Date of Award:

5-1992

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Nutrition, Dietetics, and Food Sciences

Department name when degree awarded

Nutrition and Food Science

Committee Chair(s)

Georgia C. Lauritzen

Committee

Georgia C. Lauritzen

Committee

Deloy Hendricks

Committee

Brian Pitcher

Abstract

Osteoporosis is responsible for approximately 1.3 to 1.5 million fractures per year in the United States. The risk of osteoporosis increases with age, especially among postmenopausal women, and with lifestyle factors such as the use of certain drugs, heavy alcohol consumption, cigarette smoking, high caffeine intake, and sedentary living. Genetic factors that may influence susceptibility to osteoporosis include a positive family history of the disease, or a low weight - for-height ratio. In some cases, race and geographic location may increase or decrease the risk of osteoporosis. Known protective factors include obesity, estrogen replacement therapy, weight bearing exercise, and possibly calcium, fluoride, and Vitamin D. Although several studies have examined multiple factors in single populations, few comparisons have been made between populations within the same country.

Recent epidemiological studies have shown that the Utah population has lower rates of some chronic diseases than the national average. In this study, we used a questionnaire approach to relate the incidence of osteoporotic fracture to 28 lifestyle, dietary, physical, and geographic factors in postmenopausal women between a Utah population and a combined population from North Dakota, South Dakota, and Colorado.

Logistic regressions were used to determine the probability of osteoporosis for these two populations and to determine which factors significantly (P ≤ 0.05) increased or decreased the incidence of osteoporosis. The following factors were significantly related to the occurrence of osteoporosis: age, race, arthritis, cortisone, and fluoridated water. Dietary factors, including calcium, were not significantly related to osteoporosis in this study. The model successfully predicted the occurrence of an osteoporotic event in 72% of the cases.

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