Effects of organized screening programs on breast cancer screening, incidence, and mortality in Europe.

We link data on regional Organized Screening Programs (OSPs) throughout Europe with survey data and population-based cancer registries to estimate effects of OSPs on breast cancer screening (mammography), incidence, and mortality. Identification is from regional variation in the existence and timing of OSPs, and in their age-eligibility criteria. We estimate that OSPs, on average, increase mammography by 25 percentage points, increase breast cancer incidence by 16% five years after the OSPs implementation, and reduce breast cancer mortality by about 10% ten years after.

Trust and COVID-19 vaccine hesitancy.

This article uses novel data collected on a weekly basis covering more than 35,000 individuals in the EU to analyze the relationship between trust in various dimensions and COVID-19 vaccine hesitancy. We found that trust in science is negatively correlated, while trust in social media and the use of social media as the main source of information are positively associated with vaccine hesitancy. High trust in social media is found among adults aged 65+, financially distressed and unemployed individuals, and hesitancy is largely explained by conspiracy beliefs among them. Finally, we found that the temporary suspension of the AstraZeneca vaccine in March 2021 significantly increased vaccine hesitancy and especially among people with low trust in science, living in rural areas, females, and financially distressed. Our findings suggest that trust is a key determinant of vaccine hesitancy and that pro-vaccine campaigns could be successfully targeted toward groups at high risk of hesitancy.

Predicting vaccine hesitancy from area-level indicators: A machine learning approach.

Vaccine hesitancy (VH) might represent a serious threat to the next COVID-19 mass immunization campaign. We use machine learning algorithms to predict communities at a high risk of VH relying on area-level indicators easily available to policymakers. We illustrate our approach on data from child immunization campaigns for seven nonmandatory vaccines carried out in 6062 Italian municipalities in 2016. A battery of machine learning models is compared in terms of area under the receiver operating characteristics curve. We find that the Random Forest algorithm best predicts areas with a high risk of VH improving the unpredictable baseline level by 24% in terms of accuracy. Among the area-level indicators, the proportion of waste recycling and the employment rate are found to be the most powerful predictors of high VH. This can support policymakers to target area-level provaccine awareness campaigns.

The health-economy trade-off during the Covid-19 pandemic: Communication matters.

How do people balance concerns for general health and economic outcomes during a pandemic? And, how does the communication of this trade-off affect individual preferences? We address these questions using a field experiment involving around 2000 students enrolled in a large university in Italy. We design four treatments where the trade-off is communicated using different combinations of a positive framing that focuses on protective strategies and a negative framing which refers to potential costs. We find that positive framing on the health side induces students to give greater relevance to the health dimension. The effect is sizeable and highly effective among many different audiences, especially females. Importantly, this triggers a higher level of intention to adhere to social distancing and precautionary behaviors. Moreover, irrespective of the framing, we find a large heterogeneity in students' preferences over the trade-off. Economics students and students who have directly experienced the economic impact of the pandemic are found to give greater value to economic outcomes.

Do-It-Yourself medicine? The impact of light cannabis liberalization on prescription drugs.

Governments worldwide are increasingly concerned about the booming use of CBD (cannabidiol) products. However, we know little about the impact of their liberalization. We study a unique case of unintended liberalization of a CBD-based product (light cannabis) that occurred in Italy in 2017. Using unique and high-frequency data on prescription drug sales and by exploiting the staggered local availability of the new product in each Italian province, we document a significant substitution effect between light cannabis and anxiolytics, sedatives, opioids, anti-depressants and anti-psychotics. Results are informative for regulators and suggest that bans on light cannabis use would disregard the needs of patients to seek effective reliefs of their symptoms.

A latent class approach to inequity in health using biomarker data.

We adopt an empirical approach to analyse, measure and decompose inequality of opportunity (IOp) in health, based on a latent class model. This addresses some of the limitations that affect earlier work in this literature concerning the definition of types, such as partial observability, the ad hoc selection of circumstances, the curse of dimensionality and unobserved type-specific heterogeneity that may lead to biased estimates of IOp. We apply our latent class approach to measure IOp in allostatic load, a composite measure of biomarker data. Using data from Understanding Society: The UK Household Longitudinal Study (UKHLS), we find that a latent class model with three latent types best fits the data, with the corresponding types characterised in terms of differences in their observed circumstances. Decomposition analysis shows that about two thirds of the total inequalities in allostatic load can be attributed to the direct and indirect contribution of circumstances and that the direct contribution of effort is small. Further analysis conditional on age-sex groups reveals that the relative (percentage) contribution of circumstances to the total inequalities remains mostly unaffected and the direct contribution of effort remains small.

Vaccine hesitancy and (fake) news: Quasi-experimental evidence from Italy.

The spread of fake news and misinformation on social media is blamed as a primary cause of vaccine hesitancy, which is one of the major threats to global health, according to the World Health Organization. This paper studies the effect of the diffusion of misinformation on immunization rates in Italy by exploiting a quasi-experiment that occurred in 2012, when the Court of Rimini officially recognized a causal link between the measles-mumps-rubella vaccine and autism and awarded injury compensation. To this end, we exploit the virality of misinformation following the 2012 Italian court's ruling, along with the intensity of exposure to nontraditional media driven by regional infrastructural differences in Internet broadband coverage. Using a Difference-in-Differences regression on regional panel data, we show that the spread of this news resulted in a decrease in child immunization rates for all types of vaccines.

Intergenerational transmission of nicotine within families: Have e-cigarettes influenced passive smoking?

Using an objective biomarker of active and passive smoking, we estimate Galtonian regressions of nicotine transmission and test whether the use of new nicotine delivery products (NDP) by parents had an influence on the transmission to children through passive smoking. We find evidence of a strong intergenerational transmission through passive smoking and that this is around four times larger for mothers compared to fathers. Moreover, we estimate an intention to treat difference-in-differences (DiD) model using parental cotinine as a continuous measure of exposure to the treatment and we find that the level of transmission of cotinine from parents was reduced to 51 per cent of the previous level just after the spread in the use of e-cigarettes in England and to 77 per cent when considering transmission from mothers. This is confirmed also by a DiD model which considers interaction between cotinine levels and self-reported use of NDP by parents and suggests that lower taxation of these devices may be justified on externality grounds.

Inequality of opportunity in health: A decomposition-based approach.

This paper presents new decomposition-based approaches to measure inequality of opportunity in health that capture Roemer's distinction between circumstances and effort and are consistent with both compensation and reward principles. Our approach is fully nonparametric in the way that it handles differences in circumstances and provides decompositions of both a rank-dependent relative (the Gini coefficient) and a rank-independent absolute inequality index (the variance). The decompositions distinguish the contribution of effort from the direct and indirect (through effort) contribution of circumstances to the total inequality. Our approach is illustrated by an empirical application that uses objectively measured biomarkers as health outcomes and as proxies for relevant effort variables. Using data from the Health Survey for England from 2003 to 2012, we find that circumstances are the leading determinant of inequality in cholesterol, glycated haemoglobin, and in a combined ill-health index whereas effort plays a substantial role in explaining inequality in fibrinogen only.

The Income-Health Relationship 'Beyond the Mean': New Evidence from Biomarkers.

The relationship between income and health is one of the most explored topics in health economics but less is known about this relationship at different points of the health distribution. Analysis based solely on the mean may miss important information in other parts of the distribution. This is especially relevant when clinical concern is focused on the tail of the distribution and when evaluating the income gradient at different points of the distribution and decomposing income-related inequalities in health is of interest. We use the unconditional quantile regression approach to analyse the income gradient across the entire distribution of objectively measured blood-based biomarkers. We apply an Oaxaca-Blinder decomposition at various quantiles of the biomarker distributions to analyse gender differentials in biomarkers and to measure the contribution of income (and other covariates) to these differentials. Using data from the Health Survey for England, we find a non-linear relationship between income and health and a strong gradient with respect to income at the highest quantiles of the biomarker distributions. We find that there is heterogeneity in the association of health to income across genders, which accounts for a substantial percentage of the gender differentials in observed health. Copyright © 2016 John Wiley & Sons, Ltd.

Contrast-enhanced ultrasound in portal venous system aneurysms: a multi-center study.

AIM: To investigate contrast-enhanced ultrasound (CEUS) findings in portal venous system aneurysms (PVSAs). METHODS: In this multi-center, retrospective, case series study, we evaluated CEUS features of seven cases of PVSAs that were found incidentally on conventional ultrasound in the period 2007-2013. Three Ultrasound Centers were involved (Chieti, Italy, Bad Mergentheim, Germany, and Cluj-Napoca, Romania). All patients underwent CEUS with Sonovue(®) (Bracco, Milan, Italy) at a standard dose of 2.4 mL, followed by 10 mL of 0.9% saline solution. The examinations were performed using multifrequency transducers and low mechanical index. We considered aneurysmal a focal dilatation of the portal venous system with a size that was significantly greater than the remaining segments of the same vein, and that was equal or larger than 21 mm for the extrahepatic segments of portal venous system, main portal vein and bifurcation, and 9 mm for the intrahepatic branches. RESULTS: After contrast agent injection, all PVSAs were not enhanced in the arterial phase (starting 8-22 s). All PVSAs were then rapidly enhanced in the early portal venous phase (starting three to five seconds after the arterial phase, 11-30 s), with persistence and slow washout of the contrast agent in the late phase (starting 120 s). In all patients, CEUS confirmed the presence of a "to-and-fro" flow by showing a swirling pattern within the dilatation in the early portal venous phase. CEUS also improved the delineation of the lumen, and was reliable in showing its patency degree and integrity of walls. In one patient, CEUS showed a partial enhancement of the lumen with a uniformly nonenhancing area in the portal venous and late phases, suggesting thrombosis. CONCLUSION: In our case series, we found that CEUS could be useful in the assessment and follow-up of a PVSA. Further studies are needed to validate its diagnostic accuracy.

Assessing inequalities in preventive care use in Europe.

This paper presents new international evidence on the extent of inequalities in breast cancer screening and blood test (cholesterol and blood sugar test) in 13 European Countries using data from the 2009 wave of the Survey of Health, Ageing and Retirement in Europe (SHARE). One important contribution of the paper is the inclusion of preexisting health conditions in the needs standardization procedure with the aim of taking into account utilization due to diagnosis or follow-up reasons. We find evidence of pro-rich inequalities in blood test use in some countries while high inequalities emerge in virtually every country with respect to mammography use. Decomposition analysis reveals that inequalities in mammography use are mostly driven by income while preventive needs distribution is only slightly pro-rich. On the other side, richer individuals appear to be much more likely to do blood tests despite their substantially lower diagnostic needs for that care. Generally, inequalities in mammography use are higher in countries without national breast cancer screening programs or in countries with only regional or less participated programs. Inequalities in blood tests are higher in countries with a high share of out-of-pocket payments and/or non universalistic entitlement to insurance coverage.

Health in the cities: when the neighborhood matters more than income.

Using a rich Italian cross-sectional dataset, we estimate the effect of a neighborhood problems aggregate (including pollution, crime, and noise) on self-assessed health, presence of chronic conditions and limitations in daily activities. We address the self-selection of the residents in their neighborhoods, as well as the possible endogeneity of income with respect to health, through instrumental variable methods and several endogeneity tests. The main novelty is the sound estimation of the neighborhood effect on health using observational data, which has the advantage of providing general results that are not dependent on any experimental design. This allows us to fully compare the neighborhood effect with the traditional socioeconomic determinants of health. Our main findings are that low quality neighborhoods are strongly health damaging. This effect is comparable to the primary/upper secondary education health differential and is even higher than the impact that poor economic circumstances have on health.

Social comparison and subjective well-being: does the health of others matter?

The importance of social comparison in shaping individual utility has been widely documented by subjective well-being literature. So far, income and unemployment have been the main dimensions considered in social comparison. This paper aims to investigate whether subjective well-being is influenced by inter-personal comparison with respect to health. Thus, we study the effects of the health of others and relative health hypotheses on two measures of subjective well-being: happiness and subjective health. Using data from the Italian Health Conditions survey, we show that a high incidence of chronic conditions and disability among reference groups negatively affects both happiness and subjective health. Such effects are stronger among people in the same condition. These results, robust to different econometric specifications and estimation techniques, suggest the presence of some sympathy in individual preferences with respect to health and reveal that other people's health status serves as a benchmark to assess one's own health condition.

Height and subjective well-being in Italy.

Using an Italian survey, we investigate the effect of height on individual happiness. We find that a large part of the effect of height on well-being is driven by a positive correlation between height and economic and health conditions. However, for young men the effect of height on happiness persists even after controlling for these variables, implying that height is associated with some psycho-social direct effects on well-being. Consistent with this hypothesis, we find that men care not only about their own height but also about the height of others in their reference group. Well-being is greater for individuals who are taller than other men in their reference group. Results are robust to different definitions of reference group and controlling for a number of other reference group characteristics.