Reaching the sustainable development goals through healthy environments: are we on track?

The adoption of the 2030 Agenda for Sustainable Development in 2015 opened new opportunities to work towards healthy environments through 'whole of government' and 'whole of society' approaches. It created a strong policy platform that acknowledges health as a result and an enabler of sustainable policies across all sectors of government. Five years into the process, an initial analysis of emerging trends indicates that, despite some encouraging developments in policy as well as overall progress in economy and technology, there remains a gap between rhetoric, ambition and reality. In particular, the monitoring system for environment and health-related sustainable development goals (SDGs) and targets requires further development; inequalities in environment and health persist and in some areas have increased; equity is not yet a central element of implementation and reporting on the achievement of the SDGs; and, most worrying of all, trends in key environmental indicators that are vital to the survival of the human species, such as those related to climate change and biodiversity, are still on an overall negative path. In summary, governments must significantly and rapidly increase action to secure the habitability and safety of planet Earth. The public health community assumes an unprecedented role in placing and maintaining health and equity at the heart of the political agenda. This demands new governance models conferring on the health sector a clear mandate and legitimacy to operate across sectors. It also requires enhancing capacities among health professionals to embrace this new level of complexity, understand the multiple links between sectoral policies and health, and successfully engage with other government sectors and stakeholders.

Hazardous waste and health impact: a systematic review of the scientific literature.

Waste is part of the agenda of the European Environment and Health Process and included among the topics of the Sixth Ministerial Conference on Environment and Health. Disposal and management of hazardous waste are worldwide challenges. We performed a systematic review to evaluate the evidence of the health impact of hazardous waste exposure, applying transparent and a priori defined methods. The following five steps, based on pre-defined systematic criteria, were applied. 1. Specify the research question, in terms of "Population-Exposure-Comparators-Outcomes" (PECO). POPULATION: people living near hazardous waste sites; Exposure: exposure to hazardous waste; Comparators: all comparators; Outcomes: all diseases/health disorders. 2. Carry out the literature search, in Medline and EMBASE. 3. Select studies for inclusion: original epidemiological studies, published between 1999 and 2015, on populations residentially exposed to hazardous waste. 4. Assess the quality of selected studies, taking into account study design, exposure and outcome assessment, confounding control. 5. Rate the confidence in the body of evidence for each outcome taking into account the reliability of each study, the strength of the association and concordance of results.Fifty-seven papers of epidemiological investigations on the health status of populations living near hazardous waste sites were selected for the evidence evaluation. The association between 95 health outcomes (diseases and disorders) and residential exposure to hazardous waste sites was evaluated. Health effects of residential hazardous waste exposure, previously partially unrecognized, were highlighted. Sufficient evidence was found of association between exposure to oil industry waste that releases high concentrations of hydrogen sulphide and acute symptoms. The evidence of causal relationship with hazardous waste was defined as limited for: liver, bladder, breast and testis cancers, non-Hodgkin lymphoma, asthma, congenital anomalies overall and anomalies of the neural tube, urogenital, connective and musculoskeletal systems, low birth weight and pre-term birth; evidence was defined as inadequate for the other health outcomes. The results, although not conclusive, provide indications that more effective public health policies on hazardous waste management are urgently needed. International, national and local authorities should oppose and eliminate poor, outdated and illegal practices of waste disposal, including illegal transboundary trade, and increase support regulation and its enforcement.

[Global burden of mortality in Italian polluted sites]. / Valutazioni globali del carico di mortalità nei siti di interesse nazionale per le bonifiche.

SENTIERI Project has assessed the overall mortality profile in all the IPSs combined, and performed IPS-specific analyses. The epidemiological evidence of the causal association between cause of death and exposure was classified into one of these three categories: Sufficient (S), Limited (L) and Inadequate (I). The procedures and results of the evidence evaluation have been presented in a 2010 Supplement of Epidemiology & Prevention devoted to SENTIERI. Mortality for causes of death with a priori Sufficient or Limited evidence of association with the environmental exposure exceeds the expected figures, with a SMR of 115.8 for men (90%CI 114.4-117.2; 2 439 extra deaths) and 114.4 for women (90% CI 112.4-116.5; 1 069 extra deaths). These excesses are also observed when analysis is extended to all the causes of death (i.e. with no restriction to the ones with a priori Sufficient or Limited evidence): for a total of 403 692 deaths (men and women combined), an excess of 9 969 deaths is observed, with an average of around 1 200 extra deaths per year. Most of these excesses are observed in IPSs located in Southern and Central Italy. The distribution of the causes of deaths shows that the excesses are not evenly distributed: cancer mortality accounts for 30%of all deaths, but is 43.2%of the excess deaths (4 309 cases of 9 969). Conversely, the percentage of excesses in non cancer causes, 19%, is lower than their share of total mortality (42%). Consistently with previous studies, the results suggest that the health status of populations living in the IPSs is worse than what regional averages show. Compared to previous studies, the analysis of the causes selected in SENTIERI, on the basis of a priori Sufficient or Limited evidence of association with the environmental exposures, provides additional information on their role, though some limitations, due to methodology and data used, should be considered.

Cancer mortality and congenital anomalies in a region of Italy with intense environmental pressure due to waste.

OBJECTIVES: Waste management in the Campania region has been characterised, since the 1980s, by widespread uncontrolled and illegal practices of waste dumping, generating concerns over the health implications. The objective of this study was to evaluate possible adverse health effects of such environmental pressure. METHODS: The health effects of waste-related environmental exposures in Campania were assessed in a correlation study on nine causes of death (for the years 1994-2001) and 12 types of congenital anomaly (CA) (1996-2002) in 196 municipalities of the provinces of Naples and Caserta. Poisson regression was used to analyse the association between health outcomes and environmental contamination due to waste, as measured through a composite index, adjusting for deprivation. RESULTS: Statistically significant excess relative risks (ERR, %) in high-index compared with low-index (unexposed) municipalities were found for all-cause mortality (9.2 (95% CI 6.5 to 11.9) in men and 12.4 (9.5 to 15.4) in women and liver cancer (19.3 (1.4 to 40.3) in men and 29.1 (7.6 to 54.8) in women). Increased risks were also found for all cancer mortality (both sexes), stomach and lung cancer (in men). Statistically significant ERRs were found for CAs of the internal urogenital system (82.7 (25.6 to 155.7)) and of the central nervous system (83.5 (24.7 to 169.9)). CONCLUSION: Although the causal nature of the association is uncertain, findings support the hypothesis that waste-related environmental exposures in Campania produce increased risks of mortality and, to a lesser extent, CAs.

The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: estimates of radiation-related cancer risks.

A 15-Country collaborative cohort study was conducted to provide direct estimates of cancer risk following protracted low doses of ionizing radiation. Analyses included 407,391 nuclear industry workers monitored individually for external radiation and 5.2 million person-years of follow-up. A significant association was seen between radiation dose and all-cause mortality [excess relative risk (ERR) 0.42 per Sv, 90% CI 0.07, 0.79; 18,993 deaths]. This was mainly attributable to a dose-related increase in all cancer mortality (ERR/Sv 0.97, 90% CI 0.28, 1.77; 5233 deaths). Among 31 specific types of malignancies studied, a significant association was found for lung cancer (ERR/Sv 1.86, 90% CI 0.49, 3.63; 1457 deaths) and a borderline significant (P = 0.06) association for multiple myeloma (ERR/Sv 6.15, 90% CI <0, 20.6; 83 deaths) and ill-defined and secondary cancers (ERR/Sv 1.96, 90% CI -0.26, 5.90; 328 deaths). Stratification on duration of employment had a large effect on the ERR/Sv, reflecting a strong healthy worker survivor effect in these cohorts. This is the largest analytical epidemiological study of the effects of low-dose protracted exposures to ionizing radiation to date. Further studies will be important to better assess the role of tobacco and other occupational exposures in our risk estimates.

Estimating the incidence rate ratio in cross-sectional studies using a simple alternative to logistic regression.

PURPOSE: Logistic regression is often used for the analysis of cross-sectional studies, and prevalence odds and odds ratios are obtained. Other methods have been proposed for estimating prevalence ratios. An alternative regression method is also available for estimating rate ratios. Its application to cross-sectional studies is discussed. METHODS: When dealing with chronic conditions, it is possible to model binomial data using the complementary log-log link function log(-log(1-pi)), where pi is the prevalence, an option available on many statistical software packages. In effect, these are models for the disease incidence rate lambda, which is assumed to be constant over the underlying follow-up period t. This approach is based on the well-known relationship 1-pi-exp(-lambda t). The cumulative effect of age on prevalence (effectively "time of follow up") can be accounted for in the model, by specifying it as an offset. RESULTS: The regression coefficients associated with the covariates included in the model estimate rate ratios, rather than odds or prevalence ratios. The method is applied to the analysis of the prevalence of respiratory symptoms in 4395 children aged 7-9 years who are residents of Huddersfield (northern England), surveyed in the framework of the SAVIAH (Small Area Variations of Air Quality and Health) study. CONCLUSIONS: By considering saturated models including only sex as a covariate, direct comparison of crude and fitted parameters (odds, prevalence, and rate ratios) shows that, for short follow-up periods, the complementary log-log model is a valid alternative to logistic regression. More complex models including other covariates are also discussed.

Spatial statistical methods in environmental epidemiology: a critique.

Despite recent advances in the available statistical methods for geographical analysis, there are many constraints to their application in environmental epidemiology. These include problems of data availability and quality, especially the lack in most situations of environmental exposure measurements. Methods for disease 'cluster' investigation, point source exposures, small-area disease mapping and ecological correlation studies are critically reviewed, with the emphasis on practical applications and epidemiological interpretation. It is shown that, unless dealing with rare diseases, high specificity exposures and high relative risks, cluster investigation is unlikely to be fruitful, and is often complicated by the post hoc nature of such studies. However, it is recognized that in these circumstances proper assessment of the available data is often required as part of the public health response. Newly available methods, particularly in Bayesian statistics, offer an appropriate framework for geographical analysis and disease mapping. Again, it is uncertain whether they will give important clues as to aetiology, although they do give valuable description. Perhaps the most satisfactory approach is to test a priori hypotheses using a geographical database, although problems of interpretation remain.

Declining trends of male proportion at birth in Europe.

Declining trends in male proportion at birth observed in several Western countries might reflect widespread exposure to pollutants capable of interfering with human reproduction. In this study, the authors describe male live birth proportion trends in 23 European countries from 1950 to 1996 (total of 305 million live births). Overall, there was a significant linearly decreasing trend of 10 fewer males per 100,000 births each year, resulting in a loss of 73,462 boys during a 47-yr period. The proportion of male births during the first 3 yr of the study period was higher than in the last 3 yr in 18 countries (i.e., 78%). Decreasing trends, which varied in slope and shape, were observed in 11 countries; no significant trend was found in 8 countries, and male birth proportion increased in 4 countries. The results of this study confirmed that the proportion of male births is declining in Europe, and differences exist by region and country. Social and cultural aggregations of countries with decreasing trends suggest that sociodemographic characteristics might be more likely to explain trends than environmental exposures to chemicals. Investigators should evaluate this hypothesis to assess the usefulness of male birth proportion as a sentinel event.

[Territorial distribution of mortality from malignant tumors of the pleura in Italy]. / Distribuzione territoriale della mortalità per tumore maligno della pleura in Italia.

Mortality from malignant pleural neoplasms in Italy, 1980-87, was studied in order to detect areas at risk. The number of observed deaths occurring in each of the 8000 Italian municipalities was contrasted to the expected figure obtained from regional and/or national rates; whenever a significant increase, based on at least three observed cases, was detected, the municipality was included in the study. The main findings in Piedmont concern the city of Casale Monferrato, where an important asbestos cement factory is located, and some areas characterized by the presence of the textile industry. Genoa and other harbours of the northwestern coast, where important shipyards are located, were detected. In Lombardy an increased in risk concerning women was observed in several municipalities. Major increases in risk were seen in Venice. Trieste and Monfalcone, where important shipyards are located. In Tuscany, the highest risk was reported in Leghorn and surrounding areas; naval industry and chemical industries should be considered. In southern Italy, several cities with industrial harbours were shown to be at risk.

Cluster analysis and disease mapping--why, when, and how? A step by step guide.

Growing public awareness of environmental hazards has led to an increased demand for public health authorities to investigate geographical clustering of diseases. Although such cluster analysis is nearly always ineffective in identifying causes of disease, it often has to be used to address public concern about environmental hazards. Interpreting the resulting data is not straightforward, however, and this paper presents a guide for the non-specialist. The pitfalls include the fact that cluster analyses are usually done post hoc, and not as a result of a prior hypothesis. This is particularly true for investigations prompted by reported clusters, which have the inherent danger of overestimating the disease rate through "boundary shrinkage" of the population from which the cases are assumed to have arisen. In disease surveillance the problem of making multiple comparisons can be overcome by testing for clustering and autocorrelation. When rates of disease are illustrated in disease maps undue focus on areas where random fluctuation is greatest can be minimised by smoothing techniques. Despite the fact that cluster analyses rarely prove fruitful in identifying causation, they may-like single case reports-have the potential to generate new knowledge.

[Deprivation and mortality: a deprivation index suitable for geographical analysis of inequalities]. / Deprivazione e mortalità: un indice di deprivazione per l'analisi delle disuguaglianze su base geografica.

UNLABELLED: FOREGROUND: A national deprivation index suitable for geographical analysis of inequalities in health is not yet available in Italy, although the link between deprivation and health has been clearly demonstrated in our country in a number of studies. OBJECTIVES: 1) To describe a deprivation index in Italy at municipal level, based on the percentage of selected census variables (simple components) 2) To analyse general mortality according to deprivation categories at municipal level in Italy 3) To measure the size of ecological bias using the Turin Longitudinal Study. SETTING: Italy (1-2), Turin (3). MATERIALS: 1) 1991 census data base at municipal level 2) General mortality in Italy by municipality and age bands in 1990-92. 3) Turin Longitudinal study 1991-1995. METHODS: 1) Percentages of selected indicators of inequalities for all the 8.100 Italian municipalities present at 1991 census were calculated. Factorial analysis were performed in order to help in selecting the most valuable ones. The final choice led to five indicators (low education, unemployment, rented occupier housing, no indoor bathroom, lone parent with childhood). A simple additive index was computed using the method of the sum of normal standard deviates of each component 2) Correlation of indexes with mortality was performed; SMR for each deprivation category were computed; 3) Computation of the index at different levels: individual (one million individuals), census ward (3657 wards), statistic zone (92 statistic zones), two neighborough levels (23 and 10 neighboroughs) was conducted; differential analysis was performed for each level and index category, allowing for comparison among results, adjusting for age. MAIN RESULTS: Increasing deprivation was significantly associated with mortality from all causes: there was up to a 20 percent increase in mortality between the highest and lowest quintile. The relationship was linear with no apparent threshold. The slope of the relationship between deprivation and mortality varied among regions. Differentials in inequalities measured by individual and census tract level resulted to be very small; ecological bias arises when larger areas are taken into account. CONCLUSIONS: An area based measure of deprivation has proved a valuable tool in examining differentials in death and is likely to prove of continuing value to health authorities in planning the delivery of health care.

Asbestos-related mortality in Italy: a geographical approach.

The present contribution describes two studies of asbestos-related cancer mortality in Italy: an analysis of the geographical distribution of mortality from pleural neoplasms and an investigation into the relationship between pleural and lung cancer mortality in an Italian region, Piedmont. Mortality from malignant pleural neoplasms (ICD-IX Revision 163.0-163.9) has been studied in Italy in the 20 regions and the over 8000 municipalities for the years 1988-92: restriction of analysis to municipalities with at least three observed deaths and statistically significant increases led to identification of areas where occupational and/or environmental exposure to asbestos can have occurred. The analysis of pleural and lung cancer mortality was carried out for the years 1980-87 in Piedmont using an empirical Bayes method for small-area disease mapping; the results showed that the proportion of lung cancer mortality attributable to asbestos exposure was 5.6 and 5.7 percent respectively in men and women. While analyses of routinely collected data are no substitute for ad hoc individual based studies, notwithstanding the limitations of geographical approaches to the study of asbestos-related mortality, investigations carried out at the level of small area populations appear to provide informative results, which might be of value in terms of public health.

Risk of cancer after low doses of ionising radiation: retrospective cohort study in 15 countries.

OBJECTIVES: To provide direct estimates of risk of cancer after protracted low doses of ionising radiation and to strengthen the scientific basis of radiation protection standards for environmental, occupational, and medical diagnostic exposures. DESIGN: Multinational retrospective cohort study of cancer mortality. SETTING: Cohorts of workers in the nuclear industry in 15 countries. PARTICIPANTS: 407 391 workers individually monitored for external radiation with a total follow-up of 5.2 million person years. MAIN OUTCOME MEASUREMENTS: Estimates of excess relative risks per sievert (Sv) of radiation dose for mortality from cancers other than leukaemia and from leukaemia excluding chronic lymphocytic leukaemia, the main causes of death considered by radiation protection authorities. RESULTS: The excess relative risk for cancers other than leukaemia was 0.97 per Sv, 95% confidence interval 0.14 to 1.97. Analyses of causes of death related or unrelated to smoking indicate that, although confounding by smoking may be present, it is unlikely to explain all of this increased risk. The excess relative risk for leukaemia excluding chronic lymphocytic leukaemia was 1.93 per Sv (< 0 to 8.47). On the basis of these estimates, 1-2% of deaths from cancer among workers in this cohort may be attributable to radiation. CONCLUSIONS: These estimates, from the largest study of nuclear workers ever conducted, are higher than, but statistically compatible with, the risk estimates used for current radiation protection standards. The results suggest that there is a small excess risk of cancer, even at the low doses and dose rates typically received by nuclear workers in this study.

Empirical Bayes estimation of small area prevalence of non-rare conditions.

Geographical studies are becoming increasingly common in epidemiology. The problems of small area investigations are well known, and several methods are available for the estimation and mapping of disease risk across small areas, with the emphasis mainly on applications concerning rare disease incidence or mortality. An empirical Bayes method is proposed for small area estimation of the prevalence of non-rare conditions, whose variability is binomial and cannot be approximated by a Poisson model. It is the direct equivalent of a semi-parametric non-iterative moment estimation method proposed in the Poisson case. As an example, the geographical distribution of the prevalence of respiratory symptoms in schoolchildren across 71 small areas in Huddersfield, Northern England is studied. Whereas random variability causes the crude area-specific prevalences to be unstable, the posterior estimates, corrected towards overall or local means, are capable of highlighting genuine extra-binomial variability. The method is very simple and can readily be applied to the study of a number of common conditions.

Estimating the degree of heterogeneity between event rates using likelihood.

The observed variability between mortality or morbidity rates in epidemiologic studies is partly due to random fluctuations. The same is true for rate ratios relative to reference rates. A method for estimating the distribution of true rate ratios is applied to a data set of perinatal mortality in 515 small areas in the North West Thames Health Region, England, in the period 1986-1990. Combining the random Poisson variability with the assumption that the true rate ratios are drawn from a gamma distribution (a family of positive unimodal distributions) produces a negative binomial log-likelihood for the dispersion parameter of the gamma. The maximum likelihood estimate of this parameter and its confidence interval are then found via direct numerical methods; alternatively, the hypothesis of no heterogeneity is tested by a likelihood ratio. The standardized mortality ratios (SMRs) for the data have an empirical distribution with 5th percentile at 0 and 95th percentile at 1.92, but their true variability, as described by the 5th to 95th percentiles of the fitted gamma distribution, is from 0.72 to 1.32. The likelihood ratio test confirmed this result, rejecting the hypothesis that the true rates are homogeneous (p = 0.015). The method requires only modest computing resources and is useful when assessing the need for more detailed study.

Health impact assessment of air pollution: providing further evidence for public health action.

Many epidemiological studies have demonstrated the importance of air pollution as a risk factor and characterised dose-response relationships between health endpoints and pollutants. The association between particulate matter (PM) and health is generally regarded as causal, and a nonthreshold linear relationship with, for example, mortality and hospital admission has been observed in several settings. The ubiquitous PM air pollution is likely to have a large overall impact on human health, even if risks are relatively small. There have recently been a large number of papers reporting quantitative estimations of the health impact of PM on health, as measured by the proportion of excess events that are attributable to PM exposures in the general population, mainly in industrialised countries. For example, in the eight largest Italian cities it has been estimated that concentrations beyond 30 microg x m(-3) are responsible for about 3,500 extra deaths per year. A similar study has been carried out for France, Austria and Switzerland. These evaluations fill a knowledge gap between the laboratory and clinical studies on the pathophysiological mechanisms, the epidemiological research on the nature and strength of the association at the population level, and the risk management needs for developing appropriate preventive policies. Some limitations in the methodology deserve further research, however health impact assessment type studies are informative and effective tools of communication with the general public and policy makers.

Perinatal mortality in an English health region: geographical distribution and association with socio-economic factors.

Although the international and regional variability of perinatal mortality rates have been widely studied, less is known about the variability at the small-area level. The geographical distribution of perinatal mortality in the former North-West Thames Health Region, England, during 1981-90, and its association with small-area socio-economic factors, as measured by the Carstairs index of deprivation, were studied. Recently developed methods of analysis, including use of Bayesian statistics, were applied to obtain descriptive results and maps, and for fitting regression models that allowed for the presence of unmeasured risk factors. Significant heterogeneity (P < 0.001) of perinatal mortality across census wards and districts was found. The 5% of wards with the highest mortality experienced a risk more than 1.7 times that of the 5% with lowest mortality. Significant, positive association between deprivation and perinatal mortality was also found. Assuming causality, social differentials at the small-area level accounted for between 1.3% and 14.1% of all perinatal deaths, depending on which level of the Carstairs index was selected as reference. Although a proportion of such variability might be explained by social characteristics, a better understanding of the nature of the association is necessary.

Non-parametric maximum likelihood estimators for disease mapping.

A Non-Parametric Maximum Likelihood approach to the estimation of relative risks in the context of disease mapping is discussed and a NPML approximation to conditional autoregressive models is proposed. NPML estimates have been compared to other proposed solutions (Maximum Likelihood via Monte Carlo Scoring, Hierarchical Bayesian models) using real examples. Overall, the NPML autoregressive estimates (with weighted term) were closer to the Bayesian estimates. The exchangeable NPML model ranked immediately after, even if it implied a greater shrinkage, while the truncated auto-Poisson showed inadequate for disease mapping. The coefficients of the autoregressive term for the different mixtures have clear interpretations: in the breast cancer example, the larger cities in the region showed high rates and very low correlation with the neighbouring areas, while the less populated rural areas with low rates were strongly positively correlated each other. This pattern is expected since breast cancer is strongly correlated with parity and age at first birth, and the female population of the rural areas experienced a decline in fertility much later than those living in the larger cities. The leukemia example highlighted the failure of the Poisson-Gamma model and other general overdispersion tests to detect high risk areas under specific conditions. The NPML approach in Aitkin is very general, simple and flexible. However the user should be warned against the possibility of local maxima and the difficulty in detecting the optimal number of components. Special software (such as CAMAN or DismapWin) had been developed and should be recommended mainly to not experienced users.

Case-control study on cancer risk associated to residence in the neighbourhood of a petrochemical plant.

The aim of the present study is to investigate cancer mortality and residence in the neighbourhood of the petrochemical plant located in Brindisi, South-eastern Italy. Cases were all subjects resident in Brindisi and in three neighbouring municipalities who died in the study area in 1996-1997 from lung cancer, pleural neoplasm, bladder cancer and lymphohematopoietic malignancies. Controls were subjects resident in the same area and deceased in 1996-1997 for any cause except those listed for the cases. Next of kin's of all study subjects were visited by an interviewer who collected anamnestic information. The main residence of each subject, defined as the longest held residence with exclusion of the last 10 years, was reported on a digitalized map of the study area (MapInfo). The study included 144 cases and 176 controls; response rate was 98%. Residence within 2 km from the centre of the petrochemical plant was associated with a 3 fold increase of the Odds ratios (OR) for lung cancer, which did not reach statistical significance. Living close to the petrochemical plant was associated with moderate increases of OR for bladder cancer and lymphohematopoietic neoplasms which did not reach statistical significance. In conclusion the present study has shown moderate increases in risk for lung, bladder and lymphohematopoietic neoplasms in the population resident within 2 km from the centre of the petrochemical plant in Brindisi. These figures were confirmed after adjusting for smoking habit, occupation and school level. Random misclassification may have somehow resulted in risk underestimation.