Cicero Ethan C, Reisner Sari L, Merwin Elizabeth I, Humphreys Janice C, Silva Susan G
Ethan C. Cicero, PhD, RN, is Postdoctoral Scholar Fellow, Department of Community Health Systems, School of Nursing, University of California, San Francisco. Sari L. Reisner, ScD, is Assistant Professor, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts; Associate Scientific Researcher, Division of General Pediatrics, Boston Children's Hospital, Massachusetts; Assistant Professor, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; and Affiliated Research Scientist and Director, Transgender Health Research Team, The Fenway Institute, Fenway Health, Boston, Massachusetts. Elizabeth I. Merwin, PhD, RN, FAAN, is Dean, College of Nursing and Health Innovation, University of Texas at Arlington. Janice C. Humphreys, PhD, RN, FAAN, is Professor, Duke University School of Nursing, Durham, North Carolina. Susan G. Silva, PhD, is Associate Professor, Duke University School of Nursing and School of Medicine, Durham, North Carolina.
Nurs Res. 2020 Jul/Aug;69(4):307-315. doi: 10.1097/NNR.0000000000000428.
Obtaining representative data from the transgender population is fundamental to improving their health and well-being and advancing transgender health research. The addition of the Behavioral Risk Factor Surveillance System (BRFSS) gender identity measure is a promising step toward better understanding transgender health. However, methodological concerns have emerged regarding the validity of data collected from transgender participants and its effect on the accuracy of population parameters derived from those data.
The aim of the study was to provide rationale substantiating concerns with the formulation and application of the 2015 BRFSS sampling weights and address the methodological challenges that arise when using this surveillance data to study transgender population health.
We examined the 2015 BRFSS methodology and used the BRFSS data to present a comparison of poor health status using two methodological approaches (a matched-subject design and the full BRFSS sample with sampling weights applied) to compare their effects on parameter estimates.
Measurement error engendered by BRFSS data collection procedures introduced sex/gender identity discordance and contributed to problematic sampling weights. The sex-specific "raking" algorithm used by BRFSS to calculate the sampling weights was contingent on the classification accuracy of transgender by participants. Because of the sex/gender identity discordance of 74% of the transgender women and 66% of transgender men, sampling weights may not be able to adequately remove bias. The application of sampling weights has the potential to result in inaccurate parameter estimates when evaluating factors that may influence transgender health.
Generalizations made from the weighted analysis may obscure the need for healthcare policy and clinical interventions aimed to promote health and prevent illness for transgender adults. Methods of public health surveillance and population surveys should be reviewed to help reduce systematic bias and increase the validity of data collected from transgender people.
从跨性别群体中获取具有代表性的数据对于改善他们的健康和福祉以及推进跨性别健康研究至关重要。行为危险因素监测系统（BRFSS）中增加性别认同测量是朝着更好地了解跨性别健康迈出的有希望的一步。然而，对于从跨性别参与者收集的数据的有效性及其对从这些数据得出的总体参数准确性的影响，出现了方法学上的担忧。
本研究的目的是提供理由，证实对2015年BRFSS抽样权重的制定和应用的担忧，并解决在使用该监测数据研究跨性别群体健康时出现的方法学挑战。
我们检查了2015年BRFSS的方法，并使用BRFSS数据，通过两种方法（匹配对象设计和应用抽样权重的完整BRFSS样本）对健康状况不佳进行比较，以比较它们对参数估计的影响。
BRFSS数据收集程序产生的测量误差导致了性别认同不一致，并导致抽样权重出现问题。BRFSS用于计算抽样权重的特定性别的“加权”算法取决于参与者对跨性别的分类准确性。由于74%的跨性别女性和66%的跨性别男性存在性别认同不一致，抽样权重可能无法充分消除偏差。在评估可能影响跨性别健康的因素时，应用抽样权重可能会导致参数估计不准确。
加权分析得出的概括可能会掩盖针对跨性别成年人促进健康和预防疾病的医疗保健政策和临床干预措施的必要性。应审查公共卫生监测和人口调查方法，以帮助减少系统偏差并提高从跨性别者收集的数据的有效性。
