Charting the life course: Emerging opportunities to advance scientific approaches using life course research

Hanson, Heidi A.; Leiser, Claire L.; Bandoli, Gretchen; Pollock, Brad H.; Armstrong, Daniel; Dozier, Ann; Weiskopf, Nicole G.; Monaghan, Maureen; Davis, Ann M.; Eckstrom, Elizabeth; Weng, Chunhua; Tobin, Jonathan N.; Kaskel, Frederick J.; Schleiss, Mark R.; Szilâgyi, Peter G.; Dykes, Carrie; Barkin, Shari L.

doi:10.1017/cts.2020.492

“…89 Life research is an example of integration of multiple data types from diverse sources (e.g., institutional data warehouses and research repositories) to capture the complexity of health trajectories. 14,90,91 Incorporation of geocoded data and environmental factors as well as patient-reported measures such as social well-being into the electronic health record represent concrete strategies for greater inclusion and more accurate representation of populations currently underrepresented in research and permit analysis of the impact of social determinants of health on disease pathogenesis and response to therapies. 91 A significant note of caution must be raised about racial bias in the use of physiology and electronic health record-based Big Data.…”

Section: Research Gaps and Future Directionsmentioning

confidence: 99%

Improving child health through Big Data and data science

Vesoulis

¹

,

Husain

²

,

Cole

³

2022

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Child health is defined by a complex, dynamic network of genetic, cultural, nutritional, infectious, and environmental determinants at distinct, developmentally determined epochs from preconception to adolescence. This network shapes the future of children, susceptibilities to adult diseases, and individual child health outcomes. Evolution selects characteristics during fetal life, infancy, childhood, and adolescence that adapt to predictable and unpredictable exposures/stresses by creating alternative developmental phenotype trajectories. While child health has improved in the United States and globally over the past 30 years, continued improvement requires access to data that fully represent the complexity of these interactions and to new analytic methods. Big Data and innovative data science methods provide tools to integrate multiple data dimensions for description of best clinical, predictive, and preventive practices, for reducing racial disparities in child health outcomes, for inclusion of patient and family input in medical assessments, and for defining individual disease risk, mechanisms, and therapies. However, leveraging these resources will require new strategies that intentionally address institutional, ethical, regulatory, cultural, technical, and systemic barriers as well as developing partnerships with children and families from diverse backgrounds that acknowledge historical sources of mistrust. We highlight existing pediatric Big Data initiatives and identify areas of future research. Impact Big Data and data science can improve child health. This review highlights the importance for child health of child-specific and life course-based Big Data and data science strategies. This review provides recommendations for future pediatric-specific Big Data and data science research.

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“…Широкое распространение ЦМВИ, инвалидизация новорожденных детей, серьезные последствия для людей из групп риска [32], повышение роли ЦМВИ как причины заболеваний человека на протяжении всей жизни, включая онкологические болезни и иммунное старение, отсутствие системы эпидемиологического надзора определяют тяжесть бремени инфицирования ЦМВ [33]. Для обеспечения контроля над заболеваемостью ЦМВИ в настоящее время ведутся активные разработки вакцины для всеобщей иммунизации [34].…”

Section: ограничения исследованияunclassified

Cytomegalovirus Infection in Adolescents of Russian Federation: Results of Cross-Sectional Population Analysis of Seroprevalence

Dubonosova

¹

,

Namazova-Baranova

²

,

Вишнева

³

et al. 2021

Pediatr. farmakol.

1

0

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Background. Cytomegalovirus infection (CMVI) is the reason of high mortality in perinatal period, disability in children from risk groups with further development of congenital malformations and chronic diseases. Clear understanding of epidemiology and determination of focus population groups is crucial for development of measures and algorithms of congenital CMVI prevention.Objective. The aim of the study is to study CMVI seroprevalence among immunocompetent adolescents in Russian Federation with reference to the gender, regional, social and economic, and age factors.Methods. We have used for our study data from the survey of senior schoolchildren from 7 municipalities representing various regions of Russian Federation: group 1 (10–12 years old) and group 2 (14–16 years old). The study of CMVI seroprevalence and immune response was performed via the analysis of the level of IgG antibodies to cytomegalovirus (CMV) in blood serum. The social and economic well-being of the region was determined by "RIA Rating" experts.Results. Serological prevalence of CMVI in the study group of adolescents (n = 1403) was 70.6% (n = 990). There were no statistically significant gender differences in the distribution of seropositive children in regions (p = 0.525). Infection in boys (72.6%; n = 455; median age — 12.9 (11.0; 14.9)) did not prevail over the infection in girls (68.8%; n = 535; median age — 13.1 (11.0; 14,9)); p = 0,117. The overall prevalence of CMVI increased statistically significant with age — from 68% (n = 486) in group 1 to 73% (n = 504) in group 2 (p = 0.036). The prevalence of CMVI varied statistically significant by region (p = 0.003). There was no correlation between the regional seropositive level and the social and economic situation in the region (r = 0.034, p = 0.192). Immune response intensity did not differ by age, gender, and region with the antibody median of 88.9 CU/ml.Conclusion. More than half of adolescents (by the age of 10) in Russian Federation are infected, and infection increases with approaching to childbearing age, however, age is not the only aspect associated with serological status. Factors affecting immune response intensity require further study. Understanding of the CMV prevalence among children is crucial for determining future prevention approaches in target groups.

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“…Широкое распространение ЦМВИ, инвалидизация новорожденных детей, серьезные последствия для людей из групп риска [32], повышение роли ЦМВИ как причины заболеваний человека на протяжении всей жизни, включая онкологические болезни и иммунное старение, отсутствие системы эпидемиологического надзора определяют тяжесть бремени инфицирования ЦМВ [33]. Для обеспечения контроля над заболеваемостью ЦМВИ в настоящее время ведутся активные разработки вакцины для всеобщей иммунизации [34].…”

Section: ограничения исследованияunclassified

Cytomegalovirus Infection in Adolescents of Russian Federation: Results of Cross-Sectional Population Analysis of Seroprevalence

Dubonosova

¹

,

Namazova-Baranova

²

,

Вишнева

³

et al. 2021

Pediatr. farmakol.

4

0

View full text Add to dashboard Cite

Background. Cytomegalovirus infection (CMVI) is the reason of high mortality in perinatal period, disability in children from risk groups with further development of congenital malformations and chronic diseases. Clear understanding of epidemiology and determination of focus population groups is crucial for development of measures and algorithms of congenital CMVI prevention.Objective. The aim of the study is to study CMVI seroprevalence among immunocompetent adolescents in Russian Federation with reference to the gender, regional, social and economic, and age factors.Methods. We have used for our study data from the survey of senior schoolchildren from 7 municipalities representing various regions of Russian Federation: group 1 (10–12 years old) and group 2 (14–16 years old). The study of CMVI seroprevalence and immune response was performed via the analysis of the level of IgG antibodies to cytomegalovirus (CMV) in blood serum. The social and economic well-being of the region was determined by "RIA Rating" experts.Results. Serological prevalence of CMVI in the study group of adolescents (n = 1403) was 70.6% (n = 990). There were no statistically significant gender differences in the distribution of seropositive children in regions (p = 0.525). Infection in boys (72.6%; n = 455; median age — 12.9 (11.0; 14.9)) did not prevail over the infection in girls (68.8%; n = 535; median age — 13.1 (11.0; 14,9)); p = 0,117. The overall prevalence of CMVI increased statistically significant with age — from 68% (n = 486) in group 1 to 73% (n = 504) in group 2 (p = 0.036). The prevalence of CMVI varied statistically significant by region (p = 0.003). There was no correlation between the regional seropositive level and the social and economic situation in the region (r = 0.034, p = 0.192). Immune response intensity did not differ by age, gender, and region with the antibody median of 88.9 CU/ml.Conclusion. More than half of adolescents (by the age of 10) in Russian Federation are infected, and infection increases with approaching to childbearing age, however, age is not the only aspect associated with serological status. Factors affecting immune response intensity require further study. Understanding of the CMV prevalence among children is crucial for determining future prevention approaches in target groups.

show abstract

Charting the life course: Emerging opportunities to advance scientific approaches using life course research

Cited by 9 publications

References 60 publications

Improving child health through Big Data and data science

Improving child health through Big Data and data science

Cytomegalovirus Infection in Adolescents of Russian Federation: Results of Cross-Sectional Population Analysis of Seroprevalence

Cytomegalovirus Infection in Adolescents of Russian Federation: Results of Cross-Sectional Population Analysis of Seroprevalence

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