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ABSTRACT This study describes and demonstrates different techniques for surface fitting daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 µm ([PM.sub.2.5]) for [...]

BACKGROUND: Studies on the association between prenatal exposure to fine particulate matter ≤ 2.5 µm in aerodynamic diameter ([PM.sub.2.5]) and term low birth weight (LBW) have resulted in inconsistent findings. Most studies were conducted in snapshots of small geographic areas and no national study exists. OBJECTIVES: We investigated geographic variation in the associations between ambient [PM.sub.2.5] during pregnancy and term LBW in the contiguous United States. METHODS: A total of 3,389,450 term singleton births in 2002 (37-44 weeks gestational age and birth weight of 1,000-5,500 g) were linked to daily [PM.sub.2.5] via imputed birth days. We generated average daily [PM.sub.2.5] during the entire pregnancy and each trimester. Multi-level logistic regression models with county-level random effects were used to evaluate the associations between term LBW and [PM.sub.2.5] during pregnancy. RESULTS: Without adjusting for covariates, the odds of term LBW increased 2% [odds ratio (OR) = 1.02; 95% CI: 1.00, 1.03] for every 5-µg/[m.sup.3] increase in [PM.sub.2.5] exposure during the second trimester only, which remained unchanged after adjusting for county-level poverty (OR = 1.02; 95% CI: 1.01, 1.04). The odds did change to null after adjusting for individual-level predictors (OR = 1.00; 95% CI: 0.99, 1.02). Multi-level analyses, stratified by census division, revealed significant positive associations of term LBW and [PM.sub.2.5] exposure (during the entire pregnancy or a specific trimester) in three census divisions of the United States: Middle Atlantic, East North Central, and West North Central, and significant negative association in the Mountain division. CONCLUSIONS: Our study provided additional evidence on the associations between [PM.sub.2.5] exposure during pregnancy and term LBW from a national perspective. The magnitude and direction of the estimated associations between [PM.sub.2.5] exposure and term LBW varied by geographic locations in the United States. http://dx.doi.org/10.1289/ehp.1408798, Introduction Low birth weight (LBW) is a known risk factor for infant morbidity and mortality and chronic health problems in later life (McCormick 1985). Maternal exposure to particulate matter ([PM.sub.2.5]--fine [...]

Abstract Background Progress has been made recently in estimating ambient PM2.5 (particulate matter with aerodynamic diameter < 2.5 μm) and ozone concentrations using various data sources and advanced modeling techniques, which resulted in gridded surfaces. However, epidemiologic and health impact studies often require population exposures to ambient air pollutants to be presented at an appropriate census geographic unit (CGU), where health data are usually available to maintain confidentiality of individual health data. We aim to generate estimates of population exposures to ambient PM2.5 and ozone for U.S. CGUs. Methods We converted 2001-2006 gridded data, generated by the U.S. Environmental Protection Agency (EPA) for CDC's (Centers for Disease Control and Prevention) Environmental Public Health Tracking Network (EPHTN), to census block group (BG) based on spatial proximities between BG and its four nearest grids. We used a bottom-up (fine to coarse) strategy to generate population exposure estimates for larger CGUs by aggregating BG estimates weighted by population distribution. Results The BG daily estimates were comparable to monitoring data. On average, the estimates deviated by 2 μg/m3 (for PM2.5) and 3 ppb (for ozone) from their corresponding observed values. Population exposures to ambient PM2.5 and ozone varied greatly across the U.S. In 2006, estimates for daily potential population exposure to ambient PM2.5 in west coast states, the northwest and a few areas in the east and estimates for daily potential population exposure to ambient ozone in most of California and a few areas in the east/southeast exceeded the National Ambient Air Quality Standards (NAAQS) for at least 7 days. Conclusions These estimates may be useful in assessing health impacts through linkage studies and in communicating with the public and policy makers for potential intervention.

Background: The Centers for Disease Control and Prevention (CDC) developed county level metrics for the Environmental Public Health Tracking Network (Tracking Network) to characterize potential population exposure to airborne particles with an aerodynamic diameter of 2.5 µm or less (PM2.5). These metrics are based on Federal Reference Method (FRM) air monitor data in the Environmental Protection Agency (EPA) Air Quality System (AQS); however, monitor data are limited in space and time. In order to understand air quality in all areas and on days without monitor data, the CDC collaborated with the EPA in the development of hierarchical Bayesian (HB) based predictions of PM2.5 concentrations. This paper describes the generation and evaluation of HB-based county level estimates of PM2.5. Methods: We used three geo-imputation approaches to convert grid-level predictions to county level estimates. We used Pearson (r) and Kendall Tau-B (t) correlation coefficients to assess the consistency of the relationship, and examined the direct differences (by county) between HB-based estimates and AQS-based concentrations at the daily level. We further compared the annual averages using Tukey mean-difference plots. Results: During the year 2005, fewer than 20% of the counties in the conterminous United States (U.S.) had PM2.5 monitoring and 32% of the conterminous U.S. population resided in counties with no AQS monitors. County level estimates resulting from population-weighted centroid containment approach were correlated more strongly with monitor-based concentrations (r = 0.9; t = 0.8) than were estimates from other geo-imputation approaches. The median daily difference was -0.2 µg/m³ with an interquartile range (IQR) of 1.9 µg/m³ and the median relative daily difference was -2.2% with an IQR of 17.2%. Under-prediction was more prevalent at higher concentrations and for counties in the western U.S. Conclusions: While the relationship between county level HB-based estimates and AQS-based concentrations is generally good, there are clear variations in the strength of this relationship for different regions of the U.S. and at various concentrations of PM2.5. This evaluation suggests that population-weighted county centroid containment method is an appropriate geo-imputation approach, and using the HB-based PM2.5 estimates to augment gaps in AQS data provides a more spatially and temporally consistent basis for calculating the metrics deployed on the Tracking Network. [ABSTRACT FROM AUTHOR]

The article discusses the evolution and challenges of public health surveillance in the U.S. Topics discussed include the use of public health surveillance in health problems and epidemics detection, the role of surveillance data in the demographic and geographic distribution of health events that can be used to facilitate public health planning, and the impact of information sciences dissemination and data system proliferation on public health surveillance.

A letter to the editor is presented in response to the article "The Reporting of HIV/AIDS Deaths in Women," by J. W. Buehler et al.

A response by P. Z. Siegal, J. R. Qualters and P. D. Mowery to a letter to the editor about their article "Subgroup-Specific Effects of Questionnaire Wording on Population-Based Estimates of Mammography Prevalence" in the May 2001 issue is presented.

The U.S. COVID-19 vaccination program launched on December 14, 2020. The Advisory Committee on Immunization Practices recommended prioritizing COVID-19 vaccination for specific groups of the U.S. population who were at highest risk for COVID-19 hospitalization and death, including adults aged ≥75 years*; implementation varied by state, and eligibility was gradually expanded to persons aged ≥65 years beginning in January 2021. By April 19, 2021, eligibility was expanded to all adults aged ≥18 years nationwide. † To assess patterns of COVID-19 vaccination coverage among U.S. adults, CDC analyzed data submitted on vaccinations administered during December 14, 2020-May 22, 2021, by age, sex, and community-level characteristics. By May 22, 2021, 57.0% of persons aged ≥18 years had received ≥1 COVID-19 vaccine dose; coverage was highest among persons aged ≥65 years (80.0%) and lowest among persons aged 18-29 years (38.3%). During the week beginning February 7, 2021, vaccination initiation among adults aged ≥65 years peaked at 8.2%, whereas weekly initiation among other age groups peaked later and at lower levels. During April 19-May 22, 2021, the period following expanded eligibility to all adults, weekly initiation remained <4.0% and decreased for all age groups, including persons aged 18-29 years (3.6% to 1.9%) and 30-49 years (3.5% to 1.7%); based on the current rate of weekly initiation (as of May 22), younger persons will not reach the same levels of coverage as older persons by the end of August. Across all age groups, coverage (≥1 dose) was lower among men compared with women, except among adults aged ≥65 years, and lower among persons living in counties that were less urban, had higher social vulnerabilities, or had higher percentages of social determinants of poor health. Continued efforts to improve vaccination confidence and alleviate barriers to vaccination initiation, especially among adults aged 18-49 years, could improve vaccination coverage., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Disparities in vaccination coverage by social vulnerability, defined as social and structural factors associated with adverse health outcomes, were noted during the first 2.5 months of the U.S. COVID-19 vaccination campaign, which began during mid-December 2020 (1). As vaccine eligibility and availability continue to expand, assuring equitable coverage for disproportionately affected communities remains a priority. CDC examined COVID-19 vaccine administration and 2018 CDC social vulnerability index (SVI) data to ascertain whether inequities in COVID-19 vaccination coverage with respect to county-level SVI have persisted, overall and by urbanicity. Vaccination coverage was defined as the number of persons aged ≥18 years (adults) who had received ≥1 dose of any Food and Drug Administration (FDA)-authorized COVID-19 vaccine divided by the total adult population in a specified SVI category. † SVI was examined overall and by its four themes (socioeconomic status, household composition and disability, racial/ethnic minority status and language, and housing type and transportation). Counties were categorized into SVI quartiles, in which quartile 1 (Q1) represented the lowest level of vulnerability and quartile 4 (Q4), the highest. Trends in vaccination coverage were assessed by SVI quartile and urbanicity, which was categorized as large central metropolitan, large fringe metropolitan (areas surrounding large cities, e.g., suburban), medium and small metropolitan, and nonmetropolitan counties. § During December 14, 2020-May 1, 2021, disparities in vaccination coverage by SVI increased, especially in large fringe metropolitan (e.g., suburban) and nonmetropolitan counties. By May 1, 2021, vaccination coverage was lower among adults living in counties with the highest overall SVI; differences were most pronounced in large fringe metropolitan (Q4 coverage = 45.0% versus Q1 coverage = 61.7%) and nonmetropolitan (Q4 = 40.6% versus Q1 = 52.9%) counties. Vaccination coverage disparities were largest for two SVI themes: socioeconomic status (Q4 = 44.3% versus Q1 = 61.0%) and household composition and disability (Q4 = 42.0% versus Q1 = 60.1%). Outreach efforts, including expanding public health messaging tailored to local populations and increasing vaccination access, could help increase vaccination coverage in high-SVI counties., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Approximately 60 million persons in the United States live in rural counties, representing almost one fifth (19.3%) of the population.* In September 2020, COVID-19 incidence (cases per 100,000 population) in rural counties surpassed that in urban counties (1). Rural communities often have a higher proportion of residents who lack health insurance, live with comorbidities or disabilities, are aged ≥65 years, and have limited access to health care facilities with intensive care capabilities, which places these residents at increased risk for COVID-19-associated morbidity and mortality (2,3). To better understand COVID-19 vaccination disparities across the urban-rural continuum, CDC analyzed county-level vaccine administration data among adults aged ≥18 years who received their first dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine, or a single dose of the Janssen COVID-19 vaccine (Johnson & Johnson) during December 14, 2020-April 10, 2021 in 50 U.S. jurisdictions (49 states and the District of Columbia [DC]). Adult COVID-19 vaccination coverage was lower in rural counties (38.9%) than in urban counties (45.7%) overall and among adults aged 18-64 years (29.1% rural, 37.7% urban), those aged ≥65 years (67.6% rural, 76.1% urban), women (41.7% rural, 48.4% urban), and men (35.3% rural, 41.9% urban). Vaccination coverage varied among jurisdictions: 36 jurisdictions had higher coverage in urban counties, five had higher coverage in rural counties, and five had similar coverage (i.e., within 1%) in urban and rural counties; in four jurisdictions with no rural counties, the urban-rural comparison could not be assessed. A larger proportion of persons in the most rural counties (14.6%) traveled for vaccination to nonadjacent counties (i.e., farther from their county of residence) compared with persons in the most urban counties (10.3%). As availability of COVID-19 vaccines expands, public health practitioners should continue collaborating with health care providers, pharmacies, employers, faith leaders, and other community partners to identify and address barriers to COVID-19 vaccination in rural areas (2)., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

In its landmark 1988 report, a committee of the Institute of Medicine highlighted assessment as one of the three core functions of public health along with policy development and assurance. The committee recommended that every public health agency regularly and systematically collect, assemble, analyze, and make available information on the health of the community, including statistics on health status, community health needs, and epidemiologic and other studies of health problems. Public health surveillance, often called the cornerstone of public health practice, is an essential element of the assessment function.

This study was undertaken to examine the validity of self-reported data on breast and cervical cancer screening behavior. An abbreviated version of the Behavioral Risk Factor Surveillance System telephone survey, including questions on mammography, clinical breast examination (CBE), and Papanicolaou test utilization, was administered to a sample of 480 women aged 40-74 years, enrolled in Kaiser Permanente Colorado for at least 5 years. Screening information reported in the telephone interview was compared with that abstracted from respondents' medical records. The vast majority of women had a mammogram, CBE, and Pap test according to both self-report and medical record. Sensitivity for determining whether her last test was within 2 years (3 years for Pap test) exceeded 95% for all, whereas specificities were <55%. The percentage of overall agreement between self-reported and recorded information was 88.4% (kappa = 0.62) for mammography, 87.9% (kappa = 0.45) for CBE, and 87.2% (kappa = 0.54) for Pap test. Pearson correlations between self-reported and recorded information for specific time interval since most recent mammogram, CBE, and Pap test were 0.72, 0.58, and 0.65, respectively. Correlation increased greatly when time interval was allowed to vary by +/-1 year. In most cases of disagreement, the self-report underestimated the time since last screening. These results suggest that self-reporting of breast and cervical cancer screening is fairly accurate in this managed care population, although women tend to underestimate the time since their last screening.