Sex differences in permanent mandibular tooth development in Macaca nemestrina

Sex differences in dental maturation prior to and during adolescence in 40 unrelated Macaca nemestrina were investigated. The data consisted of mixed longitudinal cephalometric films taken at regular intervals during this period. The mandibular premolars and molars presented the following sequence of initial calcification: M1 P3 (M2 P4) M3. In all stages of development, females tended to mature earlier than males, although only 10 of the 22 stages studied were significantly different. Of these, M3 crown completion, M1 cleft formation, and M3 apical closure were the most reliable for discriminating between sexes. The rate of formation of all teeth, with the exception of M3, was faster in the females than the males, and in both sexes the teeth completed their formation during adolescence. It was suggested that these sex differences in dental maturation may be associated with differences in the timing of hormone secretion, i.e., menarche

Derivation of maternal dietary patterns accounting for regional heterogeneity

Latent class models are often used to characterise dietary patterns. Yet, when subtle variations exist across different sub-populations, overall population patterns can be masked and affect statistical inference on health outcomes. We address this concern with a flexible supervised clustering approach, introduced as Supervised Robust Profile Clustering, that identifies outcome-dependent population-based patterns, while partitioning out subpopulation pattern differences. Using dietary data from the 1997–2011 National Birth Defects Prevention Study, we determine how maternal dietary profiles associate with orofacial clefts among offspring. Results indicate mothers who consume a higher proportion of fruits and vegetables compared to land meats lower the proportion of progeny with orofacial cleft defect

Gastroesophageal reflux disease and odds of head and neck squamous cell carcinoma in North Carolina

Objectives/Hypothesis Exposure to excess gastric acid resulting from gastroesophageal reflux disease, also known as acid reflux or heartburn, might contribute to initiation of head and neck squamous cell carcinoma, particularly laryngeal cancer. Prior epidemiologic studies have reported inconsistent results. We sought to clarify this relationship using an observational study with a larger available sample size and better-characterized exposure information than most prior studies. Study Design A population-based case-control study of head and neck cancer in North Carolina with 1,340 newly diagnosed cases and 1,378 controls matched on age, race, and sex. Methods We used unconditional logistic regression to examine associations between self-reported heartburn and development of overall head and neck cancer as well as development of cancer at specific tumor sites. Subgroup analysis by smoking and alcoholic drinking status was used to make comparisons with a previous study that used a similar study design. Results Overall, an increased odds of head and neck cancer was not associated with either self-reported history of heartburn symptoms (odds ratio = 0.85; 95% confidence interval 0.68, 1.06) or self-reported medical diagnosis of GERD (OR = 0.89; 95% CI 0.71, 1.11). These patterns held for specific tumor sites. For laryngopharyngeal cancer, we did not detect any associations regardless of joint smoking and alcoholic drinking status. Conclusion Gastroesophageal reflux does not appear to play a role in development of head and neck cancer

Joint modeling of survival time and longitudinal outcomes with flexible random effects

Joint models with shared Gaussian random effects have been conventionally used in analysis of longitudinal outcome and survival endpoint in biomedical or public health research. However, misspecifying the normality assumption of random effects can lead to serious bias in parameter estimation and future prediction. In this paper, we study joint models of general longitudinal outcomes and survival endpoint but allow the underlying distribution of shared random effect to be completely unknown. For inference, we propose to use a mixture of Gaussian distributions as an approximation to this unknown distribution and adopt an Expectation–Maximization (EM) algorithm for computation. Either AIC and BIC criteria are adopted for selecting the number of mixtures. We demonstrate the proposed method via a number of simulation studies. We illustrate our approach with the data from the Carolina Head and Neck Cancer Study (CHANCE)

A Bayesian Sensitivity Analysis to Partition Body Mass Index Into Components of Body Composition: An Application to Head and Neck Cancer Survival

Previous studies have suggested a "J-shaped" relationship between body mass index (BMI, calculated as weight (kg)/height (m)2) and survival among head and neck cancer (HNC) patients. However, BMI is a vague measure of body composition. To provide greater resolution, we used Bayesian sensitivity analysis, informed by external data, to model the relationship between predicted fat mass index (FMI, adipose tissue (kg)/height (m)2), lean mass index (LMI, lean tissue (kg)/height (m)2), and survival. We estimated posterior median hazard ratios and 95% credible intervals for the BMI-mortality relationship in a Bayesian framework using data from 1,180 adults in North Carolina with HNC diagnosed between 2002 and 2006. Risk factors were assessed by interview shortly after diagnosis and vital status through 2013 via the National Death Index. The relationship between BMI and all-cause mortality was convex, with a nadir at 28.6, with greater risk observed throughout the normal weight range. The sensitivity analysis indicated that this was consistent with opposing increases in risk with FMI (per unit increase, hazard ratio = 1.04 (1.00, 1.08)) and decreases with LMI (per unit increase, hazard ratio = 0.90 (0.85, 0.95)). Patterns were similar for HNC-specific mortality but associations were stronger. Measures of body composition, rather than BMI, should be considered in relation to mortality risk

The association between meat and fish intake by preparation methods and breast cancer in the Carolina Breast Cancer Study (CBCS)

Purpose: We examined the associations between intake of meat and fish by preparation methods and breast cancer in the Carolina Breast Cancer Study, a racially diverse population-based case–control study. Methods: African American (AA) and European American (EA) women aged 20–74 years with a first diagnosis of invasive or in situ breast cancers were frequency matched by race and age group to controls identified through the North Carolina Division of Motor Vehicles and Medicare lists [AA: 548 cases, 452 controls; EA: 858 cases, 748 controls]. Participants self-reported meat preparation methods and intake frequencies. Adjusted odds ratios (OR) and 95% confidence intervals (CIs) were calculated using multivariable logistic regression adjusted for age, race, alcohol intake, body mass index, family income, lactation, marital status, use of oral contraceptives, postmenopausal hormone use, smoking status, and offsets. Results: Positive associations with breast cancer were observed for intakes of grilled/barbecued hamburger (≥ once/week, OR: 1.28; 95% CI 1.01, 1.63), and pan-fried/oven-broiled beef steak (≥ once/week, OR: 1.36; 95% CI 1.08, 1.72). Inverse associations were observed for pan-fried fish (≥ once/week, OR: 0.77; 95% CI 0.60, 0.98), and for grilled/ barbecued pork chops (> 0 time/week OR: 0.81, 95% CI 0.68, 0.97). Associations tended to be stronger among EA women than among AA women. Conclusion: More frequent consumption of beef prepared with high temperature methods was associated with higher odds of breast cancer while more frequent consumption of pan-fried fish or grilled/barbecued pork chops was associated with lower odds of breast cancer

Epidemiology: Back to the Future

In 2018, the Society for Epidemiologic Research and its partner journal, the American Journal of Epidemiology, assembled a working group to develop a set of papers devoted to the "future of epidemiology." These 14 papers covered a wide range of topic areas and perspectives, from thoughts on our profession, teaching, and methods to critical areas of substantive research. The authors of those papers considered current challenges and future opportunities for research and education. In light of past commentaries, 4 papers also include reflections on the discipline at present and in the future

Centered Partition Processes: Informative Priors for Clustering (with Discussion)

There is a very rich literature proposing Bayesian approaches for clustering starting with a prior probability distribution on partitions. Most approaches assume exchangeability, leading to simple representations in terms of Exchangeable Partition Probability Functions (EPPF). Gibbs-type priors encompass a broad class of such cases, including Dirichlet and Pitman-Yor processes. Even though there have been some proposals to relax the exchangeability assumption, allowing covariate-dependence and partial exchangeability, limited consideration has been given on how to include concrete prior knowledge on the partition. For example, we are motivated by an epidemiological application, in which we wish to cluster birth defects into groups and we have prior knowledge of an initial clustering provided by experts. As a general approach for including such prior knowledge, we propose a Centered Partition (CP) process that modifies the EPPF to favor partitions close to an initial one. Some properties of the CP prior are described, a general algorithm for posterior computation is developed, and we illustrate the methodology through simulation examples and an application to the motivating epidemiology study of birth defects

Examining determinants of geographic variation in colorectal cancer mortality in North Carolina: A spatial analysis approach

Purpose: A recent study using national data from 2000 to 2009 identified colorectal cancer (CRC) mortality “hotspots” in 11 counties of North Carolina (NC). In this study, we used more recent, state-specific data to investigate the county-level determinants of geographic variation in NC through a geospatial analytic approach. Method: Using NC CRC mortality data from 2003 to 2013, we first conducted clustering analysis to confirm spatial dependence. Spatial economic models were then used to incorporate spatial structure to estimate the association between determinants and CRC mortality. We included county-level data on socio-demographic characteristics, access and quality of healthcare, behavioral risk factors (CRC screening, obesity, and cigarette smoking), and urbanicity. Due to correlation among screening, obesity and quality of healthcare, we combined these factors to form a cumulative risk group variable in the analysis. Results: We confirmed the existence of spatial dependence and identified clusters of elevated CRC mortality rates in NC counties. Using a spatial lag model, we found significant interaction effect between CRC risk groups and socioeconomic deprivation. Higher CRC mortality rates were also associated with rural counties with large towns compared to urban counties. Conclusion: Our findings depicted a spatial diffusion process of CRC mortality rates across NC counties, demonstrated intertwined effects between SES deprivation and behavioral risks in shaping CRC mortality at area-level, and identified counties with high CRC mortality that were also deprived in multiple factors. These results suggest interventions to reduce geographic variation in CRC mortality should develop multifaceted strategies and work through shared resources in neighboring areas

Differences in pre-pregnancy diet quality by occupation among employed women

Objective: Maternal risk factors for pregnancy outcomes are known to vary by employment status. We evaluated whether pre-pregnancy diet quality varies by occupation in a population-based sample.Design: We analysed interview data from 7341 mothers in a national case-control study of pregnancy outcomes. Self-reported job(s) held during the 3 months before pregnancy were classified using Standard Occupational Classification (SOC) codes. Usual diet in the year before conception was assessed with a semi-quantitative FFQ and evaluated using the Diet Quality Index for Pregnancy (DQI-P). Using logistic regression, we calculated adjusted OR and 95 % CI to estimate associations between low diet quality (defined as the lowest quartile of DQI-P scores) and occupation types.Setting: The National Birth Defects Prevention Study: Arkansas, California, Georgia, Iowa, Massachusetts, North Carolina, New Jersey, New York, Texas, Utah.Participants: Employed mothers of infants born between 1997 and 2011.Results: No occupation was strongly associated with low diet quality. Moderate but relatively imprecise associations were observed for women employed in management (OR: 1·3; 95 % CI: 1·1, 1·7); arts, design, entertainment, sports and media (OR: 1·4; 95 % CI: 0·9, 2·1); protective service (OR 1·3; 95 % CI: 0·7, 2·5) and farming, fishing, and forestry occupations (OR: 0·5; 95 % CI: 0·2, 1·1).Conclusions: Our analyses suggest that women in certain occupations may have lower diet quality in the months before pregnancy. Further research is needed to determine whether certain occupations could benefit from interventions to improve diet quality in the workplace for women of reproductive age