Lifestyle Modification for Metabolic Syndrome: A Systematic Review

Abstract Background All 5 components of metabolic syndrome have been shown to improve with lifestyle and diet modification. New strategies for achieving adherence to meaningful lifestyle change are needed to optimize atherosclerotic cardiovascular risk reduction. We performed a systematic literature review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework (PRISMA), investigating optimal methods for achieving lifestyle change in metabolic syndrome. Methods We submitted standardized search terms to the PubMed Central, CINAHL, Web of Science, and Ovid databases. Within those results, we selected randomized controlled trials (RCTs) presenting unique methods of achieving lifestyle change in patients with one or more components of the metabolic syndrome. Data extraction using the population, intervention, comparator, outcome, and risk of bias framework (PICO) was used to compare the following endpoints: prevalence of metabolic syndrome, prevalence of individual metabolic syndrome components, mean number of metabolic syndrome components, and amount of weight loss achieved. Results Twenty-eight RCTs (6372 patients) were included. Eight RCTs demonstrated improvement in metabolic syndrome risk factors after 1 year. Team-based, interactive approaches with high-frequency contact with patients who are motivated made the largest and most lasting impact. Technology was found to be a useful tool in achieving lifestyle change, but ineffective when compared with personal contact. Conclusion Patient motivation leading to improved lifestyle adherence is a key factor in achieving reduction in metabolic syndrome components. These elements can be enhanced via frequent encounters with the health care system. Use of technologies such as mobile and Internet-based communication can increase the effectiveness of lifestyle change in metabolic syndrome, but should not replace personal contact as the cornerstone of therapy. Our ability to derive quantitative conclusions is limited by inconsistent outcome measures across studies, low power and homogeneity of individual studies, largely motivated study populations, short follow-up periods, loss to follow-up, and lack of or incomplete blinding.