Iowa Leading Indicators Index October 2008

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index November 2008

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index December 2008

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index January 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, February 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index March 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, April 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, May 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, June 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Indicators used by clinicians to assess pain in the brain injured

INTRODUCTION. The assessment of pain in critically ill brain-injured patients is challenging for health professionals. In addition to be unable to self-report, the confused and stereotyped behaviors of these patients are likely to alter their ''normal'' pain responses. Therefore, the pain indicators observed in the general critically ill population may not be appropriate. OBJECTIVES. To identify behavioral and physiological indicators used by clinicians to assess pain in critically ill brain-injured patients who are unable to self-report. METHODS.Amixed-method design was used with the first step being the combination of the results of an integrative literature review with the results of nominal groups of 12 nurses and four physicians. The second step involved a web-based survey to establish content validity. Fourteen experts (clinicians and academics) from three French speaking European countries rated the relevance of each indicator. A content validity index (CVI) was computed for each indicator (I-CVI) and for each category (S-CVI). RESULTS. The first step generated 52 indicators. These indicators were classified into six categories: facial expressions, position/movement, muscle tension, vocalization, compliance with ventilator, and physiological indicators. In the second step, the agreement between raters was high with an Intraclass Correlation Coefficient of 0.88 (95% CI 0.83-0.92). The I-CVIs ranged from 0.07 to 1. Indicators with an I-CVI below 0.5 (n = 12) were not retained, resulting in a final list of 30 indicators. The CVI for this final list was 0.75 with categories ranging from 0.67 (compliance with ventilation) to 0.87 (vocalization). CONCLUSIONS. This process identified specific pain indicators for critically ill braininjured patients. Further evaluation is in progress to test the validity and relevance of these indicators in the clinical setting.

Impact of biological and environmental variabilities on biological monitoring: an approach using toxicokinetic models

Biological monitoring of occupational exposure is characterized by important variability, due both to variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a dependable application of biological monitoring. This work describes this variability,using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physicochemical, and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol, and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated with changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the 14 chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hr), this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: tables detailing the CBTK models for all 14 chemicals and the symbol nomenclature that was used.] [Authors]

Iowa Leading Indicators Index after One Year: An Assessment and Update

The Iowa Leading Indicators Index (ILII) Annual Assessment and Update assesses how well the ILII has met the goals behind its development, gauges the validity of the existing components, considers additional components that have been suggested along the way, and carries out the annual updates necessary for such an index.

Iowa Leading Indicators Index after Two Years: An Assessment and Update

The Iowa Leading Indicators Index (ILII) Annual Assessment and Update assesses how well the ILII has met the goals behind its development, gauges the validity of the existing components, considers additional components that have been suggested along the way, and carries out the annual updates necessary for such an index.

Iowa Leading Indicators Index after Three Years: An Assessment and Update

The Iowa Leading Indicators Index (ILII) Annual Assessment and Update assesses how well the ILII has met the goals behind its development, gauges the validity of the existing components, considers additional components that have been suggested along the way, and carries out the annual updates necessary for such an index.

Iowa Leading Indicators Index July 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.