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  • We conducted a retrospective cohort study comprising adult patients admitted to Soroka University Medical Center (SUMC) with a primary diagnosis of acute coronary syndrome (ACS); (ICD-9 codes 411.81(ACS), 411.1(unstable angina, UA), 410.9,410 (acute myocardial infarction (AMI), non ST elevation myocardial infarction (NSTEMI), ST elevation myocardial infarction (STEMI)) between 2001 and 2010. SUMC is the only medical center in this area serving a population of approximately 700,000 as the primary hospital and nearly 1 million as a tertiary hospital. The study area is inhabited by two main ethnic groups: predominantly urban Jews (69%) and rural Bedouin Arabs (31%). The following patient level data were obtained using the centralized electronic medical records database: diabetes (ICD-9 code 250), history of MI (ICD-9 code 410–414), hypertension (ICD-9 code), chronic obstructive lung disease (COPD) (ICD-9 code 490, 491, 492, 496) and socio-demographic data such as gender, age and ethnicity (Jews vs. Bedouin Arabs). The study was approved by the institutional review board of Soroka University Medical Center. Patient information was anonymized and de-identified prior to analysis, therefore written informed consent was not obtained. Data for the study period included PM10 concentrations (μg/ m3), NO2 (μg/m3), meteorological parameters (temperature (CO) and relative humidity (%)) obtained from monitor station in Be'er-Sheva operated by the Ministry of Environmental Protection. This is the only monitoring station in the area recording all pollutants simultaneously in 20 minute intervals. The monitoring station is located in a typical neighborhood in the center of Be’er-Sheba (the city area is about 20 km2). Thus, we have limited our population to reside within 20km radius. Seasons were defined according to Alpert et al. :[16] winter (December 7-March 30), summer (May 31-September 22) each last about 4 months (3 months and 23 days), autumn (September 23-December 6) and spring (March 31-May 30) each lasts only 2 months (75 days and 61 days, respectively). The primary source of PM10 pollution in the region is non-anthropogenic. Most of the dust storms in the Negev region originate from the North Africa. Strong dust storms can last from several hours to few days. The daily average concentration of atmospheric PM10 can reach more than 2000 μg/ m3, with hourly concentrations as high as 5000 μg m3. We defined a dust storm (DS) day as a day with an averaged PM10 concentration that was two standard deviations (SD) above the background value. [14]The background value was calculated on the basis of the average PM10 concentration for 12-hour period (from 6 am to 6 pm) during the summer season (dust free period). It reflected the background level inclusive of non-anthropogenic and anthropogenic sourced particles. [17] Furthermore, we have validated the definition of dust storm by examination in details of the back-trajectories and synoptic conditions during the dust day to confirm that the origins of the dust were external to the region. The resulting threshold value for a dust day was 71 μg/ m3. [14] The statistical analysis involved two steps. First, generalized additive Poisson regression models (GAM) were used to test a possible non-linear association of PM10 on incidence of ACS. To adjust for seasons and other temporal effects in GAM models, we used a non-linear terms with penalized splines for time with five degrees of freedom per year. Similarly, we used the same approach with five degrees of freedom for average temperature to adjust for a possible non-linear effect of temperature. The aim of the second step was to test the modification of the effect of PM10 on the ACS risk by different co morbidities (diabetes, history of MI, hypertension, COPD) and demographic factors (age and gender and ethnicity). This analysis followed a case crossover procedure where each subject with event contributes information as a case and as matched control during nonevents times. [18] We used two different methods of case definitions (exposure period); (1) case period was defined as the hospitalization day, while for the control period we used every third day either before or after the hospitalization day within the same calendar month [19] (2) case and control period defined as fix periods of 8 weeks strata (a month from a hospitalization day, bidirectional). The case period defined as three days mean of pollution ending on the hospitalization day (lag 0–2). The control periods were chosen to end on the same week-day as a hospitalization day during the weeks before and after the hospitalization (four before and four after the case period). For example, if the hospitalization occurred on Monday; the three day’s mean PM10 concentrations were compared to eight similar periods on preceding and following Mondays. Both strategies belong to symmetric bidirectional case crossover design where control periods are symmetrically spaced in time minimizing the potential time-varying confounders by season or secular trends. [20] Conditional logistic regression models were conducted to analyze the exposure odds ratio (ORs) with 95% confidence intervals (CI) on risk of ACS hospitalization. To investigate the potential modification of the effect of PM10 on the ACS risk by different co morbidities and demographic factors, we simultaneously added to the model sets of 2-way and 3-way interaction terms that expressed the impact of PM10 measurement among vulnerable population (demographic and clinical personal characteristics; diabetes, history of MI, hypertension, COPD, gender, age and ethnicity (Jews vs. Bedouin Arabs)). We controlled for daily mean temperature and humidity, indicator of the day of the week for the first case definition method and an indicator variable of month (1; 31) additionally included in the models based on the second case definition method. We performed a stratified analysis to compare the magnitude of the effect among different patients with STEMI (ST elevation myocardial infarction) and NSTEMI (non ST-elevation myocardial infarction (NSTEMI). Analyses were performed using R statistical software, version 3.0.
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