谁住在伦敦东北部拥挤的家庭里?链接的电子健康记录和能源绩效证书登记数据的横断面研究。

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2022-08-25 DOI:10.23889/ijpds.v7i3.1827
Marta Wilk, C. Dezateux, S. Liverani, G. Harper
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引用次数: 0

摘要

家庭过度拥挤与不良健康结果有关,包括传染病风险增加、精神健康问题和受教育程度低。我们通过匿名将电子健康记录(EHR)与能源绩效证书(EPC)数据联系起来,调查了伦敦城市、种族多样化和弱势群体中过度拥挤的不平等现象。我们使用假名的唯一财产参考号码将伦敦东北部321,318户目前登记的1,066156名患者的电子病历与EPC数据联系起来。我们测量了家庭入住率,并推导出卧室标准过度拥挤定义(相对于居住者性别和年龄的房间数量),以估计过度拥挤的患病率。我们研究了以下因素的相关性:家庭构成(仅成人、单身成人+子女、≥2个工作年龄成人+子女、≥1个退休年龄成人+子女、三代家庭);种族背景(白人、南亚人、黑人、混血儿、其他、失踪);和多重剥夺指数(IMD)五分位数。我们使用多变量逻辑回归来估计过度拥挤的调整几率(aOR)和95%置信区间(CI)。结果总体上有243793人(22.9%)过度拥挤。有孩子的家庭或三代同堂的家庭更有可能(aOR [95% CI] 3.79 [3.74 - 3.84];6.53[6.41 - 6.66]),单身成年人或有子女的退休年龄成年人较少(0.36 [0.35 - 0.38];0.36[分别为0.23 - 0.57]),过度拥挤。亚洲或黑人族裔背景的人更有可能过度拥挤(分别为1.24[1.22 - 1.25]和1.17[1.15 - 1.19])。IMD五分位数与过度拥挤之间存在剂量-反应关系:与最贫困五分位数相比,最贫困五分位数的OR为0.20[0.20 - 0.21]。结论:在伦敦东北部,五分之一的人生活在拥挤的家庭中,种族、家庭代际构成和贫困都存在明显的不平等。可以从相关的住房和健康记录中得出家庭过度拥挤的最新估计数,并用于评估经济政策对健康和住房不平等的影响。
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Who lives in overcrowded households in north-east London? Cross-sectional study of linked electronic health records and Energy Performance Certificate register data.
ObjectivesHousehold overcrowding is associated with adverse health outcomes, including increased risk of infectious diseases, mental health problems, and poor educational attainment. We investigated inequalities in overcrowding in an urban, ethnically diverse, and disadvantaged London population by pseudonymously linking electronic health records (EHR) to Energy Performance Certificates (EPC) data. ApproachWe used pseudonymised Unique Property Reference Numbers to link EHRs for 1,066,156 currently registered patients from 321,318 households in north-east London to EPC data. We measured household occupancy and derived the bedroom standard overcrowding definition (number of rooms relative to occupants’ sex and ages) to estimate overcrowding prevalence. We examined associations with: household composition (adults only, single adult+children, ≥2 working-age adults+children, ≥1 retirement-age adults+children, three-generational household); ethnic background (White, South Asian, Black, Mixed, Other, missing); and Index of Multiple Deprivation (IMD) quintile. We used multivariable logistic regression to estimate the adjusted odds (aOR) and 95% Confidence Intervals (CI) of overcrowding. ResultsOverall, 243,793 (22.9%) people were overcrowded. People living in households with children, or three-generational households were more likely (aOR [95% CI] 3.79 [3.74 - 3.84]; 6.53 [6.41 - 6.66] respectively), and single adults or retirement age adults with children less likely (0.36 [0.35 - 0.38]; 0.36 [0.23 - 0.57] respectively), to be overcrowded. Overcrowding was more likely among people from Asian or Black ethnic backgrounds (1.24 [1.22 - 1.25] and 1.17 [1.15 - 1.19] respectively). There was a dose-response relationship between IMD quintile and overcrowding: OR 0.20 [0.20 - 0.21] in the least deprived compared to most deprived quintile. ConclusionOne in five people in north-east London live in overcrowded households with marked inequalities by ethnicity, household generational composition, and deprivation. Up-to-date estimates of household overcrowding can be derived from linked housing and health records and used to evaluate the impact of economic policies on health and housing inequalities.
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386
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