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In the United States, more than 30,000 cases of mpox (formerly known as monkeypox) had occurred as of March 1, 2023, in an outbreak disproportionately affecting transgender persons and gay, bisexual, and other men who have sex with men. In 2019, the JYNNEOS vaccine was approved for subcutaneous administration (0.5 ml per dose) to prevent mpox infection. On August 9, 2022, an emergency use authorization was issued for intradermal administration (0.1 ml per dose); however, real-world effectiveness data are limited for either route. We conducted a case-control study based on data from Cosmos, a nationwide Epic electronic health record (EHR) database, to assess the effectiveness of JYNNEOS vaccination in preventing medically attended mpox disease among adults. Case patients had an mpox diagnosis code or positive orthopoxvirus or mpox virus laboratory result, and control patients had an incident diagnosis of human immunodeficiency virus (HIV) infection or a new or refill order for preexposure prophylaxis against HIV infection between August 15, 2022, and November 19, 2022. Odds ratios and 95% confidence intervals were estimated from conditional logistic-regression models, adjusted for confounders; vaccine effectiveness was calculated as (1 - odds ratio for vaccination in case patients vs. controls) × 100. Among 2193 case patients and 8319 control patients, 25 case patients and 335 control patients received two doses (full vaccination), among whom the estimated adjusted vaccine effectiveness was 66.0% (95% confidence interval [CI], 47.4 to 78.1), and 146 case patients and 1000 control patients received one dose (partial vaccination), among whom the estimated adjusted vaccine effectiveness was 35.8% (95% CI, 22.1 to 47.1). In this study using nationwide EHR data, patients with mpox were less likely to have received one or two doses of JYNNEOS vaccine than control patients. The findings suggest that JYNNEOS vaccine was effective in preventing mpox disease, and a two-dose series appeared to provide better protection. (Funded by the Centers for Disease Control and Prevention and Epic Research.).

Objectives. We determined differences in weight at age 18 years and at current age and weight change by sexual orientation within different racial/ethnic populations, stratifying by gender. Methods. We used 2001–2007 data from the California Health Interview Survey, resulting in an unweighted sample of 120 274 individuals aged 18 to 74 years. Using regression models, we examined overweight status and change in weight by sexual orientation, stratifying by race/ethnicity and gender. Results. Compared with heterosexual women of the same race/ethnicity, White and African American lesbians and bisexuals had increased likelihood of being overweight at age 18 years and maintaining overweight status during adulthood. Sexual minority status was unrelated to weight among Latinas and inconsistently linked to weight among Asian women compared with heterosexual women of the same race/ethnicity. Sexual minority status was protective against unhealthy weight among White, African American, Asian, and Latino men compared with heterosexual counterparts of the same race/ethnicity. This protective effect was seen after age 18 years except among African American bisexual men. Conclusions. Our findings indicate a need for age- and culture-sensitive interventions that reduce weight or prevent weight gain in sexual minority women and men.

Diabetes during pregnancy increases the risk for adverse maternal and infant health outcomes. Type 1 or type 2 diabetes diagnosed before pregnancy (preexisting diabetes) increases infants' risk for congenital anomalies, stillbirth, and being large for gestational age (1). Diabetes that develops and is diagnosed during the second half of pregnancy (gestational diabetes) increases infants' risk for being large for gestational age (1) and might increase the risk for childhood obesity (2); for mothers, gestational diabetes increases the risk for future type 2 diabetes (3). In the United States, prevalence of both preexisting and gestational diabetes increased from 2000 to 2010 (4,5). Recent state-specific trends have not been reported; therefore, CDC analyzed 2012-2016 National Vital Statistics System (NVSS) birth data. In 2016, the crude national prevalence of preexisting diabetes among women with live births was 0.9%, and prevalence of gestational diabetes was 6.0%. Among 40 jurisdictions with continuously available data from 2012 through 2016, the age- and race/ethnicity-standardized prevalence of preexisting diabetes was stable at 0.8% and increased slightly from 5.2% to 5.6% for gestational diabetes. Preconception care and lifestyle interventions before, during, and after pregnancy might provide opportunities to control, prevent, or mitigate health risks associated with diabetes during pregnancy.

Women who enter pregnancy at a weight above or below normal weight, defined as a body mass index (BMI) of 18.5-24.9 (calculated as weight in kg/height in m ), are more likely to experience adverse pregnancy outcomes and to have infants who experience adverse health outcomes. For example, prepregnancy underweight (BMI <18.5) increases the risk for small-for-gestational-age births, whereas prepregnancy overweight (BMI 25.0-29.9) and obesity (BMI ≥30.0) increase risks for cesarean delivery, large-for-gestational-age births, and childhood obesity (1). Given these outcomes, Healthy People 2020 includes an objective to increase the proportion of women entering pregnancy with a normal weight from 52.5% in 2007 to 57.8% by 2020.* Because recent trends in prepregnancy normal weight have not been reported, CDC examined 2011-2015 National Vital Statistics System (NVSS) natality data, which included prepregnancy BMI. In 2015, for 48 states, the District of Columbia (DC), and New York City (NYC) combined, the prevalence of prepregnancy normal weight was 45.0%; prevalence ranged from 37.7% in Mississippi to 52.2% in DC. Among 38 jurisdictions with prepregnancy BMI data during 2011-2015, normal weight prevalence declined from 47.3% to 45.1%; declines were observed in all jurisdictions but were statistically significant for 27 jurisdictions after standardizing to the 2011 national maternal age and race/ethnicity distribution. Screening women's BMI during routine clinical care provides opportunities to promote normal weight before entering pregnancy.

Objectives Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. Methods We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. Results Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. Practice Implications Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.

There is no known safe amount of alcohol consumption during pregnancy; drinking alcohol during pregnancy can cause fetal alcohol spectrum disorders and might increase the risk for miscarriage and stillbirth (1). The prevalence of drinking among pregnant women increased slightly during 2011-2018; however, more recent estimates are not yet reported (2). CDC estimated the prevalence of self-reported current drinking (at least one alcoholic drink in the past 30 days) and binge drinking (consuming four or more drinks on at least one occasion in the past 30 days) among pregnant adults aged 18-49 years, overall and by selected characteristics, using 2018-2020 Behavioral Risk Factor Surveillance System (BRFSS) data. During 2018-2020, 13.5% of pregnant adults reported current drinking and 5.2% reported binge drinking: both measures were 2 percentage points higher than during 2015-2017. Pregnant adults with frequent mental distress were 2.3 and 3.4 times as likely to report current and binge drinking, respectively, compared with those without frequent mental distress. In addition, pregnant adults without a usual health care provider were 1.7 times as likely to report current drinking as were those with a current provider. Alcohol consumption during pregnancy continues to be a serious problem. Integration of mental health services into clinical care and improving access to care might help address alcohol consumption and mental distress during pregnancy to prevent associated adverse outcomes (3).

Background Accurate estimation of gestational age is important for both clinical and public health purposes. Estimates of gestational age using fetal ultrasound measurements are considered most accurate but are frequently unavailable in low- and middle-income countries. The objective of this study was to assess the validity of last menstrual period and Farr neonatal examination estimates of gestational age, compared to ultrasound estimates, in a large cohort of women in Vietnam. Methods Data for this analysis come from a randomized, placebo-controlled micronutrient supplementation trial in Vietnam. We analyzed 912 women with ultrasound and prospectively-collected last menstrual period estimates of gestational age and 685 women with ultrasound and Farr estimates of gestational age. We used the Wilcoxon signed rank sum test to assess differences in gestational age estimated by last menstrual period or Farr examination compared to ultrasound and computed the intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) to quantify agreement between methods. We computed the Kappa coefficient (κ) to quantify agreement in preterm, term and post-term classification. Results The median gestational age estimated by ultrasound was 273.9 days. Gestational age was slightly overestimated by last menstrual period (median 276.0 days, P  < 0.001) and more greatly overestimated by Farr examination (median 286.7 days, P  < 0.001). Gestational age estimates by last menstrual period and ultrasound were moderately correlated (ICC = 0.78) and concordant (CCC = 0.63), whereas gestational age estimates by Farr examination and ultrasound were weakly correlated (ICC = 0.26) and concordant (CCC = 0.05). Last menstrual period and ultrasound estimates of gestational age were within ± 14 days for 88.4% of women; Farr and ultrasound estimates were within ± 14 days for 55.8% of women. Last menstrual period and ultrasound estimates of gestational age had higher agreement in term classification (κ = 0.41) than Farr and ultrasound (κ = 0.05). Conclusion In this study of women in Vietnam, we found last menstrual period provided a more accurate estimate of gestational age than the Farr examination when compared to ultrasound. These findings provide useful information about the utility and accuracy of different methods to estimate gestational age and suggest last menstrual period may be preferred over Farr examination in settings where ultrasound is unavailable. Trial registration The trial was registered at ClinicalTrials.Gov as NCT01665378 on August 13, 2012.

IntroductionPostpartum care is an important strategy for preventing and managing chronic disease in women with pregnancy complications (i.e., gestational diabetes (GDM) and hypertensive disorders of pregnancy (HDP)).MethodsUsing a population-based, cohort study among Oregon women with Medicaid-financed deliveries (2009–2012), we examined Medicaid-financed postpartum care (postpartum visits, contraceptive services, and routine preventive health services) among women who retained Medicaid coverage for at least 90 days after delivery (n = 74,933). We estimated postpartum care overall and among women with and without GDM and/or HDP using two different definitions: 1) excluding care provided on the day of delivery, and 2) including care on the day of delivery. Pearson chi-square tests were used to assess differential distributions in postpartum care by pregnancy complications (p < .05), and generalized estimating equations were used to calculate adjusted odds ratios (aORs) with 95% confidence intervals (CIs).ResultsOf Oregon women who retained coverage through 90 days after delivery, 56.6–78.1% (based on the two definitions) received any postpartum care, including postpartum visits (26.5%-71.8%), contraceptive services (30.7–35.6%), or other routine preventive health services (38.5–39.1%). Excluding day of delivery services, the odds of receiving any postpartum care (aOR 1.26, 95% CI 1.08–1.47) or routine preventive services (aOR 1.32, 95% CI 1.14–1.53) were meaningfully higher among women with GDM and HDP (reference = neither).DiscussionMedicaid-financed postpartum care in Oregon was underutilized, it varied by pregnancy complications, and needs improvement. Postpartum care is important for all women and especially those with GDM or HDP, who may require chronic disease risk assessment, management, and referrals.

BACKGROUND:The 2003 revision of the US Standard Certificate of Live Birth (birth certificate) and Pregnancy Risk Assessment Monitoring System (PRAMS) are important for maternal weight research and surveillance. We examined quality of prepregnancy body mass index (BMI), gestational weight gain, and component variables from these sources. METHODS:Data are from a PRAMS data quality improvement study among a subset of New York City and Vermont respondents in 2009. We calculated mean differences comparing prepregnancy BMI data from the birth certificate and PRAMS (n = 734), and gestational weight gain data from the birth certificate (n = 678) to the medical record, considered the gold standard. We compared BMI categories (underweight, normal weight, overweight, obese) and gestational weight gain categories (below, within, above recommendations), classified by different sources, using percent agreement and the simple κ statistic. RESULTS:For most maternal weight variables, mean differences between the birth certificate and PRAMS compared with the medical record were less than 1 kg. Compared with the medical record, the birth certificate classified similar proportions into prepregnancy BMI categories (agreement = 89%, κ = 0.83); PRAMS slightly underestimated overweight and obesity (agreement = 84%, κ = 0.73). Compared with the medical record, the birth certificate overestimated gestational weight gain below recommendations and underestimated weight gain within recommendations (agreement = 81%, κ = 0.69). Agreement varied by maternal and pregnancy-related characteristics. CONCLUSIONS:Classification of prepregnancy BMI and gestational weight gain from the birth certificate or PRAMS was mostly similar to the medical record but varied by maternal and pregnancy-related characteristics. Efforts to understand how misclassification influences epidemiologic associations are needed.