Sesgos en neuroepidemiología: consecuencias y recomendaciones

Abstract

Neuroepidemiology is a scientific discipline focused on studying the distribution, frequency, risk factors, and determinants of neurological diseases in human populations. The primary aim of this publication is to emphasize the importance of preventing or minimizing common biases in neuroepidemiology and to propose strategies for enhancing the validity and reliability of studies.

The most prevalent biases include selection bias, which typically occurs in studies focused on restricted populations; information bias, arising from errors in the measurement and definition of variables; and confounding bias, caused by external variables that distort cause-effect relationships.

Other notable biases include nonresponse bias, which distorts results when certain groups do not respond to questionnaires or are unavailable; sampling errors, which affect population representativeness; and attrition bias in longitudinal studies, which affects findings by excluding participants with higher severity. In older populations, comorbidities, and cognitive decline complicate diagnoses, leading to biases related to concurrent illnesses and memory disorders.

Access to reliable data, such as death certificates, faces administrative and technical limitations, influencing the accuracy of mortality information. Conducting pilot studies, designing cultural and linguistically adapted questionnaires, including representative populations, and involving experts in biostatistics are key strategies for minimizing these biases.