Ethnic and socio-economic inequalities in coronary heart disease, diabetes and risk factors in Europeans and South Asians
Ethnic and socio-economic inequalities in coronary heart disease, diabetes and risk factors in Europeans and South Asians
复制标题
DOI：
10.1093/pubmed/24.2.95
复制
发表时间：
2002-06-01
期刊：
影响因子：
--
通讯作者：
Alberti, G
中科院分区：
文献类型：
--
作者：
Bhopal, R;Hayes, L;Alberti, G
背景本研究的目的是检验欧洲人和南亚人（印度人，巴基斯坦人，孟加拉国人）一样，较差的社会经济地位与冠心病（CHD）的较高患病率相关，葡萄糖耐受不良（糖耐量受损和糖尿病）及相关危险因素方法通过一项以社区为基础的患病率研究，对横断面数据进行分析，受教育程度、汤森剥夺评分、冠心病心电图证据、糖耐量试验和12项心血管危险因素。研究人群包括南亚人（n = 684），包括印度人（n = 259）、巴基斯坦人（n = 305）和孟加拉国人（n = 120），以及欧洲人（n = 825），年龄在25-74岁之间，在纽卡斯尔。该分析审查了每个族裔群体多达84个协会。种族和社会经济变量之间的相互作用进行了研究，使用回归分析。主要结果的措施是协会的数量在预测的direction.Results欧洲人表现得更好的社会经济地位，南亚人在其他一些指标。与巴基斯坦人和孟加拉国人相比，印度人的社会经济地位更高。在欧洲人中，大多数社会经济地位指标与健康指标的预测方向相关[71/84（85%）协会，25个统计学显著性]，而在南亚人中则较少[58/84（69%）协会，12个统计学显著性]。在南亚男性中，25/42（60%）的关联符合预测，7个显著，在女性中，33/42（79%）符合预测，5个具有统计学显著性。印度人[52/78（67%）的协会预测，7个统计学显著]，巴基斯坦人[41/84（49%），4个统计学显著]和孟加拉国人[39/79（49%），1个统计学显著]之间存在明显差异。在印度人中，汤森剥夺分数大多与预测相关[23/27（85%），5个关联具有统计学意义]，比社会阶层更相关[14/27（52%），无统计学意义]。在南亚男性和女性中，与人体测量[18/24（75%）]，生化[15/18（83%）]和生活方式[14/18（78%）]措施的相关性通常与预测一致，但血压（4/12，33%）和CHD和葡萄糖耐受不良（7/12，58%）的相关性较低。社会经济地位和ethnications.Conclusions之间的相互作用的不平等的欧洲模式正在建立在南亚的男性和女性，可能在不同的亚组在不同的步伐。未来的不平等研究应该是大规模的，分开的印度，巴基斯坦和孟加拉国人口，分别研究男性和女性，并跟踪随时间的变化。
Background The aim of this study was to test the hypothesis that in Europeans and South Asians (Indians, Pakistanis, Bangladeshis) alike, worse socio-economic status is associated with a higher prevalence of coronary heart disease (CHD), glucose intolerance (impaired glucose tolerance and diabetes) and related risk factors (the predicted direction of association).Methods Cross-sectional data were analysed from a community-based prevalence study seeking associations between social class, education and Townsend deprivation score and ECG evidence of CHD, glucose tolerance test and 12 cardiovascular risk factors. The study population consisted of South Asians (n = 684) comprising Indians (n = 259), Pakistanis (n = 305) and Bangladeshis (n = 120), and Europeans (n = 825), aged 25-74 years in Newcastle. The analysis examined up to 84 associations for each ethnic group. Interactions between ethnicity and socio-economic variables were examined using regression analysis. The main outcome measure was the number of associations in the predicted direction.Results Europeans fared better in some indicators of socioeconomic position, South Asians in others. Indians were socio-economically advantaged compared with Pakistanis and Bangladeshis. Most measures of socio-economic position were associated with health measures in the predicted direction in Europeans [71/84 (85 per cent) associations, 25 statistically significant] and less so in the South Asians combined [58/84 (69 per cent) associations, 12 statistically signifi- cant]. In South Asian men 25/42 (60 per cent) of associations were as predicted, seven significantly so, in women 33/42 (79 per cent) were, five being statistically significant. There were apparent differences between Indians [52/78 (67 per cent) of associations as predicted, seven statistically significant], Pakistanis [41/84 (49 per cent), four statistically significant] and Bangladeshis [39/79 (49 per cent), one statistically significant]. In Indians, Townsend deprivation score was mostly associated as predicted [23/27 (85 per cent), five associations statistically significant], more so than social class [14/27 (52 per cent), none statistically significant]. In South Asian men and women combined, associations with anthropometric [18/24 (75 per cent)], biochemical [15/18 (83 per cent)], and lifestyle [14/18 (78 per cent)] measures were often as predicted, but those with blood pressure (4/12, 33 per cent) and CHD and glucose intolerance (7/12, 58 per cent) were less often so. Interactions between socio-economic position and ethnicity were found.Conclusions The European pattern of inequalities is being established in South Asian men and women, possibly at a different pace in different subgroups. Future studies of inequalities should be large, separate Indian, Pakistani and Bangladeshi populations, study men and women separately and track changes over time.