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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Am Diet Assoc. Author manuscript; available in PMC Mar 1, 2011.
Published in final edited form as:
PMCID: PMC2850196
NIHMSID: NIHMS182904

Higher HEI-2005 scores associated with reduced symptoms of depression in an urban population: Findings from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study

Marie Fanelli Kuczmarski, PhD, RD, LDN, Professor
303E Willard Hall, Department Health, Nutrition and Exercise Sciences University of Delaware Newark DE 19716 Ph: 302-831-8765 Fax:302-831-4186 ; ude.ledu@kfm
Alexandra Cremer, MS, RD
204B Alison Hall, Department Health, Nutrition and Exercise Sciences University of Delaware Newark DE 19716 Ph: 302-831-8055 Fax:302-831-4186 ; moc.oohay@remerczz
Lawrence Hotchkiss, PhD, Information Specialist
32 Smith Hall University of Delaware Newark, DE 19716 Ph: 302-831-1989 Fax:302-831-4205 ; ude.ledu@hyrral
Nancy Cotugna, DrPH, RD, LDN, Professorcorresponding author
301E Willard Hall, Department Health, Nutrition and Exercise Sciences University of Delaware Newark DE 19716 Ph: 302-831-1006 Fax:302-831-4186 ; ude.ledu@angutocn
Michele K. Evans, MD, Deputy Scientific Director
Intramural Research Program Chief, Health Disparities Research Section 251 Bayview Boulevard, Suite 100 National Institute on Aging Baltimore, MD 21224-6825 Ph: 410-558-8110 Fax:410-558-8268 ; vog.hin.ain.crg@msnave
Alan B. Zonderman, PhD, Chief

Abstract

Background

Depression affects over 15 million Americans in a given year. Compared to physical health, less is known about the affect of diet quality on symptoms of depression.

Objective

This study investigated the relationship between diet quality and reported symptoms of depression in a low-income urban population.

Subjects/setting

Subjects included 1,118 African American and white adults, aged 30–64 years, living in Baltimore, MD and represented a sub-sample of the initial examination and recruitment phase of the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study.

Methods

Nutrition data were based on two 24-hour dietary recalls collected by trained interviewers using the United States Department of Agriculture (USDA) Automated Multiple Pass Method (AMPM). Diet quality was calculated using the USDA's Healthy Eating Index (HEI)-2005. Depressive symptoms were assessed by a trained interviewer using the Center for Epidemiologic Studies Depression (CES-D) scale.

Statistical analysis

Both linear and logistic regression analyses were used to examine whether or not diet quality was associated with depressive symptoms. The dependent variable was depressive symptoms and independent variables included HEI-2005, race, sex, age, education, income, and food assistance program participation.

Results

Mean HEI-2005 score (± SEM) was 52.17 ± 0.40 (out of 100). Mean CES-D score was 11.64 ± 0.25 (out of 40). Diet quality was significantly associated with reported symptoms of depression. However, income was a significantly stronger predictor of depression compared to diet quality, education and sex.

Conclusion

Registered dietitians should be aware of relationship between psychological status and nutritional health when assisting clients to better manage their food choices to improve their overall health and quality of life.

Keywords: Healthy Eating Index, depression, healthy aging

Major depression is the leading cause of disability in the United States (US), affecting 5–8% of the American adult population (1). The prevalence of depression is related to many factors including but not limited to race, sex, age, and chronic illness. African Americans are over-represented in populations that are at risk for mental illness (2). They are less likely than whites to have a major depressive disorder, but when they do, it is often more chronic and severe (2,3). Major depression is twice as frequent in women as men (2,4), and depression is a common disorder in later life (5). Chronic illnesses common in later life, such as Alzheimer's disease, heart disease, and cancer, among others, can actually trigger symptoms of clinical depression and these illnesses sometimes cause symptoms of depression to be overlooked and left untreated (4).

Research regarding the possible influence of dietary patterns on symptoms of psychiatric diseases is limited (6). The National Alliance on Mental Illness states that “attention to diet” can result in better mental health (2). Specific dietary recommendations in relation to symptoms of psychiatric diseases have yet to be established and the direction of the relationship between dietary choices and depression is unclear. Currently, it is not known whether dietary practices actually lead to depression or whether depression causes poor dietary choices which then may possibly worsen the condition.

Much of the current nutrition research examining diet and psychiatric health focuses on single nutrients or foods in relation to disease. Some findings indicate that individual nutrients or foods such as omega-3 fatty acids, B vitamins, or vegetables may play a role in depression (611). However, due to the complexity of dietary intake as well as the possible interactions of different nutrients, it is often difficult to attribute the effects of a single dietary component on psychological well-being.

Examining dietary patterns rather than individual nutrients may be more appropriate for analyses in nutritional epidemiology (12,13). Dietary pattern as used in this paper reflects the total diet rather than single nutrient components. A healthy diet defined by the World Health Organization's Healthy Diet Indicator score (14) was shown to be associated with a reduced prevalence of impaired cognitive function in men (15). Others have also found that healthy dietary patterns rather than intake of isolated nutrients or foods may be responsible for good overall cognitive function and fewer depressive symptoms (13,16,17).

Measuring diet quality, usually defined as how well dietary intakes adhere to current recommendation, can be problematic (18). While there is no single, universally accepted index of diet quality, an investigator can define diet quality by selecting nutritional elements considered most important in relation to health promotion and disease prevention (19,20). These elements are then combined into a diet quality index. Examples of such indices are the Healthy Eating Index-2005 (HEI-2005) (21,22), assessing conformance to the Dietary Guidelines for Americans, 2005 (18), and the Healthy Diet Indicator based on World Health Organization guidelines (14).

Considering that dietary patterns directly impact physical health, it is reasonable to expect that dietary patterns may affect symptoms of depression as well. Analyzing the diet quality of minority and low socioeconomic status (SES) populations in relation to reported depressive symptoms is especially important considering that these populations are at a higher risk of both low diet quality (23) and depression (24). The purpose of the present study was to investigate the diet quality of low-income urban African American and white adults in relationship to reported symptoms of depression. To our knowledge this is the first study to explore the relationship between depressive symptoms and diet quality measured by the HEI-2005 in a relatively large sample of understudied individuals.

METHODS

Background of Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) Study

The HANDLS study was designed to examine the independent influences of race and SES on health outcomes, specifically cognitive performance, psychiatric risk factors, and cardiovascular and cerebrovascular diseases. HANDLS is a prospective longitudinal, multidisciplinary study, assessing not only physical parameters, but also genetic, biologic, demographic, psychosocial, and psychophysiological parameters (25,26). Subjects were recruited as a fixed cohort of participants by household screenings from an area probability sample of 12 census segments in the city of Baltimore, MD. These tracts were selected because they are likely to yield representative distributions of African Americans and whites, men and women, and individuals with SES <125% Federal poverty level and ≥125% Federal poverty level. To be included in the HANDLS study, participants must 1) be within ages 30–64 years at baseline, 2) be able to give informed consent, 3) be able to perform at least five of the following evaluations: medical history, physical performance, cognitive testing, dietary recall, audio questionnaire, body composition, carotid doppler, or pulse wave velocity assessment, 4) have valid picture identification, and 5) have a verifiable address at time of entry. Exclusions include participants that are pregnant at time of entry, have a diagnosis of acquired immune deficiency syndrome, and are within 6 months of active treatment of cancer (chemotherapy, biologic, radiation).

Sample

The data used in the present study were generated from a sub-sample of the initial examination and recruitment phase collected from August 2004 to January 2008. During this time period, 28,404 households were visited and 6,469 individuals were found eligible to participate from 5,066 households. From the eligible pool, 3,042 were enrolled in the HANDLS study. Of these individuals, 2,154 (70.8%) completed the second phase of the baseline examinations. Only those individuals who completed two dietary recalls were used in this study. The study protocol was approved by the human subjects review boards at both Medstar Research Institute and the University of Delaware and all participants provided written informed consent.

Assessment of Depression

Symptoms of depression were assessed by a trained interviewer during the second phase of baseline examination which occurred on the mobile research vehicles (26). The Center for Epidemiologic Studies Depression (CES-D) scale was used to identify individuals at risk for depression (27). This assessment took place during the mobile research vehicle examination phase (26). The CES-D scale consists of 20 descriptive statements referring to the frequency of depressive symptoms during the previous week (Table 1). Total scores range from 0–60, with higher scores denoting responses in the depressed range. A score of ≥16 commonly indicates risk of depression (28,29). While the CES-D scale does not provide a clinical diagnosis of major depression, it is considered a reliable and valid measurement tool, indicating the presence of depressive symptoms in an adult population (30).

Table 1
Center for Epidemiologic Studies Depression (CES-D) Scale Statementsa and Mean (±SEM) Scores by Statement for HANDLS participants

Dietary Recall Method

The nutrition data were based on the average of two 24-hour dietary recalls, recorded by a trained interviewer using the Automated Multiple Pass Method (AMPM), a method developed by the US Department of Agriculture (USDA) (31,32). The first recall was conducted during the in-home interview; the second recall was collected 4 to 7 days later during the mobile research vehicle examination. Foods and beverages were coded and analyzed using USDA Survey net system and the Food and Nutrient Database for Dietary Studies 3.0 (33).

Diet Quality

Diet quality was calculated using the USDA's HEI-2005 (21,22). The HEI-2005 (20, Table 2) is a revised version of the original HEI that was created by the Center for Nutrition Policy and Promotion in 1995 (34). There are 12 components – total fruit, whole fruit, total vegetables, dark green and orange vegetable and legumes, total grains, whole grains, milk, meat and beans, oils, saturated fat, sodium, and calories from solid fat, alcohol, and sugar. The higher each score, the more the diet corresponds with the Dietary Guidelines for Americans, 2005 and the better the diet quality (18,22). The maximum score is 100. HEI-2005 total scores for “exemplary menus” based on the Dietary Approaches to Stop Hypertension eating plan and the American Heart Association's No Fad Diet were 99.8 and 98.6, respectively (35). However, the total mean HEI-2005 score of typical diets consumed by nationally representative samples of the US population is approximately 58 (36).

Table 2
Mean (±SEM) HEI-2005 component scores for HANDLS participants by sex and race.

Statistical Analyses

To investigate whether or not diet quality is associated with reported symptoms of depression, both linear regression analysis with no CES-D cut-off point and then logistic regression analysis with a CES-D cut-off point of 16 were used. The dependent variable was depressive symptoms. The independent variables included HEI-2005, race, sex, age, education, income, and food assistance program participation. To test the effect of diet quality and of socioeconomic factors on CES-D several models were run. A model was run with HEI-2005 alone as the independent variable, then a model was run with HEI-2005 with the socioeconomic variables of income, education, sex and race. Two and three way interaction terms between socioeconomic variables and sex and race were also included in the model with HEI-2005 and the socioeconomic variables. All P-values were based on two-sided tests and a P-value < 0.05 was considered to be statistically significant. Since age and food assistance program participation were not significant in any of the models these variables were dropped from the models and the analyses were rerun.

An analysis of variance test of difference between two additional models was also performed. CES-D was the dependent variable. The independent variables of the baseline model included sex, race, education and income. Then diet quality was added to the baseline model to observe what happens to the coefficients of education and income.

All statistical analyses were carried out using the SAS statistical analysis computer package (Ver 9.1/2002–2003; SAS Institute, Cary, NC).

RESULTS

Characteristics of Sample Participants

The study sample consisted of 1,118 people between 30 and 64 years: 250 (22%) white women, 373 (33%) African American women, 196 (18%) white men, and 299 (27%) African American men. The mean age (±SEM) of the population was 48.35 ± 0.27 years. Approximately 36% of the population had fewer than 12 years of education, 31% completed high school degree or equivalent, and the remaining 33% had 1 or more years of college. Approximately one-third of the study sample (31%) reported a total household income in the last 12 months of <$10,000; 23% reported $10,000 to <$20,000; 28% reported $20,000 to <$50,000; 18% reported ≥$50,000. Only 75 participants reported an income of $75,000 or more. Sixty-nine percent of individuals reported receiving an income from an employer within the past 12 months. Approximately 22% of the sample indicated that they did not have enough money, food stamps or Women, Infants, and Children vouchers to buy enough food to eat. Twenty-three percent reported that they had inadequate money, food stamps or Women, Infants, and Children vouchers to obtain the kinds of foods they wanted or needed. However only 11% of the sample reported they had insufficient food to eat because the kinds of food they wanted were unavailable.

Depression Scores

The mean score for each depression statement, along with the total mean score, are presented in Table 1. The mean score (±SEM) on the CES-D was 11.64 ± 0.25, with a minimum score of zero and a maximum score of 40. Women scored significantly higher on the depression scale than men (mean CES-D scores (±SEM) of 12.48 ± 0.36 and 10.57 ± 0.33, respectively; P < 0.0001), meaning women reported significantly more depressive symptoms than men (Table 1).

Whites reported fewer symptoms of depression than African Americans, although the difference was not significant (23.3% versus 25.3%, respectively). White women scored highest on the CES-D while white men scored lowest. There was a significant difference in the depressive symptoms between the sexes for both races (African Americans, p = 0.0368, whites, p = 0.0002). The percentage of the sample at risk for depression ranged from 19% for white males to 35% for white females. The percentage of women at risk for depression symptoms was higher than that of men, regardless of race.

Diet Quality

Mean scores for each component and total HEI-2005 score are presented in Table 2 for the total sample, by sex, and then by sex-race group. The overall mean HEI-2005 score (±SEM) was 52.17 ± 0.40; minimum score was 20 and maximum score was 92. The HEI-2005 score for women was significantly higher than men (P = 0.0017). The mean HEI-2005 scores of white participants was significantly higher than African Americans (53.70 ± 0.67 versus 51.22 ± 0.48, respectively; P = 0.0019). The mean HEI-2005 score for African American men was significantly lower than all other sex-race groups (Table 2). The mean HEI score for African American women was significantly lower that that of white women (Table 2).

Relationship between Depression and Diet Quality

The findings of the linear regression using only HEI-2005 as the independent predictor revealed that diet quality was inversely and significantly associated with reported symptoms of depression (adjusted R2 = 0.03, P < 0.0001). Individuals with higher quality diet reported fewer symptoms of depression. A bivariate R2 seldom is very big and the value 0.03 corresponds to a correlation of about 0.17. This relationship is highly statistically significant. In addition, the Wald chi square in the logistic regression analysis, dichotomizing the CES-D scores as <16 or ≥ 16, was significant for HEI-2005 (P =0.0002). The odds ratio point estimate indicated each unit increment (1.0) on HEI reduces the odds of depressive symptoms (CES-D>16) by a factor of 0.98. This increment is not a large decrease, but the standard deviation of HEI is about 12.5. An increase of one HEI standard deviation generates a predicted decline in the odds of depressive symptoms by a factor of 0.863.

When socioeconomic variables (education, income), sex and race were added to the model in which diet quality (HEI-2005) alone predicted CES-D, diet quality, male sex, education, and income were all significant predictors of CES-D (adjusted R2 = 0.14, p < 0.0001). All four variables were negatively related to CES-D. For example, controlling for all the other regressors, the average CES-D score for men was lower than the average for women. Or, controlling for all the other regressors, as diet quality increases, depressive symptoms (CES-D) decline. The inverse effect of HEI-2005 on depressive symptoms was attenuated appreciably when SES variables, sex and race were added to the model containing CES-D as the only regressor. The parameter estimate for HEI-2005 declined by approximately 35%, but it remained statistically significant.

The analysis of variance test of difference was performed to determine if diet quality had a mediator effect on the relationships between demographic factors and depressive symptoms. Sex, education and income all are associated with significant effects on both HEI-2005(coefficients not shown) and CES-D, including control for HE-2005. And HEI-2005 has a significant effect on CES-D controlling for sex, education, race and income. This pattern implies that CES-D functions as a mediator between exogenous variables: SES and sex, and the measure of depression: CES-D.

Linear regression analyses were performed with interaction terms to determine if the effect of HEI-2005 on depression is modified by race, sex, income and education. None of the interactions were significant.

DISCUSSION

Both depression and poor diet, independently, have been linked with increased morbidity and mortality and reduced quality of life (3740). In this study, diet quality was found to be significantly associated with reported symptoms of depression. The findings support studies reporting an association between overall diet, rather than individual nutrients or foods, and psychological well-being (6,13,15,17,4146). The inverse effect of HEI-2005 on depressive symptoms was attenuated appreciably by income but remained statistically significant. Women have higher CES-D scores than men, and education is inversely related to CES-D scores. These associations hold under control for race and socioeconomic status. Based on the results of the analysis of variance test, diet quality does have a mediator effect on the relationship between demographic factors and depressive symptoms.

Poverty and low education levels are consistent predictors of depressive symptoms (47). Food insecurity has also been related to symptoms of depression (48). Compared to national statistics, the study sample has lower income and education levels (49,50), putting them at a higher risk for poor diet quality (23) and depression (24,51), independently. While there was some income variation between subjects, none of the participants could be considered affluent. More than 50% of the HANDLS sample in this study reported a total household income in the last 12 months of less than $20,000 and another 28% reported an income between 20,000 and <$50,000. Thus the income of most HANDLS participants in this study was less than the median income of an American household in 2006 which was $48,201 (49). In addition, in 2006, 85.5% of Americans had a high school diploma or more (50), while only 64% of the sample completed high school or the equivalent. At lower education levels, the likelihood of depression increases (24). In this study, the influence of socioeconomic factors (income and education) lessened the influence of diet quality.

HEI-2005 scores indicate how closely diets adhere to the Dietary Guidelines for Americans, 2005. Unlike the original HEI scores, the total scores for the HEI-2005 are not associated with specific ratings such as good, fair or poor (52). Thus the higher the score the more closely the diet consume complies with healthful eating guidelines. The component scores of the HEI-2005 assess how closely consumption matches specific recommendations. These scores can be used to provide targeted recommendations for improving diet quality. None of the component HEI-2005 scores reached the maximum score for the total HANDLS sample or for race-sex subgroups (Table 2). Component scores for meat and beans, total grains and total vegetables approached the maximum but scores for all other components were below the target in the total HANDLS sample. Examination of the HANDLS dietary intakes indicated the majority of HANDLS participants are meeting protein recommendations through animal protein sources. However, animal products are the primary source of saturated fat which is responsible for increasing the risk of developing chronic diseases such as cardiovascular disease, diabetes mellitus, and some cancers (41,42, 5355).

The median HEI-2005 score based on 2 days of dietary recall for HANDLS participants was 51.00 out of a maximum score of 100. The diets of HANDLS participants appear to be of lower quality based on the mean HEI-2005 scores compared to the diets consumed by low-income (defined as <130% Federal poverty level) participants of the NHANES 2003–04, a nationally representative US sample. NHANES 2003–04 scores were based on one day of dietary intake data collected with USDA's AMPM method. The mean HEI-2005 score for low-income persons 2 years and older examined in the NHANES 2003–04 was 56.5(56). The component score for total grains for the low-income NHANES 2003–04 sample did achieve the maximum, while the score for the meat and bean component approached the maximum score similar to the finding for the HANDLS sample (56).

Although race was not a significant predictor of CES-D, sex was a significant predictor of CES-D in the regression models and also played a role in attenuating the HEI-2005-depression relationship but its influence was less than that of income. Women in the sample scored significantly higher on the depression scale than men suggesting women experience more depressive symptoms than their male counterparts. This finding is congruent with national statistics reporting the incidence of depression is two times higher in women than men (2,4). While female HANDLS study participants also scored significantly higher on the HEI-2005 compared to the male HANDLS study participants, their scores were still below those reported for the NHANES 2003–04 low-income samples.

Limitations of Study

The HEI-2005 scores in this study were based on two nonconsecutive 24-hour dietary recalls. Two recalls provide more reliable information than one recall but there are still limitations to this dietary collection method. Recalls may be inaccurate and biased because of misreporting, primarily underreporting. Even though the AMPM method is valid, energy can be underestimated by 11% for a population of normal, overweight and obese persons (31). The energy underestimation for normal weight persons is about 3% but the underestimation for overweight and obese persons is yet to be determined (31).

No causal link can be inferred from this cross-sectional study. It is unclear whether the cross-sectional association between measure of diet quality and depression is due to the effects of diet on depression, the effects of depression on diet, or both. However, the findings of this study are consistent with previous studies relating dietary patterns and depression (6,13,15,17), reinforcing the need for further research on the relationships between diet and depression. Future longitudinal data generated from the HANDLS study may provide insight regarding the direction and cause of the relationship between diet and depression.

CONCLUSION

This study is the first analysis examining the relationship between diet quality measured by HEI-2005 and symptoms of depression in a diverse group of American adults with low education and income levels participating in the HANDLS study. The data demonstrated that diet quality was significantly associated with reported symptoms of depression. As it is widely recognized that common symptoms of psychiatric disorders such as depression contribute to the burden of diseases many of which have nutritional implications, greater collaboration between experts in the areas of depression and nutrition are warranted. When conducting nutrition assessments as part of the Nutrition Care Process, dietitians should be alert for depressive symptoms in their clients as they devise interventions to improve overall dietary patterns in their clients. This study highlights the importance of paying particular attention to the overall dietary patterns as well as individual nutrient status. While this study did not examine the obesity issues of the HANDLS population, further outcomes generated from the HANDLS study in the area of depression and obesity will also be of interest to dietitians.

Acknowledgments

Funding Disclosure This research is funded by the Intramural Research Program of the National Institute of Aging, National Institute of Health.

Footnotes

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REFERENCES

1. Pratt LA, Body DJ. NCHS Data Brief. Vol. 8. 2008. Depression in the united States Household Population, 2005–2006; pp. 1–7. DHHS Publication No. (PHS) 2008-1209. [PubMed]
2. Mental Health America Web site (formerly known as National Mental Health Association) [Accessed July 2 2009]. http://www.nmha.org/.
3. Williams DR, Gonzalez HM, Neighbors H, Nesse R, Abelson JM, Sweetman J, Jackson JS. Prevalence and distribution of major depressive disorder in African Americans, Caribbean Blacks, and Non-Hispanic Whites. Arch Gen Psychiatry. 2007;64:305–315. [PubMed]
4. National Institute of Mental Health Web site. Jan2009. [Accessed July 2, 2009]. http://www.nimh.nih.gov/.
5. Koster A, Bosma H, Kempen GIJM, Penninx BWJH, Beekman ATF, Deeg DJH, van Eijk JThM. Socioeconomic differences in incident depression in older adults: the role of psychosocial factors, physical health status, and behavioral factors. J Psychosom Res. 2006;61:619–627. [PubMed]
6. Peet M. International variations in the outcome of schizophrenia and the prevalence of depression in relation to national dietary practices: an ecological analysis. Br J Psychiatry. 2004;184:404–408. [PubMed]
7. Morris MS, Fava M, Jacques PF, Selhub J, Rosenberg IH. Depression and folate status in the US population. Psychother Psychosom. 2003;72:80–87. [PubMed]
8. Tucker KL, Quao N, Scott T, Rosenberg I, Spiro A. High homocysteine and low B vitamins predict cognitive decline in aging men: the Veterans Affairs Normative Aging Study. Am J Clin Nutr. 2005;82:627–635. [PubMed]
9. Williams A, Katz D, Ali A, Girard C, Goodman J, Bell I. Do essential fatty acids have a role in the treatment of depression? J Affect Disord. 2006;93:117–123. [PubMed]
10. Woo J, Lynn H, Lau WY, Leung J, Lau E, Wong SYS, Kwok T. Nutrient intake and psychological health in an elderly Chinese population. Int J Geriatr Psychiatr. 2006;21:1036–1043. [PubMed]
11. Sanchez-Villegas A, Henriquez P, Bes-Rastrollo M, Doreste J. Mediterranean diet and depression. Public Health Nutr. 2006;9:1105–1109. [PubMed]
12. Schulze MB, Hoffmann K. Methodological approaches to study dietary patterns in relation to risk of coronary heart disease and stroke. Br J Nutr. 2006;95:860–869. [PubMed]
13. Samieri C, Jutand MA, Feart C, Capuron L, Letenneur L, Barberger-Gateau P. Dietary patterns derived by hybrid clustering method in older people: association with cognition, mood, and self-rated health. J Am Diet Assoc. 2008;108:1461–1471. [PubMed]
14. Huijbregts P, Feskens E, Rasanen L, Rasanen L, Fidanza F, Nissinen A, Menotti A, Kromhout D. Dietary pattern and 20 year mortality in elderly men in Finland, Italy, and the Netherlands: longitudinal cohort study. Br Med J. 1997;315:13–17. [PMC free article] [PubMed]
15. Huijbregts PPCW, Feskens EJM, Rasanen L, Fidanza F, Alberti-Fidanza A, Nissinen A, Giampaoli S, Kromhout D. Dietary patterns and cognitive function in elderly men in Finland, Italy and the Netherlands. Eur J Clin Nutr. 1998;52:826–831. [PubMed]
16. World Health Organization . Report of a WHO study group. Geneva World Health Organization; 1990. Diet, nutrition, and the prevention of chronic diseases. WHO Technical Report Series no. 797. [PubMed]
17. Correa Leite ML, Nicolosi A, Cristina S, Hauser WA, Nappi G. Nutrition and cognitive deficit in the elderly: a population study. Eur J Clin Nutr. 2001;55:1053–1058. [PubMed]
18. US Department of Health and Human Services and United States Department of Agriculture Dietary Guidelines for Americans, 2005. 6th Edition Washington, DC: U.S. Government Printing Office; Jan, 2005.
19. Newby PK. Examining energy density: comments on diet quality, dietary advice, and the cost of healthful eating. J Am Diet Assoc. 2006;106:1166–1169. [PubMed]
20. Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc. 2004;104:615–635. [PubMed]
21. Healthy Eating Index (2005) United States Department of Agriculture, Center for Nutrition Policy and Promotion Web Site. Jun2008. [Accessed June 30, 2009]. http://www.cnpp.usda.gov/Publications/HEI/healthyeatingindex2005factsheet.pdf.
22. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index- 2005. J Am Diet Assoc. 2008;108:1896–1901. [PubMed]
23. Basiotis PP, Carlson A, Gerrior SA, Juan WY, Lino M. The Healthy Eating Index: 1999–2000. US Department of Agriculture, Center for Nutrition Policy and Promotion; 2002. CNPP-12.
24. Lennon MC, Blome J, English K. Executive summary. Depression and low income women: challenges for TANF and Welfare-to-work policies and programs. Research forum on children, families, and the new federalism. 2001
25. Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) Web site. [Accessed July 2, 2009]. http://handls.nih.gov/. Published July 1, 2004.
26. HANDLS Research Protocol Version No: 3. Aug 102004. [Accessed July 2, 2009]. Web site. http://handls.nih.gov/img/pdf/HANDLS-2Protocol-2004-10-08-Protocol.pdf Published July 1, 2004.
27. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401.
28. Zhang X, Norris SL, Gregg EW, Cheng YJ, Beckles G, Kahn HS. Depressive symptoms and mortality among persons with and without diabetes. Am J Epidemiol. 2005;161:652–660. [PubMed]
29. Stansbury JP, Ried LD, Velozo CA. Unidemensionality and bandwidth in the Center for Epidemiologic Studies Depression (CES-D) Scale. J Pers Assess. 2006;86:10–22. [PubMed]
30. John PD, St, Blandford AA, Strain LA. Depressive symptoms among older adults in urban and rural areas. Int J Geriatr Psychiatr. 2006;21:1175–1180. [PubMed]
31. Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, Paul DR, Sebastian RS, Kuczynski KJ, et al. The US Department of Agriculture automated multiple-pass method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008;88:324–32. [PubMed]
32. Conway JM, Ingwersen LA, Moshfegh AJ. Accuracy of dietary recall using the USDA five-step multiple-pass method in men: an observational validation study. J Am Diet Assoc. 2004;104(4):595–603. [PubMed]
33. USDA Food and Nutrient Database for Dietary Studies, 3.0 [Internet] Agricultural Research Service, Food Surveys Research Group; Beltsville: 2008. [Accessed June 10, 2009]. [cited 2009 Jun 10]. http://www.ars.usda.gov/Services/docs.htm?docid=12089.
34. Kennedy ET, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: design and applications. J Am Diet Assoc. 1995;96:1103–1108. [PubMed]
35. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB. Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc. 2008;108:1854–1864. [PubMed]
36. US Department of Agriculture, Center for Nutrition Policy and Promotion . Nutrition Insight 37. Dec, 2007. Diet quality of Americans as measured by the Healthy Eating Index-2005. slightly revised August 2008.
37. Lichtman JH, Bigger JT, Blumenthal JA, Frasure-Smith N, Kaufmann PG, Lesperance F, Mark DB, Sheps DS, Taylor CB, Froelicher ES. Depression and coronary heart disease. Circulation. 2008;118:1176–1775. [PubMed]
38. Kennedy ET. Evidence for nutritional benefits in prolonging wellness. Am J Clin Nutr. 2006;83(suppl):410S–414S. [PubMed]
39. Jiang W. Impacts of depression and emotional distress on cardiac disease. Clev Clin J Med. 2008;75(suppl):S20–S25. [PubMed]
40. van Dam RM. Combined impact of lifestyle factors on mortality: prospective cohort study in US women. Br Med J. 2008;337:a1440. doi:10.1136/bmj.a1440. [PMC free article] [PubMed]
41. Fogli-Cawley JJ, Dwyer JT, Saltzman E, McCullough ML, Troy LM, Meigs JB, Jacques PF. The 2005 Dietary Guidelines for Americans and risk of the metabolic syndrome. Am J Clin Nutr. 2007;86:1193–1201. [PubMed]
42. Fung TT, Willet WC, Stampfer MJ, Manson JE, Hu FB. Dietary patterns and the risk of coronary heart disease in women. Arch Intern Med. 2001;161:1857–1862. [PubMed]
43. Jacques PF, Tucker KL. Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr. 2001;73:1–2. [PubMed]
44. Nitzke S, Freeland-Graves J. Position of the American Dietetic Association: total diet approach to communicating food and nutrition information. J Am Diet Assoc. 2007;107:1224–1232. [PubMed]
45. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13:3–9. [PubMed]
46. Osler M, Heitmann BL, Hoidrup S, Jorgensen LM, Schroll M. Food intake patterns, self-rated health and mortality in Danish men and women. A prospective observational study. J Epidemiol Community Health. 2001;55:399–403. [PMC free article] [PubMed]
47. Johnston E, Johnson S, McLeod P, Johnston M. The relation of body mass index to depressive symptoms. Canadian J Public Health. 2004;95:179–183. [PubMed]
48. Hadley C, Patel CL. Seasonal changes in household food insecurity and symptoms of anxiety and depression. Am J Physical Anthropology. 2008;135:225–232. [PubMed]
49. DeNavas-Walt C, Proctor BD, Smith J. U.S. Census Bureau, Current Population Reports, P60-233, Income, Poverty, and Health Insurance Coverage in the United States: 2006. Washington, DC: U.S. Government Printing Office; 2007.
50. American FactFinder United States Census Bureau Web site. [Accessed July 2, 2009]. http://factfinder.census.gov.
51. Riolo SA, Nguyen TA, Greden JF, King CA. Prevalence of depression by race/ethnicity: findings from the National Health and Nutrition Examination Survey III. Am J Public Health. 2005;95:998–1000. [PMC free article] [PubMed]
52. Dixon LB. Updating the Healthy Eating Index to reflect current dietary guidance. J Am Diet Assoc. 2008;108:1837–1842. [PubMed]
53. Walker P, Rhubart-Berg P, McKenzie S, Kelling K, Lawrence RS. Public health implications of meat production and consumption. Public Health Nutr. 2005;4:348–356. [PubMed]
54. US Department of Health and Human Services, National Institutes of Health and National Heart, Lung, and Blood Institute . DASH Eating Plan. NIH Publication No. 06-4082. Revised April 2006.
55. Andrews G. Should depression be managed as a chronic disease? Br Med J. 2001;322:419–421. [PMC free article] [PubMed]
56. US Department of Agriculture, Center for Nutrition Policy and Promotion . Nutrition Insight 42. Dec, 2008. Diet quality of low Income and Higher Income Americans in 2003-04 as measured by the Healthy Eating Index-2005.
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