Utilization of Long-Acting Reversible Contraceptives in the United States After vs Before the 2016 US Presidential Election.
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ABSTRACT:
SUBMITTER: Pace LE
PROVIDER: S-EPMC6439701 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
Publications
Utilization of Long-Acting Reversible Contraceptives in the United States After vs Before the 2016 US Presidential Election.
Pace Lydia E LE Dusetzina Stacie B SB Murray Horwitz Mara E ME Keating Nancy L NL
JAMA internal medicine 20190301 3
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Project description:BackgroundThe 2016 presidential election and the controversial policy agenda of its victor have raised concerns about how the election may have impacted mental health.ObjectiveAssess how mental health changed from before to after the November 2016 election and how trends differed in states that voted for Donald Trump versus Hillary Clinton.DesignPre- versus post-election study using monthly cross-sectional survey data.ParticipantsA total of 499,201 adults surveyed in the Behavioral Risk Factor Surveillance System from May 2016 to May 2017.ExposureResidence in a state that voted for Trump versus state that voted for Clinton and the candidate's margin of victory in the state.Main measuresSelf-reported days of poor mental health in the last 30 days and depression rate.Key resultsCompared to October 2016, the mean days of poor mental health in the last 30 days per adult rose from 3.35 to 3.85 in December 2016 in Clinton states (0.50 days difference, p = 0.005) but remained statistically unchanged in Trump states, moving from 3.94 to 3.78 days (- 0.17 difference, p = 0.308). The rises in poor mental health days in Clinton states were driven by older adults, women, and white individuals. The depression rate in Clinton states began rising in January 2017. A 10-percentage point higher margin of victory for Clinton in a state predicted 0.41 more days of poor mental health per adult in December 2016 on average (p = 0.001).ConclusionsIn states that voted for Clinton, there were 54.6 million more days of poor mental health among adults in December 2016, the month following the election, compared to October 2016. Clinicians should consider that elections could cause at least transitory increases in poor mental health and tailor patient care accordingly, especially with the 2020 election upon us.
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Project description:We use 19 billion likes on the posts of top 2000 U.S. fan pages on Facebook from 2015 to 2016 to measure the dynamic ideological positions for politicians, news outlets, and users at the national and state levels. We then use these measures to derive support rates for 2016 presidential candidates in all 50 states, to predict the election, and to compare them with state-level polls and actual vote shares. We find that: (1) Assuming that users vote for candidates closer to their own ideological positions, support rates calculated using Facebook predict that Trump will win the electoral college vote while Clinton will win the popular vote. (2) State-level Facebook support rates track state-level polling averages and pass the cointegration test, showing two time series share similar trends. (3) Compared with actual vote shares, polls generally have smaller margin of errors, but polls also often overestimate Clinton's support in right-leaning states. Overall, we provide a method to forecast elections at low cost, in real time, and based on passively revealed preference and little researcher discretion.
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Project description:ObjectiveResearch suggests that sociopolitical stressors connected with the 2016 presidential election were associated with increases in preterm birth among Latina women. This study determined whether periviable births (<26 weeks gestation), which exhibit extremely high rates of infant morbidity and mortality, among US Latina women increased above expected levels after the 2016 US presidential election.MethodsWe assigned singleton live births among Latina and non-Latina white women in the US to 96 monthly conception cohorts conceived from January 2009 through December 2016. We constructed risk ratios by dividing the rate of periviable birth among Latina women by the rate among non-Latina white women. We used time-series methods to determine if the risk ratio of periviable births in cohorts conceived by Latina women and exposed to the election of 2016 exceeded those expected from autocorrelation and calendar effects.ResultsWe found an outlying sequence of risk ratios among Latina women starting with the cohort conceived in April and ending with that conceived in November 2016. Increases in the ratios ranged from 0.07 above an expected of 1.61 for the cohort conceived in June, to 0.39 above an expected of 1.27 for the cohort conceived in April.ConclusionWe find that pregnancies in gestation at the time of the 2016 election among Latina women yielded more than expected periviable births. These findings support the argument that the prospect of anti-immigrant policies promised by the Trump campaign sufficiently stressed Latina women to affect the timing of birth.
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Project description:Indonesia is one of the countries that is currently entering the political year for the election of President, Regional Heads, and Members of the Legislative in 2024. This has become a hot topic on social media, especially about the Presidential Election. Twitter is one of the platforms with the largest users in Indonesia. It is interesting to see the alignment of Twitter users towards presidential candidates who already have a carrying party, namely Ganjar Pranowo, Prabowo Subianto, and Anies Baswedan based on a sentiment analysis approach. User feedback data about Indonesian Presidential candidates are obtained from the Twitter platform using Twitter API with Python programming language. The data obtained was 30,000 data with each candidate as many as 10,000 data. Data is pulled in April 2023 with specific keywords. The time for data withdrawal is chosen based on the announcement of Presidential Candidates carried by political parties before the schedule for determining or campaigning for Presidential candidates. Current data can potentially be used again as a comparison of analysis of presidential candidates on campaign time spans and after campaigns or actual calculation results. The data that can be accessed is in CSV format and has gone through several stages such as labelling using Language experts, removing spam Tweets & empty cells and preprocessing.
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Project description:Two studies conducted during the 2016 presidential campaign examined the dynamics of the objectivity illusion, the belief that the views of "my side" are objective while the views of the opposing side are the product of bias. In the first, a three-stage longitudinal study spanning the presidential debates, supporters of the two candidates exhibited a large and generally symmetrical tendency to rate supporters of the candidate they personally favored as more influenced by appropriate (i.e., "normative") considerations, and less influenced by various sources of bias than supporters of the opposing candidate. This study broke new ground by demonstrating that the degree to which partisans displayed the objectivity illusion predicted subsequent bias in their perception of debate performance and polarization in their political attitudes over time, as well as closed-mindedness and antipathy toward political adversaries. These associations, furthermore, remained significant even after controlling for baseline levels of partisanship. A second study conducted 2 d before the election showed similar perceptions of objectivity versus bias in ratings of blog authors favoring the candidate participants personally supported or opposed. These ratings were again associated with polarization and, additionally, with the willingness to characterize supporters of the opposing candidate as evil and likely to commit acts of terrorism. At a time of particular political division and distrust in America, these findings point to the exacerbating role played by the illusion of objectivity.
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Project description:The dynamics and influence of fake news on Twitter during the 2016 US presidential election remains to be clarified. Here, we use a dataset of 171 million tweets in the five months preceding the election day to identify 30 million tweets, from 2.2 million users, which contain a link to news outlets. Based on a classification of news outlets curated by www.opensources.co , we find that 25% of these tweets spread either fake or extremely biased news. We characterize the networks of information flow to find the most influential spreaders of fake and traditional news and use causal modeling to uncover how fake news influenced the presidential election. We find that, while top influencers spreading traditional center and left leaning news largely influence the activity of Clinton supporters, this causality is reversed for the fake news: the activity of Trump supporters influences the dynamics of the top fake news spreaders.
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Project description:Previous research suggests that stressors may trigger the onset of acute cardiovascular disease (CVD) events within hours to days, but there has been limited research around sociopolitical events such as presidential elections. Among adults ≥18 y of age in Kaiser Permanente Southern California, hospitalization rates for acute CVD were compared in the time period immediately prior to and following the 2016 presidential election date. Hospitalization for CVD was defined as an inpatient or emergency department discharge diagnosis of acute myocardial infarction (AMI) or stroke using International Classification of Diseases, 10th revision codes. Rate ratios (RR) and 95% confidence intervals (CIs) were calculated comparing CVD rates in the 2 d following the 2016 election to rates in the same 2 d of the prior week. In a secondary analysis, AMI and stroke were analyzed separately. The rate of CVD events in the 2 d after the 2016 presidential election (573.14 per 100,000 person-years [PY]) compared to the rate in the window prior to the 2016 election (353.75 per 100,000 PY) was 1.62 times higher (95% CI 1.17, 2.25). Results were similar across sex, age, and race/ethnicity groups. The RRs were similar for AMI (RR 1.67, 95% CI 1.00, 2.76) and stroke (RR 1.59, 95% CI 1.03, 2.44) separately. Transiently heightened cardiovascular risk around the 2016 election may be attributable to sociopolitical stress. Further research is needed to understand the intersection between major sociopolitical events, perceived stress, and acute CVD events.
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Project description:We use data from the American National Election Studies from 1996 to 2016 to study the role of the internet in the 2016 U.S. presidential election outcome. We compare trends in the Republican share of the vote between likely and unlikely internet users, and between actual internet users and non-users. Relative to prior years, the Republican share of the vote in 2016 was as high or higher among the groups least active online.
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Project description:ObjectivesThe sex ratio at birth (proportion of boys to girls) generally shows slight male preponderance but may decrease in response to societal stressors. Discrete adverse events such as terrorist attacks and disasters typically lead to a temporary decline in the sex ratio 3-5 months later, followed by resolution over around 5 months thereafter. We hypothesised that the unexpected outcome of the 2016 US presidential election may have been a societal stressor for liberal-leaning populations and thereby precipitated such an effect on the sex ratio in Canada.DesignEcological study.SettingAdministrative data for Ontario (Canada's most populous province).ParticipantsAll births in Ontario from April 2010 to Oct 2017 inclusive (n=1 079 758).Primary and secondary outcome measuresWe determined the sex ratio at birth in Ontario for each month from April 2010 to October 2017 and performed segmented regression analysis to evaluate the seasonally adjusted sex ratio for the following three time periods: before the November 2016 election; after the election to before the anticipated impact; and from anticipated impact to 5 months thereafter.ResultsIn the 12 months following the election, the lowest sex ratio occurred in March 2017 (4 months post election). Compared with the preceding months, the sex ratio was lower in the 5 months from March to July 2017 (p=0.02) during which time it was rising (p=0.01), reflecting recovery from the nadir. Both effects were seen in liberal-leaning regions of Ontario (lower sex ratio (p=0.006) and recovery (p=0.002) in March-July 2017) but not in conservative-leaning areas (p=0.12 and p=0.49, respectively).ConclusionThe 2016 US presidential election preceded a temporary reduction in the sex ratio at birth in Canada, with the time course of changes therein matching the characteristic pattern of a discrete societal stressor.
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Project description:Background Anger and extreme stress can trigger potentially fatal cardiovascular events in susceptible people. Political elections, such as the 2016 US presidential election, are significant stressors. Whether they can trigger cardiac arrhythmias is unknown. Methods and Results In this retrospective case-crossover study, we linked cardiac device data, electronic health records, and historic voter registration records from 2436 patients with implanted cardiac devices. The incidence of arrhythmias during the election was compared with a control period with Poisson regression. We also tested for effect modification by demographics, comorbidities, political affiliation, and whether an individual's political affiliation was concordant with county-level election results. Overall, 2592 arrhythmic events occurred in 655 patients during the hazard period compared with 1533 events in 472 patients during the control period. There was a significant increase in the incidence of composite outcomes for any arrhythmia (incidence rate ratio [IRR], 1.77 [95% CI, 1.42-2.21]), supraventricular arrhythmia (IRR, 1.82 [95% CI, 1.36-2.43]), and ventricular arrhythmia (IRR, 1.60 [95% CI, 1.22-2.10]) during the election relative to the control period. There was also an increase in specific types of arrhythmia, including atrial fibrillation (IRR, 1.50 [95% CI, 1.06-2.11]), supraventricular tachycardia (IRR, 3.7 [95% CI, 2.2-6.2]), nonsustained ventricular tachycardia (IRR, 1.7 [95% CI, 1.3-2.2]), and daily atrial fibrillation burden (P<0.001). No significant interaction was found for sex, race/ethnicity, device type, age ≥65 years, hypertension, coronary artery disease, heart failure, political affiliation, or concordance between individual political affiliation and county-level election results. Conclusions There was a significant increase in cardiac arrhythmias during the 2016 US presidential election. These findings suggest that exposure to stressful sociopolitical events may trigger arrhythmogenesis in susceptible people.
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