Index-based dietary patterns and risk of lung cancer in the NIH-AARP diet and health study.

BACKGROUND/OBJECTIVES: Dietary pattern analysis considers combinations of food intake and may offer a better measure to assess diet-cancer associations than examining individual foods or nutrients. Although tobacco exposure is the major risk factor for lung cancer, few studies have examined whether dietary patterns, based on preexisting dietary guidelines, influence lung cancer risk. After controlling for smoking, we examined associations between four diet quality indices-Healthy Eating Index-2010 (HEI-2010), Alternate Healthy Eating Index-2010 (AHEI-2010), alternate Mediterranean Diet score (aMED) and Dietary Approaches to Stop Hypertension (DASH)-and lung cancer risk in the NIH-AARP (National Institutes of Health-American Association of Retired Persons) Diet and Health study. SUBJECTS/METHODS: Baseline dietary intake was assessed in 460 770 participants. Over a median of 10.5 years of follow-up, 9272 incident lung cancer cases occurred. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and confidence intervals (CIs). RESULTS: Comparing highest to lowest quintiles, HRs (95% CIs) for lung cancer were as follows: HEI-2010=0.83 (0.77-0.89), AHEI-2010=0.86 (0.80-0.92), aMED=0.85 (0.79-0.91) and DASH=0.84 (0.78-0.90). Among the individual components of the dietary indices, higher consumption of whole grains and fruits was significantly inversely associated with lung cancer risk for several of the diet indices. Total index score analyses stratified by smoking status showed inverse associations with lung cancer for former smokers; however, only HEI-2010 was inversely associated in current smokers and no index score was inversely associated among never smokers. CONCLUSIONS: Although smoking is the factor most strongly associated with lung cancer, this study adds to a growing body of evidence that diet may have a modest role in reducing lung cancer risk, especially among former smokers.

Merging dietary assessment with the adolescent lifestyle.

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children.