Almost two decades ago, Drs. Meyer Friedman and Ray Rosenman de veloped the concept of the Type A coronary-prone behavior pattern and pioneered research in the area. Since then, much effort has been devoted to investigating both medical and psychosocial implications of this phenomenon by an impressive array of biomedical and behavioral scientists. On the basis of the National Heart, Lung, and Blood Institute's (NHLBI) recent Congressional mandate concerning disease prevention and control, the Division of Heart and Vascular Diseases undertook an intensive review of the existing literature in this area. The review underscored that the very nature of the concept of coronary-prone behavior requires examination by researchers from a variety of disciplines. Publication of findings in both the medical and behavioral literature, however, has created difficulties in gaining a truly com prehensive understanding of the total effort in this area. It became obvious that there was no coherent integration of information regarding the strength of the association between behaviors and disease processes (or outcomes), how be havioral factors associated with coronary heart disease were measured, the possible physiological mechanisms mediating the relationship between be havior and disease, whether intervention could be effective, and what forms of intervention appeared most promising. In short, a clear need existed to or ganize this information in a more coherent fashion so that it could be subjected to critical review by members of both the medical and behavioral scientific communities.

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Provides a comprehensive assessment of the scientific evidence on prevalence and the resulting health effects of a range of exposures that are know to be hazardous to human health, including childhood and maternal undernutrition, nutritional and physiological risk factors for adult health, addictive substances, sexual and reproductive health risks, and risks in the physical environments of households and communities, as well as among workers. This book is the culmination of over four years of scientific equiry and data collection, know as the comparative risk assessment (CRA) project.