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PURPOSE: To evaluate the 2-year effects of intrastromal corneal ring segments (INTACS) on the corneal endothelium. METHODS: Non-contact specular microscopy was performed as a subgroup test in a Phase III clinical trial. Endothelial cell images were collected before surgery and at 6, 12, and 24 months after surgery at the central and peripheral (6 and 10 o'clock) regions. Images were recorded and analyzed later by a central reading center. Cell density, coefficient of variation, and percent hexagonal cells were determined. RESULTS: There were no clinically significant changes in the endothelial cell structure at 6, 12, and 24 months (102 eyes). There was a gain of 5 cells/mm2 (6 months) and 3 cells/mm2 (12 months) at the central region of the cornea and a loss of 28 cells/mm2 at 24 months. At the 6 o'clock region of the cornea, there was a loss of 0, 24, and 92 cells/mm2 at 6, 12, and 24 months. At the 10 o'clock region of the cornea, there was a loss of 14, 30, and 94 cells/mm2 at 6, 12, and 24 months. INTACS did not statistically affect the central cell density at 6 and 12 months, however, there was a slight loss centrally at 24 months. At 24 months, all corneal regions had a slight decrease in cell density. In all eyes, mean central and peripheral endothelial cell counts remained above 2495 cells/mm2. Coefficient of variation improved and percent hexagonal cells remained unchanged. CONCLUSION: Endothelial cell density changes at 2 years after INTACS implantation were not clinically significant and endothelial cell remodeling was present.

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Change and correlates of change in high and low density lipoprotein cholesterol (HDL and LDL) were studied in a prospective population-based study of 614 men and women in Rancho Bernardo, CA, 1972-1980. Correlations between baseline and follow-up examination an average of six years later were 0.72 for HDL and 0.68 for LDL, and 86% of HDL and 89% of LDL values were within +/- 30% of their original values. Predictions of HDL and LDL change were determined by multivariate analysis. Regression to the mean was the strongest single predictor of lipoprotein change and was more important than behavioral change. Among the behavioral variables, HDL change was positively associated with change in alcohol use in both sexes and with change in postmenopausal estrogen use in women and was inversely associated with change in obesity index in men. LDL change correlated positively with change in obesity index in both sexes. Change in reported cigarette use or exercise was unrelated to changes in HDL and LDL in this analysis. The similarity of lipoprotein values at baseline and follow-up suggests reasonable reliability and prognostic validity for a single HDL or LDL measurement. The multivariate analysis results generally confirm current cross-sectionally derived concepts about behavioral correlates of lipoproteins. However, the degree of regression to the mean indicates the wisdom of repeat measurements, particularly for persons with extreme values.

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To evaluate the validity and implications of using various obesity indices in adjusting or controlling for obesity, correlations were analyzed between six cardiovascular disease risk factors, age, cholesterol, log triglyceride, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, and weight (W), height (H), and five commonly used obesity indices, W/H, W/H2, 3 square root W/H, -H/3 square root W, and relative weight in a defined population of 4956 men and women. Subjects were residents of Rancho Bernardo, California and were surveyed in 1972-1974. Correlations of weight, height, and the obesity indices were also evaluated with each other. W/H, 3 square root W/H, and -H/3 square root W were highly correlated with weight (correlations = 0.96-0.997), but also correlated with height (correlations = 0.10-0.48). These very high correlations with weight and moderate correlations with height resulted in risk factor correlations with these three indices reflecting weight-risk factor correlations rather than obesity-risk factor correlations. W/H2 and relative weight were not quite so highly correlated with weight (correlations = 0.83-0.89), very highly correlated with each other (correlations = 0.999), and relatively uncorrelated with height (correlations = 0.17-0.01). W/H2 and relative weight risk factor correlations reflected true obesity-risk factor correlations and were significantly greater than risk factor correlations with weight, W/H, 3 square root W/H, and -H/3 square root W. These data strongly support the use of either W/H2 or relative weight for obesity adjustment in cardiovascular disease studies. Use of W/H, 3 square root W/H, or -H/3 square root W may result in underadjustment for obesity.

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Most previous studies of hyperlipidemia in diabetics are based on patients in specialty clinics or reflect an era when diabetics consumed a high-fat, low-carbohydrate diet. In this paper, data from a defined adult population aged 20-79 years in an upper middle class community in Southern California, 1972-1974, were used to ascertain the relationship of hyperlipidemia to diabetes in a current community-based population. All (n = 358) diabetics as defined by history and/or fasting hyperglycemia (fasting plasma glucose, greater than or equal to 140 mg/dl) were compared with all (n = 4387) nondiabetics defined as euglycemic (fasting plasma glucose, less than 110 mg/dl) with no personal or family history of diabetes. In both men and women 50 years of age and older, the mean cholesterol level and the prevelance of categorical hypercholesterolemia were not significantly different in diabetics vs. nondiabetics, whereas the mean triglyceride level and the prevalence of categorical hypertriglyceridemia were significantly higher in diabetics vs. nondiabetics. Case-control comparisons of 356 diabetics matched for age and obesity with 356 nondiabetics confirmed the significantly higher triglyceride levels in diabetes. Conversely, hypertriglyceridemia was associated with diabetes in 29 per cent of nonobese men and 25 per cent of obese men, and in 10 per cent of non-obese women and 21 per cent of obese women. The biologic mechanism of hypertriglyceridemia in diabetics is discussed.

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Nutrient intake and alcohol consumption were studied in a 15% random sample of a predominantly white upper-middle class suburban community in Southern California. Based on 24-h dietary recall, 51% of the 691 men and women aged 30 to 90 yr in the study population had consumed an average of 30 g alcohol during the preceding 24 h. In general, alcohol-derived calories were added to the diet, and did not replace calories derived from other nutrients. Consequently, alcohol consumers had a significantly higher total caloric intake than did nondrinkers. Dietary differences were greatest in moderate drinkers, who tended to consume fewer nonalcohol-derived calories, and less of most specific nutrients. Although dietary differences in moderate drinkers were similar in men and women, statistically significant differences in women were limited to carbohydrate consumption. Moderate drinking men consumed significantly less protein, fat, carbohydrate, and cholesterol. These dietary differences suggest one mechanism whereby moderate alcohol consumption might reduce the risk of coronary heart disease. Although alcohol intake resulted in an increase in total calories consumed, alcohol drinkers were not more obese than nondrinkers. Since similar proportions of drinkers and nondrinkers exercised regularly, these data may suggest that alcohol calories are not fully utilized.

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The effect of response bias on odds ratio results was determined based on data from a population-based cardiovascular disease survey. The study subjects consisted of 5000 adult residents of a predominantly white, upper-middle class community. Information from 60% of the 1100 non-respondents was obtained by telephone. Consistent patterns of participation associated with risk factors and diseases under study were found. A simple error term was developed to convert the odds ratio for respondents to the odds ratio for the target population using individual cell response rates. This error term demonstrates that the response patterns found tended to minimize the error in odds ratio calculations for respondents. Only by obtaining relevant information on non-respondents can investigators accurately estimate response bias and its effects on the odds ratio.

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