A Feasibility Study of Implementing the Policies on Increasing Birth Rate with an Emphasis on Socio-economic Status: A Case Study of Kermanshah Metropolis,Western Iran

Population and development have a mutual relationship, and more to the point, lack of sufficient knowledge on population development and fertility can lead to the presentation of inappropriate population plans in such a way that they may turn out to be useless and ineffective even in the event of implementation. So, the present study aimed to delve into the feasibility of implementing the new governmental policies on increasing birth rate with an emphasis on the socioeconomic status in Kermanshah Metropolis, Iran. To evaluate poverty and fertility in Kermanshah Metropolis, the present cross-sectional study used the latest statistics obtained from the Statistical Center of Iran (2011), and as for the data analysis, such tests in Arc/GIS and SPSS 20 software. The results of the present study showed that the spatial patterns of poverty and fertility were formed in clusters across the city, and the results of variance analysis of the relationship between the variables of fertility and poverty demonstrated that there was a significant difference between the selected neighborhoods in terms of the variables of poverty and total fertility (P < 0.001). Furthermore, the spatial autocorrelations of fertility and poverty in Kermanshah were positive and showed that the spatial means and standard distances of poverty and fertility were overlapping. Not all districts and urban neighborhoods were equal in the total fertility rate. So, given the societal classes’ different socioeconomic and cultural status across different neighborhoods, the government’s new approaches to increasing birthrate cannot be applied to all classes throughout Kermanshah Metropolis.

     

Evaluation of the benchmark dose for point of departure determination for a variety of chemical classes in applied regulatory settings

Repeated-dose studies received by the New Substances Assessment and Control Bureau (NSACB) of Health Canada are used to provide hazard information toward risk calculation. These studies provide a point of departure (POD), traditionally the NOAEL or LOAEL, which is used to extrapolate the quantity of substance above which adverse effects can be expected in humans. This project explored the use of benchmark dose (BMD) modeling as an alternative to this approach for studies with few dose groups. Continuous data from oral repeated-dose studies for chemicals previously assessed by NSACB were reanalyzed using U.S. EPA benchmark dose software (BMDS) to determine the BMD and BMD 95% lower confidence limit (BMDL(05) ) for each endpoint critical to NOAEL or LOAEL determination for each chemical. Endpoint-specific benchmark dose-response levels , indicative of adversity, were consistently applied. An overall BMD and BMDL(05) were calculated for each chemical using the geometric mean. The POD obtained from benchmark analysis was then compared with the traditional toxicity thresholds originally used for risk assessment. The BMD and BMDL(05) generally were higher than the NOAEL, but lower than the LOAEL. BMDL(05) was generally constant at 57% of the BMD. Benchmark provided a clear advantage in health risk assessment when a LOAEL was the only POD identified, or when dose groups were widely distributed. Although the benchmark method cannot always be applied, in the selected studies with few dose groups it provided a more accurate estimate of the real no-adverse-effect level of a substance.     

On testing more IFRA ordering

In this paper, first we consider the problem of testing that two unknown distributions are identical against the alternative that one is more IFRA than the other and propose a new test that is asymptotically normal and consistent. Next, we prove that beta family of distributions is ordered according to more IFRA ordering. The empirical power of the proposed test is simulated for some specific families of distributions like beta, gamma and Weibull that are ordered with respect to more IFRA order. Finally, we apply our test to some real data sets in the context of reliability.     

On testing more IFRA ordering-II

ABSTRACT

Suppose F and G are two life distribution functions. It is said that F is more IFRA (increasing failure rate average) than G (written by F ? _*G) if G^{? 1}F(x) is star-shaped on (0, ∞). In this paper, the problem of testing H₀: F = _*G against H₁: F ? _*G and F ≠ _*G is considered in both cases when G is known and when G is unknown. We propose a new test based on U-statistics and obtain the asymptotic distribution of the test statistics. The new test is compared with some well-known tests in the literature. In addition, we apply our test to a real data set in the context of reliability.