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2013年巴西道路交通伤害及其决定因素的地区差异

Regional disparities in road traffic injuries and their determinants in Brazil, 2013.

作者信息

Morais Neto Otaliba Libanio, Andrade Ana Lúcia, Guimarães Rafael Alves, Mandacarú Polyana Maria Pimenta, Tobias Gabriela Camargo

机构信息

Departamento de Saúde Coletiva. Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Rua 235, S/N, Setor Universitário, Goiânia, Goiás, Cep: 74605-050, Brazil.

Mestrado do Programa de Pós-Graduação em Enfermagem, Universidade Federal de Goiás, Rua 227 Qd 68, S/N - Setor Leste Universitário, Goiânia, Goiás, CEP: 74605-080, Brazil.

出版信息

Int J Equity Health. 2016 Nov 17;15(1):142. doi: 10.1186/s12939-016-0433-6.

DOI:10.1186/s12939-016-0433-6
PMID:27852263
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5112733/
Abstract

BACKGROUND

In recent decades middle-income countries have experienced a rapid increase in the number of cars and motorcycles. Increased deaths and hospitalizations due to road traffic injuries (RTI) has been observed in several countries as a result. In this study we assessed the determinants of RTIs in Brazil by mode of transportation and compared differences in RTI rates among macro-regions.

METHODS

We used data from the National Health Survey (NHS) conducted in 2013 by the Brazilian Institute of Geography and Statistics and the Ministry of Health. NHS is a comprehensive household survey which includes a representative sample (N = 60,198) of individuals aged 18 years or older. The prevalence and determinants of RTI were estimated according to different modes of transport (car/van, motorcycle, and other) and regions of the country. Bivariate and multivariable logistic regression models were applied to assess crude and adjusted odds ratios, respectively, and their 95 % CI for RTI determinants.

RESULTS

The prevalence of RTI for the Southeast, South, Central-West, Northeast and North regions of Brazil was 2.4 %, 2.9 %, 4.4 %, 3.4 % and 4.8 %, respectively, pointing to important differences among regions. High percentages of motorcyclists were observed in the Northeast and North regions. For motorcyclists, factors associated with RTIs were being male (OR = 2.6;95 % CI:2.3;3.0), aged 18-29 (OR = 3.2; 95 % CI:2.7;3.8) and 30-39 years (OR = 2.0;95 % CI:1.7;2.5), black (OR = 1.4;95 % CI:1.1;1.7), having elementary educational (OR = 1.5;95 % CI:1.1;1.9), reporting binge drinking behavior (OR = 1.3;95 % CI:1.1;1.5), and living in the Central-West (OR = 2.0;95 % CI:1.6;2.5), Northeast (OR = 1.8;95 % CI:1.5;2.1) and North (OR = 2.0;95 % CI:1.6; 2.5) regions of the country. The independent variables associated with RTI for car/van occupants were being male (OR = 1.7;95 % CI:1.4;2.1), aged 18-29 (OR = 1.5;95 % CI:1.1;2.0) and 30-39 years (OR = 2.5;95 % CI:1.9;3.2), reporting binge drinking behavior (OR = 2.0;95 % CI:1.6;2.5) and living in the South region (OR = 1.6;95 % CI:1.3;2.1).

CONCLUSIONS

There were considerable regional disparities in RTI rates across Brazil's regions. Motorcyclists contributed to the high RTI rates in these regions as did demographic factors and behaviors such as alcohol use. These findings can help guide interventions to reduce the burden of RTIs in Brazil.

摘要

背景

近几十年来,中等收入国家的汽车和摩托车数量迅速增加。因此,在一些国家,因道路交通伤害(RTI)导致的死亡和住院人数有所上升。在本研究中,我们按交通方式评估了巴西道路交通伤害的决定因素,并比较了各宏观区域道路交通伤害发生率的差异。

方法

我们使用了巴西地理与统计研究所和卫生部于2013年进行的全国健康调查(NHS)的数据。NHS是一项综合性家庭调查,包括一个具有代表性的样本(N = 60198),样本为18岁及以上的个体。根据不同的交通方式(汽车/货车、摩托车和其他)和国家地区,估计道路交通伤害的患病率和决定因素。应用双变量和多变量逻辑回归模型分别评估道路交通伤害决定因素的粗比值比和调整比值比及其95%置信区间。

结果

巴西东南部、南部、中西部、东北部和北部地区的道路交通伤害患病率分别为2.4%、2.9%、4.4%、3.4%和4.8%,表明各地区存在重要差异。在东北部和北部地区,骑摩托车者的比例较高。对于骑摩托车者,与道路交通伤害相关的因素包括男性(比值比=2.6;95%置信区间:2.3;3.0)、年龄在18 - 29岁(比值比=3.2;95%置信区间:2.7;3.8)和30 - 39岁(比值比=2.0;95%置信区间:1.7;2.5)、黑人(比值比=1.4;95%置信区间:1.1;1.7)、接受小学教育(比值比=1.5;95%置信区间:1.1;1.9)、报告有暴饮行为(比值比=1.3;95%置信区间:1.1;1.5),以及居住在该国的中西部(比值比=2.0;95%置信区间:1.6;2.5)、东北部(比值比=1.8;95%置信区间:1.5;2.1)和北部(比值比=2.0;95%置信区间:1.6;2.5)地区。与乘坐汽车/货车者道路交通伤害相关的自变量包括男性(比值比=1.7;95%置信区间:1.4;2.1)、年龄在18 - 29岁(比值比=1.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc62/5112733/b3d5488b2253/12939_2016_433_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc62/5112733/b3d5488b2253/12939_2016_433_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc62/5112733/b3d5488b2253/12939_2016_433_Fig1_HTML.jpg

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