Obesity Review Paper 2018 Part A
Preliminary Author: Bonnie Rosen - Symplan Consulting
Primary Authors and Academic Review: Dr Penny Love, Dr Kristy Bolton, Ms Jill Whelan, Dr Erin Smith - World Health Organisation Collaborating Centre for Obesity Prevention, Deakin University
Obesity in Australia has more than doubled in the past 20 years, and high body mass index (BMI) is the greatest contributor to the burden of the diseases that can ensue.
Impacts & Outcomes
Health outcomes of obesity
Serious health consequences can result from being overweight or obese. These include type 2 diabetes, hypertension, cardiovascular disease, stroke, certain cancers, risks to pregnant women, loss of mental health and wellbeing, quality of life and premature mortality. Health outcomes of obesity can include the development of non-communicable diseases (NCDs), poor mental health and wellbeing. Other health outcomes include poor oral health and sleep breathing problems (sleep apnoea).
High body mass index is the greatest contributor to the burden of disease, accounting for 55% of its burden (AIHW, 2012). Overweight and obesity contribute to four of the seven diseases included in the national health priority areas (diabetes, cancer, cardiovascular health, musculoskeletal disease) which together represent 64.2% of total expenditure on national health priority areas (AIHW, 2012).
Non-communicable diseases (NCDs)
Non-communicable diseases (NCDs) are chronic diseases of long duration and generally slow progression (WHO, 2013). There are four main types of NCDs: cardiovascular diseases (like heart attacks and stroke); cancers; chronic respiratory diseases (such as chronic obstructed pulmonary disease and asthma) and diabetes (WHO, 2013). These chronic diseases are caused by multiple factors in a person’s genetics, lifestyle and environment. The Australian Health Survey (2011-2012) highlighted that one million Australians suffered from diabetes mellitus (4.6% population, however only 3.9% with type 2 diabetes); 1.1 million from heart disease (5% population); 2.3 million from hypertensive disease (10.6% population) and 183,400 from kidney disease (0.9% population) (ABS, 2013).
Risk factors for NCDs include tobacco smoking, alcohol consumption, poor diet and not being physically active (WHO, 2013). As excess weight increases, so does the risk of chronic disease and mortality. Being overweight, and in particular, being obese increases the risk of developing a number of diseases and conditions such as coronary heart disease, increased blood pressure, increased blood cholesterol, type 2 diabetes, chronic kidney disease, certain cancers, musculoskeletal conditions, sleep apnoea and mental health problems and disorders (AIHW, 2012). Losing weight can reduce the incidence and severity of the majority of these conditions (AIHW, 2012).
People with chronic conditions such as heart disease, diabetes, arthritis, cancer and kidney disease, all of which are associated with obesity, are twice as likely to report that they experienced toothache, discomfort with their oral appearance or had avoided some foods due to oral problems often or very often. They are also more likely to experience oro-facial pain and have inadequate dentition. Similarly, people with chronic disease are less likely to report that their oral health was good, very good or excellent (74.7% compared to 86.9% respectively). Approximately 11% of people with a chronic condition expressed that oral health impacted on their general health. Oral conditions include toothache, discomfort with oral appearance, avoiding certain foods and oro-facial pain. They are also more likely to have inadequate dentition which makes it difficult to chew food. People with diabetes are less likely than people with any other chronic condition to visit the dentist (AIHW, 2012).
Obesity also poses significant risk to pregnant women. During pregnancy obesity can cause pre-eclampsia, gestational diabetes, abnormalities of the baby’s growth, development and general health and sleep apnoea. Furthermore, obesity can delay the progress of labour and delivery, because difficulties in monitoring the baby’s heart result in difficulties administering pain relief and increase the risks of complications with an emergency caesarean. After the birth, obesity can increase the risk of infection and blood clots and can cause postnatal depression (The Royal Women's Hospital, 2014).
Mental health and wellbeing
Overweight and obesity also impact mental health and wellbeing. People who are overweight or obese, particularly children, may experience discrimination and are prone to depression and problems with cognition. This may lead to productivity losses across a range of sectors. Evidence suggests diet quality contributes to some mental health issues (Jacka, Mykletun, & Berk, 2012) and poor diet is specifically implicated in increased risk of depression (Jacka & Berk, 2007). Greater fruit and vegetable consumption (a marker of diet quality) has been demonstrated to be associated with lower odds of depression, psychological distress, self-reported mood and anxiety disorders and poor perceived mental health in a study of Canadians (McMartin, FN, & Colman, 2013). Recent longitudinal studies in adults have supported cross-sectional studies that there is a bi-directional link between depression and obesity (Luppino, et al., 2010).
Individuals with obesity had a 55% increased risk of developing depression, and having depression increased the risk of developing obesity by 58% (Luppino, et al., 2010). This association is being researched further to understand the complex nature of the relationship. This information, along with the large impact on the length and quality of people’s lives, and exorbitant societal costs, prompted the Canadian Obesity Network, World Obesity (formerly the International Association for the Study of Obesity) and the Centre for Mental Health and Addiction to develop the Toronto Charter on Obesity and Mental Health to decrease the negative consequences of obesity and mental health using a range of strategies to focus on enabling change through policy, the role of health professionals, and expanding and disseminating knowledge (Canadian Obesity Network, 2012).
Other health conditions
Obesity is associated with compromised productivity in the workplace. Productivity losses amongst truck drivers who are overweight or obese are amongst the highest of any occupation. Loss of productivity in the transportation industry can have repercussions for productivity across the whole of the economy. In particular, sleep apnoea is associated with narcolepsy, i.e. falling asleep on the job, potentially causing serious injuries and fatalities in the broader community (Funder, 2011).
Obesity can result in sleep breathing abnormalities due to the increased mass (adipose tissue) loading the chest wall and abdomen which affects respiration rates (Kopelman, 2000). Irregular respiration and occasional apnoeic episodes disturb sleep patterns (Kopelman, 2000). In severe cases, these sleep breathing abnormalities can result in cardiac arrhythmias (Kopelman, 2000).
Recently, evidence has supported the notion that inadequate sleep (<7 hours) may be an independent risk factor for overweight and obesity (Jean-Louis, et al., 2014). A study using US National Health Interview Survey data (1977-2009) revealed the prevalence of overweight and obesity; and very short sleep (<5 hours) and short sleep (5-6 hours) to increase over time (Jean-Louis, et al., 2014). In comparison to 7-8 hour sleepers, the odds of being overweight increased with very short and short sleep, and the odds of being obese were increased with very short, short and long sleep (Jean-Louis, et al., 2014). The obesity-sleep relationship is not entirely understood however sleep duration should be considered in public health campaigns (Jean-Louis, et al., 2014).
Overweight and obesity contribute to four of the seven diseases included in the national health priority areas, namely, diabetes, cancer, cardiovascular health, musculoskeletal disease which together represent 64.2% of total expenditure on national health priority areas (AIHW, 2012). Health problems related to excess weight impose substantial economic burdens on individuals, families and communities. High body mass index is the greatest contributor to the burden of disease, accounting for 55% of its burden (AIHW, 2012). The total direct cost for overweight and obesity in 2005 was $21 billion ($6.5 billion for overweight and $14.5 billion for obesity). The same study estimated indirect costs of $35.6 billion per year, resulting in an overall total annual cost of $56.6 billion (Colagiuri, et al., 2010). Obese people use on average ten more days of sick leave a year (Funder, 2011).
In 2004-05, expenditure on diabetes represented 4.3% of expenditure on all national health priority area conditions (AIHW, 2012). Given that diabetes is also a cause of other diseases such as cardiovascular and renal diseases, total allocated health expenditure attributable to diabetes is greater than the $1.0 billion in direct allocated expenditure (AIHW, 2012). Between 2000-01 and 2004-05, expenditure on endocrine, nutritional and metabolic diseases increased by 32%, and expenditure on diabetes increased by 26% (AIHW, 2012).
The prevalence of obesity in Australia has more than doubled in the past 20 years. The direct costs associated with overweight and obesity in Australia exceed $21 billion per annum (Colagiuri, et al., 2010). If weight gains continue at current levels, by 2025 close to 80% of all Australian adults and a third of all children will be overweight or obese (Department of Human Services, 2008).
Global estimates from 2010 suggested that approximately one billion adults were overweight (BMI 25-29.9kg/m2) and a further 475 million were obese (IOTF, 2014). Additionally, in 2011 it was estimated that 40 million children under five years old were overweight (WHO, 2013). The prevalence of overweight and obesity among Australians has been steadily increasing for the past 30 years (AIHW, 2012). Australia currently has the third highest rate of obesity overall in the Organisation for Economic Co-operation and Development (OECD) countries, behind Mexico and the United States of America (OECD, 2013). In 2011–12, 62.8% of Australian adults were classified as overweight or obese (35.3% overweight, 27.5% obese); and 25.1% of children aged 2–17 were overweight or obese (18.2% overweight, 6.9% obese) (ABS, 2013)).
Categorisation of individuals into overweight or obese categories is conducted using body mass index (BMI), which is defined as weight in kilograms divided by the square of the height in meters (kg/m2) (WHO, 2013). Individuals with a BMI over 25kg/m2 are categorised as overweight and those with a BMI of over 30kg/m2 are categorised as obese (WHO, 2013).
Overweight and obesity in the Australian context
The continuing rise of overweight and obesity, resulting from poor diet, excessive energy intakes and low levels of physical activity, is one of the greatest public health challenges facing Australia. Due to the burden of disease that obesity places on individuals, their families and the community, halting and reversing the increase in obesity in both adults and children has become one of Australia’s key health priorities (AIHW, 2012).
In 2011–12, 62.8% of Australian adults were classified as overweight or obese (35.3% overweight, 27.5% obese) and 25.1% of children aged two–17 were overweight or obese (18.2% overweight, 6.9% obese) (ABS, 2013). It is predicted that there will be continued increases in overweight and obesity levels across all age groups during the next decade in Australia, increasing to 66% (NHMRC, 2013).
In 2012–13, two-thirds (65.6%) of Aboriginal and Torres Strait Islander people aged 15 years and over were categorised by BMI with 28.6% overweight and 37.0% obese (ABS, 2013). Furthermore, almost one-third (30.4%) of Aboriginal and Torres Strait Islander children aged two–14 years were overweight or obese (ABS, 2013). When compared to non- Aboriginal and Torres Strait Islander people, in almost every age group obesity rates for Aboriginal and Torres Strait Islander females and males were significantly higher (ABS, 2013).
In 2011-12, data from the Australian Health Survey identified that adults living in inner regional, outer regional and remote areas of Australia were more likely to be overweight or obese compared to adults living in major cities, regardless of gender (ABS, 2013). In Australia, basic nutritious foods in rural and remote areas can cost up to 30% more than in capital cities and be less available. South Australia has the highest proportion of overweight and obesity in Australia, and Victoria the lowest proportion (ABS, 2013).
Overweight and obesity in the Victorian context
In 2010, 62.6% of Victorians were overweight or obese with 38.1% being classified as overweight and 24.5% classified as obese. This equates to approximately 2.4 million people aged 18-75 (Department of Health, 2012). Results of a 2012-2013 survey of Aboriginal and Torres Strait Islander people over the age of 15 years estimated that 14,700 Victorian Aboriginal and Torres Strait Islander people were overweight or obese (7,100 overweight, 7,600 obese) (ABS, 2013).
According to the 2011 Census, the Victorian Aboriginal and Torres Strait Islander population was 37,988 persons, therefore the proportion of overweight and obese is high. The prevalence of overweight and obesity and diabetes is higher in Victorians living in rural areas than it is amongst Victorians living in urban areas (Department of Health, 2012). Additionally, in 2009, perinatal BMI was collected from 63,394 Victorian women revealing 24% women to be overweight, and 18% obese (Consultative Council on Obstetric and Paediatric Mortality and Morbidity, 2012).
Frameworks can be useful in describing the various factors which influence the development of obesity. There are various frameworks and models available, such as the social determinants of health (WHO, 2003); within a local government context (Victoria, Australia) using the Municipal Public Health Plan (Department of Health, 2001); or within a global systems approach using the Foresight Model (Government Office for Science, 2007). The social determinants of health approach examines upstream and downstream influencing factors on health (Braveman, Egerter, & Williams, 2011). The Municipal Public Health Plan (MPHP) aims to provide a framework to systematically address individual, organisational, community, social, political, economic and environmental factors involved in health; particularly through personal, social and environmental action (Department of Health, 2001).
Four key environmental dimensions are focused on – built/physical environment (e.g. urban planning, transport); social environment (e.g. demographics, ethnicity); economic environment (e.g policy, industrial development) and natural environment (e.g. climate, geography) (Department of Health, 2001). Given the strong international recognition of the Foresight Model, and its consideration of the social determinants of health (SDoH) and MPHP domains, this will be the framework focussed upon in this report. The following matrix outlines the relevant links between these three models.
The Foresight Model
The Foresight Model was designed within the Government Office for Science in conjunction with over 300 experts and stakeholders to determine how best society might tackle obesity in the UK over the next 40 years in a sustainable manner (Government Office for Science, 2007). A systems mapping approach allowed an understanding of the biological and social complexity of obesity. The map produced was highly complex, revealing that it will not be simple to tackle the issue of obesity. Overall, four key determinants driving energy balance were established.
These key determinants were physiological factors (e.g. appetite control in the brain), eating habits, activity levels (e.g. physical activity) and psychosocial influences (which influence lifestyle choice). The creators suggested that a positive feedback cycle locks individuals into a pattern of positive energy balance (energy intake exceeds energy expenditure) and combined with the four determinants the result is excess weight gain (Government Office for Science, 2007).
The map’s core was energy balance which was surrounded by 108 variables which might influence energy balance. These variables are clustered into seven themes: biology/physiology; individual activity; physical activity environment; food consumption; food production; individual psychology; social psychology (Government Office for Science, 2007). There are >300 solid or dashed lines representing relationships between variables (positive and negative influences) and some connections cause a feedback look between variables (Finegood, Merth, & Rutter, 2010).
The Foresight Model of obesity is extremely complex, with many factors contributing to the development of obesity. However, this map allows for the identification of many potential pathways which result in obesity and therefore helps to identify points at which it might be best to intervene.
Thematic clusters within the Foresight obesity map
This Foresight Model theme includes biologic variables such as genetic predisposition to obesity, satiety levels, resting metabolic rate and maintenance of appropriate body composition (Government Office for Science, 2007). Additionally, genetic/inheritable factors can affect gastrointestinal physiology, stomach capacity and emptying and inherited feelings of hunger which subsequently may affect meal size (de Castro, 2004).
Susceptibility genes which are inherited can determine who will become obese in any environmental circumstance (Kopelman, 2000). Twin studies (monozygotic (identical) versus dizygotic (non-identical) and adoption and family studies have provided evidence of the important roles genes play in the development of body composition. Differences in racial/ethnic groups also supports evidence for a genetic component of obesity (Xia & Grant, 2013).
Evidence is also emerging regarding the importance of intrauterine exposures such as maternal obesity, maternal diet and excess gestational weight gain may lead to increased risk of developing obesity in offspring (Poston, 2012). Additionally, foetal under nutrition during intrauterine development may influence the development of obesity, hypertension and type 2 diabetes later in life, regardless of inherited genetic factors (Kopelman, 2000).
In a very small proportion of individuals, endocrine and hypothalamic disorders may contribute to obesity (Jebb, 1997). Candidate genes associated with the development of obesity (e.g. leptin) have been identified to be involved in regulation of appetite and thermogenesis (Kopelman, 2000), however these genetic defects cannot be responsible for the epidemic proportions of obesity observed today.
This theme includes the types and level of physical activity (e.g. recreational, domestic, occupational, transport activity), parental modelling of physical activity and learned activity patterns (Government Office for Science, 2007). Over the last 50 years, daily energy expenditure has decreased due to fewer jobs requiring manual work; increased labour-saving technology (at home, work and retail environments), changes in work and shopping patterns which have resulted in higher dependency on motorised transport, increased self-sufficiency at home (entertainment, food storage and preparation, climate control) and reductions in active transport such as walking and cycling (Fox & Hillsdon, 2007). Of concern is the greater time spent in sedentary pursuits, particularly sitting, due to higher disposable income for consumer goods such as TVs, stereos, computers, game stations (Fox & Hillsdon, 2007).
A recent systematic review examining physical activity interventions suggested that overall exercise has a positive effect on body weight in overweight and obese individuals, particularly when the intervention included a diet component. The exercise also improved cardiovascular risk factors such as blood lipid profiles and blood pressure even when no weight loss occurred (Shaw, Gennat, O'Rourke, & Del Mar, 2009). Physical activity can also improve quality of life, particularly for older people who benefit from social interaction and engagement with the community whilst undertaking the activity (Fox & Hillsdon, 2007).
Of high importance is embedding physical activity early in life. Physical inactivity in adolescence has been found to strongly and independently predict overall and abdominal obesity in young adulthood, resulting in the development of a vicious circle of further obesity, physical inactivity and low energy expenditure in life (Pietilainen, et al., 2008).
Physical activity environment
This theme includes variables which may be enablers or barriers to conducting physical activity. These may include the influence of the environment on an individual’s behaviour, costs, perceived safety involved and cultural values (Government Office for Science, 2007). Environmental influences are important as they can increase energy intake and/or decrease energy expenditure (Jebb, 1997).
Our current environment discourages physical activity with advances in technology and transportation reducing the need to be active daily. Adults and children spend an increased about of time in appealing sedentary pursuits such as television, electronic games and computers. Creative ways will need to be designed to oppose attractive sedentary pursuits. The participation of parents for children can increase the likelihood of children participating and the activity being fun.
Environments need to be more conducive to physical activity, and schools should encourage children to engage in daily physical activity given the tracking of health behaviours over the lifespan (Hill & Peters, 1998). Creating active transport policies in conjunction with a supportive built environment have been suggested to not only be beneficial for health (e.g. mortality, obesity, chronic disease, mental health), but also advantageous to the environment in the long term (e.g. decrease air pollution, greenhouse gases, noise, traffic hazards) (de Nazelle, et al., 2011). Evidence suggests that environments that encourage walking are associated with more active transport and less driving (de Nazelle, et al., 2011).
The family home environment is important in developing children’s health behaviours and consequently is important in influencing their likelihood of developing obesity (Hendrie, Coveney, & Cox, 2011). Children can learn through behaviour imitation, parental support, reinforcement of favourable behaviours and from family rules and restrictions (Hendrie, Coveney, & Cox, 2011). In children, the family activity home environment has been found to be positively associated with physical activity (e.g. a more supportive home had higher levels of physical activity); and negatively associated with screen time (e.g. less screen time in a supportive home) (Hendrie, Coveney, & Cox, 2011).
Geographic location may be an important enabler for participation in physical activity (Veitch, Salmon, Ball, Crawford, & Timperio, 2013). An audit of Victorian parks (urban vs. rural) found that urban parks had better scores for access, lighting and safety, suitability of paths for walking and cycling and play equipment that was diverse. Rural parks were scored more aesthetically attractive (Veitch, Salmon, Ball, Crawford, & Timperio, 2013). The scores may help to explain why rural park users were less physically active than urban park users (Veitch, Salmon, Ball, Crawford, & Timperio, 2013). Furthermore, examining the association between ‘greenness’ (e.g. presence and condition of green vegetation) and weight status revealed higher levels and greater variation of neighbourhood greenness to be associated with lower odds of obesity in Australian adults (Pereira, et al., 2013). This could be due to higher levels of physical activity due to the protective effect of living in a leafy green neighbourhood (Pereira, et al., 2013). In an elderly population, the built environment (assessed by a neighbourhood walkability score) was associated with increased walking for exercise (Berke, Koepsell, Moudon, Hoskins, & Larson, 2007).
This includes variables such as the characteristics of food products (abundance, variety, nutritional quality, energy density, portion size) (Government Office for Science, 2007). The current environment promotes opportunities to consume large quantities of food by providing highly palatable, inexpensive foods in large portion sizes everywhere (Hill & Peters, 1998). In a meta-analysis analysing physical activity interventions, diet alone was significantly more effective at weight loss than exercise alone (Shaw, Gennat, O'Rourke, & Del Mar, 2009), indicating just how important diet modification is.
This includes the drivers of the food production industry (market price, ingredient cost, production efficiency, profitability, social and economic societal situation, societal pressure to consume) (Government Office for Science, 2007). Our current environment contains an unlimited supply of convenient, relatively inexpensive, highly palatable, energy-dense foods, which promotes high energy intake (Hill & Peters, 1998). The global food market is highly complex, and given the future pressures such as global population growth, economic growth in countries, climate change, a limited supply of natural resources and a rise in poor nutrition resulting in obesity and chronic disease; food industries have to develop plans to sustainable and resilient long-term (DAFF, 2011).
This includes psychological attributes and the drive for foods, such as self-esteem, stress, food literacy, parenting style (Government Office for Science, 2007). The degree in which humans can attempt to control their food intake differs amongst individuals, due to psychological factors. Physiological regulatory systems can be over-ridden by voluntary or cognitive factors (Jebb, 1997).
Hedonic pathways can drive the consumption of rewarding foods which seek pleasure. These foods are the palatable foods and often contain sugar, fat and salt which subsequently reinforce individuals to consume more to their taste. This can lead to an addictive-like cycle (Swencionis & Rendell, 2012).
Stress, and the individual’s capacity to control stress, can contribute to the development of obesity with suggestions that stress can influence the increased consumption of high fat foods (Jebb, 1997), high sugar foods and ingest more calories without having an increased appetite (Swencionis & Rendell, 2012).
There are suggestions that restrained eating can also contribute to the development of obesity whereby restrained eaters may have increased susceptibility to the availability of highly palatable foods, which then stimulates excess food consumption (Jebb, 1997).
A recent review highlights the potential negative psychological consequences of being overweight and obese in adolescents which include low self-esteem, depression, disordered eating behaviours (e.g. dieting, fasting, binging, laxatives, diuretics), body dissatisfaction, weight stigmatisation and weight-based teasing (Harriger & Thompson, 2012).
This includes variables whereby society can have an influence (media, education, social desirability/acceptability, culture, peer pressure) (Government Office for Science, 2007).
The human race is social and therefore affected by social influences. The social facilitation of food intake suggests that individuals will eat larger quantities of food if dining with other people present rather than alone (de Castro, 2004). Internal hunger cues are suggested to also be part mediated by external cues as the larger amounts and increased varieties of food also results in individuals eating more (Swencionis & Rendell, 2012)).
Media and advertising has a strong influence on society. The internet has changed the way companies market products and there is a trend to step away from television commercials as the most influential marketing vehicle (Jain, 2010). New marketing strategies include product placement within television and movies, viral marketing (e.g. chain email), guerrilla marketing (e.g. free giveaways), advertainment and advergaming (e.g. online games which include advertising)and neuromarketing research methods (which utilise brain imaging to draw upon emotions) (Jain, 2010). Mobile phones, music players, social networking sites and social connectivity allow continuous exposure to advertising in many different forms (Jain, 2010).
From a young age it is thought that individuals learn what constitutes an idea or attractive body size via sociocultural exposure. Different racial and ethnic groups perceive body size in different ways. In some Pacific Island communities, the church plays a central role in influencing attitudes to giving and eating food and places a high value on it since many individuals cannot afford monetary donations. The celebration of food is embedded into Fijian and Tongan culture, with communal gatherings with a wealth of traditional food and drink for religious, political, economic and social activities. Television, magazines and advertisements promote an ideal body image (Bonsergent, et al., 2012). This combined with the social stigma attached to obesity and a “fat phobia” has been suggested to influence individuals daily regarding their body image, with the suggestion that girls are more aware of their bodies compared to boys (Bonsergent, et al., 2012).
Risk & Protective Factors
There are many risk factors associated with the development of overweight and obesity. Main risk factors include low fruit and vegetable intake, low levels of physical activity, increased levels of sedentary behaviour and low breastfeeding rates.
Fruit and vegetable consumption
The food we eat plays a significant role in our health and wellbeing. It contributes to the healthy development of infants and children and the reduction of chronic disease and premature death amongst adults. Poor diet is a risk factor associated with chronic diseases such as cardiovascular disease, diabetes and some cancers, all of which are major causes of death and disability in Australia (AIHW, 2012). Inadequate vegetable and fruit intake is responsible for 30% of coronary heart disease, 20% of gastrointestinal cancer and 14% of stroke (VicHealth, 2012)).
Eating a balanced and varied diet is essential for good health. This involves eating fruits and vegetables and reduced fat products to provide the body with sufficient fibre, minerals and vitamins (VicHealth, 2012)). Poor diet involves the consumption of large intakes of energy-dense foods with high saturated fat, sugar and/or salt content and low intakes of nutrient-dense foods such as vegetables, fruit and wholegrain cereals (AIHW, 2012). Diets high in fat are associated with increased risk of obesity (AIHW, 2012). A substantial amount of evidence has suggested a link between sugar-sweetened beverages and an increased weight gain and risk of obesity (Hu, 2013)). Sugar-sweetened beverages include soft drinks, fruit drinks, energy and vitamin water drinks containing sugar (Hu, 2013)); and in the Australian context, cordial. Sugar-sweetened beverages can be referred to as offering ‘empty calories’ as whilst they provide energy, they provide almost no nutritional value (Hu, 2013)). There is a suggestion that decreasing sugar-sweetened beverages will reduce obesity risk and the risk of developing other obesity-related consequences such as type 2 diabetes (Hu, 2013)). The World Health Organisation is currently updating its guidelines on sugar intake for adults and children. The Australian Dietary Guideline 3c states to limit intake of foods and drinks containing added sugars which include confectionary, sugar-sweetened beverages (soft drink, cordial, fruit drinks, vitamin waters, energy drinks and sports drinks) with supporting evidence of an association between these items and type 2 diabetes, excess weight, dental caries and reduced bone strength (NHMRC, 2013)).
The Australian Dietary Guidelines for fruit and vegetable consumption are presented in Table 2. Examples of a serve of vegetables are: half a cup of cooked green or orange vegetables, beans, peas or lentils, one cup of green leafy or raw salad vegetables, half of a medium potato. Examples of a serve of fruit include one medium apple/banana/orange/pear, two small apricots/plums, one cup diced/canned fruit (NHMRC, 2013)).
Table 2- Minimum recommended serves of vegetable and fruit per day, by age and gender (adapted) (NHMRC, 2013))
Family meal times
Additionally, family meal times appears to be a protective factor for the development of overweight, unhealthy and disordered eating (Hammons & Fiese, 2011)). A meta-analysis of studies examining shared family meals and their frequency in relation to the nutritional status of children and adolescents revealed that children and adolescents who shared three or more family meals a week were more likely to be in the normal weight range, with healthier diets and eating patterns, and less likely to adopt disordered eating habits (Hammons & Fiese, 2011)).
Physical activity is defined as any bodily movement produced by skeletal muscles that requires energy expenditure (WHO, n.d.). Physical activity time is calculated as the sum of the time spent walking or performing moderate physical activity per week, plus double the time spent in vigorous physical activity. In 2010, the proportion of Victorians undertaking sufficient physical activity to meet national guidelines was 69% (Department of Health, 2012).
Inadequate physical activity may result from sedentary lifestyles associated with prolonged and uninterrupted periods of sitting or reclining. Sedentary behaviour is the overall sitting time which is eight or more hours per day (Department of Health, 2012). Sedentary lifestyles are associated with time spent sitting e.g. while watching TV or at the computer. Most people spend between three and six hours a day sitting during their leisure time, over and above sitting during their working day (AIHW, 2012). At present, over a quarter of Australians (26%) report sitting for eight or more hours during a typical day (Australian Government, 2009). Prolonged sitting, which differs from inadequate physical activity, can lead to a number of health issues such as musculoskeletal disorders, cardiovascular disease, diabetes and eye strain (Healy, et al., 2012). Workplace sitting has been associated with an increased risk of mental disorders and depression including job stress, depression and fatigue (Healy, et al., 2012). In addition, the use of email and internal telephone systems are likely to have reduced the amount of time employees have in face-to-face contact with each other, potentially affecting social wellbeing (Healy, et al., 2012).
Physical inactivity is associated with an increased risk of ill health and death, particularly for diseases such as cardiovascular disease, type 2 diabetes and chronic kidney disease. In addition, it is associated with other risk factors such as overweight or obesity, increased blood pressure and increased blood cholesterol (AIHW, 2012). Physical inactivity has been identified as the fourth leading risk factor for global mortality causing an estimated 3.2 million deaths globally (WHO, n.d.), and estimated to cost Australia more than $719 million a year, contributing to 6.6% per the burden of disease and injury in Australia, rating second after tobacco smoking, 22% of heart disease, 11% of stroke, 14% of diabetes and 10% of breast cancer, in addition to 16,178 premature deaths (VicHealth, 2012). Individually, physical inactivity accounted for approximately 7% of the overall burden of disease and injury in Australia in 2003, placing it fourth out of the 14 risk factors analysed. For diabetes, physical inactivity was the second highest contributor to the burden of disease, accounting for 24% of its burden (AIHW, 2012).
Adequate physical activity supports optimum health and wellbeing by preventing and managing chronic disease and maintaining a healthy body weight (AIHW, 2012). Regular physical activity has a protective effect, reducing the risk of developing diseases such as cardiovascular disease, chronic kidney disease and type 2 diabetes (AIHW, 2012). Furthermore, increasing participation in physical activity and reducing time spent sitting in a day is associated with a number of health benefits including promoting health and prevention of disease, improving individual self-confidence and social connectedness, improving the wellbeing of the local workforce and productivity, reducing local traffic congestion and contributing to safer (VicHealth, 2012). The benefits of physical activity have prompted the development of Healthy by Design, a practical guideline to help local governments in Victoria develop supportive environments and opportunities for individuals to be physically active where they live, work and visit (National Heart Foundation of Australia, 2012).
The idea is to incorporate health into planning and design for walking and cycling routes, streets, local destinations (which are walkable/rideable), open space, public transport, supporting infrastructure (e.g. seating, signage, lighting, fencing and walls) and fostering community spirit (National Heart Foundation of Australia, 2012). This initiative was internationally recognised in the WHO “Closing the gap in generations” report (CSDH, 2008). In further support of the importance of creating supportive environments for health such as increasing open park space and ensuring maintenance of these parks; a recent study conducted in New York City demonstrated that greater access to park spaces and park cleanliness was associated with lower BMI in adults (Stark, et al., 2014).
Breastfeeding has many health benefits for both infant and mother. For infants, breastfeeding helps protect against infection, some chronic diseases (e.g. type 1 and type 2 diabetes), coeliac disease, inflammatory bowel disease, lowers cardiovascular disease risk factors (high blood pressure, cholesterol and obesity) and enhances cognitive development. Mothers can benefit from reduced risk of ovarian and breast cancer and type 2 diabetes in women who have experienced gestational diabetes. Current National Health and Medical Research Council Infant Feeding Guidelines (2013) recommend sole breastfeeding until approximately six months old when solids are then introduced and to continue breastfeeding until 12 months of age and beyond as mother and child choose (NHMRC, 2013).
Obesity prevention background
Current evidence regarding effective strategies to prevent obesity is lacking (de Silva-Sanigorski, et al., 2010), with insufficient information to draw strong conclusions about which approaches are most effective (Lemmens, Oenema, Klepp, Henriksen, & Brug, 2008). More understanding of the characteristics of obesity prevention interventions such as the impact, the extent to which they work equitably and how safe they are to implement is required (Waters, et al., 2011). The most promising equitable, sustainable and cost-effective community-based obesity prevention approaches appear to be multi-sector, multi-strategy approaches in children (de Silva-Sanigorski, et al., 2010).
Settings such as schools, preschools and child care facilities have an important role of promoting healthy eating and physical activity, and the majority of obesity prevention interventions have been conducted in schools (de Silva-Sanigorski, et al., 2010). Schools have the advantage of being able to reach large populations of children, with varying socioeconomic circumstances, and provide an opportunity to subsequently implement the programs into surrounding communities (Manios, et al., 2012). However, given the multifactorial nature of obesity, and the many potential factors which influence its development, it is important to implement a holistic multifactorial approach, of which, can be guided by a socio-ecological framework (Manios, et al., 2012). The socio-ecological framework incorporates multi-level influences on individual behaviours with other important factors such as culture, organisational policies, practices and regulations, and engagement with the wider community such as engaging relevant stakeholders to be involved in the design, implementation and evaluation of the proposed program (de Silva-Sanigorski, et al., 2010) (Manios, et al., 2012). This model will be discussed in detail below.
The Socio-Ecological Framework
The socio-ecological framework considers interactions between individual behaviours and the role of the environment. With regards to obesity, it suggests that not only is weight status influenced by energy intake and expenditure, but it is also influenced by interrelationships between an individual’s personal dimensions (e.g. biomedical, attitudinal, behavioural factors) and other multiple components of the individual’s life context (e.g. social, organisational, community, public policy, physical environment) (Willows, Hanley, & Delormier, 201). This framework is a variation of Bronfenbrenner’s Ecological Systems Theory (Center for Disease Control and Prevention, 2013) (McLeroy, Bibeau, Steckler, & Glanz, 1988).
Individual factors include characteristics of the actual individual such as knowledge, attitudes, behaviour, attributions, beliefs and the developmental history of the individual. Strategies focused at the individual level aim to facilitate behaviour change through enhancing the individual’s knowledge, skills, life experience, attitudes and beliefs through the provision of information and education. An example of a strategy which would target this component includes a social media campaign to educate adolescents and young adults regarding the benefits of physical activity in order to increase knowledge and influence the development of a positive attitude to physical activity (WHO, 1986).
This component represents interpersonal processes and primary groups, individual’s interactions with one another, including social network and social support systems (families, peer groups, friendship networks) (Center for Disease Control and Prevention, 2013) (McLeroy, Bibeau, Steckler, & Glanz, 1988). Strategies focused at the interpersonal level aim to facilitate behaviour change by affecting social and cultural norms and overcoming individual-level barriers via networks and relationships with friends, family, health care providers, community health workers, etc. to enhance self-help, social support and greater participation. A strategy which would target this component would be the creation of a walking group which allows peers to support the individual and influence change.
Institutions and organisations
This component includes social institutions with organisational characteristics and rules for operation (e.g. commercial organisations, social institutions, associations and clubs, workplaces, schools, health services). Strategies focused at the organisational level aim to facilitate behaviour change by influencing organisational systems and policies, structure, organisational culture, rules and regulations enabling them to influence the physical and social environments maintained within their organisation. The replacement of fast food and soft drinks in a workplace would be one strategy which would target this component and subsequently encourage employees to replace unhealthy food with healthier options (McLeroy, Bibeau, Steckler, & Glanz, 1988) (WHO, 1986).
Communities can be defined as a larger societal construct comprised of the three previous components of the model with geographical, political, structural and cultural characteristics (Center for Disease Control and Prevention, 2013). Strategies focused at the community level aim to facilitate behaviour change by influencing the structural and functional components of the community to create supportive, healthy places and spaces where people live and play – and leveraging resources and participation of community-level institutions and coalitions, community advocacy groups and the media. A strategy which covers this component includes creating a food co-operative and farmers market for a community which may have poor access to fresh fruit and vegetables.
Structures, policies and systems
The outermost component includes local, state and national laws and policies (McLeroy, Bibeau, Steckler, & Glanz, 1988) and represent the structures and systems that affect the built environment surrounding the communities and subsequently the individual (Center for Disease Control and Prevention, 2013). Strategies focused at the policy and system level aim to facilitate behaviour change by influencing and building healthy public policy by putting health on the agenda of policy makers in all sectors and at all levels, and promoting a coordinated action that leads to health, income and social policies that foster greater equity. The development of safe parks and recreational areas, and ensuring footpaths are present to increase walkability, as part of local government planning processes, is an example of a structural change embedded into policy to facilitate increased activity (Center for Disease Control and Prevention, 2013).
Paper continues in Part B