Prognostic factors in midlife for predicting subsequent frailty: a systematic literature review

This systematic review aimed to identify, describe, and critically appraise the evidence for prognostic factors and models in midlife (defined as a mean population age of 40-64 years) associated with frailty onset in later life.

Medline, Embase, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Latin American and Caribbean Health Science Information, and the Health Technology Assessment databases were searched for eligible studies involving midlife populations without frailty that assessed prognostic factors for incident frailty with ≥5 years of follow-up (up to January 2025). Studies reporting the development or validation of a prediction model to be used in midlife for predicting frailty were also included. Risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool and Prediction model Risk of Bias Assessment Tool. A qualitative synthesis of the evidence was conducted, using an adapted version of the grading of recommendations, assessment, development, and evaluation framework. Members from the public contributed to this review through a patient and public involvement (PPI) advisory group.

Thirty-five prognostic factor studies (including >2.3 million individuals) and one prediction model (n = 287) were included. Fifty-two prognostic factors were identified across six categories: demographic, lifestyle, general health, social networks or support, psychological, work-related, and environmental. Twenty-eight studies were rated at high risk of bias in at least one QUIPS domain. No prognostic factors for frailty onset with high-quality evidence were identified. Moderate-quality evidence was found for older age, being single, smoking, depression, perceived unmet health-care needs, area deprivation, lower occupational level, and lower wealth. The sole prediction model showed that musculoskeletal factors accounted for a significant proportion of the predicted risk of frailty, but it was rated at high risk of bias. Eighteen additional factors were suggested by PPI contributors for future investigation.

Robust studies are needed to improve our understanding of those at higher risk of developing frailty later in life to inform potential targets for preventive interventions. We identified eight prognostic factors with moderate-quality evidence. Smoking, depression, and unmet health-care needs are modifiable and should be considered as candidate predictors for inclusion in future prediction models. Members of the PPI advisory group emphasized the importance of investigating additional prognostic factors not captured in this review as priorities for future research.

As our population gets older, more people will become frail. People who are frail are at greater risk of adverse health events. Understanding what contributes to frailty can help identify people at higher risk early in life. We wanted to find out whether characteristics in midlife (defined as a mean population age of 40-64 years) could predict frailty later in life. We also looked for tools used in midlife to predict who might become frail. We searched for studies that examined factors linked to frailty and tools used to detect people at higher risk. We included studies that followed community-dwelling midlife populations for at least 5 years. We explored which characteristics predicted frailty and investigated how well prediction tools worked. We critically evaluated study quality, summarized the findings, and judged the strength of the evidence for each factor. We found 35 studies that looked at factors linked to frailty and one study that developed a prediction tool. Across these studies, 52 potential factors were identified. Most studies (80%) were rated as poor quality. We found moderate-quality evidence that older age, being divorced or widowed, smoking, depression, unmet health-care needs, living in more deprived neighborhoods, lower occupational level, and lower wealth were associated with developing frailty later in life. Members of the public contributed to this review and identified 18 additional factors, beyond this review. More high-quality research is needed to better understand who is most likely to develop frailty so people at high risk can be identified earlier and supported to help prevent frailty. Some of the strongest factors we identified, including smoking, depression, and unmet health-care needs, can potentially be changed or treated and may help identify people at higher risk of frailty. Public contributors also highlighted important factors not covered by the existing research that should be explored in future studies.