Using zero-inflated models to explain chronic illness, pain, and complementary and alternative medicine use

Area of Science:

• Integrative Medicine
• Health Services Research
• Biostatistics

Background:

• Complementary and alternative medicine (CAM) use is prevalent, yet understanding the drivers of its adoption and intensity remains incomplete.
• Previous research has explored various factors influencing CAM use, but a consistent predictor across different domains has been elusive.

Purpose of the Study:

• To investigate the relationship between poor health indicators and the initiation and diversity of complementary and alternative medicine (CAM) usage.
• To identify specific health factors that consistently predict both the likelihood of trying CAM and the number of CAM modalities utilized.

Main Methods:

• Analysis of the 2002 National Health Interview Survey's Supplemental Section data.
• Application of zero-inflated statistical models to assess CAM utilization across five distinct domains.
• Examination of pain levels, general health status, and chronic conditions as predictors of CAM use.

Main Results:

• Pain emerged as the sole consistent predictor, significantly increasing both the odds of trying CAM and the number of CAM types used across all domains.
• Health status and chronic conditions showed mixed associations with CAM use.
• Prayer was the only modality significantly associated with higher odds and number of types used for chronic illnesses (OR=1.705 for odds, OR=1.024 for number).

Conclusions:

• Zero-inflated models reveal significant variability in complementary and alternative medicine (CAM) use behaviors.
• Pain is the most robust predictor influencing both the decision to try CAM and the breadth of CAM modalities employed.
• The impact of chronic illness on CAM use appears specific, primarily influencing the use of prayer.