A spatial indicator of environmental and climatic vulnerability in Rome.

BACKGROUND: Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies. METHODS: From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km2 in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM2.5, PM10, NO2, C6H6, SO2), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described. RESULTS: The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO2 in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index. CONCLUSIONS: A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

Growth and Metabolic Changes After Antiretroviral Initiation in South African Children.

BACKGROUND: Poor growth and metabolic disturbances remain concerns for children living with HIV (CLHIV). We describe the impact of viral load (VL) on growth and lipid outcomes in South African CLHIV <12 years initiating World Health Organization recommended first-line antiretroviral therapy (ART) from 2012 to 2015. METHODS: Z scores for length-for-age (LAZ), weight-for-age (WAZ) and body mass index-for-age were calculated. Lipids (total cholesterol, low-density lipoprotein and high-density lipoprotein) were measured. Hemoglobin A1C ≥5.8 was defined as at risk for type 2 diabetes. Mixed effects models were used to assess the association of VL at ART initiation with Z scores and lipids over time. RESULTS: Of 241 CLHIV, 151 (63%) were <3 years initiating LPV/r-based ART and 90 (37%) were ≥3 years initiating EFV-based ART. Among CLHIV <3 years, higher VL at ART initiation was associated with lower mean LAZ (ß: -0.30, P=0.03), WAZ (ß: -0.32, P=0.01) and low-density lipoprotein (ß: -6.45, P=0.03) over time. Among CLHIV ≥3, a log 10 increase in pretreatment VL was associated with lower mean LAZ (ß: -0.29, P=0.07) trending towards significance and lower WAZ (ß: -0.32, P=0.05) as well as with more rapid increases in LAZ (ß: 0.14 per year, P=0.01) and WAZ (ß: 0.19 per year, P=0.04). Thirty percent of CLHIV were at risk for type 2 diabetes at ART initiation. CONCLUSIONS: CLHIV initiating ART <3 years exhibited positive gains in growth and lipids, though high viremia at ART initiation was associated with persistently low growth and lipids, underscoring the need for early diagnosis and rapid treatment initiation. Future studies assessing the long-term cardiometabolic impact of these findings are warranted.

[Spatial analysis for detecting clusters of cases during the COVID-19 emergency in Rome and in the Lazio Region (Central Italy)]. / Analisi spaziale per l'identificazione di cluster di casi durante l'emergenza COVID-19 a Roma e nel Lazio.

BACKGROUND: one of the most affected European countries by the COVID-19 epidemic is Italy; data show the strong geographical heterogeneity of the epidemic. OBJECTIVES: to propose an analysis strategy to ascertain the non-random nature of the spatial spread of COVID-19 cases infection and identify any territorial aggregations, in order to enhance contact tracing activities in specific areas of the Lazio Region (Central Italy) and a large urban area as Rome. METHODS: all cases of COVID-19 of the Lazio Region notified to the Regional Service for Epidemiology, Surveillance, and Control of Infectious Diseases (Seresmi) with daily updates from the beginning of the epidemic to April 27, 2020 were considered. The analyses were carried out considering two periods (the first from the beginning of the epidemic to April 6 and the second from the beginning of the epidemic to April 27) and two different levels of spatial aggregation: the entire Lazio region excluding the Municipality of Rome, where the 377 municipalities represent the area units, and the Municipality of Rome, where the area units under study are the 155 urban areas (ZUR). The Scan statistic of Kulldorff was used to ascertain the non-random nature of the spatial spread of infected cases and to identify any territorial aggregations of cases of COVID-19 infection, using a retrospective spatial analysis in two overlapping periods. RESULTS: analysis was conducted at regional level in the two survey periods and revealed the presence of 7 localized clusters. In the Municipality of Rome, a single cluster (Historic Centre) was identified in the first period which includes 7 urban areas, while in the second period two distinct clusters (Omo and Farnesina) were observed. CONCLUSIONS: Scan statistics are an important surveillance tool for monitoring disease outbreaks during the active phase of the epidemic and a useful contribution to epidemiological surveillance during the COVID-19 epidemic in a specific territory.

Social network analysis to characterize women victims of violence.

BACKGROUND: In Europe, it is estimated that one third of women had experienced at least one physical or sexual violence after their 15. Taking into account the severe health consequences, the Emergency Department (ED), may offer an opportunity to recognize when an aggression is part of the spectrum of violence. This study applies Social Network analysis (SNA) to ED data in the Lazio region with the objective to identify patterns of diagnoses, within all the ED accesses of women experiencing an aggression, that are signals for gender-based violence against women. We aim to develop a risk assessment tool for ED professionals in order to strength their ability to manage victims of violence. METHODS: A cohort of 124,691 women aged 15-70 with an ED visit for aggression between 2003 and 2015 was selected and, for each woman, the ED history of diagnoses and traumas was reconstructed. SNA was applied on all these diagnoses and traumas, including also 9 specific violence diagnoses. SNA community detection algorithms and network centrality measures were used to detect diagnostic patterns more strongly associated to violence. A logistic model was developed to validate the capability of these patterns to predict the odds for a woman of having an history of violence. Model results were summed up into a risk chart. RESULTS: Among women experiencing an aggression, SNA identified four communities representing specific violence-related patterns of diagnoses. Diagnoses having a central role in the violence network were alcohol or substance abuse, pregnancy-related conditions and psychoses. These high-risk violence related patterns accounted for at most 20% of our cohort. The logistic model had good predictive accuracy and predictive power confirming that diagnosis patterns identified through the SNA are meaningful in the violence recognition. CONCLUSIONS: Routine ED data, analyzed using SNA, can be a first-line warning to recognize when an aggression related access is part of the spectrum of gender-based violence against women. Increasing the available number of predictors, such procedures may be proven to support ED staff in identifying early signs of violence to adequately support the victims and mitigate the harms.

The inter-annual variability of heat-related mortality in nine European cities (1990-2010).

BACKGROUND: The association between heat and daily mortality and its temporal variation are well known. However, few studies have analyzed the inter-annual variations in both the risk estimates and impacts of heat. The aim is to estimate inter-annual variations in the effect of heat for a fixed temperature range, on mortality in 9 European cities included in the PHASE (Public Health Adaptation Strategies to Extreme weather events) project for the period 1990-2010. The second aim is to evaluate overall summer effects and heat-attributable deaths for each year included in the study period, considering the entire air temperature range (both mild and extreme temperatures). METHODS: A city-specific daily time-series analysis was performed, using a generalized additive Poisson regression model, restricted to the warm season (April-September). To study the temporal variation for a fixed air temperature range, a Bayesian Change Point analysis was applied to the relative risks of mortality for a 2 °C increase over the 90th percentile of the city-specific distribution. The number of heat attributable deaths in each summer were also calculated for mild (reference to 95th percentile) and extreme heat (95th percentile to maximum value). RESULTS: A decline in the effects of heat over time was observed in Athens and Rome when considering a fixed interval, while an increase in effects was observed in Helsinki. The greatest impact of heat in terms of attributable deaths was observed in the Mediterranean cities (Athens, Barcelona and Rome) for extreme air temperatures. In the other cities the impact was mostly related to extreme years with 2003 as a record breaking year in Paris (+ 1900 deaths) and London (+ 1200 deaths). CONCLUSIONS: Monitoring the impact of heat over time is important to identify changes in population vulnerability and evaluate adaptation measures.

[Cluster statistical analysis in epidemiology]. / L'analisi statistica dei cluster in epidemiologia.

Statistical analysis represents a critical point in cluster analysis, because a methodology able to take into consideration the complexity of this analysis has not yet been developed. However, a common approach in statistical analysis of a suspected cluster is a necessary tool for public health operators who have to face population worries and requests. We propose an approach for the analysis of clusters and discuss the main limitations and strengths of the used methods. To this aim, we present, as a case study, the spatial clustering analysis of acute lymphoblastic leukaemia (ALL) cases among children in Rome between 2000 and 2011. Cases were selected through a record linkage of three different health and administrative current databases. Cases were geocoded at 3 spatial resolutions: 20 districts (D), 155 neighbourhoods (NB), and 5,812 census areas (CA). Indirect standardized incidence ratios (SIR) were computed for the NBs with Rome average incidence rate (IR) of ALL as reference and then smoothed by Besag-York-Mollie (BYM) model. General clustering was tested by Tango statistics, whereas localized clustering was detected through two different statistics: Besag and Newell's, and Kulldorf and Nagarwalla's. Both general and local clustering were tested at city level, using NBs as area units, and at district level, using CAs as area units. We identified 194 ALL cases in the 0-14 age group (IR: 43.7x1,000,000). SIRs ranged between 0.00 and 18.1 among NBs. After smoothing, a significant excess of cases was identified only in 3 Ds. At city level, no general clustering was highlighted (Tango's test p-value: 0.08), while both tests for local clustering were significant in one of the 3 Ds with the highest SIRs. Finally, at district level, although no general cluster was founded, a total of 7 clusters were identified in the 3 Ds with the highest SIRs, each cluster being composed by a number of cases ranging between 2 and 6. Results indicate the presence of clusters in some areas of Rome, which are evident only when the finest spatial resolution is used. This standardised procedure is an important tool to properly analyse potential clusters.

Changes in Susceptibility to Heat During the Summer: A Multicountry Analysis.

Few studies have examined the variation in mortality risk associated with heat during the summer. Here, we apply flexible statistical models to investigate the issue by using a large multicountry data set. We collected daily time-series data of temperature and mortality from 305 locations in 9 countries, in the period 1985-2012. We first estimated the heat-mortality relationship in each location with time-varying distributed lag non-linear models, using a bivariate spline to model the exposure-lag-response over lag 0-10. Estimates were then pooled by country through multivariate meta-analysis. Results provide strong evidence of a reduction in risk over the season. Relative risks for the 99th percentile versus the minimum mortality temperature were in the range of 1.15-2.03 in early summer. In late summer, the excess was substantially reduced or abated, with relative risks in the range of 0.97-1.41 and indications of wider comfort ranges and higher minimum mortality temperatures. The attenuation is mainly due to shorter lag periods in late summer. In conclusion, this multicountry analysis suggests a reduction of heat-related mortality risk over the summer, which can be attributed to several factors, such as true acclimatization, adaptive behaviors, or harvesting effects. These findings may have implications on public health policies and climate change health impact projections.

Changes in the Effect of Heat on Mortality in the Last 20 Years in Nine European Cities. Results from the PHASE Project.

The European project PHASE aims to evaluate patterns of change in the temperature-mortality relationship and in the number of deaths attributable to heat in nine European cities in two periods, before and after summer 2003 (1996-2002 and 2004-2010). We performed age-specific Poisson regression models separately in the two periods, controlling for seasonality, air pollution and time trends. Distributed lag non-linear models were used to estimate the Relative Risks of daily mortality for increases in mean temperature from the 75th to 99th percentile of the summer distribution for each city. In the recent period, a reduction in the mortality risk associated to heat was observed only in Athens, Rome and Paris, especially among the elderly. Furthermore, in terms of heat-attributable mortality, 985, 787 and 623 fewer deaths were estimated, respectively, in the three cities. In Helsinki and Stockholm, there is a suggestion of increased heat effect. Noteworthy is that an effect of heat was still present in the recent years in all cities, ranging from +11% to +35%. In Europe, considering the warming observed in recent decades and population ageing, effective intervention measures should be promoted across countries, especially targeting vulnerable subgroups of the population with lower adaptive resources.

Temporal Variation in Heat-Mortality Associations: A Multicountry Study.

BACKGROUND: Recent investigations have reported a decline in the heat-related mortality risk during the last decades. However, these studies are frequently based on modeling approaches that do not fully characterize the complex temperature-mortality relationship, and are limited to single cities or countries. OBJECTIVES: We assessed the temporal variation in heat-mortality associations in a multi-country data set using flexible modelling techniques. METHODS: We collected data for 272 locations in Australia, Canada, Japan, South Korea, Spain, the United Kingdom, and the United States, with a total 20,203,690 deaths occurring in summer months between 1985 and 2012. The analysis was based on two-stage time-series models. The temporal variation in heat-mortality relationships was estimated in each location with time-varying distributed lag nonlinear models, expressed through an interaction between the transformed temperature variables and time. The estimates were pooled by country through multivariate meta-analysis. RESULTS: Mortality risk due to heat appeared to decrease over time in several countries, with relative risks associated to high temperatures significantly lower in 2006 compared with 1993 in the United States, Japan, and Spain, and a nonsignificant decrease in Canada. Temporal changes are difficult to assess in Australia and South Korea due to low statistical power, and we found little evidence of variation in the United Kingdom. In the United States, the risk seems to be completely abated in 2006 for summer temperatures below their 99th percentile, but some significant excess persists for higher temperatures in all the countries. CONCLUSIONS: We estimated a statistically significant decrease in the relative risk for heat-related mortality in 2006 compared with 1993 in the majority of countries included in the analysis. CITATION: Gasparrini A, Guo Y, Hashizume M, Kinney PL, Petkova EP, Lavigne E, Zanobetti A, Schwartz JD, Tobias A, Leone M, Tong S, Honda Y, Kim H, Armstrong BG. 2015. Temporal variation in heat-mortality associations: a multicountry study. Environ Health Perspect 123:1200-1207; http://dx.doi.org/10.1289/ehp.1409070.

Mortality risk attributable to high and low ambient temperature: a multicountry observational study.

BACKGROUND: Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. METHODS: We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature-mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles. FINDINGS: We analysed 74,225,200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43-7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80-90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02-7·49) than by heat (0·42%, 0·39-0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84-0·87) of total mortality. INTERPRETATION: Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. FUNDING: UK Medical Research Council.

Global variation in the effects of ambient temperature on mortality: a systematic evaluation.

BACKGROUND: Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously. METHODS: We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country. RESULTS: The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long. CONCLUSIONS: People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context of climate change.

Attributable risk from distributed lag models.

BACKGROUND: Measures of attributable risk are an integral part of epidemiological analyses, particularly when aimed at the planning and evaluation of public health interventions. However, the current definition of such measures does not consider any temporal relationships between exposure and risk. In this contribution, we propose extended definitions of attributable risk within the framework of distributed lag non-linear models, an approach recently proposed for modelling delayed associations in either linear or non-linear exposure-response associations. METHODS: We classify versions of attributable number and fraction expressed using either a forward or backward perspective. The former specifies the future burden due to a given exposure event, while the latter summarizes the current burden due to the set of exposure events experienced in the past. In addition, we illustrate how the components related to sub-ranges of the exposure can be separated. RESULTS: We apply these methods for estimating the mortality risk attributable to outdoor temperature in two cities, London and Rome, using time series data for the periods 1993-2006 and 1992-2010, respectively. The analysis provides estimates of the overall mortality burden attributable to temperature, and then computes the components attributable to cold and heat and then mild and extreme temperatures. CONCLUSIONS: These extended definitions of attributable risk account for the additional temporal dimension which characterizes exposure-response associations, providing more appropriate attributable measures in the presence of dependencies characterized by potentially complex temporal patterns.

A time series study on the effects of heat on mortality and evaluation of heterogeneity into European and Eastern-Southern Mediterranean cities: results of EU CIRCE project.

BACKGROUND: The Mediterranean region is particularly vulnerable to the effect of summer temperature.Within the CIRCE project this time-series study aims to quantify for the first time the effect of summer temperature in Eastern-Southern Mediterranean cities and compared it with European cities around the Mediterranean basin, evaluating city characteristics that explain between-city heterogeneity. METHODS: The city-specific effect of maximum apparent temperature (Tappmax) was assessed by Generalized Estimation Equations, assuming a linear threshold model. Then, city-specific estimates were included in a random effect meta-regression analysis to investigate the effect modification by several city characteristics. RESULTS: Heterogeneity in the temperature-mortality relationship was observed among cities. Thresholds recorded higher values in the warmest cities of Tunis (35.5°C) and Tel-Aviv (32.8°C) while the effect of Tappmax above threshold was greater in the European cities. In Eastern-Southern Mediterranean cities a higher effect was observed among younger age groups (0-14 in Tunis and 15-64 in Tel-Aviv and Istanbul) in contrast with the European cities where the elderly population was more vulnerable. Climate conditions explained most of the observed heterogeneity and among socio-demographic and economic characteristics only health expenditure and unemployment rate were identified as effect modifiers. CONCLUSIONS: The high vulnerability observed in the young populations in Eastern-Southern Mediterranean cities represent a major public health problem. Considering the large political and economic changes occurring in this region as well future temperature increase due to climate change, it is important to strengthen research and public health efforts in these Mediterranean countries.

The impact of the February 2012 cold spell on health in Italy using surveillance data.

In February 2012 Italy was hit by an exceptional cold spell with extremely low temperatures and heavy snowfall. The aim of this work is to estimate the impact of the cold spell on health in the Italian cities using data from the rapid surveillance systems. In Italy, a national mortality surveillance system has been operational since 2004 in 34 cities for the rapid monitoring of daily mortality. Data from this system were used to evaluate the impact of the February 2012 cold spell on mortality shortly after the occurrence of the event. Furthermore, a cause-specific analysis was conducted in Roma using the Regional Mortality Registry and the emergency visits (ER) surveillance system. Cold spell episodes were defined as days when mean temperatures were below the 10(th) percentile of February distribution for more than three days. To estimate the impact of the cold spell, excess mortality was calculated as the difference between observed and daily expected values. An overall 1578 (+25%) excess deaths among the 75+ age group was recorded in the 14 cities that registered a cold spell in February 2012. A statistically significant excess in mortality was observed in several cities ranging from +22% in Bologna to +58% in Torino. Cause-specific analysis conducted in Roma showed a statistically significant excess in mortality among the 75+ age group for respiratory disease (+64%), COPD (+57%), cardiovascular disease +20% ischemic heart disease (14%) and other heart disease (+33%). Similar results were observed for ER visits. Surveillance systems need to become are a key component of prevention plans as they can help improve public health response and are a valid data source to rapidly quantify the impact on health. Cold-related mortality is still an important issue and should not be underestimated by public health Authorities.

Changes in the effects of heat on mortality among the elderly from 1998-2010: results from a multicenter time series study in Italy.

BACKGROUND: This multicenter study is aimed at estimating changes in the effect of high temperatures on elderly mortality before and after the 2003 heat waves and following the introduction of heat prevention activities. METHODS: A total of sixteen cities were included in the study. City-specific relationships between maximum apparent temperature (MAT) and elderly daily mortality before (1998-2002) and after (2006-2010) intervention were modelled through non-linear distributed lag models and estimates were combined using a random effect meta-analysis. We estimated the percentage change in daily mortality for 3°C variations in MAT above the 25th percentile of the June city-specific 1998-2002 distribution. A time-varying analysis was carried out to describe intra-seasonal variations in the two periods. RESULTS: We observed a reduction in high temperatures' effect post intervention; the greatest reduction was for increases in temperature from 9°C to 12°C above the 25th percentile, with a decrease from +36.7% to +13.3%. A weak effect was observed for temperatures up to 3°C above the 25th percentile only after. Changes were month-specific with a reduction in August and an increase in May, June and September in 2006-2010. CONCLUSIONS: A change in the temperature-mortality relationship was observed, attributable to variations in temperature distributions during summer and to the introduction of adaptation measures. The reduction in the effect of high temperature suggests that prevention programs can mitigate the impact. An effect of lower temperature remains, indicating a relevant impact of temperature at the beginning of summer when the population has not yet adapted and intervention activities are not fully operational.

Surveillance of summer mortality and preparedness to reduce the health impact of heat waves in Italy.

Since 2004, the Italian Department for Civil Protection and the Ministry of Health have implemented a national program for the prevention of heat-health effects during summer, which to-date includes 34 major cities and 93% of the residents aged 65 years and over. The Italian program represents an important example of an integrated approach to prevent the impact of heat on health, comprising Heat Health Watch Warning Systems, a mortality surveillance system and prevention activities targeted to susceptible subgroups. City-specific warning systems are based on the relationship between temperature and mortality and serve as basis for the modulation of prevention measures. Local prevention activities, based on the guidelines defined by the Ministry of Health, are constructed around the infrastructures and services available. A key component of the prevention program is the identification of susceptible individuals and the active surveillance by General Practitioners, medical personnel and social workers. The mortality surveillance system enables the timely estimation of the impact of heat, and heat waves, on mortality during summer as well as to the evaluation of warning systems and prevention programs. Considering future predictions of climate change, the implementation of effective prevention programs, targeted to high risk subjects, become a priority in the public health agenda.