A framework for exploration and cleaning of environmental data : Tehran air quality data experience

Management and cleaning of large environmental monitored data sets is a specific challenge. In this article, the authors present a novel framework for exploring and cleaning large datasets. As a case study, we applied the method on air quality data of Tehran, Iran from 1996 to 2013. ; The framework consists of data acquisition [here, data of particulate matter with aerodynamic diameter ≤10 µm (PM10)], development of databases, initial descriptive analyses, removing inconsistent data with plausibility range, and detection of missing pattern. Additionally, we developed a novel tool entitled spatiotemporal screening tool (SST), which considers both spatial and temporal nature of data in process of outlier detection. We also evaluated the effect of dust storm in outlier detection phase.; The raw mean concentration of PM10 before implementation of algorithms was 88.96 µg/m3 for 1996-2013 in Tehran. After implementing the algorithms, in total, 5.7% of data points were recognized as unacceptable outliers, from which 69% data points were detected by SST and 1% data points were detected via dust storm algorithm. In addition, 29% of unacceptable outlier values were not in the PR.  The mean concentration of PM10 after implementation of algorithms was 88.41 µg/m3. However, the standard deviation was significantly decreased from 90.86 µg/m3 to 61.64 µg/m3 after implementation of the algorithms. There was no distinguishable significant pattern according to hour, day, month, and year in missing data.; We developed a novel framework for cleaning of large environmental monitored data, which can identify hidden patterns. We also presented a complete picture of PM10 from 1996 to 2013 in Tehran. Finally, we propose implementation of our framework on large spatiotemporal databases, especially in developing countries

Weight, height and body mass index nomograms; early adiposity rebound in a sample of children in Tehran, Iran

Background: Assessing growth is a useful tool for defining health and nutritional status of children. The objective of this study was to construct growth reference curves of Iranian infants and children (0-6 years old) and compare them with previous and international references. Methods: Weight, height or length of 2107 Iranian infants and children aged 0-6 years old were measured using a cross-sectional survey in Tehran in 2010. Standard smooth reference curves for Iranian population were constructed and compared to multinational World Health Organization 2006 reference standards as well as a previous study from two decades ago. Results: Growth index references for Iranian girls are increased in compare to data from two decades ago and are approximately close to the international references. In boys; however, the increment was considerably large as it passed the international references. Not only the values for indexes was changed during two decades, but also the age at adiposity rebound came near the age of 3, which is an important risk factor for later obesity. Conclusions: During two decades, growth indexes of Iranian children raised noticeable. Risk factors for later obesity are now apparent and demand immediate policy formulations. In addition, reference curves presented in this paper can be used as a diagnostic tool for monitoring growth of Iranian children