As seen in F1, the lifetime prevalence rate for bipolar spectrum disorder varied across 12 countries from 0.2 in Iceland to 6.5 in Germany. Rates for the intermediate countries, in order of increasing prevalence, were as follows: Taiwan=0.4, Korea=0.5, Puerto Rico=0.9, Canada=1.1, New Zealand=2.4, Israel=2.6, the United States=3.0, Italy=3.4, Switzerland=5.1, and Hungary=5.5. The lifetime prevalence rate for bipolar I disorder varied across 11 countries from 0.3 in Taiwan to 2.6 in Israel. Rates for the intermediate countries, in order of increasing prevalence, were as follows: Iceland=0.4, Korea=0.4, Canada=0.6, Puerto Rico=0.6, United States=0.9, Switzerland=1.3, Germany=1.4, New Zealand=1.5, and Italy=1.7. The lifetime prevalence rate for bipolar II disorder varied across eight countries from 0.1 in Taiwan to 2.0 in Hungary. Rates for the intermediate countries, in order of increasing prevalence, were as follows: Puerto Rico=0.2, Korea=0.2, Germany=0.4, United States=0.5, Canada=0.5, and New Zealand=1.0. For schizophrenia, the lifetime prevalence rate varied across 14 countries as follows: Hong Kong=0.1, Greece=0.2, Korea=0.3, Taiwan=0.3, Iceland=0.3, New Zealand=0.3, United Kingdom=0.4, Australia=0.5, Germany=0.6, Canada=0.6, Israel=0.7, United States=1.3, Puerto Rico=1.6, and Spain=1.7.
In simple linear regression models, higher national seafood consumption predicted lower prevalence rates of bipolar spectrum disorder (r=–0.67, df=10, p=0.02), bipolar I disorder (r=–0.52, df=9, p=0.09), and bipolar II disorder (r=–0.70, df=6, p=0.04). An examination of the residual plots of these findings suggested that nonlinear regressions would better describe the relationship between seafood consumption and rates of bipolar disorders. According to logarithmic regression models, greater seafood consumption predicted lower prevalence rates of bipolar I disorder (r=–0.60; r2=0.36, p<0.02), bipolar II disorder (r=–0.87; r2=0.76, p<0.0009), and bipolar spectrum disorder (r=–0.80; r2=0.64, p<0.0003). The best curve fitting came from a simple exponential decay regression (y=a × exp–bx); greater seafood consumption predicted lower rates of bipolar I disorder (r=–0.63; r2=0.40, p<0.04), bipolar II disorder (r=–0.89; r2=0.78, p<0.004), and bipolar spectrum disorder (r=–0.85; r2=0.72, p<0.0004). When defined as all bipolar disorders (i.e., all diagnostic subcategories summed), linear regression results (r=–0.74; r2=–0.54, p<0.0001) and exponential decay regression results (r=–0.85; r2=0.72, p<0.0001) remained significant. Exclusion of Iceland improved the strength of the relationship, per exponential decay regression, between seafood consumption and lifetime prevalence rate of bipolar II disorder (r=–0.91; r2=0.82, p<0.002) and did not significantly alter the results for bipolar I disorder (r=–0.59; r2=0.36, p<0.07) and bipolar spectrum disorder (r=–0.83; r2=0.68, p<0.002). There were no correlational relationships between lifetime prevalence rates of schizophrenia compared with any of the bipolar disorders across countries. Seafood consumption did not predict prevalence rates of schizophrenia in either linear or nonlinear models.