Help-Seeking Behavior during Elevated Temperature in Chinese Population

The negative impact of extreme temperatures on health is well-established. Individual help-seeking behavior, however, may mitigate the extent of morbidity and mortality during elevated temperatures. This study examines individual help-seeking behavior during periods of elevated temperatures among a Chinese population. Help-seeking patterns and factors that influence behavior will be identified so that vulnerable subgroups may be targeted for health protection during heat crises. A retrospective time-series Poisson generalized additive model analysis, using meteorological data of Hong Kong Observatory and routine emergency help call data from The Hong Kong Senior Citizen Home Safety Association during warm seasons (June–September) 1998–2007, was conducted. A “U”-shaped association was found between daily emergency calls and daily temperature. About 49% of calls were for explicit health-related reasons including dizziness, shortness of breath, and general pain. The associate with maximum temperature was statistically significant (p = 0.034) with the threshold temperature at which the frequency of health-related calls started to increase being around 30–32°C. Mean daily relative humidity (RH) also had a significant U-shaped association with daily emergency health-related calls with call frequency beginning to increase with RH greater than 70–74% (10–25% of the RH distribution). Call frequency among females appeared to be more sensitive to high temperatures, with a threshold between 28.5°C and 30.5°C while calls among males were more sensitive to cold temperatures (threshold 31.5–33.5°C). Results indicate differences in community help-seeking behavior at elevated temperatures. Potential programs or community outreach services might be developed to protect vulnerable subgroups from the adverse impact of elevated temperatures

Effect Modification of the Association between Short-term Meteorological Factors and Mortality by Urban Heat Islands in Hong Kong

Background Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. Method An urban heat island index (UHII) was calculated for each of Hong Kong’s 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Results Mean temperatures (lags 0–4) above 29°C and low mean wind speeds (lags 0–4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1°C rise above 29°C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: −2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5th percentile vs. 95th percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a −0.3% (95% CI: −3.2%, 2.6%) change in low UHII areas. Conclusion The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions

The Population Genetics of Pseudomonas aeruginosa Isolates from Different Patient Populations Exhibits High-Level Host Specificity

Objective To determine whether highly prevalent P. aeruginosa sequence types (ST) in Dutch cystic fibrosis (CF) patients are specifically linked to CF patients we investigated the population structure of P. aeruginosa from different clinical backgrounds. We first selected the optimal genotyping method by comparing pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and multilocus variable number tandem-repeat analysis (MLVA). Methods Selected P. aeruginosa isolates (n = 60) were genotyped with PFGE, MLST and MLVA to determine the diversity index (DI) and congruence (adjusted Rand and Wallace coefficients). Subsequently, isolates from patients admitted to two different ICUs (n = 205), from CF patients (n = 100) and from non-ICU, non-CF patients (n = 58, of which 19 were community acquired) were genotyped with MLVA to determine distribution of genotypes and genetic diversity. Results Congruence between the typing methods was >79% and DIs were similar and all >0.963. Based on costs, ease, speed and possibilities to compare results between labs an adapted MLVA scheme called MLVA9-Utrecht was selected as the preferred typing method. In 363 clinical isolates 252 different MLVA types (MTs) were identified, indicating a highly diverse population (DI = 0.995; CI = 0.993–0.997). DI levels were similarly high in the diverse clinical sources (all >0.981) and only eight genotypes were shared. MTs were highly specific (>80%) for the different patient populations, even for similar patient groups (ICU patients) in two distinct geographic regions, with only three of 142 ICU genotypes detected in both ICUs. The two major CF clones were unique to CF patients. Conclusion The population structure of P. aeruginosa isolates is highly diverse and population specific without evidence for a core lineage in which major CF, hospital or community clones co-cluster. The two genotypes highly prevalent among Dutch CF patients appeared unique to CF patients, suggesting specific adaptation of these clones to the CF lung

Effects of apparent temperature on daily mortality in Lisbon and Oporto, Portugal

<p>Abstract</p> <p>Background</p> <p>Evidence that elevated temperatures can lead to increased mortality is well documented, with population vulnerability being location specific. However, very few studies have been conducted that assess the effects of temperature on daily mortality in urban areas in Portugal.</p> <p>Methods</p> <p>In this paper time-series analysis was used to model the relationship between mean apparent temperature and daily mortality during the warm season (April to September) in the two largest urban areas in Portugal: Lisbon and Oporto. We used generalized additive Poisson regression models, adjusted for day of week and season.</p> <p>Results</p> <p>Our results show that in Lisbon, a 1°C increase in mean apparent temperature is associated with a 2.1% (95%CI: 1.6, 2.5), 2.4% (95%CI: 1.7, 3.1) and 1.7% (95%CI: 0.1, 3.4) increase in all-causes, cardiovascular, and respiratory mortality, respectively. In Oporto the increase was 1.5% (95%CI: 1.0, 1.9), 2.1% (95%CI: 1.3, 2.9) and 2.7% (95%CI: 1.2, 4.3) respectively. In both cities, this increase was greater for the group >65 years.</p> <p>Conclusion</p> <p>Even without extremes in apparent temperature, we observed an association between temperature and daily mortality in Portugal. Additional research is needed to allow for better assessment of vulnerability within populations in Portugal in order to develop more effective heat-related morbidity and mortality public health programs.</p