A Prospective Longitudinal Study of Seasonality in African Students Living in the Greater Washington, D.C. Metropolitan Area

• Main Authors: Alvaro Guzman, Ryszard Zebrak, Kelly J. Rohan, Irshad A. Sumar, Svetlana Savchenko, John W. Stiller, Adela Valadez-Meltzer, Cara Olsen, Manana Lapidus, Joseph J. Soriano, Teodor T. Postolache
• Format: Article
• Language: English
• Published: Hindawi Limited 2007-01-01
• Series: The Scientific World Journal
• Online Access: http://dx.doi.org/10.1100/tsw.2007.110

We conducted a prospective, longitudinal study of seasonality in a vulnerable population, i.e., African students who migrated to a temperate climate. Consistent with previous cross-sectional studies, we hypothesized lower mood and energy, and higher appetite and weight, in fall/winter than in spring/summer. Four cohorts of African students attending a year-long nursing school program without vacation in Washington, D.C., were assessed monthly for 1 year. Forty-three subjects (mean age = 33.46 ± 6.25), consisting of predominantly females (76.7%), completed the study. The cohorts began their academic program in different seasons (one each in winter, spring, summer, and fall), inherently minimizing confounding influences on seasonality, such as academic and immigration stress, as well as allowing adjustment for an order effect. At each assessment, students completed three 100-mm visual analog scales for mood, energy, and appetite, and were weighed on a digital scale. For each standardized dependent variable, a repeated measure ANOVA was used and, if a significant effect of month was identified, averages for spring/summer and fall/winter were compared using paired ttests. In addition, a mixed model for repeated measures was applied to raw (nonstandardized) data. Body weight was significantly higher in fall/winter than in spring/summer (p < 0.01). No seasonal differences in mood, energy, or appetite were found. Benefiting from certain unique features of our cohorts allowing adjustment for order effects, this is the first study to identify a seasonal variation in body weight with a peak in winter using longitudinal monthly measurements.