Annual Review of Public Health - Volume 25, 2004

As a consequence of global aging of the human population, the occurrence of cognitive impairment and dementia is rapidly becoming a significant burden for medical care and public health systems. By the year 2020, the WHO predicts there will be nearly 29 million demented people in both developed and developing countries. Primary and secondary prevention of dementia through individual and population-level interventions could reduce this imminent risk. Vascular risk factors such as type 2 diabetes, hypertension, dietary fat intake, high cholesterol, and obesity have emerged as important influences on the risk of both vascular and Alzheimer's dementia. Understanding the reasons for differences between populations in genetic vulnerability and environmental exposures may help to identify modifiable risk factors that may lead to effective prevention of vascular and Alzheimer's dementia.

Public health agencies often require data that address the needs of special populations, such as minority groups. Sources of surveillance data often contain insufficient numbers of subjects to fully inform health agencies. In this review, we address the problems of and potential approaches for situations with insufficient surveillance data. We use the examples of race and ethnic minority groups throughout our discussion. However, many of the broad issues are applicable to other special groups with low frequency or who are especially hard to reach. Our recommendations are based, in part, on a symposium held in Missouri with the collaboration of state health agency, community, and academic research participants. We review problems in using existing data and collecting new data, especially from nonprobability samples. We also describe fieldwork issues for reaching and collecting information from special populations. Decisions among methods and solutions may require seeking additional resources for surveillance.

Multilevel statistical models have become increasingly popular among public health researchers over the past decade. Yet the enthusiasm with which these models are being adopted may obscure rather than solve some problems of statistical and substantive inference. We discuss the three most common applications of multilevel models in public health: (a) cluster-randomized trials, (b) observational studies of the multilevel etiology of health and disease, and (c) assessments of health care provider performance. In each area of investigation, we describe how multilevel models are being applied, comment on the validity of the statistical and substantive inferences being drawn, and suggest ways in which the strengths of multilevel models might be more fully exploited. We conclude with a call for more careful thinking about multilevel causal inference.

Health among the older population as measured by most dimensions has improved during the last two decades. Mortality has continued to decline, and disability and functioning loss are less common now than in the past. However, the prevalence of most diseases has increased in the older population as people survive longer with disease, and the reduction in incidence does not counter the effect of increased survival. On the other hand, having a disease appears to be less disabling than in the past.

Missing data are a pervasive problem in many public health investigations. The standard approach is to restrict the analysis to subjects with complete data on the variables involved in the analysis. Estimates from such analysis can be biased, especially if the subjects who are included in the analysis are systematically different from those who were excluded in terms of one or more key variables. Severity of bias in the estimates is illustrated through a simulation study in a logistic regression setting. This article reviews three approaches for analyzing incomplete data. The first approach involves weighting subjects who are included in the analysis to compensate for those who were excluded because of missing values. The second approach is based on multiple imputation where missing values are replaced by two or more plausible values. The final approach is based on constructing the likelihood based on the incomplete observed data. The same logistic regression example is used to illustrate the basic concepts and methodology. Some software packages for analyzing incomplete data are described.

Emission trading policies are increasingly important in environmental protection, especially in controlling air pollution in the United States. Their popularity results in part from the limitations and frustrations of centralized command and control regulation. Well-designed emission trading programs can achieve the same or better environmental and health outcomes as command and control regulations but provide regulated industries with greater flexibility. This lowers costs and improves the process of negotiating environmental policy. We present key concepts and important applications of emission trading, focusing on health impacts. These programs generally are well-designed, speeding emission abatement; improving health outcomes; and reducing compliance costs. Flaws have stopped a few poorly designed emission trading programs. A key issue in evaluating emission trading is our inability to know what the environmental outcome would have been under another approach.

With the completion of the Human Genome Project, it is likely that genetic testing for susceptibility to a wide range of diseases will increase in society. One venue for such increased testing is likely to be the workplace as employers attempt to protect workers from unhealthy gene-environment interactions, improve productivity, and control escalating health care costs. Past and recent examples of genetic testing in the workplace raise serious concerns that such testing could pose a significant threat to workers' privacy, autonomy, and dignity. Thus, defining the ethically, legally, and socially appropriate and inappropriate uses of genetic testing in the workplace presents a major challenge for occupational health professionals in the years ahead.

Pesticides are widely used in agricultural and other settings, resulting in continuing human exposure. Epidemiologic studies indicate that, despite premarket animal testing, current exposures are associated with risks to human health. In this review, we describe the routes of pesticide exposures occurring today, and summarize and evaluate the epidemiologic studies of pesticide-related carcinogenicity and neurotoxicity in adults. Better understanding of the patterns of exposure, the underlying variability within the human population, and the links between the animal toxicology data and human health effects will improve the evaluation of the risks to human health posed by pesticides. Improving epidemiology studies and integrating this information with toxicology data will allow the human health risks of pesticide exposure to be more accurately judged by public health policy makers.

The precautionary principle (PP) is an extension of the public health presage that prevention is better than cure. The PP has recently achieved new relevance in regard to serious but uncertain threats to human health and the environment and has now entered national and international legislation. However, frameworks for its unambiguous application in practice are yet to be designed. They will depend on legal and cultural circumstances and are likely to involve pluralities of perspectives and stakeholder participation. The rules for causal reasoning and dose dependence need to be addressed and may be conveniently expressed in accordance with probability theory. Although the PP will allow action before convincing evidence is secured, it is not science averse. However, it provides an occasion to review environmental health research strategies, methodologies, and research-reporting traditions. From this perspective, current research is afflicted by important biases and insufficient focus on major environmental health problems.

Agricultural work is the most prevalent type of employment in the world. In the United States only a few are engaged in creating food and fiber for many. Agriculture includes farming, ranching, fishing, and forestry, and together they carry significant risk for the development of injury or illness. There are numerous special-population issues related to agriculture. Farmers are old and growing older, many workers are children, and migrant and seasonal help, often foreign born, make up a large percentage of the workforce. It has been only relatively recently that concerns of agricultural safety and health have become a major research focus in the United States.

Studies of air pollution and human health have evolved from descriptive studies of the early phenomena of large increases in adverse health effects following extreme air pollution episodes to time-series analyses based on the use of sophisticated regression models. In fact, advanced statistical methods are necessary to address the challenges inherent in the detection of a relatively small pollution risk in the presence of potential confounders. This paper reviews the history, methods, and findings of the time-series studies estimating health risks associated with short-term exposure to particulate matter (PM), though much of the discussion is applicable to epidemiological studies of air pollution in general. We review the critical role of epidemiological studies in setting regulatory standards and the history of PM epidemiology and time-series analysis. We also summarize recent time-series results and conclude with a discussion of current and future directions of time-series analysis of particulates, including research on mortality displacement and the resolution of results from cohort and time-series studies.

The Guide to Community Preventive Services (Community Guide) is being developed under the leadership of the independent, nonfederal Task Force on Community Preventive Services. The Task Force makes recommendations for the use of public health programs and policies based on scientific evidence about what practices have worked to improve health. The Community Guide thoroughly searches scientific literature for topic-relevant studies, evaluates their quality according to established criteria, and makes recommendations based on the overall strength of the body of evidence and the size and variability of reported effects. In addition, the Community Guide identifies promising interventions that have not been adequately researched, thus helping to inform the public health research agenda. The continuously updated and expanded body of recommendations and research agenda formulated by this rigorous process have been published on the Internet and in various publications since 1999 and constitute a highly valued and objective evidence-based resource for guiding current and future public health activities. More remains to be learned, however, on how best to disseminate Community Guide findings to key target audiences and encourage their use to inform practice, policy, and additional research.

Understanding what determines patterns of infection spread in populations is important for controlling infection transmission. The science that advances this understanding uses mathematical and computer models that vary from deterministic models of continuous populations to models of dynamically evolving contact networks between individuals. These provide insight, serve as scientific theories, help design studies, and help analyze data. The key to their use lies in assessing the robustness of inferences made using them to violation of their simplifying assumptions. This involves changing model forms from deterministic to stochastic and from compartmental to network, as well as adding realistic detail and changing parameter values. Currently inferences about infection transmission are often made using stratified rate or risk comparisons, logistic regression models, or proportionate hazards models that assume an absence of transmission. Robustness assessment will show many of these inferences to be wrong. A community of epidemiologist modelers is needed for effective robustness assessment.

In the past 50 years, China has made great achievements in controlling infectious diseases and improving the public's health and hygiene. However, in the twenty-first century, owing to the negative effects brought on by aging of the population and the burdens of diseases, urbanization, industrialization, and globalization, Chinese public health officials are encountering greater difficulties than ever. Old operating models of public health cannot meet present requirements. The main problems are poor capacity to respond to public health emergencies, severe inequality of health care services, and lagging development of public health information systems. Public health in China can gradually meet the requirements of social development and the increasing public demand for health care services only when the public health is directed by informatization, globalization, technification, and humanization.

The development of a fully-competent public health workforce as a key component of the nation's public health infrastructure has become the focus of increasing attention. The subject is included in one, and is the major topic of a second, report from the Institute of Medicine published late in 2002. Workforce issues have stimulated the convening of the majority of public health–related associations in a range of collaborations on the subjects of defining, enumerating, credentialing, educating, and studying the workforce. The authors review the major questions confronting the field and introduce key components of current thinking about approaches to improvement.

Over the past 20 years, the United States has experienced one of the largest waves of immigration in its history. Understanding the health status and needs of immigrants is important because of their growing numbers and their contribution to the health of the nation, but it is challenging because of gaps in national databases, the heterogeneity of immigrant populations, and uncertainty about how migration affects health. Healthy People 2010 outlines the nation's public health objectives for the current decade. It includes ten leading health indicators (LHIs) chosen because of their importance as public health issues, their ability to motivate action, and the availability of data to measure their progress. In this paper, we discuss the health of immigrants from the perspective of these LHIs, as they provide a framework for anticipating some of the future health needs of immigrants and help define priority areas for research and action.

Tobacco harm reduction approaches are gaining increased attention. Much of this attention is due to a growing concern that significant populations of smokers either do not want to quit or believe they are unable to quit smoking, and to a concern over tobacco-industry attempts to produce tobacco products that claim to result in less toxin exposure. Decreasing tobacco toxin exposure as a method for reducing mortality and morbidity may be a reasonable tobacco control strategy. However, the impact of this strategy must be explored both on individual and population levels. A significant amount of independent research is needed to inform policy decisions. Regulatory authority over potential reduced exposure products is also essential.

This review considers the broad area of housing and public health, one of the traditional and core areas of public health research and intervention. The review takes into account the range of factors, acting at different levels, directly and indirectly, through which housing affects health. In public health terms, housing affects health in a myriad of relatively minor ways, in total forming one of the key social determinants of health. The paper closes by considering how the improvement of housing and neighborhoods has been a core activity of public health and a central component in tackling poverty. Investment in housing can be more than an investment in bricks and mortar: It can also form a foundation for the future health and well-being of the population. Addressing poor-quality housing and detrimental neighborhoods, in the broadest sense, is thus a task that should be grasped with vigor and determination by all those involved in public health.