Nutritional assessment of older adults with diabetes mellitus.

Abstract Objective This systematic review evaluates the relationship between adiposity and incident colorectal cancer (CRC) risk. Methods MEDLINE, Scopus, Embase, CINAHL, and CENTRAL were searched for articles that met the following criteria: 1) assessed adiposity measures; 2) included incident data for any diagnosed malignant stage of CRC, colon cancer, or rectal cancer; and 3) studied adults aged older than 18 years. Articles were assessed for bias using the National Institutes of Health study quality assessment tools. Results Fifteen articles across ten studies met the inclusion criteria. Three significant associations were positive, one was negative, and eleven were nonsignificant and positive. Measures varied based on the tool, and these four tools were used to gather body composition measures: bioelectrical impedance, computerized tomography, dual‐energy x‐ray absorptiometry, and ultrasound. The most used were total body fat mass and percent fat, along with abdominal visceral and subcutaneous adipose tissues. Overall, higher levels of adipose were positively associated with an increased risk of CRC. The strength of associations and significance varied by body composition variable, measurement technique, tumor location, and sex. Conclusions Standardization is needed to better elucidate the relation between CRC and adiposity to allow for comparisons across papers. Additionally, a balance among precision, accessibility, and cost of measurements must be struck. image 

Adiposity associations with risk of colorectal cancer: a systematic review

Objectives
Abdominal fat may be a better predictor than body mass index (BMI) for risk of metabolically-related diseases, such as diabetes, cardiovascular disease, and some cancers. We sought to validate the percent fat reported on dual energy X-ray absorptiometry (DXA) regional spine scans (spine fat fraction, SFF) against abdominal fat obtained from total body scans using the iDXA machine (General Electric, Madison, WI), as previously done on the Prodigy model.

Methods
Total body scans and regional spine scans were completed on the same day (N = 50). In alignment with the Prodigy-based study, the following regions of interest (ROI) were assessed from total body scans and compared to the SFF from regional spine scans: total abdominal fat at (1) lumbar vertebrae L2-L4 and (2) L2-Iliac Crest (L2-IC); (3) total trunk fat; and (4) visceral fat in the android region. Separate linear regression models were used to predict each total body scan ROI from SFF; models were validated by bootstrapping.

Results
The sample was 84% female, a mean age of 38.5 ± 17.4 years, and mean BMI of 23.0 ± 3.8 kg/m2. The SFF, adjusted for BMI, predicted L2-L4 and L2-IC total abdominal fat (%; Adj. R2: 0.90) and total trunk fat (%; Adj. R2: 0.88) well; visceral fat (%) adjusted R2 was 0.83. Linear regression models adjusted for additional participant characteristics resulted in similar adjusted R2 values.

Conclusions
This replication of the strong correlation between SFF and abdominal fat measures on the iDXA in a new population confirms the previous Prodigy model findings and improves generalizability.

Use of iDXA spine scans to evaluate total and visceral abdominal fat.

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Use of iDXA spine scans to evaluate total and visceral abdominal fat.