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Author: Toralf Kirsten20
Monitoring Motor Skills of Children and Adolescents in LIFE Child
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Life Child is an epidemiological study running at the LIFE Research Center for Civilization Diseas-es (University of Leipzig) since 2011. It aims at monitoring the development in children and adolescents … by examining thousands of children in and around Leipzig. Of particular interest in this study are motor skills and physical activities of children between 6 and 18 years. There are multiple examinations including interviews, self-completed questionnaires and physical examinations (e.g., sport tests) to generate data describing the determined child as well her lifestyle and environment. The goal is to find causes for low to non physical activity and unincisive motor skills and capabilities since they are commonly attended with diseases, such as obesity and diabetes. As a first step in this direction, we analyzed data of specific sport tests, such as pushups, side steps and long jumps, according to the body mass index (BMI) of participants. We found that participants with high BMI achieve a similar number of pushups in early years like the normal BMI group, while in later years the pushup number of participants with normal BMI exceeds the pushup number of high BMI group. Surprisingly, the number of side steps is indifferent over age categories (6-18, yearly) between both groups. Conversely, the normal BMI group achieve higher distances through-out all age categories than the high BMI group. In future, we will associate these results with socio-economic and lifestyle indicators, e.g., interest in sport and physical activities of child and parents.

Authors: J. Lang, C. Warnatsch, M. Vogel, Toralf Kirsten, W. Kiess

Date Published: 17th Dec 2014

Publication Type: Not specified

Soziodemographische Merkmale und soziökonomischer Status der Teilnehmer in der LIFE Child Kohorte im nationalen Vergleich
LIFE Child

Abstract (Expand)

Soziodemographische Merkmale gelten in den Humanwissenschaften als globale Einflussfaktoren in fast allen Forschungsgebieten und bilden das Basiselement von Kohortenstudien. Darüber hinaus wurde in … vielen Bereichen ein direkter Zusammenhang zwischen sozialen Faktoren und Gesundheit nachgewiesen. Insbesondere im Kindes- und Jugendalter nimmt der sozioökonomische Status einer Familie entscheidenden Einfluss auf die physische sowie mentale Entwicklung. Derartige und weitere Forschungsfragen stehen im Blickpunkt des Projektes LIFE Child.

Authors: L. Meißner, C. Bucher, M. Vogel, Toralf Kirsten, S. Nerlich, U. Igel, W. Kiess, A. Hiemisch

Date Published: 17th Dec 2014

Publication Type: Not specified

Spatial Analysis of Anthropometric and Lifestyle Data for Children and Adolescents
LIFE Child

Abstract (Expand)

LIFE Child is an epidemiological cohort study at the Leipzig Research Center for Civilization Dis-eases (University of Leipzig). A main goal of LIFE Child is to study the influence of environment and … lifestyle factors to the development of children and adolescent in and near Leipzig. In particu-lar, we search for predominant aspects in the development of children with obesity. Typically, data is analyzed by different statistical methods and approaches to find (perhaps multi-variate) pre-dominant markers. Additionally, we map selected data to geographical maps to study their spatial distribution over urban districts of Leipzig, on the one hand. This allows to compara-tively analyze anthropometric measurements, such as age- and gender-corrected height, weight, and body mass index, together with further participant-related data including social indicators, e.g., in-come, education, socio economic indexes and lifestyle data, to distinguish city districts with a high correlation to those with low or no correlation. On the other hand, we associate anthropometric measurements with publicly available data, such as official statistics including district-specific un-employment rates and inhabitant densities by taking the participant's place of living into account. We developed a spatial analysis pipeline of anthropometric and lifestyle data according to Leipzig city districts. While cohort and publicly available data is managed by a database system, the analysis pipeline is implemented by dedicated R scripts. The sample is with more than 2,500 children large enough for first analyses. … Our first results show that unemployment of parents could be a factor for obesity of children especially in districts with low social index.

Authors: M. Vogel, A. Kiel, M. Rühle, Toralf Kirsten, M. Geserick, R. Gausche, G. Grande, D. Molis, U. Igel, S. Alvanides, W. Kiess

Date Published: 1st Nov 2014

Publication Type: Not specified

Data Quality Control and Data Analysis of Body-Scanner Measurement Values in Children and Adolescents
LIFE Child

Abstract (Expand)

Introduction LIFE child as a part of the 'Leipzig Research Centre for Civilization Diseases' is a longitudinal cohort study aiming, inter alia, at monitoring normal development in children and … adolescents from fetal life to adulthood. As an important part of the study, anthropometric dimensions are measured via classic methods, e.g. stadiometer or tape measure (ca. 15 items), but also via 3D body scanner technology (ca. 150 items). Because of missing standards data quality control and analysis of the latter one is a particular challenge. Methods We address the problem of absent reference values by using the data itself as a reference sample. Applying the LMS-method using the VGAM/GAMLSS packages [XXX] on a reference sample which is large enough results in age and gender corrected standard deviation scores (SDS) respectively percentile curves. A combination of variable clustering and clustering of values using these SDS is applied to the detect groups of dependend variables and peculiar cases respectively. Results In LIFE child the current reference sample consists of around 4000 scans of 1700 children. The age dependend l, m, and s values for each item are generated by dedicated R-routines and stored in a relational database system. The transformation algorithm by Cole is implemented as database function and dynamically applied on all associated raw data. Conspiciuous values can be detected using the SDS itself or the SDS in comparison with the belonging variable cluster and/or taking into account the follow-up data of the respective participant. These values can be reported and visualized using automated routines.

Authors: M. Vogel, A.L. Fischer, C. Bucher, W. Kiess, Toralf Kirsten

Date Published: 1st Nov 2014

Publication Type: Not specified

The comprehensive IT-Infrastructure for epidemiological Research in LIFE
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Introduction LIFE is a large epidemiological study aiming at causes of common civilization diseases including adiposity, dementia, and depression. Participants of the study are probands and patients. … Probands are randomly selected and invited from the set of Leipzig (Germany) inhabitants while patients with known diseases are recruited from several local hospitals. The management of these participants, their invitation and contact after successful attendance as well as the support of nearly all ambulance processes requires a complex ambulance management. Each participant is examined by a set of investigation instruments including interviews, questionnaires, device-specific investigations, specimen extrac- tions and analyses. This necessitates a complex management of the participantspecific examination program but also specific input forms and systems allowing to capture administrative (measurement and process environment or specific set-ups) and scientific data. Additionally, the taken and prepared specimens need to be labeled and registered from which participant they stem and in which fridge or bio-tank they are stored. At the end, all captured data from ambu- lance management, investigation instruments and laboratory analyses need to be integrated before they can be analyzed. These complex processes and requirements necessitate a comprehensive IT-infrastructure. Methods Our IT-infrastructure modularly consists of several software applications. A main application is responsible for the complex participant and ambulance man- agement. The participant management cope with selected participant data and contact information. To protect participant’s privacy, a participant identifier (PID) is created for each participant that is associated to all data which is managed and captured in the following. In ambulance management, each participant is associated with a predefined investigation program. This investigation program is represented in our systems by a tracking card that is available as print-out and electronically. The electronic version of tracking cards is utilized by two software applications, the Assessment Battery and the CryoLab. The former system coordinates the input of scientific data into online input forms. The input forms are designed in the open source system LimeSurvey. Moreover, the Assessment Battery is used to monitor the input process, i.e., it shows which investigations are already completed and which of them are still to do. The Cryolab system registers and tracks all taken specimens and is used to annotate extraction and specific preparation processes, e.g., for DNA isolation. Moreover, it tracks specimen storage in fridges and bio-tanks. A central component is the metadata repository collecting metadata from ambulance management and data input systems. It is the base for the integra- tion of relevant scientific data into a central research database. The integration follows a mapping-based approach. The research database makes raw data and special pre-computations called derivatives available for later data analysis. Results & Discussion We designed and implemented a complex and comprehensive IT-infrastructure for the epidemiological research in LIFE. This infrastructure consists of several software applications which are loosely coupled over specified interfaces. Most of the software applications are new implementations; only for capturing scientific data external software application are applied.

Authors: Toralf Kirsten, A. Kiel, M. Kleinert, R. Speer, M. Rühle, Hans Binder, Markus Löffler

Date Published: 30th Sep 2013

Publication Type: Not specified

Curation-DB: Curating Scientific Data in LIFE
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Introduction LIFE is a epidemiological study aiming at discovering causes of common disorders as well as therapy and diagnostic possibilities. It applies a huge set (currently more then 400) of complex … instruments including different kinds of interviews, questionnaires, and technically founded investigations on thousands of Leipzig inhabitants. Correlations in data, e.g., between diseases on the one hand and a combination of life conditions on the other requires high quality data. Data errors affect this data quality. However, avoiding every error is nearly impossible. Therefore, the captured data routinely needs to be validated and revised (curated) in case of error. Methods From the data-perspective, we differentiate between two main types of data errors, syntax or format errors and semantic errors. Syntax errors mostly occur when the data needs to be converted to change its data type, e.g., from text to number or from text to date/time fields. This is often the case when data is captured as text by the data input system but should be centrally managed and analyzed in a different format. Hence, the data conversion is only successful when the input data contains the data in the right format. Data conversion is applied when the data is transfered from data input systems to the central research database collecting all captured data in an integrated and harmonized form. Corrupted data that cannot be converted to the target data type is replaced by a missing value (also called null value, nil etc.). The definition of a default value is not sufficient since the default usually depends on the corresponding question or measurement input field and can strain analysis results when they are not concerned. Moreover, the definition process for every question/input field would be to time-consuming. Semantic errors are much harder to detect than syntax errors. Typically, they are semantically implausible outliers or are part of other artefacts, e.g.,when data of two input fields is mixed up. Currently, we let the detection of semantic errors to a epidemiological quality analysis that is performed by several statisticians. Conversely, syntax errors can be easily technically detected; they are logged when they occur in the process of transferring data from data input systems to the central research database. With respect to both types of errors, syntax and semantic errors, we designed and implemented a software application called Curation-DB allowing to curate (adapt and change) data. In particular, the system lists the logged syntax errors occurring during the data conversion step daily at night. A user can adapt the current input value by specifying a new (target) value for a listed syntax problem. With this specification, the corresponding input value is replaced by the specified value before the next conversion step is started. This specification process can be iteratively applied for a corresponding input value when the syntax problem is not solved by the current specification. The semantic errors need to be first detected separately. Then, a user can specify value changes replacing an existing value with the new specified one. Results & Discussion The Curation-DB application is already in use. Currently, selected quality managers routinely check the listed syntax errors. There are currently more than 2000 of such errors curated. In near future, we will extend this software to manage rules validating research data semantically to automatically detect obvious semantic errors.

Authors: J. Wagner, A. Kiel, Toralf Kirsten

Date Published: 30th Sep 2013

Publication Type: Not specified

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