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Many countries are developing or reviewing national adaptation policy for climate change but the extent to which these meet the health needs of vulnerable groups has not been assessed. This study examines the adequacy of such policies for nine known climate-vulnerable groups: people with mental health conditions, Aboriginal people, culturally and linguistically diverse groups, aged people, people with disabilities, rural communities, children, women, and socioeconomically disadvantaged people.The study analyses an exhaustive sample of national adaptation policy documents from Annex 1 ('developed') countries of the United Nations Framework Convention on Climate Change: 20 documents from 12 countries. A 'critical computational linguistics' method was used involving novel software-driven quantitative mapping and traditional critical discourse analysis.The study finds that references to vulnerable groups are relatively little present or non-existent, as well as poorly connected to language about practical strategies and socio-economic contexts, both also little present.The conclusions offer strategies for developing policy that is better informed by a 'social determinants of health' definition of climate vulnerability, consistent with best practice in the literature and global policy prescriptions.

In 2015, an estimated 429,000 deaths and 212 million cases of malaria occurred worldwide, while 70% of the deaths occurred in children under five years old. Changes in climatic exposure such as temperature and precipitation makes malaria one of the most climate sensitive outcomes. Using a global malaria mortality dataset for 105 countries between 1980 and 2010, we estimate that the global optimal temperature maximizing all-age malaria mortality is 20.6, lower than previously predicted in the literature. While in the case of child mortality, a significantly lower optimum temperature of 19.3° is estimated. Our results also suggest that in Africa and Asia, the continents where malaria is most prevalent malaria, mortality is maximized at 28.4 and 26.3, respectively. Furthermore, we estimate that child mortality (ages 0-4) is likely to increase by up to 20 percent in some areas due to climate change by the end of the 21st century.

I read with interest the commentary article by Bongaarts and Sitruk-Ware.1 I think this commentary is very timely, and I am so glad to see this topic being discussed. However, I wondered whether there could have been more of a focus on the impact of population in developed countries, particularly on the impact of having a child if you are in the most socioeconomically developed subgroup of the population? I would be really interested to hear the commentary authors' views on this. Although …

Alcohol outlets tend to be located in lower income areas, exposing lower income populations to excess risks associated with alcohol sales through these establishments. The objective of this study was to test two hypotheses about the etiology of these differential exposures based on theories of the economic geography of retail markets: (a) outlets will locate within or near areas of high alcohol demand, and (b) outlets will be excluded from areas with high land and structure rents.Data from the 2010 National Drug Strategy Household Survey were used to develop a surrogate for alcohol demand (i.e., market potential) at two census geographies for the city of Melbourne, Australia. Bayesian conditional autoregressive Poisson models estimated multilevel spatial relationships between counts of bars, restaurants, and off-premise outlets and market potential, income, and zoning ordinances (Level 1: n = 8,914).Market potentials were greatest in areas with larger older age, male, English-speaking, high-income populations. Independent of zoning characteristics, greater numbers of outlets appeared in areas with greater market potentials and the immediately surrounding areas. Greater income excluded outlets in local and surrounding areas.These findings are consistent with the hypothesis that alcohol outlets are located in areas with high demand and are excluded from high-income areas. These processes appear to take place at relatively small geographic scales, encourage the concentration of outlets in specific low-income areas, and represent a very general economic process likely to take place in communities throughout the world.

The Pan-African Consortium for the Evaluation of Anti-Tuberculosis Antibiotics (PanACEA) was designed to build tuberculosis (TB) trial capacity whilst conducting clinical trials on novel and existing agents to shorten and simplify TB treatment. PanACEA has now established a dynamic network of 11 sub-Saharan clinical trial sites and four European research institutions.In 2011, a capacity development program, funded by the European & Developing Countries Clinical Trials Partnership (EDCTP), was launched with four objectives, aiming at strengthening collaborating TB research sites to reach the ultimate goal of becoming self-sustainable institutions: networking; training; conducting clinical trials; and infrastructure scaling-up of sites.Assessment in six sub-Saharan TB-endemic countries (Gabon, Kenya, South Africa, Tanzania, Uganda and Zambia) were performed through a structured questionnaire, site visits, discussion with the PanACEA consortium, setting of milestones and identification of priorities and followed-up with evaluations of each site. The results of this needs-based assessment was then translated into capacity development measures.In the initial phase, over a four-year period (March 2011 - June 2014), the programme scaled-up six sites; conducted a monitoring training program for 11 participants; funded five MSc and four PhD students, fostering gender balance; conducted four epidemiological studies; supported sites to conduct five Phase II studies and formed a sustainable platform for TB research (panacea-tb.net).Our experience of conducting TB clinical trials within the PanACEA programme environment of mentoring, networking and training has provided a sound platform for establishing future sustainable research centres. Our goal of facilitating emergent clinical TB trial sites to better initiate and lead research activities has been mostly successful.

Despite overall progress toward achieving the Millennium Development Goals, large health discrepancies persist between developed and developing countries. The world is rapidly changing and the influences of societal change and climate change will disproportionately affect the world's most vulnerable populations, thus exacerbating current inequities. Current development strategies do not adequately address these disproportionate impacts of environmental exposures. The aim of this study was to propose a new framework to address the health consequences of environmental exposures beyond 2015. This framework is transdisciplinary and precautionary. It is based on identifying social and economic determinants of health, strengthening primary health systems, and improving the health of vulnerable populations. It incorporates deliberate plans for assessment and control of avoidable environmental exposures. It sets specific, measurable targets for health and environmental improvement.

As several contributions in this issue of International Journal of Public Health suggest (in particular that from Kjellstrom 2009), there is a wide range of potential—direct and indirect—health consequences of climate change. However, the science of such effects is still in its infancy and faces considerable challenges, as we try to suggest in our contribution (Xun et al. 2009). Possible events attributable to climate change range from rapid and catastrophic to slow and mild. For example, IPCC does not rule out (though it is very unlikely) a cascade of events leading to Bangladesh being swept away because of rapid Himalayan glacier melting. Apart from extreme and unlikely effects, some of the direct consequences of climate change are rather obvious and can be easily perceived, such as the deaths related to heat waves in Europe in 2003. The causal pathway in these cases is clear, and does not require any particularly sophisticated epidemiological technique. Confounding is irrelevant as far as we consider the causal association between the climate event (heat wave) and its direct health consequences. But still: were all heat waves in the recent past due to what we call climate change, i.e. a man-made trend in temperature and its related epiphenomena? Was the flood in Bangladesh in 1974 the first attributable to climate change, or the last not due to it? And what about the one in 1998? Clearly borders are fuzzy, and causal chains intricate. Uncertain inferences on the causal nature of events also concern the attribution to climate change of indirect health effects, such as infectious disease outbreaks, changes in food quality and availability, water salinization and the ensuing epidemic of hypertension (Xun et al. 2009). Even wars and conflicts (like in Darfur), mass migrations and effects on mental health have been attributed to climate change. In a survey conducted among children aged between 2 and 9 in Bangladesh, Durkin et al. (1993) found post-flood changes in behaviour and bedwetting. Children were reported to have ‘‘very aggressive behaviour’’ after floods, with a significant increase compared to the preflood situation. A qualitative study explored the experiences of female adolescents during the 1998 floods in Bangladesh, focusing on the implications of sociocultural norms related to notions of honour, shame, purity and pollution. A number of the girls were vulnerable to sexual and mental harassment through exposure to unfamiliar environment of flood shelters and relief camps. Common mental health disorders following climate-induced displacement include anxiety, depression, post-traumatic stress disorder, irritability, sleeplessness and suicide. Moreover, conflict situations that may arise among farmers in times of climate-induced natural disasters like droughts and floods need to be addressed. Is all of this attributable to what we call climate change? Where are the borders between the burden of events that would occur anyhow, particularly in low-income countries, even in the absence of climate change, and those attributable to the latter? How can we identify the chain of events that eventually explains the local outbreak? Again, fuzzy borders have to be acknowledged. It should be noted that the effects we have described are mainly occurring or Paolo Vineis is Chair of Environmental Epidemiology at Imperial College, London. His main interests are in the field of molecular epidemiology and gene–environment interactions. He also works on climate change with the Grantham Institute for Climate Change in London.