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使用潜在类别分析建立社会经济地位与种族之间关系的模型:来自多民族出生队列研究的横断面分析。

Using latent class analysis to develop a model of the relationship between socioeconomic position and ethnicity: cross-sectional analyses from a multi-ethnic birth cohort study.

作者信息

Fairley Lesley, Cabieses Baltica, Small Neil, Petherick Emily S, Lawlor Debbie A, Pickett Kate E, Wright John

机构信息

Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK.

出版信息

BMC Public Health. 2014 Aug 12;14:835. doi: 10.1186/1471-2458-14-835.

Abstract

BACKGROUND

Almost all studies in health research control or investigate socioeconomic position (SEP) as exposure or confounder. Different measures of SEP capture different aspects of the underlying construct, so efficient methodologies to combine them are needed. SEP and ethnicity are strongly associated, however not all measures of SEP may be appropriate for all ethnic groups.

METHODS

We used latent class analysis (LCA) to define subgroups of women with similar SEP profiles using 19 measures of SEP. Data from 11,326 women were used, from eight different ethnic groups but with the majority from White British (40%) or Pakistani (45%) backgrounds, who were recruited during pregnancy to the Born in Bradford birth cohort study.

RESULTS

Five distinct SEP subclasses were identified in the LCA: (i) "Least socioeconomically deprived and most educated" (20%); (ii) "Employed and not materially deprived" (19%); (iii) "Employed and no access to money" (16%); (iv) "Benefits and not materially deprived" (29%) and (v) "Most economically deprived" (16%). Based on the magnitude of the point estimates, the strongest associations were that compared to White British women, Pakistani and Bangladeshi women were more likely to belong to groups: (iv) "benefits and not materially deprived" (relative risk ratio (95% CI): 5.24 (4.44, 6.19) and 3.44 (2.37, 5.00), respectively) or (v) most deprived group (2.36 (1.96, 2.84) and 3.35 (2.21, 5.06) respectively) compared to the least deprived class. White Other women were more than twice as likely to be in the (iv) "benefits and not materially deprived group" compared to White British women and all ethnic groups, other than the Mixed group, were less likely to be in the (iii) "employed and not materially deprived" group than White British women.

CONCLUSIONS

LCA allows different aspects of an individual's SEP to be considered in one multidimensional indicator, which can then be integrated in epidemiological analyses. Ethnicity is strongly associated with these identified subgroups. Findings from this study suggest a careful use of SEP measures in health research, especially when looking at different ethnic groups. Further replication of these findings is needed in other populations.

摘要

背景

健康研究中的几乎所有研究都将社会经济地位(SEP)作为暴露因素或混杂因素进行控制或调查。SEP的不同测量方法反映了潜在结构的不同方面,因此需要有效的方法来将它们结合起来。SEP与种族密切相关,然而并非所有SEP测量方法都适用于所有种族群体。

方法

我们使用潜在类别分析(LCA),通过19种SEP测量方法来定义具有相似SEP特征的女性亚组。使用了来自11326名女性的数据,她们来自八个不同的种族群体,但大多数是英国白人(40%)或巴基斯坦裔(45%)背景,这些女性是在孕期被招募进入布拉德福德出生队列研究的。

结果

在LCA中识别出五个不同的SEP亚类:(i)“社会经济剥夺最少且受教育程度最高”(20%);(ii)“就业且无物质剥夺”(19%);(iii)“就业但无资金可用”(16%);(iv)“领取福利且无物质剥夺”(29%)和(v)“经济剥夺最严重”(16%)。基于点估计的幅度,最强的关联是,与英国白人女性相比,巴基斯坦和孟加拉裔女性更有可能属于以下群体:(iv)“领取福利且无物质剥夺”(相对风险比(95%置信区间):分别为5.24(4.44,6.19)和3.44(2.37,5.))或(v)最贫困群体(分别为2.36()和3.35(2.21,5.06)),与最不贫困类别相比。与英国白人女性相比,其他白人女性属于(iv)“领取福利且无物质剥夺群体”的可能性是其两倍多,除混血群体外的所有种族群体属于(iii)“就业且无物质剥夺”群体的可能性均低于英国白人女性。

结论

LCA允许在一个多维指标中考虑个体SEP的不同方面,然后可将其纳入流行病学分析。种族与这些识别出的亚组密切相关。本研究结果表明在健康研究中应谨慎使用SEP测量方法,尤其是在研究不同种族群体时。需要在其他人群中进一步重复这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4527/4141955/70c006ecf54c/12889_2013_6965_Fig1_HTML.jpg

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