Iowa Wetland Monitoring, 2007

This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.

Iowa Beach Monitoring Program, 2007

This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.

Asymptotic robustness in multi-sample analysis of multivariate linear relations

Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

Step count is associated with lower nighttime systolic blood pressure and increased dipping.

BACKGROUND: Higher nighttime blood pressure (BP) and the loss of nocturnal dipping of BP are associated with an increased risk for cardiovascular events. However, the determinants of the loss of nocturnal BP dipping are only beginning to be understood. We investigated whether different indicators of physical activity were associated with the loss of nocturnal dipping of BP. METHODS: We conducted a cross-sectional study of 103 patients referred for 24-hour ambulatory monitoring of BP. We measured these patients' step count (SC), active energy expenditure (AEE), and total energy expenditure simultaneously, using actigraphs. RESULTS: In our study population of 103 patients, most of whom were hypertensive, SC and AEE were associated with nighttime systolic BP in univariate (SC, r = -0.28, P < 0.01; AEE, r = -0.20, P = 0.046) and multivariate linear regression analyses (SC, coefficient beta = -5.37, P < 0.001; AEE, coefficient beta = -0.24, P < 0.01). Step count was associated with both systolic (r = 0.23, P = 0.018) and diastolic (r = 0.20, P = 0.045) BP dipping. Nighttime systolic BP decreased progressively across the categories of sedentary, moderately active, and active participants (125mm Hg, 116mm Hg, 112mm Hg, respectively; P = 0.002). The degree of BP dipping of BP increased progressively across the same three categories of activity (respectively 8.9%, 14.6%, and 18.6%, P = 0.002, for systolic BP and respectively 12.8%, 18.1%, and 22.2%, P = 0.006, for diastolic BP). CONCLUSIONS: Step count is continuously associated with nighttime systolic BP and with the degree of BP dipping independently of 24-hour mean BP. The combined use of an actigraph for measuring indicators of physical activity and a device for 24-hour measurement of ambulatory BP may help identify patients at increased risk for cardiovascular events in whom increased physical activity toward higher target levels may be recommended.

Nocturnal hypoglycaemias in type 1 diabetic patients: what can we learn with continuous glucose monitoring?

AIM: In type 1 diabetic patients (T1DM), nocturnal hypoglycaemias (NH) are a serious complication of T1DM treatment; self-monitoring of blood glucose (SMBG) is recommended to detect them. However, the majority of NH remains undetected on an occasional SMBG done during the night. An alternative strategy is the Continuous glucose monitoring (CGMS), which retrospectively shows the glycaemic profile. The aims of this retrospective study were to evaluate the true incidence of NH in T1DM, the best SMBG time to predict NH, the relationship between morning hyperglycaemia and NH (Somogyi phenomenon) and the utility of CGMS to reduce NH. METHODS: Eighty-eight T1DM who underwent a CGMS exam were included. Indications for CGMS evaluation, hypoglycaemias and correlation with morning hyperglycaemias were recorded. The efficiency of CGMS to reduce the suspected NH was evaluated after 6-9 months. RESULTS: The prevalence of NH was 67% (32% of them unsuspected). A measured hypoglycaemia at bedtime (22-24 h) had a sensitivity of 37% to detect NH (OR=2.37, P=0.001), while a single measure < or =4 mmol/l at 3-hour had a sensitivity of 43% (OR=4.60, P<0.001). NH were not associated with morning hyperglycaemias but with morning hypoglycaemias (OR=3.95, P<0.001). After 6-9 months, suspicions of NH decreased from 60 to 14% (P<0.001). CONCLUSION: NH were highly prevalent and often undetected. SMBG at bedtime, which detected hypoglycaemia had sensitivity almost equal to that of 3-hour and should be preferred because it is easier to perform. Somogyi phenomenon was not observed. CGMS is useful to reduce the risk of NH in 75% of patients.

My older sibling was drunk - younger siblings' drunkenness in relation to parental monitoring and the parent-adolescent relationship.

This study explored the links between having older siblings who get drunk, satisfaction with the parent-adolescent relationship, parental monitoring, and adolescents' risky drinking. Regression models were conducted based on a national representative sample of 3725 8th to 10th graders in Switzerland (mean age 15.0, SD = .93) who indicated having older siblings. Results showed that both parental factors and older siblings' drinking behaviour shape younger siblings' frequency of risky drinking. Parental monitoring showed a linear dose-response relationship, and siblings' influence had an additive effect. There was a non-linear interaction effect between parent-adolescent relationship and older sibling's drunkenness. The findings suggest that, apart from avoiding an increasingly unsatisfactory relationship with their children, parental monitoring appears to be important in preventing risky drinking by their younger children, even if the older sibling drinks in such a way. However, a satisfying relationship with parents does not seem to be sufficient to counterbalance older siblings' influence.

Financial intermediation and equity investment with costly monitoring

This paper studies the efficiency of equilibria in a productive OLG economy where the process of financial intermediation is characterized by costly state verification. Both competitive equilibria and Constrained Pareto Optimal allocations are characterized. It is shown that market outcomes can be socially inefficient, even when a weaker notion than Pareto optimality is considered.

Results of Wetland Monitoring 2005-2007

This monthly report from the Iowa Department of Natural Resources is about the water quality management of Iowa's rivers, streams and lakes.

Iowa's Beach Monitoring Program 2007, 2008

This monthly report from the Iowa Department of Natural Resources is about the water quality management of Iowa's rivers, streams and lakes.

Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.