ABSTRACT. Objective: This study examines the growth of neighborhood disorder and subsequent marijuana use among urban adolescents transitioning into young adulthood. Method: Data are derived from a longitudinal sample of 434 predominately African American 12th graders followed-up at 2 years after high school. The data are rich in repeated measures documenting substance use and misuse and neighborhood characteristics. Growth mixture modeling was used to examine how neighborhood disorder trajectories, measured through the presence of abandoned buildings on the blocks where participants reside, infl uence subsequent drug use beginning in late adolescence and into young adulthood. Results: A four-class solution characterizing neighborhood growth was selected as the fi nal model and included rapidly improving, slightly improving, always-good, and deteriorating neighborhoods. Young adults living in neighborhoods that had been deteriorating over time were 30% more likely to use marijuana 2 years after high school than adolescents living in always-good neighborhoods (odds ratio = 1.30, p = .034). There was no relationship between living in a neighborhood that was improving and marijuana use. Conclusions: This study identifi ed a salient and malleable neighborhood characteristic, abandoned housing, which predicted elevated risk for young-adult marijuana use. This research supports environmental strategies that target abandoned buildings as a means to improve health and health behaviors for community residents, particularly young-adult substance use. (J. Stud. Alcohol Drugs, 72,

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PurposeThis study estimated the economic burden of cancer in Korea during 2000-2010 by cancer site, gender, age group, and cost component.Materials and MethodsData came from national health insurance claims data and information from Statistics Korea. Based on the cost of illness method, this study calculated direct, morbidity and mortality cost of cancer in the nation during 2000-2010 by cancer site, gender, and age group.ResultsWith an average annual growth rate of 8.9%, the economic burden of cancer in Korea increased from 11,424 to 20,858 million US$ (current US dollars) during 2000-2010. Colorectal, thyroid, and breast cancers became more significant during the period, i.e., the 5th/837, the 11th/257, and the 7th/529 in 2000 to the 3rd/2,210, the 5th/1,724, and the 6th/1,659 in 2010, respectively (rank/amount in million US$ for the total population). In addition, liver and stomach cancers were prominent during the period in terms of the same measures, i.e., the 1st/2,065 and the 2nd/2,036 in 2000 to the 1st/3,114 and the 2nd/3,046 in 2010, respectively. Finally, the share of mortality cost in the total burden dropped from 71% to 51% in Korea during 2000-2010, led by colorectal, thyroid, breast, and prostate cancers during the period. These results show that the economic burden of cancer in Korea is characterized by an increasing importance of chronic components.ConclusionIncorporation of distinctive epidemiological, sociocultural contexts into Korea’s cancer control program, with greater emphasis on primary prevention such as sodium-controlled diet and hepatitis B vaccination, may be needed.

Background Little research based on the artificial neural network (ANN) is done on preterm birth (spontaneous preterm labor and birth) and its major determinants. This study uses an ANN for analyzing preterm birth and its major determinants. Methods Data came from Anam Hospital in Seoul, Korea, with 596 obstetric patients during March 27, 2014 - August 21, 2018. Six machine learning methods were applied and compared for the prediction of preterm birth. Variable importance, the effect of a variable on model performance, was used for identifying major determinants of preterm birth. Analysis was done in December, 2018. Results The accuracy of the ANN (0.9115) was similar with those of logistic regression and the random forest (0.9180 and 0.8918, respectively). Based on variable importance from the ANN, major determinants of preterm birth are body mass index (0.0164), hypertension (0.0131) and diabetes mellitus (0.0099) as well as prior cone biopsy (0.0099), prior placenta previa (0.0099), parity (0.0033), cervical length (0.0001), age (0.0001), prior preterm birth (0.0001) and myomas & adenomyosis (0.0001). Conclusion For preventing preterm birth, preventive measures for hypertension and diabetes mellitus are required alongside the promotion of cervical-length screening with different guidelines across the scope/type of prior conization.

This study aimed to use artificial intelligence to determine whether biological and psychosocial factors, such as stress, socioeconomic status, and working conditions, were major risk factors for temporomandibular disorders (TMDs). Data were retrieved from the fourth Korea National Health and Nutritional Examination Survey (2009), with information concerning 4744 participants’ TMDs, demographic factors, socioeconomic status, working conditions, and health-related determinants. Based on variable importance observed from the random forest, the top 20 determinants of self-reported TMDs were body mass index (BMI), household income (monthly), sleep (daily), obesity (subjective), health (subjective), working conditions (control, hygiene, respect, risks, and workload), occupation, education, region (metropolitan), residence type (apartment), stress, smoking status, marital status, and sex. The top 20 determinants of temporomandibular disorders determined via a doctor’s diagnosis were BMI, age, household income (monthly), sleep (daily), obesity (subjective), working conditions (control, hygiene, risks, and workload), household income (subjective), subjective health, education, smoking status, residence type (apartment), region (metropolitan), sex, marital status, and allergic rhinitis. This study supports the hypothesis, highlighting the importance of obesity, general health, stress, socioeconomic status, and working conditions in the management of TMDs.