Analysis the Effect of Missing Data in UK Biobank¶
Overview¶
The traditional view of missing data in epidemiological studies has been as a limitation to be addressed through statistical methods like exclusion or imputation. However, emerging evidence suggests that missing response patterns themselves—specifically "don't know/can't remember" (DK)—may hold valuable clinical information. This study leverages data from 500,000 UK Biobank participants to explore how these patterns relate to disease risk and health outcomes.
We found that DK responses, often linked to memory and cognitive function, are strongly associated with an increased risk of neurodegenerative diseases such as dementia and Alzheimer’s disease, with a clear dose-response relationship. The associations were particularly pronounced among older participants, highlighting the potential of DK patterns as early markers of cognitive decline. Behavioral factors, such as smoking, amplified the associations, suggesting that external exposures may influence these patterns. These findings emphasize the significance of behavioral modifiers in understanding the relationship between DK responses and neurodegenerative risks.
This work reframes missing questionnaire data from a nuisance to an asset, demonstrating that DK response patterns can provide critical insights into participants' cognitive health and disease risks. By systematically analyzing these patterns, we can identify early indicators of disease, enabling more precise risk stratification and targeted interventions. These findings pave the way for novel applications of response pattern analysis in population health, transforming data limitations into opportunities for actionable clinical insights.
We found that DK responses, often linked to memory and cognitive function, are strongly associated with an increased risk of neurodegenerative diseases such as dementia and Alzheimer’s disease, with a clear dose-response relationship. The associations were particularly pronounced among older participants, highlighting the potential of DK patterns as early markers of cognitive decline. Behavioral factors, such as smoking, amplified the associations, suggesting that external exposures may influence these patterns. These findings emphasize the significance of behavioral modifiers in understanding the relationship between DK responses and neurodegenerative risks.
This work reframes missing questionnaire data from a nuisance to an asset, demonstrating that DK response patterns can provide critical insights into participants' cognitive health and disease risks. By systematically analyzing these patterns, we can identify early indicators of disease, enabling more precise risk stratification and targeted interventions. These findings pave the way for novel applications of response pattern analysis in population health, transforming data limitations into opportunities for actionable clinical insights.