Socioeconomic inequalities in hypertension in Kenya: a decomposition analysis of 2015 Kenya STEPwise survey on non-communicable diseases risk factors.
Socioeconomic inequalities in hypertension in Kenya: a decomposition analysis of 2015 Kenya STEPwise survey on non-communicable diseases risk factors.
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肯尼亚高血压的社会经济不平等：2015年肯尼亚的分解分析逐步调查了非通信疾病的危险因素。
DOI：
10.1186/s12939-020-01321-1
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发表时间：
2020-12-02
影响因子：
4.8
通讯作者：
John TW
中科院分区：
文献类型：
--
作者：
Gatimu SM;John TW
18-69岁的肯尼亚人中有四分之一的人血压升高。尽管高血压患病率很高，而且社会经济地位与高血压之间存在已知的关联，但对肯尼亚血压升高不平等的原因了解有限。因此，我们量化了肯尼亚高血压的社会经济不平等，并分解了导致这种不平等的决定因素。我们使用了2015年肯尼亚STEPwise非传染性疾病风险因素调查的数据。我们纳入了4422名年龄在18-69岁之间的受访者。我们使用集中指数（C）估计社会经济不平等，并使用Wagstaff分解分析分解C。肯尼亚高血压的总体集中指数为-0.08（95%CI：-0.14，-0.02; p = 0.005），表明高血压的社会经济不平等不利于贫困人口。大约一半（47.1%）的高血压亲富人不平等是由身体质量指数解释的，26.7%是由社会经济因素（财富指数（10.4%），教育（9.3%）和有偿就业（7.0%））解释的，17.6%是由社会人口因素（女性性别（10.5%），年龄（4.3%）和婚姻状况（0.6%））解释的。区域差异解释了7.1%的估计不平等，仅中部地区就解释了6.0%的观察到的不平等。我们的模型解释了肯尼亚高血压估计的99.7%的社会经济不平等，还有一小部分不平等（-0.0002）。本研究表明，肯尼亚高血压的社会经济不平等，主要是由代谢风险因素（体重指数），个人健康行为和社会经济因素解释的。肯尼亚需要注重性别平等和公平的干预措施，以遏制高血压负担的上升和高血压不平等现象。在线版本包含补充材料，可通过10.1186/s12939-020-01321-1获得。
One in four Kenyans aged 18–69 years have raised blood pressure. Despite this high prevalence of hypertension and known association between socioeconomic status and hypertension, there is limited understanding of factors explaining inequalities in raised blood pressure in Kenya. Hence, we quantified the socioeconomic inequality in hypertension in Kenya and decomposed the determinants contributing to such inequality. We used data from the 2015 Kenya STEPwise survey for non-communicable diseases risk factors. We included 4422 respondents aged 18–69 years. We estimated the socioeconomic inequality using the concentration index (C) and decomposed the C using Wagstaff decomposition analysis. The overall concentration index of hypertension in Kenya was − 0.08 (95% CI: − 0.14, − 0.02; p = 0.005), showing socioeconomic inequalities in hypertension disfavouring the poor population. About half (47.1%) of the pro-rich inequalities in hypertension was explained by body mass index while 26.7% by socioeconomic factors (wealth index (10.4%), education (9.3%) and paid employment (7.0%)) and 17.6% by sociodemographic factors (female gender (10.5%), age (4.3%) and marital status (0.6%)). Regional differences explained 7.1% of the estimated inequality with the Central region alone explaining 6.0% of the observed inequality. Our model explained 99.7% of the estimated socioeconomic inequality in hypertension in Kenya with a small non-explained part of the inequality (− 0.0002). The present study shows substantial socioeconomic inequalities in hypertension in Kenya, mainly explained by metabolic risk factors (body mass index), individual health behaviours, and socioeconomic factors. Kenya needs gender- and equity-focused interventions to curb the rising burden of hypertension and inequalities in hypertension. The online version contains supplementary material available at 10.1186/s12939-020-01321-1.
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