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INNOVATIVE METHODOLOGY

New approach to the statistical analysis of cardiovascular data

¹Department of Biostatistics, Mailman School of Public Health, ²Department of Psychiatry, Columbia University, New York, ³Behavioral Medicine Program, Columbia-University Medical Center, New York, and ⁴New York State Psychiatric Institute, New York, New York

Submitted 22 July 2004 ; accepted in final form 15 February 2005

Fourier-based approaches to analysis of variability of R-R intervals or blood pressure typically compute power in a given frequency band (e.g., 0.01–0.07 Hz) by aggregating the power at each constituent frequency within that band. This paper describes a new approach to the analysis of these data. We propose to partition the blood pressure variability spectrum into more narrow components by computing power in 0.01-Hz-wide bands. Therefore, instead of a single measure of variability in a specific frequency interval, we obtain several measurements. The approach generates a more complex data structure that requires a careful account of the nested repeated measures. We briefly describe a statistical methodology based on generalized estimating equations that suitably handles this more complex data structure. To illustrate the methods, we consider systolic blood pressure data collected during psychological and orthostatic challenge. We compare the results with those obtained using the conventional methods to compute blood pressure variability, and we show that our approach yields more efficient results and more powerful statistical tests. We conclude that this approach may allow a more thorough analysis of cardiovascular parameters that are measured under different experimental conditions, such as blood pressure or heart rate variability.

blood pressure variability; generalized estimating equations; repeated measures