Marco Morabito

Weather-Related Changes in 24-Hour Blood Pressure Profile. Effects of Age and Implications for Hypertension Management

A downward titration of antihypertensive drug regimens in summertime is often performed on the basis of seasonal variations of clinic blood pressure (BP). However, little is known about the actual interaction between outdoor air temperature and the effects of antihypertensive treatment on ambulatory BP. The combined effects of aging, treatment, and daily mean temperature on clinic and ambulatory BP were investigated in 6404 subjects referred to our units between October 1999 and December 2003. Office and mean 24-hour systolic BP, as well as morning pressure surge, were significantly lower in hot (>90th percentiles of air temperature; 136±19, 130±14, and 33.3±16.1 mm Hg; P<0.05 for all), and higher in cold (<10th percentiles) days (141±12, 133±11, and 37.3±9.5 mm Hg; at least P<0.05 for all) when compared with intermediate days (138±18, 132±14, and 35.3±15.4 mm Hg). At regression analysis, 24-hour and daytime systolic pressure were inversely related to temperature (P<0.01 for all). Conversely, nighttime systolic pressure was positively related to temperature (P<0.02), with hot days being associated with higher nighttime pressure. Air temperature was identified as an independent predictor of nighttime systolic pressure increase in the group of elderly treated hypertensive subjects only. No significant relationship was found between air temperature and heart rate. Our results show for the first time that hot weather is associated with an increase in systolic pressure at night in treated elderly hypertensive subjects. This may be because of a nocturnal BP escape from the effects of a lighter summertime drug regimen and may have important implications for seasonal modulation of antihypertensive treatment.

Role of Endothelin-1 in Exposure to High Altitude Acute Mountain Sickness and Endothelin-1 (ACME-1) Study

Background— The degree of pulmonary hypertension in healthy subjects exposed to acute hypobaric hypoxia at high altitude was found to be related to increased plasma endothelin (ET)-1. The aim of the present study was to investigate the effects of ET-1 antagonism on pulmonary hypertension, renal water, and sodium balance under acute and prolonged exposure to high-altitude–associated hypoxia. Methods and Results— In a double-blind fashion, healthy volunteers were randomly assigned to receive bosentan (62.5 mg for 1 day and 125 mg for the following 2 days; n=10) or placebo (n=10) at sea level and after rapid ascent to high altitude (4559 m). At sea level, bosentan did not induce any significant changes in hemodynamic or renal parameters. At altitude, bosentan induced a significant reduction of systolic pulmonary artery pressure (21±7 versus 31±7 mm Hg, P<0.03) and a mild increase in arterial oxygen saturation versus placebo after just 1 day of treatment. However, both urinary volume and free water clearance (H2OCl/glomerular filtration rate) were significantly reduced versus placebo after 2 days of ET-1 antagonism (1100±200 versus 1610±590 mL; −6.7±3.5 versus −1.8±4.8 mL/min, P<0.05 versus placebo for both). Sodium clearance and segmental tubular function were not significantly affected by bosentan administration. Conclusions— The present results indicate that the early beneficial effect of ET-1 antagonism on pulmonary blood pressure is followed by an impairment in volume adaptation. These findings must be considered for the prevention and treatment of acute mountain sickness.

Seasonal blood pressure changes: an independent relationship with temperature and daylight hours.

Seasonal blood pressure (BP) changes have been found to be related to either outdoor or indoor temperature. No information regarding the independent effects of temperature measured proximally to the patient, the personal-level environmental temperature (PET), is available. Inclusion of daylight hours in multivariate analysis might allow exploring the independent interaction of BP with seasonality. To investigate whether ambulatory BP monitoring is affected by PET or by seasonality, 1897 patients referred to our hypertension units underwent ambulatory BP monitoring with a battery-powered temperature data logger fitted to the carrying pouch of the monitor. Predictors of 24-hour daytime and nighttime BP and of morning BP surge were investigated with a multivariate stepwise regression model, including age, sex, body mass index, antihypertensive treatment, office BP, ambulatory heart rate, PET, relative humidity, atmospheric pressure, and daylight hours as independent variables. At adjusted regression analysis, daytime systolic BP was negatively related to PET (−0.14; 95% confidence interval, −0.25 to −0.02); nighttime BP was positively related to daylight hours (0.63; 0.37–0.90); and morning BP surge was negatively related to daylight hours (−0.54; −0.87 to −0.21). These results provide new evidence that PET and seasonality (daylight hours) are 2 independent predictors of ambulatory BP monitoring.Seasonal blood pressure (BP) changes have been found to be related to either outdoor or indoor temperature. No information regarding the independent effects of temperature measured proximally to the patient, the personal-level environmental temperature (PET), is available. Inclusion of daylight hours in multivariate analysis might allow exploring the independent interaction of BP with seasonality. To investigate whether ambulatory BP monitoring is affected by PET or by seasonality, 1897 patients referred to our hypertension units underwent ambulatory BP monitoring with a battery-powered temperature data logger fitted to the carrying pouch of the monitor. Predictors of 24-hour daytime and nighttime BP and of morning BP surge were investigated with a multivariate stepwise regression model, including age, sex, body mass index, antihypertensive treatment, office BP, ambulatory heart rate, PET, relative humidity, atmospheric pressure, and daylight hours as independent variables. At adjusted regression analysis, daytime systolic BP was negatively related to PET (−0.14; 95% confidence interval, −0.25 to −0.02); nighttime BP was positively related to daylight hours (0.63; 0.37–0.90); and morning BP surge was negatively related to daylight hours (−0.54; −0.87 to −0.21). These results provide new evidence that PET and seasonality (daylight hours) are 2 independent predictors of ambulatory BP monitoring. # Novelty and Significance {#article-title-25}

Innovative Approaches Helpful to Enhance Knowledge on Weather-Related Stroke Events Over a Wide Geographical Area and a Large Population

Background and Purpose— Results on the effect of weather on stroke occurrences are still confusing and controversial. The aim of this study was to retrospectively investigate in Tuscany (central Italy) the weather-related stroke events through the use of an innovative source of weather data (Reanalysis) together with an original statistical approach to quantify the prompt/delayed health effects of both cold and heat exposures. Methods— Daily stroke hospitalizations and meteorologic data from the Reanalysis 2 Achieve were obtained for the period 1997 to 2007. Generalized linear and additive models and an innovative modeling approach, the constrained segmented distributed lag model, were applied. Results— Both daily averages and day-to-day changes of air temperature and geopotential height (a measure that approximates the mean surface pressure) were selected as independent predictors of all stroke occurrences. In particular, a 5°C temperature decrease was associated with 16.5% increase of primary intracerebral hemorrhage of people ≥65 years of age. A general short-term cold effect on hospitalizations limited to 1 week after exposure was observed and, for the first time, a clear harvesting effect (deficit of hospitalization) for cold-related primary intracerebral hemorrhage was described. Day-to-day changes of meteorologic parameters disclosed characteristic U- and J-shaped relationships with stroke occurrences. Conclusions— Thanks to the intrinsic characteristic of Reanalysis, these results might simply be implemented in an operative forecast system regarding weather-related stroke events with the aim to develop preventive health plans.

A synoptic approach to weather conditions discloses a relationship with ambulatory blood pressure in hypertensives.

BACKGROUND Higher blood pressure (BP) values in cold than in hot months has been documented in hypertensives. These changes may potentially contribute to the observed excess winter cardiovascular mortality. However, the association with weather has always been investigated by considering the relationship with a single variable rather than considering the combination of ground weather variables characterizing a specific weather pattern (air mass (AM)). METHODS We retrospectively investigate in Florence (Italy) the relationship between BP and specific AMs in hypertensive subjects (n = 540) referred to our Hypertension Unit for 24-h ambulatory BP monitoring during the period of the year characterized by the highest weather variability (winter). Five different winter daily AMs were classified according to the combination of ground weather data (air temperature, cloud cover, relative humidity, atmospheric pressure, wind speed, and direction). RESULTS Multiple variable analysis selected the AM as a significant predictor of mean 24-h BP (P < 0.01 for diastolic BP (DBP) and P < 0.05 for systolic BP (SBP)), daytime DBP (P < 0.001) and nighttime BP (P < 0.01 for both SBP and DBP), with higher BP values observed in cyclonic (unstable, cloudy, and mild weather) than in anticyclonic (settled, cloudless, and cold weather) days. When the association with 2-day sequences of AMs was considered, an increase in ambulatory BP followed a sudden day-to-day change of weather pattern going from anticyclonic to cyclonic days. CONCLUSIONS The weather considered as a combination of different weather variables may affect BP. The forecast of a sudden change of AM could provide important information helpful for hypertensives during winter.

Air temperature-related human health outcomes: current impact and estimations of future risks in Central Italy.

The association between air temperature and human health is described in detail in a large amount of literature. However, scientific publications estimating how climate change will affect the populations health are much less extensive. In this study current evaluations and future predictions of the impact of temperature on human health in different geographical areas have been carried out. Non-accidental mortality and hospitalizations, and daily average air temperatures have been obtained for the 1999-2008 period for the ten main cities in Tuscany (Central Italy). High-resolution city-specific climatologic A1B scenarios centered on 2020 and 2040 have been assessed. Generalized additive and distributed lag models have been used to identify the relationships between temperature and health outcomes stratified by age: general adults (<65), elderly (aged 65-74) and very elderly (≥75). The cumulative impact (over a lag-period of 30 days) of the effects of cold and especially heat, was mainly significant for mortality in the very elderly, with a higher impact on coastal plain than inland cities: 1 °C decrease/increase in temperature below/above the threshold was associated with a 2.27% (95% CI: 0.17-4.93) and 15.97% (95% CI: 7.43-24.51) change in mortality respectively in the coastal plain cities. A slight unexpected increase in short-term cold-related mortality in the very elderly, with respect to the baseline period, is predicted for the following years in half of the cities considered. Most cities also showed an extensive predicted increase in short-term heat-related mortality and a general increase in the annual temperature-related elderly mortality rate. These findings should encourage efforts to implement adaptation actions conducive to policy-making decisions, especially for planning short- and long-term health intervention strategies and mitigation aimed at preventing and minimizing the consequences of climate change on human health.

The impact of built-up surfaces on land surface temperatures in Italian urban areas

Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (p<0.001) between built-up surfaces and spatial LST variations were observed in all the cities studied, with a higher impact during the warm/hot period than in the cool/cold ones. Daytime and nighttime LST slope patterns depend on the city size and relative urban morphology. If implemented in the existing city plan, the urban maps of built-up-surface-related LST developed in this study might be able to support more sustainable urban land management practices by identifying the critical areas (Hot-Spots) that would benefit most from mitigation actions by local authorities, land-use decision makers, and urban planners.

Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities

Background Short-term impacts of high temperatures on the elderly are well known. Even though Italy has the highest proportion of elderly citizens in Europe, there is a lack of information on spatial heat-related elderly risks. Objectives Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥65). Methods A long time-series (2001–2013) of remote sensing MODIS data, averaged over the summer period for eleven major Italian cities, were downscaled to obtain high spatial resolution (100 m) daytime and night-time land surface temperatures (LST). LST was estimated pixel-wise by applying two statistical model approaches: 1) the Linear Regression Model (LRM); 2) the Generalized Additive Model (GAM). Total and elderly population density data were extracted from the Joint Research Centre population grid (100 m) from the 2001 census (Eurostat source), and processed together using “Crichton’s Risk Triangle” hazard-risk methodology for obtaining a Heat-related Elderly Risk Index (HERI). Results The GAM procedure allowed for improved daytime and night-time LST estimations compared to the LRM approach. High-resolution maps of daytime and night-time HERI levels were developed for inland and coastal cities. Urban areas with the hazardous HERI level (very high risk) were not necessarily characterized by the highest temperatures. The hazardous HERI level was generally localized to encompass the city-centre in inland cities and the inner area in coastal cities. The two most dangerous HERI levels were greater in the coastal rather than inland cities. Conclusions This study shows the great potential of combining geospatial technologies and spatial demographic characteristics within a simple and flexible framework in order to provide high-resolution urban mapping of daytime and night-time HERI. In this way, potential areas for intervention are immediately identified with up-to-street level details. This information could support public health operators and facilitate coordination for heat-related emergencies.

Environmental temperature and thermal indices: What is the most effective predictor of heat-related mortality in different geographical contexts?

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (≥75 years) who died in inland and coastal cities from 2006 to 2008 (May–October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress.

Urban morbidity in summer: ambulance dispatch data, periodicity and weather

Over recent years the impact of weather on human health has become more severe, especially for people living in urban areas. Even though many studies have analysed the impact of weather on human mortality, few have quantified the impact of heat on morbidity, including ambulance response calls. In this study, 13,354 calls collected in the city of Florence (Italy) during summer were analyzed by month, day of the week, hour, and time slot of the day. An objective air mass classification was used to classify days and time slots with similar weather characteristics and a multiple variable analysis was applied to evaluate the relationship between emergency calls and weather. A positive trend was observed in the morning and a negative one during the night for all emergency calls, but only for food poisoning and alcoholic diseases. Calls for cardiovascular events increased in the morning and on hot days. Calls for psychiatric disorders rose significantly with temperature during the afternoon. The total number of calls and those for alcoholic diseases rose during the hottest nights. Our results, which show a clear relationship between ambulance response calls, periodicity, and weather, could contribute to an understanding the impact of weather on morbidity.