Syndrome X: Is it for real?

The term syndrome X has been applied to the association of hypertension, non-insulin-dependent diabetes mellitus (NIDDM), android obesity, insulin resistance, and dyslipidemia. In this paper, based on population samples from Tecumseh, Michigan, and Hiroshima, Japan, characterized by persons ≥40 years of age, we examine the validity of regarding this constellation of traits as a true syndrome, i.e., an array of traits with a single, unifying pathophysiology underlying its components. Data were not available on insulin resistance and dyslipidemia, and obesity was expressed as body mass index (BMI) without the division into android and non-android types. The four ethnic-gender data sets were analyzed on the basis of two age classes, age ≥40 years and age ≥50 years, and two obesity classes, BMI ≥27 and ≥30. A simple Χ 2 test of goodness-of-fit under a model of independence revealed non-random associations between hypertension, NIDDM, and BMI which were in part attributable to an excess of persons with all three traits. However, when the four data sets were subjected to separate log-linear analyses of the three-way association tables, none of the three-factor interaction terms (i.e., syndrome X) was significant. High significance was, however, observed in the two-factor interaction term for BMI*hypertension. It is concluded that the significant association between these three traits is driven by the BMI*hypertension interaction, and there is no evidence in these data sets of a significant role for a syndrome X. Genet. Epidemiol. 15:19–32,1998. © 1998 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38510/1/2_ftp.pd

Changing patterns of life-style and nutrition of men In Japan and Australia

This was a simultaneous study of cross-cultural and inter-generational men from Japan and Australia that involved an extensive questionnaire containing food intake, physical activity, anthropometric and lifestyle items. A comparative lifestyle index was constructed and examined. The food intakes were further analysed using factor analysis. The dietary patterns that emerged were correlated against anthropometric obesity measurements, nutrients and lifestyle items and discussed in the context of the current literature on chronic diseases