INDICADORES ENERGÉTICOS

The need for estimating health impacts of major transport initiatives has been acknowledged by the policy makers in most developed countries (European countries, USA, Canada, New Zealand, Australia, etc.) for decision making in transportation. Though it is well known that HIA is an instrument for evidence-based policymaking, the question that remains unanswered is how hard the evidence can be with regard to the consequences of strategic policy proposals. Do we have to conclude that certain transport policies or strategies should not be assessed for health consequences, or that they should be assessed only in a ‘‘mini’’ HIA (Broeder et al. 2003)? In this context, economic analysis can support various options and policy perspectives related to specific activity sectors (for example, different transport modes or transport investment programs) and integrate economic and social activities with health concerns for a group of an identified population.

HIA is usually conducted for policy areas other than health services – such as transport, housing or social inequalities, where health impacts have tended to be neglected in policy development. There are several ways in which evidence on health and its determinants can be related to policies in the transport sector. HIA plays a role in the political decision making process using scientific findings, most of which is epidemiological and toxicological evidence. However, this evidence cannot establish causal links between policy initiatives and health outcomes as it ignores the changes in behavioural patterns exhibited by an individual or a community, driven by economic or lifestyle changes. This thesis argues that an economic approach has the ability to address this missing link as economic analysis can investigate and explain

the factors driving changes in the group and individual behaviour in a given economic set up. Additionally, reduction in health inequality in the target population group through policy initiatives is an important element of HIA. In this context, economic analysis can quantify the policy induced changes in population health inequality to assess the intended policy effectiveness. In addition, a quantitative economic analysis can generate and analyse future health impact outcomes in dollar terms of a specific policy initiative.

For example, in the context of applying HIA in transport policies, most public programs are expected to have health consequences. Since health hazard identification and health risk management are the salient features of the HIA (Lerer 1999), transport policies are now recognised as important determinants of public health and application of HIA in the transport policy field has become a popular practice in the last decade. In fact, the existing transport network generates significant health costs in terms of transport-related accidents, air pollution, noise, climate change impacts and physical inactivity (Harris-Roxas and Harris 2013, Bhatia and Setu 2011, WHO 2008) as well as obesity.

However, according to WHO’s 2010 Global Burden Disease Study (WHO GBD), across the world, the major share of adverse health effects were born by the low income populations. The WHO study estimated that diseases associated with poverty accounted for 45 per cent of the disease burden in the poorest countries. Infectious diseases of poverty (IDoP) were found to affect the poorest populations in the world disproportionately, decreasing their productivity due to long-term illness, disability, and social stigma, consequently adding to a cycle of poverty (Bhutta et al. 2014). In developed countries, obesity was found to be negatively associated with household income level (Kim & Leigh 2010, McLaren 2007). A study, based on a

large USA national study, reported that obesity (measured by annual body mass index (or BMI), an indicator of excess body fat) was higher among adults in the lowest income group and the lowest education group compared to those in the highest income and education groups during the period from 1986 and 2002 (Truong & Sturm 2005). Another study based on Australian data showed that both men and women in the lowest income group had significantly higher rates of obesity in relation to those in the highest income group (Burns 2004). These findings have raised a serious policy concern globally on health equity aspects of transport investments and transport policy options.

However, a study using US national data investigated the disparities between socio-economic status (SES) based on educational level and obesity over time (1971 to 2000) and found weak relationships between higher BMI and lower SES as well as between greater obesity and lower SES (Zhang & Wang 2004). The weak association between low income and obesity was observed across most gender and ethnic groups, particularly among women, despite a significant rise in overall obesity incidence. Moreover, the study observed the highest growth rate of obesity over time in the high-SES group across gender-racial categories.

In addition to poverty, obesity is also affected by individuals’ lifestyle, for example food habits, less physical activity and more time spent in auto vehicles. In fact, obesity showed a positively link with motor vehicle driving (Bell et al. 2002, Parra et al. 2009, Hess & Russell 2012, Sugiyama et al. 2013). To be specific, the link between time spent in cars and higher obesity rates was supported by studies that reported a higher incidence of overweight and obesity in auto-oriented neighbourhoods with more users of motor vehicles as compared to pedestrian- oriented neighbourhoods (Coogan et al. 2011, Frank et al 2007). This finding was

supported by a systematic review that identified eight out of ten studies provided evidence suggesting a positive relationship between driving time and distance and risk of obesity in an adult population (McCormack & Virk 2014).

Overall, though research supported higher prevalence of obesity among lower income households, a significant volume of literature highlighted that obesity was not entirely “a poor person’s disease”.

Given this wide range of adverse health effects, it becomes necessary to have a Health Impact Assessment of transport policies and transport investments, which can ensure that the maximum health benefits are leveraged for the community with improvements in the transport system.

This research has therefore developed and estimated an economic model which is incorporated within the HIA framework. The significance of this study lies in addressing the research inadequacies discussed in previous works in the field. Another significance of this study is its ability to expand the current knowledge-base of policy makers on the long run behaviour of observed health determinants covering a range of economic, socio-economic, environmental and lifestyle factors. Moreover, using the health impacts analysis developed in this thesis, policy makers will be able to identify major public investments programs, both transport and non-transport, beneficial to public health as a whole and easily estimate a set of monetary health benefits. This information can be also used for budget analysis and various major transport and non-transport investment program reviews (infrastructure program review) purposes in the decision making.

However, though evidence suggested a strong association of obesity with driving behaviour and thus the important health benefits of physical activity resulting from active transportation investments, the economic model developed in this thesis

could not include physical activity as a determinant of population health status due to the lack of annual time series data for the reference 50 year period.