Krieger School of Arts and Sciences Johns Hopkins University Baltimore MD.
Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Cardiovascular Disease Johns Hopkins University School of Medicine Baltimore MD.
J Am Heart Assoc. 2022 Sep 6;11(17):e024885. doi: 10.1161/JAHA.121.024885. Epub 2022 Sep 3.
Background Mobile health (mHealth) has an emerging role in the prevention of cardiovascular disease. This study evaluated possible inequities in mHealth access in older adults. Methods and Results mHealth access was assessed from 2019 to 2020 in MESA (Multi-Ethnic Study of Atherosclerosis) telephone surveys of 2796 participants aged 62 to 102 years. A multivariable logistic regression model adjusted for general health status assessed associations of mHealth access measures with relevant demographic, socioeconomic, and cognitive characteristics. There were lower odds of all access measures with older age (odds ratios [ORs], 0.37-0.59 per 10 years) and annual income <$50 000 (versus ≥$50 000 ORs, 0.55-0.62), and higher odds with higher Cognitive Abilities Screening Instrument Score (ORs, 1.22-1.29 per 5 points). Men (versus women) had higher odds of internet access (OR, 1.32 [95% CI,1.05-1.66]) and computing device ownership (OR, 1.31 [95% CI, 1.05-1.63]) but lower fitness tracker ownership odds (OR, 0.70 [95% CI, 0.49-0.89]). For internet access and computing device ownership, we saw lower odds for Hispanic participants (versus White participants OR, 0.61 [95% CI, 0.44-0.85]; OR, 0.69 [95% CI, 0.50-0.95]) and less than a high school education (versus bachelor's degree or higher OR, 0.27 [95% CI, 0.18-0.40]; OR, 0.32 [95% CI, 0.28-0.62]). For internet access, lower odds were seen for Black participants (versus White participants OR, 0.64 [95% CI, 0.47-0.86]) and other health insurance (versus health maintenance organization/private OR, 0.59 [95% CI, 0.47-0.74]). Chinese participants (versus White participants) had lower internet access odds (OR, 0.63 [95% CI, 0.44-0.91]) but higher computing device ownership odds (OR, 1.87 [95% CI, 1.28-2.77]). Conclusions Among older-age adults, mHealth access varied by major demographic, socioeconomic, and cognitive characteristics, suggesting a digital divide. Novel mHealth interventions should consider individual access barriers. Registration URL: https://www.clinicaltrials.gov/; Unique identifier: NCT00005487.
背景 移动医疗（mHealth）在心血管疾病预防中发挥着新兴作用。本研究评估了老年人使用 mHealth 方面可能存在的不公平现象。
方法和结果 2019 年至 2020 年，通过 MESA（动脉粥样硬化多民族研究）电话调查对 2796 名年龄在 62 至 102 岁的参与者评估了 mHealth 的使用情况。使用多变量逻辑回归模型，根据一般健康状况调整了 mHealth 使用措施与相关人口统计学、社会经济和认知特征的关联。与年龄较大（每 10 岁的优势比 [OR] 为 0.37-0.59）和年收入<$50000（与年收入≥$50000 的 OR 为 0.55-0.62）相关的所有使用措施的可能性较低，而与更高的认知能力筛查工具评分（每 5 分的 OR 为 1.22-1.29）相关的可能性更高。男性（与女性相比）拥有互联网访问（OR，1.32[95%CI，1.05-1.66]）和计算设备所有权（OR，1.31[95%CI，1.05-1.63]）的可能性更高，但健身追踪器所有权的可能性较低（OR，0.70[95%CI，0.49-0.89]）。对于互联网访问和计算设备所有权，我们发现西班牙裔参与者的可能性较低（与白人参与者相比，OR 为 0.61[95%CI，0.44-0.85]；OR 为 0.69[95%CI，0.50-0.95]），并且受教育程度较低（与学士学位或更高学历相比，OR 为 0.27[95%CI，0.18-0.40]；OR 为 0.32[95%CI，0.28-0.62]）。对于互联网访问，黑人参与者的可能性较低（与白人参与者相比，OR 为 0.64[95%CI，0.47-0.86]），其他医疗保险（与健康维护组织/私人保险相比，OR 为 0.59[95%CI，0.47-0.74]）。中国参与者（与白人参与者相比）的互联网访问机会较低（OR，0.63[95%CI，0.44-0.91]），但计算设备拥有机会较高（OR，1.87[95%CI，1.28-2.77]）。
结论 在老年人群中，mHealth 的使用情况因主要人口统计学、社会经济和认知特征而异，这表明存在数字鸿沟。新的 mHealth 干预措施应考虑个体的访问障碍。
