scholarly journals Program for Studying Intergenerational Transmissions in Infant Mortality Using the Intermediate Data Structure (IDS)

2018 ◽  
Vol 7 ◽  
pp. 11-27
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Infant Mortality ◽  
Demographic Data ◽  
Intergenerational Transfers ◽  
Infant Deaths ◽  
Intermediate Data ◽  
Different Populations ◽  
Social And Cultural Factors ◽  
Death Clustering ◽  
Intergenerational Transmissions

Studies conducted in historical populations and developing countries have evidenced the existence of clustering in infant deaths, which could be related to genetic inheritance and/or to social and cultural factors such as education, socioeconomic status or parental care. A transmission of death clustering has also been found across generations. One way of expanding the knowledge on intergenerational transfers in infant mortality is by conducting comparable studies across different populations. The Intermediate Data Structure (IDS) was developed as a strategy aimed at simplifying the collecting, storing and sharing of historical demographic data. The current work presents two programs that were developed in STATA to construct a dataset for analysis and run statistical models to study intergenerational transfers in infant mortality using databases that are stored in the IDS. The programs use information stored in the IDS tables and after elaborating such information produce Excel files with results. They can be used with any longitudinal database constructed from church books, civil registers, or population registers.

scholarly journals Intergenerational Transfers in Infant Mortality in Southern Sweden, 1740-1968

2018 ◽  
Vol 7 ◽  
pp. 88-105
Author(s):  
Luciana Quaranta
Keyword(s):  
Socioeconomic Status ◽  
Infant Mortality ◽  
Southern Sweden ◽  
Infant Deaths ◽  
Intermediate Data ◽  
Rural Parishes ◽  
Social And Cultural Factors ◽  
Death Clustering ◽  
Early Life Exposures ◽  
Intergenerational Transmissions

Studies conducted in historical populations and developing countries have evidenced the existence of clustering in infant deaths, which could be related to genetic inheritance, early life exposures, and/or to social and cultural factors such as education, socioeconomic status or parental care. A transmission of death clustering has also been found across generations. This paper is one of five studies that analyses intergenerational transmissions in infant mortality by using a common program to create the dataset for analysis and run the statistical models with data stored in the Intermediate Data Structure. The results of this study show that in five rural parishes in Scania, the southernmost province of Sweden, during the years 1740-1968 infant mortality was transmitted across generations. Children whose maternal grandmothers experienced two or more infant deaths had higher risks of dying in infancy. The results remained consistent when restricting the sample only to cases where the grandmother had been observed for her entire reproductive history or when controlling for socioeconomic status. When running sex specific models, significant effects of the number of infant deaths of the grandmother were observed for girls but not for boys.

scholarly journals Intergenerational Transfers of Infant Mortality in 19th-Century Northern Sweden

2018 ◽  
Vol 7 ◽  
pp. 106-122
Author(s):  
Göran Broström ◽  
Sören Edvinsson ◽  
Elisabeth Engberg
Keyword(s):  
Infant Mortality ◽  
Infant Death ◽  
Comparative Research ◽  
Demographic Data ◽  
Intergenerational Transfers ◽  
Intermediate Data ◽  
International Comparative ◽  
Further Development ◽  
Analytical Power ◽  
Intergenerational Transmissions

This contribution is part of an international comparative initiative with the aim to assess the analytical power of the Intermediate Data Structure (IDS) in a study of possible intergenerational transmissions of death in infancy. An evaluation of the data in applied research will be useful for further development of the IDS structure and for its future use in comparative research. An additional methodological aim for this part of the study is to evaluate and compare different models for statistical analysis of intergenerational transfers. The analysis is based on a cohort of mothers born 1826-1854, whose experiences of infant mortality are compared to the ones of the previous generation, the grandmothers. Data are collected from Swedish parish records, available in the database POPUM at the Demographic Data Base in Umeå. The analysis shows a clear association between infant mortality among mothers and grandmothers. The probability of an infant death for a woman is increased if her mother also had experienced an infant death. Having tested for different approaches of analysis, we found that simple models with few restrictive assumptions gave similar results as more complicated models. Since it is easy to feel confident in the models with the weakest assumptions, we argue that such models are preferred for this type of analysis.

scholarly journals Introduction: Intergenerational Transmissions of Infant Mortality using the Intermediate Data Structure (IDS)

2018 ◽  
Vol 7 ◽  
pp. 1-10
Author(s):  
Luciana Quaranta ◽  
Hilde Leikny Sommerseth
Keyword(s):  
Data Structure ◽  
Infant Mortality ◽  
Empirical Studies ◽  
Special Issue ◽  
Maternal Line ◽  
Demographic Research ◽  
Intermediate Data ◽  
Current Article ◽  
Death Clustering ◽  
Intergenerational Transmissions

It has previously been shown that infant mortality clusters in a subset of families, a phenomenon which was observed in historical populations as well as contemporary developing countries. A transmission of death clustering across generations has also been shown in Belgium, but it is unknown whether such effects are specific to the studied context or are also found in other areas. The current article introduces a special issue devoted to analysing intergenerational transmissions of infant mortality across the maternal line in Belgium, the Netherlands, northern and southern Sweden, and Norway. Taking advantage of the Intermediate Data Structure (IDS), the five empirical studies created datasets for analysis and ran statistical models using exactly the same programs, which are also published within the special issue. These works are the first set of studies using the IDS on several databases for comparative purposes. Consistent results across the studied contexts were shown: transfers of infant mortality across the maternal line were seen in all five areas. In addition, the works have shown that there are large advantages of adopting the IDS for historical demographic research. The structure has in fact allowed researchers to conduct studies which were fully comparable, transparent and replicable.

scholarly journals STATA Programs for Using the Intermediate Data Structure (IDS) to Construct Files for Statistical Analysis

2016 ◽  
Vol 3 ◽  
pp. 1-19
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Statistical Analysis ◽  
Open Access ◽  
Demographic Data ◽  
Intermediate Data ◽  
Common Structure ◽  
Current Article ◽  
Using Data ◽  
New Variables ◽  
Extract Information

The Intermediate Data Structure (IDS) provides a common structure for storing and sharing historical demographic data. The structure also facilitates the construction of different open-access software to extract information from these tables and construct new variables. The article Using the Intermediate Data Structure (IDS) to Construct Files for Analysis (Quaranta 2015) presented a series of concepts and programs that allow the user to construct a rectangular episodes file for longitudinal statistical analysis using data stored in the IDS. The current article discusses, in detail, each of these programs, describing their technicalities, structure and syntax, and also explaining how they can be used.

scholarly journals Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data

2014 ◽  
Vol 1 ◽  
pp. 27-46
Author(s):  
Finn Hedefalk ◽  
Lars Harrie ◽  
Patrick Svensson
Keyword(s):  
Data Structure ◽  
Demographic Data ◽  
Extended Version ◽  
Intermediate Data ◽  
Common Structure ◽  
Geographic Data ◽  
Extensible Markup ◽  
Geographic Datasets ◽  
Historical Databases

The Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The geographic data that will be stored in IDS-Geo are primarily buildings and/or property units, and the purpose of these geographic data is mainly to link individuals to places in space. When we want to assign such detailed spatial locations to individuals (in times before there were any detailed house addresses available), we often have to create tailored geographic datasets. In those cases, there are benefits of storing geographic data in the same structure as the demographic data. Moreover, we propose the export of data from IDS-Geo using an eXtensible Markup Language (XML) Schema. IDS-Geo is implemented in a case study using historical property units, for the period 1804 to 1913, stored in a geographically extended version of the Scanian Economic Demographic Database (SEDD). To fit into the IDS-Geo data structure, we included an object lifeline representation of all of the property units (based on the snapshot time representation of single historical maps and poll-tax registers). The case study verifies that the IDS-Geo model is capable of handling geographic data that can be linked to demographic data.

scholarly journals Reflections on the Use of the Intermediate Data Structure (IDS) in Historical Demographic Research

2021 ◽  
Vol 10 ◽  
pp. 76-80
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Demographic Data ◽  
Demographic Research ◽  
Intermediate Data ◽  
Micro Level

The Intermediate Data Structure (IDS) was developed as a strategy aimed at standardizing the dissemination of micro-level historical demographic data. The structure provides a common and clear data strategy which facilitates studies that consider several databases, and the development and exchange of software. Based on my own experiences from working with the IDS, in this article I provide reflections on the use of IDS to create datasets for analysis and to conduct comparative demographic research.

scholarly journals The Intergenerational Transfer of Infant Mortality in Northern Norway during the 19th and Early 20th Centuries

2018 ◽  
Vol 7 ◽  
pp. 69-87 ◽  
Author(s):  
Hilde Leikny Sommerseth
Keyword(s):  
Infant Mortality ◽  
Intergenerational Transmission ◽  
Infant Death ◽  
Intergenerational Transfer ◽  
Maternal Line ◽  
Northern Norway ◽  
Infant Deaths ◽  
Intermediate Data ◽  
19Th And 20Th Century ◽  
Longitudinal Dataset

This paper is one of a series of five studying the intergenerational transfer of infant mortality down the maternal line. All five studies share the same theoretical and methodological design, and use data derived from a standard database format: the Intermediate Data Structure (IDS). The data for the research reported in this paper were derived from a longitudinal dataset covering the 19th and 20th century population of the province of Troms in Northern Norway. Our results suggest that there was an element of intergenerational transmission in women’s risk of experiencing an infant death; the children of a woman whose mother had had a high number of infant deaths also had a greater risk of dying before their first birthday. The risk of an infant death occurring among the children of daughters from such ‘high risk’ families was at least 30 per cent higher than that amongst infants born to the daughters of mothers who had experienced zero infant deaths.

scholarly journals Like Mother, Like Daughter. Intergenerational Transmission of Infant Mortality Clustering in Zeeland, the Netherlands, 1833-1912

2018 ◽  
Vol 7 ◽  
pp. 28-46
Author(s):  
Ingrid K. Van Dijk ◽  
Kees Mandemakers
Keyword(s):  
Infant Mortality ◽  
The Netherlands ◽  
Intergenerational Transmission ◽  
Comparative Research ◽  
Early Death ◽  
Demographic Characteristics ◽  
Infant Survival ◽  
Infant Deaths ◽  
Intermediate Data ◽  
The Family

The burden of infant mortality is not shared equally by all families, but clusters in high risk families. As yet, it remains unclear why some families experience more infant deaths than other families. Earlier research has shown that the risk of early death among infants may at least partially be transmitted from grandmothers to mothers. In this paper, we focus on the intergenerational transmission of mortality clustering in the Netherlands in the province of Zeeland between 1833 and 1912, using LINKS Zeeland, a dataset containing family reconstitutions based on civil certificates of birth, marriage and death. We assess whether intergenerational transmission of mortality clustering occurred in Zeeland, and if so, whether it can be explained on the basis of the demographic characteristics of the families in which the infants were born. In addition, we explore the opportunities for comparative research using the Intermediate Data Structure (IDS). We find that mortality clustering is indeed transmitted from grandmothers to mothers, and that the socioeconomic status of the family, the survival of mothers and fathers, and the demographic characteristics of the family affected infant survival. However, they explain the heterogeneity in infant mortality at the level of the mother only partially.

scholarly journals Using the Intermediate Data Structure (IDS) to Construct Files for Statistical Analysis

2015 ◽  
Vol 2 ◽  
pp. 86-107
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Statistical Analysis ◽  
Demographic Data ◽  
Intermediate Data ◽  
Micro Level ◽  
And Storage

The use of longitudinal historical micro-level demographic data for research presents many challenges. The Intermediate Data Structure (IDS) was developed to try to solve some of these challenges by facilitating the storing and sharing of such data. This article proposes an extension to the IDS, which allows the standardization and storage of constructed variables. It also describes how to produce a rectangular episodes file for statistical analysis from data stored in the IDS and presents programs developed for such purpose.

scholarly journals Health capabilities and the determinants of infant mortality in Brazil, 2004–2015: an innovative methodological framework

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alexandre Bugelli ◽  
Roxane Borgès Da Silva ◽  
Ladislau Dowbor ◽  
Claude Sicotte
Keyword(s):  
Infant Mortality ◽  
Educational Attainment ◽  
Health Professionals ◽  
Capita Income ◽  
Mortality Rates ◽  
Fertility Rate ◽  
Employment Rate ◽  
Infant Deaths ◽  
Bolsa Familia ◽  
Per Capita

Abstract Background Despite the implementation of a set of social and health policies, Brazil has experienced a slowdown in the decline of infant mortality, regional disparities and persistent high death levels, raising questions about the determinants of infant mortality after the implementation of these policies. The objective of this article is to propose a methodological approach aiming at identifying the determinants of infant mortality in Brazil after the implementation of those policies. Method A series of multilevel panel data with fixed effect nested within-clusters were conducted supported by the concept of health capabilities based on data from 26 Brazilian states between 2004 and 2015. The dependent variables were the neonatal, the infant and the under-five mortality rates. The independent variables were the employment rate, per capita income, Bolsa Família Program coverage, the fertility rate, educational attainment, the number of live births by prenatal visits, the number of health professionals per thousand inhabitants, and the access to water supply and sewage services. We also used different time lags of employment rate to identify the impact of employment on the infant mortality rates over time, and household income stratified by minimum wages to analyze their effects on these rates. Results The results showed that in addition to variables associated with infant mortality in previous studies, such as Bolsa Família Program, per capita income and fertility rate, other factors affect child mortality. Educational attainment, quality of prenatal care and access to health professionals are also elements impacting infant deaths. The results also identified an association between employment rate and different infant mortality rates, with employment impacting neonatal mortality up to 3 years and that a family income below 2 minimum wages increases the odds of infant deaths. Conclusion The results proved that the methodology proposed allowed the use of variables based on aggregated data that could hardly be used by other methodologies.

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