Research reportThe association between dietary patterns, diabetes and depression
Section snippets
Background
Diabetes is a chronic disease with serious complications, affecting approximately 347 million people worldwide (Danaei et al., 2011) and 29.1 million children and adults in the United States (US) (9.3% of the US population) (Centers for Disease Control and Prevention, 2014). Type 2 diabetes is the most common type, with risks related to lack of regular physical activity, unhealthy eating and excess weight. Throughout the western world, obesity and prevalence of Type 2 diabetes are rising, with
Methods
Cross-sectional, population-based data from the National Health and Nutrition Examination Surveys (NHANES) (2009–2010) (Centers for Disease Control and Prevention National Center for Health Statistics, 2013) were utilized for this research study. Approximately 5000 non-institutionalized US civilians aged 20–75 per annum responded to a detailed home based interview and physical examinations at mobile examination centers across the country. The sampling methodology involved a stratified,
Depression
The Patient Health Questonnaire-9 (PHQ-9) (Kroenke and Spitzer, 2002, Kroenke et al., 2001, Martin et al., 2006) was used to assess depressive symptoms. The PHQ-9 comprises depression modules taken from the larger PRIME-MD Patient Health Questionnaire (Spitzer et al., 1999). The nine items used incorporate key depressive disorder diagnosis criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (American Psychiatric Association, 2000, Kroenke and
Statistical analysis
Initial dietary results were analyzed using exploratory factor analysis (EFA), with correlations matrix as input. Factorability of R was examined using four key measures (Tabachnick and Fidell, 2012): 1) Sample size; 2) Inspection of item correlations; 3) Kaiser–Meyer–Olkin (KMO) test of sampling adequacy; 4) Bartlett׳s test of sphericity. Factor analysis was deemed appropriate as the unweighted sample size was large, with a ratio of 179 observations per item. There were also several
Exploratory factor analysis for the diet factors
Visual inspection of correlations matrix identified several correlations more than 0.3 (Appendix 1). For the 26 items, KMO was 0.70 and Bartlett׳s test was significant (χ² (300)=317,378,113.4, p<0.001), supporting factorability of the 25 item set. Results of dimensionality tests disagreed on the number of factors potentially underlying the dietary item set: Kaiser׳s criterion identified 8 factors with eigenvalues above 1, scree test suggested the presence of 3, 5 or 8 factors (Fig. 1), parallel
Discussion
This study supports previous research in showing that a healthy diet is associated with a reduced probability of depressive symptoms or depression, particularly in those with Type 2 diabetes (Lai et al., 2014, Psaltopoulou et al., 2013, Sánchez-Villegas et al., 2013). However, it extends the extant literature in suggesting that one important mechanism linking diabetes and depression is diet quality. This finding is consistent with the results of the recent PREDIMED study, which demonstrated the
Role of funding source
There was no funding source involved with this manuscript.
Conflict of interest
JFD has no conflicts of interest.
JAP has received Grant/Research Support from the NHMRC, Perpetual, Amgen (Europe) GmBH, BUPA Foundation and Arthritis Australia and has received speaker fees from Amgen and Sanofi Aventis.
DM has no conflicts of interest.
MB has received Grant/Research Support from the NIH, Cooperative Research Centre, Simons Autism Foundation, Cancer Council of Victoria, Stanley Medical Research Foundation, MBF, NHMRC, Beyond Blue, Rotary Health, Geelong Medical Research
Acknowledgments
There are no acknowledgments to declare.
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