Viewing the US presidential electoral map through the lens of public health

Political voting in the United Kingdom 2019 general election and risk of living with obesity in a nationally representative sample

BACKGROUND

Limited evidence from the United States suggests that county/state rates of people with obesity are positively associated with voting for the Republican Party presidential candidate, although this question has not yet been studied at the individual level, and/or outside of the United States, where the health and political systems are very different in other countries.

OBJECTIVES

Using individual level data, assess differences in rates of people with obesity according to political voting in the United Kingdom 2019 general election, and examine whether people living in constituencies won by Members of Parliament (MPs) from the Conservative Party were more likely to be living with obesity than those living in constituencies won by MPs from other parties.

METHODS

Data was obtained by the Ipsos KnowledgePanel where panellists are recruited via a random probability unclustered address-based sampling method. 4000/14,016 panellists were randomly invited to provide data on socio-demographics, health outcomes, voting behaviour and height/weight.

RESULTS

2668/4000 (67%) of invitees provided data, 95/2668 (3.5%) were not eligible to vote, with the remaining 2573 (96.5%) included. Conservative Party voters were more likely to be living with obesity than those who voted Labour (OR:1.42 95% CI (1.01-1.99)) or Liberal Democrats (1.54 95% CI (1.00-2.37)). Conservative Party voters on average had significantly higher BMI scores than those voting Labour and Liberal Democrats; BMI mean difference 0.88 points (95% CI: 0.16-1.61) between Conservative and Labour voters, and 1.04 points (95% CI: 0.07-2.02) between Conservatives and Liberal Democrats voters. There was no evidence participants living in constituencies won by Conservative MPs were more likely to be living with obesity than constituencies won by other party MPs.

CONCLUSION

Governments and public health agencies may need to focus on the political affiliation of the public when developing strategies to reduce the number of people with obesity.

Rapid sleep education: If you could tell people one thing about sleep, what should it be?

Informal learning settings such as museums provide unique opportunities for educating a local community about sleep. However, in such settings, information must be capable of immediately inciting interest. We developed a series of sleep "icebreakers" (brief, informal facts) to determine whether they elicited interest in sleep and encouraged behavioural change. There were 859 participants across three cross-sectional samples: (a) members of the local museum; (b) Mechanical Turk workers who responded to a "sleep" study advertisement; and (c) Mechanical Turk workers who responded to a "various topics" study advertisement that did not mention sleep. All three samples demonstrated high interest in sleep topics, though delayed recall of the icebreakers was strongest in participants who expected to learn about the sleep topics. Icebreaker interest ratings were independent of age, gender and race/ethnicity, suggesting that sleep is a topic of universal interest. Importantly, regardless of demographics and sample, the more the icebreakers interested the participants, the more likely participants were to indicate willingness to donate to a sleep exhibit, change their sleep behaviours, and post to social media. Thus, sleep icebreakers can rapidly elicit people's interest, and future outreach efforts should couple icebreakers with opportunities for subsequent personalized learning.

Political environment and mortality rates in the United States, 2001-19: population based cross sectional analysis

OBJECTIVE

To assess recent trends in age adjusted mortality rates (AAMRs) in the United States based on county level presidential voting patterns.

DESIGN

Cross sectional study.

SETTING

USA, 2001-19.

PARTICIPANTS

99.8% of the US population.

MAIN OUTCOME MEASURES

AAMR per 100 000 population and average annual percentage change (APC).

METHODS

The Centers for Disease Control and Prevention WONDER database was linked to county level data on US presidential elections. County political environment was classified as either Democratic or Republican for the four years that followed a November presidential election. Additional sensitivity analyses analyzed AAMR trends for counties that voted only for one party throughout the study, and county level gubernatorial election results and state level AAMR trends. Joinpoint analysis was used to assess for an inflection point in APC trends.

RESULTS

The study period covered five presidential elections from 2000 to 2019. From 2001 to 2019, the AAMR per 100 000 population decreased by 22% in Democratic counties, from 850.3 to 664.0 (average APC -1.4%, 95% confidence interval -1.5% to -1.2%), but by only 11% in Republican counties, from 867.0 to 771.1 (average APC -0.7%, -0.9% to -0.5%). The gap in AAMR between Democratic and Republican counties therefore widened from 16.7 (95% confidence interval 16.6 to 16.8) to 107.1 (106.5 to 107.7). Statistically significant inflection points in APC occurred for Democratic counties between periods 2001-09 (APC -2.1%, -2.3% to -1.9%) and 2009-19 (APC -0.8%, -1.0% to -0.6%). For Republican counties between 2001 and 2008 the APC was -1.4% (-1.8% to -1.0%), slowing to near zero between 2008 and 2019 (APC -0.2%, -0.4% to 0.0%). Male and female residents of Democratic counties experienced both lower AAMR and twice the relative decrease in AAMR than did those in Republican counties. Black Americans experienced largely similar improvement in AAMR in both Democratic and Republican counties. However, the AAMR gap between white residents in Democratic versus Republican counties increased fourfold, from 24.7 (95% confidence interval 24.6 to 24.8) to 101.3 (101.0 to 101.6). Rural Republican counties experienced the highest AAMR and the least improvement. All trends were similar when comparing counties that did not switch political environment throughout the period and when gubernatorial election results were used. The greatest contributors to the widening AAMR gap between Republican and Democratic counties were heart disease (difference in AAMRs 27.6), cancer (17.3), and chronic lower respiratory tract diseases (8.3), followed by unintentional injuries (3.3) and suicide (3.0).

CONCLUSION

The mortality gap in Republican voting counties compared with Democratic voting counties has grown over time, especially for white populations, and that gap began to widen after 2008.