Search

Interest in using internet search data, such as that from the Google Health Trends Application Programming Interface (GHT-API), to measure epidemiologically relevant exposures or health outcomes is growing due to their accessibility and timeliness. Researchers enter search term(s), geography, and time period, and the GHT-API returns a scaled probability of that search term, given all searches within the specified geographic-time period. In this study, we detailed a method for using these data to measure a construct of interest in 5 iterative steps: first, identify phrases the target population may use to search for the construct of interest; second, refine candidate search phrases with incognito Google searches to improve sensitivity and specificity; third, craft the GHT-API search term(s) by combining the refined phrases; fourth, test search volume and choose geographic and temporal scales; and fifth, retrieve and average multiple samples to stabilize estimates and address missingness. An optional sixth step involves accounting for changes in total search volume by normalizing. We present a case study examining weekly state-level child abuse searches in the United States during the coronavirus disease 2019 pandemic (January 2018 to August 2020) as an application of this method and describe limitations.

In recent years, there has been growing interest in “moving beyond the individual” to measure area-level racism as a social determinant of health. Much of this work has aggregated racial prejudice data collected at the individual-level to the area-level. As this is a rapidly emerging area of research, we conducted a systematic literature review to describe evidence of the relationship between area-level racial prejudice and health, whether associations differed by race/ethnicity, and to characterize key conceptual and methodological considerations to guide future research. We searched four interdisciplinary databases for US-based, peer-reviewed articles measuring area-level racial prejudice by aggregating individual-level indicators of racial prejudice and examining associations with mental or physical health outcome(s). Data extraction followed PRISMA guidelines and also included theory and conceptualization, pathways to health, and strengths and limitations. Fourteen of 14,632 identified articles met inclusion criteria and were included in the review. Health outcomes spanned all-cause (n=4) and cause-specific (n=4) mortality, birth outcomes (n=4), cardiovascular outcomes (n=2), mental health (n=1), and self-rated health (n=1). All studies found a positive association between area-level racial prejudice and adverse health outcomes among racial/ethnic minoritized groups, with four studies also showing a similar association among Whites. Engagement with formal theory was limited and exposure conceptualization was mixed. Methodological considerations included unmeasured confounding and trade-offs between generalizability, self-censorship, and specificity of measurement. We suggest directions for future research to further develop the conceptual and methodological rigor of this work and inform evidence-based interventions to advance population health and reduce racial health inequities.

The COVID-19 pandemic has led to unemployment, school closures, movement restrictions, and social isolation, all of which are child abuse risk factors. Our objective was to estimate the effect of COVID-19 shelter in place (SIP) policies on child abuse as captured by Google searches. We applied a differences-in-differences design to estimate the effect of SIP on child abuse search volume. We linked state-level SIP policies to outcome data from the Google Health Trends Application Programming Interface. The outcome was searches for child abuse-related phrases as a scaled proportion of total searches for each state-week between December 31, 2017 and June 14, 2020. Between 914 and 1512 phrases were included for each abuse subdomain (physical, sexual, and emotional). Eight states and DC were excluded because of suppressed outcome data. Of the remaining states, 38 introduced a SIP policy between March 19, 2020 and April 7, 2020 and 4 states did not. The introduction of SIP generally led to no change, except for a slight reduction in child abuse search volume in weeks 8-10 post-SIP introduction, net of changes experienced by states that did not introduce SIP at the same time. We did not find strong evidence for an effect of SIP on child abuse searches. However, an increase in total search volume during the pandemic that may be differential between states with and without SIP policies could have biased these findings. Future work should examine the effect of SIP at the individual and population level using other data sources.

In recent years, life expectancy in the United States has stagnated, followed by three consecutive years of decline. The decline is small in absolute terms but is unprecedented and has generated considerable research interest and theorizing about potential causes. Recent trends show that the decline has affected nearly all race/ethnic and gender groups, and the proximate causes of the decline are increases in opioid overdose deaths, suicide, homicide, and Alzheimer's disease. A slowdown in the long-term decline in mortality from cardiovascular diseases has also prevented life expectancy from improving further. Although a popular explanation for the decline is the cumulative decline in living standards across generations, recent trends suggest that distinct mechanisms for specific causes of death are more plausible explanations. Interventions to stem the increase in overdose deaths, reduce access to mechanisms that contribute to violent deaths, and decrease cardiovascular risk over the life course are urgently needed to improve mortality in the United States.

ImportanceThe risk and timing of suicide among patients who undergo surgery for cancer remain largely unknown, and, to our knowledge, there are currently no organized programs in place to implement regular suicide screening among this patient population.ObjectiveTo evaluate the incidence, timing, and factors associated with suicide among patients undergoing cancer operations.Design, Setting, and ParticipantsThis retrospective population-based cohort study used data from the Surveillance, Epidemiology, and End Results Program database to examine the incidence of suicide, compared with the general US population, and timing of suicide among patients undergoing surgery for the 15 deadliest cancers in the US from 2000 to 2016. A Fine-Gray competing risks regression model was used to identify factors associated with an increased risk of suicide among patients in the cohort. Data were analyzed from September 2021 to January 2022.ExposuresSurgery for cancer.Main Outcomes and MeasuresIncidence, compared with the general US population, timing, and factors associated with suicide after surgery for cancer.ResultsFrom 2000 to 2016, 1 811 397 patients (74.4% female; median [IQR] age, 62.0 [52.0-72.0] years) met study inclusion criteria. Of these patients, 1494 (0.08%) committed suicide after undergoing surgery for cancer. The incidence of suicide, compared with the general US population, was statistically significantly higher among patients undergoing surgery for cancers of the larynx (standardized mortality ratio [SMR], 4.02; 95% CI, 2.67-5.81), oral cavity and pharynx (SMR, 2.43; 95% CI, 1.93-3.03), esophagus (SMR, 2.25; 95% CI, 1.43-3.38), bladder (SMR, 2.09; 95% CI, 1.53-2.78), pancreas (SMR, 2.08; 95% CI, 1.29-3.19), lung (SMR, 1.73; 95% CI, 1.47-2.02), stomach (SMR, 1.70; 95% CI, 1.22-2.31), ovary (SMR, 1.64; 95% CI, 1.13-2.31), brain (SMR, 1.61; 95% CI, 1.12-2.26), and colon and rectum (SMR, 1.28; 95% CI, 1.16-1.40). Approximately 3%, 21%, and 50% of suicides were committed within the first month, first year, and first 3 years after surgery, respectively. Patients who were male, White, and divorced or single were at greatest risk of suicide.Conclusions and RelevanceIn this cohort study, the incidence of suicide among patients undergoing cancer operations was statistically significantly elevated compared with the general population, highlighting the need for programs to actively implement regular suicide screening among such patients, especially those whose demographic and tumor characteristics are associated with the highest suicide risk.

BACKGROUND The COVID-19 pandemic has created environments with increased risk factors for household violence, such as unemployment and financial uncertainty. At the same time, it led to the introduction of policies to mitigate financial uncertainty. Further, it hindered traditional measurements of household violence. OBJECTIVE Using an infoveillance approach, our goal was to determine if there were excess Google searches related to exposure to child abuse, intimate partner violence (IPV), and child-witnessed IPV during the COVID-19 pandemic and if any excesses are temporally related to shelter-in-place and economic policies. METHODS Data on relative search volume for each violence measure was extracted using the Google Health Trends application programming interface for each week from 2017 to 2020 for the United States. Using linear regression with restricted cubic splines, we analyzed data from 2017 to 2019 to characterize the seasonal variation shared across prepandemic years. Parameters from prepandemic years were used to predict the expected number of Google searches and 95% prediction intervals (PI) for each week in 2020. Weeks with searches above the upper bound of the PI are in excess of the model’s prediction. RESULTS Relative search volume for exposure to child abuse was greater than expected in 2020, with 19% (10/52) of the weeks falling above the upper bound of the PI. These excesses in searches began a month after the Pandemic Unemployment Compensation program ended. Relative search volume was also heightened in 2020 for child-witnessed IPV, with 33% (17/52) of the weeks falling above the upper bound of the PI. This increase occurred after the introduction of shelter-in-place policies. CONCLUSIONS Social and financial disruptions, which are common consequences of major disasters such as the COVID-19 pandemic, may increase risks for child abuse and child-witnessed IPV.

Background The COVID-19 pandemic has created environments with increased risk factors for household violence, such as unemployment and financial uncertainty. At the same time, it led to the introduction of policies to mitigate financial uncertainty. Further, it hindered traditional measurements of household violence. Objective Using an infoveillance approach, our goal was to determine if there were excess Google searches related to exposure to child abuse, intimate partner violence (IPV), and child-witnessed IPV during the COVID-19 pandemic and if any excesses are temporally related to shelter-in-place and economic policies. Methods Data on relative search volume for each violence measure was extracted using the Google Health Trends application programming interface for each week from 2017 to 2020 for the United States. Using linear regression with restricted cubic splines, we analyzed data from 2017 to 2019 to characterize the seasonal variation shared across prepandemic years. Parameters from prepandemic years were used to predict the expected number of Google searches and 95% prediction intervals (PI) for each week in 2020. Weeks with searches above the upper bound of the PI are in excess of the model’s prediction. Results Relative search volume for exposure to child abuse was greater than expected in 2020, with 19% (10/52) of the weeks falling above the upper bound of the PI. These excesses in searches began a month after the Pandemic Unemployment Compensation program ended. Relative search volume was also heightened in 2020 for child-witnessed IPV, with 33% (17/52) of the weeks falling above the upper bound of the PI. This increase occurred after the introduction of shelter-in-place policies. Conclusions Social and financial disruptions, which are common consequences of major disasters such as the COVID-19 pandemic, may increase risks for child abuse and child-witnessed IPV.

Exposure to nitrogen dioxide (NO(2)), black carbon (BC), and ultrafine particles (UFP) during pregnancy may increase risk of preeclampsia, but previous studies have not assessed hyper-localized differences in pollutant levels which may cause exposure misclassification. We used data from Google Street View cars with mobile air monitors that repeatedly sampled NO(2), BC, and UFP every 30-meters in Downtown and West Oakland neighborhoods during 2015–2017. Data were linked to electronic health records of pregnant women in the 2014-2016 Sutter Health population who resided within 120-meters of monitoring data (N=1,095) to identify preeclampsia cases. We used G-computation with log-binomial regression to estimate risk differences (RD) associated with hypothetical interventions reducing pollutant levels to 25(th) percentiles observed in our sample on preeclampsia risk, overall and stratified by race/ethnicity. Prevalence of preeclampsia was 6.8%. Median (interquartile range) levels of NO(2), BC, and UFP were 10.8 ppb (9.0, 13.0), 0.34 μg/m(3) (0.27, 0.42), and 29.2 # × 10(3)/cm(3) (26.6, 32.6), respectively. Changes in the risk of preeclampsia achievable by limiting each pollutant to the 25(th) percentile was NO(2) RD =−1.5 per 100 women (95% confidence interval (CI): −2.5, −0.5); BC RD=−1.0 (95% CI: −2.2, 0.02); and UFP RD = −0.5 (95% CI: −1.8, 0.7). Estimated effects were largest for non-Latina Black mothers: NO(2) RD=−2.8 (95% CI: −5.2, −0.3) and BC RD=−3.0 (95% CI: −6.4, 0.4).

Supplemental Digital Content is available in the text., Background: Fetal growth restriction is commonly defined using small for gestational age (SGA) birth (birthweight < 10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying fetal growth restriction at birth that combines information on multiple, imperfect measures of fetal growth restriction in a probabilistic manner. Methods: We combined information on birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia using latent profile analysis to classify fetal growth in births at the Royal Victoria Hospital in Montreal, Canada, 2001–2009. We examined the clinical characteristics and health outcomes of infants classified as growth-restricted and nongrowth-restricted by our model, and among the subgroup of growth-restricted infants who had a birthweight ≥10th percentile (i.e., would have been missed by the conventional SGA proxy). Results: Among 26,077 births, 345 (1.3%) were classified as growth-restricted by our latent profile model. Growth-restricted infants were more likely than nongrowth-restricted infants to have an Apgar score

Background US preterm-birth rates are 1.6 times higher for Black mothers than for White mothers. Although traffic-related air pollution (TRAP) may increase the risk of preterm birth, evaluating its effect on preterm birth and disparities has been challenging because TRAP is often measured inaccurately. This study sought to estimate the effect of TRAP exposure, measured at the street level, on the prevalence of preterm birth by race/ethnicity. Methods We linked birth-registry data with TRAP measured at the street level for singleton births in sampled communities during 2013–2015 in Oakland and San Jose, California. Using logistic regression and marginal standardization, we estimated the effects of exposure to black carbon, nitrogen dioxide and ultrafine particles on preterm birth after confounder adjustment and stratification by race/ethnicity. Results There were 8823 singleton births, of which 760 (8.6%) were preterm. Shifting black-carbon exposure from the 10th to the 90th percentile was associated with: 6.8%age point higher risk of preterm birth (95% confidence interval = 0.1 to 13.5) among Black women; 2.1%age point higher risk (95% confidence interval = –1.1 to 5.2) among Latinas; and inconclusive null findings among Asian and White women. For Latinas, there was evidence of a positive association between the other pollutants and risk of preterm birth, although effect sizes were attenuated in models that co-adjusted for other TRAP. Conclusions Exposure to TRAP, especially black carbon, may increase the risk of preterm birth for Latina and Black women but not for Asian and White women.

Objectives: Racial differences in mortality in the United States have narrowed and vary by time and place. The objectives of our study were to (1) examine the gap in life expectancy between white and black persons (hereinafter, racial gap in life expectancy) in 4 states (California, Georgia, Illinois, and New York) and (2) estimate trends in the contribution of major causes of death (CODs) to the racial gap in life expectancy by age group. Methods: We extracted data on the number of deaths and population sizes for 1969-2013 by state, sex, race, age group, and 6 major CODs. We used a Bayesian time-series model to smooth and impute mortality rates and decomposition methods to estimate trends in sex- and age-specific contributions of CODs to the racial gap in life expectancy. Results: The racial gap in life expectancy at birth decreased in all 4 states, especially among men in New York (from 8.8 to 1.1 years) and women in Georgia (from 8.0 to 1.7 years). Although few deaths occurred among persons aged 1-39, racial differences in mortality at these ages (mostly from injuries and infant mortality) contributed to the racial gap in life expectancy, especially among men in California (1.0 year of the 4.3-year difference in 2013) and Illinois (1.9 years of the 6.7-year difference in 2013). Cardiovascular deaths contributed most to the racial gap in life expectancy for adults aged 40-64, but contributions decreased among women aged 40-64, especially in Georgia (from 2.8 to 0.5 years). The contribution of cancer deaths to inequality increased in California and Illinois, whereas New York had the greatest reductions in inequality attributable to cancer deaths (from 0.6 to 0.2 years among men and from 0.2 to 0 years among women). Conclusions: Future research should identify policy innovations and economic changes at the state level to better understand New York’s success, which may help other states emulate its performance.

Life expectancy has increased in the United States over many decades. The difference in life expectancy between black and white Americans has also decreased, but some states have made much more progress towards racial equality than others. This paper describes the pattern of contributions of six major causes of death to the black-white life expectancy gap within US states and the District of Columbia between 1969 and 2013, and identifies states diverging from the overall pattern. Across multiple causes, the District of Columbia, Illinois, Wisconsin, and Michigan had the highest contributions to black-white inequality, while New York, Massachusetts, and Rhode Island had the lowest contributions and have either achieved or are the closest to achieving black-white equality in life expectancy.

Objective To establish the degree of variation across hospitals in the use of Caesarean delivery for the indication of labour dystocia before and after accounting for maternal, fetal, and hospital characteristics. Methods This study was a retrospective, population-based cohort study of nulliparous women delivering term singletons in cephalic position following labour. Delivery visits were extracted from three provincial perinatal registries in the Canadian provinces of Ontario, Alberta, and British Columbia, from 2008-2012. Crude hospital-specific rates of Caesarean delivery for labour dystocia were reported, and these rates were then stabilized to account for hospitals with low delivery volumes. Rates were then adjusted for maternal, fetal, and hospital characteristics using hierarchical logistic regression. Results Among 403 205 women delivering at 170 hospitals, the overall Caesarean delivery rate was 21.0%, and the rate of Caesarean delivery for labour dystocia was 12.7%, indicating that 60% of all Caesarean deliveries were performed in part for this indication. The middle 95% of hospitals had Caesarean delivery rates for labour dystocia ranging from 4.5% to 24.7%. Differences in maternal case mix and hospital characteristics explained only a small proportion of this variation (95% central range 6.3%–21.7%). Conclusion Considerable inter-hospital variation in rates of Caesarean delivery for labour dystocia remained after accounting for differences in maternal and hospital factors. Reporting systems that monitor variation in inter-institutional rates should incorporate stabilization and adjustment for case-mix differences and consider indication-specific rates of Caesarean delivery to more fairly compare hospital performance and better target interventions to reduce Caesarean delivery for specific indications.

BACKGROUND: In recent decades, many smaller hospitals in British Columbia, Canada, have stopped providing planned obstetric services. We examined the effect of these service closures on the labour and delivery outcomes of pregnant women living in affected communities. METHODS: We used maternal postal codes to identify delivery records (1998–2014) of women residing in a community affected by service closure. The records were obtained from the British Columbia Perinatal Data Registry. We examined the effect of the closures using a within-communities fixed-effects framework and included similar-sized communities without service closures to control for underlying time trends. The primary outcome was a previously published composite measure of labour and delivery safety, the Adverse Outcome Index, which includes adverse events such as birth injury and unanticipated operative procedures, and includes weights for severity of adverse events. Secondary outcomes included maternal or newborn transfer, and use of obstetric interventions. RESULTS: We found little evidence that closure of planned obstetric services affected the risk of composite adverse maternal–newborn outcome (−0.4 excess adverse events per 100 deliveries, 95% confidence interval [CI] −2.0 to 1.1), or most other secondary outcomes. The severity of composite outcome events decreased following the closures (rate ratio 0.58, 95% CI 0.36 to 0.89). Closures were associated with increases in use of epidural analgesia (3.4 excess events per 100 deliveries, 95% CI 0.4 to 6.3) and length of antepartum stay (0.6 h, 95% CI 0.1 to 1.0 h). INTERPRETATION: Closure of planned obstetric services in low-volume hospitals was not associated with an increase or decrease in frequency of adverse events during labour and delivery.

Summary Background A good understanding of developmental trajectories is crucial for making prognoses, planning interventions, and monitoring progress in children and adolescents with cerebral palsy. Our study aimed to describe developmental trajectories of mobility and self-care capability in a large sample of children and adolescents with cerebral palsy from the Netherlands and Canada. Methods We did longitudinal data analyses of cohorts from the Netherlands (Pediatric Rehabilitation Research in the Netherlands; PERRIN) and Ontario, Canada (Adolescent Study of Quality of Life, Mobility, and Exercise; ASQME). All participants had a confirmed diagnosis of cerebral palsy and ranged in age from 1 year to 17 years at baseline, and were recruited from rehabilitation centres and university medical centres. Individuals diagnosed with additional conditions affecting motor function other than cerebral palsy (eg, spina bifida or muscle diseases) were excluded. After baseline assessment, up to three follow-up assessments were done at 1 year intervals. The whole spectrum of severity of cerebral palsy was represented in terms of motor function, using the Gross Motor Function Classification System (GMFCS). Mobility and self-care capability were assessed with the Pediatric Evaluation of Disability Inventory (PEDI). We applied non-linear mixed-effects modelling to estimate limits, rates, and variations of development. Findings For both projects, recruitment took place between 2002 and 2007. The combined dataset included 551 individuals with cerebral palsy (321 individuals from the PERRIN programme and 230 from ASQME), aged 1 year to 17 years at baseline, with longitudinal data available for up to 4 years. On the basis of a total of 1754 PEDI observations, we created developmental curves for ages 1–21 years. Both for mobility and self-care, limits and rates of development differed among individuals across GMFCS levels, resulting in distinct curves. For individuals classified as being in GMFCS level I, the estimated mean limit for mobility and self-care were both higher than 90 (95·6, 95% CI 94·5–96·7 for mobility and 91·8, 90·1–93·4 for self-care), indicating capability for most if not all items on the PEDI. By comparison, the estimated mean limits for children in levels II–V varied from 83·0 (80·3–85·7) to 23·6 (20·7–26·4), with increasing limitations in mobility and self-care capability for higher GMFCS levels. Individuals with lower GMFCS levels (ie, less severe cerebral palsy) showed higher developmental limits that were reached during a longer period of development. However, among individuals within the same GMFCS level, we found substantial interindividual variation in development for mobility, and even more so for self-care. Interpretation Prognosis for mobility and self-care capability can largely be based on developmental trajectories for children and adolescents with cerebral palsy grouped by GMFCS level. The interindividual variation in development within GMFCS levels indicates that, in addition to GMFCS level, other contextual factors need to be considered when discussing prognosis and management. Using the curves for individuals with cerebral palsy aged 1 year to 21 years, we illustrate how this new knowledge can be applied in paediatric practice. Funding The Netherlands Organisation for Health Research and Development and the Canadian Institutes of Health Research.

The biomarker-adaptive threshold design (BATD) allows researchers to simultaneously study the efficacy of treatment in the overall group and to investigate the relationship between a hypothesized predictive biomarker and the treatment effect on the primary outcome. It was originally developed for survival outcomes for Phase III clinical trials where the biomarker of interest is measured on a continuous scale. In this paper, generalizations of the BATD to accommodate count biomarkers and outcomes are developed and then studied in the multiple sclerosis (MS) context where the number of relapses is a commonly used outcome. Through simulation studies, we find that the BATD has increased power compared with a traditional fixed procedure under varying scenarios for which there exists a sensitive patient subgroup. As an illustration, we apply the procedure for two hypothesized markers, baseline enhancing lesion count and disease duration at baseline, using data from a previously completed trial. MS duration appears to be a predictive marker relationship for this dataset, and the procedure indicates that the treatment effect is strongest for patients who have had MS for less than 7.8 years. The procedure holds promise of enhanced statistical power when the treatment effect is greatest in a sensitive patient subgroup.

BackgroundIn recent decades, suicide and fatal overdose rates have increased in the US, particularly for working-age adults with no college education. The coincident decline in manufacturing has limited stable employment options for this population. Erosion of the Michigan automobile industry provides a striking case study.MethodsWe used individual-level data from a retrospective cohort study of 26 804 autoworkers in the United Autoworkers-General Motors cohort, using employment records from 1970 to 1994 and mortality follow-up from 1970 to 2015. We estimated HRs for suicide or fatal overdose in relation to leaving work, measured as active or inactive employment status and age at worker exit.ResultsThere were 257 deaths due to either suicide (n=202) or overdose (n=55); all but 21 events occurred after leaving work. The hazard rate for suicide was 16.1 times higher for inactive versus active workers (95% CI 9.8 to 26.5). HRs for suicide were elevated for all younger age groups relative to those leaving work after age 55. Those 30–39 years old at exit had the highest HR for suicide, 1.9 (95% CI 1.2 to 3.0). When overdose was included, the rate increased by twofold for both 19- to 29-year-olds and 30- to 39-year-olds at exit. Risks remained elevated when follow-up was restricted to 5 years after exit.ConclusionsAutoworkers who left work had a higher risk of suicide or overdose than active employees. Those who left before retirement age had higher rates than those who left after, suggesting that leaving work early may increase the risk.

Background The extent to which differences in homicide and suicide rates in black versus white men vary by U.S. state is unknown. Objective To compare the rates of firearm and nonfirearm homicide and suicide in black and white non-Hispanic men by U.S. state and to examine whether these deaths are associated with state prevalence of gun ownership. Design Surveillance study. Setting 50 states and the District of Columbia, 2008 to 2016. Cause-of-death data were abstracted by using the Centers for Disease Control and Prevention's WONDER (Wide-ranging Online Data for Epidemiologic Research) database. Participants Non-Hispanic black and non-Hispanic white males, all ages. Measurements Absolute rates of and rate differences in firearm and nonfirearm homicide and suicide in black and white men. Results During the 9-year study period, 84 113 homicides and 251 772 suicides occurred. Black-white differences in rates of firearm homicide and suicide varied widely across states. Relative to white men, black men had between 9 and 57 additional firearm homicides per 100 000 per year, with black men in Missouri, Michigan, Illinois, Indiana, and Pennsylvania having more than 40 additional firearm homicides per 100 000 per year. White men had between 2 fewer and 16 more firearm suicides per 100 000 per year, with the largest inequalities observed in southern and western states and the smallest in the District of Columbia and densely populated northeastern states. Limitations Some homicides and suicides may have been misclassified as deaths due to unintentional injury. Survey data on state household gun ownership were collected in 2004 and may have shifted during the past decade. Conclusion The large state-to-state variation in firearm homicide and suicide rates, as well as the racial inequalities in these numbers, highlights states where policies may be most beneficial in reducing homicide and suicide deaths and the racial disparities in their rates. Primary funding source McGill University and the National Institutes of Health.

OBJECTIVE:To identify whether a hospital's vaginal birth after cesarean delivery rate, trial of labor after cesarean delivery rate, or trial of labor success rate decrease after the occurrence of a uterine rupture.METHODS:The study population was drawn from the Nationwide Inpatient Sample, a sample of U.S. hospitals, between 1998 and 2010. We extracted deliveries to women with a previous cesarean delivery. International Classification of Diseases, 9th Revision, Clinical Modification codes were used to identify severe uterine ruptures and rates of vaginal birth, trial of labor, and trial of labor success. We used the difference-in-differences design and compared the rates of the outcomes before and after a rupture across hospitals using hospitals without ruptures to control for secular trends. Included in the analysis were 1,202,284 delivery records from 7,975 hospital-years without ruptures and 211,850 records from 510 hospital-years with uterine ruptures.RESULTS:Before the occurrence of a severe uterine rupture, there were an estimated 60 successful vaginal deliveries for every 100 women with a previous cesarean delivery who entered labor. In the month after the rupture, the trial of labor success rate decreased by an estimated 25 cases per 1,000 labors (95% confidence interval [CI] 6-44/1,000, P=.01) before returning to baseline. The percentage of women with a previous cesarean delivery who attempted vaginal delivery did not significantly change after the rupture. Overall, there were 17 more cesarean deliveries per 1,000 women with a previous cesarean delivery (95% CI 4-31/1,000, P=.01) in the month after the uterine rupture.CONCLUSION:The decrease in the trial of labor success rate after a recent uterine rupture is likely the result of short-term changes in risk evaluation.LEVEL OF EVIDENCE:II

States have fared differently in their progress towards eliminating the black-white life expectancy gap. Our objective is to describe the pattern of contributions of each of six major causes of deaths to the sex-specific black-white life expectancy gap across states over the last half-century, and identify divergent states.Using vital statistics and census data, we extracted the number of deaths and population sizes for the years 1969 to 2013, by state, gender, race, 19 age groups, and six major causes of death.Although mortality from cardiovascular disease has decreased dramatically, its contribution to the life expectancy gap increased over time for men (from 0.9 to 1.2 years), but decreased for women (from 2.4 to 1 years). The contribution of non-communicable diseases to the gap was stable over time for men (approximately 0.4 years) but decreased for women (from 0.7 to 0.2 years), while cancers exhibited an inverted-U trend for men (peaking at 1.1 years in 1988) and a stable contribution for women (approximately 0.5 years). Both genders exhibited a decreased contribution from injuries (men: 2.2 to 0.4 years), that became negative for women (women: 0.5 to -0.1 years). Several states diverged from these general trends.Life expectancy for both races has improved substantially in the US. For men, much of this improvement was due to narrowing differences in injury-related mortality, but these contributions were rivaled by an increasing gap in CVD-related mortality. In women, a crossover in injury-related mortality led to a narrower gap, realized partially by increasing mortality among whites.

Background Gestational weight gain is often characterized by the total amount of weight gained during pregnancy, however, the pattern of gain may be an important determinant of health outcomes. The SITAR (Super Imposition by Translation And Rotation) model has been used to describe childhood growth trajectories and has appeal because of the biological interpretability of its parameters. The objective of this study was to determine the feasibility of applying this model to gestational weight gain trajectories. Methods The study cohort included 3470 normal-weight, overweight, and obese women delivering at Magee-Womens Hospital in Pittsburgh, Pennsylvania, 1998 to 2010. We applied the SITAR model, a non-linear mixed effects model, to serial prenatal weight gain measurements in each pre-pregnancy body mass index (BMI) category. We fit models of varying complexity, and chose the best-fitting model to describe the pattern of weight gain (by its absolute amount, timing, and acceleration) for each BMI group. Results The most complex SITAR models failed to converge, but reduced models could successfully be fit by specifying fewer random effects and simplifying the modelling of gestational age. Best-fitting models for each BMI group explained between 95% and 97% of the variation in weight gain trajectories. Peak rates of weight gain were reached between the 20th and 22nd weeks, and were higher for normal and overweight women (0.59 kg/week and 0.57 kg/week, respectively) than obese women (0.46 kg/week). Conclusions Following some modifications, the SITAR model can be used to characterize pregnancy weight gain patterns.

Background Most methodologists recommend intention-to-treat (ITT) analysis in order to minimize bias. Although ITT analysis provides an unbiased estimate for the effect of treatment assignment on the outcome, the estimate is biased for the actual effect of receiving treatment (active treatment) compared to some comparison group (control). Other common analyses include measuring effects in (1) participants who follow their assigned treatment (Per Protocol), (2) participants according to treatment received (As Treated), and (3) those who would comply with recommended treatment (Complier Average Causal Effect (CACE) as estimated by Principal Stratification or Instrumental Variable Analyses). As each of these analyses compares different study subpopulations, they address different research questions. Purpose For each type of analysis, we review and explain (1) the terminology being used, (2) the main underlying concepts, (3) the questions that are answered and whether the method provides valid causal estimates, and (4) the situations when the analysis should be conducted. Methods We first review the major concepts in relation to four nuances of the clinical question, ‘Does treatment improve health?’ After reviewing these concepts, we compare the results of the different analyses using data from two published randomized controlled trials (RCTs). Each analysis has particular underlying assumptions and all require dichotomizing adherence into Yes or No. We apply sensitivity analyses so that intermediate adherence is considered (1) as adherence and (2) as non-adherence. Results The ITT approach provides an unbiased estimate for how active treatment will improve (1) health in the population if a policy or program is enacted or (2) health of patients if a clinician changes treatment practice. The CACE approach generally provides an unbiased estimate of the effect of active treatment on health of patients who would follow the clinician’s advice to take active treatment. Unfortunately, there is no current analysis for clinicians and patients who want to know whether active treatment will improve the patient’s health if taken, which is different from the effect in patients who would follow the clinician’s advice to take active treatment. Sensitivity analysis for the CACE using two published data sets suggests that the underlying assumptions appeared to be violated. Limitations There are several methods within each analytical approach we describe. Our analyses are based on a subset of these approaches. Conclusions Although adherence-based analyses may provide meaningful information, the analytical method should match the clinical question, and investigators should clearly outline why they believe assumptions hold and should provide empirical tests of the assumptions where possible.

Background: Canada’s Aboriginal population faces significantly higher rates of stillbirth and neonatal and postnatal death than those seen in the general population. The objective of this study was to compare indicators of obstetric care quality and use of obstetric interventions between First Nations and non-First Nations mothers in British Columbia, Canada. Methods: We linked obstetrical medical records with the First Nations Client File for all nulliparous women who delivered single infants in British Columbia from 1999 to 2011. Using logistic regression models, we examined differences in the proportion of women who received services aligned with best practice guidelines, as well as the overall use of obstetric interventions among First Nations mothers compared with the general population, controlling for geographic barriers (distance to hospital) and other relevant confounders. Results: During the study period, 215 993 single births occurred in nulliparous women in British Columbia, 9152 of which were to members of our First Nations cohort. First Nations mothers were less likely to have early ultrasonography (adjusted risk difference = 10.2 fewer women per 100 deliveries [95% confidence interval {CI} −11.3 to −9.3]), to have at least 4 antenatal care visits (3.6 fewer women per 100 deliveries [95% CI −4.6 to −2.6]), and to undergo labour induction after prolonged (> 24 hours) prelabour rupture of membranes (−5.9 [95% CI −11.8 to 0.1]) or at post-dates gestation (−10.6 [95% CI −13.8 to −7.5]). Obstetric interventions including epidural, labour induction, instrumental delivery and cesarean delivery were used less often in First Nations mothers. Interpretation: We identified differences in the obstetric care received by First Nations mothers compared with the general population. Such differences warrant further investigation, given increases in perinatal mortality that are consistently shown and that may be a downstream consequence of differences in care.

This study investigates recent trends in the absolute difference in overall and cause-specific infant mortality rates between non-Hispanic black infants and white infants.

Introduction Studies on the association of a polymorphism in codon 72 of the p53 tumour suppressor gene (rs1042522) with cervical neoplasia have inconsistent results. While several methods for genotyping p53 exist, they vary in accuracy and are often discrepant. Methods We used latent class models (LCM) to examine the accuracy of six methods for p53 determination, all conducted by the same laboratory. We also examined the association of p53 with cytological cervical abnormalities, recognising potential test inaccuracy. Results Pairwise disagreement between laboratory methods occurred approximately 10% of the time. Given the estimated true p53 status of each woman, we found that each laboratory method is most likely to classify a woman to her correct status. Arg/Arg women had the highest risk of squamous intraepithelial lesions (SIL). Test accuracy was independent of cytology. There was no strong evidence for correlations of test errors. Discussion Empirical analyses ignore possible laboratory errors, and so are inherently biased, but test accuracy estimated by the LCM approach is unbiased when model assumptions are met. LCM analysis avoids ambiguities arising from empirical test discrepancies, obviating the need to regard any of the methods as a “gold” standard measurement. The methods we presented here to analyse the p53 data can be applied in many other situations where multiple tests exist, but where none of them is a gold standard.