Association between sexually explicit messages and sleep health among French sexual minority men

It has been demonstrated that sexual minority men (SMM) participate in sexting. While research has shown that engagement in the exchange of sexually explicit media is associated with poor health outcomes, no previous research has investigated its association with sleep health outcomes. This study sought to examine the association between sexually explicit media and sleep health among SMM, a population that suffers from poor sleep health. A popular geosocial networking application was used to recruit SMM individuals (N?=?580) in the Paris, France, metropolitan area. Multivariate analyses, adjusting for sociodemographics, were used to test the association between the frequency of sexually explicit messaging and three dimensions of sleep health: (1) sleep quality, (2) sleep duration, and (3) two aspects of sleep problems. In multivariate analyses, those who reported engaging in sexually explicit messaging more were more likely to report getting less than seven?hours of sleep (aRR = 1.24; 95% CI = 1.08, 1.43) compared with those who reported engaging in sexually explicit messaging less. No significant associations were found between sexting and sleep quality or reporting sleep problems. Sexually explicit messaging was associated with shorter sleep duration. Intervention targeted at individuals who sext could potentially improve sleep health outcomes.     

Examining the Impact of Demographic Factors on Air Pollution

This study adds to the emerging literature examining empirically the link between population size, other demographic factors and pollution. We contribute by using more reliable estimation techniques and examine two air pollutants. By considering sulfur dioxide, we become the first study to explicitly examine the impact of demographic factors on a pollutant other than carbon dioxide at the cross-national level. We also take into account the urbanization rate and the average household size neglected by many prior cross-national econometric studies. For carbon dioxide emissions we find evidence that population increases are matched by proportional increases in emissions while a higher urbanization rate and lower average household size increase emissions. For sulfur dioxide emissions, we find a U-shaped relationship, with the population-emissions elasticity rising at higher population levels. Urbanization and average household size are not found to be significant determinants of sulfur dioxide emissions. For both pollutants, our results suggest that an increasing share of global emissions will be accounted for by developing countries. Implications for the environmental Kuznets curve literature are described and directions for further work identified.     

Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose‐infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion.     

Use of incentives to motivate healthy behaviors among employees

We conducted an extensive literature search of both published and unpublished sources to assess the use and effectiveness of worksite interventions that offer financial and other incentives. Many companies are using financial incentives, either alone or in combination with other interventions, to motivate employees to adopt and maintain healthier lifestyles. These incentives include cash bonuses, paid vacation days, and health insurance rebates. Although more research is needed, the literature suggests that financial incentives, if properly implemented, may successfully promote behavioral change among employees. Eric A. Finkelstein Ph.D., M.H.A. currently conducts economic and health policy research at RTI International, teaches an undergraduate Health Economics course at Duke University, and is a member of RTI-UNC Center of Excellence in Health promotion Economics. He focuses on the economic causes and consequences of health behaviors, with a primary emphasis on behaviors related to obesity. He has published several peer-reviewed papers in this area. A recent publication entitled “National Medical Expenditures Attributable to Overweight and Obesity,” was published in Health Affairs and garnered national media attention, including a front-page story in USA Today, coverage in Time magazine and the Washington Post, and was reported in other radio, television, newspaper, and Internet outlets across the country. That paper is now routinely cited as a driving motivation to reduce obesity rates. Dr. Finkelstein currently leads several projects concerning the causes and consequences of health behaviors for the CDC and other public and private sector agencies, and frequently speaks at conferences concerning the economic impact of obesity and strategies for reducing this burden. Katherine M. Kosa, M.S. conducts economic and food and nutrition policy research at RTI International with a primary focus on consumer behavior research. She recently completed a study to examine the general public's attitude and support for obesity interventions recently introduced at the state and federal level. To inform labeling policy decisions for USDA and FDA, Ms. Kosa conducts focus groups and surveys to understand consumer attitudes, knowledge, and practices.     

HIV/AIDS and Cross-National Convergence in Life Expectancy

This article analyzes the effect of HIV/AIDS on the cross-national convergence in life expectancy as well as infant and child survival rates by comparing three scenarios. One is based on historical and future best-guess estimated values given the existence of the epidemic. The second scenario assumes that the effect of the epidemic is much worse than expected. The final scenario is based on hypothetical values derived from estimations where the mortality caused by the epidemic is removed. For life expectancy, convergence becomes stalled in the late 1980s (without weighting by country population size) or 1990s (with weighting). Convergence in infant and child survival rates does not become stalled, but slows down. These results are mainly attributable to the epidemic since all signs of stalled convergence or even divergence disappear in the “No AIDS scenario.” Given the existence of the epidemic, however, the reduced degree of inequality in life expectancy attained by 1985 is only expected to be achieved again by 2015 at the earliest. If the epidemic turns out much worse than expected, divergence could continue to 2050. No divergence is to be expected in infant and child survival rates in any of the scenarios.     

A comparison study of realtime fatality rates: severe acute respiratory syndrome in Hong Kong, Singapore, Taiwan, Toronto and Beijing, China

Summary.  In an outbreak of a completely new infectious disease like severe acute respiratory syndrome (SARS), estimation of the fatality rate over the course of the epidemic is of clinical and epidemiological importance. In contrast with the constant case fatality rate, a new measure, termed the 'realtime' fatality rate, is proposed for monitoring the new emerging epidemic at a population level. A competing risk model implemented via a counting process is used to estimate the realtime fatality rate in an epidemic of SARS. It can capture and reflect the time-varying nature of the fatality rate over the course of the outbreak in a timely and accurate manner. More importantly, it can provide information on the efficacy of a certain treatment and management policy for the disease. The method has been applied to the SARS data from the regions affected, namely Hong Kong, Singapore, Toronto, Taiwan and Beijing. The magnitudes and patterns of the estimated fatalities are virtually the same except in Beijing, which has a lower rate. It is speculated that the effect is linked to the different treatment protocols that were used. The standard estimate of the case fatality rate that was used by the World Health Organization has been shown to be unable to provide useful information to monitor the time-varying fatalities that are caused by the epidemic.     

The Greater Ability of Graphical Versus Numerical Displays to Increase Risk Avoidance Involves a Common Mechanism

By displaying a risk reduction of 50% graphically rather than numerically, Stone, Yates, and Parker significantly increased professed risk-avoidant behavior. The current experiments replicated this effect at various risk ratios. Specifically, participants were willing to spend more money to reduce a risk when the risk information was displayed by asterisks rather than by numbers for risk-reduction ratios ranging from 3% to 97%. Transforming the amount participants were willing to spend to logarithms significantly improved a linear fit to the data, suggesting that participants convert this variable within the decision-making process. Moreover, a log-linear model affords an exceptional fit to both the graphical and numerical data, suggesting that a graphical presentation elicits the same decision-making mechanism as does the numerical display. In addition, the data also suggest that each person removed from harm is weighted more by some additional factor in the graphical compared to the numerical presentations.