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Browsing by Subject "Social vulnerability"
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Item Association Between Social Vulnerability Index and Cardiovascular Disease: A Behavioral Risk Factor Surveillance System Study(American Heart Association, 2022) Jain, Vardhmaan; Al Rifai, Mahmoud; Khan, Safi U.; Kalra, Ankur; Rodriguez, Fatima; Samad, Zainab; Pokharel, Yashashwi; Misra, Arunima; Sperling, Laurence S.; Rana, Jamal S.; Ullah, Waqas; Medhekar, Ankit; Virani, Salim S.; Medicine, School of MedicineBackground: Social and environmental factors play an important role in the rising health care burden of cardiovascular disease. The Centers for Disease Control and Prevention developed the Social Vulnerability Index (SVI) from US census data as a tool for public health officials to identify communities in need of support in the setting of a hazardous event. SVI (ranging from a least vulnerable score of 0 to a most vulnerable score of 1) ranks communities on 15 social factors including unemployment, minoritized groups status, and disability, and groups them under 4 broad themes: socioeconomic status, housing and transportation, minoritized groups, and household composition. We sought to assess the association of SVI with self‐reported prevalent cardiovascular comorbidities and atherosclerotic cardiovascular disease (ASCVD). Methods and Results: We performed a retrospective cohort analysis of adults (≥18 years) in the Behavioral Risk Factor Surveillance System 2016 to 2019. Data regarding self‐reported prevalent cardiovascular comorbidities (including diabetes, hypertension, hyperlipidemia, smoking, substance use), and ASCVD was captured using participants' response to a structured telephonic interview. We divided states on the basis of the tertile of SVI (first—participant lives in the least vulnerable group of states, 0–0.32; to third—participant lives in the most vulnerable group of states, 0.54–1.0). Multivariable logistic regression models adjusting for age, race and ethnicity, sex, employment, income, health care coverage, and association with federal poverty line were constructed to assess the association of SVI with cardiovascular comorbidities. Our study sample consisted of 1 745 999 participants ≥18 years of age. States in the highest (third) tertile of social vulnerability had predominantly Black and Hispanic adults, lower levels of education, lower income, higher rates of unemployment, and higher rates of prevalent comorbidities including hypertension, diabetes, chronic kidney disease, hyperlipidemia, substance use, and ASCVD. In multivariable logistic regression models, individuals living in states in the third tertile of SVI had higher odds of having hypertension (odds ratio (OR), 1.14 [95% CI, 1.11–1.17]), diabetes (OR, 1.12 [95% CI, 1.09–1.15]), hyperlipidemia (OR, 1.09 [95% CI, 1.06–1.12]), chronic kidney disease (OR, 1.17 [95% CI, 1.12–1.23]), smoking (OR, 1.05 [95% CI, 1.03–1.07]), and ASCVD (OR, 1.15 [95% CI, 1.12–1.19]), compared with those living in the first tertile of SVI. Conclusions: SVI varies across the US states and is associated with prevalent cardiovascular comorbidities and ASCVD, independent of age, race and ethnicity, sex, employment, income, and health care coverage. SVI may be a useful assessment tool for health policy makers and health systems researchers examining multilevel influences on cardiovascular‐related health behaviors and identifying communities for targeted interventions pertaining to social determinants of health.Item Loneliness Interacts With Cognition in Relation to Healthcare and Financial Decision Making Among Community-Dwelling Older Adults(Oxford University Press, 2020-11-23) Stewart, Christopher C.; Yu, Lei; Glover, Crystal M.; Mottola, Gary; Bennett, David A.; Wilson, Robert S.; Boyle, Patricia A.; Neurology, School of MedicineBackground and objectives: Cognition is a known determinant of healthcare and financial decision making in old age. Social vulnerabilities also might play a role in such decisions; however, the evidence for this is less clear. Here, we examined the association of loneliness with decision making and tested the hypothesis that loneliness is associated with decision making via its interaction with global cognition. Research design and methods: Participants were 1,121 nondemented older adults from the Rush Memory and Aging Project. Healthcare and financial decision making was assessed via a performance-based measure; loneliness was assessed via the De Jong Gierveld Loneliness Scale; and cognition was assessed via a 19-test neuropsychological battery. Results: In a regression model adjusted for age, sex, and education, global cognition was associated with decision making (B = 2.43, SE = 0.14, p < .001) but loneliness was not (B = -0.04, SE = 0.11, p = .72). However, in a model including the interaction of loneliness with global cognition, the interaction was significant (B = 0.44, SE = 0.20, p = .03), such that the detrimental effect of loneliness on decision making was stronger when cognition was low. In secondary analyses examining the interaction of loneliness with 5 specific cognitive domains, the interaction between loneliness and working memory with decision making was significant (B = 0.35, SE = 0.15, p = .02). Discussion and implications: Our results suggest that loneliness compromises healthcare and financial decision making among older adults with lower global cognition and, more specifically, lower working memory.Item Worlds Further Apart: The Widening Gap in Life Expectancy among Communities of the Indianapolis Metropolitan Area(IU Richard M. Fairbanks School of Public Health; The Polis Center at IUPUI, 2021-08) Weathers, T; Kiehl, NT; Colbert, JT; Nowlin, M; Comer, KF; Staten, LKIndianapolis metro area residents are a diverse group of people. What we have in common is that many of our best and worst days have been lived within this larger community. We may recall warm summer hours in our favorite park, a day spent at “the track,” or taking the kids to the Children’s Museum. We may also remember days spent at the bedside of a sick family member in an area hospital or places of tragic loss. Year after year, we build our lives within the Indianapolis metro area. In this way, our lives are linked by a shared community. However, in the neighborhoods we each call home, our daily lives are often vastly different. For some, getting groceries means lugging plastic sacks onto the IndyGo bus after waiting on a patch of worn grass. For others, grocery shopping is a quick drive to one of three favorite options, and the farmer’s market is a weekend routine for fresh produce. Some kids go to school with laptops and fresh smelling pages of new textbooks, while others have worn books and no internet access. Playing outside with friends in one neighborhood builds fitness and friendships, while in another playing outside triggers an asthma attack because of all the car exhaust along the busy roadway. Place differences add up over the days of our lives to affect our health and length of life. The children of one neighborhood have the same biological capacity for a long and healthy life as do the children of any other neighborhood, but where they live and grow and learn often unfairly cuts short their opportunities and their life. In our updated analysis of 104 ZIP Codes in the metro area (2014-2018), we identified the northern suburb of Fishers as our longest living community and just 17 miles away, within the Indianapolis city limits, is the shortest living community within the metro area. Though only 17 miles of distance separate them, their life expectancy is worlds apart. As the White River winds its way through the metro area, flowing northeast to southwest, it connects us as a larger community across time and space. The history of central Indiana is rooted in access to this shared life-supporting resource, where tribes, then towns and cities grew along its banks. Following the winding path of the White River, we see a pattern in life expectancy that also plays out throughout the metro area (See Life Expectancy Mapped Along the White River, 2014-2018, on next page). Life expectancy is lowest in places within the urban core of Indianapolis and also on the outer periphery of the metro area (red), while highest life expectancy is found in the suburban transitions from the city (green). Similar to our earlier findings residents of the longest-living community are living years longer than the U.S. average with a life expectancy comparable to the top high-income countries of the world.1 Residents of the shortest living community are living only as long as U.S. residents lived on average more than six decades ago, and the gap has widened. There is no genetic reason for this inequity. These data compel us to put equity at the forefront in addressing the economic and social policies and structures driving this unfairness. Inequity, in life and health, “saps the strength of the whole society.”2