gain, data not shown), we could not fully exclude the residual confounding effects. Whether antidepressants have independent effects on diabetes warrants further investigations.

Type 2 diabetes and incident depression

We observed a significant increased risk of developing depression in the diabetic patients compared to non-diabetic patients during the 10 years of follow-up, which supports the previous notion that diabetes is a “depressogenic” condition and “stress-sensitive” disorder.5 A diagnosis of diabetes may lead to the symptoms of depression due to the following reasons: depression may result from the biochemical changes directly caused by diabetes or its treatment, or from the stresses and strains associated with suffering from diabetes and its often debilitating consequences.33 Our results are largely consistent with those from previous studies.34–35 A previous meta-analysis of seven cohort studies reported a moderate (15%) increased risk of developing depression in the diabetic patients.5 In the current investigation, we also found that women with insulin therapy, which might be a sign of poor glycemic control or severe diabetes complications, had a significantly higher risk of incident depression. Furthermore, the association between diabetes and incident clinical depression was somewhat attenuated after adjustment for comorbidities, suggesting part of the association was mediated by these comorbid conditions or diabetes complications.36–37

Strengths and Limitations

The present study was well suited to investigate the complex association between depression and type 2 diabetes using biennially repeated measurements of the diseases along with their risk factors. Therefore, time-dependent Cox regression models were performed to incorporate these repeated measures, which minimized the possibility of residual and time-dependent confounding. Consequently, we could simultaneously test the two temporal hypotheses of whether depression predicting future type 2 diabetes, and vice versa, whether type 2 diabetes increasing risk of incident depression. Furthermore, we used three measures (MHI-5 scale, antidepressants use, and physician-diagnosed depression) to define depression status. Additionally, participants with coronary heart disease, cancers, and stroke at baseline that could be associated to mood disorders were excluded from the analysis. Including those with depression associated general medical conditions did not change the results (data not shown).

Several limitations should also be borne in mind when interpreting our findings. First, the study sample was a homogeneous population and all the participants are registered nurses and more than 94% participants were white. They had a greater concern about their health and better understanding of health-related issues, which enhanced the reliability of our questionnaire assessment, but on the other hand, the results might not be generalized to other populations. Second, the exact diagnose date of depression was not available, which may lead to reverse causation to some extent in the current analysis. However, we estimated and used the date of incident depression by several different approaches in sensitivity analyses, and the results did not change materially. Third, information of physician-diagnosed depression and antidepressants use was self-reported. Physician recognition rate of MDD was not high compared to the Structured Clinical Interview according to Diagnostic and Statistical Manual of Mental Disorders,38 and the prevalence of untreated mental disorders is relatively high in US and other countries.39 Therefore, we speculate that history of or prevalent depression might be underreported. Furthermore, surveillance bias due to the disease diagnosis is also possible in our analyses.

CONCLUSIONS

This large well-established cohort study provides evidence that the association between depression and diabetes is bidirectional, and this association is partially explained by but independent of other known risk factors, such as adiposity and lifestyle variables. Future studies are needed to confirm our findings in different populations, and investigate the potential mechanisms underlying this association. Furthermore, depression and diabetes are highly prevalent in the middle-aged and elderly population, particularly in females. Thus, proper lifestyle interventions including adequate weight management and regular physical activity are recommended to lower the risk of both conditions. Although antidepressant medication use might be a marker of severe depression, its specific association with elevated risk of diabetes warrants further scrutiny.

Acknowledgments

Funding

The study was supported by the National Institute of Health (NIH) grant DK58845 (Dr Hu). Dr Ascherio received a grant from the National Alliance for Research on Schizophrenia & Depression (Project ID: 5048070-01). Dr Lucas received a postdoctoral fellowship from the Fonds de recherche en santé du Québec (FRSQ).

The funding sources did not involve in the data collection, data analysis, manuscript writing and publication.

Footnotes

Contributors:

Dr Frank Hu has full access to all of the data (including statistical reports and tables) in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

FBH, AA, JEM and WCW obtained funding and were investigators of the Nurses’ Health Study. AP, ML, JEM, WCW, AA and FBH collected data and had the idea for the current analysis. AP, ML, QS, RVD, OHF, AA and FBH provided statistical expertise. AP and ML analyzed the data. AP wrote the first draft of the manuscript. All authors contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content and approved the final version of the manuscript.

Competing Interests:

None of the authors had any financial or personal conflict of interest to disclose.

REFERENCES

• 1.Centers for Disease Control and Prevention. National diabetes fact sheet: general information and national estimates on diabetes in the United States. [Accessed on December 20, 2009];2007 http://www.cdc.gov/diabetes/pubs/factsheet07.htm.
• 2.Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005 Jun;62(6):617–627. doi: 10.1001/archpsyc.62.6.617. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 3.Belmaker RH, Agam G. Major depressive disorder. N Engl J Med. 2008 Jan 3;358(1):55–68. doi: 10.1056/NEJMra073096. [DOI] [PubMed] [Google Scholar]
• 4.Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24(6):1069–1078. doi: 10.2337/diacare.24.6.1069. [DOI] [PubMed] [Google Scholar]
• 5.Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care. 2008;31(12):2383–2390. doi: 10.2337/dc08-0985. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 6.Palinkas LA, Lee PP, Barrett-Connor E. A prospective study of Type 2 diabetes and depressive symptoms in the elderly: the Rancho Bernardo Study. Diabet Med. 2004;21(11):1185–1191. doi: 10.1111/j.1464-5491.2004.01315.x. [DOI] [PubMed] [Google Scholar]
• 7.Engum A. The role of depression and anxiety in onset of diabetes in a large population-based study. J Psychosom Res. 2007;62(1):31–38. doi: 10.1016/j.jpsychores.2006.07.009. [DOI] [PubMed] [Google Scholar]
• 8.Golden SH, Lazo M, Carnethon M, et al. Examining a bidirectional association between depressive symptoms and diabetes. JAMA. 2008;299(23):2751–2759. doi: 10.1001/jama.299.23.2751. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 9.Arroyo C, Hu FB, Ryan LM, et al. Depressive symptoms and risk of type 2 diabetes in women. Diabetes Care. 2004;27(1):129–133. doi: 10.2337/diacare.27.1.129. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 10.Whang W, Kubzansky LD, Kawachi I, et al. Depression and risk of sudden cardiac death and coronary heart disease in women: results from the Nurses' Health Study. J Am Coll Cardiol. 2009;53(11):950–958. doi: 10.1016/j.jacc.2008.10.060. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 11.Ware JE, Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–483. [PubMed] [Google Scholar]
• 12.McHorney CA, Ware JE, Jr, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care. 1993;31(3):247–263. doi: 10.1097/00005650-199303000-00006. [DOI] [PubMed] [Google Scholar]
• 13.McHorney CA, Ware JE, Jr, Lu JF, Sherbourne CD. The MOS 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care. 1994;32(1):40–66. doi: 10.1097/00005650-199401000-00004. [DOI] [PubMed] [Google Scholar]
• 14.Berwick DM, Murphy JM, Goldman PA, Ware JE, Jr, Barsky AJ, Weinstein MC. Performance of a five-item mental health screening test. Med Care. 1991;29(2):169–176. doi: 10.1097/00005650-199102000-00008. [DOI] [PubMed] [Google Scholar]
• 15.Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. National Diabetes Data Group. Diabetes. 1979;28(12):1039–1057. doi: 10.2337/diab.28.12.1039. [DOI] [PubMed] [Google Scholar]
• 16.Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care. 1997;20(7):1183–1197. doi: 10.2337/diacare.20.7.1183. [DOI] [PubMed]
• 17.Manson JE, Rimm EB, Stampfer MJ, et al. Physical activity and incidence of non-insulin-dependent diabetes mellitus in women. Lancet. 1991;338(8770):774–778. doi: 10.1016/0140-6736(91)90664-b. [DOI] [PubMed] [Google Scholar]
• 18.Field AE, Coakley EH, Must A, et al. Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med. 2001;161(13):1581–1586. doi: 10.1001/archinte.161.13.1581. [DOI] [PubMed] [Google Scholar]
• 19.Willett WC, Stampfer MJ, Bain C, et al. Cigarette smoking, relative weight, and menopause. Am J Epidemiol. 1983;117(6):651–658. doi: 10.1093/oxfordjournals.aje.a113598. [DOI] [PubMed] [Google Scholar]
• 20.Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc. 1993;25(1):71–80. doi: 10.1249/00005768-199301000-00011. [DOI] [PubMed] [Google Scholar]
• 21.de Munter JS, Hu FB, Spiegelman D, Franz M, van Dam RM. Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review. PLoS Med. 2007;4(8):e261. doi: 10.1371/journal.pmed.0040261. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 22.Fung TT, Schulze M, Manson JE, Willett WC, Hu FB. Dietary patterns, meat intake, and the risk of type 2 diabetes in women. Arch Intern Med. 2004;164(20):2235–2240. doi: 10.1001/archinte.164.20.2235. [DOI] [PubMed] [Google Scholar]
• 23.Schulze MB, Hoffmann K, Manson JE, et al. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. Am J Clin Nutr. 2005;82(3):675–684. doi: 10.1093/ajcn.82.3.675. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 24.Salazar-Martinez E, Willett WC, Ascherio A, et al. Coffee consumption and risk for type 2 diabetes mellitus. Ann Intern Med. 2004;140(1):1–8. doi: 10.7326/0003-4819-140-1-200401060-00005. [DOI] [PubMed] [Google Scholar]
• 25.Rockhill B, Willett WC, Manson JE, et al. Physical activity and mortality: a prospective study among women. Am J Public Health. 2001;91(4):578–583. doi: 10.2105/ajph.91.4.578. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 26.Giovannucci E, Colditz G, Stampfer MJ, et al. The assessment of alcohol consumption by a simple self-administered questionnaire. Am J Epidemiol. 1991;133(8):810–817. doi: 10.1093/oxfordjournals.aje.a115960. [DOI] [PubMed] [Google Scholar]
• 27.Willett W. Nutritional epidemiology. USA: Oxford University Press; 1998. [Google Scholar]
• 28.Knol MJ, Twisk JW, Beekman AT, Heine RJ, Snoek FJ, Pouwer F. Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia. 2006;49(5):837–845. doi: 10.1007/s00125-006-0159-x. [DOI] [PubMed] [Google Scholar]
• 29.Demakakos P, Pierce MB, Hardy R. Depressive symptoms and risk of type 2 diabetes in a national sample of middle-aged and older adults. The English Longitudinal Study of Aging. Diabetes Care. 2010 Jan 19; doi: 10.2337/dc09-1663. [Epub ahead of print] [DOI] [PMC free article] [PubMed] [Google Scholar]
• 30.Rubin RR, Ma Y, Marrero DG, et al. Elevated depression symptoms, antidepressant medicine use, and risk of developing diabetes during the diabetes prevention program. Diabetes Care. 2008;31(3):420–426. doi: 10.2337/dc07-1827. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 31.McIntyre RS, Soczynska JK, Konarski JZ, Kennedy SH. The effect of antidepressants on glucose homeostasis and insulin sensitivity: synthesis and mechanisms. Expert Opin Drug Saf. 2006;5(1):157–168. doi: 10.1517/14740338.5.1.157. [DOI] [PubMed] [Google Scholar]
• 32.Aronne LJ, Segal KR. Weight gain in the treatment of mood disorders. J Clin Psychiatry. 2003;64 Suppl 8:22–29. [PubMed] [Google Scholar]
• 33.Talbot F, Nouwen A. A review of the relationship between depression and diabetes in adults: is there a link? Diabetes Care. 2000;23(10):1556–1562. doi: 10.2337/diacare.23.10.1556. [DOI] [PubMed] [Google Scholar]
• 34.Maraldi C, Volpato S, Penninx BW, et al. Diabetes Mellitus, Glycemic Control, and Incident Depressive Symptoms Among 70- to 79-Year-Old Persons: The Health, Aging, and Body Composition Study. Arch Intern Med. 2007;167(11):1137–1144. doi: 10.1001/archinte.167.11.1137. [DOI] [PubMed] [Google Scholar]
• 35.Aarts S, van den Akker M, van Boxtel MP, Jolles J, Winkens B, Metsemakers JF. Diabetes mellitus type II as a risk factor for depression: a lower than expected risk in a general practice setting. Eur J Epidemiol. 2009;24(10):641–648. doi: 10.1007/s10654-009-9385-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 36.Lustman PJ, Anderson RJ, Freedland KE, de Groot M, Carney RM, Clouse RE. Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care. 2000;23(7):934–942. doi: 10.2337/diacare.23.7.934. [DOI] [PubMed] [Google Scholar]
• 37.de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ. Association of depression and diabetes complications: a meta-analysis. Psychosom Med. 2001;63(4):619–630. doi: 10.1097/00006842-200107000-00015. [DOI] [PubMed] [Google Scholar]
• 38.Lowe B, Spitzer RL, Grafe K, et al. Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians' diagnoses. J Affect Disord. 2004;78(2):131–140. doi: 10.1016/s0165-0327(02)00237-9. [DOI] [PubMed] [Google Scholar]
• 39.The WHO World Mental Health Survey Consortium. Prevalence, Severity, and Unmet Need for Treatment of Mental Disorders in the World Health Organization World Mental Health Surveys. JAMA. 2004;291(21):2581–2590. doi: 10.1001/jama.291.21.2581. [DOI] [PubMed]