Evaluating the Use of an Electronic Death Registration System for Mortality Surveillance During and After Hurricane Sandy: New York City, 2012.

OBJECTIVES: We evaluated the use of New York City's (NYC's) electronic death registration system (EDRS) to conduct mortality surveillance during and after Hurricane Sandy. METHODS: We used Centers for Disease Control and Prevention guidelines for surveillance system evaluation to gather evidence on usefulness, flexibility, stability, timeliness, and quality. We assessed system components, interviewed NYC Health Department staff, and analyzed 2010 to 2012 death records. RESULTS: Despite widespread disruptions, NYC's EDRS was stable and collected timely mortality data that were adapted to provide storm surveillance with minimal additional resources. Direct-injury fatalities and trends in excess all-cause mortality were rapidly identified, providing useful information for response; however, the time and burden of establishing reports, adapting the system, and identifying indirect deaths limited surveillance. CONCLUSIONS: The NYC Health Department successfully adapted its EDRS for near real-time disaster-related mortality surveillance. Retrospective assessment of deaths, advanced methods for case identification and analysis, standardized reports, and system enhancements will further improve surveillance. Local, state, and federal partners would benefit from partnering with vital records to develop EDRSs for surveillance and to promote ongoing evaluation.

How well do birth records serve maternal and child health programs? Birth registration system evaluation, New York City, 2008-2011.

National birth registration guidelines were revised in 2003 to improve data quality; however, few studies have evaluated the impact on local jurisdictions and their data users. In New York City (NYC), approximately 125,000 births are registered annually with the NYC Department of Health and Mental Hygiene, and data are used routinely by the department's maternal and child health (MCH) programs. In order to better meet MCH program needs, we used Centers for Disease Control and Prevention guidelines to assess birth data usefulness, simplicity, data quality, timeliness and representativeness. We interviewed birth registration and MCH program staff, reviewed a 2009 survey of birth registrars (n = 39), and analyzed 2008-2011 birth records for timeliness and completeness (n = 502,274). Thirteen MCH programs use birth registration data for eligibility determination, needs assessment, program evaluation, and surveillance. Demographic variables are used frequently, nearly 100 % complete, and considered the gold standard by programs; in contrast, medical variables' use and validity varies widely. Seventy-seven percent of surveyed birth registrars reported ≥1 problematic items in the system; 64.1 % requested further training. During 2008-2011, the median interval between birth and registration was 5 days (range 0-260 days); 11/13 programs were satisfied with timeliness. The NYC birth registration system provides local MCH programs useful, timely, and representative data. However, some medical items are difficult to collect, of low quality, and rarely used. We recommend enhancing training for birth registrars, continuing quality improvement efforts, increasing collaboration with program users, and removing consistently low-quality and low-use variables.

Reliability of Reported Maternal Smoking: Comparing the Birth Certificate to Maternal Worksheets and Prenatal and Hospital Medical Records, New York City and Vermont, 2009.

Maternal smoking is captured on the 2003 US Standard Birth Certificate based on self-reported tobacco use before and during pregnancy collected on post-delivery maternal worksheets. Study objectives were to compare smoking reported on the birth certificate to maternal worksheets and prenatal and hospital medical records. The authors analyzed a sample of New York City (NYC) and Vermont women (n = 1,037) with a live birth from January to August 2009 whose responses to the Pregnancy Risk Assessment Monitoring System survey were linked with birth certificates and abstracted medical records and maternal worksheets. We calculated smoking prevalence and agreement (kappa) between sources overall and by maternal and hospital characteristics. Smoking before and during pregnancy was 13.7 and 10.4% using birth certificates, 15.2 and 10.7% using maternal worksheets, 18.1 and 14.1% using medical records, and 20.5 and 15.0% using either maternal worksheets or medical records. Birth certificates had "almost perfect" agreement with maternal worksheets for smoking before and during pregnancy (κ = 0.92 and 0.89) and "substantial" agreement with medical records (κ = 0.70 and 0.74), with variation by education, insurance, and parity. Smoking information on NYC and Vermont birth certificates closely agreed with maternal worksheets but was underestimated compared with medical records, with variation by select maternal characteristics. Opportunities exist to improve birth certificate smoking data, such as reducing the stigma of smoking, and improving the collection, transcription, and source of information.

A case study of the impact of inaccurate cause-of-death reporting on health disparity tracking: New York City premature cardiovascular mortality.

OBJECTIVES: Heart disease death overreporting is problematic in New York City (NYC) and other US jurisdictions. We examined whether overreporting affects the premature (< 65 years) heart disease death rate disparity between non-Hispanic Blacks and non-Hispanic Whites in NYC. METHODS: We identified overreporting hospitals and used counts of premature heart disease deaths at reference hospitals to estimate corrected counts. We then corrected citywide, age-adjusted premature heart disease death rates among Blacks and Whites and a White-Black premature heart disease death disparity. RESULTS: At overreporting hospitals, 51% of the decedents were White compared with 25% at reference hospitals. Correcting the heart disease death counts at overreporting hospitals decreased the age-adjusted premature heart disease death rate 10.1% (from 41.5 to 37.3 per 100,000) among Whites compared with 4.2% (from 66.2 to 63.4 per 100,000) among Blacks. Correction increased the White-Black disparity 6.1% (from 24.6 to 26.1 per 100,000). CONCLUSIONS: In 2008, NYC's White-Black premature heart disease death disparity was underestimated because of overreporting by hospitals serving larger proportions of Whites. Efforts to reduce overreporting may increase the observed disparity, potentially obscuring any programmatic or policy-driven advances.

Causal models for investigating complex disease: I. A primer.

BACKGROUND/AIMS: To illustrate the utility of causal models for research in genetic epidemiology and statistical genetics. Causal models are increasingly applied in risk factor epidemiology, economics, and health policy, but seldom used in statistical genetics or genetic epidemiology. Unlike the statistical models usually used in genetic epidemiology, causal models are explicitly formulated in terms of cause and effect relationships occurring at the individual level. METHODS: We describe two causal models, the sufficient component cause model and the potential outcomes model, and show how key concepts in genetic epidemiology, including penetrance, phenocopies, genetic heterogeneity, etiologic heterogeneity, gene-gene interaction, and gene-environment interaction, can be framed in terms of these causal models. We also illustrate how potential outcomes models can provide insight into the potential for confounding and bias in the measurement of causal effects in genetic studies. RESULTS: Our analysis illustrates how causal models can elucidate the relationships among underlying causal mechanisms and measures obtained from statistical analysis of observed data. CONCLUSION: Causal models can enhance research aimed at identifying causal genes.

Causal models for investigating complex genetic disease: II. what causal models can tell us about penetrance for additive, heterogeneity, and multiplicative two-locus models.

BACKGROUND/AIMS: Statistical geneticists commonly use certain two-locus penetrance models because these models are familiar and mathematically tractable. We investigate whether and under what circumstances these two-locus penetrance models correspond to models of causation. METHODS: We describe a sufficient component cause model for a hypothetical disease with two genetic causes. We then use the potential outcomes framework to determine the expected two-locus penetrances from this causal model and contrast them with commonly used two-locus penetrance models (additive, heterogeneity, and multiplicative penetrance models, as formulated by Risch [Am J Hum Genet 1990;46:222-228]). RESULTS: Conventional additive and multiplicative models can correspond to any two-locus causal model only when certain very specific algebraic relationships hold. The heterogeneity model corresponds to a two-locus causal model only if the model stipulates that no disease cases are caused by the combined presence of the causal genotypes at both loci (i.e. only when there is no causal gene-gene interaction). Hence the heterogeneity model provides a valid test of the null hypothesis of no gene-gene interaction, whereas the additive and multiplicative models do not. CONCLUSION: We suggest that causal principles should provide the basis for statistical modeling in genetics.

Postapproval Comparative Safety Study of Tofacitinib and Biological Disease-Modifying Antirheumatic Drugs: 5-Year Results from a United States-Based Rheumatoid Arthritis Registry.

OBJECTIVE: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). We compared 5-year adverse event (AE) incidence rates (IRs) between patients initiating tofacitinib and those initiating new biological disease-modifying antirheumatic drugs (bDMARDs) within the United States (US) Corrona RA registry. METHODS: IRs (number of first events/100 patient-years) of major adverse cardiovascular events (MACE), serious infection events (SIEs), herpes zoster (HZ), malignancies, and death were estimated among tofacitinib and bDMARD initiators, regardless of dose/schedule, between November 6, 2012 (US Food and Drug Administration tofacitinib approval), and July 31, 2018 (follow-up through January 31, 2019). Propensity score (PS) methods were used to control for nonrandom prescribing practices. Hazard ratios (HRs) were calculated to compare rates using multivariable-adjusted Cox regression. Different risk windows were used for acute (MACE, SIEs, HZ, and venous thromboembolic events [VTEs]) and long-term (malignancy and death) events. VTEs were assessed descriptively. RESULTS: For MACE, SIEs, and HZ, 1999 (3152.1 patient-years) and 8358 (12 869.4 years) tofacitinib and bDMARD initiators were included, respectively; for malignancy/death, 1999 (4505.6 patient-years) and 6354 (16 670.8 patient-years) initiators were included, respectively. AE rates were similar across cohorts, except for HZ, which was significantly higher with tofacitinib versus bDMARDs (PS-trimmed adjusted HR 2.32; 95% confidence interval [CI] 1.43-3.75). There were 45 (zero serious) and 88 (five serious) HZ events with tofacitinib and bDMARDs, respectively. Sensitivity analyses demonstrated similar results. VTE IRs (95% CI) were 0.29 (0.13-0.54) and 0.33 (0.24-0.45) for tofacitinib and bDMARDs, respectively. CONCLUSION: In this registry analysis, both cohorts had similar MACE, SIE, malignancy, death, and VTE rates; HZ rates were higher for tofacitinib initaitors than for bDMARD initiators.

Antioxidant vitamin supplementation reduces benzo(a)pyrene-DNA adducts and potential cancer risk in female smokers.

BACKGROUND: Elevated benzo(a)pyrene [B(a)P]-DNA adducts have been associated with 3-fold increased risk of lung cancer in current smokers. We assessed the chemopreventive effects of antioxidant supplementation using B(a)P-DNA adducts in leukocytes as an intermediate cancer risk marker. METHODS: Subjects were randomized to a double-blinded placebo-controlled clinical trial of antioxidant vitamin supplementation [500 mg vitamin C and 400 IU vitamin E (dl-alpha-tocopherol) daily] or placebo. Smokers with > or =10 cigarettes per day and serum cotinine > or =25 ng/mL were eligible for the study. B(a)P-DNA adduct level was the outcome. The randomization was stratified by gender and cigarettes per day (< or =20 or >20). Smoking habits and blood samples were collected every 3 months during the 15-month treatment period. Samples were analyzed for B(a)P-DNA adducts (high-performance liquid chromatography), plasma cotinine, vitamin levels, and GSTM1 genotype. The intent-to-treat model adjusted for B(a)P-DNA and cotinine at randomization. RESULTS: Overall and among men, there was no effect of treatment on B(a)P-DNA adduct levels. Among treated women, B(a)P-DNA adducts decreased by 31% compared with women on placebo (P = 0.03). Among treated women with the GSTM1 genotype, there was a 43% decrease in adducts (P = 0.04). CONCLUSION: Our primary hypothesis that the mean level of smoking-related B(a)P-DNA adducts would be lower in all subjects in the vitamin treatment group compared with all placebo-treated subjects was not substantiated. However, oursecondary gender-specific analysis found a significant reduction in B(a)P-DNA adducts in women with vitamin treatment, suggesting that antioxidant supplementation maymitigate some of the procarcinogenic effects of exposuretoB(a)P. The effect in GSTM1-null women suggeststhat certain subgroups may derive more benefit fromsupplementation. Although the results of this trial showthe potential chemopreventive role of antioxidants, thebest way for smokers to reduce their cancer risk remains smoking cessation.

Assessing electronic death registration and american red cross systems for mortality surveillance during Hurricane Sandy, October 29-November 10, 2012, New York City.

OBJECTIVE: We briefly describe 2 systems that provided disaster-related mortality surveillance during and after Hurricane Sandy in New York City, namely, the New York City Health Department Electronic Death Registration System (EDRS) and the American Red Cross paper-based tracking system. METHODS: Red Cross fatality data were linked with New York City EDRS records by using decedent name and date of birth. We analyzed cases identified by both systems for completeness and agreement across selected variables and the time interval between death and reporting in the system. RESULTS: Red Cross captured 93% (41/44) of all Sandy-related deaths; the completeness and quality varied by item, and timeliness was difficult to determine. The circumstances leading to death captured by Red Cross were particularly useful for identifying reasons individuals stayed in evacuation zones. EDRS variables were nearly 100% complete, and the median interval between date of death and reporting was 6 days (range: 0-43 days). CONCLUSIONS: Our findings indicate that a number of steps have the potential to improve disaster-related mortality surveillance, including updating Red Cross surveillance forms and electronic databases to enhance timeliness assessments, greater collaboration across agencies to share and use data for public health preparedness, and continued expansion of electronic death registration systems.