Associations between patterns of modifiable risk factors in mid-life to late life and longevity: 36 year prospective cohort study. Issue 1 (26th September 2022)

• Record Type: Journal Article
• Authors: Ding, Ming; Fitzmaurice, Garrett M; Arvizu, Mariel; Willett, Walter C; Manson, JoAnn E; Rexrode, Kathryn M; Hu, Frank B; Chavarro, Jorge E
• Is Part Of: BMJ medicine. Volume 1:Issue 1(2022)
• Publication Date: 2022-09-26
• Subjects: preventive medicine; Medicine -- Periodicals; 610
• DOI: 10.1136/bmjmed-2021-000098
• Languages: English
• ISSNs: 2754-0413

Abstract

Abstract : Objective: To examine the associations between patterns of mid-life to late life modifiable risk factors and longevity. Design: Prospective cohort study. Setting: Data collected from the Nurses' Health Study starting in 1984 and the Health Professionals Follow-up Study starting in 1986. Participants: 85 346 participants from the Nurses' Health Study and the Health Professionals Follow-up Study. Main outcome measures: Death from any cause by 31 October 2020 for the Nurses' Health Study and Health Professionals Follow-up Study. Risk factors investigated were body mass index, physical activity, alcohol intake, smoking status, and quality of diet. Trajectories of each risk factor and trajectories of changes in the risk factor were identified from baseline with smoothing mixture models, and the joint group memberships of participants was used to most efficiently capture patterns of the factor over time. For each risk factor, three trajectories (patterns with high, medium, and low values) and three trajectories of change in the risk factor (patterns with increase, no change, and decrease in the factor from baseline) were assumed, giving nine joint patterns: high-stable, high-increase, high-decrease, medium-stable, medium-increase, medium-decrease, low-stable, low-increase, and low-decrease. Associations between patterns of modifiable risk factors and longevity (age at death ≥85 years) and life expectancy were examined with logistic regression and accelerated failure time models, respectively. Results: The analysis included 85 346 participants, with 46 042 participants achieving longevity and 25 322 participants achieving healthy longevity (those who did not have a diagnosis of cardiovascular disease, type 2 diabetes, or cancer). Mean age at baseline was 56 years (standard deviation 5 years). Maximum longevity was achieved in participants with a low-stable pattern for body mass index (compared with a medium-stable pattern, odds ratio of longevity of 1.05, 95% confidence interval 1.00 to 1.10); those with a medium-increase pattern for physical activity (compared with a medium-stable pattern, odds ratio 1.08, 1.01 to 1.15); those with a medium-stable pattern for alcohol intake (high-increase v medium-stable pattern, odds ratio 0.83, 0.74 to 0.93); those who never smoked (low-stable v medium-stable pattern, odds ratio 3.09, 2.84 to 3.37); and those who with a high-increase pattern for quality of diet (compared with a medium-stable pattern, odds ratio 1.09, 1.01 to 1.18). The associations between each factor and life expectancy and healthy longevity (no diagnosis of cardiovascular disease, type 2 diabetes, or cancer) were similar to those for longevity. Conclusions: During mid-life and late life, maximum longevity was achieved in participants who maintained a normal body mass index, never smoked, ate a healthy diet, and had physical activity levels and alcohol consumption that met public health recommendations.