Age and Sex Disparities in Adherence to CPAP

Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.

The purpose of the present article is to provide a detailed description of the highly successful lifestyle intervention administered to 1,079 participants, which included 45% racial and ethnic minorities and resulted in a 58% reduction in the incidence rate of diabetes (2). The two major goals of the Diabetes Prevention Program (DPP) lifestyle intervention were a minimum of 7% weight loss/weight maintenance and a minimum of 150 min of physical activity similar in intensity to brisk walking. Both goals were hypothesized to be feasible, safe, and effective based on previous clinical trials in other countries (3-7). The methods used to achieve these lifestyle goals include the following key features: 1) individual case managers or "lifestyle coaches;" 2) frequent contact with participants; 3) a structured, state-of-the-art, 16-session core-curriculum that taught behavioral self-management strategies for weight loss and physical activity; 4) supervised physical activity sessions; 5) a more flexible maintenance intervention, combining group and individual approaches, motivational campaigns, and "restarts;" 6) individualization through a "toolbox" of adherence strategies; 7) tailoring of materials and strategies to address ethnic diversity; and finally 8) an extensive network of training, feedback, and clinical support.