Cluster Analysis Methods to Support Population Health Improvement Among US Counties.

CONTEXT: Population health rankings can be a catalyst for the improvement of health by drawing attention to areas in need of relative improvement and summarizing complex information in a manner understood by almost everyone. However, ranks also have unintended consequences, such as being interpreted as "hard truths," where variations may not be significant. There is a need to improve communication about uncertainty in ranks, with accurate interpretation. The most common solutions discussed in the literature have included modeling approaches to minimize statistical noise or borrow strength from covariates. However, the use of complex models can limit communication and implementation, especially for broad audiences. OBJECTIVES: Explore data-informed grouping (cluster analysis) as an easier-to-understand, empirical technique to account for rank imprecision that can be effectively communicated both numerically and visually. DESIGN: Cluster analysis, specifically k-means clustering with Wasserstein (earth mover's) distance, was explored as an approach to identify natural and meaningful groupings and gaps in the data distribution for the County Health Rankings' (CHR) health outcomes ranks. SETTING: County-level health outcomes from the 2022 CHR. PARTICIPANTS: 3082 counties that were ranked in the 2022 CHR. MAIN OUTCOME MEASURE: Data-informed health groups. RESULTS: Cluster analysis identified 30 health groupings among counties nationwide, with cluster size ranging from 9 to 184 counties. On average, states had 16 identified clusters, ranging from 3 in Delaware and Hawaii to 27 in Virginia. Number of clusters per state was associated with number of counties per state and population of the state. The method helped address many of the issues that arise from providing rank estimates alone. CONCLUSIONS: Public health practitioners can use this information to understand uncertainty in ranks, visualize distances between county ranks, have context around which counties are not meaningfully different from one another, and compare county performance to peer counties.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Population simulation modeling of disparities in US breast cancer mortality.

BACKGROUND: Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence. METHODS: Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy. RESULTS: Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness. CONCLUSION: Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.

Change in alcohol consumption during the Covid-19 pandemic and associations with mental health and financial hardship: results from a survey of Wisconsin patients with cancer.

PURPOSE: Alcohol consumption increases health risks for patients with cancer. The Covid-19 pandemic may have affected drinking habits for these individuals. We surveyed patients with cancer to examine whether changes in drinking habits were related to mental health or financial effects of the pandemic. METHODS: From October 2020 to April 2021, adult patients (age 18-80 years at diagnosis) treated for cancer in southcentral Wisconsin were invited to complete a survey. Age-adjusted percentages for history of anxiety or depression, emotional distress, and financial impacts of Covid-19 overall and by change in alcohol consumption (non-drinker, stable, decreased, or increased) were obtained via logistic regression. RESULTS: In total, 1,875 patients were included in the analysis (median age 64, range 19-87 years), including 9% who increased and 23% who decreased drinking. Compared to stable drinkers (32% of sample), a higher proportion of participants who increased drinking alcohol also reported anxiety or depression (45% vs. 26%), moderate to severe emotional distress (61% vs. 37%) and viewing Covid-19 as a threat to their community (67% vs. 55%). Decreased (vs. stable) drinking was associated with higher prevalence of depression or anxiety diagnosis, emotional distress, and negative financial impacts of the pandemic. Compared to non-drinkers (36% of sample), participants who increased drinking were more likely to report emotional distress (61% vs. 48%). CONCLUSIONS: Patients with cancer from Wisconsin who changed their alcohol consumption during the Covid-19 pandemic were more likely to report poor mental health including anxiety, depression, and emotional distress than persons whose alcohol consumption was stable. IMPLICATIONS FOR CANCER SURVIVORS: Clinicians working with cancer survivors should be aware of the link between poor mental health and increased alcohol consumption and be prepared to offer guidance or referrals to counseling, as needed.

Racial Arrest Disparities in the USA by Rural-Urban Location and Region.

BACKGROUND: Urban racial arrest disparities are well known. Emerging evidence suggests that rural policing shares similar patterns as urban policing in the USA, but without receiving the same public scrutiny, raising the risk of biased rural policing going unnoticed. METHODS: We estimated adult and adolescent arrest rates and rate ratios (RR) by race, rural-urban status, and US region based on 2016 Uniform Crime Reporting Program arrest and US Census population counts using general estimating equation Poisson regression models with a 4-way interaction between race, region, age group, and urbanicity. RESULTS: With few exceptions, arrest rates were highest in small towns and rural areas, especially among Black and American Indian populations. Arrest rates differed between US regions with highest rates and racial disparities in the Midwest. For example, arrest rates among Black adults in the rural Midwest were 148.6 arrests [per 1000 population], 95% CI 131.4-168.0, versus 94.4 arrests, 95% CI 77.2-115.4 in the urban Midwest; and versus corresponding rural Midwest arrests among white adults, 32.7 arrests, 95% CI 30.8-34.8, Black versus white rural RR 4.54, 95% CI 4.09-5.04. Racial arrest disparities in the South were lower but still high, e.g., rural South, Black versus White adults, RR 1.86, 95% CI 1.71-2.03. CONCLUSIONS: Rural areas and small towns are potential hotspots of racial arrest disparities across the USA, especially in the Midwest. Approaches to overcoming structural racism in policing must include strategies targeted at rural/small town communities. Our findings underscore the importance of dismantling racist policing in all US communities.

Breast cancer risk for women with diabetes and the impact of metformin: A meta-analysis.

BACKGROUND: Diabetes mellitus has been associated with increased breast cancer (BC) risk; however, the magnitude of this effect is uncertain. This study focused on BC risk for women with type 2 diabetes mellitus (T2DM). METHODS: Two separate meta-analyses were conducted (1) to estimate the relative risk (RR) of BC for women with T2DM and (2) to evaluate the risk of BC for women with T2DM associated with the use of metformin, a common diabetes treatment. In addition, subgroup analyses adjusting for obesity as measured by body mass index (BMI) and menopausal status were also performed. Studies were identified via PubMed/Scopus database and manual search through April 2021. RESULTS: A total of 30 and 15 studies were included in the first and second meta-analyses, respectively. The summary RR of BC for women with T2DM was 1.15 (95% confidence interval [CI], 1.09-1.21). The subgroup analyses adjusting BMI and adjusting BMI and menopause resulted in a summary RR of 1.22 (95% CI, 1.15-1.30) and 1.20 (95% CI, 1.05-1.36), respectively. For women with T2DM, the summary RR of BC was 0.82 (95% CI, 0.60-1.12) for metformin users compared with nonmetformin users. CONCLUSIONS: Women with T2DM were more likely to be diagnosed with BC and this association was strengthened by adjusting for BMI and menopausal status. No statistically significant reduction of BC risk was observed among metformin users. IMPACT: These two meta-analyses can inform decision-making for women with type 2 diabetes regarding their use of metformin and the use of screening mammography for early detection of breast cancer.

US Mass public shootings since Columbine: victims per incident by race and ethnicity of the perpetrator.

White individuals in the United States (US) have historically had disproportionate access to firearms. The real-life availability of firearms, including those most lethal, may still be greater among White populations, manifesting in the number of victims in shootings. We compared the severity of US mass public shootings since Columbine by race and/or ethnicity of the perpetrator using The Violence Project Database of Mass Shooters, assessing fatalities (minimum four), total victims, type, and legal status of guns used. We used data visualization and Quasi-Poisson regression of victims minus four - accounting for truncation at 4 fatalities - to assess fatality and total victim rates comparing Non-Hispanic (NH) White with NH Black shooters, using winsorization to account for outlier bias from the 2017 Las Vegas shooting. In 104 total mass public shootings until summer 2021, NH White shooters had higher median fatalities (6 [IQR 5-9] versus 5 [IQR 4-6]) and total victims (9 [IQR 6-19] versus 7 [IQR 5-12]) per incident. Confidence intervals of NH Black versus NH White fatalities rate ratios (RR) ranged from 0.17-1.15, and of total victim RRs from 0.15-1.04. White shooters were overrepresented in mass public shootings with the most victims, typically involving legally owned assault rifles. To better understand the consequences when firearms are readily available, including assault rifles, we need a database of all US gun violence. Our assessment of total victims beyond fatalities emphasizes the large number of US gun violence survivors and the need to understand their experiences to capture the full impact of gun violence.

Regularized spatial and spatio-temporal cluster detection.

Spatial and spatio-temporal cluster detection are important tools in public health and many other areas of application. Cluster detection can be approached as a multiple testing problem, typically using a space and time scan statistic. We recast the spatial and spatio-temporal cluster detection problem in a high-dimensional data analytical framework with Poisson or quasi-Poisson regression with the Lasso penalty. We adopt a fast and computationally-efficient method using a novel sparse matrix representation of the effects of potential clusters. The number of clusters and tuning parameters are selected based on (quasi-)information criteria. We evaluate the performance of our proposed method including the false positive detection rate and power using a simulation study. Application of the method is illustrated using breast cancer incidence data from three prefectures in Japan.

A Flexible Method for Identifying Spatial Clusters of Breast Cancer Using Individual-Level Data.

Prior research has shown that cancer risk varies by geography, but scan statistics methods for identifying cancer clusters in case-control studies have been limited in their ability to identify multiple clusters and adjust for participant-level risk factors. We develop a method to identify geographic patterns of breast cancer odds using the Wisconsin Women's Health Study, a series of 5 population-based case-control studies of female Wisconsin residents aged 20-79 enrolled in 1988-2004 (cases=16,076, controls=16,795). We create sets of potential clusters by overlaying a 1 km grid over each county-neighborhood and enumerating a series of overlapping circles. Using a two-step approach, we fit a penalized binomial regression model to the number of cases and trials in each grid cell, penalizing all potential clusters by the least absolute shrinkage and selection operator (Lasso). We use BIC to select the number of clusters, which are included in a participant-level logistic regression model. We identify 15 geographic clusters, resulting in 23 areas of unique geographic odds ratios. After adjustment for known risk factors, confidence intervals narrowed but breast cancer odds ratios did not meaningfully change; one additional hotspot was identified. By considering multiple overlapping spatial clusters simultaneously, we discern gradients of spatial odds across Wisconsin.

Forgoing physician visits due to cost: regional clustering among cancer survivors by age, sex, and race/ethnicity.

BACKGROUND: Innovative treatments have improved cancer survival but also increased financial hardship for patients. While demographic factors associated with financial hardship among cancer survivors are known in the USA, the role of geography is less clear. METHODS: We evaluated prevalence of forgoing care due to cost within 12 months by US Census region (Northeast, North Central/Midwest [NCMW], South, West) by demographic factors (age, sex, race/ethnicity) among 217,981 cancer survivors aged 18 to 82 years from the 2015-2019 Behavioral Risk Factor Surveillance System survey. We summarized region- and group-specific prevalence of forgoing physician visits due to cost and used multilevel logistic regression models to compare regions. RESULTS: The prevalence of forgoing physician visits due to cost was highest in the South (aged < 65 years: 19-38%; aged ≥ 65: 4-21%; adjusted odds ratios [OR], NCMW versus South, OR: 0.63 [0.56-0.71]; Northeast versus South, OR: 0.63 [0.55-0.73]; West versus South, OR: 0.73 [0.64-0.84]). Across the USA, including regions with broad Medicaid expansion, younger, female, and persons of color most often reported cost-related forgoing physician visits. CONCLUSION: Forgoing physician visits due to cost among cancer survivors is regionally clustered, raising concerns for concentrated poor long-term cancer outcomes. Underlying factors likely include variation in regional population compositions and contextual factors, such as Medicaid expansion and social policies. Disproportionate cost burden among survivors of color in all regions highlight systemic barriers, underscoring the need to improve access to the entire spectrum of care for cancer survivors, and especially for those most vulnerable.

Coordinating Centers as a Strategy for Accelerating Cancer Epidemiology Consortia: Best Practices.

Purposeof Review: This review highlights six "best practices" for cancer epidemiology coordinating centers to facilitate the success of a research consortium. Recent Findings: Evidence from emerging literature regarding the Science of Team Science suggests that coordinating centers can more effectively foster collaborative cancer epidemiology research in consortia by (1) establishing collaboration as a shared goal at the start, (2) providing scientific expertise complementary to the research sites that adapts over the course of the project, (3) enacting anti-racist and inclusive approaches in all consortium decisions and activities, (4) fostering early-stage investigator career development, (5) engaging stakeholders including cancer survivors as peers, and (6) delivering reliable logistical support and technology tools with planned process evaluation so that researchers can collaboratively focus on the science. Summary: By drawing on the Science of Team Science, coordinating centers can accelerate research progress and increase the impact of cancer epidemiology consortia.

Mortality risk and physical activity across the lifespan in endometrial cancer survivors.

PURPOSE: Physical activity (pre- and post-diagnosis) has been studied in prevention and survivorship contexts for endometrial cancer. However, the association of physical activity (PA) across the lifespan on mortality risk among endometrial cancer survivors is understudied. The study's objective was to identify the association of lifetime PA on mortality risk in endometrial cancer survivors. METHODS: Seven hundred forty-five endometrial cancer survivors drawn from a population-based cancer registry (diagnosed between 1991 and 1994) reported the frequency (sessions/week) of moderate- and vigorous intensity physical activity (MVPA) at age 12, age 20, and 5 years pre-interview (post-diagnosis). Cox proportional hazards were used to estimate hazard ratios (HR) and 95% confidence intervals for the association between PA, all-cause, and cardiovascular disease mortality as assessed in 2016. MVPA was modeled using natural cubic splines. RESULTS: Diagnosis age, body mass index, and smoking (pack-years) were each positively associated with increased all-cause mortality risk. Those who did one session of MVPA 5 years pre-interview had a lower mortality risk (HR 0.61; 95% CI 0.41-0.92) compared to those with no MVPA. Those reporting one session of MVPA was similarly observed at age 12 (HR 0.95; 95% CI 0.86-1.06) and at age 20 (HR 0.87; 95% CI 0.65-1.16). CONCLUSION: Those who participated in PA, compared to those who did not, in the 5 years before diagnosis had a lower mortality risk. While PA was not independently protective against mortality risk at ages 12 or 20, PA is still important for endometrial cancer survivors for other non-mortality outcomes.

Identifying Equitable Screening Mammography Strategies for Black Women in the United States Using Simulation Modeling.

BACKGROUND: Screening mammography guidelines do not explicitly consider racial differences in breast cancer epidemiology, treatment, and survival. OBJECTIVE: To compare tradeoffs of screening strategies in Black women versus White women under current guidelines. DESIGN: An established model from the Cancer Intervention and Surveillance Modeling Network simulated screening outcomes using race-specific inputs for subtype distribution; breast density; mammography performance; age-, stage-, and subtype-specific treatment effects; and non-breast cancer mortality. SETTING: United States. PARTICIPANTS: A 1980 U.S. birth cohort of Black and White women. INTERVENTION: Screening strategies until age 74 years with varying initiation ages and intervals. MEASUREMENTS: Outcomes included benefits (life-years gained [LYG], breast cancer deaths averted, and mortality reduction), harms (mammographies, false positives, and overdiagnoses), and benefit-harm ratios (tradeoffs) by race. Efficiency (benefits per unit resource), mortality disparity reduction, and equity in tradeoffs were evaluated. Equitable strategies for Black women were defined as those with tradeoffs closest to benchmark values for screening White women biennially from ages 50 to 74 years. RESULTS: Biennial screening from ages 45 to 74 years was most efficient for Black women, whereas biennial screening from ages 40 to 74 years was most equitable. Initiating screening 10 years earlier in Black versus White women reduced Black-White mortality disparities by 57% with similar LYG per mammogram for both populations. Selection of the most equitable strategy was sensitive to assumptions about disparities in real-world treatment effectiveness: The less effective treatment was for Black women, the more intensively Black women could be screened before tradeoffs fell short of those experienced by White women. LIMITATION: Single model. CONCLUSION: Initiating biennial screening in Black women at age 40 years reduces breast cancer mortality disparities and yields benefit-harm ratios that are similar to tradeoffs of White women screened biennially from ages 50 to 74 years. PRIMARY FUNDING SOURCE: National Cancer Institute at the National Institutes of Health.

Recent Changes in the Patterns of Breast Cancer as a Proportion of All Deaths According to Race and Ethnicity.

BACKGROUND: Recent reports suggest that racial differences in breast cancer incidence rates have decreased. We examined whether these findings apply to breast cancer mortality while considering age, period, and cohort influences on both absolute and relative measures of breast cancer mortality. METHODS: Using publicly available datasets (CDC WONDER, Human Mortality Database), we developed an age-period-cohort model of breast cancer mortality and breast cancer deaths as a proportion of all deaths during 1968-2019 among all women and by 5 race/ethnicity groups with sufficient numbers for estimation: Hispanic (all races), American Indian/Alaska Native and Asian/Pacific Islanders (regardless of ethnicity), non-Hispanic Black, and non-Hispanic White. RESULTS: Initially increasing after 1968, age-adjusted breast cancer mortality rates have decreased among all racial/ethnic groups since 1988. The age-adjusted percent of all deaths due to breast cancer also has been declining for non-Hispanic White women since about 1990 while increasing or holding steady for other race/ethnic groups. In 2019, the age-adjusted percent of deaths due to breast cancer for women was highest for Asian/Pacific Islanders (5.6%) followed by non-Hispanic Black (4.5%), Hispanic (4.4%), non-Hispanic White (4.1%), and American Indian/Alaska Native women (2.6%). CONCLUSIONS: Breast cancer mortality disparities are now greater on both relative and absolute scales for non-Hispanic Black women, and using the relative scale for Asian/Pacific Islander and Hispanic women, compared with non-Hispanic White women for the first time in 50 years.

Provision of Immediate Postpartum Long-Acting Reversible Contraceptives Before and After Wisconsin Medicaid's Payment Change.

OBJECTIVES: We aimed to estimate the association between Medicaid unbundling of payment for long-acting reversible contraceptives (LARC) from the global delivery fee and immediate postpartum (IPP) LARC provision, in a state outside a select group of early-adopters. We also examine the potential moderating roles of hospital academic affiliation and Catholic status on the association between unbundling and IPP LARC provision. METHODS: We used a pre-post design to examine the association between unbundling and IPP LARC provision. We observed Medicaid-covered childbirth deliveries in Wisconsin hospitals between January 2016 and December 2017 (n = 45,200) in the State Inpatient Database from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. We conducted multivariate regressions using generalized linear mixed models. RESULTS: From 2016 to 2017, IPP LARC provision increased from 0.28% to 0.44% of deliveries (p = .003). In our adjusted model, IPP LARC provision was 1.55 times more likely in the post-period versus the pre-period (95% confidence interval, 1.12-2.13). Both before and after unbundling, IPP LARC provision was significantly more common in academic versus nonacademic settings and was exceedingly rare in Catholic institutions. CONCLUSIONS: In contrast with many early adopting states, in this later adopting state, Wisconsin Medicaid's unbundling of LARC from the global fee did not meaningfully change the rates of IPP LARC provision. These results indicate that delivery hospital characteristics are strong correlates of access to IPP LARC and suggest the need for interventions-perhaps outside of the inpatient setting-to ensure that patients can access desired contraceptive methods promptly postpartum.

Weapon Carrying Among Boys in US Schools by Race and/or Ethnicity: 1993-2019.

BACKGROUND: High adolescent gun-related mortality, gun violence, pro-gun policies, white supremacy, and the long-term socioeconomic and other effects of racial oppression are intricately linked in the United States. Racist prejudice depicts male individuals of color as more prone to criminality than white male individuals. We described long-term patterns of weapon carrying in US schools among non-Hispanic (NH) white, NH Black/African American, and Hispanic boys, hypothesizing that in contrast to racist stereotypes, boys of color did not bring weapons into schools more often than NH white boys in recent years. METHODS: We conducted a time series analysis using 1993-2019 Youth Risk Behavior Surveillance System data comparing boys' self-reported weapon carrying in a nationally representative sample of US high schools by race and/or ethnicity, age, and self-reported experience of safety and violence at school. RESULTS: Weapon carrying in schools has declined among all boys. Comparing all schools, we found no significant differences in weapon carrying (4%-5%) by race and/or ethnicity in 2017 and 2019. Boys who reported experiencing violence or feeling unsafe at school were at least twice as likely to bring a weapon into school, and such negative experiences were more common among boys of color (8%-12%) than among NH white boys (4%-5%). In schools perceived as safer, NH white boys have been more likely to bring weapons into schools than NH Black/African American or Hispanic boys in the past 20 years. CONCLUSIONS: Our findings contradict racist prejudice with regard to weapon carrying in schools, particularly in more favorable school environments. Making schools safer may reduce weapon carrying in schools where weapon carrying is most common.

Clustered spatio-temporal varying coefficient regression model.

In regression analysis for spatio-temporal data, identifying clusters of spatial units over time in a regression coefficient could provide insight into the unique relationship between a response and covariates in certain subdomains of space and time windows relative to the background in other parts of the spatial domain and the time period of interest. In this article, we propose a varying coefficient regression method for spatial data repeatedly sampled over time, with heterogeneity in regression coefficients across both space and over time. In particular, we extend a varying coefficient regression model for spatial-only data to spatio-temporal data with flexible temporal patterns. We consider the detection of a potential cylindrical cluster of regression coefficients based on testing whether the regression coefficient is the same or not over the entire spatial domain for each time point. For multiple clusters, we develop a sequential identification approach. We assess the power and identification of known clusters via a simulation study. Our proposed methodology is illustrated by the analysis of a cancer mortality dataset in the Southeast of the U.S.

Bicycling Rates and the Prevalence of Bicycle Helmet Usage in Wisconsin.

INTRODUCTION: Bicycles are a source of transportation, recreation, and exercise throughout the world. Bicycling is associated with both health and environmental benefits but also poses a risk of injury. The use of bicycle helmets has been shown to reduce morbidity and mortality associated with cycling. It is unknown if helmet use differs across Wisconsin geographic areas and sociodemographic groups. METHODS: Data were obtained from the Survey of the Health of Wisconsin (SHOW). Bicycle use and helmet use frequency were determined from a self-administered questionnaire that contained questions specific to preventative health behaviors. Descriptive statistics summarized overall bicycle ridership. Chi-square and Student t tests were performed to assess relationships between bicycle and helmet use across geographic categories and sociodemographic groups. RESULTS: Differences between sex, race or ethnicity, and education level were found to be associated with bicycle ridership and the frequency of helmet use. Men were significantly more likely to report riding a bicycle and never wearing a helmet. Individuals from urban communities reported always wearing a helmet more often than rural communities. Higher education levels were associated with higher levels of bicycle and helmet use. Race or ethnicity was not associated with bicycle ridership but was associated with differences in helmet use frequency. CONCLUSION: Nearly half of those who ride bicycles in Wisconsin report never wearing a helmet. Since bicycle ridership and helmet use were found to be associated with a number of sociodemographic characteristics, any solution should consider the role of equity when attempting to increase ridership or helmet use.

Patterns of farm exposure are associated with reduced incidence of atopic dermatitis in early life.

BACKGROUND: Farm exposures may reduce the risk of atopic dermatitis (AD) in children, but this is controversial and US data are limited. OBJECTIVE: This study was conducted to identify patterns of farm exposure in Wisconsin family farms that modify AD incidence and prevalence in early childhood. METHODS: Environmental exposures, health history, and clinical outcomes were prospectively recorded for 111 farm families and 129 non-farm families enrolled in the Wisconsin Infant Study Cohort birth cohort study. Exposures from the prenatal and early postnatal (2-month) visits were evaluated together with parental report of AD diagnosis by a health care provider through age 24 months. Latent class analysis was performed with prenatal and early postnatal farm-exposure variables to assign farm children to 3 classes. RESULTS: Overall, children of farm families had reduced AD incidence (P = .03). Within farm families, exposures including poultry (3% vs 28%; P = .003), pig (4% vs 25%; P = .04), feed grain (13% vs 34%; P = .02), and number of animal species were inversely associated with AD incidence. Among the latent class groups, children in families with diverse or more intense farm exposures (classes A and B) had reduced AD incidence, whereas low-exposure (class C) infants had AD incidence similar to that in nonfarm children. CONCLUSIONS: Infants in Wisconsin farm families had reduced AD incidence, and patterns of farm exposures further defined AD risk. These findings suggest that exposure to diverse farm animals, feed, and bedding during the prenatal period and in early infancy reduce the risk of early-onset AD, a phenotype associated with multiple other atopic diseases.