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AbstractThis study examines the probability of twins by birth year, maternal race–ethnicity, age, and parity and the influences of these demographic factors on the probability of male in twins and singletons in a large, racially diverse population. Recent publications note steep increases in twin births while the probability of male births has been reported to vary by parental race–ethnicity and age and birth order. Probability of male stratified by plurality has not been investigated in California prior to this study. Cubic spline estimates and Poisson regression techniques were employed to describe trends in twins and males using California vital statistics birth and fetal death records over the period from 1983–2003. This study includes 127,787 twin pair and 11,025,106 singleton births. The probability of twins varied by birth year, maternal race–ethnicity, age, and parity. The probability of twins increased by 10.1% from 1983–1992 and increased by 20.1% from 1993–2003, nearly doubling the previous increase. All maternal race–ethnicity groups showed increases in probability of twins with increasing maternal age. Parous women compared to nulliparous women had larger increases in the probability of twins. The probability of males in twins decreased from 1983–1992 and increased from 1993–2003; while in singletons the probability appeared unchanged. These findings show increases in the probability of twins in California from 1983–2003 and identify maternal age, race–ethnicity, and parity groups most likely to conceive twins. The cause of the increase in twins is unknown but coincides with trends towards delayed childbearing and increased use of subfertility treatments.

AbstractThis study presents a general model of two binary variables and applies it to twin sex pairing data from 21 twin data sources to estimate the frequency of dizygotic twins. The purpose of this study is to clarify the relationship between maximum likelihood and Weinberg's differential rule zygosity estimation methods. We explore the accuracy of these zygosity estimation measures in relation to twin ascertainment methods and the probability of a male. Twin sex pairing data from 21 twin data sources representing 15 countries was collected for use in this study. Maximum likelihood estimation of the probability of dizygotic twins is applied to describe the variation in the frequency of dizygotic twin births. The differences between maximum likelihood and Weinberg's differential rule zygosity estimation methods are presented as a function of twin data ascertainment method and the probability of a male. Maximum likelihood estimation of the probability of dizygotic twins ranges from 0.083 (95% approximate CI: 0.082, 0.085) to 0.750 (95% approximate CI: 0.749, 0.752) for voluntary ascertainment data sources and from 0.374 (95% approximate CI: 0.373, 0.375) to 0.987 (95% approximate CI: 0.959, 1.016) for active ascertainment data sources. In 17 of the 21 twin data sources differences of 0.01 or less occur between maximum likelihood and Weinberg zygosity estimation methods. The Weinberg and maximum likelihood estimates are negligibly different in most applications. Using the above general maximum likelihood estimate, the probability of a dizygotic twin is subject to substantial variation that is largely a function of twin data ascertainment method.

IntroductionEctopic pregnancy occurs in 1% to 2% of the all recognized pregnancies, yet half of women who have an ectopic pregnancy do not have any known risk factors. A potential but unstudied risk factor for ectopic pregnancy is benzodiazepine use, which could affect muscle contraction in the fallopian tube.
Objectives and ApproachWe compared the risk of ectopic pregnancy among women with and women without benzodiazepine prescriptions before conception. using data from United States commercial insurance claims (IBM® MarketScan® Databases). We performed a cohort study of 1,691,366 pregnancies between November 1, 2008 and September 30, 2015, and used unadjusted and inverse probability of treatment (IPT) weighted log-binomial models to calculate relative risks (RR) of ectopic pregnancy for pregnant women who did and did not fill any prescriptions for benzodiazepines in the 90 days before conception. Sub-group analysis was conducted on women who had anxiety and women who had insomnia diagnoses in the year before conception.
ResultsOf the 1,691,366 pregnant women, 1.06% filled at least two benzodiazepine prescriptions in the 90 days before conception. Among women with a benzodiazepine prescription, there was an excess of 80 ectopic pregnancies per 10,000 pregnancies, and their IPT-weighted risk of ectopic pregnancies was 1.47 (95% CI 1.32 to 1.63) times greater relative to women without benzodiazepine prescriptions before conception. The IPT-weighted RR between ectopic pregnancy and benzodiazepine use was 1.34 (95% CI 1.18 to 1.53) among women with anxiety disorder diagnoses and 1.28 (95% CI 0.99 to 1.68) among women with an insomnia diagnosis.
Conclusion / ImplicationsThis study found that women who have a benzodiazepine prescription before conception are at an increased risk of ectopic pregnancy. This information can help women and their health care providers make more fully informed decisions about benzodiazepine use in their reproductive years.

OBJECTIVE: Our primary objective was to identify risk factors for maternal readmission with sepsis. Our secondary objectives were to (1) assess diagnoses and infecting organisms at readmission and (2) compare early (<6 weeks) and late (6 weeks to 9 months postpartum) maternal readmission with sepsis. STUDY DESIGN: We identified our cohort using linked hospital discharge data and birth certificates for California deliveries from 2008 to 2011. Consistent with the 2016 sepsis classification, we defined sepsis as septicemia plus acute organ dysfunction. We compared women with early or late readmission with sepsis to women without readmission with sepsis. RESULTS: Among 1,880,264 women, 494 (0.03%) were readmitted with sepsis, 61% after 6 weeks. Risk factors for readmission with sepsis included preterm birth, hemorrhage, obesity, government-provided insurance, and primary cesarean. For both early and late sepsis readmissions, the most common diagnoses were urinary tract infection and pyelonephritis, and the most frequently identified infecting organism was gram-negative bacteria. Women with early compared with late readmission with sepsis shared similar obstetric characteristics. CONCLUSION: Maternal risk factors for both early and late readmission with sepsis included demographic characteristics, cesarean, hemorrhage, and preterm birth. Risks for sepsis after delivery persist beyond the traditional postpartum period of 6 weeks.

BackgroundThe Government of Bihar (GoB) in India, the Bill and Melinda Gates Foundation and several non-governmental organisations launched the Ananya program aimed to support the GoB to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) statewide. Here we summarise changes in indicators attained during the initial two-year pilot phase (2012-2013) of implementation in eight focus districts of approximately 28 million population, aimed to inform subsequent scale-up.MethodsThe quasi-experimental impact evaluation included statewide household surveys at two time points during the pilot phase: January-April 2012 ("baseline") including an initial cohort of beneficiaries and January-April 2014 ("midline") with a new cohort. The two arms were: 1) eight intervention districts, and 2) a comparison arm comprised of the remaining 30 districts in Bihar where Ananya interventions were not implemented. We analysed changes in indicators across the RMNCHN continuum of care from baseline to midline in intervention and comparison districts using a difference-in-difference analysis.ResultsIndicators in the two arms were similar at baseline. Overall, 40% of indicators (20 of 51) changed significantly from baseline to midline in the comparison districts unrelated to Ananya; two-thirds (n = 13) of secular indicator changes were in a direction expected to promote health. Statistically significant impact attributable to the Ananya program was found for 10% (five of 51) of RMNCHN indicators. Positive impacts were most prominent for mother's behaviours in contraceptive utilisation.ConclusionsThe Ananya program had limited impact in improving health-related outcomes during the first two-year period covered by this evaluation. The program's theories of change and action were not powered to observe statistically significant differences in RMNCHN indicators within two years, but rather aimed to help inform program improvements and scale-up. Evaluation of large-scale programs such as Ananya using theory-informed, ...

BackgroundThe Ananya program in Bihar implemented household and community-level interventions to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) in two phases: a first phase of intensive ancillary support to governmental implementation and innovation testing by non-government organisation (NGO) partners in eight focus districts (2012-2014), followed by a second phase of state-wide government-led implementation with techno-managerial assistance from NGOs (2014 onwards). This paper examines trends in RMNCHN indicators in the program's implementation districts from 2012-2017.MethodsEight consecutive rounds of cross-sectional Community-based Household Surveys conducted by CARE India in 2012-2017 provided comparable data on a large number of indicators of frontline worker (FLW) performance, mothers' behaviours, and facility-based care and outreach service delivery across the continuum of maternal and child care. Logistic regression, considering the complex survey design and sample weights generated by that design, was used to estimate trends using survey rounds 2-5 for the first phase in the eight focus districts and rounds 6-9 for the second phase in all 38 districts statewide, as well as the overall change from round 2-9 in focus districts. To aid in contextualising the results, indicators were also compared amongst the formerly focus and the non-focus districts at the beginning of the second phase.ResultsIn the first phase, the levels of 34 out of 52 indicators increased significantly in the focus districts, including almost all indicators of FLW performance in antenatal and postnatal care, along with mother's birth preparedness, some breastfeeding practices, and immunisations. Between the two phases, 33 of 52 indicators declined significantly. In the second phase, the formerly focus districts experienced a rise in the levels of 14 of 50 indicators and a decline in the levels of 14 other indicators. There was a rise in the levels of 22 out of 50 indicators in the non-focus districts ...

BackgroundSelf-help group (SHG) interventions have been widely studied in low and middle income countries. However, there is little data on specific impacts of health layering, or adding health education modules upon existing SHGs which were formed primarily for economic empowerment. We examined three SHG interventions from 2012-2017 in Bihar, India to test the hypothesis that health-layering of SHGs would lead to improved health-related behaviours of women in SHGs.MethodsA model for health layering of SHGs - Parivartan - was developed by the non-governmental organisation (NGO), Project Concern International, in 64 blocks of eight districts. Layering included health modules, community events and review mechanisms. The health layering model was adapted for use with government-led SHGs, called JEEViKA+HL, in 37 other blocks of Bihar. Scale-up of government-led SHGs without health layering (JEEViKA) occurred contemporaneously in 433 other blocks, providing a natural comparison group. Using Community-based Household Surveys (CHS, rounds 6-9) by CARE India, 62 reproductive, maternal, newborn and child health and nutrition (RMNCHN) and sanitation indicators were examined for SHGs with health layering (Pavivartan SHGs and JEEViKA+HL SHGs) compared to those without. We calculated mean, standard deviation and odds ratios of indicators using surveymeans and survey logistic regression.ResultsIn 2014, 64% of indicators were significantly higher in Parivartan members compared to non-members residing in the same blocks. During scale up, from 2015-17, half (50%) of indicators had significantly higher odds in health layered SHG members (Parivartan or JEEViKA+HL) in 101 blocks compared to SHG members without health layering (JEEViKA) in 433 blocks.ConclusionsHealth layering of SHGs was demonstrated by an NGO-led model (Parivartan), adapted and scaled up by a government model (JEEViKA+HL), and associated with significant improvements in health compared to non-health-layered SHGs (JEEViKA). These results strengthen the evidence ...

In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's selfhelp groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011–2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011–2013. This paper—the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement—seeks to provide a broad description of Ananya and subsequent statewide adaptation and scaleup, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, to ...

In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply- and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's self-help groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011-2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011-2013. This paper - the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement - seeks to provide a broad description of Ananya and subsequent statewide adaptation and scale-up, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, to analyse and synthesise data from multiple sources. Capturing lessons from the Ananya pilot program and statewide scale-up will assist program managers and policymakers to more effectively design and implement RMNCHN programs at scale through technical assistance to governments.

In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply- and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's self-help groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011-2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011-2013. This paper - the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement - seeks to provide a broad description of Ananya and subsequent statewide adaptation and scale-up, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, ...