Holly B. Shulman

Risk factors for legal induced abortion-related mortality in the United States.

OBJECTIVE: To assess risk factors for legal induced abortion–related deaths. METHODS: This is a descriptive epidemiologic study of women dying of complications of induced abortions. Numerator data are from the Abortion Mortality Surveillance System. Denominator data are from the Abortion Surveillance System, which monitors the number and characteristics of women who have legal induced abortions in the United States. Risk factors examined include age of the woman, gestational length of pregnancy at the time of termination, race, and procedure. Main outcome measures include crude, adjusted, and risk factor–specific mortality rates. RESULTS: During 1988–1997, the overall death rate for women obtaining legally induced abortions was 0.7 per 100,000 legal induced abortions. The risk of death increased exponentially by 38% for each additional week of gestation. Compared with women whose abortions were performed at or before 8 weeks of gestation, women whose abortions were performed in the second trimester were significantly more likely to die of abortion-related causes. The relative risk (unadjusted) of abortion-related mortality was 14.7 at 13–15 weeks of gestation (95% confidence interval [CI] 6.2, 34.7), 29.5 at 16–20 weeks (95% CI 12.9, 67.4), and 76.6 at or after 21 weeks (95% CI 32.5, 180.8). Up to 87% of deaths in women who chose to terminate their pregnancies after 8 weeks of gestation may have been avoidable if these women had accessed abortion services before 8 weeks of gestation. CONCLUSION: Although primary prevention of unintended pregnancy is optimal, among women who choose to terminate their pregnancies, increased access to surgical and nonsurgical abortion services may increase the proportion of abortions performed at lower-risk, early gestational ages and help further decrease deaths. LEVEL OF EVIDENCE: II-2

The Pregnancy Risk Assessment Monitoring System (PRAMS): Current Methods and Evaluation of 2001 Response Rates

Objectives. Our objectives were to describe the methodology of the Pregnancy Risk Assessment Monitoring System (PRAMS), examine recent response rates, determine characteristics associated with response, and track response patterns over time. Methods. PRAMS is a mixed-mode surveillance system, using mail and telephone surveys. Rates for response, contact, cooperation, and refusal were computed for 2001. Logistic regression was used to examine the relationship between maternal and infant characteristics and the likelihood of response. Response patterns from 1996 to 2001 were compared for nine states. Results. The median response rate for the 23 states in 2001 was 76% (range: 49% to 84%). Cooperation rates ranged from 86% to 97% (median 91%); contact rates ranged from 58% to 93% (median 82%). Response rates were higher for women who were older, white, married, had more education, were first-time mothers, received early prenatal care, and had a normal birthweight infant. Education level was the most consistent predictor of response, followed by marital status and maternal race. From 1996 to 2001, response to the initial mailing decreased in all states compared, but the decrease was offset by increases in mail follow-up and telephone response rates. Overall response rates remained unchanged. Conclusions. The PRAMS mail/telephone methodology is an effective means of reaching most recent mothers in the 23 states examined, but some population subgroups are more difficult to reach than others. Through more intensive follow-up efforts, PRAMS states have been able to maintain high response rates over time despite decreases in response to the initial mailing.

The Pregnancy Risk Assessment Monitoring System (PRAMS): methods and 1996 response rates from 11 states.

Objectives: To determine if the Pregnancy Risk Assessment Monitoring System (PRAMS) is a unique and valuable MCH data source and an effective mechanism for states to collect MCH data, and to assess if recent changes in it have improved efficiency and flexibility. Methods: Each component of the PRAMS methodology is described: sampling and stratification, data collection, questionnaire, and data management and weighting. To assess effectiveness, we calculated response rates, contact rates, cooperation rates, refusal rates, and questionnaire completion rates. Logistic regression was used to examine the relationship between maternal and infant characteristics and the likelihood of response. Four criteria were defined to measure improvement in PRAMS functioning. Results: Overall response rates for the 11 states in 1996 ranged from 66% to 80%. Cooperation rates were high (85–99%), with contact rates somewhat lower (73–87%). Response rates were higher for women who were older, White, married, had more education, were first-time mothers, and had a normal-birthweight infant. In all states, parity and education were the most consistent predictors of response, followed by marital status and race. Between 1988–1990 and 1996–1999, the number of states and areas participating in PRAMS increased from 6 to 23, response rates improved, and the time for a state to start data collection and to obtain a weighted dataset both decreased. Conclusions: PRAMS is a unique and valuable MCH data source. The mail/telephone methodology used in PRAMS is an effective means of reaching most women who have recently given birth in the 11 states examined; however, some population subgroups are not reached as well as others. The system has become more efficient and flexible over time and more states now participate.

Sliding-Spans Diagnostics for Seasonal and Related Adjustments

Abstract When are the results of a seasonal adjustment procedure (or another smoothing procedure) likely to be of little value? The diagnostic approach presented in this article offers an answer to this question and to other questions concerned with the comparison of competing adjustments. It is based on a straightforward idea. A minimal requirement of the output of any smoothing or adjustment procedure is stability: Appending or deleting a small number of series values should not substantially change the smoothed values—otherwise, what reliable interpretation can they have? An important related principle is that, for a given series, if only one of several plausible signal-extraction procedures has a stable output, then this procedure should be the preferred one for the series. To implement these principles successfully, the definition of stability must be made precise in an appropriate way. The implementation described in this article is focused on multiplicative adjustments produced by the widely used X...

Vital Signs: Trends and Disparities in Infant Safe Sleep Practices — United States, 2009–2015

INTRODUCTION There have been dramatic improvements in reducing infant sleep-related deaths since the 1990s, when recommendations were introduced to place infants on their backs for sleep. However, there are still approximately 3,500 sleep-related deaths among infants each year in the United States, including those from sudden infant death syndrome, accidental suffocation and strangulation in bed, and unknown causes. Unsafe sleep practices, including placing infants in a nonsupine (on side or on stomach) sleep position, bed sharing, and using soft bedding in the sleep environment (e.g., blankets, pillows, and soft objects) are modifiable risk factors for sleep-related infant deaths.

Implementation Science and the Pregnancy Risk Assessment Monitoring System

This paper describes the restructuring of the Pregnancy Risk Assessment Monitoring System (PRAMS), a surveillance system of the Centers for Disease Control and Prevention (CDC)s Division of Reproductive Health conducted for 25 years in collaboration with state and city health departments. With the ultimate goal to better inform health care providers, public health programs, and policy, changes were made to various aspects of PRAMS to enhance its capacity on assessing and monitoring public health interventions and clinical practices in addition to risk behaviors, disease prevalence, comorbidities, and service utilization. Specifically, the three key PRAMS changes identified as necessary and described in this paper are questionnaire revision, launching the web-based centralized PRAMS Integrated Data Collection System, and enhancing the access to PRAMS data through the web query system known as Centers for Disease Control and Preventions PRAMS Online Data for Epidemiologic Research/PRAMStat. The seven action steps of Knowledge To Action cycle, an illustration of the implementation science process, that reflect the milestones necessary in bridging the knowledge-to-action gap were used as framework for each of these key changes.

The Pregnancy Risk Assessment Monitoring System (PRAMS): Overview of Design and Methodology

Data System The Pregnancy Risk Assessment Monitoring System (PRAMS) is an ongoing state-based surveillance system of maternal behaviors, attitudes, and experiences before, during, and shortly after pregnancy. PRAMS is conducted by the Centers for Disease Control and Prevention’s Division of Reproductive Health in collaboration with state health departments. Data Collection/Processing Birth certificate records are used in each participating jurisdiction to select a sample representative of all women who delivered a live-born infant. PRAMS is a mixed-mode mail and telephone survey. Annual state sample sizes range from approximately 1000 to 3000 women. States stratify their sample by characteristics of public health interest such as maternal age, race/ethnicity, geographic area of residence, and infant birth weight. Data Analysis/Dissemination States meeting established response rate thresholds are included in multistate analytic data sets available to researchers through a proposal submission process. In addition, estimates from selected indicators are available online. Public Health Implications PRAMS provides state-based data for key maternal and child health indicators that can be tracked over time. Stratification by maternal characteristics allows for examinations of disparities over a wide range of health indicators.