Utilizing residential histories to assess environmental exposure and socioeconomic status over the life course among mesothelioma patients.

Background: Exposure misclassification based solely on the address at cancer diagnosis has been widely recognized though not commonly assessed. Methods: We linked 1,015 mesothelioma cases diagnosed during 2011-2015 from the New York State Cancer Registry to inpatient claims and LexisNexis administrative data and constructed residential histories. Percentile ranking of exposure to ambient air toxics and socioeconomic status (SES) were based on the National Air Toxic Assessment and United States Census data, respectively. To facilitate comparisons over time, relative exposures (REs) were calculated by dividing the percentile ranking at individual census tract by the state-level average and subtracting one. We used generalized linear regression models to compare the RE in the past with that at cancer diagnosis, adjusting for patient-level characteristics. Results: Approximately 43.7% of patients had residential information available for up to 30 years, and 96.0% up to 5 years. The median number of unique places lived was 4 [interquartile range (IQR), 2-6]. The time-weighted-average RE from all addresses available had a median of -0.11 (IQR, -0.50 to 0.30) for air toxics and -0.28 (IQR, -0.65 to 0.25) for SES. RE associated with air toxics (but not SES) was significantly higher for earlier addresses than addresses at cancer diagnosis for the 5-year [annual increase =1.24%; 95% confidence interval (CI): 0.71-1.77%; n=974] and 30-year (annual increase =0.36%; 95% CI: 0.25-0.48%; n=444) look-back windows, respectively. Conclusions: Environmental exposure to non-asbestos air toxics among mesothelioma patients may be underestimated if based solely on the address at diagnosis. With geospatial data becoming more readily available, incorporating cancer patients' residential history would lead to reduced exposure misclassification and accurate health risk estimates.

Utilizing Residential History to Examine Heterogeneous Exposure Trajectories: A Latent Class Mixed Modeling Approach Applied to Mesothelioma Patients.

Background: Life-course exposure assessment, as opposed to a one-time snapshot assessment based on the address at cancer diagnosis, has become increasingly possible with available cancer patients' residential history data. To demonstrate a novel application of residential history data, we examined the heterogeneous trajectories of the nonasbestos air toxic exposures among mesothelioma patients, and compared the patients' residential locations with the spatiotemporal clusters estimated from the National Air Toxic Assessment (NATA) data. Methods: Patients' residential histories were obtained by linking mesothelioma cases diagnosed during 2011-2015 in the New York State (NYS) Cancer Registry to LexisNexis administrative data and inpatient claims data. To compare cancer risks over time, yearly relative exposure (RE) was calculated by dividing the NATA cancer risk at individual census tracts by the NYS average and subtracting 1. We used a latent class mixed model to identify distinct exposure trajectories among patients with a 15-year residential history prior to cancer diagnosis (n = 909). We further examined patient characteristics by the latent trajectory groups using bivariate comparisons and a logistic regression model. The spatiotemporal clusters of RE were generated based on all NATA data (n = 72,079) across the contiguous United States and using the SaTScan software. Results: The median number of addresses lived was 2 (IQR, 1-4), with a median residential duration of 8 years (IQR, 4.7-13.2 years). We identified 3 distinct exposure trajectories: persistent low exposure (27%), decreased low exposure (41%), and increased high exposure (32%). Patient characteristics did not differ across trajectory groups, except for race and Hispanic ethnicity (P < .0001) and residential duration (P = .03). Compared to their counterparts, non-Hispanic White patients had a significantly lower odds of belonging to the increased high exposure group (adjusted odds ratio, 0.14; 95% CI, 0.09-0.23) than the persistent low exposure and decreased low exposure groups. Patients in the increased high exposure group tended to reside in New York City (NYC), which was covered by one of the high-RE clusters. On the other hand, patients in the persistent low exposure group tended to reside outside of NYC within NYS, which was largely covered by 2 low-RE clusters. Conclusion: Using mesothelioma as an example, we quantified the heterogeneous trajectories of nonasbestos air toxic exposure based on patients' residential histories. We found that patients' race and ethnicity differed across the latent groups, likely reflecting the differences in patients' residential mobility before their cancer diagnoses. Our method can be used to study cancer types that do not have a clear etiology and may have a higher attributable risk due to environmental exposures as well as socioeconomic conditions.

Estimating uncertainty in a socioeconomic index derived from the American community survey.

Socioeconomic indexes are widely used in public health to facilitate neighborhood-scale analyses. Although they are calculated with high levels of precision, they are rarely reported with accompanying measures of uncertainty (e.g., 90% confidence intervals). Here we use the variance replicate tables that accompany the United States Census Bureau's American Community Survey to report confidence intervals around the Yost Index, a socioeconomic index comprising seven variables that is frequently used in cancer surveillance. The Yost Index is reported as a percentile score from 1 (most affluent) to 100 (most deprived). We find that the average uncertainty for a census tract in the United States is plus or minus 8 percentiles, with the uncertainty a function of the value of the index itself. Scores at the extremes of the distribution are more precise and scores near the center are less precise. Less-affluent tracts have greater uncertainty than corresponding more-affluent tracts. Fewer than 50 census tracts of 72,793 nationally have unusual distributions of socioeconomic conditions that render the index uninformative. We demonstrate that the uncertainty in a census-based socioeconomic index is calculable and can be incorporated into any analysis using such an index.

Predictors of Survival among Male and Female Patients with Malignant Pleural Mesothelioma: A Random Survival Forest Analysis of Data from the 2000-2017 Surveillance, Epidemiology, and End Results Program.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy with a dismal prognosis. We aimed to identify predictors of survival among male and female MPM patients in the United States. METHODS: We identified MPM cases reported by 18 cancer registries in the Surveillance, Epidemiology, and End Results Program (2000-2017). We applied a random survival forest (RSF) algorithm to identify and rank the importance of 10 variables at patient, cancer, and area level in predicting all-cause survival overall and by female and male subgroups. RESULTS: Approximately 91.4% (n = 11,160) of the MPM patients had died, with better survival among females than males (11.7% vs 7.8%). The median follow-up time was 7 months (interquartile range, 2-17 months). A majority of the patients were male (78.6%), non-Hispanic White (81.8%), and residing in metropolitan counties with a population greater than 1 million (63.7%). The top 3 factors for predicting overall MPM survival were age, histological type, and cancer-directed surgery status. Except for age, the relative ranking of covariates varied by the 3 sample groups. Stage ranked fifth in predicting female survival, while it was replaced by metastasis status for male and overall patients. Race/ethnicity was not a good predictor for survival among MPM patients overall or the male subgroup, but ranked sixth for predicting survival among females. Median household income was not a good predictor for survival among females. CONCLUSION: We demonstrated that RSF successfully identified predictors of MPM survival. RSF is a viable complement to the commonly used Cox proportional hazard model and a viable alternative, particularly when the proportional hazard assumption is unmet. RSF also identified differences between the sexes, which may help explain the sex differences in MPM survival rates.

Residential mobility among adult cancer survivors in the United States.

BACKGROUND: While residential mobility affects people's health, the dynamic of neighborhood tenure and its associated factors among cancer patients and survivors have not been studied in detail. This cross-sectional study aimed to identify sociodemographic factors associated with neighborhood tenure and relocation after the first cancer diagnosis among U.S. adult cancer survivors and patients. METHODS: Based on a nationally representative sample of non-institutionalized civilian adults (≥18 years, n = 185,637) from the 2013-2018 National Health Interview Survey, we compared neighborhood tenure between adults with and without a history of cancer, and identified factors associated with their neighborhood tenure and relocation after the first cancer diagnosis, using propensity score matching, and logistic regression models with survey design incorporated. RESULTS: Among adults with cancer (9.0%), 39.6% had a neighborhood tenure ≤10 years (vs. 61.2% among those without cancer), and 25.6% (equivalent to 5.4 million) relocated after their first cancer diagnosis. The odds of having shorter neighborhood tenure was higher among the cancer group in the propensity-matched samples (odds ratio = 1.05; 95% CI: 1.05-1.06; n = 17,259). Among cancer survivors, the odds of neighborhood relocation were negatively associated with increasing age, perceived neighborhood social cohesion, having high school level education, and being married; while positively associated with having family income below the poverty threshold, being uninsured, and living in non-Northeast regions. CONCLUSIONS: High residential mobility was found among a sizable proportion of adults with a history of cancer, and was associated with multiple socioeconomic factors. Incorporating and addressing modifiable risk factors associated with residential mobility among cancer patients and survivors may offer new intervention opportunities to improve cancer care delivery and reduce cancer disparities.

Can Oncology Practice Claims Data Replace Physician Reporting to State Cancer Registries?

BACKGROUND: Recently, the Surveillance, Epidemiology, and End Results Program facilitated the linkage of claims data from oncology practices to cancer registry data. Since physician reporting places a burden on oncology practices and presents a challenge for cancer registries, the question arises as to whether claims data can replace physician reporting. Using data reported to the New York State Cancer Registry, we evaluated the information that would be lost if oncology practices were to cease reporting abstracted data to the registry. METHODS: We identified cancer cases diagnosed in 2017 and reported by 3 oncology practices. We estimated the proportion of cases reported solely by these practices and examined characteristics of these cases compared to those reported by multiple sources. We used Match*Pro to link cases reported by the oncology practices to claims data and examined the availability of claims data for these cases. RESULTS: The 3 oncology practices reported 3,224 malignant tumors diagnosed in 2017. Of these, 233 (7.2%) were reported solely by the practices. Cases reported by an oncology practice only tended to be older than those reported by multiple sources and were statistically significantly more likely to be non-Hispanic White and less likely to be a first reportable cancer, early stage, or receive treatment. Of the 233 sole report tumors, 5 (2.1%) were not captured in claims data. CONCLUSIONS: Most cancers reported by oncology practices were also reported by other sources or were included in claims data. However, relying on claims data for these cases would result in missing data items and a small number of unreported cancers. These results may help to optimize oncology practice reporting by informing reporting requirements to balance the need for complete data with the convenience of obtaining data through automated means.

Outcome Evaluation of the You Can Do It Initiative to Promote Exclusive Breastfeeding Among Women Enrolled in the New York State WIC Program by Race/Ethnicity.

OBJECTIVE: To evaluate the effectiveness of You Can Do It at improving exclusive breastfeeding (BF) among New York State women enrolled in Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). DESIGN: Quasi-experimental study, September, 2013 through February, 2016. SETTING: Multicomponent intervention paired with a yearlong learning community in 12 clinics. PARTICIPANTS: Women who were enrolled in WIC during the first trimester, intended to breastfeed or were undecided, and continued in WIC after delivery, comprised 1 baseline cohort (n = 688) and 2 intervention cohorts: Breastfeeding Attrition Prediction Tool (BAPT) (consented, n = 362) and non-BAPT (declined, n = 408). INTERVENTION: The BAPT was offered to all eligible women in the intervention enrollment period. Consenting women received multiple counseling sessions tailored to individual BAPT results throughout pregnancy and were contacted promptly after delivery. MAIN OUTCOME MEASURE(S): Prevalence of exclusive BF at 7, 30, and 60 days. ANALYSIS: Multivariate logistic regression, stratified by race/ethnicity. Statistical significance set at P < .05. RESULTS: Prevalence of exclusive BF at 7 and 30 days was significantly higher among BAPT women compared with non-BAPT or baseline cohorts. Non-Hispanic black and Hispanic women in the BAPT cohort achieved significantly higher exclusive BF rates at 30 and 60 days compared with those in non-BAPT and baseline cohorts. CONCLUSIONS AND IMPLICATION: The initiative seems to be effective at increasing exclusive BF, particularly among non-Hispanic black and Hispanic women in the New York State WIC program.

Implementing a WIC-Based Intervention to Promote Exclusive Breastfeeding: Challenges, Facilitators, and Adaptive Strategies.

OBJECTIVE: Understand factors that contributed to the implementation of a successful multicomponent intervention to promote exclusive breastfeeding (EBF) within Special Supplemental Nutrition Program for Woman, Infants, and Children (WIC) clinics. DESIGN: Qualitative study of staff implementers' experiences using implementation status reports, facilitated group discussion immediately after implementation, and WIC administrative data. SETTING: WIC staff from 12 clinics participated in an EBF Learning Community composed of 8 intervention trainings and ongoing support from trainers and peers. PARTICIPANTS: A total of 47 WIC staff including 11 directors, 20 other administrators, 8 nutritionists, and 6 peer counselors. INTERVENTION: A WIC-integrated EBF promotion initiative, supported through a Learning Community, composed of prenatal screening, tailored trimester-specific counseling, and timely postpartum follow-up. PHENOMENON OF INTEREST: Challenges and facilitators to implementation within clinics. ANALYSIS: Iterative qualitative analysis using directed, emergent, and thematic coding. RESULTS: Implementation experiences were characterized by (1) perceived benefits of implementation, including improved EBF knowledge and counseling confidence among staff; and (2) managing implementation, including responding to challenges posed by clinic settings (resources, routine practices, values, and perceptions of mothers) through strategies such as adapting clinic practices and intervention components. CONCLUSIONS AND IMPLICATIONS: Implementation was shaped by clinic setting and adaptive strategies. Future WIC interventions may benefit from formal consideration of intervention fit with local clinic setting and allowable adaptations.

Heterogeneity identified at birth and blood pressure in adulthood.

OBJECTIVE: In the developmental programming literature, the association of birth weight and blood pressure later in life is modest at best. This article reexamines this issue using Covariate Density Defined mixture of regressions (CDDmr) to determine if a latent variable, based on birth weight, and known to influence infant mortality, provides a stronger indicator of developmental programming. METHODS: CDDmr identifies two latent components in the birth weight distribution, generally interpreted in the infant mortality literature as "compromised" and "normal" fetal development. The data are taken from the 1958 British National Child Development Study. RESULTS: In the 1958 cohort, the "compromised" component consists of about 10% of the birth weight distribution. Compared to "normal" births, the mean systolic blood pressure at age 45 of "compromised" births is 20.3 (females) and 26.4 (males) mm Hg higher than "normal" births. The relative risks of stage-I-II systolic hypertension (>140 mm Hg) of "compromised" births compared to "normal" births are 10.7 (females) and 4.2 (males). The relative risks of stage-II systolic hypertension (>160 mm Hg) are considerably higher, 241.6 (females) and 74.3 (males). In general, the highest blood pressures are observed in "compromised" births with birth weights within the normal (about 3.0-3.5 kg) birth weight range. Results for diastolic blood pressure are similar. CONCLUSIONS: These associations are much stronger than those identified using conventional methods. CDDmr is likely to be useful for studying the dynamics of developmental programming particularly in large cohort studies where birth weight is often the only indicator of programming available. Am. J. Hum. Biol. 28:545-554, 2016. © 2016 Wiley Periodicals, Inc.