scholarly journals Decoding State Vaccination Rates Using educational aptitude, Income, and Political Affiliation

2021 ◽  
Author(s):  
Azad Kabir ◽  
Raeed Kabir ◽  
Jebun Nahar ◽  
Ritesh Sengar
Keyword(s):  
United States ◽  
Risk Factors ◽  
Low Income ◽  
The United States ◽  
Political Affiliation ◽  
Lower Income ◽  
Vaccination Rates ◽  
Factors Associated ◽  
The Us ◽  
Per Capita

The objective of the study was to evaluate the risk factors associated with lower COVID-19 vaccination rates in the United States. The study evaluated the effect of red-blue political affiliation and the effect of the US state's average educational aptitude score and per capita income on states' vaccination rates. The study found that states with concomitantly lower income along with lower educational aptitude scores are less vaccinated while the states with higher income have higher vaccination rates even among those with lower educational aptitude scores. These findings stayed significant after adjusting for red-blue political affiliation where states with red political affiliation have lower vaccination rates. Further study is needed to evaluate how to stop online misinformation among states with low income and low educational aptitude scores; and whether such an effort will increase overall vaccination rates in the United States.

scholarly journals Decoding State Vaccination Rates Using Intelligence Quotient, Income, and Political Affiliation

2021 ◽  
Author(s):  
Azad Kabir ◽  
Raeed Kabir ◽  
Jebun Nahar ◽  
Ritesh Sengar
Keyword(s):  
United States ◽  
Low Income ◽  
Intelligence Quotient ◽  
The United States ◽  
Political Affiliation ◽  
Vaccination Rates ◽  
Factors Associated ◽  
Average Intelligence ◽  
The Us ◽  
Lower Intelligence

The objective of the study was to evaluate the risk factors associated with lower COVID-19 vaccination rates in the United States. The study evaluated the effect of red-blue political affiliation, and the effect of the US state's average intelligence quotient (IQ) and per capita income on states vaccination rates. The study found that states with concomitantly lower income along with lower intelligence quotient (IQ) are less vaccinated while the states with higher income have higher vaccination rates even among those with lower intelligence quotients. These findings stayed significant after adjusting for red-blue political affiliation where states with red political affiliation have lower vaccination rates. Further study is needed to evaluate how to stop online misinformation among low-income low intelligence quotient states and whether such an effort will increase overall vaccination rates in the United States.

scholarly journals Decoding the Risk of Accepting Online Misinformation Using Intelligence Quotient and Income

2021 ◽  
Author(s):  
Azad Kabir ◽  
Raeed Kabir ◽  
Jebun Nahar ◽  
Ritesh Sengar
Keyword(s):  
United States ◽  
Low Income ◽  
Intelligence Quotient ◽  
The United States ◽  
Demographic Groups ◽  
Factors Associated ◽  
The Us ◽  
Surrogate Measure ◽  
Lower Intelligence ◽  
The Impact

Abstract: The object of the study was to evaluate the risk factors associated with accepting online misinformation about COVID-19 vaccination in the United States. The percentages of fully vaccinated people, with regards to COVID-19, were considered as a surrogate measure of accepting online misinformation. The study evaluated the impact of the US state's average intelligence quotient (IQ) and per capita income on accepting misinformation. The study found that socio-demographic groups with lower income along with lower intelligence quotient (IQ) are more vulnerable to online misinformation theories surrounding COVID-19. Further study is needed to evaluate how to increase the intelligence quotient among low-income individuals and whether such an effort will reduce the acceptance of misinformation among the vulnerable population in the United States.

scholarly journals A spatially detailed blue water footprint of the United States economy

2018 ◽  
Vol 22 (5) ◽  
pp. 3007-3032 ◽  
Author(s):  
Richard R. Rushforth ◽  
Benjamin L. Ruddell
Keyword(s):  
United States ◽  
Water Use ◽  
Water Footprint ◽  
Virtual Water ◽  
The United States ◽  
Energy Information Administration ◽  
Blue Water ◽  
Consumptive Use ◽  
The Us ◽  
Per Capita

Abstract. This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale (county-level) federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the US Energy Information Administration (EIA), the US Department of Transportation (USDOT), the US Department of Energy (USDOE), and the US Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the US water footprint (F) and in the observed pattern of virtual water flows. Four virtual water accounting scenarios were developed with minimum (Min), median (Med), and maximum (Max) consumptive use scenarios and a withdrawal-based scenario. The median water footprint (FCUMed) of the US is 181 966 Mm3 (FWithdrawal: 400 844 Mm3; FCUMax: 222 144 Mm3; FCUMin: 61 117 Mm3) and the median per capita water footprint (FCUMed′) of the US is 589 m3 per capita (FWithdrawal′: 1298 m3 per capita; FCUMax′: 720 m3 per capita; FCUMin′: 198 m3 per capita). The US hydroeconomic network is centered on cities. Approximately 58 % of US water consumption is for direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total US blue water footprint, and is dominated by irrigated agriculture in the western US. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 to over 99 % depending on location. Harmonized region-specific, economic-sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere.

Environmental risk factors associated with Helicobacter pylori seroprevalence in the United States: a cross-sectional analysis of NHANES data

2015 ◽  
Vol 143 (12) ◽  
pp. 2520-2531 ◽  
Author(s):  
W. S. KRUEGER ◽  
E. D. HILBORN ◽  
R. R. CONVERSE ◽  
T. J. WADE
Keyword(s):  
United States ◽  
Risk Factors ◽  
Helicobacter Pylori ◽  
Environmental Risk ◽  
The United States ◽  
Environmental Risk Factors ◽  
Living Conditions ◽  
Well Water ◽  
Factors Associated ◽  
H Pylori

SUMMARYHelicobacter pylori imparts a considerable burden to public health. Infections are mainly acquired in childhood and can lead to chronic diseases, including gastric ulcers and cancer. The bacterium subsists in water, but the environment's role in transmission remains poorly understood. The nationally representative National Health and Nutrition Examination Survey (NHANES) was examined for environmental risk factors associated with H. pylori seroprevalence. Data from 1999–2000 were examined and weighted to represent the US population. Multivariable logistic regression estimated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for associations with seropositivity. Self-reported general health condition was inversely associated with seropositivity. Of participants aged <20 years, seropositivity was significantly associated with having a well as the source of home tap water (aOR 1·7, 95% CI 1·1–2·6) and living in a more crowded home (aOR 2·3, 95% CI 1·5–3·7). Of adults aged ⩾20 years, seropositivity was not associated with well water or crowded living conditions, but adults in soil-related occupations had significantly higher odds of seropositivity compared to those in non-soil-related occupations (aOR 1·9, 95% CI 1·2–2·9). Exposures to both well water and occupationally related soil increased the effect size of adults' odds of seropositivity compared to non-exposed adults (aOR 2·7, 95% CI 1·3-5·6). Environmental exposures (well-water usage and occupational contact with soil) play a role in H. pylori transmission. A disproportionate burden of infection is associated with poor health and crowded living conditions, but risks vary by age and race/ethnicity. These findings could help inform interventions to reduce the burden of infections in the United States.

scholarly journals Nature inequity and higher COVID-19 case rates in less-green neighbourhoods in the United States

2021 ◽  
Author(s):  
Erica N. Spotswood ◽  
Matthew Benjamin ◽  
Lauren Stoneburner ◽  
Megan M. Wheeler ◽  
Erin E. Beller ◽  
...  
Keyword(s):  
United States ◽  
Low Income ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The United States ◽  
Incidence Rates ◽  
Lower Income ◽  
Urban Nature ◽  
Urbanized Areas ◽  
Block Groups

AbstractUrban nature—such as greenness and parks—can alleviate distress and provide space for safe recreation during the COVID-19 pandemic. However, nature is often less available in low-income populations and communities of colour—the same communities hardest hit by COVID-19. In analyses of two datasets, we quantified inequity in greenness and park proximity across all urbanized areas in the United States and linked greenness and park access to COVID-19 case rates for ZIP codes in 17 states. Areas with majority persons of colour had both higher case rates and less greenness. Furthermore, when controlling for sociodemographic variables, an increase of 0.1 in the Normalized Difference Vegetation Index was associated with a 4.1% decrease in COVID-19 incidence rates (95% confidence interval: 0.9–6.8%). Across the United States, block groups with lower income and majority persons of colour are less green and have fewer parks. Our results demonstrate that the communities most impacted by COVID-19 also have the least nature nearby. Given that urban nature is associated with both human health and biodiversity, these results have far-reaching implications both during and beyond the pandemic.

Abstract WMP60: Temporal Trends in Incidence, Prevalence and Epidemiological Characteristics of Cerebral Venous Thrombosis in the United States

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Fadar Otite ◽  
Smit Patel ◽  
Richa Sharma ◽  
Pushti Khandwala ◽  
Devashish Desai ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Cerebral Venous Thrombosis ◽  
The United States ◽  
P Value ◽  
Joinpoint Regression ◽  
The Us ◽  
Epidemiological Characteristics ◽  
Over Time ◽  
Age And Sex

Background: The primary aim of this study is to describe current trends in racial-, age- and sex-specific incidence, clinical characteristics and burden of cerebral venous thrombosis (CVT) in the United States (US). Methods: Validated International Classification of Disease codes were used to identify all adult new cases of CVT (n=5,567) in the State Inpatients Database of New York and Florida (2006-2016) and all cases of CVT in the entire US from the National Inpatient Sample 2005-2016 (weighted n=57,315). Incident CVT counts were combined with annual US Census data to compute age and sex-specific incidence of CVT. Joinpoint regression was used to evaluate trends in incidence over time. Results: From 2005-2016, 0.47%-0.80% of all strokes in the US were CVTs but this proportion increased by 70.4% over time. Of all CVTs over this period, 66.7% were in females but this proportion declined over time (p<0.001). Pregnancy/puerperium (27.4%) and cancer (11.8%) were the most common risk factors in women, while cancer (19.5%) and central nervous trauma (11.3) were the most common in men. Whereas the prevalence of pregnancy/puerperium declined significantly over time in women, that of cancer, inflammatory conditions and trauma increased over time in both sexes. Annual age and sex-standardized incidence of CVT in cases/million population ranged from 13.9-20.2, but incidence varied significantly by sex (women: 20.3-26.9; men 6.8-16.8) and by age/sex (women 18-44yo: 24.0-32.6%; men: 18-44yo: 5.3-12.8). Age and sex-standardized incidence also differed by race (Blacks:18.6-27.2; whites: 14.3-18.5; Asians: 5.1-13.8). On joinpoint regression, incidence increased across 2006-2016 but most of this increase was driven by increase in all age groups of men (combined annualized percentage change (APC) 9.2%, p-value <0.001), women 45-64 yo (APC 7.8%, p-value <0.001) and women ≥65 yo (APC 7.4%, p-value <0.001). Incidence in women 18-44 yo remained unchanged over time . Conclusion: The epidemiological characteristics of CVT patients in the US is changing. Incidence increased significantly over the last decade. Further studies are needed to determine whether this increase represents a true increase from changing risk factors or artefactual increase from improved detection.

Risk factors associated with strongylid egg count prevalence and abundance in the United States equine population

2018 ◽  
Vol 257 ◽  
pp. 58-68 ◽  
Author(s):  
M.K. Nielsen ◽  
M.A. Branan ◽  
A.M. Wiedenheft ◽  
R. Digianantonio ◽  
J.A. Scare ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
The United States ◽  
Factors Associated

scholarly journals Sociodemographic and Clinical Risk Factors Associated With Tuberculosis Mortality in the United States, 2009-2013

2017 ◽  
Vol 132 (3) ◽  
pp. 366-375 ◽  
Author(s):  
Haylea A. Hannah ◽  
Roque Miramontes ◽  
Neel R. Gandhi
Keyword(s):  
United States ◽  
Risk Factors ◽  
Multinomial Logistic Regression ◽  
The United States ◽  
Multidrug Resistant ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Specific Mortality ◽  
Stage Renal Disease ◽  
End Stage

Objectives: The objectives of our study were (1) to determine risk factors associated with tuberculosis (TB)–specific and non–TB-specific mortality among patients with TB and (2) to examine whether risk factors for TB-specific mortality differed from those for non–TB-specific mortality. Methods: We obtained data from the National Tuberculosis Surveillance System and included all patients who had TB between 2009 and 2013 in the United States and its territories. We used multinomial logistic regression analysis to determine the adjusted odds ratio (aOR) of each risk factor for TB-specific and non–TB-specific mortality. Results: Of 52 175 eligible patients with TB, 1404 died from TB, and 2413 died from other causes. Some of the risk factors associated with the highest odds of TB-specific mortality were multidrug-resistant TB diagnosis (aOR = 3.42; 95% CI, 1.95-5.99), end-stage renal disease (aOR = 3.02; 95% CI, 2.23-4.08), human immunodeficiency virus infection (aOR = 2.63; 95% CI, 2.02-3.42), age 45-64 years (aOR = 2.57; 95% CI, 2.01-3.30) or age ≥65 years (aOR = 5.76; 95% CI, 4.37-7.61), and immunosuppression (aOR = 2.20; 95% CI, 1.71-2.83). All of these risk factors except multidrug-resistant TB were also associated with increased odds of non–TB-specific mortality. Conclusion: TB patients with certain risk factors have an elevated risk of TB-specific mortality and should be monitored before, during, and after treatment. Identifying the predictors of TB-specific mortality may help public health authorities determine which subpopulations to target and where to allocate resources.

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