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This book was commissioned by the Department of Ethics, Equity, Trade and Human Rights as part of the work undertaken by the Priority Public Health Conditions Knowledge Network of the Commission on Social Determinants of Health, in collaboration with 16 of the major public health programs of WHO: alcohol-related disorders, cardiovascular diseases, child health, diabetes, food safety, HIV/AIDS, maternal health, malaria, mental health, neglected tropical diseases, nutrition, oral health, sexual and reproductive health, tobacco and health, tuberculosis, and violence and injuries. In addition to this, through collaboration with the Special Programme of Research, Development and Research Training in Human Reproduction, the Special Programme for Research and Training in Tropical Diseases, and the Alliance for Health Policy and Systems Research, 13 case studies were commissioned to examine the implementation challenges in addressing social determinants of health in low-and middle-income settings. The Priority Public Health Conditions Knowledge Network has analyzed the impact of social determinants on specific health conditions, identified possible entry-points, and explored possible interventions to improve health equity by addressing social determinants of health.

Integrates the various disciplines of the science of health disparities in one comprehensive volume The Science of Health Disparities Research is an indispensable source of up-to-date information on clinical and translational health disparities science. Building upon the advances in health disparities research over the past decade, this authoritative volume informs policies and practices addressing the diseases, disorders, and gaps in health outcomes that are more prevalent in minority populations and socially disadvantaged communities. Contributions by recognized scholars and leaders in the field—featuring contemporary research, conceptual models, and a broad range of scientific perspectives—provide an interdisciplinary approach to reducing inequalities in population health, encouraging community engagement in the research process, and promoting social justice. In-depth chapters help readers better understand the specifics of minority health and health disparities while demonstrating the importance of advancing theory, refining measurement, improving investigative methods, and diversifying scientific research. In 26 chapters, the book examines topics including the etiology of health disparities research, the determinants of population health, research ethics, and research in African American, Asians, Latino, American Indian, and other vulnerable populations. Providing a unified framework on the principles and applications of the science of health disparities research, this important volume: * Defines the field of health disparities science and suggests new directions in scholarship and research * Explains basic definitions, principles, and concepts for identifying, understanding and addressing health disparities * Provides guidance on both conducting health disparities research and translating the results * Examines how social, historical and contemporary injustices may influence the health of racial and ethnic minorities * Illustrates the increasing national and global importance of addressing health disparities * Discusses population health training, capacity-building, and the transdisciplinary tools needed to advance health equity A significant contribution to the field, The Science of Health Disparities Research is an essential resource for students and basic and clinical researchers in genetics, population genetics, and public health, health care policymakers, and epidemiologists, medical students, and clinicians, particularly those working with minority, vulnerable, or underserved populations.

To raise awareness about health inequalities, a well-functioning health inequality monitoring system (HIMS) is crucial. Drawing on work conducted under the Joint Action Health Equity Europe, the aim of this paper is to illustrate the strengths and weaknesses in current health inequality monitoring based on lessons learned from 12 European countries and to discuss what can be done to strengthen their capacities. Fifty-five statements were used to collect information about the status of the capacities at different steps of the monitoring process. The results indicate that the preconditions for monitoring vary greatly between countries. The availability and quality of data are generally regarded as strong, as is the ability to disaggregate data by age and gender. Regarded as poorer is the ability to disaggregate data by socioeconomic factors, such as education and income, or by other measures of social position, such as ethnicity. Few countries have a proper health inequality monitoring strategy in place and, where in place, it is often regarded as poorly up to date with policymakers’ needs. These findings suggest that non-data-related issues might be overlooked aspects of health inequality monitoring. Structures for stakeholder involvement and communication that attracts attention from policymakers are examples of aspects that deserve more effort.

The last 10 years have seen a resurgence in interest and research around inequalities in the health sector. While a disproportionate share of the new research has focused on measuring inequality in the health sector, work is emerging on how to understand the causes of inequality and on identifying successful approaches for tackling the problem. This book summarizes the operational lessons emerging from this new focus. It is intended to be an operational resource for change agents within and outside government in low and middle countries committed to improve access and use of critical health services to income poor and social vulnerable populations.

You see someone smoking a cigarette and say,Smoking is bad for your health, when what you mean is, You are a bad person because you smoke. You encounter someone whose body size you deem excessive, and say, Obesity is bad for your health, when what you mean is, You are lazy, unsightly, or weak of will. You see a woman bottle-feeding an infant and say,Breastfeeding is better for that child's health, when what you mean is that the woman must be a bad parent. You see the smokers, the overeaters, the bottle-feeders, and affirm your own health in the process. In these and countless other instances, the perception of your own health depends in part on your value judgments about others, and appealing to health allows for a set of moral assumptions to fly stealthily under the radar.Against Health argues that health is a concept, a norm, and a set of bodily practices whose ideological work is often rendered invisible by the assumption that it is a monolithic, universal good. And, that disparities in the incidence and prevalence of disease are closely linked to disparities in income and social support. To be clear, the book's stand against health is not a stand against the authenticity of people's attempts to ward off suffering. Against Health instead claims that individual strivings for health are, in some instances, rendered more difficult by the ways in which health is culturally configured and socially sustained.The book intervenes into current political debates about health in two ways. First, Against Health compellingly unpacks the divergent cultural meanings of health and explores the ideologies involved in its construction. Second, the authors present strategies for moving forward. They ask, what new possibilities and alliances arise? What new forms of activism or coalition can we create? What are our prospects for well-being? In short, what have we got if we ain't got health? Against Health ultimately argues that the conversations doctors, patients, politicians, activists, consumers, and policymakers have about health are enriched by recognizing that, when talking about health, they are not all talking about the same thing. And, that articulating the disparate valences of health can lead to deeper, more productive, and indeed more healthy interactions about our bodies.

A guide to a holistic approach to healthcare measurement aimed at improving access and outcomes Healthcare System Access is an important resource that bridges two areas of research—access modeling and healthcare system engineering. The book's mathematical modeling approach highlights fundamental approaches on measurement of and inference on healthcare access. This mathematical modeling facilitates translating data into knowledge in order to make data-driven estimates and projections about parameters, patterns, and trends in the system. The complementary engineering approach uses estimates and projections about the system to better inform efforts to design systems that will yield better outcomes. The author—a noted expert on the topic—offers an in-depth exploration of the concepts of systematic disparities, reviews measures for systematic disparities, and presents a statistical framework for making inference on disparities with application to disparities in access. The book also includes information health outcomes in the context of prevention and chronic disease management. In addition, this text: * Integrates data and knowledge from various fields to provide a framework for decision making in transforming access to healthcare * Provides in-depth material including illustrations of how to use state-of-art methodology, large data sources, and research from various fields * Includes end-of-chapter case studies for applying concepts to real-world conditions Written for health systems engineers, Healthcare System Access: Measurement, Inference, and Intervention puts the focus on approaches to measure healthcare access and addresses important enablers of such change in healthcare towards improving access and outcomes.

There is growing interest and concern about the unacceptable differentials in health between and within countries. This comes out of the realization that poor people will only be able to prosper, and emerge from poverty, if they enjoy better health. Healthy populations are a precondition for sustainable development. Using a novel combination of the personal studies of patients and description of conditions or diseases, this book provides a highly original and accessible introduction to key issues in global health today. Especially during the past decade, global health initiatives have become a prominent part of the international aid picture, bringing new resources, political commitment, and more attention for international health issues in the media. The author provides examples of diseases and problems related to health that disproportionally impact the poor, and gives their experiences 'a human face' through individual case studies. A specific case study of a health problem, such as malaria, tuberculosis and HIV or health financing, introduces each chapter and is followed by a historical review of the problem, why it is still now a problem for poor people or poor countries, and what can be done about it. These will inspire the reader to become more engaged with international health and development.

Link and Phelan (1995) developed the theory of fundamental causes to explain why the association between socioeconomic status (SES) and mortality has persisted despite radical changes in the diseases and risk factors that are presumed to explain it. They proposed that the enduring association results because SES embodies an array of resources, such as money, knowledge, prestige, power, and beneficial social connections that protect health no matter what mechanisms are relevant at any given time. In this article, we explicate the theory, review key findings, discuss refinements and limits to the theory, and discuss implications for health policies that might reduce health inequalities. We advocate policies that encourage medical and other health-promoting advances while at the same time breaking or weakening the link between these advances and socioeconomic resources. This can be accomplished either by reducing disparities in socioeconomic resources themselves or by developing interventions that, by their nature, are more equally distributed across SES groups.

Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Bill & Melinda Gates Foundation.

Context: Quantitative estimates of the magnitude, direction, and rate of change of health inequalities play a crucial role in creating and assessing policies aimed at eliminating the disproportionate burden of disease in disadvantaged populations. It is generally assumed that the measurement of health inequalities is a value-neutral process, providing objective data that are then interpreted using normative judgments about whether a particular distribution of health is just, fair, or socially acceptable. Methods: We discuss five examples in which normative judgments play a role in the measurement process itself, through either the selection of one measurement strategy to the exclusion of others or the selection of the type, significance, or weight assigned to the variables being measured. Findings: Overall, we find that many commonly used measures of inequality are value laden and that the normative judgments implicit in these measures have important consequences for interpreting and responding to health inequalities. Conclusions: Because values implicit in the generation of health inequality measures may lead to radically different interpretations of the same underlying data, we urge researchers to explicitly consider and transparently discuss the normative judgments underlying their measures. We also urge policymakers and other consumers of health inequalities data to pay close attention to the measures on which they base their assessments of current and future health policies.