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In Chile, childhood obesity rates are high. The purpose of this article is to compare BMI growth characteristics of normal (N), overweight (OW), and obese (OB) 5-year olds from 0 to 5 years and explore the influence of some prenatal factors on these patterns of growth. The study was done on a retrospective cohort of 1,089 5-year olds with birth weight >2,500 g. Weight and height were obtained from records at nine occasions (0-36 months); at 52 and 60 months, we measured them. At 60 months, children were classified as N, OW, and OB. At each age, BMI and z-score of BMI (BMI Z) differences were compared among groups. The influence of birth weight, pre-pregnancy BMI, and prenatal variables (weight gain, smoking, and presence of diabetes and preeclampsia) on BMI Z differences between N and OB was also explored. Adiposity rebound (AR) was not observed for the N, although for the OW, it occurred approximately 52 months and for the OB at approximately 24 months. BMI Z differences between N and OB were significant from birth, but were greatest between 6-12 and 36-52 months. Additional adjustment by birth weight, pre-pregnancy BMI, and prenatal variables decreased the BMI Z differences for the first 24 months with virtually no effect after this age. Accelerated growth in OB children from post-transition countries occurs immediately after birth, much earlier than the AR. The influence of prenatal factors on adiposity acquisition may extend at most until 2 years of life, although BMI gains thereafter are more related to postnatal variables.

Non-communicable chronic diseases are now a worldwide epidemic. Diet and physical activity throughout life are among its main determinants. In countries undergoing the early stages of the nutrition transition weight gain from birth to 2 years of life is related to lean mass gain, while ponderal gain after age 2 years is related to adiposity and later diabetes and CVD risk. Evidence from developing countries undergoing the more advanced stages of the nutrition transition is limited. The early growth patterns of a cohort of Chilean children born in 2002 with normal birth weight who at 4 years had a high prevalence of obesity and CVD risk factors have been assessed. Results indicate that BMI gain in early life, particularly from 6 months to 24 months, is positively associated with adiposity and CVD risk status at 4 years. These results together with existing evidence suggest that actions to prevent obesity and nutrition-related chronic diseases in developing countries should start early in life, possibly after 6 months of age. This approach should consider assessing the effect of mode of feeding and the amount and type of energy fed, as well as the resulting growth patterns. The challenge for researchers addressing the nutrition transition is to define the optimal nutrition in early life, considering not only the short- and long-term health consequences but also taking into account the stage of the nutritional transition for the given population of interest. The latter will probably require redefining optimal postnatal growth based on the context of maternal size and fetal growth.

Mitochondrial complex II (succinate dehydrogenase) is part of the tricarboxylic acid cycle and the respiratory chain. Three nuclear genes encode its essential iron-sulfur subunit in Arabidopsis (Arabidopsis thaliana). One of them, SUCCINATE DEHYDROGENASE2-3 (SDH2-3), is specifically expressed in the embryo during seed maturation, suggesting that SDH2-3 may have a role as the complex II iron-sulfur subunit during embryo maturation and/or germination. Here, we present data demonstrating that three abscisic acid-responsive elements and one RY-like enhancer element, present in the SDH2-3 promoter, are involved in embryo-specific SDH2-3 transcriptional regulation. Furthermore, we show that ABSCISIC ACID INSENSITIVE3 (ABI3), FUSCA3 (FUS3), and LEAFY COTYLEDON2, three key B3 domain transcription factors involved in gene expression during seed maturation, control SDH2-3 expression. Whereas ABI3 and FUS3 interact with the RY element in the SDH2-3 promoter, the abscisic acid-responsive elements are shown to be a target for bZIP53, a member of the basic leucine zipper (bZIP) family of transcription factors. We show that group S1 bZIP53 protein binds the promoter as a heterodimer with group C bZIP10 or bZIP25. To the best of our knowledge, the SDH2-3 promoter is the first embryo-specific promoter characterized for a mitochondrial respiratory complex protein. Characterization of succinate dehydrogenase activity in embryos from two homozygous sdh2-3 mutant lines permits us to conclude that SDH2-3 is the major iron-sulfur subunit of mature embryo complex II. Finally, the absence of SDH2-3 in mutant seeds slows down their germination, pointing to a role of SDH2-3-containing complex II at an early step of germination.

Historically, the anthropometric assessment of nutritional welfare programs has been targeted to assess nutritional deficiencies based on weight-to-age and height-to-age indicators. Recently, given the increase on childhood obesity, it has been also recommended the measurement of indicators of obesity (i.e., weight-to-height) and central obesity (i.e., waist circumference). However, the agreement of these indicators in preschool children is unclear. The aims of this study were: (1) assess the nutritional status of children attending the Chilean National Nursery Schools Council Program (JUNJI); (2) assess the agreement between general and central obesity anthropometric measurements in these children. In 574 girls and 580 boys, 3.0 to 5.9 years old, we measured: weight, height, waist and hip circumference, and five skinfolds. We used the WHO 2006 growth standards to estimate Z-scores. We defined general obesity as WHZ or BAZ= 2, and central obesity as waist circumference > or =90 percentile of NHANES III. The participants were on average slightly shorter but considerably heavier and obese than the reference populations. Prevalence of general obesity was close to 16% with both indicators while prevalence of central obesity reached 15%. There was good agreement among general obesity indicators and central obesity indicators (Kappa = 0.6-0.7). In summary, we found a high prevalence of obesity and central obesity among Chilean preschool children beneficiaries of a welfare program. At this age, there was a good agreement among general obesity indicators and central obesity indicators. These results suggest that waist circumferences measurements should not be incorporated to the program.

Countries undergoing the nutrition transition are experiencing a progressive increase in obesity and nutrition-related chronic diseases (NRCDs). In transitional countries, stunting (shortness for age) and micronutrient deficiencies (iron, vitamin A, and zinc) in children coexist with obesity and NRCDs originating the double burden of nutritional disease. The causal web for obesity and NRCDs is complex and multifaceted; changes in diet and physical activity of the population are likely the main concurrent determinant factors. However, recent evidence suggests that specific patterns of prenatal and postnatal growth are also potential contributors. Evidence indicates that intervention strategies to prevent malnutrition should emphasize improvements in linear growth in the first 2-3 years of life rather than aim at gaining weight. Avoiding excessive weight gain relative to height gain (BMI) is especially relevant after the first 2 years of life. Routine assessment of child growth based on the new World Health Organization (WHO) standard, defining energy needs based on the recent Food and Agricultural Organization (FAO)/WHO norms, and providing critical micronutrients to support lean mass growth are critical to prevent obesity and NRCDs starting early in the life course. These actions should contribute in the prevention and control of obesity in childhood and thus help prevent NRCDs in future generations of adults.

Climate change is an emerging threat to global public health. It is also highly inequitable, as the greatest risks are to the poorest populations, who have contributed least to greenhouse gas (GHG) emissions. The rapid economic development and the concurrent urbanization of poorer countries mean that developing-country cities will be both vulnerable to health hazards from climate change and, simultaneously, an increasing contributor to the problem. We review the specific health vulnerabilities of urban populations in developing countries and highlight the range of large direct health effects of energy policies that are concentrated in urban areas. Common vulnerability factors include coastal location, exposure to the urban heat-island effect, high levels of outdoor and indoor air pollution, high population density, and poor sanitation. There are clear opportunities for simultaneously improving health and cutting GHG emissions most obviously through policies related to transport systems, urban planning, building regulations and household energy supply. These influence some of the largest current global health burdens, including approximately 800,000 annual deaths from ambient urban air pollution, 1.2 million from road-traffic accidents, 1.9 million from physical inactivity, and 1.5 million per year from indoor air pollution. GHG emissions and health protection in developing-country cities are likely to become increasingly prominent in policy development. There is a need for a more active input from the health sector to ensure that development and health policies contribute to a preventive approach to local and global environmental sustainability, urban population health, and health equity.

There is very little systematically collected evidence on the overall contribution of environmental risk factors to the global burden of disease. The World Health Organization (WHO) recently completed a comprehensive, systematic, and transparent estimate of the disease burden attributable to the environment highlighting the full potential for environmental interventions to improve human health. This report is the result of a systematic literature review on environmental risks completed by a survey of expert opinion using a variant of the Delphi method. More than 100 experts provided quantitative estimates on the fractions of 85 diseases attributable to the environment. They were asked to consider only the contributions of the "reasonably modifiable environment"-that is, the part of environment that can plausibly be changed by existing interventions. The report estimates that 24% of the global burden of disease was due to environmental risk factors. Environmental factors were judged to play a role in 85 of the 102 diseases taken into account. Major diseases were, for example, diarrheal diseases with fractions attributable to the environment of 94%, lower respiratory infections with 41%, malaria with 42%, and unintentional injuries with 42%. The evidence shows that a large proportion of this "environmental disease burden" could be averted by existing cost-effective interventions such as clean water, clean air, and basic safety measures. In children, 34% of the disease burden is attributable to the environment, and much of this burden is in developing countries.

Objectives: We studied the association between socioeconomic status (SES) and asthma symptoms, severity of asthma, atopy, and bronchial hyperresponsiveness (BHR) to methacholine., Methods: We studied 1232 men and women born between 1974 and 1978 in a semirural area of Chile. We assessed asthma symptoms with a standardized questionnaire, atopy with a skin-prick test to 8 allergens, and BHR to methacholine with the tidal breathing method. SES was derived from several indicators: education, occupation, completion of a welfare form, belongings, housing, number of siblings, and overcrowding., Results: Those with fewer belongings had more asthma symptoms. Those who had higher education and those who owned cars had fewer asthma symptoms and BHR. Overcrowding was negatively related to atopy, atopy with asthma symptoms, and BHR. Higher education and noncompletion of a welfare form were risk factors for atopy., Conclusion: The strength and direction of the association between asthma and SES depended on what definition of asthma was analyzed. Asthma symptoms were more common among poor people. There was some support for the hygiene hypothesis, as overcrowding was associated with less wheezing with atopy, less atopy, and less BHR.

Evidence from environmental burden-of-disease studies can provide valuable input in the decision-making process in environmental health, facilitating priority setting and cost effectiveness evaluation. This paper discusses important aspects of environmental burden-of-disease estimates in the light of) published examples. To produce reliable and comparable burden-of-disease estimates for environmental and occupational risk factors, harmonized methods are needed. Such methods should address the feasibility of data collection at national, regional, and global levels, the reliability of estimates, the uncertainty around estimates, and scenario tools to investigate the health gains of options for preventive action in different domains of policy. Any such method will require a framework (i.e., causal inference model) able to take into account the contributions of distal and proximal causes, and the possible interactions between risk factors.

Over the years, estimates have been made of the portions of human mortality and morbidity that can be attributed to environmental factors. Frustratingly, however, even for a single category of disease such as cancer, these estimates have often varied widely. Here we attempt to explain why such efforts have come to such different results in the past and to provide guidance for doing such estimates more consistently in the future to avoid the most important pitfalls. We do so by carefully defining what we mean by the terms "environmental," "ill health," and "attributable." Finally, based on these recommendations, we attempt our own estimate, appropriately qualified according to the many remaining uncertainties. Our estimate is that 25-33% of the global burden of disease can be attributed to environmental risk factors. Children under 5 years of age seem to bear the largest environmental burden, and the portion of disease due to environmental risks seems to decrease with economic development. A summary of these estimates first appeared in the 1997 report, "Health and Environment in Sustainable Development," which was the World Health Organization's contribution to the 5-year anniversary of the Rio Earth Summit. A full explanation of how these estimates were made is first presented here. We end with a call for a program of "strategic epidemiology," which would be designed to fill important gaps in the understanding of major environmental health risks in important population groups worldwide.

This paper reviews methodologic issues pertinent to the application of epidemiology in risk assessment and discusses concerns in the presentation of results from such an activity. Assessment of the health risks associated with occupational and environmental exposures involves four phases: hazard identification, i.e., the detection of the potential for agents to cause adverse health effects in exposed populations; exposure assessment, i.e., the quantification of exposures and the estimation of the characteristics and sizes of the exposed populations; dose-response assessment, i.e., the modeling for risk realization; and risk characterization, i.e., the evaluation of the impact of a change in exposure levels on public health effects. The risk-assessment process involves limitations of exposure data, many assumptions, and subjective choices that need to be considered when using this approach to provide guidance for health policy or action. In view of these uncertainties, we suggest that the provision of estimates of individual risk and disease burden in a population must be accompanied by the corresponding estimates of precision; risks should be presented in a sufficiently disaggregated form so that population heterogeneities are not lost in the data aggregation; and different scenarios and risk models should be applied. The methods are illustrated by an assessment on the health impacts of exposure to silica.

This paper discusses the links among health, environment, and sustainable development and presents a framework that extends from the epidemiological domain to the policy domain and includes the driving forces that generate environmental pressures, creating changes in the state of the environment and eventually contributing to human exposures. Health effects are the end result of this complex net of events. Environmental health interventions should not be limited to treatment of cases and directly reducing human exposures. The paper discusses the need for integrated action at all levels and, in particular, on the need to focus on long-term action directed at reducing the driving forces that generate the environmental health threats. Only this approach can achieve sustained health benefits and environmental protection in accord with the principles of sustainable development.

This article gives a overview of the HEADLAMP project and its background. The project aims at bringing valid and useful information on the local and national health impacts of environmental hazards to those responsible for environmental health protection. Its main tools are health and environment data linkage methods, environmental health indicators used to quantify and monitor the local situation, and the interpretation and decision-making process. The project has 3 main characteristics which differentiate it from ad hoc epidemiological studies: (i) it is based on scientifically established relationships between environmental exposures and health effects; (ii) it uses routinely-collected data, or where necessary, new data collected using low-cost techniques; and (iii) it aims at providing information on which to base preventive action against environmental health problems. Based on these characteristics, a framework is proposed for the application of HEADLAMP for managing specific environmental health problems.

Environmental health indicators provide information about scientifically-based linkages between environment and health. This information can be used for environmental health management and decision-making. Environmental health indicators are rendered more complex than either environmental indicators or health indicators because they must take account of factors such as the variability in susceptibility in individuals and variability in co-exposures. Such variability implies that any links that are defined may not apply to all individuals or groups at all times. Individual-level epidemiological studies can contribute to establishing environmental health relationships for particular places and time periods. However, cost-efficiency demands that aggregated data and known environment and health relationships be used to derive these indicators. Environmental health indicators can therefore be constructed by linking aggregated data, or by identifying environmental indicators with a health linkage, or health indicators with an environmental linkage. The framework for environmental health indicators proposed here is an adaptation of the Pressure-State-Response framework. Its first level consists of driving forces, which create pressures on the environment. These in turn alter the state of the environment by increasing existing exposures or introducing new ones, which produces a measurable health effect. In order to rectify the problem, actions (i.e., environmental health management) must be undertaken at each level. Thus the framework becomes the Driving-force--Pressure--State--Effects--Action (DPSEA).

Despite our current knowledge about harmful exposures obtained from environmental epidemiology studies, preventive action is lacking in many fronts. To reverse this trend, results from environmental epidemiological studies must be translated from theory into public health practice more efficiently. This process requires epidemiology to provide the right type of data for decision-making and to communicate the results of environmental epidemiology studies in a form understandable to the community at large and to those empowered to take action. Tools for decision-making based on epidemiological data need to be developed further, and the epidemiologist has a role to play in the process of addressing the solutions to the problems they study. Similarly, while those with decision-making responsibilities are not expected to be directly involved with technical aspects of conducting epidemiological studies, it is necessary that they learn new ways of thinking and of evaluating information on health. They have a responsibility to understand the implications of the uncertainties in the information and the value this information has for decision-making. Decision-making involves choosing among alternative ways of meeting objectives. Often, however, there may be a number of objectives that may be in competition or conflict. Not infrequently, this combination of uncertainty and conflict produces diverse conclusions about the "best alternative" when viewed by different observers. A decision-maker must choose between competing alternatives, and may face uncertainties and difficulties at every step. These difficulties, however, should not serve as excuses for lack of action. While it is true that increasing evidence about a potential environmental health problem would aid the decision-making process, lack of action while waiting for more evidence may also carry significant adverse consequences.

From 1980 to 1985, the Australian Mesothelioma Surveillance Program, and since 1986, the Australian Mesothelioma Register, have been collecting data on all cases of malignant mesothelioma that could be ascertained in Australia. Incidence rates were calculated on 854 Program and 696 Register cases (total 1271) diagnosed in Australia between January 1, 1982 and December 31, 1988. Australia has one of the highest national rates of mesothelioma in the world (15.8 cases per million of population aged 20 years and older), and the rate is rising. The rate is far higher in males (28.3) than females (3.3). The Western Australian rate (28.9) is the highest among the states, as may be expected because of the crocidolite mine at Wittenoom; however, the largest numbers of cases occur in the more populous and industrial New South Wales. The high incidence rate, its expected continuing increase, and absence of a history of exposure to asbestos in approximately 28% of cases, demand consideration of potential environmental factors other than asbestos in the causation of this tumor, as well as continued surveillance.