Structural Racism, Mass Incarceration, and Racial and Ethnic Disparities in Severe Maternal Morbidity

Importance

Racial and ethnic inequities in the criminal-legal system are an important manifestation of structural racism. However, how these inequities may influence the risk of severe maternal morbidity (SMM) and its persistent racial and ethnic disparities remains underinvestigated.

Objective

To examine the association between county-level inequity in jail incarceration rates comparing Black and White individuals and SMM risk in California.

Design, Setting, and Participants

This population-based cross-sectional study used state-wide data from California on all live hospital births at 20 weeks of gestation or later from January 1, 1997, to December 31, 2018. Data were obtained from hospital discharge and vital statistics records, which were linked with publicly available county-level data. Data analysis was performed from January 2022 to February 2023.

Exposure

Jail incarceration inequity was determined from the ratio of jail incarceration rates of Black individuals to those of White individuals and was categorized as tertile 1 (low), tertile 2 (moderate), tertile 3 (high), with mean cutoffs across all years of 0 to 2.99, 3.00 to 5.22, and greater than 5.22, respectively.

Main Outcome and Measures

This study used race- and ethnicity-stratified mixed-effects logistic regression models with birthing people nested within counties and adjusted for individual- and county-level characteristics to estimate the odds of non-blood transfusion SMM (NT SMM) and SMM including blood transfusion-only cases (SMM; as defined by the Centers for Disease Control and Prevention SMM index) associated with tertiles of incarceration inequity.

Results

This study included 10 200 692 births (0.4% American Indian or Alaska Native, 13.4% Asian or Pacific Islander, 5.8% Black, 50.8% Hispanic or Latinx, 29.6% White, and 0.1% multiracial or other [individuals who self-identified with ≥2 racial groups and those who self-identified as "other" race or ethnicity]). In fully adjusted models, residing in counties with high jail incarceration inequity (tertile 3) was associated with higher odds of SMM for Black (odds ratio [OR], 1.14; 95% CI, 1.01-1.29 for NT SMM; OR, 1.20, 95% CI, 1.01-1.42 for SMM), Hispanic or Latinx (OR, 1.24; 95% CI, 1.14-1.34 for NT SMM; OR, 1.20; 95% CI, 1.14-1.27 for SMM), and White (OR, 1.02; 95% CI, 0.93-1.12 for NT SMM; OR, 1.09; 95% CI, 1.02-1.17 for SMM) birthing people, compared with residing in counties with low inequity (tertile 1).

Conclusions and Relevance

The findings of this study highlight the adverse maternal health consequences of structural racism manifesting via the criminal-legal system and underscore the need for community-based alternatives to inequitable punitive practices.

Structural racism, nativity and risk of adverse perinatal outcomes among Black women

BACKGROUND

Black women in the United States (US) have the highest risk of preterm birth (PTB) and small for gestational age (SGA) births, compared to women of other racial groups. Among Black women, there are disparities by nativity whereby foreign-born women have a lower risk of PTB and SGA compared to US-born women. Differential exposure to racism may confer nativity-based differences in adverse perinatal outcomes between US- and foreign-born Black women. This remains unexplored among US- and African-born women in California.

OBJECTIVES

Evaluate the relationship between structural racism, nativity, PTB and SGA among US- and African-born Black women in California.

METHODS

We conducted a population-based study of singleton births to US- and African-born Black women in California from 2011 to 2017 (n = 131,424). We examined the risk of PTB and SGA by nativity and neighbourhoods with differing levels of structural racism, as measured by the Index of Concentration at the Extremes. We fit crude and age-adjusted Poisson regression models, estimated using generalized estimating equations, with risk ratios (RR) and 95% confidence intervals (CI) as the effect measure.

RESULTS

The proportions of PTB and SGA were 9.7% and 14.5%, respectively, for US-born women, while 5.6% and 8.3% for African-born women. US-born women (n = 24,782; 20.8%) were more likely to live in neighbourhoods with high structural racism compared to African-born women (n = 1474; 11.6%). Structural racism was associated with an elevated risk of PTB (RR 1.19, 95% CI 1.12, 1.26) and SGA (RR 1.19, 95% CI 1.13, 1.25) for all Black women, however, there was heterogeneity by nativity, with US-born women experiencing a higher magnitude of effect than African-born women.

CONCLUSIONS

Among Black women in California, exposure to structural racism and the impacts of structural racism on the risk of PTB and SGA varied by nativity.

Racial differences in associations between adverse childhood experiences and physical, mental, and behavioral health

Purpose

Adverse childhood experiences (ACEs) are associated with poor adulthood health. Multiracial people have elevated mean ACEs scores and risk of several outcomes. We aimed to determine whether this group should be targeted for prevention efforts.

Methods

We analyzed three waves (1994-2009) of the National Longitudinal Study of Adolescent to Adult Health (n = 12,372) in 2023, estimating associations between four or more ACEs and physical (metabolic syndrome, hypertension, asthma), mental (anxiety, depression), and behavioral (suicidal ideation, drug use) outcomes. We estimated adjusted risk ratios for each outcome in modified Poisson models interacting race and ACEs. We used the interaction contrast to estimate race-specific excess cases per 1000 relative to Multiracial participants.

Results

Excess case estimates of asthma were smaller for White (-123 cases, 95% CI: -251, -4), Black (-141, 95% CI: -285, -6), and Asian (-169, 95% CI: -334, -7) participants compared to Multiracial participants. Black (-100, 95% CI: -189, -10), Asian (-163, 95% CI: -247, -79) and Indigenous (-144, 95% CI: -252, -42) participants had fewer excess cases of and weaker relative scale association with anxiety compared to Multiracial participants.

Conclusions

Adjusted associations with asthma and anxiety appear stronger for Multiracial people. Existing ACEs prevention strategies should be tailored to support Multiracial youth and families.

Comparing Two-way Fixed Effects and New Estimators for Difference-in-Differences: A Simulation Study and Empirical Example

BACKGROUND

Two-way fixed effects methods have been used to estimate effects of policies adopted in different places over time, but they can provide misleading results when effects are heterogeneous or dynamic, and alternate methods have been proposed.

METHODS

We compared methods for estimating the average treatment effect on the treated (ATT) under staggered adoption of policies, including two-way fixed effects, group-time ATT, cohort ATT, and target-trial approaches. We applied each method to assess the impact of Medicaid expansion on preterm birth using the National Center for Health Statistics' birth records. We compared each estimator's performance in a simulation parameterized to mimic the empirical example. We generated constant, heterogeneous, and dynamic effects and calculated bias, mean squared error, and confidence interval coverage of each estimator across 1000 iterations.

RESULTS

Two-way fixed effects estimated that Medicaid expansion increased the risk of preterm birth (risk difference [RD], 0.12; 95% CI = 0.02, 0.22), while the group-time ATT, cohort ATT, and target-trial approaches estimated protective or null effects (group-time RD, -0.16; 95% CI = -0.58, 0.26; cohort RD, -0.02; 95% CI = -0.46, 0.41; target trial RD, -0.16; 95% CI = -0.59, 0.26). In simulations, two-way fixed effects performed well when treatment effects were constant and less well under heterogeneous and dynamic effects.

CONCLUSIONS

We demonstrated why new approaches perform better than two-way fixed effects when treatment effects are heterogeneous or dynamic under a staggered policy adoption design, and created simulation and analysis code to promote understanding and wider use of these methods in the epidemiologic literature.

A hypothetical intervention to reduce inequities in anxiety for Multiracial people: simulating an intervention on childhood adversity

Multiracial people report higher mean Adverse Childhood Experiences (ACEs) scores and prevalence of anxiety than other racial groups. Studies using statistical interactions to estimate racial differences in ACEs-anxiety associations do not show stronger associations for Multiracial people. Using data from Waves 1 (1995-97) through 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we simulated a stochastic intervention over 1,000 resampled datasets to estimate the race-specific cases averted per 1,000 of anxiety if all racial groups had the same exposure distribution of ACEs as Whites. Simulated cases averted were greatest for the Multiracial group, (median = -4.17 cases per 1,000, 95% CI: -7.42, -1.86). The model also predicted smaller risk reductions for Black participants (-0.76, 95% CI: -1.53, -0.19). CIs around estimates for other racial groups included the null. An intervention to reduce racial disparities in exposure to ACEs could help reduce the inequitable burden of anxiety on the Multiracial population. Stochastic methods support consequentialist approaches to racial health equity, and can encourage greater dialogue between public health researchers, policymakers, and practitioners.

Racial Differences in Associations Between Adverse Childhood Experiences and Physical, Mental, and Behavioral Health

Introduction

Adverse childhood experiences (ACEs) are associated with poor adulthood health, with individuals experiencing multiple ACEs at greatest risk. Multiracial people have high mean ACEs scores and elevated risk of several outcomes, but are infrequently the focus of health equity research. This study aimed to determine whether this group should be targeted for prevention efforts.

Methods

We analyzed Waves 1 (1994-95), 3 (2001-02), and 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (n = 12,372) in 2023, estimating associations between four or more ACEs and physical (metabolic syndrome, hypertension, asthma), mental (anxiety, depression), and behavioral (suicidal ideation, drug use) outcomes. We estimated risk ratios for each outcome in modified Poisson models with a race × ACEs interaction, adjusted for hypothesized confounders of the ACE-outcome relationships. We used the interaction contrast to estimate excess cases per 1,000 individuals for each group relative to Multiracial participants.

Results

Excess case estimates of asthma were significantly smaller for White (-123 cases, 95% CI: -251, -4), Black (-141, 95% CI: -285, -6), and Asian (-169, 95% CI: -334, -7) participants compared to Multiracial participants. Black (-100, 95% CI: -189, -10), Asian (-163, 95% CI: -247, -79) and Indigenous (-144, 95% CI: -252, -42) participants had significantly fewer excess cases of and weaker (p < 0.001) relative scale association with anxiety compared to Multiracial participants.

Conclusions

Adjusted associations between ACEs and asthma or anxiety appear stronger for Multiracial people than other groups. ACEs are universally harmful but may contribute disproportionately to morbidity in this population.

Incidence, Timing, and Factors Associated With Suicide Among Patients Undergoing Surgery for Cancer in the US

Importance

The 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.

Objective

To evaluate the incidence, timing, and factors associated with suicide among patients undergoing cancer operations.

Design, Setting, and Participants

This 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.

Exposures

Surgery for cancer.

Main Outcomes and Measures

Incidence, compared with the general US population, timing, and factors associated with suicide after surgery for cancer.

Results

From 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 Relevance

In 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.

Harnessing Google Health Trends Data for Epidemiologic Research

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.

Area-level racial prejudice and health: A systematic review

BACKGROUND

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.

OBJECTIVE

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 results differed by race/ethnicity, and to characterize key conceptual and methodological considerations to guide future research.

METHOD

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.

RESULTS

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.

CONCLUSIONS

Future research should continue to develop the conceptual and methodological rigor of this work and test hypotheses to inform evidence-based interventions to advance population health and reduce racial health inequities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Hyper-localized measures of air pollution and risk of preterm birth in Oakland and San Jose, California

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.

Declining Life Expectancy in the United States: Missing the Trees for the Forest

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.

A New Approach for Classifying Fetal Growth Restriction

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 <7 (10% vs. 2%), have hypoglycemia at birth (17% vs. 3%), require neonatal intensive care unit admission (59% vs. 6%), die in the perinatal period (3.8% vs. 0.2%), and require an emergency cesarean delivery (42% vs. 15%). Risks remained elevated in growth-restricted infants who were not SGA, suggesting our model identified at-risk infants not detected using the SGA proxy.

CONCLUSIONS

Latent profile analysis is a promising strategy for classifying growth restriction at birth in fetal growth restriction research.

Suicide, overdose and worker exit in a cohort of Michigan autoworkers

BACKGROUND

In 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.

METHODS

We 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.

RESULTS

There 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.

CONCLUSIONS

Autoworkers 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.

Using change in a seat belt law to study racially-biased policing in South Carolina

Seat belt laws have increased seat belt use in the US and contributed to reduced fatalities and injuries. However, these policies provide the potential for increased discrimination. The objective of this study is to determine whether a change in seat belt use enforcement led to a differential change in the number of stops, arrests, and searches to White, Black and Hispanic drivers in one US state. We used data on 1,091,424 traffic stops conducted by state troopers in South Carolina in 2005 and 2006 to examine how the change from secondary to primary enforcement of seat belt use in December 2005 affected the number of stops, arrests, and searches to White, Black, and Hispanic drivers using quasi-Poisson and logistic regressions. We found that the policy led to a 50% increase in the number of non-speeding stops for White drivers, and that this increase was 5% larger among Black drivers [RR (95% CI) = 1.05 (1.00, 1.10)], but not larger among Hispanic drivers [1.00 (0.93, 1.08)]. The policy decreased arrests and searches among non-speeding stops, with larger decreases for Black vs. White drivers [RR searches = 0.86 (0.81, 0.91) and RR arrests = 0.90 (0.85, 0.96)]. For Hispanic drivers, effects of the policy change were also found among stops for speeding, which failed the falsification test and suggested that other changes likely affected this group. These findings may support the hypothesis of differential enforcement of seat belt policy in South Carolina for Black and White drivers.

Black and White Differences in Life Expectancy in 4 US States, 1969-2013

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.

Informing randomized clinical trials of respiratory syncytial virus vaccination during pregnancy to prevent recurrent childhood wheezing: A sample size analysis

BACKGROUND

Early RSV illness is associated with wheeze-associated disorders in childhood. Candidate respiratory syncytial virus (RSV) vaccines may prevent acute RSV illness in infants. We investigated the feasibility of maternal RSV vaccine trials to demonstrate reductions in recurrent childhood wheezing in general paediatric populations.

METHODS

We calculated vaccine trial effect sizes that depended on vaccine efficacy, allocation ratio, rate of early severe RSV illness, risk of recurrent wheezing at age 3, and increased risk of RSV infection on recurrent wheezing. Model inputs came from systematic reviews and meta-analyses. For each combination of inputs, we estimated the sample size required to detect the effect of vaccination on recurrent wheezing.

RESULTS

There were 81 scenarios with 1:1 allocation ratio. Risk ratios between vaccination and recurrent wheezing ranged from 0.9 to 1.0 for 70% of the scenarios. Among the 57 more plausible scenarios, the lowest sample size required to detect significant reductions in recurrent wheezing was 6196 mother-infant pairs per trial arm; however, 75% and 47% of plausible scenarios required >31,060 and >100,000 mother-infant pairs per trial arm, respectively. Studies with asthma endpoints at age 5 will likely need to be larger.

DISCUSSION

Clinical efficacy trials of candidate maternal RSV vaccines undertaken for licensure are unlikely to demonstrate an effect on recurrent wheezing illness due to the large sample sizes likely needed to demonstrate a significant effect. Further efforts are needed to plan for alternative study designs to estimate the impact of maternal RSV vaccine programs on recurrent childhood wheezing in general populations.

Trends in the contribution of major causes of death to the black-white life expectancy gap by US state

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.

Comparison of Rates of Firearm and Nonfirearm Homicide and Suicide in Black and White Non-Hispanic Men, by U.S. State

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.

Classifying Gestational Weight Gain Trajectories Using the SITAR Growth Model

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.

Safety of labour and delivery following closures of obstetric services in small community hospitals

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.

Differences in obstetric care among nulliparous First Nations and non-First Nations women in British Columbia, Canada

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.

Beyond intention to treat: what is the right question?

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.

An adaptive clinical trials procedure for a sensitive subgroup examined in the multiple sclerosis context

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.

Accuracy of p53 codon 72 polymorphism status determined by multiple laboratory methods: a latent class model analysis

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.