Given the recent emphasis on the totality of the diet by national guidelines, we examined the relationship between the quality of diet and overall and cancer-speciﬁc mortality among cancer survivors. From the Third National Health and Nutrition Examination Survey (NHANES III), 1191 participants diagnosed with cancer were identiﬁed. Healthy Eating Index (HEI) scores were utilized; higher HEI score indicated better adherence to dietary recommendations. During a median follow- up of 17.2 years, a total of 607 cancer-speciﬁc deaths occurred. A high-quality diet (highest-quartile HEI score) was associated with decreased risk of overall (hazard ratio [HR] ¼ 0.59, 95% conﬁdence interval [CI] ¼ 0.45 to 0.77) and cancer-speciﬁc (HR ¼ 0.35, 95% CI ¼ 0.19 to 0.63) mortality when compared with a poor-quality diet (lowest-quartile HEI score). Among individual dietary components, the highest-quartile score for saturated fat intake was associated decreased cancer-speciﬁc mortality (HR ¼ 0.55, 95% CI ¼ 0.36 to 0.86). Our results highlight the importance of a “total diet” approach to improving survival among cancer patients. The Dietary Guidelines for Americans (2015–2020) (1), MyPlate 1988 and 1994 (n ¼ 33 994). Participants in the NHANES are non- guidelines (2), Academy of Nutrition and Dietetics (3), and institutionalized US civilians who are identified using a com- Healthy People 2020 (4) have emphasized that a high-quality plex, stratified, multistage probability sampling technique. The “total diet”—and not just individual foods—plays a pivotal role survey includes an interview and an examination component. in health outcomes. In the past, dietary investigations have The interview component contains the standardized question- tended to focus on the impact of specific nutrients, foods, or naires on demographics, socioeconomic status, diet, and health. bioactive food components on cancer incidence and mortality. The medical examinations include data regarding medical, den- A growing body of evidence (5–9) suggests that a high-quality tal, and physiological measurements and laboratory tests. A de- and prudent diet are beneficial for specific cancer survivors (10), tailed description of the survey is available elsewhere which necessitates further investigation regarding the impor- (11). Mortality from the date of the NHANES III participation tance of overall diet quality and its association with oncologic through December 2011 was obtained from the National Center outcomes. Therefore, we examined the association between the for Health Statistics Linked Mortality Files. overall quality of dietary intake and all-cause and cancer- Participants age 18 years or older who were reportedly diag- specific mortality using a nationally representative sample of nosed with cancer (ie, replied “yes” when asked “has a doctor or cancer survivors. health care professional ever told you that you had skin or other We analyzed the Third National Health and Nutrition cancer?”) were included. Demographics, cancer diagnosis, and Examination Survey (NHANES III), conducted between the years dietary intake data were self-reported. An overall Healthy Received: February 22, 2018; Revised: April 17, 2018; Accepted: April 20, 2018 © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact firstname.lastname@example.org Downloaded from https://academic.oup.com/jncics/article-abstract/2/2/pky022/5026131 1of 4 by Ed 'DeepDyve' Gillespie user on 21 June 2018 2of 4 | JNCI J Natl Cancer Inst, 2018, Vol. 0, No. 0 A B All-cause mortality, all patients Cancer-specific mortality, all patients 1.00 1.00 HR=0.59 (95% CI, 0.45-0.77) HR=0.35 (95% CI, 0.19-0.63) 0.90 0.90 0.80 0.80 0.70 0.70 Poor quality diet 0.60 0.60 High quality diet 0.50 0.50 0.40 0.40 0.30 0.30 Poor quality diet 0.20 0.20 0.10 0.10 High quality diet 0.00 0.00 0 5 10 15 20 05 10 15 20 Time, years Time, years C All-cause mortality, non-skin cancer patients D Cancer-specific mortality, non-skin cancer patients 1.00 1.00 HR=0.64 (95% CI, 0.43-0.96) HR=0.4 (95% CI, 0.18-0.89) 0.90 0.90 0.80 0.80 0.70 0.70 0.60 0.60 Poor quality diet 0.50 0.50 High quality diet 0.40 0.40 0.30 0.30 Poor quality diet 0.20 0.20 0.10 0.10 High quality diet 0.00 0.00 0 5 10 15 20 0 5 10 15 20 Time, years Time, years All-cause mortality, skin cancer patients Cancer-specific mortality, skin cancer patients 1.00 1.00 HR=0.59 (95% CI, 0.40-0.85) HR=0.25 (95% CI, 0.11-0.58) 0.90 0.90 0.80 0.80 Poor quality diet 0.70 0.70 0.60 0.60 High quality diet 0.50 0.50 0.40 0.40 0.30 0.30 Poor quality diet 0.20 0.20 0.10 0.10 High quality diet 0.00 0.00 0 5 10 15 20 0 5 10 15 20 Time, years Time , years G H All-cause mortality, breast cancer patients Cancer-specific mortality, breast cancer patients 1.00 1.00 HR=0.37 (95% CI, 0.14-0.97) HR=0.16 (95% CI, 0.03-1.02) 0.90 0.90 0.80 0.80 0.70 0.70 Poor quality diet 0.60 0.60 0.50 0.50 High quality diet 0.40 0.40 0.30 0.30 Poor quality diet 0.20 0.20 0.10 0.10 High quality diet 0.00 0.00 0 5 10 15 20 0 5 10 15 20 Time, years Time, years Figure 1. Cumulative incidence for all-cause and cancer-speciﬁc mortality by high- and poor-quality dietary intake in cancer-diagnosed patients, NHANES III. Figure 1 illustrates cumulative incidence curves for high-quality and poor-quality dietary intake. The overall Healthy Eating Index (HEI) score was computed, and cases in the highest quartile (overall HEI score 77) were identiﬁed as those consuming a high-quality diet, whereas those in the lowest quartile (overall HEI score 57.5) were identiﬁed as those consuming a poor-quality diet. A) Cumulative incidence curves for all-cause mortality among all cancer-diagnosed patients (n ¼ 590). B) Cumulative incidence curves for cancer-speciﬁc mortality among all cancer-diagnosed patients (n ¼ 590). C) Cumulative incidence curves for all-cause mortality among patients di- agnosed with nonskin cancers (n ¼ 278). D) Cumulative incidence curves for cancer-speciﬁc mortality among patients diagnosed with nonskin cancers (n ¼ 278). E) Cumulative incidence curves for all-cause mortality among patients diagnosed with skin cancer (n ¼ 290). F) Cumulative incidence curves for cancer-speciﬁc mortal- ity among patients diagnosed with skin cancer (n ¼ 290). G) Cumulative incidence curves for all-cause mortality among patients diagnosed with breast cancer (n ¼ 65). H) Cumulative incidence curves for cancer-speciﬁc mortality among patients diagnosed with breast cancer (n ¼ 65). Cumulative incidence curves (unweighted) derived using the Cox proportional hazards model. Cumulative incidence curves (unweighted) derived using a competing risks model. CI ¼ conﬁdence interval; HR ¼ hazard ratio. Eating Index (HEI) score was between 0 and 100, which was cal- recall (12). A score of 0 is assigned for zero servings, and the culated via summation of 10 equally weighted dietary compo- maximum score indicates that the recommended servings were nents scored between 0 and 10 using a single 24-hour dietary consumed. Higher HEI scores are associated with better-quality Downloaded from https://academic.oup.com/jncics/article-abstract/2/2/pky022/5026131 by Ed 'DeepDyve' Gillespie user on 21 June 2018 Cumulative Incidence Cumulative Incidence a Cumulative Incidence Cumulative Incidence b b Cumulave Incidence b Cumulative Incidence Cumulative Incidence Cumulative Incidence A. A. Deshmukh et al. | 3 of 4 diets. The NHANES III data use the 1994–1996 version of HEI. The Table 1. Mortality by HEI components and overall HEI, NHANES III score is calculated using queries developed in Microsoft Access. Hazards ratio* (95% CI) Details of these query strategies are available elsewhere (13). Date and cause of mortality were identified from the mortal- HEI components All-cause mortality† Cancer-specific mortality‡ ity data file. The causes of mortality were defined using the International Classification of Diseases coding (ICD-10). Overall Vegetables 0.67 (0.52 to 0.86) 0.65 (0.38 to 1.14) Meat 0.82 (0.60 to 1.11) 0.66 (0.37 to 1.20) mortality included death due to any reason. Mortality was con- Grain 0.92 (0.71 to 1.20) 1.25 (0.82 to 1.91) sidered cancer specific if the reported cause was “malignant Fruit 0.71 (0.51 to 0.98) 0.58 (0.32 to 1.03) neoplasm” (ICD-10: C00-C97). Dairy 0.78 (0.65 to 0.94) 0.86 (0.57 to 1.30) We calculated the median, lower quartile, and upper quartile Fat 0.90 (0.71 to 1.15) 0.65 (0.42 to 1.02) scores for each of the 11 dietary scores (the 10 HEI dietary com- Saturated fat 0.72 (0.60 to 0.86) 0.55 (0.36 to 0.86) ponents and the overall HEI). Hazards ratios adjusted for base- Cholesterol 1.00 (0.83 to 1.19) 1.03 (0.74 to 1.43) line characteristics (age, sex, income, education, and body mass Sodium 1.04 (0.81 to 1.35) 0.75 (0.46 to 1.23) index) and comorbidities (hypertension, hyperlipidemia, diabe- Variety 0.76 (0.63 to 0.97) 0.67 (0.41 to 1.10) tes, and cardiovascular diseases) were estimated to compare Overall 0.59 (0.45 to 0.77) 0.35 (0.19 to 0.63) the mortality risk between those in the upper (indicating high- quality dietary intake) and lower (indicating poor-quality die- *NHANES III weighted hazards ratio for high-quality vs poor-quality dietary in- tary intake) quartiles for each dietary component. To exclude take among US adults diagnosed with cancer, adjusted for age, sex, income, ed- ucation, body mass index, and comorbidities (hypertension, hyperlipidemia, the participants who may have had underlying cancers at the diabetes, and cardiovascular diseases). CI ¼ conﬁdence interval; HEI ¼ Healthy time of interview, we performed sensitivity analysis where we Eating Index. censored deaths that occurred within a five-year follow-up win- †Hazard ratios estimated using Cox proportional hazards models. dow. All outcomes were assessed for the subgroups of skin can- ‡Hazard ratios estimated using competing risk models. cer patients, non–skin cancer patients, and breast cancer patients. The analyses were conducted using SAS 9.4 (Cary, NC) dietary recall and may not represent habitual dietary behavior. and adjusted using NHANES sampling weights. Information on cancer was limited to diagnosis of cancer and A total of 1191 NHANES III participants diagnosed with can- cancer type (eg, it was not possible to differentiate skin cancer cer with complete HEI scores were identified. The majority of types); stage of cancer was not available. Finally, our results may the patients were white (95%), female (60.3%), and between age be confounded due to reasons other than diet, such as lifestyle 40 and 69 years (52.5%). The two most common oncologic diag- (eg, physical activity), cancer surveillance, and treatment. noses were skin cancer (55%) and breast cancer (11%). The me- In conclusion, overall high-quality dietary intake may pro- dian overall HEI score was 68 (lower quartile ¼ 47.5, upper tect against death among cancer survivors. Identifying optimal quartile ¼ 77). Median scores for the 10 HEI components were combinations of foods and the mechanisms by which such vegetable (7.3), meat (7), grain (6.5), fruit (4.7), dairy (6.5), total fat combinations affect cancer outcomes should be the focus of (7.6), saturated fat (8.6), cholesterol (10), sodium (8.7), and vari- population health and oncology research. ety (10). A total of 607 cancer-specific deaths occurred during a median follow-up of 17.2 years. Overall and cancer-specific mortality risks are presented in Notes Figure 1. A high overall HEI score was inversely associated with Affiliations of authors: Department of Health Services Research, overall mortality (hazard ratio [HR] ¼ 0.59, 95% confidence inter- Management and Policy, College of Public Health and Health val [CI] ¼ 0.45 to 0.77). We found a similar association for Professions, University of Florida, Gainesville, FL (AAD, KS); cancer-specific mortality (HR ¼ 0.35, 95% CI ¼ 0.19 to 0.63). Department of Radiation Oncology, Banner MD Anderson Cancer Findings for cancer-specific mortality were consistent among Center, Gilbert, AZ (SMS, AL); Massachusetts General Hospital the subgroups of nonskin cancer (HR ¼ 0.4, 95% CI ¼ 0.18 to 0.89) Institute for Technology Assessment, Harvard Medical School, and skin cancer (HR ¼ 0.25, 95% CI ¼ 0.11 to 0.58) (Figure 1). The Boston, MA (JC); Department of Medicine, Section of Infectious result of sensitivity analysis (ie, when deaths within a five-year Diseases, Baylor College of Medicine, Houston, TX (EYC). window were censored) for cancer-specific mortality was con- Author contributions: study concept and design: AAD, KS; sistent (HR ¼ 0.33, 95% CI ¼ 0.18 to 0.54) with the main analysis. drafting of brief research report: AAD, KS; critical revision of the Among the individual dietary components, only saturated fat manuscript for important intellectual content: AAD, SMS, AL, intake was associated with cancer-specific mortality (Table 1), JC, EYC, KS; statistical analysis: AAD, KS; interpretation of data: but the effect size for this component (HR ¼ 0.55 for both) was AAD, SMS, AL, JC, EYC, KS. less pronounced than the overall HEI score. Dr. Chhatwal received grant support from Gilead and con- Nutritional guidelines for the general populations in several sulting fees from Gilead and Merck on unrelated projects. countries emphasize the need for a “total diet” approach to healthy eating, but guidelines for cancer patients have tended to focus on specific food components. Our study adds to a grow- Funding ing body of knowledge suggesting that an overall high-quality This work was supported by the US National Cancer dietary intake has a strong association with improved cancer- specific mortality among individuals diagnosed with cancer. Institute [R01 CA163103 to EC]. Our findings lend evidence to the emerging concept that a total diet approach to healthful eating may be more impactful than References strategies based on specific nutritional components. 1. US Department of Health and Human Services, US Department of Our findings should be interpreted within the context of their Agriculture. Dietary Guidelines for Americans: 2015 – 2020. 8th ed. 2015. limitations. Dietary intake data in the NHANES are self-reported. Alexandria, VA: Center for nutrition policy and promotion. Accessed January The HEI scores in our analysis are based on only one 24-hour 1, 2018. Downloaded from https://academic.oup.com/jncics/article-abstract/2/2/pky022/5026131 by Ed 'DeepDyve' Gillespie user on 21 June 2018 4of 4 | JNCI J Natl Cancer Inst, 2018, Vol. 0, No. 0 2. US Department of Agriculture. MyPlate. https://www.choosemyplate.gov/ womeninthe Women’s Health Initiative Observational Study: MyPlate. Accessed January 1, 2018. Evidence to inform national dietary guidance. Am J Epidemiol. 2014; 3. Freeland-Graves JH, Nitzke S, Academy of Nutrition and Dietetics, et al. 180(6):616–625. Position of the Academy of Nutrition and Dietetics: Total diet approach to 9. Kim EH, Willett WC, Fung T, et al. Diet quality indices and postmenopausal healthy eating. J Acad Nutr Diet. 2013;113(2):307–317. breast cancer survival. Nutr Cancer. 2011;63(3):381–388. 4. Department of Health and Human Services, Ofﬁce of Disease Prevention and 10. Jochems SHJ, Van Osch FHM, Bryan RT, et al. Impact of dietary patterns and Health Promotion. Healthy people 2020: Nutrition and weight status. https:// the main food groups on mortality and recurrence in cancer survivors: A sys- www.healthypeople.gov/2020/topics-objectives/topic/nutrition-and-weight- tematic review of current epidemiological literature. BMJ Open. 2018;8(2): status. Accessed January 1, 2018. e014530. 5. George SM, Irwin ML, Smith AW, et al. Postdiagnosis diet quality, the combi- 11. CDC National Center for Health Statistics. National Health and Nutrition nation of diet quality and recreational physical activity, and prognosis after Examination Survey. http://www.cdc.gov/nchs/nhanes/nhanes_question- early-stage breast cancer. Cancer Causes Control. 2011;22(4):589–598. naires.htm. Accessed January 1, 2018. 6. George SM, Ballard-Barbash R, Shikany JM, et al. Better postdiagnosis diet 12. Jones LW, Demark-Wahnefried W. Diet, exercise, and complementary ther- quality is associated with reduced risk of death among postmenopausal apies after primary treatment for cancer. Lancet Oncol. 2006;7(12): women with invasive breast cancer in the Women’s Health Initiative. Cancer 1017–1026. Epidemiol Biomarkers Prev. 2014;23(4):575–583. 13. Douglass JS, Waylett DK, Doyle E, et al. Healthy Eating Index Scores for the 7. Izano MA, Fung TT, Chiuve SS, et al. Are diet quality scores after breast can- Third National Health and Nutrition Examination Survey. TAS-ENVIRON Final cer diagnosis associated with improved breast cancer survival? Nutr Cancer. Report prepared for the National Center for Health Statistics, Centers for 2013;65(6):820–826. Disease Control and Prevention, US Department of Health and Human 8. George SM, Ballard-Barbash R, Manson JE, et al. Comparing indices of Services. 1999. Emory, Atlanta: Center for Disease Control and diet quality with chronic disease mortality risk in postmenopausal Prevention. Downloaded from https://academic.oup.com/jncics/article-abstract/2/2/pky022/5026131 by Ed 'DeepDyve' Gillespie user on 21 June 2018
JNCI Cancer Spectrum – Oxford University Press
Published: Jun 5, 2018
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