RESUMO
OBJECTIVE: Fall-related deaths have been on the rise nationwide. Our objective was to characterise the trend in unintentional fall-related adult deaths in Utah and evaluate the underlying and contributing causes associated with these deaths. METHODS: We used 2010-2020 Utah death certificate data and included all Utah deaths aged 18 and older with a fall listed on their death records as the underlying or contributing cause of death in the analysis. RESULTS: From 2010 to 2020, the overall age-adjusted unintentional fall death rate increased 70% from 15.7 to 26.8 per 100 000 person-years, while the overall age-adjusted death rate increase was 12% at the time. On average, the group with falls as one of the contributing causes had 4.9 other contributing causes, while the group with falls as an underlying cause had 3.3; the two averages were statistically different. Incidence of death increased 60% (12.1-19.4 per 100 000) for falls classified as the underlying cause of death and 103% (3.6-7.3 per 100 000) for those with fall as a contributing cause. Coding for the type of fall became more specific with a 30% decrease in unspecified fall (International Classification of Diseases, 10th revision code W19) (5.9-4.1 per 100 000). CONCLUSION: There was an increasing trend of unintentional fall-related adult deaths in Utah from 2010 to 2020. This increase is consistent with national trends. Our data supports there is more specific reporting of fall deaths, but better reporting alone cannot explain the uptrend. Furthermore, the deaths with falls as contributing causes increased the most, and these individuals have more comorbidities.
RESUMO
Allergic rhino-conjunctivitis (AR) is a globally relevant health disorder characterized by sneezing, rhinorrhea and sleep disturbance. Ragweed (Ambrosia artemisiifolia) is a plant common to North America and an important allergen. Coarse methods of measuring airborne pollen counts are used to predict seasonal allergy symptoms. This research used a longitudinal study design with a novel, model-based raster of predicted pollen counts to test associations with self-reported symptoms of AR collected from patients receiving immunotherapy for pollen allergies at an allergy clinic. Researchers visited a clinic six times over three weeks. Immunotherapy patients were asked to fill out a brief intake survey on allergic and symptomatic profiles, daytime sleepiness, housing quality, and demographics. Participants responded to a daily, emailed survey on sleepiness and asthma symptoms for 21 days. Using the date and location of responses, ragweed pollen counts were extracted from a prognostic, model based raster (25km pixels). Lag associations of pollen counts with sleepiness were tested using a logistic regression model , adjusted for housing and demographic characteristics, in a distributed lag non-linear model (DLNM) framework. 49 people participated in the study. 26 (52%) were female. The mean age was 37.9 years. Asthma/allergy symptoms were not associated with ragweed pollen but sleepiness was highest two days after exposure (Estimate: 0.33 [0.04,0.62]). Subjects traveled widely during the study period. Intense exposures to ragweed pollen may be associated with daytime sleepiness within small exposure windows. Model-based predicted pollen counts could be used to study health impacts of pollen in people with disease severe enough to receive immunotherapy. Daytime sleepiness can affect productivity and injury risk, and pollen season length and allergenicity may be increasing with climate change. Thus our results may have important implications for population health.