It is well known that the leading causes of death are now chronic diseases such as cancer, cerebrovascular problems and heart disease in developed countries, including Japan. 1 They are related to daily lifestyle, including dietary habit, alcohol drinking, smoking, physical exercise, and factors for stress. Because dietary habit, in particular, appears to play a major role in their pathogenesis, batteries of tests to assess intake of foods/nutrients, including fats/fatty acids, antioxidants and dietary fibers, are needed for epidemiologic studies.There are several tools available, including diet records (DRs)/weighed diet records (WDRs), 24-hour recall, food frequency questionnaires (FFQs), and duplicate methods. Calculation of intake of nutrientsWe computed the average daily consumption of energy and selected nutrients using information from the FFQ and lifestyle questionnaire, including consumption of alcohol. According to the regression analysis, selected nutrients were adopted as dependent parameters and foods/food groups consumed, intake frequency, portion size (in grams) from our database, 5,8 or typical/standard values from the literature, nutrient contents per 100 grams of foods/food groups listed in the respective composition tables or of the model recipes were assumed to be independent variables. [9][10][11][12][13] With the WDRs, we calculated mean daily intakes of selected nutrients by multiplying the consumption of foods/food groups (in grams) and nutrient contents per 100 grams of foods as listed in the composition tables or model recipes. ValidationFirst, we compared mean daily intakes of energy and 26 selected nutrients gauged with the FFQ against those with the 3d-WDRs. Differences in means and ratios were computed with the FFQ vs. 3d-WDRs values, and examined by t-test using Excel ® and the SPSS ® -10.0 software package.Second, we calculated crude Pearson's correlation coefficients (CCs), log-transformed Pearson's CCs, log-transformed and energy-adjusted Pearson's CCs, and de-attenuated, log-transformed and energy-adjusted Pearson's CCs between intakes of selected nutrients based on the FFQ and 3d-WDRs. Energy adjustment was executed using regression models. 14 De-attenuated Pearson's CCs were computed by partitioning within-and inter-individual variations by one way of analysis of variance according to the formula described elsewhere. 3, 15-17 Crude Spearman's rank CCs and energy-adjusted Spearman's rank CCs were also calculated. 18,19 Statistical significance was verified with the 95% confidence interval.Third, after categorizing daily intakes of nutrients quantified with the FFQ and 3d-WDRs into quartiles, we computed percentages of exact agreement, agreement within adjacent categories, and disagreement. Ethical issuesOur study protocol was reviewed and approved by the Internal Review Board at Nagoya City University Graduate School of Medical Sciences. Written informed consent was obtained from each participant. Profile of study subjectsThe mean ages standard deviations (SDs) (minimum -max...

A cross-sectional study was conducted to clarify the associations of lifestyle factors (habitual exercise, alcohol intake and smoking habit) and plasma fatty acid (FA) concentrations as biomarkers of dietary FA intakes. We collected 7-d weighed diet records, lifestyle information and blood samples from 15 male and 79 female Japanese dietitians, and estimated dietary FA intakes and analyzed plasma FA concentrations. Plasma concentrations of eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and (n-3) highly unsaturated FA (HUFA) derived from marine foods, but not linoleic and alpha-linolenic acid from plant origins, demonstrated positive correlations with dietary intakes (r = 0.303-0.602, P < 0.05) in both genders. Multiple linear regression analyses adjusted for age, BMI, total energy intake, fat (or respective FA) consumption and lifestyle factors showed that dietary intakes of EPA, DHA and (n-3) HUFA were positively associated with age in men (P < 0.05) and negatively associated with BMI in women [P < 0.01 for DHA and (n-3) HUFA]. The plasma concentrations of EPA, DHA and (n-3) HUFA in women were found to be positively associated with age and marine oil (or respective FA) intake (P < 0.01), and negatively associated with total energy intake [P < 0.05 for EPA and (n-3) HUFA]. Lifestyle factors were not associated with dietary FA intakes and plasma FA concentrations. These findings suggest that the plasma concentrations of EPA, DHA and (n-3) HUFA might be useful biomarkers for the assessment of relative FA intakes without considering associations with habitual exercise, alcohol intake and smoking habit.

There has been increasing interest in lifestyle, including dietary habits, as an etiological factor for chronic diseases. To establish strategies for lifestyle alterations, we need to adopt a comprehensive approach for evaluating dietary habits, alcohol consumption, smoking, physical exercise, and stress. However, Japanese dietary patterns differ from those of Western developed countries, due to its distinctive culture, climate, food supply system, cooking methods, and standard serving sizes. 1-3 Japanese cuisine is rich in variety; for example, the major contributors of protein are rice, soybeans, and fish rather than meat and eggs. Moreover, people often enjoy not only Japanese foods but also Chinese, American, Italian, and French foods.

BackgroundMost diseases are thought to arise from interactions between environmental factors and the host genotype. To detect gene–environment interactions in the development of lifestyle-related diseases, and especially cancer, the Japan Multi-institutional Collaborative Cohort (J-MICC) Study was launched in 2005.MethodsWe initiated a cross-sectional study to examine associations of genotypes with lifestyle and clinical factors, as assessed by questionnaires and medical examinations. The 4519 subjects were selected from among participants in the J-MICC Study in 10 areas throughout Japan. In total, 108 polymorphisms were chosen and genotyped using the Invader assay.ResultsThe study group comprised 2124 men and 2395 women with a mean age of 55.8 ± 8.9 years (range, 35–69 years) at baseline. Among the 108 polymorphisms examined, 4 were not polymorphic in our study population. Among the remaining 104 polymorphisms, most variations were common (minor allele frequency ≥0.05 for 96 polymorphisms). The allele frequencies in this population were comparable with those in the HapMap-JPT data set for 45 Japanese from Tokyo. Only 5 of 88 polymorphisms showed allele-frequency differences greater than 0.1. Of the 108 polymorphisms, 32 showed a highly significant difference in minor allele frequency among the study areas (P < 0.001).ConclusionsThis comprehensive data collection on lifestyle and clinical factors will be useful for elucidating gene–environment interactions. In addition, it is likely to be an informative reference tool, as free access to genotype data for a large Japanese population is not readily available.

The relative contributions of variability by person were largest for all nutrients, followed by those due to sequence of days, season and day of week. Within-individual variation was greater than between-individual variation. Minimal days necessary for ascertaining major nutrients were in general fewer than micro-nutrients.