8 research outputs found

    The Healthy Aging Index analyzed over 15 years in the general population

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    The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled ‘gradual’ aging and ‘early’ aging. Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to ‘gradual’ aging of 1.46, 1.93, 1.26 and 1.76, respectively. Between 30 and 70 years of age, men in the ‘early’ aging trajectory had the least healthy years, followed by women, and ‘gradual’ aging men. This study emphasizes that ‘physiological aging’ is not only an issue of older ages. Between 30 and 70 years of age, ‘early’ aging men and women had approximately five healthy years less compared to ‘gradual’ aging men. Lifestyle factors seem to play an important role in optimal aging

    How should ICU beds be allocated during a crisis? Evidence from the COVID-19 pandemic

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    Background The first wave of the COVID-19 pandemic overwhelmed healthcare systems in many countries, and the rapid spread of the virus and the acute course of the disease resulted in a shortage of intensive care unit (ICU) beds. We studied preferences of the public in the Netherlands regarding the allocation of ICU beds during a health crisis. Methods We distributed a cross-sectional online survey at the end of March 2020 to a representative sample of the adult population in the Netherlands. We collected preferences regarding the allocation of ICU beds, both in terms of who should be involved in the decision-making and which rationing criteria should be considered. We conducted Probit regression analyses to investigate associations between these preferences and several characteristics and opinions of the respondents. Results A total of 1,019 respondents returned a completed survey. The majority favored having physicians (55%) and/or expert committees (51%) play a role in the allocation of ICU beds and approximately one-fifth did not favor any of the proposed decision-makers. Respondents preferred to assign higher priority to vulnerable patients and patients who have the best prospect of full recovery. They also preferred that personal characteristics, including age, play no role. Conclusion "Our findings show that current guidelines for allocating ICU beds that include age as an independent criterion may not be consistent with societal preferences. Age may only play a role indirectly, in relation to the vulnerability of patients and their prospect of full recovery. Allocation of ICU beds during a health crisis requires a multivalue ethical framework.

    Viewpoints among experts and the public in the Netherlands on including a lifestyle criterion in the healthcare priority setting

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    Context: It remains unclear whether there would be societal support for a lifestyle criterion for the healthcare priority setting. This study examines the viewpoints of experts in healthcare and the public regarding support for a lifestyle-related decision criterion, relative to support for the currently applied criteria, in the healthcare priority setting in the Netherlands. Methods: We conducted a Q methodology study in samples of experts in healthcare (n = 37) and the public (n = 44). Participants (total sample N = 81) ranked 34 statements that reflected currently applied decision criteria as well as a lifestyle criterion for setting priorities in healthcare. The ranking data were subjected to principal component analysis, followed by oblimin rotation, to identify clusters of participants with similar viewpoints. Findings: We identified four viewpoints. Participants with Viewpoint 1 believe that treatments that have been proven to be effective should be reimbursed. Those with Viewpoint 2 believe that life is precious and every effort should be made to save a life, even when treatment still results in a very poor state of health. Those with Viewpoint 3 accept government intervention in unhealthy lifestyles and believe that individual responsibility should be taken into account in reimbursement decisions. Participants with Viewpoint 4 attribute importance to the cost-effectiveness of treatments; however, when priorities have to be set, treatment effects are considered most important. All viewpoints were supported by a mix of public and experts, but Viewpoint 1 was mostly supported by experts and the other viewpoints were mostly supported by members of the public. Conclusions: This study identified four distinct viewpoints on the healthcare priority setting in the Netherlands, each supported by a mix of experts and members of the public. There seems to be some, but limited, support for a lifestyle criterion—in particular, among members of the public. Experts seem to favour the decision criteria that are currently applied. The diversity in views deserves attention when policymakers want to adhere to societal preferences and increase policy acceptance

    The Healthy Aging Index analyzed over 15 years in the general population: The Doetinchem Cohort Study.

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    The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled 'gradual' aging (76%) and 'early' aging (24%). Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to 'gradual' aging of 1.46 (CI: 1.18-1.81), 1.93 (CI: 1.42-2.62), 1.26 (1.02-1.57) and 1.76 (1.32-2.35), respectively. Between 30 and 70 years of age, men in the 'early' aging trajectory had the least healthy years (29.6 years), followed by women (30.1 years), and 'gradual' aging men (34.7 years). This study emphasizes that 'physiological aging' is not only an issue of older ages. Between 30 and 70 years of age, 'early' aging men and women had approximately five healthy years less compared to 'gradual' aging men. Lifestyle factors (e.g. nutrition and physical activity) seem to play an important role in optimal aging
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