Dragano Nico, Reuter Marvin, Greiser Karin Halina, Becher Heiko, Zeeb Hajo, Mikolajczyk Rafael, Kluttig Alexander, Leitzmann Michael, Fischer Beate, Jöckel Karl-Heinz, Emmel Carina, Krause Gérard, Castell Stefanie, Damms-Machado Antje, Obi Nadia, Schikowski Tamara, Kuss Oliver, Hoffmann Wolfgang, Schipf Sabine, Pischon Tobias, Jaeschke Lina, Krist Lilian, Keil Thomas, Lieb Wolfgang, Holleczek Bernd, Brenner Hermann, Wirkner Kerstin, Loeffler Markus, Michels Karin B, Franzke Claus-Werner, Peters Annette, Linseisen Jakob, Berger Klaus, Legath Nicole, Ahrens Wolfgang, Lampert Thomas, Schmidt Börge
Institut für Medizinische Soziologie, Centre for Health and Society, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland.
Abteilung Epidemiologie von Krebserkrankungen, DKFZ Heidelberg, Heidelberg, Deutschland.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2020 Mar;63(3):267-278. doi: 10.1007/s00103-020-03098-8.
In epidemiologic studies, standardised measurement of socio-demographic and employment-related factors is becoming increasingly important, as variables such as gender, age, education or employment status are factors influencing health and disease risks.
The article gives an overview of the scientific background and assessment of socio-demographic factors in the German National Cohort Study. In addition, the distribution of individual characteristics in the cohort as well as relationships with health-related measures are presented by way of example.
The analysis is based on the data of the first half of the baseline survey (n = 101,724). On this basis, we present the distribution of key socio-demographic characteristics and analyse relationships with exemplary selected health indicators (body mass index, self-reported health) to assess the validity of socio-demographic data measurements.
On average, study participants were 52.0 years old (SD = 12.4). Of the participants, 53.6% were women, 54.3% had high education, 60.1% were married and 72% were employed while 3.4% were unemployed. Well-established correlations between socio-demographic factors and health could be reproduced with the German National Cohort data. For example, low education, old age and unemployment were associated with an increased prevalence of obesity and poor self-reported health.
The German National Cohort provides a comprehensive measurement of socio-demographic characteristics. Combined with a wide range of health data and the longitudinal measurements available in the future, this opens up new opportunities for health science and social epidemiological research in Germany.
在流行病学研究中，社会人口学和与就业相关因素的标准化测量变得越来越重要，因为诸如性别、年龄、教育程度或就业状况等变量是影响健康和疾病风险的因素。
本文概述了德国国民队列研究中社会人口学因素的科学背景和评估。此外，还举例介绍了队列中个体特征的分布以及与健康相关指标的关系。
分析基于基线调查上半年的数据（n = 101,724）。在此基础上，我们呈现关键社会人口学特征的分布，并分析与选定的示例性健康指标（体重指数、自我报告的健康状况）的关系，以评估社会人口学数据测量的有效性。
研究参与者的平均年龄为52.0岁（标准差 = 12.4）。参与者中，53.6%为女性，54.3%受过高等教育，60.1%已婚，72%就业，3.4%失业。德国国民队列数据能够重现社会人口学因素与健康之间已确立的相关性。例如，低教育程度、老年和失业与肥胖患病率增加及自我报告的健康状况不佳有关。
德国国民队列提供了对社会人口学特征的全面测量。结合广泛的健康数据以及未来可用的纵向测量，这为德国的健康科学和社会流行病学研究开辟了新的机会。
