Physical and environmental determinants

This chapter describes physical and environmental determinants of the health of Australians, providing a background to the development of successful public health activity. Health determinants are the biomedical, genetic, behavioural, socio-economic and environmental factors that impact on health and wellbeing. These determinants can be influenced by interventions and by resources and systems (AIHW 2006). Many factors combine to affect the health of individuals and communities. People’s circumstances and the environment determine whether the population is healthy or not. Factors such as where people live, the state of their environment, genetics, their education level and income, and their relationships with friends and family, all are likely to impact on their health. The determinants of population health reflect the context of people’s lives; however, people are very unlikely to be able to control many of these determinants (WHO 2007). This chapter and Chapter 6 illustrate how various determinants can relate to, and influence other determinants, as well as health and wellbeing. We believe it is particularly important to provide an understanding of determinants and their relationship to health and illness in order to provide a structure in which a broader conceptualisation of health can be placed. Determinants of health do not exist in isolation from one another. More frequently they work together in a complex system. What is clear to anyone who works in public health is that many factors impact on the health and wellbeing of people. For example, in the next chapter we discuss factors such as living and working conditions, social support, ethnicity and class, income, housing, work stress and the impact of education on the length and quality of people’s lives. In 1974, the influential ‘Lalonde Report’ (Lalonde 1974) described key factors that impact on health status. These factors included lifestyle, environment, human biology and health services. Taking a population health approach builds on the Lalonde Report, and recognises that a range of factors, such as living and working conditions and the distribution of wealth in society, interact to determine the health status of a population. Tackling health determinants has great potential to reduce the burden of disease and promote the health of the general population. In summary, we understand very clearly now that health is determined by the complex interactions between individual characteristics, social and economic factors and physical environments; the entire range of factors that impact on health must be addressed if we are to make significant gains in population health, and focussing interventions on the health of the population or significant sub-populations can achieve important health gains. In 2007, the Australian Government included in the list of National Health Priority Areas the following health issues: cancer control, injury prevention and control, cardiovascular health, diabetes mellitus, mental health, asthma, and arthritis and musculoskeletal conditions. The National Health Priority Areas set the agenda for the Commonwealth, States and Territories, Local Governments and not-for-profit organisations to place attention on those areas considered to be the major foci for action. Many of these health issues are discussed in this chapter and the following chapter.

Biological and environmental determinants

- describe the complex web of determinants as part of broad causal pathways that affect health - identify and discuss the range of physical, biological and environmental determinants that impact on health - suggest why it is important to the practice of public health that you understand how determinants contribute to health - understand the complexity of health and illness and the multifaceted role of health determinants - relate determinants of health to public health activity and realise the need for multisectoral action and multiple approaches when working to improve health

Biological and environmental determinants

This chapter describes biological and environmental determinants of the health of Australians, providing a background to the development of successful public health activity. You will recall from the introduction to Section 2 that health determinants are the biomedical, genetic, behavioural, socioeconomic and environmental factors that impact on health and wellbeing. These determinants can be influenced by interventions and by resources and systems (Australian Institute of Health and Welfare (AIHW) AIHW 2012a). Many factors combine to affect the health of individuals and communities. People’s circumstances and the environment determine whether a population is healthy or not. Factors such as where people live, the state of their environment, genetics, their education level and income, and their relationships with friends and family are all likely to impact on their health. The determinants of population health reflect the context of people’s lives; however, people have limited control over many of these determinants (WHO 2007).

Biologging, Remotely-Sensed Oceanography and the Continuous Plankton Recorder Reveal the Environmental Determinants of a Seabird Wintering Hotspot

Marine environments are greatly affected by climate change, and understanding how this perturbation affects marine vertebrates is a major issue. In this context, it is essential to identify the environmental drivers of animal distribution. Here, we focused on the little auk (Alle alle), one of the world’s most numerous seabirds and a major component in Arctic food webs. Using a multidisciplinary approach, we show how little auks adopt specific migratory strategies and balance environmental constraints to optimize their energy budgets. Miniature electronic loggers indicate that after breeding, birds from East Greenland migrate .2000 km to overwinter in a restricted area off Newfoundland. Synoptic data available from the Continuous Plankton Recorder (CPR) indicate that this region harbours some of the highest densities of the copepod Calanus finmarchicus found in the North Atlantic during winter. Examination of large-scale climatic and oceanographic data suggests that little auks favour patches of high copepod abundance in areas where air temperature ranges from 0uC to 5uC. These results greatly advance our understanding of animal responses to extreme environmental constraints, and highlight that information on habitat preference is key to identifying critical areas for marine conservation.

Macrophyte community structure and species occurrence in relation to environmental determinants in the ephemeral aquatic habitats of Gavdos, Greece

The aims of this study were to explore the environmental factors that determine the distribution of plant communities in temporary rock pools and provide a quantitative analysis of vegetation-environment relationships for five study sites on the island of Gavdos, southwest of Crete, Greece. Data from 99 rock pools were collected and analysed using Two-Way Indicator Species Analysis (TWINSPAN), Detrended Correspondence Analysis (DCA) and Canonical Correspondence Analysis (CCA) to identify the principal communities and environmental gradients that are linked to community distribution. A total of 46 species belonging to 21 families were recorded within the study area. The dominant families were Labiatae, Gramineae and Compositae while therophytes and chamaephytes were the most frequent life forms. The samples were classified into six community types using TWINSPAN, which were also corroborated by CCA analysis. The principal gradients for vegetation distribution, identified by CCA, were associated with water storage and water retention ability, as expressed by pool perimeter and water depth. Generalised Additive Models (GAMs) were employed to identify responses of four dominant rock pool species to water depth. The resulting species response curves showed niche differentiation in the cases of Callitriche pulchra and Tillaea vaillantii and revealed competition between Zannichellia pedunculata and Chara vulgaris. The use of classification in combination with ordination techniques resulted in a good discrimination between plant communities. Generalised Additive Models are a powerful tool in investigating species response curves to environmental gradients. The methodology adopted can be employed for improving baseline information on plant community ecology and distribution in Mediterranean ephemeral pools.

Investigating Environmental Determinants of Diet, Physical Activity, and Overweight among Adults in Sao Paulo, Brazil

There is worldwide recognition that the burden of noncommunicable diseases (NCDs) and obesity-related health problems is rapidly increasing in low- and middle-income countries. Environmental determinants of obesity are likely to differ between countries, particularly in those undergoing rapid socioeconomic and nutrition transitions such as Brazil. This study aims to describe some built environment and local food environment variables and to explore their association with the overweight rate and diet and physical activity area-level aggregated indicators of adults living in the city of Sao Paulo, the largest city in Brazil. This formative study includes an ecological analysis of environmental factors associated with overweight across 31 submunicipalities of the city of Sao Paulo using statistical and spatial analyses. Average prevalence of overweight was 41.69% (95% confidence interval 38.74, 44.64), ranging from 27.14% to 60.75% across the submunicipalities. There was a wide geographical variation of both individual diet and physical activity, and indicators of food and built environments, favoring wealthier areas. After controlling for area socioeconomic status, there was a positive correlation between regular fruits and vegetables (FV) intake and density of FV specialized food markets (r = 0.497; p < 0.001), but no relationship between fast-food restaurant density and overweight prevalence was found. A negative association between overweight prevalence and density of parks and public sport facilities was seen (r = -0.527; p < 0.05). Understanding the relationship between local neighborhood environments and increasing rates of poor diet, physical activity, and obesity is essential in countries undergoing rapid economic and urban development, such as Brazil, in order to provide insights for policies to reduce increasing rates of NCDs and food access and health inequalities.

Do the Genetic or Environmental Determinants of Anxiety and Depression Change with Age? A Longitudinal Study of Australian Twins

Because the determinants of anxiety and depression in late adolescence and early adulthood may differ from those in later life, we investigated the temporal stability and magnitude of genetic and environmental correlates of symptoms of anxiety and depression across the life span. Data were collected from a population-based Australian sample of 4364 complete twin pairs and 777 singletons aged 20 to 96 years who were followed-up over three studies between 1980 and 1996. Each study contained the 14-item self-report DSSI/sAD scale which was used to measure recently experienced symptoms of anxiety and depression. Symptom scores were then divided and assigned to age intervals according to each subject's age at time of participation. We fitted genetic simplex models to take into account the longitudinal nature of the data. For male anxiety and depression, the best fitting simplex models comprised a single genetic innovation at age 20 which was transmitted, and explained genetic variation in anxiety and depression at ages 30, 40, 50 and 60. Most of the lifetime genetic variation in female anxiety and depression could also be explained by innovations at age 20 which were transmitted to all other ages; however, there were also smaller age-dependent genetic innovations at 30 for anxiety and at 40 and 70 for depression. Although the genetic determinants of anxiety and depression appear relatively stable across the life-span for males and females, there is some evidence to support additional mid-life and late age gene action in females for depression. The fact that mid-life onset for anxiety occurs one decade before depression is also consistent with a causal relationship (anxiety leading to depression) between these conditions. These findings have significance for large scale depression prevention projects.

Social and environmental determinants, household food insecurity

Food security is defined as a situation that exists when “all people, at all times, have physical and economic access to sufficient, safe and nutritious food to maintain a healthy and active life. It is a multilevel concept, which includes four main dimensions: availability related to food supply; accessibility in order to ensure the physical and economic access to food; adequacy to meet nutritional needs in quantity and quality while respecting individual food preferences and cultural issues (utilization); and, lastly, stability of the guarantee of food security over time. According to the food security definition, it is abroad concept where all these dimensions are largely affected by a considerable number of factors related to: public policies of different sectors, food production/industry/distribution food systems, marketing and advertising of food, social support networks and individual determinants related to food choice behaviour.

Inequities in energy-balance related behaviours and family environmental determinants in European children: baseline results of the prospective EPHE evaluation study

BACKGROUND:Tackling inequalities in overweight, obesity and related determinants has become a top priority for the European research and policy agendas. Although it has been established that such inequalities accumulate from early childhood onward, they have not been studied extensively in children. The current article discusses the results of an explorative analysis for the identification of inequalities in behaviours and their determinants between groups with high and low socio-economic status. METHODS: This study is part of the Epode for the Promotion of Health Equity (EPHE) evaluation study, the overall aim of which is to assess the impact and sustainability of EPODE methodology to diminish inequalities in childhood obesity and overweight. Seven community-based programmes from different European countries (Belgium, Bulgaria, France, Greece, Portugal, Romania, The Netherlands) participate in the EPHE study. In each of the communities, children aged 6-8 years participated, resulting in a total sample of 1266 children and their families. A parental self-administrated questionnaire was disseminated in order to assess the socio-economic status of the household, selected energy balance-related behaviours (1. fruit and vegetable consumption; 2. soft drink/ fruit juices and water consumption; 3. screen time and 4. sleep duration) of the children and associated family environmental determinants. The Mann-Whitney U test and Pearson's chi-square test were used to test differences between the low and high education groups. The country-specific median was chosen as the cut-off point to determine the educational level, given the different average educational level in every country. RESULTS: Children with mothers of relatively high educational level consumed fruits and vegetables more frequently than their peers of low socio-economic status. The latter group of children had a higher intake of fruit juices and/or soft drinks and had higher screen time. Parental rules and home availability were consistently different between the two socio-economic groups in our study in all countries. However we did not find a common pattern for all behaviours and the variability across the countries was large. CONCLUSIONS: Our findings are indicative of socio-economic inequalities in our samples, although the variability across the countries was large. The effectiveness of interventions aimed at chancing parental rules and behaviour on health inequalities should be studied.