搜索结果：Perspectives in public health

Ten per cent of the world's school-aged children are estimated to be carrying excess body fat (Fig. 1), with an increased risk for developing chronic disease. Of these overweight children, a quarter are obese, with a significant likelihood of some having multiple risk factors for type 2 diabetes, heart disease and a variety of other co-morbidities before or during early adulthood. The prevalence of overweight is dramatically higher in economically developed regions, but is rising significantly in most parts of the world. Prevalence of overweight and obesity among school-age children in global regions. Overweight and obesity defined by IOTF criteria. Children aged 5–17 years. Based on surveys in different years after 1990. Source: IOTF (1). In many countries the problem of childhood obesity is worsening at a dramatic rate. Surveys during the 1990s show that in Brazil and the USA, an additional 0.5% of the entire child population became overweight each year. In Canada, Australia and parts of Europe the rates were higher, with an additional 1% of all children becoming overweight each year. The burden upon the health services cannot yet be estimated. Although childhood obesity brings a number of additional problems in its train – hyperinsulinaemia, poor glucose tolerance and a raised risk of type 2 diabetes, hypertension, sleep apnoea, social exclusion and depression – the greatest health problems will be seen in the next generation of adults as the present childhood obesity epidemic passes through to adulthood. Greatly increased rates of heart disease, diabetes, certain cancers, gall bladder disease, osteoarthritis, endocrine disorders and other obesity-related conditions will be found in young adult populations, and their need for medical treatment may last for their remaining life-times. The costs to the health services, the losses to society and the burdens carried by the individuals involved will be great. The present report has been written to focus attention on the issue and to urge policy-makers to consider taking action before it is too late. Specifically, the report: reviews the measurement of obesity in young people and the need to agree on standardized methods for assessing children and adolescents, and to compare populations and monitor trends; reviews the global and regional trends in childhood obesity and overweight and the implications of these trends for understanding the factors that underlie childhood obesity; notes the increased risk of health problems that obese children and adolescents are likely to experience and examines the associated costs; considers the treatment and management options and their effectiveness for controlling childhood obesity; emphasizes the need for prevention as the only feasible solution for developed and developing countries alike. This document reflects contributions from experts working in a wide range of circumstances with a diversity of approaches, but with many shared opinions. The report has been endorsed by the Federation of International Societies for Paediatric Gastroenterology, Hepatology and Nutrition (FISPGHAN) and the International Paediatric Association (IPA). Health professionals are aware that the rising trends in excess weight among children and adolescents will put a heavy burden on health services (for example, 10% of young people with type 2 diabetes are likely to develop renal failure by the time they enter adulthood, requiring hospitalization followed by life-long dialysis treatment (2). Health services, especially in developing countries, may not easily bear these costs, and the result could be a significant fall in life expectancy. In industrially developed countries, children in lower-income families are particularly vulnerable because of poor diet and limited opportunities for physical activity. There may also be an ethnic component; for example, in the USA the prevalence of overweight among children aged 4–12 years rose twice as fast in Hispanic and African–American groups compared with white groups over the period 1986–1998 (3). In developing nations child obesity is most prevalent in wealthier sections of the population. However, child obesity is also rising among the urban poor in these countries, possibly due to their exposure to Westernized diets co-inciding with a history of undernutrition. Such rapid changes in the numbers of obese children within a relatively stable population indicate that genetic factors are not the primary reason for change. Some migration of populations may account for a proportion of the epidemic, but cannot account for it all. Although studies of twins brought up in separate environments have shown that a genetic predisposition to gain weight could account for 60–85% of the variation in obesity (4), for most of these children the genes for overweight are expressed where the environment allows and encourages their expression. These obesity-promoting environmental factors are sometimes referred to as ‘obesogenic’ (or ‘obesigenic’). Put graphically, a child's genetic make-up ‘loads the gun’ while their environment ‘pulls the trigger’ (5). A genetic predisposition to accumulate weight is a significant element in the equation, but its importance might best be viewed from another perspective: the genes that predispose for obesity are likely to be commonplace, with only a small proportion of children able to resist gaining weight in an obesogenic environment. The changing nature of the environment towards greater inducement of obesity has been described in WHO Technical Report (6) on chronic disease as follows: ‘Changes in the world food economy have contributed to shifting dietary patterns, for example, increased consumption of energy-dense diets high in fat, particularly saturated fat, and low in unrefined carbohydrates. These patterns are combined with a decline in energy expenditure that is associated with a sedentary lifestyle—motorized transport, labour-saving devices at home, the phasing out of physically demanding manual tasks in the workplace, and leisure time that is preponderantly devoted to physically undemanding pastimes.’ (pp. 1–2) This emphasis on the environmental causes of obesity leads to certain conclusions: first that the treatment for obesity is unlikely to succeed if we deal only with the child and not with the child's prevailing environment, and second that the prevention of obesity – short of genetically engineering each child to resist weight gain – will require a broad-based, public health programme. A doctor presented with an obese child must nevertheless attempt some form of remedial intervention to prevent the child's health deteriorating. The aim is to stabilize and hopefully reduce that child's accumulation of body fat, using a range of approaches discussed in the next few paragraphs. For a great majority of obese patients, the first point of contact is with a primary care physician or a public health nurse. Yet the relevant training in bariatric methods (methods related to the assessment, prevention and treatment of obesity) at the undergraduate level remains inadequate. Two national surveys in the USA conducted over 10 years, indicated that paediatric obesity was the most wanted topic for continuing medical education (7). For children who are moderately overweight, measures to prevent further weight gain, combined with normal growth in height, can be expected to lead to a decrease in BMI – i.e. children may be able to ‘grow into’ their weight. For the more seriously obese child, treatment regimes are largely palliative and designed to manage and control rather than resolve the problem. Weight control and improved self-esteem may be achieved, but the child is likely to remain seriously overweight and at risk of chronic disease throughout his or her life. The clinical management of obese children may require an extended amount of time and the assembly of a professional team including a dietitian, exercise physiologist and psychologist in addition to the physician. As paediatric obesity becomes more common, patient management may not be restricted to obesity clinics and other forms of management may be developed. Obesity clinics may be necessary for morbid obesity, but less severe forms of obesity may be better managed in primary care settings by a range of health practitioners. Obesity control in adults relies on a range of options: improvements in nutritional habits, raised levels of physical activity, behavioural modification and psychotherapy, pharmaceutical treatment and as a last resort, surgery. These options can be used alone or in combination. For children, neither surgery nor drug therapy can currently be recommended unless within a closely monitored research study (8). Of the remaining choices, no single method will ensure success, although some consensus exists. For example, reducing the time engaged in sedentary activities (such as watching television or playing computer and video games) has been shown to facilitate better treatment outcome (9). Dietary interventions in combination with exercise programmes have been reported to have better outcomes than dietary modulation alone. Exercise programmes alone without dietary modification are unlikely to be effective, because increased energy expenditure is likely to be matched by increased energy intake (10). A whole-family approach also appears vital, with several studies showing that outcomes are improved if the parents are engaged in the process, or even are the key instigators of the process, at least for younger children (11). Very strict dietary limitations were reported to have better short-term results than moderate dietary limitations. However, strictly modified diets cannot be maintained for long periods of time. More marked rebound effects are observed after the discontinuation of strict diets than after moderate dietary modifications. Two additional concerns regarding strict dietary limitations are: (1) the risk of not meeting basic nutrient requirements and thus adversely affecting growth; and (2) the risk of inducing adverse psychological effects, including appetite or eating disorders, feelings of stigmatization, anxiety and low self-esteem, especially if the intervention is not successful or the child has prior psychological problems (12, 13). Many questions regarding what constitutes the best treatment remain unanswered: there have been few sufficiently large multicentre clinical trials to test the efficacy and safety of well-defined obesity treatment programmes. Such trials may reveal which non-pharmacological and non-surgical interventions can help manage obesity over the long term. Losing weight over the short term, but then experiencing a rebound gain in weight, remains the usual experience for the majority of obese children and adolescents. The importance of further research cannot be over stated, but it is not uncommon for research and treatment to compete for limited financial resources, with research frequently being more successful in securing financial support. The lack of paediatric obesity clinics at many well-respected academic institutions illustrates this point. If the current approach to treatment is largely aimed at bringing the problem under control, rather than effecting a cure, and if this aim is only successful when a multi-disciplinary and intensive regimen is mounted, then managing the obesity epidemic will be vastly expensive and probably unaffordable for most countries. Pharmaceutical approaches may assist, but cannot replace, the multi-disciplinary management of obesity. Prevention is the only feasible option and is essential for all affected countries. Yet effective techniques for prevention have also proved elusive. Programmes to prevent obesity in children may start by identifying those children at greatest risk, but there are problems with this approach. Although screening for obesity potential may help target resources where they are most needed, such screening also creates stigma among the children identified if they are singled out for special attention. Furthermore, genetic studies suggest that most children are at risk of weight gain, and that strategies to prevent obesity in a child population – such as encouraging healthful diets and plentiful physical activity – will benefit the health of all children, whether at risk of obesity or not. The most logical settings for preventive interventions are school settings and home-based settings. A number of interventions have been tried at these levels, and these are reviewed in the present report, but success has been hard to demonstrate. A Cochrane review of those trials of sufficient duration to detect the effects of intervention concluded that there was little evidence of success (14). It suggested that a more reliable evidence base is needed in order to determine the most cost-effective and health promoting strategies that have sustainable results and can be generalized to other situations. As shown in the present report, there are several examples of interventions designed to prevent the rising levels of obesity – such as the school-based ‘Trim and Fit’ programme in Singapore and the ‘Agita Sao Paulo’ programme in Sao Paulo, Brazil. Favourable outcomes have been shown with small-scale interventions, modifying children's TV watching behaviour and promoting consumption of healthier foods by establishing a price differential. Although the beneficial results of such interventions may be detectable and significant, they are small compared with the size of the problem. Moreover, the improvements tend to decline after the intervention ends. It must be concluded that interventions at the family or school level will need to be matched by changes in the social and cultural context so that the benefits can be sustained and enhanced. Such prevention strategies will require a co-ordinated effort between the medical community, health administrators, teachers, parents, food producers and processors, retailers and caterers, advertisers and the media, recreation and sport planners, urban architects, city planners, politicians and legislators. This report highlights the underlying social changes that have led to rising levels of obesity in both the adult and child populations. These underlying factors, as listed below, are often a part of, or a consequence of social development and urbanization. Such development based on economic growth to enhance consumption is generally regarded in a positive light and, especially in developing countries as they emerge from poverty, may be aspired to. Increase in use of motorized transport, e.g. to school. Increase in traffic hazards for walkers and cyclists. Fall in opportunities for recreational physical activity. Increased sedentary recreation. Multiple TV channels around the clock. Greater quantities and variety of energy dense foods available. Rising levels of promotion and marketing of energy-dense foods. More frequent and widespread food purchasing opportunities. More use of restaurants and fast food stores. Larger portions of food offering better ‘value’ for money. Increased frequency of eating occasions. Rising use of soft drinks to replace water, e.g. in schools. Changes in these social trends may require increased awareness by countries of the health consequences of the pattern of consumption as the first step in a strategy to promote healthier diets and more active lives. Several authors 15-18) have suggested that efforts to prevent obesity should include measures involving a wide range of social actions, such as: public funding of quality physical education and sports facilities; the protection of open urban spaces, provision of safer pavements, parks, playgrounds and pedestrian zones, creation of more cycling paths; taxes on unhealthy foods and subsidies for the promotion of healthy, nutritious foods; dietary standards for school lunch programmes; elimination or displacement of soft drinks and confectionery from vending machines in schools and offering healthier choices (i.e. low-fat dairy products, fruits and vegetables); clear food labelling and controls on inconsistent health messages; controls on the political contributions given by the food industry; restrictions or bans on the advertising of foods to children; limits on other forms of marketing of foods to children; assessment of food industry initiatives to improve formulations and marketing strategies. It is clear from these suggestions that policies and actions will be needed at a variety of levels, some local and individually based, some national or internationally based. All of them will require the support and involvement of departments across the broad range of government and may include education, social and welfare services, environment and planning, transport, food production and marketing, advertising and media, and international trading and standard-setting bodies. Obesity prevention will involve work at all levels of the obesogenic environment. As Fig. 2illustrates, attempts to improve the environment at one level, for example the school, may be undermined by a failure to improve the environment at another level, be it below in the home, or above in the social and cultural context involving food marketing and advertising, lost recreational facilities or unsafe streets. The opportunities for influencing a child's environment. Children are vulnerable to the social and environmental pressures that raise the risk of obesity. Although they can be encouraged to increase their self-control in the face of temptation, and although they can be given knowledge and skills to help understand the context of their choices, children cannot be expected to bear the full burden of responsibility for preventing excess weight gain. 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The term "metabolic syndrome" refers to the clustering of a number of cardiovascular risk factors (obesity, hypertension, dyslipidemia and hyperglycaemia) believed to be related to insulin resistance. The prevalence of each of these diseases as well as the metabolic syndrome is increasing world wide. Obesity, hypertension, dyslipidemia and diabetes are no longer diseases of the wealthy. By 2025, three out of four people with diabetes will be living in third world countries, and similar trends are likely for the other components of the syndrome. Preventive action is urgently needed, and studies in China and India have proven to be effective.

BACKGROUND: The terms health app and medical app are often used interchangeably but do not necessarily mean the same thing. To better understand these terms and better regulate such technologies, we need distinct definitions of health and medical apps. OBJECTIVE: This study aimed to provide an overview of the definitions of health and medical apps from an interdisciplinary perspective. We summarized the core elements of the identified definitions for their holistic understanding in the context of digital public health. METHODS: The legal frameworks for medical device regulation in the United States, the European Union, and Germany formed the basis of this study. We then searched 6 databases for articles defining health or medical apps from an interdisciplinary perspective. The narrative literature review was supported by a forward and backward snowball search for more original definitions of health and medical apps. A qualitative analysis was conducted on the identified relevant aspects and core elements of each definition. On the basis of these findings, we developed a holistic definition of health and medical apps and created a decision flowchart to highlight the differences between the 2 types. RESULTS: The legal framework showed that medical apps could be regulated as mobile medical devices, whereas there is no legal term for health apps. Our narrative literature review identified 204 peer-reviewed publications that offered a definition of health and medical apps. After screening for original definitions and applying the snowball method, 11.8% (24/204) of the publications were included in the qualitative analysis. Of these 24 publications, 22 (88%) provided an original definition of health apps and 11 (44%) described medical apps. The literature suggests that medical apps are a part of health apps. To describe health or medical apps, most definitions used the user group, a description of health, the device, the legal regulation, collected data, or technological functions. However, the regulation should not be a distinction criterion as it requires legal knowledge, which is neither suitable nor practical. An app's intended medical or health use enables a clear differentiation between health and medical apps. Ultimately, the health aim of an app and its main target group are the only distinction criteria. CONCLUSIONS: Health apps are software programs on mobile devices that process health-related data on or for their users. They can be used by every health-conscious person to maintain, improve, or manage the health of an individual or the community. As an umbrella term, health apps include medical apps. Medical apps share the same technological functions and devices. Health professionals, patients, and family caregivers are the main user groups. Medical apps are intended for clinical and medical purposes and can be legally regulated as mobile medical devices.

SUMMARY: In 1995 the American College of Sports Medicine and the Centers for Disease Control and Prevention published national guidelines on Physical Activity and Public Health. The Committee on Exercise and Cardiac Rehabilitation of the American Heart Association endorsed and supported these recommendations. The purpose of the present report is to update and clarify the 1995 recommendations on the types and amounts of physical activity needed by healthy adults to improve and maintain health. Development of this document was by an expert panel of scientists, including physicians, epidemiologists, exercise scientists, and public health specialists. This panel reviewed advances in pertinent physiologic, epidemiologic, and clinical scientific data, including primary research articles and reviews published since the original recommendation was issued in 1995. Issues considered by the panel included new scientific evidence relating physical activity to health, physical activity recommendations by various organizations in the interim, and communications issues. Key points related to updating the physical activity recommendation were outlined and writing groups were formed. A draft manuscript was prepared and circulated for review to the expert panel as well as to outside experts. Comments were integrated into the final recommendation. PRIMARY RECOMMENDATION: To promote and maintain health, all healthy adults aged 18 to 65 yr need moderate-intensity aerobic (endurance) physical activity for a minimum of 30 min on five days each week or vigorous-intensity aerobic physical activity for a minimum of 20 min on three days each week. [I (A)] Combinations of moderate- and vigorous-intensity activity can be performed to meet this recommendation. [IIa (B)] For example, a person can meet the recommendation by walking briskly for 30 min twice during the week and then jogging for 20 min on two other days. Moderate-intensity aerobic activity, which is generally equivalent to a brisk walk and noticeably accelerates the heart rate, can be accumulated toward the 30-min minimum by performing bouts each lasting 10 or more minutes. [I (B)] Vigorous-intensity activity is exemplified by jogging, and causes rapid breathing and a substantial increase in heart rate. In addition, every adult should perform activities that maintain or increase muscular strength and endurance a minimum of two days each week. [IIa (A)] Because of the dose-response relation between physical activity and health, persons who wish to further improve their personal fitness, reduce their risk for chronic diseases and disabilities or prevent unhealthy weight gain may benefit by exceeding the minimum recommended amounts of physical activity. [I (A)]

Rapidly evolving technology, data and analytic landscapes are permeating many fields and professions. In public health, the need for data science skills including data literacy is particularly prominent given both the potential of novel data types and analysis methods to fill gaps in existing public health research and intervention practices, as well as the potential of such data or methods to perpetuate or augment health disparities. Through a review of public health courses and programs at the top 10 U.S. and globally ranked schools of public health, this article summarizes existing educational efforts in public health data science. These existing practices serve to inform efforts for broadening such curricula to further schools and populations. Data science ethics course offerings are also examined in context of assessing how population health principles can be blended into training across levels of data involvement to augment the traditional core of public health curricula. Parallel findings from domestic and international 'outside the classroom' training programs are also synthesized to advance approaches for increasing diversity in public health data science. Based on these p

Digital health interventions, particularly electronic referrals (e-referrals) and health information systems, have revolutionised clinical workflows in public hospitals by automating processes. However, the utilization of e-referrals has yielded mixed outcomes, with varying levels of success in organisational processes.This paper explores improvisation of health information systems in Southern African public hospitals from a socio-technical perspective. In particular the paper explains the design-reality gaps giving rise to improvisations of mandated health information systems in order to understand their occurrence and impact on referral outcomes. We employed the design-reality framework and the Process framework for Healthcare Information System Workarounds and Impacts to explain the socio-technical issues related to the phenomenon of interest.We conducted semi-interviews with 31 respondents from health organisations as case studies.Respondents from two public hospitals in South Africa and two in Namibia were interviewed to examine how they devised improvisations to various health information systems in each setting.The findings showed that using WhatsApp or improvising existing

The surging demand for artificial intelligence (AI) has led to a rapid expansion of energy-intensive data centers, contributing to criteria air pollutant emissions and raising public health concerns that have received comparatively limited attention in sustainability assessments. This paper introduces a principled methodology to model air pollutant emissions for data centers and estimate the public health impacts. Our findings reveal that the growing demand for AI and computing technologies is projected to push the total annual public health burden of U.S. data centers up to more than $20 billion in 2028. Although national-level impacts remain modest, data center health costs are unevenly distributed: in the most affected counties, the estimated per-household health burden can reach about seven times the national average. Next, we propose a health-informed computing framework that explicitly incorporates public health impacts into data center resource management across space and time, mitigating public health costs while supporting environmental sustainability. More broadly, we recommend extended energy reporting to include public health impact of data centers and paying attention

Artificial Intelligence (AI) is revolutionizing various fields, including public health surveillance. In Africa, where health systems frequently encounter challenges such as limited resources, inadequate infrastructure, failed health information systems and a shortage of skilled health professionals, AI offers a transformative opportunity. This paper investigates the applications of AI in public health surveillance across the continent, presenting successful case studies and examining the benefits, opportunities, and challenges of implementing AI technologies in African healthcare settings. Our paper highlights AI's potential to enhance disease monitoring and health outcomes, and support effective public health interventions. The findings presented in the paper demonstrate that AI can significantly improve the accuracy and timeliness of disease detection and prediction, optimize resource allocation, and facilitate targeted public health strategies. Additionally, our paper identified key barriers to the widespread adoption of AI in African public health systems and proposed actionable recommendations to overcome these challenges.

The electric power sector is a leading source of air pollutant emissions, impacting the public health of nearly every community. Although regulatory measures have reduced air pollutants, fossil fuels remain a significant component of the energy supply, highlighting the need for more advanced demand-side approaches to reduce the public health impacts. To enable health-informed demand-side management, we introduce HealthPredictor, a domain-specific AI model that provides an end-to-end pipeline linking electricity use to public health outcomes. The model comprises three components: a fuel mix predictor that estimates the contribution of different generation sources, an air quality converter that models pollutant emissions and atmospheric dispersion, and a health impact assessor that translates resulting pollutant changes into monetized health damages. Across multiple regions in the United States, our health-driven optimization framework yields substantially lower prediction errors in terms of public health impacts than fuel mix-driven baselines. A case study on electric vehicle charging schedules illustrates the public health gains enabled by our method and the actionable guidance it

The rapid spread of health misinformation on online social networks (OSNs) during global crises such as the COVID-19 pandemic poses challenges to public health, social stability, and institutional trust. Centrality metrics have long been pivotal in understanding the dynamics of information flow, particularly in the context of health misinformation. However, the increasing complexity and dynamism of online networks, especially during crises, highlight the limitations of these traditional approaches. This study introduces and compares three novel centrality metrics: dynamic influence centrality (DIC), health misinformation vulnerability centrality (MVC), and propagation centrality (PC). These metrics incorporate temporal dynamics, susceptibility, and multilayered network interactions. Using the FibVID dataset, we compared traditional and novel metrics to identify influential nodes, propagation pathways, and misinformation influencers. Traditional metrics identified 29 influential nodes, while the new metrics uncovered 24 unique nodes, resulting in 42 combined nodes, an increase of 44.83%. Baseline interventions reduced health misinformation by 50%, while incorporating the new metrics

BACKGROUND: Health literacy concerns the knowledge and competences of persons to meet the complex demands of health in modern society. Although its importance is increasingly recognised, there is no consensus about the definition of health literacy or about its conceptual dimensions, which limits the possibilities for measurement and comparison. The aim of the study is to review definitions and models on health literacy to develop an integrated definition and conceptual model capturing the most comprehensive evidence-based dimensions of health literacy. METHODS: A systematic literature review was performed to identify definitions and conceptual frameworks of health literacy. A content analysis of the definitions and conceptual frameworks was carried out to identify the central dimensions of health literacy and develop an integrated model. RESULTS: The review resulted in 17 definitions of health literacy and 12 conceptual models. Based on the content analysis, an integrative conceptual model was developed containing 12 dimensions referring to the knowledge, motivation and competencies of accessing, understanding, appraising and applying health-related information within the healthcare, disease prevention and health promotion setting, respectively. CONCLUSIONS: Based upon this review, a model is proposed integrating medical and public health views of health literacy. The model can serve as a basis for developing health literacy enhancing interventions and provide a conceptual basis for the development and validation of measurement tools, capturing the different dimensions of health literacy within the healthcare, disease prevention and health promotion settings.

Quantum technologies, including quantum computing, cryptography, and sensing, among others, are set to revolutionize sectors ranging from materials science to drug discovery. Despite their significant potential, the implications for public health have been largely overlooked, highlighting a critical gap in recognition and preparation. This oversight necessitates immediate action, as public health remains largely unaware of quantum technologies as a tool for advancement. The application of quantum principles to epidemiology and health informatics, termed quantum health epidemiology and quantum health informatics, has the potential to radically transform disease surveillance, prediction, modeling, and analysis of health data. However, there is a notable lack of quantum expertise within the public health workforce and educational pipelines. This gap underscores the urgent need for the development of quantum literacy among public health practitioners, leaders, and students to leverage emerging opportunities while addressing risks and ethical considerations. Innovative teaching methods, such as interactive simulations, games, visual models, and other tailored platforms, offer viable sol

Time elapsed till an event of interest is often modeled using the survival analysis methodology, which estimates a survival score based on the input features. There is a resurgence of interest in developing more accurate prediction models for time-to-event prediction in personalized healthcare using modern tools such as neural networks. Higher quality features and more frequent observations improve the predictions for a patient, however, the impact of including a patient's geographic location-based public health statistics on individual predictions has not been studied. This paper proposes a complementary improvement to survival analysis models by incorporating public health statistics in the input features. We show that including geographic location-based public health information results in a statistically significant improvement in the concordance index evaluated on the Surveillance, Epidemiology, and End Results (SEER) dataset containing nationwide cancer incidence data. The improvement holds for both the standard Cox proportional hazards model and the state-of-the-art Deep Survival Machines model. Our results indicate the utility of geographic location-based public health feat

Health literacy is a relatively new concept in health promotion. It is a composite term to describe a range of outcomes to health education and communication activities. From this perspective, health education is directed towards improving health literacy. This paper identifies the failings of past educational programs to address social and economic determinants of health, and traces the subsequent reduction in the role of health education in contemporary health promotion. These perceived failings may have led to significant underestimation of the potential role of health education in addressing the social determinants of health. A 'health outcome model' is presented. This model highlights health literacy as a key outcome from health education. Examination of the concept of health literacy identifies distinctions between functional health literacy, interactive health literacy and critical health literacy. Through this analysis, improving health literacy meant more than transmitting information, and developing skills to be able to read pamphlets and successfully make appointments. By improving people's access to health information and their capacity to use it effectively, it is argued that improved health literacy is critical to empowerment. The implications for the content and method of contemporary health education and communication are then considered. Emphasis is given to more personal forms of communication, and community-based educational outreach, as well as the political content of health education, focussed on better equipping people to overcome structural barriers to health.