Causal relationships among demographic variables, life-change events, psychosocial functioning, and diabetic disease control.

Abstract

The study investigates how positive, negative, and neutral events affect diabetes control and whether a weighted or unweighted scale provides a better prediction of diabetes control. This study used linear structural relations (LISREL) to explore causal models of demographic variables, different categories of life-change events, and psychosocial functioning in predicting body weight and blood glucose levels in 213 patients with Non-Insulin-Dependent Diabetes Mellitus (NIDDM). This study also extends previous debates on the dimensionality, desirability, and scaling of life change events by examining the influences of various dimensions of life-change events. Factor analysis was employed to identify four life-change event dimensions: personal and social activity change, work and financial change, family stability change, and family structure change. Life-change events were also categorized as positive, negative, and neutral depending on individual circumstances. Four causal models were analyzed: two using the weighted and unweighted four dimensions of life-change events and two using positive/negative/neutral life-change events. The causal relationships among demographic variables, life-change events, psychosocial functioning, and diabetic disease control were compared. Results of this study indicated that patients differences in sex, age, income, and marital status lead to different life-change events. Life-change events have multidimensional characteristics. Only personal and social activity changes and work and financial changes affect body weight and blood glucose levels. Positive and negative events have different influences on diabetes control. Psychosocial functioning only mediated the influence of life-change events on blood glucose levels. Higher body weight, however, led to a lower psychosocial functioning. The weighted and unweighted life-change events indicated differences only on how life-change events are categorized. The weighted and unweighted four dimensions of life-change events models are identical; however, when the life change events were categorized as positive, negative, and neutral, the weighted and unweighted models differ. In conclusion, different demographic variables lead to different life-change events. Work and financial changes and social activity changes have stronger effects on body weight control. Psychosocial functioning has the strongest effect on blood glucose control. Both body weight and psychosocial functioning are intervening variables in the process by which life-change events influence blood glucose levels.