Center for Biomedical Modeling, Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States.
Afrobarometer / Institute for Democracy, Citizenship and Public Policy in Africa, University of Cape Town, Cape Town, South Africa.
Elife. 2022 Oct 18;11:e79615. doi: 10.7554/eLife.79615.
Mobile health (mHealth) interventions, which require ownership of mobile phones, are being investigated throughout Africa. We estimate the percentage of individuals who own mobile phones in 33 African countries, identify a relationship between ownership and proximity to a health clinic (HC), and quantify inequities in ownership. We investigate basic mobile phones (BPs) and smartphones (SPs): SPs can connect to the internet, BPs cannot. We use nationally representative data collected in 2017-2018 from 44,224 individuals in Round 7 of the Afrobarometer surveys. We use Bayesian multilevel logistic regression models for our analyses. We find 82% of individuals in 33 countries own mobile phones: 42% BPs and 40% SPs. Individuals who live close to an HC have higher odds of ownership than those who do not (aOR: 1.31, Bayesian 95% highest posterior density [HPD] region: 1.24-1.39). Men, compared with women, have over twice the odds of ownership (aOR: 2.37, 95% HPD region: 1.96-2.84). Urban residents, compared with rural residents, have almost three times the odds (aOR: 2.66, 95% HPD region: 2.22-3.18) and, amongst mobile phone owners, nearly three times the odds of owning an SP (aOR: 2.67, 95% HPD region: 2.33-3.10). Ownership increases with age, peaks in 26-40 year olds, then decreases. Individuals under 30 are more likely to own an SP than a BP, older individuals more likely to own a BP than an SP. Probability of ownership decreases with the Lived Poverty Index; however, some of the poorest individuals own SPs. If the digital devices needed for mHealth interventions are not equally available within the population (which we have found is the current situation), rolling out mHealth interventions in Africa is likely to propagate already existing inequities in access to healthcare.
移动医疗(mHealth)干预措施需要拥有手机,目前正在非洲各地进行研究。我们估计了 33 个非洲国家个人拥有手机的比例,确定了拥有手机与靠近诊所(HC)之间的关系,并量化了拥有手机的不平等现象。我们调查了基本手机(BP)和智能手机(SP):SP 可以连接互联网,BP 则不能。我们使用 2017-2018 年 Afrobarometer 调查第 7 轮中收集的来自 44224 个人的全国代表性数据进行分析。我们使用贝叶斯多层次逻辑回归模型进行分析。我们发现,33 个国家中有 82%的个人拥有手机:42%是 BP,40%是 SP。居住在 HC 附近的人比不居住在 HC 附近的人拥有手机的可能性更高(优势比[OR]:1.31,贝叶斯 95%最高后验密度[HPD]区间:1.24-1.39)。与女性相比,男性拥有手机的可能性高出两倍多(OR:2.37,95% HPD 区间:1.96-2.84)。与农村居民相比,城市居民拥有手机的可能性几乎高出三倍(OR:2.66,95% HPD 区间:2.22-3.18),在手机拥有者中,拥有智能手机的可能性高出近三倍(OR:2.67,95% HPD 区间:2.33-3.10)。拥有手机的可能性随着年龄的增长而增加,在 26-40 岁达到峰值,然后下降。30 岁以下的人更有可能拥有 SP,而年龄较大的人更有可能拥有 BP。拥有手机的可能性随着生活贫困指数的降低而降低;然而,一些最贫困的人拥有 SP。如果 mHealth 干预措施所需的数字设备在人群中不能平等获得(我们发现这是目前的情况),那么在非洲推出 mHealth 干预措施可能会加剧医疗保健获取方面已经存在的不平等现象。