Deaths Involving High Levels of Medical, Elder Care Use Found to be More Common as Older Adults Age

Article

This research was conducted to examine the end-of-life trajectories of older adults and investigate distribution over gender, age, and causes of mortality.

Marcus Ebeling, PhD, 

Credit: Twitter.com

Marcus Ebeling, PhD,

Credit: Twitter.com

Deaths which are characterized by high levels of elder care and medical care utilization become more common with age, according to recent findings, demonstrating that longer lifespans are partly the result of a prolonged dying process.1

The findings were the result of a study in Sweden which examined end-of-life trajectories for older adults with regard to both elder and medical care care and how they are linked to gender, age, and mortality causes.

The research was authored by Marcus Ebeling, PhD, from the Institute of Environmental Medicine’s Unit of Epidemiology at the Karolinska Institute in Stockholm.

“The aim of this study was to derive a classification of end-of-life trajectories and to investigate how they are distributed over age, gender, and causes of death,” Ebeling and colleagues wrote. “This will allow us to link the end of life to population mortality and shed more light on the overarching question: how do we die?”

Background and Findings

The investigators utilized data from the Cause of Death Register to gather data on date and causes of death.2 The National Patient Register was used to extract information on inpatient and outpatient care utilization in the last 12 months of life, measured by the total number of hospital days and visits.

The research team assed the type of medical care received through the field of medical activity code, which indicated whether individuals received acute care or specialized clinical care. Elder care status was measured by the team through the Social Service Register, with the investigators differentiating between home care, no care, and living in a care home.

Latent class analysis was also employed by the investigators to identify patterns of end-of-life trajectories based on indicators including:

  • Elder care status
  • Acute care
  • Inpatient and outpatient care utilization
  • Specialized clinical care

The investigators examined the number of deaths in Sweden among individuals aged 70 and older over a 3-year time frame, which accounted for around 80% of the total annual deaths in the country. The increase in deaths in 2020 was attributed to the COVID-19 pandemic.

The research team found 6 unique types of end-of-life trajectories, with the "terminally ill" type being the most common and the "sudden death" and "impaired" types being the least common among those they identified. The types were noted as being characterized by variations in elder care and medical care use.

The team’s inclusion of medical care as an indicator divided the overall types into more specific trajectories for their research. They also assessed gender and age differences, noting that trajectory types with high elder care needs became more prevalent with increasing age, particularly for women.

The causes of death varied across the trajectory types, with cancer being prominent among the "terminally ill" type and cardiovascular diseases among the "sudden death" type. The trajectory types with high medical care utilization had a lower proportion of deaths from cardiovascular diseases.

“Our analysis has shown that most individuals experience a last year of life with high elder care needs and medical care utilization; a pattern that becomes even more pronounced with increasing age at death,” they wrote. “Most end-of-life trajectories that we identified may only partially align with the principles of a good death.”

References

  1. Marcus Ebeling, Anna C. Meyer, and Karin Modig, 2023: Variation in End-of-Life Trajectories in Persons Aged 70 Years and Older, Sweden, 2018‒2020 American Journal of Public Health 113, 786_794, https://doi.org/10.2105/AJPH.2023.307281.
  2. Brooke HL, Talbäck M , Hörnblad J, et al. The Swedish cause of death register. Eur J Epidemiol. 2017;32(9):765–773. https://doi.org/10.1007/s10654-017-0316-1.
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