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  • ISSN: 2378-9328
    Volume 2, Issue 1
    Research Article
    Jiajun Wen1, Ge Lin2 and KM Islam3*
    Abstract:
    Background: Lung cancer is one of the leading cancers in both incidence and mortality in Nebraska. We investigated how social determinants were associated with the stage at diagnosis and survival time for Nebraska non-small cell lung cancer patients.
    Methods: A total of 12,821 NSCLC cases diagnosed between 1995 and the end of 2012 were identified using the Nebraska Cancer Registry database linked with the census tract poverty level. General logistic regression model was used to analyze the relationship between social factors and stage at diagnosis, and Cox proportional hazard model was used to investigate the adjusted effect of social factors on lung cancer survival.
    Results: Among 12,821 lung cancer patients, 2,954 (23.04%) were diagnosed in situ or at localized stages and 9,867 (76.96%) were diagnosed at more advanced stages. Male gender, younger age, Hispanic origin, rural residency and being single were associated with increased ORs of being diagnosed at advanced stages. In survival analysis, patients being single at the time of diagnosis were related with 1.23 time's greater hazard of death, compared to patients who were married. The adjusted hazard ratio was also associated with the type of insurance used (p < 0.0001).
    Conclusions: Both stage at diagnosis and survival time for NSCLC were associated with different social determinants. Health care providers should provide more emphasis on educating minority populations, patients living alone, and patients with limited insurance coverage about early diagnosis and follow-up care of lung cancer.
    Jiaqing Chen1, Renfu Wang2* and Yangxin Huang3
    Abstract: Spatial data arise frequently in econometric studies and it is a common practice to analyze such data with spatial autoregressive (SAR) models. This paper proposes a two-step Bayesian approach for inference in the semiparametric spatial autoregressive (SPSAR) model, including the cases for mixed data. With proper transformation, the estimation problem under SPSAR model is conducted into two steps. In the first step, a transformed SAR model is offered to fit the utilized data using Bayesian method, and then the residuals of the transformed SAR model are smoothed via nonparametric kernel estimator. In the second step, we substitute the kernel estimator into the SPSAR model to recalculate the parameters. Since the likelihood function of spatial autoregressive model is so complex to get an analytic solution, the Markov chain Monte Carlo (MCMC) algorithm is adopted to implement Bayesian inferential approach. A simulation study is conducted to assess the performance of the proposed method, and a real example is analyzed with the proposed method.
    Research Article
    Patrick G. Hogan1, Carey-Ann D. Burnham1,2, Lauren N. Singh1, Carol A. Patrick1, Christian Lukas J1, Jeffrey W. Wang1, Victoria J. Fraser3 and Stephanie A. Fritz1*
    Abstract: We evaluated a variety of methods to recover S. aureus from inanimate surfaces. Two contact agar plates and three swab sampling methods were tested on porous and non-porous surfaces and bar soap. The cost and ease of use of each method was also evaluated. S. aureus was recovered using all methods on both porous and non-porous surfaces. S. aureus could not be detected on three of four brands of soap.
    Short Communication
    Maxime Jeanjean1,2*, Kihal Wahida1,2, Cindy Padilla1,2, Esther Kai-Chieh Chen1 and Severine Deguen1,2
    Abstract: Congenital abnormalities (CAs) remain a major cause of stillbirth and neonatal mortality. The literature has shown that congenital malformations are suggested to have multifactorial determinants, including environmental exposures and socioeconomic patterns. Moreover, since a decade, combined effects of environmental and socioeconomic characteristics are suspected to have an impact on the risk of congenital anomalies. Three mechanisms have been proposed in the literature suggesting the possible combined effect of the social health inequalities and the environmental exposures. This commentary presents the role of the neighbourhood deprivation in the adverse effect of air pollution on congenital anomalies. Both air pollution and neighbourhood deprivation have been reported in the literature to increase the risk of congenital abnormalities.
    Masanari Watanabe1*, Jun Kurai1, Hisashi Noma2, Tetsushi Watanabe3, Sayaka Minato4, Hiroyuki Sano5, Futoshi Okada6, Akira Yamasaki1 and Eiji Shimizu1
    Abstract: The objective of this study was to investigate the influence of metals bound to airborne particles on pulmonary function of schoolchildren. Morning Peak Expiratory Flow (PEF) was measured daily in 399 schoolchildren, aged between eight and nine, from April to May 2012, and the levels of Ca, Fe, K, Mg, Mn, and Ti (natural metals) and Cd, Cu, Pb, V and Zn (anthropogenic metals) bound to airborne particles were monitored. A linear mixed model was used to estimate the association of PEF with metals bound to airborne particles. Natural and anthropogenic metals (except for Ba, Ni and Na) bound to airborne particles had significant negative associations with PEF. Metals bound to airborne particles may decrease pulmonary function of children.
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