Leading determinants for disease-free status in community-dwelling middle-aged men and women : A 9-year follow-up cohort study

Background: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status using machine learning methods.

Methods: We included 52,036 participants aged 45–64 years from the 45 and Up Study who were free of 13 predefined chronic conditions at baseline (2006–2009). Disease-free status was defined as participants aging from 45–64 years at baseline to 55–75 years at the end of the follow-up (December 31, 2016) without developing any of the 13 chronic conditions. We used machine learning methods to evaluate the importance of 40 potential predictors and analyzed the association between the number of leading modifiable healthy factors and disease-free status.

Results: Disease-free status was found in about half of both men and women during a mean 9-year follow-up. The five most common leading predictors were body mass index (6.4–9.5% of total variance), self-rated health (5.2–8.2%), self-rated quality of life (4.1–6.8%), red meat intake (4.5–6.5%), and chicken intake (4.5–5.9%) in both genders. Modifiable behavioral factors including body mass index, diets, smoking, alcohol consumption, and physical activity, contributed to 37.2–40.3% of total variance. Participants having six or more modifiable health factors were 1.63–8.76 times more likely to remain disease-free status and had 0.60–2.49 more disease-free years (out of 9-year follow-up) than those having two or fewer. Non-behavioral factors including low levels of education and income and high relative socioeconomic disadvantage, were leading risk factors for disease-free status.

Conclusions: Body mass index, diets, smoking, alcohol consumption, and physical activity are key factors for disease-free status promotion. Individuals with low socioeconomic status are more in need of care.