Diabetes and Tuberculosis Pilot

筛查结核分枝杆菌感染的高风险发展为临床结核病（TB）是疾病控制和预防中心（CDC）控制结核病在美国传播的关键策略。这在美国/墨西哥边境尤其重要，与美国全国平均水平相比，社会经济和人口因素的融合导致结核病负担更高。该地区也有高患病率的II型糖尿病（DB），这一直是众所周知的易患活动性结核病。根据这些信息，我们假设DB有助于结核病的负担在西班牙裔人口从四个德克萨斯州县沿着墨西哥-美国边境。该试点项目将分析下格兰德河谷（LRGV）的四个县：伊达尔戈、卡梅隆、威利西和 斯塔尔2001年期间，将使用ICD 9编码对德克萨斯州医院出院病例和对照进行二次分析。非条件多元Logistic回归分析将用于评估结核病与暂定相关因素的关系。健康生产函数将估计，以及使用无条件多元逻辑回归。该项目的具体目标是： 目的1：确定LRGV中西班牙裔人DB和TB的关联程度 目标二：确定结核病与其相关风险因素（除DB外）之间的关联强度，重点是潜在的医疗条件。 目标3：估计卫生生产函数，确定结核病和DB的相关社会经济指标。

Screening for Mycobacterium tuberculosis infection in those at high risk for developing clinical tuberculosis (TB) is a key strategy of the Centers for Disease Control and Prevention (CDC) to control the spread of TB in the US. This is particularly important at the US/Mexico border, where converging socioeconomic and demographic factors contribute to the higher burden of TB when compared to the US national average. This region also has high prevalence of type II diabetes (DB), which has long been known to predispose to active tuberculosis. Based on this information, we hypothesize that DB contributes to the burden of TB in the Hispanic population from four Texan counties along the Mexican-American border. Four counties in the Lower Rio Grande Valley (LRGV) will be analyzed in this pilot project: Hidalgo, Cameron, WilIacy and Starr. A secondary analysis of the Texas hospital discharges during 2001 will be implemented using ICD 9 codes for case and control selection. Unconditional multiple logistic regression analysis will be used to evaluate the relationship between tuberculosis and tentative associated factors. Health production functions will be estimated, using unconditional multiple logistic regression as well. The specific aims of the project are: Aim 1: Determine the degree of association of DB and TB in Hispanics in the LRGV Aim 2: Determine the strength of the association between TB and its associated risk factors (besides DB), with emphasis on underlying medical conditions. Aim 3: Estimate health production function that will identify relevant socio-economic indicators of TB and DB.