The Iranian Vital Horoscope; Appropriate Tool to Collect Health Statistics in Rural Areas

This paper aims to describe the Iranian Vital Horoscope System. This system has been designed to collect and display vital events within the community. Baseline population data are collected by health workers ( Behvarz ), and are entered onto the Vital Horoscope Chart. The objective of this data collection system is to compile relevant data to quantitatively assess the performance of the health unites at the different levels each year, according to conventional health indicators. Assessing indices reported based on this data sources confirmed the consistency of the Vital Horoscope as a data collection mechanism and provided face validity of the data source. However, further study is needed to evaluate content validity and reliability of data from this system.

[1]  B. Gompertz,et al.  On the Nature of the Function Expressive of the Law of Human Mortality , 1825 .

[2]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[3]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[4]  D. F. Morrison,et al.  Multivariate Statistical Methods , 1968 .

[5]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[6]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[7]  B. Manly.  Multivariate Statistical Methods : A Primer , 1986 .

[8]  Kurt Hornik,et al.  FEED FORWARD NETWORKS ARE UNIVERSAL APPROXIMATORS , 1989 .

[9]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[10]  Nobutoshi Tanaka,et al.  Data Analysis of Daily Collection Tonnage of Residential Solid Waste in Japan , 1993 .

[11]  Hans Wackernagel,et al.  Multivariate Geostatistics: An Introduction with Applications , 1996 .

[12]  Christopher M. Bishop,et al.  Neural Network for Pattern Recognition , 1995 .

[13]  Annegrete Bruvoll,et al.  Future waste generation forecasts on the basis of a macroeconomic model , 1997 .

[14]  Ni-Bin Chang,et al.  An analysis of recycling impacts on solid waste generation by time series intervention modeling , 1997 .

[15]  B. Helena,et al.  Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga river, Spain) by Principal Component Analysis. , 2000 .

[16]  Zhifeng Liu,et al.  Recycling strategy and a recyclability assessment model based on an artificial neural network , 2002 .

[17]  Changqing Dong,et al.  Predicting the heating value of MSW with a feed forward neural network. , 2003, Waste management.

[18]  Ashu Jain,et al.  Comparative Analysis of Event-Based Rainfall-Runoff Modeling Techniques—Deterministic, Statistical, and Artificial Neural Networks , 2003 .

[19]  Kefa Cen,et al.  SO2 emission characteristics and BP neural networks prediction in MSW/coal co-fired fluidized beds , 2005, Journal of environmental sciences.

[20]  Handan Çamdevýren,et al.  Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs , 2005 .

[21]  M. Naghavi,et al.  Primary Health Care System, Narrowing of Rural-Urban Gap in Health Indicators, and Rural Poverty Reduction: The Experience , 2005 .

[22]  Hung-Yee Shu,et al.  Prediction for Energy Content of Taiwan Municipal Solid Waste Using Multilayer Perceptron Neural Networks , 2006, Journal of the Air & Waste Management Association.

[23]  Ferhat Karaca,et al.  NN-LEAP: A neural network-based model for controlling leachate flow-rate in a municipal solid waste landfill site , 2006, Environ. Model. Softw..

[24]  Mohsen Naghavi,et al.  Mortality in the Islamic Republic of Iran, 1964-2004. , 2007, Bulletin of the World Health Organization.

[25]  Nouri Rouh Elah,et al.  Assessment of Importance of Water Quality Monitoring Stations Using Principal Components Analysis and Factor Analysis: A Case Study of the Karoon River , 2007 .

[26]  Nouri Rouh Elah,et al.  PREDICTION OF MUNICIPAL SOLID WASTE GENERATION BY USE OF ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF MASHHAD , 2008 .

[27]  Khosro Ashrafi,et al.  COMPARISON OF ANN AND PCA BASED MULTIVARIATE LINEAR REGRESSION APPLIED TO PREDICT THE DAILY AVERAGE CONCENTRATION OF CO: A CASE STUDY OF TEHRAN , 2008 .

[28]  Mohammad Ali Abdoli,et al.  Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: A case study of Mashhad , 2009 .