Obesity and occupation in Thailand: using a Bayesian hierarchical model to obtain prevalence estimates from the National Health Examination Survey.
Obesity and occupation in Thailand: using a Bayesian hierarchical model to obtain prevalence estimates from the National Health Examination Survey.
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DOI：
10.1186/s12889-021-10944-0
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发表时间：
2021-05-13
影响因子：
4.5
通讯作者：
Sunpuwan M
中科院分区：
文献类型：
--
作者：
Rittirong J;Bryant J;Aekplakorn W;Prohmmo A;Sunpuwan M
与许多发展中国家一样，泰国的肥胖率迅速上升，职业结构也发生了迅速变化。这两种趋势似乎是相关的，久坐不动的职业会导致肥胖率增加。全国健康检查调查数据包含有关肥胖和社会经济状况的信息，有助于理清这种关系，但由于样本量较小，分析具有挑战性。本文利用 2009 年全国健康体检调查中 10,127 名 20-59 岁受访者的数据探讨了职业与肥胖之间的关系。肥胖是通过腰围来测量的。建模是使用称为后分层多重回归 (MRP) 的方法进行的。我们使用贝叶斯分层模型构建按年龄、性别、教育程度、城乡居住地、地区和职业分类的患病率估计值，并使用人口普查人口权重进行汇总。贝叶斯分层模型旨在防止过度拟合和错误发现，这在像本研究这样的探索性研究中尤为重要。职业的总体久坐性质与肥胖之间没有明确的关系。相反，肥胖似乎因职业而异。例如，职业女性和农业或渔业工人的肥胖率相对较低。贝叶斯分层模型加上后分层为使用调查了解复杂的健康问题提供了新的可能性。
Like many developing countries, Thailand has experienced a rapid rise in obesity, accompanied by a rapid change in occupational structure. It is plausible that these two trends are related, with movement into sedentary occupations leading to increases in obesity. National health examination survey data contains information on obesity and socioeconomic conditions that can help untangle the relationship, but analysis is challenging because of small sample sizes. This paper explores the relationship between occupation and obesity using data on 10,127 respondents aged 20–59 from the 2009 National Health Examination Survey. Obesity is measured using waist circumference. Modelling is carried out using an approach known as Multiple Regression with Post-Stratification (MRP). We use Bayesian hierarchical models to construct prevalence estimates disaggregated by age, sex, education, urban-rural residence, region, and occupation, and use census population weights to aggregate up. The Bayesian hierarchical model is designed to protect against overfitting and false discovery, which is particularly important in an exploratory study such as this one. There is no clear relationship between the overall sedentary nature of occupations and obesity. Instead, obesity appears to vary occupation by occupation. For instance, women in professional occupations, and men who are agricultural or fishery workers, have relatively low rates of obesity. Bayesian hierarchical models plus post-stratification offers new possibilities for using surveys to learn about complex health issues.
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作者：
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DOI：
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