通过使用多次归算的伤害监测数据来解决健康差异
Yang Liu1, Amy F Wolkin2, Marcie-Jo Kresnow2
1Division of Injury Prevention, National Center for Injury Prevention and Control, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA. wcq6@cdc.gov.
International journal for equity in health
|July 3, 2023
概括
这项研究揭示了非致命性攻击伤害的显著差异,非西班牙裔黑人,公共场合和男性的伤害率更高. 解决这些伤害差异对于有效的预防策略至关重要.
科学领域:
- 公共卫生 公共卫生
- 伤害预防 预防伤害
- 健康差距 研究 研究 研究 研究
背景情况:
- 评估伤害差异对于有效预防至关重要,但由于缺少数据而受到阻碍.
- 国家电子伤害监测系统-所有伤害计划 (NEISS-AIP) 是伤害数据的关键资源.
- 解决数据的局限性对于可靠的差异分析至关重要.
研究的目的:
- 证明NEISS-AIP在检查损害差异方面的实用性和可靠性.
- 为了产生多个归算的伴随数据集,以克服缺失的数据限制.
- 系统地评估非致命性攻击伤害中的健康差异.
主要方法:
- 使用了2014-2018年的NEISS-AIP数据.
- 进行模拟研究,以确定处理缺失数据的最佳策略.
- 通过完全有条件规范 (FCS MI) 采用多次归算,并开发了用于归算性能评估的Brier Skill Score (BSS).
- 分析了在紧急诊所的种族/种族,受伤地点和性别的差异.
主要成果:
- 在非西班牙裔黑人中 (1306.8 / 100,000),在公共场合 (286.3 / 100,000) 和男性中 (603.5 / 100,000) 观察到明显更高的年龄调整的非致命性攻击伤害率.
- 从2014年到2017年,这些利率的趋势显示出大幅增加,随后在2018年大幅下降.
- 这项研究提供了第一个综合分析的健康差异在非致命的袭击伤害使用多重指定的数据.
结论:
- 非致命的攻击伤害导致大量的医疗保健费用和生产力损失.
- 这项研究强调了特定的人口和基于位置的群体中非致命性攻击伤害的显著差异.
- 了解这些差异对于制定有针对性和有效的伤害预防计划至关重要.
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