Machine learning prediction of combat basic training injury from 3D body shape images.

INTRODUCTION: Athletes and military personnel are both at risk of disabling injuries due to extreme physical activity. A method to predict which individuals might be more susceptible to injury would be valuable, especially in the military where basic recruits may be discharged from service due to injury. We postulate that certain body characteristics may be used to predict risk of injury with physical activity. METHODS: US Army basic training recruits between the ages of 17 and 21 (N = 17,680, 28% female) were scanned for uniform fitting using the 3D body imaging scanner, Human Solutions of North America at Fort Jackson, SC. From the 3D body imaging scans, a database consisting of 161 anthropometric measurements per basic training recruit was used to predict the probability of discharge from the US Army due to injury. Predictions were made using logistic regression, random forest, and artificial neural network (ANN) models. Model comparison was done using the area under the curve (AUC) of a ROC curve. RESULTS: The ANN model outperformed two other models, (ANN, AUC = 0.70, [0.68,0.72], logistic regression AUC = 0.67, [0.62,0.72], random forest AUC = 0.65, [0.61,0.70]). CONCLUSIONS: Body shape profiles generated from a three-dimensional body scanning imaging in military personnel predicted dischargeable physical injury. The ANN model can be programmed into the scanner to deliver instantaneous predictions of risk, which may provide an opportunity to intervene to prevent injury.

Role of persistent cascades in diffusion.

We define a structural property of real-world large-scale communication networks consisting of the recurring patterns of communication among individuals, which we term persistent cascades. Using methods of inexact tree matching and agglomerative clustering, we group these patterns into classes which we claim represent some underlying way in which individuals tend to disseminate information. We extend methods from epidemic modeling to offer a way to analytically model this recurring structure in a random network, and comparing to the data, we find that the real cascading structure is significantly larger and more recurrent than the random model. We find that the cascades reveal a habitual hierarchy of spreading, alternative roles in weekday vs weekend spreading, and the existence of hidden spreaders. Finally, we show that cascade membership increases the likelihood of receiving information spreading through the network through simulation on the real order of communication events.

A machine learning approach relating 3D body scans to body composition in humans.

A long-standing question in nutrition and obesity research involves quantifying the relationship between body fat and anthropometry. To date, the mathematical formulation of these relationships has relied on pairing easily obtained anthropometric measurements such as the body mass index (BMI), waist circumference, or hip circumference to body fat. Recent advances in 3D body shape imaging technology provides a new opportunity for quickly and accurately obtaining hundreds of anthropometric measurements within seconds, however, there does not yet exist a large diverse database that pairs these measurements to body fat. Herein, we leverage 3D scanned anthropometry obtained from a population of United States Army basic training recruits to derive four subpopulations of homogenous body shape archetypes using a combined principal components and cluster analysis. While the Army database was large and diverse, it did not have body composition measurements. Therefore, these body shape archetypes were paired to an alternate smaller sample of participants from the Pennington Biomedical Research Center in Baton Rouge, LA that were not only similarly imaged by the same 3D scanning machine, but also had concomitant measures of body composition by dual-energy X-ray absorptiometry body composition. With this enhanced ability to obtain anthropometry through 3D scanning quickly of large populations, our machine learning approach for pairing body shapes from large datasets to smaller datasets that also contain state-of-the-art body composition measurements can be extended to pair other health outcomes to 3D body shape anthropometry.

A survey of the knowledge, attitudes and practices on Zika virus in new York City.

BACKGROUND: Over 900 travel-associated Zika virus cases have been identified in New York City (NYC), New York. A survey was administered in NYC adapted from the Knowledge, Attitudes, and Practices (KAP) survey on Zika virus developed by the World Health Organization (WHO). METHODS: A standardized, self-administered, anonymous questionnaire was administered to a convenience sample in Manhattan and the Bronx from June 30th, 2016 to October 21st, 2016. Responses were grouped into six domains based on the content and structure of the questions and were summarized using descriptive statistics or converted into a continuous knowledge score and assessed for associations with pregnancy status and travel history using linear regression. RESULTS: There were 224 respondents with a mean age of 33 (SD ± 11.6) with 77% (170/224) female and 24% (51/224) pregnant. The majority (98% (213/217)) were unable to identify all of the symptoms associated with acute Zika virus infection and all modes of transmission (97% (213/219)). Most participants (85% (187/219)) identified mosquitoes as a mode of transmission. 95% (116/122) reported an association between Zika virus and microcephaly. The most concerning aspect of Zika virus in 46% (91/200) was the risk of disabilities to babies, and risk of sexual transmission (25% (49/200)). When asked what precautions pregnant persons should to reduce the risk of transmission when traveling to a Zika endemic region, only 27% (50/185) identified using condoms during intercourse or refraining from intercourse while pregnant. Knowledge of Zika transmission is significantly positively associated with pregnancy status, but not with travel history. CONCLUSION: Our results indicate an overall poor understanding of Zika virus symptoms and possible complications, transmission modes, and current recommended prevention guidelines. Pregnancy is positively associated with Knowledge of Zika Transmission, but not other knowledge scores. Reported travel history to Zika endemic regions is not significantly associated with Zika knowledge. There is a need for implementing future public health interventions that particularly focus on protection against Zika transmission, that Zika is sexually transmitted, and risks that the Guillain-Barré Syndrome poses a risk to adults.

Early school-age outcomes of late preterm infants.

OBJECTIVE: Late preterm infants represent a significant portion of preterm deliveries. Until recently, these infants have received little attention because of assumptions that they carry minimal risk for long-term morbidities. The purpose of this study was to compare prekindergarten and kindergarten outcomes among healthy late preterm infants, 34 0/7 to 36 6/7 weeks' gestation at birth, and healthy term infants, 37 0/7 to 41 6/7 weeks' gestation at birth. METHODS: The study sample consisted of singleton infants who were born in Florida between January 1, 1996, and August 31, 1997, with a gestational age between 34 and 41 weeks (N = 161804) with a length of stay < or =72 hours. Seven early school-age outcomes were analyzed. Outcomes were adjusted for 15 potential confounding maternal and infant variables. Unadjusted and adjusted relative risk with 95% confidence interval was estimated for each outcome by using Poisson regression modeling. RESULTS: Risk for developmental delay or disability was 36% higher among late preterm infants compared with term infants. Risk for suspension in kindergarten was 19% higher for late preterm infants. The remaining 4 outcomes, disability in prekindergarten at 3 and 4 years of age, exceptional student education, and retention in kindergarten, all carried a 10% to 13% increased risk among late preterm infants. The assessment "not ready to start school" was borderline significant. CONCLUSIONS: This study suggests that healthy late preterm infants compared with healthy term infants face a greater risk for developmental delay and school-related problems up through the first 5 years of life.

Length of prenatal participation in WIC and risk of delivering a small for gestational age infant: Florida, 1996-2004.

OBJECTIVE: To assess the association between length of prenatal participation in WIC and a marker of infant morbidity. By focusing on small for gestational age, we consider one of the possible pathways through which prenatal nutrition affects fetal growth. DESIGN/METHODS: The study sample consists of 369,535 matched mother-infant pairs drawn from all singleton live births in Florida hospitals from 1996 to 2004. All subjects received WIC and Medicaid-funded prenatal services during pregnancy. We controlled for selection bias on observed variables using a generalized propensity scoring approach and performed separate analyses by gestational age category to control for simultaneity bias. RESULTS: Ten percent increase in the percent of time in WIC was associated with 2.5% decrease (95% CI: 2.1-3.0%) in the risk of a full-term an SGA infant. The risk was also significantly decreased for very preterm and late preterm infants (29-33 and 34-36 weeks gestation) but not for extremely preterm infants (23-28 weeks gestation). CONCLUSIONS: The observed small negative dose response relationship between percent of pregnancy spent in WIC and fetal growth restriction implies that longer participation in the program confers a small measure of protection against delivering an SGA infant.

Racial and gender differences in the viability of extremely low birth weight infants: a population-based study.

OBJECTIVE: The purpose of this study is to provide a race- and gender-specific model for predicting 1-year survival rates for extremely low birth weight (ELBW) infants by using population-based data. METHODS: Birth and death certificates were analyzed for all children (N = 5076) with birth weights between 300 g and 1000 g who were born in Florida between 1996 and 2000. Semiparametric, multivariate, logistic regression analysis was used to model 1-year survival probabilities as a function of birth weight, gestational age, mother's race, and infant's gender. Estimated survival rates among different race/gender groups were compared by using odds ratios (ORs). RESULTS: One-year survival rates for 5076 ELBW infants born between 1996 and 2000 did not change during the 5-year period (60-62%). The survival rate at < or = 500 g was < or = 14% (n = 716). Survival rates at 501 to 600 g and 601 to 700 g were 36% and 62%, respectively. The survival rate reached > 85% for infants of > 800 g. Modeling indicated a survival advantage for female infants, compared with male infants (OR: 1.7; 95% confidence interval: 1.5-1.9), and for black infants, compared with white infants (OR: 1.3; 95% confidence interval: 1.1-1.5). Black female infants had 2.1 greater odds of survival than did white male infants. CONCLUSIONS: This population-based study highlights the significant race and gender differences in 1-year survival rates for ELBW infants, as well as the interactions of these 2 factors. These findings can assist obstetricians and neonatologists not only in the care of ELBW infants but also in frank discussions with families.

The risk of birth defects in multiple births: a population-based study.

OBJECTIVES: To determine if multiple births have higher risks of birth defects compared to singletons and to identify types of birth defects that occur more frequently in multiple births, controlling for seven sociodemographic and health-related variables. METHODS: A retrospective cohort study was conducted of all resident live births in Florida during 1996-2000 using data from a population-based surveillance system. Birth defects were defined as in the 9th edition of the International Classification of Diseases-Clinical Modification (ICD-9-CM) code for the 42 reportable categories in the Centers for Disease Control and Prevention (CDC) Birth Defects Registry list and eight major birth defects classifications. Relative risks (RR) before and after adjusting for control variables and 95% confidence intervals (95% CI) were calculated. The control variables included mother's race, age, previous adverse pregnancy experience, education, Medicaid participation during pregnancy, infant's sex and number of siblings. RESULTS: This study included 972,694 live births (27,727 multiple births and 944,967 singletons). Birth defects prevalence per 10,000 live births was 358.50 for multiple births and 250.54 for singletons. After adjusting for control variables, multiple births had a 46% increased risk of birth defects compared to singletons. Higher risks were found in 23 of 40 birth defects for multiple births. Five highest adjusted relative risks for birth defects among multiple births were: anencephalus, biliary atresia, hydrocephalus without spina bifida, pulmonary valve atresia and stenosis, and bladder exstrophy. Increased risks were also found in 6 out of 8 major birth defects classifications. CONCLUSIONS: Multiple births have increased risks of birth defects compared to singletons.

Maternal and infant factors associated with excess kindergarten costs.

OBJECTIVE: To estimate the excess educational costs at kindergarten from infant and maternal factors that are reported routinely at birth. METHODS: Birth and school records were analyzed for all children who were born in Florida between September 1, 1990, and August 31, 1991, and entered kindergarten from 1996 through 1999 (N = 120,554). Outcome measure was cost to state, derived from base allocation for students in regular classrooms plus multiplier weights for those who were assigned to 8 mutually exclusive special education categories or who repeated kindergarten. RESULTS: More than one quarter of the study cohort was found to be assigned to special education classes at kindergarten. Regression model estimates indicated that children who were born at <1000 g (n = 380) generated 71% higher costs in kindergarten than children who were born at >or=2500 g. Children who were born at 1000 to 1499 g (n = 839) generated 49% higher costs. Other birth conditions, independent of birth weight, were associated with higher kindergarten costs: family poverty (31%), congenital anomalies (29%), maternal education less than high school (20%), and no prenatal care (14%). Because of their prevalence, family poverty and low maternal education accounted for >75% of excess kindergarten costs. If 9% of infants who weighed between 1500 and 2499 g (n = 1027) could be delivered at 2500 g, then the state of Florida potentially could save 1 million dollars in kindergarten costs. Savings of a similar magnitude might be achieved if 3% of mothers who left school without a diploma (n = 1528) were to graduate. CONCLUSIONS: Any policy recommendation aimed at reducing education costs in kindergarten must take into consideration 3 factors: the prevalence of risk conditions whose amelioration is desired, the potential cost savings associated with reducing those conditions, and the costs of amelioration. Projecting these costs from information that is available at birth can assist school districts and state agencies in allocating resources.