BackgroundEvidence is mounting to suggest a causal relationship between the built environment and people’s physical activity behaviours, particularly active transport. The evidence base has been hindered to date by restricted consideration of cost and economic factors associated with built environment interventions, investigation of socioeconomic or ethnic differences in intervention effects, and an inability to isolate the effect of the built environment from other intervention types. The aims of this systematic review were to identify which environmental interventions increase physical activity in residents at the local level, and to build on the evidence base by considering intervention cost, and the differential effects of interventions by ethnicity and socioeconomic status.MethodsA systematic database search was conducted in June 2015. Articles were eligible if they reported a quantitative empirical study (natural experiment or a prospective, retrospective, experimental, or longitudinal research) investigating the relationship between objectively measured built environment feature(s) and physical activity and/or travel behaviours in children or adults. Quality assessment was conducted and data on intervention cost and whether the effect of the built environment differed by ethnicity or socioeconomic status were extracted.ResultsTwenty-eight studies were included in the review. Findings showed a positive effect of walkability components, provision of quality parks and playgrounds, and installation of or improvements in active transport infrastructure on active transport, physical activity, and visits or use of settings. There was some indication that infrastructure improvements may predominantly benefit socioeconomically advantaged groups. Studies were commonly limited by selection bias and insufficient controlling for confounders. Heterogeneity in study design and reporting limited comparability across studies or any clear conclusions to be made regarding intervention cost.ConclusionsImproving neighbourhood walkability, quality of parks and playgrounds, and providing adequate active transport infrastructure is likely to generate positive impacts on activity in children and adults. The possibility that the benefits of infrastructure improvements may be inequitably distributed requires further investigation. Opportunities to improve the quality of evidence exist, including strategies to improve response rates and representativeness, use of valid and reliable measurement tools, cost-benefit analyses, and adequate controlling for confounders.Electronic supplementary materialThe online version of this article (10.1186/s12966-017-0613-9) contains supplementary material, which is available to authorized users.

The effects of the legislation change were favourable from a public health perspective. Areas for further investigation and possible regulation were identified such as SHS related pollution in semi-enclosed outdoor areas. The study adds to a growing body of literature documenting the positive impact of comprehensive smoke-free legislation. The scientific and public health case for introducing comprehensive smoke-free legislation that covers all indoor public places and workplaces is now overwhelming, and should be a public health priority for legislators across the world as part of the globalization of effective public health policy to control the tobacco epidemic.

Background:Between 2010 and 2012, the World Health Organization Division of Pacific Technical Support led a regional climate change and health vulnerability assessment and adaptation planning project, in collaboration with health sector partners, in 13 Pacific island countries—Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Palau, Samoa, Solomon Islands, Tonga, Tuvalu, and Vanuatu.Objective:We assessed the vulnerabilities of Pacific island countries to the health impacts of climate change and planned adaptation strategies to minimize such threats to health.Methods:This assessment involved a combination of quantitative and qualitative techniques. The former included descriptive epidemiology, time series analyses, Poisson regression, and spatial modeling of climate and climate-sensitive disease data, in the few instances where this was possible; the latter included wide stakeholder consultations, iterative consensus building, and expert opinion. Vulnerabilities were ranked using a “likelihood versus impact” matrix, and adaptation strategies were prioritized and planned accordingly.Results:The highest-priority climate-sensitive health risks in Pacific island countries included trauma from extreme weather events, heat-related illnesses, compromised safety and security of water and food, vector-borne diseases, zoonoses, respiratory illnesses, psychosocial ill-health, non-communicable diseases, population pressures, and health system deficiencies. Adaptation strategies relating to these climate change and health risks could be clustered according to categories common to many countries in the Pacific region.Conclusion:Pacific island countries are among the most vulnerable in the world to the health impacts of climate change. This vulnerability is a function of their unique geographic, demographic, and socioeconomic characteristics combined with their exposure to changing weather patterns associated with climate change, the health risks entailed, and the limited capacity of the countries to manage and adapt in the face of such risks.Citation:McIver L, Kim R, Woodward A, Hales S, Spickett J, Katscherian D, Hashizume M, Honda Y, Kim H, Iddings S, Naicker J, Bambrick H, McMichael AJ, Ebi KL. 2016. Health impacts of climate change in Pacific island countries: a regional assessment of vulnerabilities and adaptation priorities. Environ Health Perspect 124:1707–1714; http://dx.doi.org/10.1289/ehp.1509756

It is well known that social, cultural and economic factors cause substantial inequalities in health. Should we strive to achieve a more even share of good health, beyond improving the average health status of the population? We examine four arguments for the reduction of health inequalities. 1 Inequalities are unfair. Inequalities in health are undesirable to the extent that they are unfair, or unjust. Distinguishing between health inequalities and health inequities can be contentious. Our view is that inequalities become "unfair" when poor health is itself the consequence of an unjust distribution of the underlying social determinants of health (for example, unequal opportunities in education or employment). 2 Inequalities aVect everyone. Conditions that lead to marked health disparities are detrimental to all members of society. Some types of health inequalities have obvious spillover eVects on the rest of society, for example, the spread of infectious diseases, the consequences of alcohol and drug misuse, or the occurrence of violence and crime. 3 Inequalities are avoidable. Disparities in health are avoidable to the extent that they stem from identifiable policy options exercised by governments, such as tax policy, regulation of business and labour, welfare benefits and health care funding. It follows that health inequalities are, in principle, amenable to policy interventions. A government that cares about improving the health of the population ought therefore to incorporate considerations of the health impact of alternative options in its policy setting process. 3 Interventions to reduce health inequalities are cost eVective. Public health programmes that reduce health inequalities can also be cost eVective. The case can be made to give priority to such programmes (for example, improving access to cervical cancer screening in low income women) on eYciency grounds. On the other hand, few programmes designed to reduce health inequalities have been formally evaluated using cost eVectiveness analysis. We conclude that fairness is likely to be the most influential argument in favour of acting to reduce disparities in health, but the concept of equity is contested and susceptible to diVerent interpretations. There is persuasive evidence for some outcomes that reducing inequalities will diminish "spill over" eVects on the health of society at large. In principle, you would expect that diVerences in health status that are not biologically determined are avoidable. However, the mechanisms giving rise to inequalities are still imperfectly understood, and evidence remains to be gathered on the eVectiveness of interventions to reduce such inequalities. (J Epidemiol Community Health 2000;54:923-929) It is well known that good health is not evenly shared. For example, according to the UK Independent Inquiry into Inequalities in Health, if all men aged 20-64 had the same mortality rates as those in the top two social classes, there would be approximately 17 000 fewer deaths each year in that country.

The objective of the study was to investigate the relationship between reported incidence of dengue fever and El Niño southern oscillation (ENSO) in 14 island nations of the South Pacific. Using a mixed ecological study design, we calculated correlations between annual averages of the southern oscillation index (SOI), local temperature and rainfall, and dengue fever. We also calculated temporal correlations between monthly reports of dengue fever cases on different islands. There were positive correlations between SOI and dengue in 10 countries. In five of these (including all of the larger islands) there were also positive correlations between SOI and estimates of local temperature and/or rainfall. There were temporal correlations between monthly reports of dengue cases within two groups of countries. Climate changes associated with ENSO may trigger an increase in dengue fever transmission in larger, more populated islands where the disease is endemic. There was also evidence of propagation of infection from larger islands to smaller neighbors. Unlike the initiation of epidemics, this transfer between islands appears to be independent of interannual climate variations, pointing to the importance of modulating factors in dengue transmission such as population density and travel. In the future, models of the impact of climate change must attempt to account for these factors.ImagesFigure 1Figure 2Figure 3Figure 4