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1.  Connections between pharmacoepidemiology and cancer biology: designing biologically relevant studies of cancer outcomes 
Annals of epidemiology  2016;26(11):741-745.
doi:10.1016/j.annepidem.2016.10.001
PMCID: PMC5765753  PMID: 27837786
pharmacoepidemiology; cancer epidemiology; cancer biology; study design
2.  Space-time variation of respiratory cancers in South Carolina: A flexible multivariate mixture modeling approach to risk estimation 
Annals of epidemiology  2016;27(1):42-51.
Purpose
Many types of cancer have an underlying spatio-temporal distribution. Spatio-temporal mixture modeling can offer a flexible approach to risk estimation via the inclusion of latent variables.
Methods
In this paper, we examine the application and benefits of using four different spatio-temporal mixture modeling methods in the modeling of cancer of the lung and bronchus as well as “other” respiratory cancer incidences in the state of South Carolina, USA.
Results
Of the methods tested, no single method outperforms the other methods; which method is best depends on the cancer under consideration. The lung and bronchus cancer incidence outcome is best described by the univariate modeling formulation while the “other” respiratory cancer incidence outcome is best described by the multivariate modeling formulation.
Conclusion
Spatio-temporal multivariate mixture methods can aid in the modeling of cancers with small and sparse incidences when including information from a related, more common type of cancer.
doi:10.1016/j.annepidem.2016.08.014
PMCID: PMC5272780  PMID: 27653555
Spatio-temporal; Bayesian; multivariate; respiratory cancers; mixture modeling; MCMC; lung and bronchus cancer
3.  Quantifying Spatial Misclassification in Exposure to Noise Complaints Among Low-Income Housing Residents Across New York City Neighborhoods: A Global Positioning System (GPS) Study 
Annals of epidemiology  2016;27(1):67-75.
Purpose
To examine if there was spatial misclassification in exposure to neighborhood noise complaints among a sample of low-income housing residents in New York City, comparing home-based spatial buffers and Global Positioning Systems (GPS) daily path buffers.
Methods
Data came from the community-based NYC Low-Income Housing, Neighborhoods and Health Study, where GPS tracking of the sample was conducted for a week (analytic n=102). We created a GPS daily path buffer (a buffering zone drawn around GPS tracks) of 200-meters and 400-meters. We also used home-based buffers of 200-meters and 400-meters. Using these “neighborhoods” (or exposure areas) we calculated neighborhood exposure to noisy events from 311 complaints data (analytic n=143,967). Friedman tests (to compare overall differences in neighborhood definitions) were applied.
Results
There were differences in neighborhood noise complaints according to the selected neighborhood definitions (p<0.05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-meter home-based and 812 per square kilometer for the 400-meter activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.
Conclusions
These analyses suggest that, whenever appropriate, GPS neighborhood definitions can be used in spatial epidemiology research in spatially mobile populations to understand people's lived experience.
doi:10.1016/j.annepidem.2016.09.017
PMCID: PMC5272798  PMID: 28063754
spatial epidemiology; spatial misclassification; neighborhoods; geographic information systems; global positioning systems; low-income housing residents; noise complaint exposure
4.  Using Residential Segregation to Predict Colorectal Cancer Stage at Diagnosis: Two Different Approaches 
Annals of epidemiology  2016;27(1):10-19.
Purpose
Studies have found a variety of evidence regarding the association between residential segregation measures and health outcomes in the US. Some have focused on any individuals living in residentially segregated places, while others have examined whether persons of specific races or ethnicities living in places with high segregation of their own race or ethnicity have differential outcomes. This paper compares and contrasts these two approaches in the study of predictors of late-stage CRC diagnoses in a cross-national study. We argue that it is very important when interpreting results from studies like this to carefully consider the geographic scope of the analysis, which can significantly change the context and meaning of the results.
Methods
We use US Cancer Statistics Registry data from 40 states to identify late-stage diagnoses among over 500 thousand CRC cases diagnosed during 2004–2009. We pool data over the states and estimate a multilevel model with person, county, and state levels and a random intercepts specification to ensure robust effect estimates. The isolation index of residential segregation is defined for racial and ethnic groups at the county level using Census 2000 data. The association between isolation indices and late stage CRC diagnosis was measured by 1) anyone living in minority segregated areas (place-centered approach), and by 2) individuals living in areas segregated by one’s own racial or ethnic peers (person-centered approach).
Results
Findings from the place-centered approach suggest that living in a highly segregated African American community is associated with lower likelihood of late-stage CRC diagnosis, while the opposite is true for people living in highly segregated Asian communities, and living in highly segregated Hispanic communities has no significant association. Using the person-centered approach, we find that living in places segregated by one’s racial or ethnic peers is associated with lower likelihood of late-stage CRC diagnosis.
Conclusions
In a model that covers a large geographic area across the nation, the place-centered approach is most likely picking up geographic disparities that may be deepened by targeted interventions in minority communities. By contrast, the person-centered approach provides a national average estimate suggesting that residential isolation may confer community cohesion or support that is associated with better CRC prevention.
doi:10.1016/j.annepidem.2016.11.008
PMCID: PMC5272810  PMID: 27939165
5.  Disease Mapping of Zero-excessive Mesothelioma Data in Flanders 
Annals of epidemiology  2016;27(1):59-66.e3.
Purpose
To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion.
Methods
The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero-inflation and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature.
Results
The results indicate that hurdle models with a random effects term accounting for extra-variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra-variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra-variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary.
Conclusions
Models taking into account zero-inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this.
doi:10.1016/j.annepidem.2016.10.006
PMCID: PMC5272833  PMID: 27908590
Excess Zeros; Mesothelioma; Disease Mapping; Conditional Autoregressive Convolution Model; Bayesian Analysis
6.  The Utility of EMR Address Histories for Assessing Neighborhood Exposures 
Annals of epidemiology  2016;27(1):20-26.
Purpose
Electronic medical records (EMR) include residential address histories, which may alleviate exposure misclassification caused by exclusion of patient spatiotemporal location. EMR data are increasingly available but rarely leveraged as a measure of cumulative environmental exposure, in part due to limited understanding of the validity of EMR-derived address histories.
Methods
We compared EMR address histories to self-reported histories among 100 patients of a safety-net healthcare system completing a telephone survey. We assessed agreement and compared 7 neighborhood-level environmental exposures as assessed using both data sources.
Results
While 17.1% of respondents did not live at the most recent EMR-derived address during the survey, nearly all (98%) lived there at some point. For respondents with >1 EMR-derived address (N=64), 87.5% had once lived at the previous EMR address. Of these, 30.4% lived at ≥1 additional residences between the two most recent EMR address. For all measures, neighborhood-level environmental exposures did not differ when using EMR-derived vs. self-report addresses.
Conclusions
More recent EMR-derived addresses are more accurate and differences compared to self-reported addresses in neighborhood-level exposures are negligible. EMR-derived address histories are incomplete and likely suffer from collection bias; future research should further assess their validity and reliability.
doi:10.1016/j.annepidem.2016.07.016
PMCID: PMC5482357  PMID: 27663209
Residential mobility; electronic medical record; neighborhoods; geographic information systems (GIS)
7.  Widespread recent increases in county-level heart disease mortality across age groups 
Annals of epidemiology  2017;27(12):796-800.
Purpose
Recent national trends show decelerating declines in heart disease mortality, especially among younger adults. National trends may mask variation by geography and age. We examined recent county-level trends in heart disease mortality by age group.
Methods
Using a Bayesian statistical model and National Vital Statistics Systems data, we estimated overall rates and percent change in heart disease mortality from 2010 through 2015 for four age groups (35–44, 45–54, 55–64, and 65–74 years) in 3098 US counties.
Results
Nationally, heart disease mortality declined in every age group except ages 55–64 years. County-level trends by age group showed geographically widespread increases, with 52.3%, 58.5%, 69.1%, and 42.0% of counties experiencing increases with median percent changes of 0.6%, 2.2%, 4.6%, and −1.5% for ages 35–44, 45–54, 55–64, and 65–74 years, respectively. Increases were more likely in counties with initially high heart disease mortality and outside large metropolitan areas.
Conclusions
Recent national trends have masked local increases in heart disease mortality. These increases, especially among adults younger than age 65 years, represent challenges to communities across the country. Reversing these trends may require intensification of primary and secondary prevention—focusing policies, strategies, and interventions on younger populations, especially those living in less urban counties.
doi:10.1016/j.annepidem.2017.10.012
PMCID: PMC5733620  PMID: 29122432
Heart diseases; Geography; Mortality decline; Mortality rates; Age groups
8.  Self-reported herpes zoster, pain, and health care seeking in the Health and Retirement Study: implications for interpretation of health care–based studies 
Annals of epidemiology  2016;26(6):441-446.e3.
Purpose
To describe self-reported herpes zoster (HZ) and explore factors that could impact interpretation of results from health care–based HZ studies.
Methods
We performed logistic regression using data from the 2008 Health and Retirement Study (HRS) to evaluate risk factors for having a history of HZ and experiencing severe HZ pain, and predictors for seeking health care for HZ.
Results
Among 14,564 respondents aged ≥55 years, women were more likely than men to report a history of HZ (15.7% vs. 11.6%, P < .01). Blacks (6.4% vs. 14.7% in whites, P < .01) and respondents with less than a high school diploma (12.2% vs.14.2% in respondents with at least a high school diploma, P = .01) were less likely to report a history of HZ. Women, blacks, Hispanics, and those with less than a high school diploma were more likely to report severe HZ pain. Most (91.1%) respondents sought health care for HZ; Hispanics (64.2% vs. 92.1% in whites, P < .001) and those with recurrent HZ were less likely to seek health care for HZ, whereas those with severe pain were more likely (95.4% vs. 87.9% in those without severe pain, P < .01).
Conclusions
HRS provides a new platform for studies of HZ, one which allowed us to uncover issues that warrant particular attention when interpreting results of health care–based studies.
doi:10.1016/j.annepidem.2016.04.006
PMCID: PMC5719862  PMID: 27180114
Herpes zoster; Health surveys; Epidemiologic methods; Population surveillance; Risk factors; Pain; Health care seeking behaviour; Medical records
9.  The association between handheld phone bans and the prevalence of handheld phone conversations among young drivers in the United States 
Annals of epidemiology  2016;26(12):833-837.e1.
Purpose
Fourteen U.S. states and the District of Columbia have banned handheld phone use for all drivers. We examined whether such legislation was associated with reduced handheld phone conversations among drivers < 25 years of age.
Methods
Data from the 2008–2013 National Occupant Protection Use Survey were merged with states’ legislation. The outcome was roadside-observed handheld phone conversation at stop signs or lights. Logistic regression was used.
Results
A total of 32,784 young drivers were observed. Relative to drivers who were observed in states without a universal handheld phone ban, the adjusted odds ratio (aOR) of phone conversation was 0.42 (95% confidence interval CI: 0.33, 0.53) for drivers who were observed in states with bans. The relative reduction in phone conversation was 46% (23%, 61%) for laws that were effective < 1 year, 55% (32%, 70%) for 1–2 years, 63% (51%, 72%) for ≥ 2 years, relative to no laws.
Conclusions
Universal handheld phone bans may be effective at reducing handheld phone use among young drivers.
doi:10.1016/j.annepidem.2016.10.002
PMCID: PMC5134740  PMID: 27894566
Automobile driving; adolescent; epidemiology; legislation
10.  Validating a summary measure of weight history for modeling the health consequences of obesity 
Annals of epidemiology  2016;26(12):821-826.e2.
Purpose
Data on weight history may enhance the predictive validity of epidemiological models of the health risks of obesity but collecting such data is often not feasible. In this study, we investigate the validity of a summary measure of weight history.
Methods
We evaluated the quality of reporting of maximum weight in a sample of adults ages 50-84 using data from the Health and Retirement Study. Recalled max body mass index (BMI, measured in kg/m2) based on recalled weight in 2004 was compared to calculated max BMI based on self-reported weight collected biennially between 1992 and 2004. Logistic regression was used to assess similarity between the measures in predicting prevalent conditions.
Results
The correlation coefficient between recalled and calculated max weight in the overall sample was 0.95. Recalled max BMI value was within 3 BMI units of the calculated value 91.4% of the time. The proportion of individuals obese I (BMI 30.0-34.9), obese II (35.0-39.9) and obese III (40.0 and above) were 28.8%, 12.7% and 6.6% using recalled values compared to 27.1%, 10.5% and 4.9% using calculated values. In multivariate analyses, the two BMI measures similarly predicted disease prevalence across a number of chronic conditions.
Conclusions
Recalled max BMI was strongly correlated with max BMI calculated over the twelve year period prior to recall, suggesting that this measure can serve as a reliable summary measure of recent weight status.
doi:10.1016/j.annepidem.2016.10.005
PMCID: PMC5142761  PMID: 27894565
Overweight; obesity; body mass index; weight histories; maximum weight; aging and lifecourse; mortality; epidemiology; validation; Health and Retirement Study
11.  Challenges in evaluating cancer as a clinical outcome in postapproval studies of drug safety 
Annals of epidemiology  2016;26(11):735-740.
Pharmaceuticals approved in the United States are largely not known human carcinogens. However, cancer signals associated with pharmaceuticals may be hypothesized or arise after product approval. There are many study designs that can be used to evaluate cancer as an outcome in the postapproval setting. Because prospective systematic collection of cancer outcomes from a large number of individuals may be lengthy, expensive, and challenging, leveraging data from large existing databases are an integral approach. Such studies have the capability to evaluate the clinical experience of a large number of individuals, yet there are unique methodological challenges involved in their use to evaluate cancer outcomes. To discuss methodological challenges and potential solutions, the Food and Drug Administration and the National Cancer Institute convened a two-day public meeting in 2014. This commentary summarizes the most salient issues discussed at the meeting.
doi:10.1016/j.annepidem.2016.04.012
PMCID: PMC5673103  PMID: 27663208
Cancer epidemiology; Pharmacoepidemiology; Drug safety
13.  Racial differences in renal replacement therapy initiation among children with a non-glomerular cause of chronic kidney disease 
Annals of epidemiology  2016;26(11):780-787.e1.
Purpose
African American (AA) adults with chronic kidney disease (CKD) have a faster progression to end stage renal disease (ESRD) and are less likely to receive a kidney transplant. It is unclear whether AA children experience renal replacement therapy (RRT) for ESRD sooner than non-AA children after accounting for socioeconomic status (SES).
Methods
Among children with non-glomerular CKD in the Chronic Kidney Disease in Children (CKiD) study, we investigated time to RRT (i.e., first dialysis or transplant) after CKD onset using parametric survival models and accounted for SES differences by inverse probability weights (IPWs).
Results
Of 110 AA and 493 non-AA children (median age= 10 years), AA children had shorter time to first RRT: median time was 3.2 years earlier than non-AA children (95%CI: −6.1, −0.3). When accounting for SES, this difference was diminished and non-significant (−1.6 years; 95%CI: −4.6, +1.5) and its directionality was consistent with faster GFR decline among AA children (−6.2% vs. −4.4% per year, p= 0.098). When RRT was deconstructed into dialysis or transplant, the time to dialysis was 37.5% shorter for AA children and 53.7% longer for transplant. These inferences were confirmed by the frequency and timing of transplant after initiating dialysis.
Conclusions
Racial differences in time to RRT were almost fully accounted for by SES and the remaining difference was congruent with a faster GFR decline among AA children. Access to transplant occurred later, yet times to dialysis were shorter among AA children even when accounting for SES which may be due to a lack of organ availability.
doi:10.1016/j.annepidem.2016.09.011
PMCID: PMC5110248  PMID: 27789133
pediatric nephrology; chronic kidney disease; health disparities; renal replacement therapy; inverse probability weights
14.  Examining the Relationship Between Multidrug-Resistant Organism Acquisition and Exposure to Antimicrobials in Long-term Care Populations: A Review 
Annals of epidemiology  2016;26(11):810-815.
Purpose
Methodological approaches to examining the association between antimicrobial exposure and multidrug resistant organism (MDRO) acquisition are complex. This report’s objectives are to review approaches used in and findings of prior studies in the long-term care setting, illustrate how these challenges were addressed in a recently completed large prospective study, and discuss strategies for future studies.
Methods
Key design and analytic approaches used in studies conducted since 2000 examining the association between antimicrobial exposure and MDRO acquisition in the long-term care setting were reviewed. The Study of Pathogen Resistance and Exposure to Antimicrobials in Dementia (SPREAD) in nursing home residents in Boston from 2009 to 2014 is used to illustrate how to approach these challenges.
Results
Prior investigations reporting the association between antimicrobial exposure and MDRO acquisition vary considerably in their approaches. In SPREAD, grouped-time hazard models with complementary log-log link function were used to model acquisition accounting for clustering within facilities using generalized estimating equations and including all days of exposure prior to acquisition.
Conclusions
Future studies in these populations should make use of all available acquisition status data, incorporate the timing of antimicrobial exposure relative to acquisition, and collect detailed covariate information that facilitates examining confounding by indication.
doi:10.1016/j.annepidem.2016.09.007
PMCID: PMC5119547  PMID: 27751631
Antimicrobial drug resistance; long-term care; hazard models; antimicrobial exposure
15.  Quantitative Bias Analysis in an Asthma Study of Rescue-Recovery Workers and Volunteers from the 9/11 World Trade Center Attacks 
Annals of epidemiology  2016;26(11):794-801.
Purpose
When learning bias analysis, epidemiologists are taught to quantitatively adjust for multiple biases by correcting study results in the reverse order of the error sequence. To understand the error sequence for a particular study, one must carefully examine the health study’s epidemiologic data-generating process. In this manuscript, we describe the unique data-generating process of a man-made disaster epidemiologic study.
Methods
We described the data-generating process and conducted a bias analysis for a study associating September 11, 2001 dust cloud exposure and self-reported newly-physician diagnosed asthma among rescue-recovery workers and volunteers. We adjusted an odds ratio estimate for the combined effect of missing data, outcome misclassification, and nonparticipation.
Results
Under our assumptions about systematic error, the odds ratios adjusted for all three biases ranged from 1.33 to 3.84. Most of the adjusted estimates were greater than the observed odds ratio of 1.77 and were outside the 95% confidence limits (1.55, 2.01).
Conclusions
Man-made disasters present some situations that are not observed in other areas of epidemiology. Future epidemiologic studies of disasters could benefit from a proactive approach that focuses on the technical aspect of data collection and gathers information on bias parameters to provide more meaningful interpretations of results.
doi:10.1016/j.annepidem.2016.09.002
PMCID: PMC5135411  PMID: 27756685
Asthma; Bias Analysis; Outcome Misclassification; Selection Bias; Sensitivity Analysis; World Trade Center; 9/11
16.  Accuracy of name and age data provided about network members in a social network study of people who use drugs: Implications for constructing sociometric networks 
Annals of epidemiology  2016;26(11):802-809.
Purpose
Network analysis has become increasingly popular in epidemiologic research, but the accuracy of data key to constructing risk networks is largely unknown. Using network data from people who use drugs (PWUD), the study examined how accurately PWUD reported their network members’ (i.e., alters’) names and ages.
Methods
Data were collected from 2008 to 2010 from 503 PWUD residing in rural Appalachia. Network ties (n=897) involved recent (past 6 months) sex, drug co-usage, and/or social support. Participants provided alters’ names, ages, and relationship-level characteristics; these data were cross-referenced to that of other participants to identify participant-participant relationships and to determine the accuracy of reported ages (years) and names (binary).
Results
Participants gave alters’ exact names and ages within two years in 75% and 79% of relationships, respectively. Accurate name was more common in relationships that were reciprocally reported and those involving social support and male alters. Age was more accurate in reciprocal ties and those characterized by kinship, sexual partnership, recruitment referral, and financial support, and less accurate for ties with older alters.
Conclusions
Most participants reported alters’ characteristics accurately, and name accuracy was not significantly different in relationships involving drug-related/sexual behavior compared to those not involving these behaviors.
doi:10.1016/j.annepidem.2016.09.010
PMCID: PMC5283838  PMID: 28126091
data accuracy; drug abuse; HIV; hepatitis C; intravenous drug abuse; social networks; self report; rural health
17.  Menopausal Hormone Therapy and Sleep-Disordered Breathing: Evidence for a Healthy-User Bias 
Annals of epidemiology  2015;25(10):779-84.e1.
Purpose
Observational studies suggest that menopausal hormone therapy protects against sleep-disordered breathing, but such findings may be biased by a “healthy-user effect.” When the Women’s Health Initiative Study reported in 2002 that estrogen-progestin therapy increases heart disease risk, many women discontinued hormone therapy. We investigate healthy-user bias in the association of hormone therapy with sleep-disordered breathing in the Sleep in Midlife Women Study.
Methods
228 women age 38–62 were recruited from the Wisconsin Sleep Cohort Study. They underwent polysomnography to measure apnea-hypopnea index, at home semiannually from 1997–2006, and in the sleep laboratory every four years (N=1,828 studies). Hormone therapy was recorded monthly. Linear models with empirical standard errors regressed logarithm of apnea-hypopnea index on hormone use with a pre/post-July 2002 interaction, adjusting for menopause and age.
Results
The association of hormone therapy and sleep-disordered breathing was heterogeneous (p<0.01); apnea-hypopnea index among users was 15% lower in the early period (95% confidence interval: −27%, −1%), but similar to non-users in the late.
Conclusions
Hormone therapy was negatively associated with sleep-disordered breathing only until the Women’s Health Initiative results were publicized. Hormone therapy may have been a marker for healthfulness in the early period, creating a spurious association with sleep-disordered breathing.
doi:10.1016/j.annepidem.2015.07.004
PMCID: PMC5645789  PMID: 26358364
Sleep Apnea Syndromes; Sleep Apnea; Obstructive; Women’s Health; Menopause; Estrogen Replacement Therapy; Bias (Epidemiology)
18.  Sepsis surveillance from administrative data in the absence of a perfect verification 
Annals of epidemiology  2016;26(10):717-722.e1.
Purpose
Past studies of sepsis epidemiology did not address misclassification bias due to imperfect verification of sepsis detection methods to estimate the true prevalence.
Methods
We examined 273 126 hospitalizations from 2008–2012 at a tertiary-care center to develop surveillance-aimed sepsis detection criteria, based on the presence of the sepsis explicit International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes (995.92 or 785.52), blood culture orders, and antibiotics administration. We used Bayesian multinomial latent class models to estimate the true prevalence of sepsis, while adjusting for the imperfect sensitivity and specificity and the conditional dependence among the individual criteria.
Results
The apparent annual prevalence of sepsis hospitalizations based on explicit ICD-9-CM codes were 1.5%, 1.4%, 1.6%, 2.2%, and 2.5% for the years 2008 to 2012. Bayesian posterior estimates for the true prevalence of sepsis suggested that it remained stable from 2008, 19.2% (95% credible interval [CI]: 17.9%, 22.9%), to 2012, 17.8% (95% CI: 16.8%, 20.2%). The sensitivity of sepsis-explicit codes, however, increased from 7.6% (95% CI: 6.4%, 8.4%) in 2008 to 13.8% (95% CI: 12.2%, 14.9%) in 2012.
Conclusions
The true prevalence of sepsis remained high, but stable despite an increase in the sensitivity of sepsis-explicit codes in administrative data.
doi:10.1016/j.annepidem.2016.08.002
PMCID: PMC5086291  PMID: 27600804
Bayesian estimation; No reference standard; Prevalence; Sensitivity; Sepsis; Specificity; Surveillance
19.  An argument for renewed focus on epidemiology for public health 
Annals of epidemiology  2016;26(10):729-733.
Purpose
While epidemiology has an indispensable role in serving public health, the relative emphasis of applications of epidemiology often tend toward individual-level medicine over public health in terms of resources and impact.
Methods
We make distinctions between public health and medical applications of epidemiology to raise awareness among epidemiologists, many of whom came to the field with public health in mind. We discuss reasons for the overemphasis on medical epidemiology and suggest ways to counteract these incentives.
Results
Public health epidemiology informs interventions that are applied to populations or that confer benefits beyond the individual, while medical epidemiology informs interventions that improve the health of treated individuals. Available resources, new biomedical technologies, and existing epidemiologic methods favor medical applications of epidemiology. Focus on public health impact and methods suited to answer public health questions can create better balance and promote population-level improvements in public health.
Conclusions
By deliberately reflecting on research motivations and long-term goals, we hope the distinctions presented here will facilitate critical discussion and a greater consciousness of our potential impact on both individual and population-level health. Renewed intentions towards public health can help epidemiologists navigate potential projects and ultimately contribute to an epidemiology of consequence.
doi:10.1016/j.annepidem.2016.08.008
PMCID: PMC5086292  PMID: 27659585
20.  Lipopolysaccharide-pathway proteins are associated with gallbladder cancer among adults in Shanghai, China with mediation by systemic inflammation 
Annals of epidemiology  2016;26(10):704-709.
Purpose
We examined inflammation as a mediator of associations between bacterial infection markers and gallbladder cancer (GBC).
Methods
Bacterial response proteins [lipopolysaccharide (LPS), soluble CD14 (sCD14), and LPS-binding protein (LBP)] were measured in 40 GBC cases and 126 gallstone controls with data on 63 serum inflammation markers. The relationships of LPS, LBP, and sCD14 with GBC were examined by logistic regression, which also was used to evaluate whether these associations are influenced by systemic inflammation as measured by a combinatorial inflammation score.
Results
The third versus the first tertiles of sCD14 and of LBP were associated with an increased GBC risk [Odds Ratio (95% Confidence Interval): 5.41 (2.00–16.75) for sCD14, and 6.49 (2.24–23.79) for LBP]. sCD14 and LBP were strongly associated with inflammation score (above versus below the median), which itself was associated with a >21-fold increased risk of GBC for the third vs. first tertiles. Associations between GBC and sCD14 and LBP were markedly attenuated when the inflammation score was included in the model. While LPS was not associated with GBC or inflammation, only 35% of cases and 22% of controls had detectable levels.
Conclusions
These findings suggest that these LPS-pathway proteins are associated with GBC via inflammation-related pathways.
doi:10.1016/j.annepidem.2016.08.009
PMCID: PMC5123694  PMID: 27793274
Gallbladder cancer; Lipopolysaccharide-pathway; Inflammation; Mediation analysis
21.  Does water kill? A call for less casual causal inferences 
Annals of epidemiology  2016;26(10):674-680.
“Can this number be interpreted as a causal effect?” is a key question for scientists and decision makers. The potential outcomes approach, a quantitative counterfactual theory, describes conditions under which the question can be answered affirmatively. This article reviews one of those conditions, known as consistency, and its implications for real world decisions.
doi:10.1016/j.annepidem.2016.08.016
PMCID: PMC5207342  PMID: 27641316
22.  Delayed presentation and diagnosis of breast cancer in African women: a systematic review 
Annals of Epidemiology  2017;27(10):659-671.e7.
Purpose
Africa has low breast cancer incidence rates but high mortality rates from this disease due to poor survival. Delays in presentation and diagnosis are major determinants of breast cancer survival, but these have not been comprehensively investigated in Africa.
Methods
MEDLINE, Embase, and Global Health were searched to identify studies reporting on delays in presentation and/or diagnosis of breast cancer published between January 1, 2000 and May 31, 2016. Data were synthesized in narrative, tabular, and graphical forms. Meta-analyses were not possible due to between-study differences in the way delays were reported.
Results
Twenty-one studies were included in the review. Study-specific average times between symptom recognition and presentation to a health care provider ranged from less than 1 to 4 months in North Africa and from less than 3 to greater than 6 months in sub-Saharan Africa. Study-specific average times from presentation to diagnosis were less than 1 month in North Africa but ranged from less than 3 to greater than 6 months in sub-Saharan Africa. Reported reasons for these delays included patient-mediated (e.g., socioeconomic factors) and health system–mediated factors (e.g., referral pathways).
Conclusions
This systematic review revealed marked delays in presentation and diagnosis of breast cancer in Africa. Identification of their drivers is crucial to the development of appropriate control strategies in the continent.
doi:10.1016/j.annepidem.2017.09.007
PMCID: PMC5697496  PMID: 29128086
Breast cancer; Africa; Delayed presentation; Delayed diagnosis; Late-stage breast cancer
23.  Reproductive Factors and Ovarian Cancer Risk in African American Women 
Annals of epidemiology  2016;26(9):654-662.
Purpose
Reproductive characteristics, the most established ovarian cancer risk factors, differ markedly between African American and White women. Studies in predominantly White populations suggest that associations between reproductive characteristics and ovarian cancer vary by timing of the events and menopause status. This analysis examined associations between number, duration and timing of reproductive events and epithelial ovarian cancer among African American women.
Methods
Data from a multi-center case-control study of ovarian cancer in African American women (641 cases/752 controls) were used to examine associations with oral contraceptive use and pregnancy characteristics. Odds ratios(OR) and 95% confidence intervals(CI) associated with reproductive characteristics were calculated with logistic regression models.
Results
Oral contraceptive use (OR=0.7, 95%CI 0.5–0.9), parity (OR=0.5, 95% CI 0.3–0.6) and breastfeeding for >12 months (OR=0.3, 95% CI 0.2–0.5) were inversely associated with ovarian cancer. More recent pregnancies and oral contraceptive use had stronger associations with ovarian cancer than pregnancies or oral contraceptive use that occurred earlier in life, especially among pre-menopausal women.
Conclusions
This study provides the first thorough documentation that pregnancy, breastfeeding and oral contraceptive use are inversely associated with ovarian cancer in African American women, similar to what has been observed in White women. The associations with timing of the exposures suggest that these factors have both short and long-term effects.
doi:10.1016/j.annepidem.2016.07.004
PMCID: PMC5035608  PMID: 27528178
African Americans; breastfeeding; case-control study; oral contraceptives; ovarian cancer; parity; pregnancy
24.  The Muscle Quality Index and Mortality among Males and Females 
Annals of epidemiology  2016;26(9):648-653.
Purpose
The muscle quality index (MQI) was proposed as a measure to quantify age-related alterations in muscle function. It is unknown if the MQI predicts mortality.
Methods
This was a population-based cohort study from the Third National Health and Nutrition Survey (NHANES III; 1988–1994). The MQI was quantified using a timed sit-to-stand test, body mass, and leg length. Vital status was obtained through the National Center for Health Statistics. We fit multivariable-adjusted regression models to estimate the Hazard Ratio (HR) and 95% Confidence Interval (CI) between the MQI and mortality.
Results
During 14.6 years of follow-up, 3,299 (73.1%) of 4,510 study participants died. Lower MQI was associated with a higher risk of mortality (Ptrend<0.001). The multivariable-adjusted HR for mortality was 1.50 (95% CI: 1.15–1.96) for those in the lowest quintile of MQI compared to the highest quintile. The association between MQI and mortality was stronger among males [highest versus lowest quintile of MQI, HR: 1.37 (95% CI: 1.00–1.87); Ptrend=0.001] compared to females [highest versus lowest quintile of MQI, HR: 1.27 (95% CI: 0.89–1.83); Ptrend=0.044; Pinteraction=0.005].
Conclusions
The MQI predicts mortality, and may differ between males and females. Additional research examining the MQI is warranted.
doi:10.1016/j.annepidem.2016.07.006
PMCID: PMC5035612  PMID: 27480478
physical function; mobility; aging; physical activity; muscle strength
25.  The Validity of Self-Reported Behaviors: Methods for Estimating Underreporting of Risk Behaviors 
Annals of epidemiology  2016;26(9):612-618.e2.
Purpose
When individuals underreport risk behaviors, data gathered from public health research and practice will underestimate risk. To date, there is little guidance on if or how reports can be adjusted to better reflect true levels of a risk behavior in a given cohort, sample or, by extension, population.
Methods
We develop the underreporting correction factor (UCF), which can be used to correct estimates of the prevalence of a risk behavior using self-report of the behavior and a specific (but not necessarily sensitive) biomarker. The UCF rests on three assumptions: (1) there is no overreporting of the behavior (2) the biomarker can only be acquired if the person engages in the behavior, and (3) the presence of the biomarker does not affect reporting of the behavior. We investigate the sensitivity of the UCF to violation of these assumptions and develop confidence intervals for the UCF and the corrected prevalence of the behavior.
Results
The UCF is most sensitive to the second assumption (biomarker perfectly specific). We apply the UCF to estimates of sexual risk behaviors in various settings using a variety of biomarkers.
Conclusions
Implementation of the UCF corrects for underreporting and more accurately quantifies risk in cohorts.
doi:10.1016/j.annepidem.2016.07.011
PMCID: PMC5035638  PMID: 27566912

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