Postpartum Visit Attendance Increases the Use of Modern Contraceptives

Background. Delays in postpartum contraceptive use may increase risk for unintended or rapid repeat pregnancies. The postpartum care visit (PPCV) is a good opportunity for women to discuss family planning options with their health care providers. This study examined the association between PPCV attendance and modern contraceptive use using data from a managed care organization. Methods. Claims and demographic and administrative data came from a nonprofit managed care organization in Virginia (2008–2012). Information on the most recent delivery for mothers with singleton births was analyzed (N = 24,619). Routine PPCV (yes, no) and modern contraceptive use were both dichotomized. Descriptive analyses provided percentages, frequencies, and means. Multiple logistic regression was conducted and ORs and 95% CIs were calculated. Results. More than half of the women did not attend their PPCV (50.8%) and 86.9% had no modern contraceptive use. After controlling for the effects of confounders, women with PPCV were 50% more likely to use modern contraceptive methods than women with no PPCV (OR = 1.50, 95% CI = 1.31, 1.72). Conclusions. These findings highlight the importance of PPCV in improving modern contraceptive use and guide health care policy in the effort of reducing unintended pregnancy rates

Estimation of Disproportions in Patent Activity of OECD Countries Using Spatio-Temporal Methods

The article contains a presentation of possibility of using panel-based sample and modelling based on this sample as methods of determining indicators of patent activity. The research was conducted with the help of data from European countries. Results in association with used methodology, which takes into account modern approach to stationary and cointegration for panel-based samples, indicate the usefulness of applied methods.patent activity, panel model, decomposition of intercept.

Bias Characterization in Probabilistic Genotype Data and Improved Signal Detection with Multiple Imputation

Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data

Using GWAS Data to Identify Copy Number Variants Contributing to Common Complex Diseases

Copy number variants (CNVs) account for more polymorphic base pairs in the human genome than do single nucleotide polymorphisms (SNPs). CNVs encompass genes as well as noncoding DNA, making these polymorphisms good candidates for functional variation. Consequently, most modern genome-wide association studies test CNVs along with SNPs, after inferring copy number status from the data generated by high-throughput genotyping platforms. Here we give an overview of CNV genomics in humans, highlighting patterns that inform methods for identifying CNVs. We describe how genotyping signals are used to identify CNVs and provide an overview of existing statistical models and methods used to infer location and carrier status from such data, especially the most commonly used methods exploring hybridization intensity. We compare the power of such methods with the alternative method of using tag SNPs to identify CNV carriers. As such methods are only powerful when applied to common CNVs, we describe two alternative approaches that can be informative for identifying rare CNVs contributing to disease risk. We focus particularly on methods identifying de novo CNVs and show that such methods can be more powerful than case-control designs. Finally we present some recommendations for identifying CNVs contributing to common complex disorders.Comment: Published in at http://dx.doi.org/10.1214/09-STS304 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Discontinuation and switching of postpartum contraceptive methods over twelve months in Burkina Faso and the Democratic Republic of the Congo: a secondary analysis of the Yam Daabo trial.

IntroductionWomen who use contraceptive methods sometimes stop early, use methods intermittently, or switched contraceptive methods. All these events (discontinuations and switching) contribute to the occurrence of unwanted and close pregnancies. This study aimed to explore contraceptive discontinuation and switching during the Yam-Daabo project to measure the effect of interventions on the continuation of contraceptive methods use.MethodsWe conducted a secondary analysis of the Yam-Daabo trial data. We choose the discontinuation and switching of a modern contraceptive method as outcome measures. We performed a survival analysis using the Stata software package to estimate the effect of the interventions on contraceptive discontinuation. We also studied the main reasons for discontinuation and switching.ResultsIn total, 637 out of the 1120 women used at least one contraceptive method (of any type), with 267 women in the control and 370 in the intervention group. One hundred seventy-nine women of the control group used modern methods compared to 279 women of the intervention group with 24 and 32 who discontinued, respectively. We observed no statistically significant association between interventions and modern methods discontinuation and switching. However, modern methods' discontinuation was higher in pills and injectables users than implants and IUDs users. The pooled data comparison showed that, in reference to the women who had not switched while using a modern method, the likelihood of switching to a less or equal effectiveness method among the women of the control group was 3.8(95% CI: 1.8-8.0) times the likelihood of switching to a less or equal effectiveness method among the women of the intervention group. And this excess was statistically significant (p ConclusionThe results of this study show no statistically significant association between interventions and modern methods discontinuation. Discontinuation is more related to the methods themselves than to any other factor. It is also essential to set up specific actions targeting women's partners and influential people in the community to counter inhibiting beliefs.Trial registrationPan African Clinical Trials Registry (PACTR201609001784334, https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=1784 )

Ethnicity and Reproductive Autonomy: A Study of the Relationship Between Indigenous Self-Identification and Current Use of a Modern Contraceptive Method in the Huehuetenango Department of Northwestern Guatemala

Objectives: Indigenous women in Guatemala have lower rates of contraceptive use than non-indigenous women. This study explores the relationship between indigenous self-identification and current use of a modern contraceptive method among women of reproductive age in the Huehuetenango Department of Guatemala. Methods: Data from the 2014-2015 Demographic and Health Surveys (DHS) for Guatemala were used to examine contraceptive use among varying populations of women. Descriptive and multivariate logistic regression analyses are performed to examine the association of demographic and social factors on modern contraceptive use. Results: There is a negative association between indigenous self-identification and modern contraceptive use. Women who were married and those who were an older age were significantly more likely to be modern contraception users. Conclusions: Understanding the contraceptive needs that indigenous women have throughout their lives will allow family planning programs to better serve this target population.Master of Public Healt