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This paper reviews the evidence for the effectiveness and cost-effectiveness of policies to reduce alcohol-related harm. Policies focus on price, marketing, availability, information and education, the drinking environment, drink-driving, and brief interventions and treatment. Although there is variability in research design and measured outcomes, evidence supports the effectiveness and cost-effectiveness of policies that address affordability and marketing. An adequate reduction in temporal availability, particularly late night on-sale availability, is effective and cost-effective. Individually-directed interventions delivered to at-risk drinkers and enforced legislative measures are also effective. Providing information and education increases awareness, but is not sufficient to produce long-lasting changes in behaviour. At best, interventions enacted in and around the drinking environment lead to small reductions in acute alcohol-related harm. Overall, there is a rich evidence base to support the decisions of policy makers in implementing the most effective and cost-effective policies to reduce alcohol-related harm.

Governments can use fiscal policies to regulate the prices and consumption of potentially unhealthy products. However, policies aimed at reducing consumption by increasing prices, for example by taxation, might impose an unfair financial burden on low-income households. We used data from household expenditure surveys to estimate patterns of expenditure on potentially unhealthy products by socioeconomic status, with a primary focus on low-income and middle-income countries. Price policies affect the consumption and expenditure of a larger number of high-income households than low-income households, and any resulting price increases tend to be financed disproportionately by high-income households. As a share of all household consumption, however, price increases are often a larger financial burden for low-income households than for high-income households, most consistently in the case of tobacco, depending on how much consumption decreases in response to increased prices. Large health benefits often accrue to individual low-income consumers because of their strong response to price changes. The potentially larger financial burden on low-income households created by taxation could be mitigated by a pro-poor use of the generated tax revenues.

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BackgroundAir pollution damages health by promoting the onset of some non-communicable diseases (NCDs), putting additional strain on the National Health Service (NHS) and social care. This study quantifies the total health and related NHS and social care cost burden due to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in England.Method and findingsAir pollutant concentration surfaces from land use regression models and cost data from hospital admissions data and a literature review were fed into a microsimulation model, that was run from 2015 to 2035. Different scenarios were modelled: (1) baseline ‘no change’ scenario; (2) individuals’ pollutant exposure is reduced to natural (non-anthropogenic) levels to compute the disease cases attributable to PM2.5 and NO2; (3) PM2.5 and NO2 concentrations reduced by 1 μg/m3; and (4) NO2 annual European Union limit values reached (40 μg/m3). For the 18 years after baseline, the total cumulative cost to the NHS and social care is estimated at £5.37 billion for PM2.5 and NO2 combined, rising to £18.57 billion when costs for diseases for which there is less robust evidence are included. These costs are due to the cumulative incidence of air-pollution-related NCDs, such as 348,878 coronary heart disease cases estimated to be attributable to PM2.5 and 573,363 diabetes cases estimated to be attributable to NO2 by 2035. Findings from modelling studies are limited by the conceptual model, assumptions, and the availability and quality of input data.ConclusionsApproximately 2.5 million cases of NCDs attributable to air pollution are predicted by 2035 if PM2.5 and NO2 stay at current levels, making air pollution an important public health priority. In future work, the modelling framework should be updated to include multi-pollutant exposure–response functions, as well as to disaggregate results by socioeconomic status.