The major objectives of this revised continuation proposal are: 1) to extend follow-up and evaluation of the RENO Diet Heart Study for 5 additional years; and 2) to complete and extend testing of the primary hypotheses. The study is currently unfunded, but will be completed 9/30/91. To date, 303/508 subjects have been seen in their fifth year and a retention of over 90% is anticipated. Three major hypotheses are being pursued: 1) weight fluctuations affect cardiovascular disease (CVD) risk factors over and above weight change alone; 2) weight changes, fluctuations and patterns interact with nutritional, behavioral, psychological and medical factors, but these factors may also affect CVD risk independent of weight; and 3) retrospective, self-reported weights, fluctuations and patterns are predictive of prospective weights and weight fluctuations. Secondary aims of the study are to: 1) study weight maintenance and relapse behaviors (intentional and unintentional) in both normal weight and obese individuals in an effort to define and develop new weight control strategies; 2) continue to develop and refine needed methodologies in the assessment of important behaviors and lifestyle patterns (e.g. diet/eating, activity/exercise, energy balance); and 3) identify ancillary studies of importance that can be supported by our unique multidisciplinary design at minimal cost to our project (e.g. energy balance, obese elderly women, biochemical and biological markers).
Seven specific aims have been prioritized for the study: 1) define discrete and continuous measures of weight change, fluctuations and patterns; 2) determine the effect of short term weight change, fluctuation and pattern on selected CVD risk factors; 3) determine the relationships between long term weight change, fluctuations and patterns and the selected CVD risk factors; 4) compare short-term and longer term weight changes, fluctuations and patterns for their independent and cumulative effects; 5) determine associations of weight changes, fluctuations and patterns with selected variables of weight, diet/nutrition, activity, behaviors, psychological measures, medical status; 6) determine the interrelationships between and among the selected variables and evaluate their independent and combined effects; and 7) determine the predictability of self-reported and recalled weights with actual measurements. New statistical strategies have been developed to address the challenging question regarding how best to measure weight fluctuations. This proposal utilizes several approaches, including a generalized circadian model which simplifies into a regression model when a number of weights are available for analyses. Other traditional methods, including path analysis, will be utilized to address interrelationships of variables. A multi-site model with a statistical subcontractor and behavioral subcontractor is proposed. A multidisciplinary team of creative collaborators will utilize electronic communications with remote interactions off site in addition to on site visits.
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