Researchers simulated 20,000-person cohorts across 500 replications to quantify how preclinical dementia phases bias observational studies examining BMI's relationship with dementia risk. They found that when studies begin tracking participants at age 65, reverse causation creates 9% bias in effect estimates. This bias intensifies dramatically when studies start at age 80, reaching 32% distortion of true associations. The simulation methodology used reverse Mendelian randomization to calibrate realistic scenarios where BMI either has no causal effect or genuinely increases dementia risk. This work addresses a fundamental challenge in dementia research: the disease's long preclinical phase can make protective factors appear harmful in observational data. Years before clinical diagnosis, neurodegeneration may already be altering metabolism, appetite, and body weight, creating spurious associations that mislead both researchers and clinicians. The findings suggest that age-stratified analyses and genetic instruments may be essential for accurate risk factor identification in dementia research. However, as this remains a preprint awaiting peer review, these simulation-based estimates require validation through independent replication before informing clinical guidelines.