Preventive medicine
-
Preventive medicine · Jul 2020
Identifying patterns and predictors of lifestyle modification in electronic health record documentation using statistical and machine learning methods.
Just under half of the 85.7 million US adults with hypertension have uncontrolled blood pressure using a hypertension threshold of systolic pressure ≥ 140 or diastolic pressure ≥ 90. Uncontrolled hypertension increases risks of death, stroke, heart failure, and myocardial infarction. Guidelines on hypertension management include lifestyle modification such as diet and exercise. ⋯ Logistic regression was the best machine learning method for classifying lifestyle modification documentation at ≤3 months with an AUROC of 0.685. Analyzing narrative and coded data from electronic health records can improve understanding of timing of lifestyle modification and patient, clinic and provider characteristics that are correlated with or predictive of documentation of lifestyle modification for hypertension. This information can inform improvement efforts in hypertension care processes, treatment implementation, and ultimately hypertension control.
-
Preventive medicine · Jul 2020
Chronic condition patterns in the US population and their association with health related quality of life.
This study aims to identify chronic disease patterns and their relationship to health-related quality of life (HRQL) in the US population. This cross-sectional study used data from 86,745 participants aged 18 years and older of the Medical Expenditure Panel Survey (MEPS) 2010-2015, we employed latent class analysis (LCA) to identify subgroups of participants with different combinations of 23 chronic conditions which had medical utilization during the past 12 months. Derived chronic condition latent classes were used to predict the 12-Item Short Form Survey physical component score (PCS), mental component score (MCS) in addition to overall HRQL (SF-6D) while controlling for covariates. ⋯ The relationship between physical and mental health functioning varied across different multi-morbidity groups, and the discordance was more pronounced in younger ages and females. Our research also identified an older age group that was mentally robust and maintained a strong HRQL. Findings can inform the development of targeted interventions to improve physical and mental health functioning in vulnerable populations.
-
Preventive medicine · Jul 2020
Do youth who vape exhibit risky health lifestyles? Monitoring the future, 2017.
Previous research links cigarette smoking with an array of unhealthy behaviors including poor diet, poor sleep quality, and reduced levels of physical exercise. To date, however, limited research has explored whether vaping nicotine (or marijuana) is associated with these same health risk behaviors. ⋯ The results suggest that youths who vaped nicotine (or marijuana) did not exhibit significant elevations in risky health behavior outcomes relative to abstaining youths. Even so, cigarette smoking and recent use of marijuana through traditional means are significantly associated with risky health outcomes.
-
Preventive medicine · Jul 2020
Positive emotions and favorable cardiovascular health: A 20-year longitudinal study.
No studies have examined whether positive emotions lead to favorable cardiovascular health (CVH) early in the lifespan, before cardiovascular disease is diagnosed. Moreover, the direction of the association has not been thoroughly investigated. Among younger adults, we investigated whether baseline positive emotions were associated with better CVH over 20 years. ⋯ Positive emotions in early to middle adulthood were associated with better CVH across several decades. Baseline CVH was also associated with greater positive emotions during follow-up. Future research may be able to disentangle these relationships by assessing positive emotions and CVH earlier in life.
-
Preventive medicine · Jul 2020
Opioid prescriptions in emergency departments: Findings from the 2016 National Hospital Ambulatory Medical Care Survey.
In the past decade, there has been a rising trend in the emergency department (ED) visits in the US and these visits carry a significant burden of prescription opioids. This study utilized the latest available data from the 2016 National Hospital Ambulatory Medical Care Survey (NHAMCS) and examined the factors associated with opioid prescriptions in the ED. The outcome variable was receipt of opioid prescription, and the primary variable of interest was the type of visit (dental/non-dental). ⋯ Opioid prescriptions among 45-64 years old were 7.1 times (95% CI = 5.5-9.1] more likely compared to those among under 18 age-group. Opioid prescriptions in ED differed significantly by the type of visit and pain level. Given the higher likelihood of opioid prescriptions among dental visits, it is imperative to develop better prescription guidelines for dental visits in ED.