Folate status and mood: is there a relationship?

Subjective well-being in older adults: folate and vitamin B12 independently predict positive affect

Vitamin B12, folate and homocysteine have long been implicated in mental illness, and growing evidence suggests that they may play a role in positive mental health. Elucidation of these relationships is confounded due to the dependence of homocysteine on available levels of vitamin B12 and folate. Cross-sectional and longitudinal relationships between vitamin B12, folate, homocysteine and subjective well-being were assessed in a sample of 391 older, community-living adults without clinically diagnosed depression. Levels of vitamin B12, but not folate, influenced homocysteine levels 18 months later. Vitamin B12, folate and their interaction significantly predicted levels of positive affect (PA) 18 months later, but had no impact on the levels of negative affect or life satisfaction. Cross-sectional relationships between homocysteine and PA were completely attenuated in the longitudinal analyses, suggesting that the cross-sectional relationship is driven by the dependence of homocysteine on vitamin B12 and folate. This is the first study to offer some evidence of a causal link between levels of folate and vitamin B12 on PA in a large, non-clinical population.

Reliability Generalization

The assessment of positive affect (PA) and negative affect (NA) by means of the Positive Affect and Negative Affect Schedule has received a remarkable popularity in the social sciences. Using a meta-analytic tool—namely, reliability generalization (RG)—population reliability scores of both scales have been investigated on the basis of a random effects model in 147 studies. Correcting for measurement errors, the results demonstrate moderate to high internal consistency coefficients and variations of the PA and NA reliability scores with regard to time frame instructions, language of items, and sample characteristics. The percentage of PA and NA true score variance differs in subpopulations up to 11%. RG analysis of test–retest coefficients illustrates state-like fluctuations and trait-like stability of both scales. Calculations of the fail-safe number point at the robustness of the results. Applications of RG coefficients compared to single-study coefficients highlight the relevance of population coefficients for research and assessment situations.