ResearchCurrent ResearchThe Diet Quality Index-Revised: A Tool to Promote and Evaluate Dietary Change among Older Cancer Survivors Enrolled in a Home-Based Intervention Trial
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Subjects
The methods for this trial have been detailed elsewhere (21). In brief, 2,010 older adults within 18 months of diagnosis with loco-regional prostate or female breast cancer were identified through cancer registries, physician’s offices, and self-referral, and were invited into this trial after permission was received from their oncology care physicians (see Figure 1). The trial complied with Health Insurance Portability and Accountability Act of 1996 guidelines and was approved by the Duke
Results
A total of 182 people were accrued into this trial. Study participants were predominantly white, married, female, and from moderate-income households. The sample also was well-educated because 67% had education beyond high school, compared to 59% of elders reported by the US Bureau of Statistics (36). Furthermore, their quality of life scores were high. Like many survivors of breast and prostate cancer (12), most were overweight. There were no significant differences between arms with regard to
Discussion
Although several cross-sectional studies have quantified diet quality using global dietary indexes (1, 2, 4, 5, 13, 14, 15, 17, 18, 25, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49) and a handful of dietary intervention studies have used global diet quality as an outcome measure (50, 51, 52, 53), to our knowledge this is one of the first trials that has used a global diet quality index as both an intervention strategy and an evaluation tool. The only other study to report such methodology
Conclusions
The DQI-R was helpful in guiding dietary counseling and measuring overall diet quality for this randomized controlled trial. Recent changes in the Dietary Guidelines (61) include focusing on specific fats (consuming more unsaturated than saturated or trans fats) rather than total fat. Refining diet quality measures to focus on quality nutrient sources (fish and white meats replacing red meats and whole grains over refined breads) may improve current measures. Using indexes encompassing multiple
D. C. Snyder is a clinical trials manager, School of Nursing, R. Sloane is a biostatistician, Center for Study of Aging and Human Development, C. Pieper is an assistant professor, department of Biometry and Bioinformatics, and W. Demark-Wahnefried is a professor, School of Nursing and Department of Surgery, Duke University, Durham, NC.
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Cited by (22)
ESPEN guidelines on nutrition in cancer patients
2017, Clinical NutritionCitation Excerpt :This incorporates calculation or measurement of energy and nutrient requirements, food preparation and/or modifying of texture or nutrient content, increasing meal frequency by distribution of foods to several small meals, enriching dishes with energy- and protein-dense additives, offering oral nutritional supplements, a meal set-up plan that emphasizes supportive interventions to improve oral food intake (e.g. treating mucositis and other symptoms), digestion (e.g. pancreatic enzymes) or absorption (e.g. slowing of rapid gastrointestinal transit), antiemetics, and other relevant conditions. Applicability of guideline recommendations on these topics is improved by using standardized diagnostic tools and therapeutic procedures [150–153]. Artificial nutrition is indicated if patients are unable to eat adequately (e.g. no food for more than one week or less than 60% of requirement for more than 1–2 weeks; see A.1).
Evaluation of Nutrition Interventions
2013, Nutrition in the Prevention and Treatment of DiseaseSFNEP oncology nutrition guidelines: Therapeutic strategy for the management of undernutrition in the elderly
2012, Nutrition Clinique et MetabolismeEvaluation of Nutrition Interventions
2012, Nutrition in the Prevention and Treatment of Disease, Third EditionBenefits of wellness interventions for persons with chronic and disabling conditions: A review of the evidence
2010, Disability and Health JournalIs improvement in the Healthy Food Intake Index (HFII) related to a lower risk for gestational diabetes?
2017, British Journal of Nutrition
D. C. Snyder is a clinical trials manager, School of Nursing, R. Sloane is a biostatistician, Center for Study of Aging and Human Development, C. Pieper is an assistant professor, department of Biometry and Bioinformatics, and W. Demark-Wahnefried is a professor, School of Nursing and Department of Surgery, Duke University, Durham, NC.
E. C. Clipp is a professor of nursing and medicine, Duke University, Durham, NC, and a nurse scientist, Geriatric Research Education and Clinical Center, Veterans Administration Medical Center, Durham, NC.
M. C. Morey is an associate research professor of medicine, Duke University, Durham, NC, and associate director for research, Geriatric Research Education and Clinical Center, Veterans Administration Medical Center, Durham, NC.
H. Cohen is a chair and professor, Department of Medicine, and director, Center for the Study of Aging, Duke University Medical Center, Durham, NC.
P. S. Haines is an associate professor, Department of Nutrition, University of North Carolina at Chapel Hill.
P. Miller is a doctoral candidate, Department of Nutritional Sciences, The Pennsylvania State University, University Park; at the time of the study, she was a research assistant, Department of Surgery, Duke University, Durham, NC.