Approximately 200 studies that examined the relationship between fruit and vegetable intake and cancers of the lung, colon, breast, cervix, esophagus, oral cavity, stomach, bladder, pancreas, and ovary are reviewed. A statistically significant protective effect of fruit and vegetable consumption was found in 128 of 156 dietary studies in which results were expressed in terms of relative risk. For most cancer sites, persons with low fruit and vegetable intake (at least the lower one-fourth of the population) experience about twice the risk of cancer compared with those with high intake, even after control for potentially confounding factors. For lung cancer, significant protection was found in 24 of 25 studies after control for smoking in most instances. Fruits, in particular, were significantly protective in cancers of the esophagus, oral cavity, and larynx, for which 28 of 29 studies were significant. Strong evidence of a protective effect of fruit and vegetable consumption was seen in cancers of the pancreas and stomach (26 of 30 studies), as well as in colorectal and bladder cancers (23 of 38 studies). For cancers of the cervix, ovary, and endometrium, a significant protective effect was shown in 11 of 13 studies, and for breast cancer a protective effect was found to be strong and consistent in a meta analysis. It would appear that major public health benefits could be achieved by substantially increasing consumption of these foods.

A self-administered diet history questionnaire has been developed for epidemiologic and clinical use. Both the food list and the nutrient values to be associated with it were developed using dietary data from 11,658 adult respondents to the Second National Health and Nutrition Examination Survey (NHANES II). Food items were selected on the basis of their contribution to total population intake of energy and each of 17 nutrients in the NHANES II data, and represent over 90% of each of those nutrients. Associated nutrient composition values were determined from the NHANES II database using frequency of consumption data in that survey. Portion sizes to be associated with each food item were derived from observed portion size distributions in NHANES II, based on three-dimensional models. The resulting food list and its corresponding brief data base, when used to calculate nutrients from a diet record, yielded correlations of r greater than 0.70 with the more detailed method. Field administration produced mean values comparable to national data.

Conventional risk factors of cardiovascular disease and mortality in the general population such as body mass, serum cholesterol, and blood pressure are also found to relate to outcome in maintenance dialysis patients, but often in an opposite direction. Obesity, hypercholesterolemia, and hypertension appear to be protective features that are associated with a greater survival among dialysis patients. A similar protective role has been described for high serum creatinine and possibly homocysteine levels in end-stage renal disease (ESRD) patients. These findings are in contrast to the well-known association between over-nutrition and poor outcome in the general population. The association between under-nutrition and adverse cardiovascular outcome in dialysis patients, which stands in contrast to that seen in non-ESRD individuals, has been referred to as "reverse epidemiology." Publication bias may have handicapped or delayed additional reports with such paradoxical findings in ESRD patients. The etiology of this inverse association between conventional risk factors and clinical outcome in dialysis patients is not clear. Several possible causes are hypothesized. First, survival bias may play a role since only a small number of patients with chronic kidney disease (CKD) survive long enough to reach ESRD. Hence, the dialysis patients are probably a distinctively selected population out of CKD patients and may not represent the risk factor constellations of their CKD predecessors. Second, the time discrepancy between competitive risk factors may play a role. For example, the survival disadvantages of under-nutrition, which is frequently present in dialysis patients, may have a major impact on mortality in a shorter period of time, and this overwhelms the long-term negative effects of over-nutrition on survival. Third, the presence of the "malnutrition-inflammation complex syndrome" (MICS) in dialysis patients may also explain the existence of reverse epidemiology in dialysis patients. Both protein-energy malnutrition and inflammation or the combination of the two are much more common in dialysis patients than in the general population and many elements of MICS, such as low weight-for-height, hypocholesterolemia, or hypocreatininemia, are known risk factors of poor outcome in dialysis patients. The existence of reverse epidemiology may have a bearing on the management of dialysis patients. It is possible that new standards or goals for such traditional risk factors as body mass, serum cholesterol, and blood pressure should be considered for these individuals.

Malnutrition inflammation complex syndrome (MICS) occurs commonly in maintenance hemodialysis (MHD) patients and may correlate with increased morbidity and mortality. An optimal, comprehensive, quantitative system that assesses MICS could be a useful measure of clinical status and may be a predictor of outcome in MHD patients. We therefore attempted to develop and validate such an instrument, comparing it with conventional measures of nutrition and inflammation, as well as prospective hospitalization and mortality. Using components of the conventional Subjective Global Assessment (SGA), a semiquantitative scale with three severity levels, the Dialysis Malnutrition Score (DMS), a fully quantitative scoring system consisting of 7 SGA components, with total score ranging between 7 (normal) and 35 (severely malnourished), was recently developed. To improve the DMS, we added three new elements to the 7 DMS components: body mass index, serum albumin level, and total iron-binding capacity to represent serum transferrin level. This new comprehensive Malnutrition-Inflammation Score (MIS) has 10 components, each with four levels of severity, from 0 (normal) to 3 (very severe). The sum of all 10 MIS components ranges from 0 to 30, denoting increasing degree of severity. These scores were compared with anthropometric measurements, near-infrared-measured body fat percentage, laboratory measures that included serum C-reactive protein (CRP), and 12-month prospective hospitalization and mortality rates. Eighty-three outpatients (44 men, 39 women; age, 59 +/- 15 years) on MHD therapy for at least 3 months (43 +/- 33 months) were evaluated at the beginning of this study and followed up for 1 year. The SGA, DMS, and MIS were assessed simultaneously on all patients by a trained physician. Case-mix-adjusted correlation coefficients for the MIS were significant for hospitalization days (r = 0.45; P < 0.001) and frequency of hospitalization (r = 0.46; P < 0.001). Compared with the SGA and DMS, most pertinent correlation coefficients were stronger with the MIS. The MIS, but not the SGA or DMS, correlated significantly with creatinine level, hematocrit, and CRP level. During the 12-month follow-up, 9 patients died and 6 patients left the cohort. The Cox proportional hazard-calculated relative risk for death for each 10-unit increase in the MIS was 10.43 (95% confidence interval, 2.28 to 47.64; P = 0.002). The MIS was superior to its components or different subversions for predicting mortality. The MIS appears to be a comprehensive scoring system with significant associations with prospective hospitalization and mortality, as well as measures of nutrition, inflammation, and anemia in MHD patients. The MIS may be superior to the conventional SGA and the DMS, as well as to individual laboratory values, as a predictor of dialysis outcome and an indicator of MICS.