<新刊紹介>瀧澤直七著稿本「日本金融史論」

<div><p></p><p><i>Background</i>: The relationship between metabolic disease and the non-modifiable risk factors sex, age and ethnicity in Africans is not well-established.</p><p><i>Aim</i>: This study aimed to describe sex, age and ethnicity differences in blood pressure (BP) and lipid status in rural Kenyans.</p><p><i>Subjects and methods</i>: A cross-sectional study was undertaken among rural Kenyans. BP and pulse rate (PR) were measured while sitting and fasting blood samples were taken for analysis of standard lipid profile. Standard anthropometric measurements were collected. Physical activity energy expenditure was obtained objectively and lifestyle data were obtained using questionnaires.</p><p><i>Results</i>: In total, 1139 individuals (61.0% women) participated aged 17–68 years. Age was positively associated with BP and plasma cholesterol levels. Sitting PR was negatively associated with age in women only (sex-interaction <i>p</i> < 0.001). Ethnicity did not modify any of the age-associations with haemodynamic or lipid outcomes. Differences in intercept between women and men were found in all parameters except for diastolic BP (<i>p</i> = 0.154), with men having lower HDL-C but higher values in all other cardiovascular risk factors.</p><p><i>Conclusion</i>: BP and plasma cholesterol levels increase with age at a similar gradient in men and women, but absolute levels of the majority of the risk factors were higher in men.</p></div

Reclassification of subjects with impaired fasting glucose and/or elevated HbA1c in three MetS groups by DRS.

<p>Reclassification of subjects with impaired fasting glucose and/or elevated HbA1c in three MetS groups by DRS.</p

Reclassification of all subjects in three MetS groups by DRS.

<p>Reclassification of all subjects in three MetS groups by DRS.</p

Baseline characteristics of subset of subjects from Inter99 cohort.

<p>Data are <i>n</i> (%) or median (interquartile range) for continuous variables. For categorical descriptors, values are counts (percentage of total for that cohort). Differences in frequency between converters and nonconverters were evaluated with a Monte Carlo estimation of the χ² statistic (2,000 replicates). Differences in medians of continuous variables were evaluated with a Wilcoxon test. NFG, normal fasting glucose; IFG, impaired fasting glucose; eHbA1c, elevated hemoglobin HbA1c.</p

Mean biomarker and risk factor values by DRS for subjects with 4–5 MetS factors.

<p>Mean levels of biomarker and MetS variables within each DRS group (A–C) for all subjects with 4–5 MetS risk factors (n = 470). The P-values are calculated by ANOVA.</p

Comparison of risk assessment of Metabolic Syndrome and DRS.

<p>*P for comparison with the row immediately above.</p><p>**95% C.I based on observed variance under bootstrap resampling of the differences to MetS.</p>#<p> = Positive Predictive Value.</p>∧<p> = Negative Predictive Value.</p

Quantitative obesity-related traits in the combined study sample and the population-based Inter99 cohort.

<p>Data are means±standard deviation. <i>p</i>-values were calculated assuming a recessive model (<i>p</i>_rec) for <i>INSIG2</i> rs7566605 variant (GG/GC vs. CC) and an additive model (<i>p</i>_add) for <i>PFKP</i> rs6602024 variant (GG vs. GA vs. AA) in the combined study sample (where all four study groups, the Inter99 cohort, the ADDITION cohort, the SDC population-based and type 2 diabetes sample were included) and the population-based Inter99 cohort. Known type 2 diabetic patients were excluded from the analyses. ^*Adjustments for the effect of age, sex and study group was introduced for the combined study sample, and for age and sex in the ^**population-based Inter99 cohort.</p

Effect of physical activity on the impact of the <i>INSIG2</i> rs7566605 genotype on BMI.

<p>Participants (<i>n</i> = 5,604) from the population-based Inter99 cohort, were divided according to self-reported physical activity categorised as physically passive and physically active and stratified according to <i>INSIG2</i> rs7566605 genotype applying a recessive model. Bars indicate mean BMI, and error bars indicate standard error. The number of participants (physically passive/physically active) are (1,712/3,259) for G-allele carriers and (202/431) for homozygous C-allele carriers. We tested for interaction effects using linear models, with or without, interaction parameters for physical activity compared by an ANOVA test (<i>p</i>_Int = 0.004).</p