Supply and demand effects between tobacco retailer density and smoking prevalence.

OBJECTIVE: Places with more tobacco retailers have higher smoking prevalence levels, but whether this is because retailers locate where people who smoke live or whether tobacco availability prompts tobacco use is unknown. In this study, we compare the role of consumer demand with that of tobacco supply in longitudinal, area-based associations of tobacco retailer density with smoking prevalence. METHODS: We merged annual adult smoking prevalence estimates derived from the USA Behavioural Risk Factor Surveillance System data with annual county estimates of tobacco retailer density calculated from the National Establishment Time Series data for 3080 counties between 2000 and 2010. We analysed relationships between retailer density and smoking in 3080 counties, using random intercept cross-lagged panel models and employing two measures of tobacco retailer density capturing the number of likely tobacco retailers in a county divided by either the population or land area. RESULTS: Both density models provided evidence of significant demand and supply effects; in the population-based model, the association of smoking prevalence in 1 year with tobacco retailer density in the next year (standardised coefficient=0.038, p<0.01) was about double the association between tobacco retailer density with subsequent smoking prevalence (0.017, p<0.01). The reverse was true in the land area-based model, where the supply effect (0.042, p<0.01) was more than 10 times stronger than the demand effect (0.003, p<0.01). CONCLUSIONS: Policies that restrict access to retail tobacco have the potential to reduce smoking prevalence, but pairing such policies with interventions to reduce consumer demand remains important.

Tobacco retailer density and its association with birth outcomes in the USA: 2000-2016.

INTRODUCTION: Significant progress has been made in reducing maternal exposure to tobacco smoke and subsequent adverse birth outcomes, however, reductions may require strategies that reduce the availability of tobacco retailers. In this study, we investigated the relationship between tobacco retailer density and birth outcomes across the USA and predicted the potential impact of a tobacco retailer density cap on these outcomes. METHODS: Annual US county (n=3105), rates of preterm birth, low birth weight, small-for-gestational age, all-cause infant mortality and sudden infant death syndrome (SIDS) were calculated using National Vital Statistics System data. Tobacco retailers were identified from the National Establishment Time-Series Database. We used Poisson regression to estimate the effect of capping retailer density at 1.4 retailers per 1000 population, controlling for county demographics and air pollution, using propensity score weighting. RESULTS: Tobacco retailer density was positively associated with most adverse birth outcomes. We estimate that a nationwide cap on tobacco retailer density, implemented in 2016, would have resulted in a reduction of 4275 (95% CI 2210 to 6392) preterm births, 6096 (95% CI 4421 to 7806) small-for-gestational-age births, 3483 (95% CI 2615 to 4378) low birthweight births, 538 (95% CI 345 to 733) all-cause infant deaths and 107 (95% CI 55 to 158) SIDS deaths in that year. CONCLUSION: Higher rates of adverse birth outcomes were seen in counties with high tobacco retailer density compared with those with low density. These results provide further support for regulating tobacco retail density to reduce adverse health outcomes associated with tobacco use.

Multi-level predictors of being up-to-date with colorectal cancer screening.

PURPOSE: Assessing factors associated with being up-to-date with colorectal cancer (CRC) screening is important for identifying populations for which targeted interventions may be needed. METHODS: This study used Medicare and private insurance claims data for residents of North Carolina to identify up-to-date status in the 10th year of continuous enrollment in the claims data and in available subsequent years. USPSTF guidelines were used to define up-to-date status for multiple recommended modalities. Area Health Resources Files provided geographic and health care service provider data at the county level. A generalized estimating equation logistic regression model was used to examine the association between individual- and county-level characteristics and being up-to-date with CRC screening. RESULTS: From 2012-2016, 75% of the sample (n = 274,660) age 59-75 was up-to-date. We identified several individual- (e.g., sex, age, insurance type, recent visit with a primary care provider, distance to nearest endoscopy facility, insurance type) and county-level (e.g., percentage of residents with a high school education, without insurance, and unemployed) predictors of being up-to-date. For example, individuals had higher odds of being up-to-date if they were age 73-75 as compared to age 59 [OR: 1.12 (1.09, 1.15)], and if living in counties with more primary care physicians [OR: 1.03 (1.01, 1.06)]. CONCLUSION: This study identified 12 individual- and county-level demographic characteristics related to being up-to-date with screening to inform how interventions may optimally be targeted.

Sociodemographic Disparities in Tobacco Retailer Density in the United States, 2000-2017.

INTRODUCTION: Studies find differences in tobacco retailer density according to neighborhood sociodemographic characteristics, raising issues of social justice, but not all research is consistent. AIMS AND METHODS: This study examined associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints (2000, 2007, 2012, and 2017) and investigated if associations remained stable over time. Data on tobacco retailers came from the National Establishment Time-Series Database. Adjusted log-linear models examined the relationship between retailer density and census tract sociodemographic characteristics (% non-Hispanic Black [Black], % Hispanic, % vacant housing units, median household income), controlling for percentage of youth, urbanicity, and US region. To examine whether the relationship between density and sociodemographic characteristics changed over time, additional models were estimated with interaction terms between each sociodemographic characteristic and year. RESULTS: Tobacco retailer density ranged from 1.22 to 1.44 retailers/1000 persons from 2000 to 2017. There were significant, positive relationships between tobacco retailer density and the percentage of Black (standardized exp(b) = 1.05 [95% CI: 1.04% to 1.07%]) and Hispanic (standardized exp(b) = 1.06 [95% CI: 1.05% to 1.08%]) residents and the percentage of vacant housing units (standardized exp(b) =1.08 [95% CI: 1.07% to 1.10%]) in a census tract. Retailer density was negatively associated with income (standardized exp(b) = 0.84 [95% CI: 0.82% to 0.86%]). From 2000 to 2017, the relationship between retailer density and income and vacant housing units became weaker. CONCLUSIONS: Despite the weakening of some associations, there are sociodemographic disparities in tobacco retailer density from 2000 to 2017, which research has shown may contribute to inequities in smoking. IMPLICATIONS: This study examines associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints from 2000 to 2017. Although some associations weakened, there are sociodemographic disparities in tobacco retailer density over the study period. Research suggests that sociodemographic disparities in retailer density may contribute to inequities in smoking. Findings from this study may help identify which communities should be prioritized for policy intervention and regulation.

Tobacco Retail Outlets, Neighborhood Deprivation and the Risk of Prenatal Smoke Exposure.

INTRODUCTION: Smoking and smoke exposure among pregnant women remain persistent public health issues. Recent estimates suggest that approximately one out of four nonsmokers have measurable levels of cotinine, a marker indicating regular exposure to secondhand smoke. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy. However, most of these studies have relied upon self-reported measures of smoking. AIMS AND METHODS: To more accurately assess smoke exposure resulting from both smoking and secondhand exposure in mothers during pregnancy, we used Bayesian regression models to estimate the association of cotinine levels with tobacco retail outlet (TRO) exposure and a neighborhood deprivation index (NDI) in six counties in North Carolina centered on Durham County. RESULTS: Results showed a significant positive association between TRO exposure (ß = 0.008, 95% credible interval (CI) = [0.003, 0.013]) and log cotinine after adjusting for individual covariates (eg, age, race/ethnicity, education, marital status). TRO exposure was not significant after including the NDI, which was significantly associated with log cotinine (ß = 0.143, 95% CI = [0.030, 0.267]). However, in a low cotinine stratum (indicating secondhand smoke exposure), TRO exposure was significantly associated with log cotinine (ß = 0.005, 95% CI = [0.001, 0.009]), while in a high cotinine stratum (indicating active smoking), the NDI was significantly associated with log cotinine (ß = 0.176, 95% CI = [0.005, 0.372]). CONCLUSIONS: In summary, our findings add to the evidence that contextual factors are important for active smoking during pregnancy. IMPLICATIONS: In this study, we found several significant associations that suggest a more nuanced understanding of the potential influence of environmental- and individual-level factors for levels of prenatal smoke exposure. Results suggested a significant positive association between TRO exposure and cotinine levels, after adjusting for the individual factors such as race, education, and marital status. Individually, NDI was similarly positively associated with cotinine levels as well. However, when combining TRO exposure alongside NDI in the same model, TROs were no longer significantly associated with overall cotinine levels.

Temporal Changes in Treatment Patterns for Rural and Urban Patients With Early-Stage Non-Small Cell Lung Cancer.

BACKGROUND Our objectives were to evaluate geographic access to lung cancer treatment modalities in North Carolina and to characterize how practice patterns are changing over time. We hypothesized that rural patients would be less likely to undergo treatment compared to urban patients, with widening disparities over time.METHODS We identified patients with Stage I non-small cell lung cancer (NSCLC) from 2006 to 2015 using the North Carolina Central Cancer Registry linked with Medicaid, Medicare, and private insurance claims. The primary outcome was first-course treatment: surgery, radiation, or no treatment. Calendar years were split into earlier (2006-2010) and later (2011-2015) periods. We estimated the adjusted odds ratio (OR) of rural/urban status and time period with 1) surgery and 2) any treatment (surgery or radiation) using multivariable logistic regression.RESULTS Among 5504 patients, 3206 (58%) underwent surgery as initial therapy, 1309 (24%) received radiation as initial therapy, and 989 (18%) had no therapy. There were no rural-urban disparities in treatment patterns. For rural and urban patients, the odds of surgery decreased over time and the odds of radiation increased. We also found that only 48% of those receiving no treatment ever reached a surgeon or radiation oncologist.LIMITATIONS This was an insured, single-state population. Treatment preferences are unknown.CONCLUSIONS Among all treated patients, whether urban or rural, there was increasing use of radiation and decreasing use of surgery over time. Many patients without treatment never had a consultation with a surgeon/radiation oncologist, and this is an actionable target for improving treatment access for early-stage NSCLC.

Influence of Treating Facility, Provider Volume, and Patient-Sharing on Survival of Patients With Multiple Myeloma.

BACKGROUND: Population-based studies suggest that patients with multiple myeloma (MM) have better outcomes when treated at high-volume facilities, but the relative contribution of provider expertise and hospital resources to improved outcomes is unknown. This study explored how treating facility, individual provider volume, and patient-sharing between MM specialists and community providers influenced outcomes for patients with MM. PATIENTS AND METHODS: A state cancer registry linked to public and private insurance claims was used to identify a cohort of patients diagnosed with MM in 2006 through 2012. Three multivariable Cox models were used to examine how the following factors impacted overall survival: (1) evaluation at an NCI-designated Comprehensive Cancer Center (NCICCC), (2) the primary oncologist's volume of patients with MM, and (3) patient-sharing between MM specialists and community oncologists. RESULTS: A total of 1,029 patients diagnosed with MM in 2006 through 2012 were identified. Patients who were not evaluated at an NCICCC had an increased risk of mortality compared with those evaluated at an NCICCC (hazard ratio [HR], 1.50; 95% CI, 1.21-1.86; P<.001). Compared with patients treated by NCICCC MM specialists, those treated by both low-volume community providers (HR, 1.47; 95% CI, 1.14-1.90; P<.01) and high-volume community providers (HR, 1.29; 95% CI, 1.04-1.61; P<.05) had a higher risk of mortality. No difference in mortality was seen between patients treated by NCICCC MM specialists and those treated by the highest-volume community oncologists in the ninth and tenth deciles (HR, 1.08; 95% CI, 0.84-1.37; P=.5591). Patients treated by community oncologists had a higher risk of mortality regardless of patient-sharing compared with patients treated by MM specialists (eg, community oncologist with a history of sharing vs NCICCC MM specialist: HR, 1.49; 95% CI, 1.10-2.02; P<.05). CONCLUSIONS: Findings of this study add to the accumulating evidence showing that patients with MM benefit from care at high-volume facilities, and suggest that similar outcomes can be achieved by the highest-volume providers in the community.

Structural Racism and Treatment Delay Among Black and White Patients With Breast Cancer.

PURPOSE: Structural racism (SR) is a potential driver of health disparities, but research quantifying its impacts on cancer outcomes has been limited. We aimed to develop a multidimensional county-level SR measure and to examine the association of SR with breast cancer (BC) treatment delays among Black and White patients. METHODS: The cohort included 32,095 individuals from the North Carolina Central Cancer Registry with stage I to III BC diagnosed between 2004 and 2017 and linked to multipayer insurance claims from the Cancer Information and Population Health Resource. County-level data were drawn from multiple public sources aggregated in the Robert Wood Johnson County Health Rankings database. Racial gaps in eight social determinants across five domains were quantified at the county level and ranked on a 0-100 minimum-maximum scale. Domain scores were averaged to create a SR Composite Index (SRCI) score. We used multilevel logistic regression with random intercepts and multiple cross-level interaction terms to evaluate the association between county-level SRCI and patient-level treatment delays, adjusting for patient-level characteristics and stratified by race. RESULTS: The SRCI score ranged from 21 to 75 with a median (IQR) of 39.0 (31.8, 45.7). For Black patients, a 10-unit increase in SRCI score was associated with increased odds of delay (Adjusted odds ratios [aOR], 1.25; 95% confidence limits [CL], 1.08 to 1.45). No such association was found for White patients (OR, 1.05; 95% CL, 0.97 to 1.15). CONCLUSION: Area-level SR measured by a composite index is associated with higher odds of BC treatment delays among Black, but not White patients. Increasing county-level SR is associated with increasing Black-White disparities in treatment delay. Further research is needed to refine the measurement of SR and to examine its association with other cancer care disparities.

Neighborhood Inequities in Tobacco Retailer Density and the Presence of Tobacco-Selling Pharmacies and Tobacco Shops.

Studies document inequitable tobacco retailer density by neighborhood sociodemographics, but these findings may not be robust to different density measures. Policies to reduce density may be less equitable depending on how the presence of store types differs by neighborhood characteristics. We built a 2018 list of probable tobacco retailers in the United States and calculated four measures of density for all census tracts (N = 71,495), including total count, and number of retailers per 1,000 people, square mile, and kilometers of roadway. We fit multivariable regression models testing associations between each density measure and tract-level sociodemographics. We fit logistic regression models testing associations between sociodemographics and the presence of a tobacco-selling pharmacy or tobacco shop. Across all measures, tracts with a greater percentage of residents living below 150% of the federal poverty level (FPL) had higher density. A higher percentage of Black residents, Hispanic or Latino residents, and vacant housing was inconsistently associated with density across measures. Neighborhoods with a greater percentage of Black residents had a lower odds of having a pharmacy (adjusted odds ratio [aOR] = 0.96, 95% confidence interval [CI; 0.95, 0.97]) and tobacco shop (aOR = 0.87, CI [0.86, 0.89]), while those with a greater percentage of residents living below 150% FPL had greater odds of having a tobacco shop (aOR = 1.18, CI [1.16, 1.20]). Researchers and policymakers should consider how various measures of retailer density may capture different aspects of the environment. Furthermore, there may be an inequitable impact of retailer-specific policies on tobacco availability.

Oral Anticancer Agent (OAA) Adherence and Survival in Elderly Patients With Metastatic Renal Cell Carcinoma (mRCC).

OBJECTIVE: To examine real-world adherence to oral anticancer agents (OAAs) and its association with outcomes among Medicare beneficiaries with metastatic renal cell carcinoma (mRCC). METHODS: SEER-Medicare retrospective cohort study of patients with metastatic renal cell carcinoma (mRCC) who received an OAA between 2007 and 2015. We examined A) adherence and B) overall and disease-specific 2-year survival landmarked at 3 months after OAA initiation. Adherence was assessed by calculating the proportion of days covered (PDC) within 3 months of OAA initiation, with adherent use being defined as PDC > 80%. RESULTS: A total of 905 patients met study criteria, of whom 445 patients (49.2%) were categorized as adherent to initial OAA treatment. Adjusting for clinical and demographic factors revealed decreased odds of adherence associated with living within an impoverished neighborhood (OR 0.49, CI 0.0.33 - 0.74) and out-of-pocket costs > $200 (OR 0.68, CI 0.47-.98). Adherence was associated with improved 2-year survival in univariate analysis (logrank test, P = .01) and a non-significant trend toward an association with decreased all-cause (HR 0.87, CI 0.72 - 1.05) and RCC-specific survival (HR 0.84, CI 0.69 - 1.03) in multivariable analysis. CONCLUSION: Local poverty levels and high out-of-pocket costs are associated with poor initial adherence to OAA therapy in Medicare beneficiaries with mRCC, which in turn, suggests a trend toward poor overall and disease-specific survival. Efforts to improve outcomes in the broader mRCC population should incorporate OAA adherence and economic factors.

Patient, provider, and hospital factors associated with oral anti-neoplastic agent initiation and adherence in older patients with metastatic renal cell carcinoma.

INTRODUCTION: Oral anti-neoplastic agents (OAAs) for metastatic renal cell carcinoma (mRCC) are associated with increased cancer-specific survival. However, racial disparities in survival persist and older adults have the lowest rates of cancer-specific survival. Research from other cancers demonstrates specialty access is associated with high-quality cancer care, but older adults receive cancer treatment less often than younger adults. We therefore examined whether patient, provider, and hospital characteristics were associated with OAA initiation, adherence, and cancer-specific survival after initiation and whether race, ethnicity, and/or age was associated with an increased likelihood of seeing a medical oncologist for diagnosis of mRCC. PATIENTS AND METHODS: We used Surveillance, Epidemiology, and End Results (SEER)Medicare data to identify patients ≥65 years of age who were diagnosed with mRCC from 2007 to 2015 and enrolled in Medicare Part D. Insurance claims were used to identify receipt of OAAs within twelve months of metastatic diagnosis, calculate proportion of days covered, and to identify the primary cancer provider and hospital. We examined provider and hospital characteristics associated with OAA initiation, adherence, and all-cause mortality after OAA initiation. RESULTS: We identified 2792 patients who met inclusion criteria. Increased OAA initiation was associated with access to a medical oncologist. Patients were less likely to begin OAA treatment if their primary oncologic provider was a urologist (hazard ratio [HR] 0.62; 95% confidence interval [CI] 0.49-0.77). Provider/hospital characteristics were not associated with differences in OAA adherence or mortality. Patients who started sorafenib (odds ratio [OR] 0.50; 95% CI 0.29-0.86), were older (aged >81 OR 0.56; 95% CI 0.34-0.92), and those living in high poverty ZIP codes (OR 0.48; 95% CI 0.29-0.80) were less likely to adhere to OAA treatment. Furthermore, provider characteristics did not account for differences in mortality once an OAA was initiated. Last, only age > 81 years was statistically and clinically associated with a decreased relative risk of seeing a medical oncologist (risk ratio [RR] 0.87; CI 0.82-0.92). CONCLUSION: Provider/hospital factors, specifically, being seen by a medical oncologist for mRCC diagnosis, are associated with OAA initiation. Older patients were less likely to see a medical oncologist; however, race and/or ethnicity was not associated with differences in seeing a medical oncologist. Patient factors are more critical to OAA adherence and mortality after OAA initiation than provider/hospital factors.

Associations of County Tobacco Retailer Availability With U.S. Adult Smoking Behaviors, 2014-2015.

INTRODUCTION: Greater availability of tobacco product retailers in an area may be associated with smoking behaviors, and the majority of people who smoke purchase their cigarettes at gas stations and convenience stores. This cross-sectional study investigates the associations of overall tobacco retailer density and gas/convenience density with adult smoking behaviors. METHODS: This study built a list of tobacco retailers in 2014 and calculated the county-level number of retailers per 1,000 people. Individual-level smoking behavior data were drawn from the 2014-2015 Tobacco Use Supplement for a sample of adults (n=88,850) residing in metropolitan counties across the U.S. General estimating equation models were fit to investigate the associations between retailer density and cigarette smoking behaviors (smoking status, quit attempt, quit length). Analyses were conducted in 2020. RESULTS: A greater number of tobacco retailers (AOR=1.63, 95% CI=1.35, 1.96) and gas stations and convenience stores (AOR=3.29, 95% CI=2.39, 4.52) per 1,000 people were each associated with a higher odds of a respondent smoking every day than the odds of a respondent not smoking. In addition, both measures were associated with a higher odds of a respondent being an every-day than being a some-day smoker. Associations for gas/convenience density were similar in models that additionally controlled for other tobacco retailers (excluding gas/convenience). Study results did not support associations between retailer density and cessation. CONCLUSIONS: Tobacco retailer density, especially gas/convenience density, is correlated with daily smoking, the most harmful tobacco use behavior. Calculating tobacco retailer density using gas/convenience stores may be a feasible proxy for overall tobacco retailer density.

Sociodemographic inequities in tobacco retailer density: Do neighboring places matter?

We apply a spatial perspective to measure the extent to which the 2018 U.S. racial, ethnic, and socioeconomic composition of census tracts were each associated with tobacco retailer density within a tract and in its neighboring tracts (n = 71,409). A 10-percentage point increase in the Black population was associated with 0.07 (p < 0.05) more retailers per square mile within a focal tract and 0.35 (p < 0.001) more retailers per square mile in its neighbors on average. A greater percent of Hispanic/Latino residents was associated with more retailers per square mile, both within a focal tract (b = 0.95, p < 0.001) and in its neighbors 0.39 (p < 0.001). Inverse associations were observed for percent white. We also observed inequities by socioeconomic status. The overall magnitude of inequities may be underestimated if the spatial dependence between focal tracts and their neighbors are not taken into consideration. Policymakers should prioritize interconnected geographic areas experiencing high racialized and socioeconomic segregation when designing and implementing policies to reduce retail tobacco product availability.

Understanding and identifying immortal-time bias in surgical health services research: An example using surgical resection of stage IV breast cancer.

Surgical health services researchers are increasingly utilizing observational data to assess associations between treatments and outcomes, especially since some procedures are unable to be evaluated through randomized controlled trials. However, the results of many of these studies may be affected by the presence of immortal-time bias, which exists when treatment does not occur on Day 0 of the study. This bias can result in researchers overestimating a treatment benefit, or even observe a treatment benefit when none exists. In this paper, we describe what immortal-time bias is, the challenges it presents, and how to recognize and address it using the real-world example of surgical resection of the primary tumor for stage IV breast cancer throughout. In our example, we guide researchers and illustrate how the early studies, which did not account for immortal-time bias, suggested a protective benefit of surgery, and how these results were supplanted by more recent studies through identifying and addressing immortal-time bias in their design and analyses.

The Adolescent and Young Adult (AYA) Horizon Study: An AYA Cancer Survivorship Cohort.

BACKGROUND: In the United States, >45,000 adolescent and young adult (AYA) women are diagnosed with cancer annually. Reproductive issues are critically important to AYA cancer survivors, but insufficient information is available to address their concerns. The AYA Horizon Study was initiated to contribute high-quality, contemporary evidence on reproductive outcomes for female cancer survivors in the United States. METHODS: The study cohort includes women diagnosed with lymphoma, breast, melanoma, thyroid, or gynecologic cancer (the five most common cancers among women ages 15-39 years) at three study sites: the state of North Carolina and the Kaiser Permanente health systems in Northern and Southern California. Detailed information on cancer treatment, fertility procedures, and pregnancy (e.g., miscarriage, live birth) and birth (e.g., birth weight, gestational length) outcomes are leveraged from state cancer registries, health system databases and administrative insurance claims, national data on assisted reproductive technology procedures, vital records, and survey data. RESULTS: We identified a cohort of 11,072 female AYA cancer survivors that includes >1,200 African American women, >1,400 Asian women, >1,600 Medicaid enrollees, and >2,500 Hispanic women using existing data sources. Active response to the survey component was low overall (N = 1,679), and notably lower among minority groups compared with non-Hispanic white women. CONCLUSIONS: Passive data collection through linkage reduces participant burden and prevents systematic cohort attrition or potential selection biases that can occur with active participation requirements. IMPACT: The AYA Horizon study will inform survivorship planning as fertility and parenthood gain increasing recognition as key aspects of high-quality cancer care.

Objectively assessed associations between physical activity and body composition in middle-school girls: the Trial of Activity for Adolescent Girls.

Declining levels of physical activity probably contribute to the increasing prevalence of overweight in US youth. In this study, the authors examined cross-sectional and longitudinal associations between physical activity and body composition in sixth- and eighth-grade girls. In 2003, girls were recruited from six US states as part of the Trial of Activity for Adolescent Girls. Physical activity was measured using 6 days of accelerometry, and percentage of body fat was calculated using an age- and ethnicity-specific prediction equation. Sixth-grade girls with an average of 12.8 minutes of moderate-to-vigorous physical activity (MVPA) per day (15th percentile) were 2.3 times (95% confidence interval: 1.52, 3.44) more likely to be overweight than girls with 34.7 minutes of MVPA per day (85th percentile), and their percent body fat was 2.64 percentage points greater (95% confidence interval: 1.79, 3.50). Longitudinal analyses showed that percent body fat increased 0.28 percentage points less in girls with a 6.2-minute increase in MVPA than in girls with a 4.5-minute decrease (85th and 15th percentiles of change). Associations between MVPA in sixth grade and incidence of overweight in eighth grade were not detected. More population-based research using objective physical activity and body composition measurements is needed to make evidence-based physical activity recommendations for US youth.

Trends in myocardial infarction rates and case fatality by anatomical location in four United States communities, 1987 to 2008 (from the Atherosclerosis Risk in Communities Study).

Although the incidence of and mortality after ST-segment elevation myocardial infarction (STEMI) is decreasing, time trends in anatomical location of STEMI and associated short-term prognosis have not been examined in a population-based community study. We determined 22-year trends in age- and race-adjusted gender-specific incidences and 28-day case fatality of hospitalized STEMI by anatomic infarct location among a stratified random sample of 35- to 74-year-old residents of 4 communities in the Atherosclerosis Risk in Communities study. STEMI infarct location was assessed by 12-lead electrocardiograms from the hospital record and was coded as anterior, inferior, lateral, and multilocation STEMIs using the Minnesota code. From 1987 to 2008, a total of 4,845 patients had an incident STEMI; 37.2% were inferior STEMI, 32.8% were anterior, 16.8% occurred in multiple infarct locations, and 13.2% were lateral STEMI. For inferior, anterior, and lateral STEMIs in both men and women, significant decreases were observed in the age-adjusted annual incidence and the associated 28-day case fatality. In contrast, for STEMI in multiple infarct locations, neither the annual incidence nor the 28-day case fatality changed over time. The age- and race-adjusted annual incidence and associated 28-day case fatality of STEMI in anterior, inferior, and lateral infarct locations decreased during 22 years of surveillance; however, no decrease was observed for STEMI in multiple infarct locations. In conclusion, our findings suggest that there is room for improvement in the care of patients with multilocation STEMI.

Classification of acute decompensated heart failure: an automated algorithm compared with a physician reviewer panel: the Atherosclerosis Risk in Communities study.

BACKGROUND: An algorithm to classify heart failure (HF) end points inclusive of contemporary measures of biomarkers and echocardiography was recently proposed by an international expert panel. Our objective was to assess agreement of HF classification by this contemporaneous algorithm with that by a standardized physician reviewer panel, when applied to data abstracted from community-based hospital records. METHODS AND RESULTS: During 2005-2007, all hospitalizations were identified from 4 US communities under surveillance as part of the Atherosclerosis Risk in Communities (ARIC) study. Potential HF hospitalizations were sampled by International Classification of Diseases discharge codes and demographics from men and women aged ≥ 55 years. The HF classification algorithm was automated and applied to 2729 (n=13854 weighted hospitalizations) hospitalizations in which either brain natriuretic peptide measures or ejection fraction were documented (mean age, 75 years). There were 1403 (54%; n=7534 weighted) events classified as acute decompensated HF by the automated algorithm, and 1748 (68%; n=9276 weighted) such events by the ARIC reviewer panel. The chance-corrected agreement between acute decompensated HF by physician reviewer panel and the automated algorithm was moderate (κ=0.39). Sensitivity and specificity of the automated algorithm with ARIC reviewer panel as the referent standard were 0.68 (95% confidence interval, 0.67-0.69) and 0.75 (95% confidence interval, 0.74-0.76), respectively. CONCLUSIONS: Although the automated classification improved efficiency and decreased costs, its accuracy in classifying HF hospitalizations was modest compared with a standardized physician reviewer panel.

Prognostic significance of serial Q/ST-T changes by the Minnesota Code and Novacode in the Atherosclerosis Risk in Communities (ARIC) study.

AIMS: To compare the value of serial electrocardiographic (ECG) changes by the two most widely used ECG classification systems-the Minnesota Code (MC) and Novacode (Nova) for the prediction of subsequent coronary heart disease (CHD) and total mortality. METHODS AND RESULTS: We studied 12-lead ECGs from 12,477 participants (average age 54 years at baseline; 58% women; 76% non-Hispanic white) in the Atherosclerosis Risk in Communities (ARIC) Study, who were free of CHD at baseline in 1987, had both good-quality ECGs at baseline and at first study-scheduled follow-up visit, and had ECG QRS duration <120 ms. A total 2119 participants died (17%), including 280 CHD deaths during an average 17-year follow up. Cox regression models assessed outcome associated with significant serial ECG changes by MC and Nova separately. For CHD death the hazard ratio was 6.8 (95% CI 3.5-13.3) for incident Nova myocardial infarction (MI), and 5.7 (95% CI 2.7-11.9) for MC-MI in a multivariable model adjusted for clinical and demographic characteristics, and ECG left ventricular hypertrophy. The increased risk for total mortality doubled for both Nova and MC serial ECG MI. Major evolving ST-T wave abnormalities alone were associated with a ≥132% increased risk for CHD death and a 50% increased risk for total mortality by either Nova or MC. CONCLUSION: ECG serial change by both MC and Nova are equally valuable predictors for future fatal cardiac events and total mortality and hence equally useful prognostic indicators in clinical trials and epidemiological studies.

Classification of heart failure in the atherosclerosis risk in communities (ARIC) study: a comparison of diagnostic criteria.

BACKGROUND: Population-based research on heart failure (HF) is hindered by lack of consensus on diagnostic criteria. Framingham (FRM), National Health and Nutrition Examination Survey (NHANES), Modified Boston (MBS), Gothenburg (GTH), and International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) code criteria, do not differentiate acute decompensated heart failure (ADHF) from chronic stable HF. We developed a new classification protocol for identifying ADHF in the Atherosclerosis Risk in Communities (ARIC) Study and compared it with these other schemes. METHODS AND RESULTS: A sample of 1180 hospitalizations with a patient address in 4 study communities and eligible discharge codes were selected. After assessing whether the chart contained evidence of possible HF signs, 705 were fully abstracted. Two independent reviewers classified each case as ADHF, chronic stable HF, or no HF, using ARIC classification guidelines. Fifty-nine percent of cases met ARIC criteria for ADHF and 13.9% and 27.1% were classified as chronic stable HF or no HF, respectively. Among events classified as HF by FRM criteria, 68.4% were validated as ADHF, 9.6% as chronic stable HF, and 21.9% as no HF. However, 92.5% of hospitalizations with a primary ICD-9-CM 428 "heart failure" code were validated as ADHF. Sensitivities of comparison criteria to classify ADHF ranged from 38-95%, positive predictive values from 62-92%, and specificities from 19-96%. CONCLUSIONS: Although comparison criteria for classifying HF were moderately sensitive in identifying ADHF, specificity varied when applied to a randomly selected set of suspected HF hospitalizations in the community.