Michael Nonnemacher

Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Long-term urban particulate air pollution, traffic noise, and arterial blood pressure.

Background: Recent studies have shown an association of short-term exposure to fine particulate matter (PM) with transient increases in blood pressure (BP), but it is unclear whether long-term exposure has an effect on arterial BP and hypertension. Objectives: We investigated the cross-sectional association of residential long-term PM exposure with arterial BP and hypertension, taking short-term variations of PM and long-term road traffic noise exposure into account. Methods: We used baseline data (2000–2003) on 4,291 participants, 45–75 years of age, from the Heinz Nixdorf Recall Study, a population-based prospective cohort in Germany. Urban background exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) was assessed with a dispersion and chemistry transport model. We used generalized additive models, adjusting for short-term PM, meteorology, traffic proximity, and individual risk factors. Results: An interquartile increase in PM2.5 (2.4 μg/m3) was associated with estimated increases in mean systolic and diastolic BP of 1.4 mmHg [95% confidence interval (CI): 0.5, 2.3] and 0.9 mmHg (95% CI: 0.4, 1.4), respectively. The observed relationship was independent of long-term exposure to road traffic noise and robust to the inclusion of many potential confounders. Residential proximity to high traffic and traffic noise exposure showed a tendency toward higher BP and an elevated prevalence of hypertension. Conclusions: We found an association of long-term exposure to PM with increased arterial BP in a population-based sample. This finding supports our hypothesis that long-term PM exposure may promote atherosclerosis, with air-pollution–induced increases in BP being one possible biological pathway.

Predicting pressure ulcer risk: a multifactorial approach to assess risk factors in a large university hospital population

AIMS The purpose of this study was: (1) to determine the combination of risk factors which best predicts the risk of developing pressure ulcers among inpatients in an acute care university hospital; (2) to determine the appropriate weight for each risk factor; and (3) to derive a concise and easy-to-use risk assessment tool for daily use by nursing staff. BACKGROUND Efficient application of preventive measures against pressure ulcers requires the identification of patients at risk. Adequate risk assessment tools are still needed because the predictive value of existing tools is sometimes unsatisfactory. DESIGN Survey. METHODS A sample of 34,238 cases admitted to Essen University Clinics from April 2003 and discharged up to and including March 2004, was enrolled into the study. Nursing staff recorded data on pressure ulcer status and potential risk factors on admission. Predictors were identified and weighted by multivariate logistic regression. We derived a risk assessment scale from the final logistic regression model by assigning point values to each predictor according to its individual weight. RESULTS The period prevalence rate of pressure ulcers was 1.8% (625 cases). The analysis identified 12 predictors for developing pressure ulcers. With the optimum cut-off point sensitivity and specificity were 83.4 and 83.1%, respectively, with a positive predictive value of 8.4% and a negative predictive value of 99.6%. The diagnostic probabilities of the derived scale were similar to those of the original regression model. CONCLUSIONS The predictors mostly correspond to those used in established scales, although the use of weighted factors is a partly novel approach. Both the final regression model and the derived scale show good prognostic validity. RELEVANCE TO CLINICAL PRACTICE The derived risk assessment scale is an easy-to-understand, easy-to-use tool with good prognostic validity and can assist in effective application of preventive measures against pressure ulcer.

Long-term residential exposure to urban air pollution, and repeated measures of systemic blood markers of inflammation and coagulation

Background In several studies, exposure to fine particulate matter (PM) has been associated with inflammation, with inconsistent results. We used repeated measurements to examine the association of long-term fine and ultrafine particle exposure with several blood markers of inflammation and coagulation. Methods We used baseline (2000–2003) and follow-up (2006–2008) data from the Heinz Nixdorf Recall Study, a German population-based prospective cohort of 4814 participants. A chemistry transport model was applied to model daily surface concentrations of PM air pollutants (PM10, PM2.5) and particle number on a grid of 1 km2. Applying mixed regression models, we analysed associations of long-term (mean of 365 days prior to blood draw) particle exposure at each participants residence with the level of high-sensitivity C reactive protein (hs-CRP), fibrinogen, platelet and white cell count (WCC), adjusting for short-term PM exposure (moving averages of 1–7 days), personal characteristics, season, ambient temperature (1–5 days), ozone and time trend. Results We analysed 6488 observations: 3275 participants with baseline data and 3213 with follow-up data. An increase of 2.4 µg/m3 in long-term PM2.5 was associated with an adjusted increase of 5.4% (95% CI 0.6% to 10.5%) in hs-CRP and of 2.3% (95% CI 1.4% to 3.3%) in the platelet count. Fibrinogen and WCC were not associated with long-term particle exposure. Conclusions In this population-based cohort, we found associations of long-term exposure to PM with markers of inflammation (hs-CRP) and coagulation (platelets). This finding supports the hypothesis that inflammatory processes might contribute to chronic effects of air pollution on cardiovascular disease.

Prevention of pressure ulcer: interaction of body characteristics and different mattresses

We analysed the effect of different body features on contact area, interface pressure and pressure distribution of three different mattresses. Thirty‐eight volunteers (age ranged from 17 to 73 years, 23 females) were asked to lie on three different mattresses in a random order: I, standard hospital foam mattresses; II, higher specification foam mattresses (Viscorelax Sure®); III, constant low pressure devices (CareMedx®, AirSystems). Measurements were performed in supine position and in a 90° left‐ and right‐sided position, respectively, using a full‐body mat (pressure mapping device Xsensor X2‐Modell). Outcome variables were contact area (CA) in cm2, mean interface pressure (IP) in mmHg and pressure distribution (PD) estimated as rate of low pressures between 5 and 33 mmHg on each mattress in percent. Mean CA was lowest in the standard hospital foam mattresses and increased in the higher specification foam mattresses and was highest in the constant low pressure device (supine position: 491 ± 86 cm2, 615 ± 95 cm2, 685 ± 116 cm2). Mean IP was highest in the standard hospital foam mattresses and lower but similar in the higher specification foam mattresses and the constant low pressure devices (supine position: 22·3 ± 1·5 mmHg, 17·6 ± 1·7 mmHg, 17·6 ± 2·2 mmHg). Models were estimated for CA, IP and PD including the independent variables height, weight and waist‐to‐hip‐ratio (WHR). They show that body morphology seems to play a minor role for CA, IP and PD, but very thin and tall patients and very small and obese people might benefit from different mattresses. Our data show that CA increases with increasing specification of mattresses. Higher specification foam mattresses and constant low pressure devices show similar IP, but constant low pressure devices show a wider pressure distribution. Body morphology should be considered to optimise prevention for single patients.

Association of long-term exposure to local industry- and traffic-specific particulate matter with arterial blood pressure and incident hypertension.

BACKGROUND Long-term exposure to fine particulate matter (PM2.5) may lead to increased blood pressure (BP). The role of industry- and traffic-specific PM2.5 remains unclear. OBJECTIVE We investigated the associations of residential long-term source-specific PM2.5 exposure with arterial BP and incident hypertension in the population-based Heinz Nixdorf Recall cohort study. METHODS We defined hypertension as systolic BP≥140mmHg, or diastolic BP≥90mmHg, or current use of BP lowering medication. Long-term concentrations of PM2.5 from all local sources (PM2.5ALL), local industry (PM2.5IND) and traffic (PM2.5TRA) were modeled with a dispersion and chemistry transport model (EURAD-CTM) with a 1km(2) resolution. We performed a cross-sectional analysis with BP and prevalent hypertension at baseline, using linear and logistic regression, respectively, and a longitudinal analysis with incident hypertension at 5-year follow-up, using Poisson regression with robust variance estimation. We adjusted for age, sex, body mass index, lifestyle, education, and major road proximity. Change in BP (mmHg), odds ratio (OR) and relative risk (RR) for hypertension were calculated per 1μg/m(3) of exposure concentration. RESULTS PM2.5ALL was highly correlated with PM2.5IND (Spearmans ρ=0.92) and moderately with PM2.5TRA (ρ=0.42). In adjusted cross-sectional analysis with 4539 participants, we found positive associations of PM2.5ALL with systolic (0.42 [95%-CI: 0.03, 0.80]) and diastolic (0.25 [0.04, 0.46]) BP. Higher, but less precise estimates were found for PM2.5IND (systolic: 0.55 [-0.05, 1.14]; diastolic: 0.35 [0.03, 0.67]) and PM2.5TRA (systolic: 0.88 [-1.55, 3.31]; diastolic: 0.41 [-0.91, 1.73]). We found crude positive association of PM2.5TRA with prevalence (OR 1.41 [1.10, 1.80]) and incidence of hypertension (RR 1.38 [1.03, 1.85]), attenuating after adjustment (OR 1.19 [0.90, 1.58] and RR 1.28 [0.94, 1.72]). We found no association of PM2.5ALL and PM2.5IND with hypertension. CONCLUSIONS Long-term exposures to all-source and industry-specific PM2.5 were positively related to BP. We could not separate the effects of industry-specific PM2.5 from all-source PM2.5. Estimates with traffic-specific PM2.5 were generally higher but inconclusive.

Measuring Data Quality: A Review of the Literature between 2005 and 2013

A literature review was done within a revision of a guideline concerned with data quality management in registries and cohort studies. The review focused on quality indicators, feedback, and source data verification. Thirty-nine relevant articles were selected in a stepwise selection process. The majority of the papers dealt with indicators. The papers presented concepts or data analyses. The leading indicators were related to case or data completeness, correctness, and accuracy. In the future, data pools as well as research reports from quantitative studies should be obligatory supplemented by information about their data quality, ideally picking up some indicators presented in this review.

Qualitätsstandards für epidemiologische Kohortenstudien

Primary care physicians (PCPs) play a crucial role for guideline-oriented intervention in patients with depression. Based on a diagnostic screening questionnaire, this study investigates the sensitivity of PCPs to recognize patients with depression as well as the factors facilitating recognition and concordant diagnostic decisions. In a cross-sectional epidemiological study in six regions of Germany, 3563 unselected patients filled in questionnaires on mental and physical complaints and were diagnostically evaluated by their PCP (N = 253). The patient reports on an established Depression-Screening-Questionnaire (DSQ), which allows the approximate derivation of an ICD-10 depression diagnosis, were compared with the physician diagnosis (N = 3211). In a subsample of discordant cases a comprehensive standardized clinical-diagnostic interview (DIA-X/CIDI) was applied. On the study day, the prevalence of ICD-10 depression was 14.3% according to the DSQ and 10.7% according to the physician diagnosis. Half of the patients identified by DSQ were diagnosed with depression by their physician and two thirds were recognized as mental disorder cases. More severe depression symptomatology and the persistent presence of main depression symptoms were related to better recognition and concordant diagnostic decisions. Diagnostic validation interviews confirmed the DSQ diagnosis in the majority of the false-negative cases. Indications for at least a previous history of depression were found in up to 70% of false-positive cases. Given the high prevalence of depression in primary care patients, there is continued need to improve the recognition and diagnosis of these patients to assure guideline-oriented treatment.

Erratum to: Influence of short-term exposure to ultrafine and fine particles on systemic inflammation

In the European Journal of Epidemiology 25(8) a printing error occurred in the manuscript concerning the unit of particle number concentration. The correct summary statistics of particle number concentrations (PN) given in the text and in Table 2, p. 584 is 10/l instead of 10/ml. Please find the revised Table 2. Since effect estimates of particle number were given per percent increase, results of the regression models in the text, tables and figures are correct as printed in the original publication.