Multimodal associations of physical exercise, diet, body mass index, and sleep on white matter injury: The SOL‐INCA‐MRI study
Authors: Sapkota Shraddha , Maillard Pauline , Stickel Ariana M , Tarraf Wassim , Gonzalez Kevin A , Ivanovic Vladimir , Paredes Alejandra Morlett , Zeng Donglin , Cai Jianwen , Isasi Carmen R , Kaplan Robert C. , Lipton Richard B. , Daviglus Martha L , Testai Fernando Daniel , Lamar Melissa , Gallo Linda C , Talavera Gregory A , Gellman Marc D , Ramos Alberto R , González Hector M , Decarli Charles 
Published: December 2023

Background

Everyday modifiable lifestyle factors play a crucial role in the development and maintenance of successful cognitive and neurodegenerative trajectories in later life. Although research has focused on independent associations of physical exercise (PE), diet, body mass index (BMI), and sleep, how all four factors simultaneously work in a larger multimodal association has not been studied. We examine the synergistic associations of all four risk factors to predict two markers of future white matter injury (cerebral free water [FW] content, a sensitive and early biomarker of white matter injury and white matter hyperintensities [WMH]) in Hispanic/Latino‐population.

Method

We used cognitively normal older adults (n = 1386; mean age = 50.96(10.14) years; 66.2% female) with cross‐sectional data from the Study of Latinos‐Investigation of Neurocognitive Aging‐Magnetic Resonance Imaging (SOL‐INCA‐MRI). First, we applied path analyses to test independent associations of diet(Healthy‐Eating‐Index‐2010), PE(total activity), BMI, and sleep‐duration (measured 2008‐2015) on FW and WMH (measured 2018‐2022). Higher PE score represents lower exercise. Second, we tested mediations using significant independent predictors of FW and WMH. Third, we explored the best possible models that incorporated all six factors. We accounted for age, sex, and education in the final model.

Result

First, lower PE predicted greater WMH (β = 0.171,SE = 0.064,p = 0.008) and FW (β = 0.004,SE = 0.002, p = 0.013). Higher BMI (β = 0.018,SE = 0.007, p = 0.017), and higher FW (β = 22.230,SE = 0.939, p<0.001) was associated with greater WMH. Second, we did not find that any of the three modifiable factors mediated the relationship between PE and FW. However, the association between PE and WMH was mediated by BMI (indirect model[borderline]:β = 0.012,SE = 0.006, p = 0.050) and by FW (indirect model:β = 0.066,SE = 0.025, p = 0.007). Third, the addition of diet and sleep in this double mediation model strengthened both mediations (PE→BMI→WMH:β = 0.012,SE = 0.006, p = 0.039; PE→FW→WMH:β = 0.065,SE = 0.025, p = 0.008) resulting in an overall indirect model (PE→BMI→WMH+ PE→FW→WMH:β = 0.077,SE = 0.025,p = 0.002) (Figure 1). Better diet was associated with lower BMI (β = ‐0.026,SE = 0.012,p = 0.029) and lower PE with more sleep (β = 0.190,SE = 0.061,p = 0.002).

Conclusion

We observed that the association between PE and WMH is mediated by both BMI and FW, and the overall double mediation is clearer when diet and sleep are accounted for in the model. Our complex multimodal model provides a potential framework on how everyday modifiable risk factors synergistically predict WMH years later.