Understanding the burden of health conditions in older adults in the U.S. is essential in addressing the healthcare demands of this patient population. This is of particular importance as the life expectancy in the U.S. continues to advance. In this retrospective cohort study, investigators analyzed data from 1998-2014 that was collected on 30,101 participants age 50 years or older diagnosed with at least one of 10 health conditions in order to examine the effect of these conditions on disability-adjusted life years (DALYs) within this population. The 10 conditions included in this study were cancer, chronic obstructive pulmonary disease (COPD), congestive heart failure, diabetes, back pain, hypertension, hip fracture, myocardial infarction (MI), rheumatism or arthritis, and stroke. Investigators found that the average age of death for those who died (n=10,504) was 79.6 + 10.5 years. DALY estimates for men ranged from 4092 for hip fractures, 28,707 for congestive heart failure, 36,688 for MI, 42,413 for COPD, 45,197 for stroke, 59,006 for diabetes, 68,237 for cancer, 86,392 for back pain, 144,991 for arthritis, and 178,055 for hypertension. DALY estimates for women ranged from 13,621 for hip fractures, 27,855 for MI, 33,874 for congestive heart failure, 47,802 for COPD, 48,587 for stroke, 58,101 for diabetes, 73,529 for cancer, 99,736 for back pain, 188,177 for arthritis, and 200,794 for hypertension. Combined, an estimated 693,778 DALYs could be attributed to the 10 heath conditions studied in men, while an estimated 792,076 DALYs were attributable in women. In terms of sex differences, only MI and diabetes were linked to DALYs that were higher in men than in women. The results from this study indicate that there is a huge loss of healthy life for older individuals related to the 10 health conditions studied. As such, improved interventions and treatments for these conditions are needed in older adults. This study was limited in that DALY calculations were driven by incidence and that DALY estimates did not explicitly measure quality of life.
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