Pub Date : 2024-11-21DOI: 10.1016/j.annepidem.2024.11.003
Alexander Testa , Jack Tsai
{"title":"History of arrest and firearm ownership among low-income US military veterans","authors":"Alexander Testa , Jack Tsai","doi":"10.1016/j.annepidem.2024.11.003","DOIUrl":"10.1016/j.annepidem.2024.11.003","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 57-59"},"PeriodicalIF":3.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-21DOI: 10.1016/j.annepidem.2024.11.002
SuJung Jung, Ji Young Choi, Pradeep Tiwari, Itai M Magodoro, Shivani A Patel, Ahlam Jadalla, Daesung Choi
Purpose: Using a US nationally representative survey of adults, we aimed to evaluate the association between prevalent diabetes and the uptake of COVID-19 testing, rate of positive testing and symptom severity.
Methods: Data were sourced from the 2020-2021 National Health Interview Survey. COVID-19 outcomes were defined as: (1) test uptake (2) test positivity (3) diagnosis of COVID-19 and (4) severe disease symptoms with a positive COVID-19 test result. We compared the prevalence of COVID-19 outcomes by diabetes status and examined their associations using multivariate adjusted logistic and ordered logistic regression models.
Results: The prevalence of test uptake and test positivity were 50.7% and 9.4% in the US population, respectively. 10.3% were diagnosed with COVID-19 infection by health professionals. There were no statistically significant differences in the outcomes by diabetes status. However, individuals with diabetes were more likely to have severe symptoms. In adjusted regression model, we found no significant associations of diagnosed diabetes with all outcomes.
Conclusions: Our findings contrast with prior evidence derived from hospitalized patients. Researchers and policy makers are encouraged to review the properties of data sources and their impact on public health recommendations, particularly in response to future pandemics.
{"title":"Reevaluating Diabetes and COVID-19 outcomes using national-level data.","authors":"SuJung Jung, Ji Young Choi, Pradeep Tiwari, Itai M Magodoro, Shivani A Patel, Ahlam Jadalla, Daesung Choi","doi":"10.1016/j.annepidem.2024.11.002","DOIUrl":"https://doi.org/10.1016/j.annepidem.2024.11.002","url":null,"abstract":"<p><strong>Purpose: </strong>Using a US nationally representative survey of adults, we aimed to evaluate the association between prevalent diabetes and the uptake of COVID-19 testing, rate of positive testing and symptom severity.</p><p><strong>Methods: </strong>Data were sourced from the 2020-2021 National Health Interview Survey. COVID-19 outcomes were defined as: (1) test uptake (2) test positivity (3) diagnosis of COVID-19 and (4) severe disease symptoms with a positive COVID-19 test result. We compared the prevalence of COVID-19 outcomes by diabetes status and examined their associations using multivariate adjusted logistic and ordered logistic regression models.</p><p><strong>Results: </strong>The prevalence of test uptake and test positivity were 50.7% and 9.4% in the US population, respectively. 10.3% were diagnosed with COVID-19 infection by health professionals. There were no statistically significant differences in the outcomes by diabetes status. However, individuals with diabetes were more likely to have severe symptoms. In adjusted regression model, we found no significant associations of diagnosed diabetes with all outcomes.</p><p><strong>Conclusions: </strong>Our findings contrast with prior evidence derived from hospitalized patients. Researchers and policy makers are encouraged to review the properties of data sources and their impact on public health recommendations, particularly in response to future pandemics.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Violence against pregnant and postpartum individuals is a major public health problem. Homicides during the perinatal period have recently increased, yet these deaths reflect only the most extreme manifestation of violence. Far less is known about trends and disparities in pregnancy-associated violence morbidity. Examining emergency department (ED) utilization for violence-related injuries in this population can shed light on overall incidence and patterns of risk.
Methods
We used longitudinal, all-payer, statewide data from California, comprising all individuals with a live-birth hospital delivery in each year from 2010–2018 (N = 3068,921). We followed annual cohorts of women before and after their delivery hospitalizations to identify ED visits for violent injury. We analyzed trends and disparities in annual incidence rates.
Results
The cumulative incidence of any pregnancy-associated ED visit for violence was 0.84 % overall; incidence increased slightly over the study period (annual ORadj = 1.01, 95 % CI = 1.01,1.02). The highest risk of pregnancy-associated violence was observed in younger individuals, non-Hispanic Black individuals, and Medicaid users.
Conclusion
Our findings suggest risk of pregnancy-associated violence morbidity has increased over the past decade and is amplified for structurally vulnerable populations. The emergency department may be a critical opportunity for screening and providing resources to at-risk individuals.
{"title":"Trends and disparities in violence-related injury morbidity among pregnant and postpartum individuals","authors":"Shaina Sta. Cruz , Claire Margerison , Alison Gemmill , Sandie Ha , Thelma Hurd , Jordan Jensen , Sidra Goldman-Mellor","doi":"10.1016/j.annepidem.2024.11.001","DOIUrl":"10.1016/j.annepidem.2024.11.001","url":null,"abstract":"<div><h3>Purpose</h3><div>Violence against pregnant and postpartum individuals is a major public health problem. Homicides during the perinatal period have recently increased, yet these deaths reflect only the most extreme manifestation of violence. Far less is known about trends and disparities in pregnancy-associated violence morbidity. Examining emergency department (ED) utilization for violence-related injuries in this population can shed light on overall incidence and patterns of risk.</div></div><div><h3>Methods</h3><div>We used longitudinal, all-payer, statewide data from California, comprising all individuals with a live-birth hospital delivery in each year from 2010–2018 (N = 3068,921). We followed annual cohorts of women before and after their delivery hospitalizations to identify ED visits for violent injury. We analyzed trends and disparities in annual incidence rates.</div></div><div><h3>Results</h3><div>The cumulative incidence of any pregnancy-associated ED visit for violence was 0.84 % overall; incidence increased slightly over the study period (annual OR<sub>adj</sub> = 1.01, 95 % CI = 1.01,1.02). The highest risk of pregnancy-associated violence was observed in younger individuals, non-Hispanic Black individuals, and Medicaid users.</div></div><div><h3>Conclusion</h3><div>Our findings suggest risk of pregnancy-associated violence morbidity has increased over the past decade and is amplified for structurally vulnerable populations. The emergency department may be a critical opportunity for screening and providing resources to at-risk individuals.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 50-56"},"PeriodicalIF":3.3,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.annepidem.2024.10.010
Ruvani T. Jayaweera , Dana E. Goin , Ryan G. Wagner , Torsten B. Neilands , Sheri A. Lippman , Kathleen Kahn , Audrey Pettifor , Jennifer Ahern
Purpose
To assess the relationship between school environment and health and behavior outcomes.
Methods
Data are from baseline and first follow-up of the HIV Prevention Trials Network (HPTN) 068 longitudinal trial established in 2012 of adolescent girls and young women in rural Mpumalanga Province, South Africa. Data from 2212 participants are included. We measured the association between four school environment domains: school resources, school safety, negative personal experiences, and school connectedness, and several health and behavior outcomes: depressive symptoms, low attendance, recent pregnancy, recent unprotected sex, transactional sex, and having an older romantic partner. We used a g-computation approach to estimate risk differences (RD) for the longitudinal relationship between the school environment (measured at the individual and school level) on individual health and behavior outcomes, controlling for baseline covariates.
Results
The mean age of participants at baseline was 15.4; mean age at first follow-up was 16.6. Individual baseline perceptions of an unsafe school environment (RD = 3.1 %, 95 % CI: 1.3–5.2 %) and more frequent negative experiences (RD = 4.0 %, 95 % CI: 2.0–5.9 %) were associated with higher absolute risk of depressive symptoms at follow-up. There was an overall trend toward higher risk of pregnancy, unprotected sex, and having an older partner among those who reported fewer school resources, lack of school safety, more negative personal experiences, and lack of school connectedness.
Conclusions
Our findings provide evidence of an overall trend toward higher risk of depression, pregnancy, unprotected sex, and having an older partner among those reporting a worse school environment across four school environment domains.
{"title":"School environment and adolescent health: Results from the HPTN 068 cohort","authors":"Ruvani T. Jayaweera , Dana E. Goin , Ryan G. Wagner , Torsten B. Neilands , Sheri A. Lippman , Kathleen Kahn , Audrey Pettifor , Jennifer Ahern","doi":"10.1016/j.annepidem.2024.10.010","DOIUrl":"10.1016/j.annepidem.2024.10.010","url":null,"abstract":"<div><h3>Purpose</h3><div>To assess the relationship between school environment and health and behavior outcomes.</div></div><div><h3>Methods</h3><div>Data are from baseline and first follow-up of the HIV Prevention Trials Network (HPTN) 068 longitudinal trial established in 2012 of adolescent girls and young women in rural Mpumalanga Province, South Africa. Data from 2212 participants are included. We measured the association between four school environment domains: school resources, school safety, negative personal experiences, and school connectedness, and several health and behavior outcomes: depressive symptoms, low attendance, recent pregnancy, recent unprotected sex, transactional sex, and having an older romantic partner. We used a g-computation approach to estimate risk differences (RD) for the longitudinal relationship between the school environment (measured at the individual and school level) on individual health and behavior outcomes, controlling for baseline covariates.</div></div><div><h3>Results</h3><div>The mean age of participants at baseline was 15.4; mean age at first follow-up was 16.6. Individual baseline perceptions of an unsafe school environment (RD = 3.1 %, 95 % CI: 1.3–5.2 %) and more frequent negative experiences (RD = 4.0 %, 95 % CI: 2.0–5.9 %) were associated with higher absolute risk of depressive symptoms at follow-up. There was an overall trend toward higher risk of pregnancy, unprotected sex, and having an older partner among those who reported fewer school resources, lack of school safety, more negative personal experiences, and lack of school connectedness.</div></div><div><h3>Conclusions</h3><div>Our findings provide evidence of an overall trend toward higher risk of depression, pregnancy, unprotected sex, and having an older partner among those reporting a worse school environment across four school environment domains.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 42-49"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142567866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.annepidem.2024.09.005
Alessandro Rovetta, Mohammad Ali Mansournia
{"title":"Letter to the editor on \"The Conclusion Generator\"","authors":"Alessandro Rovetta, Mohammad Ali Mansournia","doi":"10.1016/j.annepidem.2024.09.005","DOIUrl":"10.1016/j.annepidem.2024.09.005","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"99 ","pages":"Pages 56-57"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142407175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.annepidem.2024.10.004
Rachel R. Yorlets , Youjin Lee , Jason R. Gantenberg
Epidemiologic research questions often focus on evaluating binary outcomes, yet curricula and scientific literature do not always provide clear guidance or examples on selecting and calculating an appropriate measure of association in these scenarios. Reporting inappropriate measures may lead to misleading statistical conclusions. We present a hands-on tutorial that includes annotated code written in an open-source statistical programming language (R) showing readers how to apply, compare, and understand four methods used to estimate a risk or prevalence ratio (or difference), rather than presenting an odds ratio. We will provide guidance on when to use each method, discuss the strengths and limitations of each approach, and compare the results obtained across them. Ultimately, we aim to help trainees, public health researchers, and interdisciplinary professionals develop an intuition for these methods and empower them to implement and interpret these methods in their own research.
{"title":"Calculating risk and prevalence ratios and differences in R: Developing intuition with a hands-on tutorial and code","authors":"Rachel R. Yorlets , Youjin Lee , Jason R. Gantenberg","doi":"10.1016/j.annepidem.2024.10.004","DOIUrl":"10.1016/j.annepidem.2024.10.004","url":null,"abstract":"<div><div>Epidemiologic research questions often focus on evaluating binary outcomes, yet curricula and scientific literature do not always provide clear guidance or examples on selecting and calculating an appropriate measure of association in these scenarios. Reporting inappropriate measures may lead to misleading statistical conclusions. We present a hands-on tutorial that includes annotated code written in an open-source statistical programming language (R) showing readers how to apply, compare, and understand four methods used to estimate a risk or prevalence ratio (or difference), rather than presenting an odds ratio. We will provide guidance on when to use each method, discuss the strengths and limitations of each approach, and compare the results obtained across them. Ultimately, we aim to help trainees, public health researchers, and interdisciplinary professionals develop an intuition for these methods and empower them to implement and interpret these methods in their own research.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"99 ","pages":"Pages 48-53"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.annepidem.2024.09.006
Morten Schmidt , Erik Parner
{"title":"Contextualizing the Conclusion Generator: From the ASA statement to PhD curriculum","authors":"Morten Schmidt , Erik Parner","doi":"10.1016/j.annepidem.2024.09.006","DOIUrl":"10.1016/j.annepidem.2024.09.006","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"99 ","pages":"Pages 54-55"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.annepidem.2024.10.005
Larry R. Hearld , Madeline C. Pratt , Donna Smith , Mariel Parman , Rendi Murphree , Kevin P. Michaels , Stephanie Woods-Crawford , Aadia I. Rana , Lynn T. Matthews
Purpose
In this manuscript we illustrate how implementation science (IS) researchers and practitioners can deploy and integrate existing and novel methods to develop a more comprehensive understanding of organizational context, particularly organizational routines and processes, to inform adaptation and implementation of evidence-based interventions.
Methods
The work reported here was part of a broader investigation of how to adapt and implement a three-component combination intervention in a county health department in Mobile, Alabama. Based on pre-implementation efforts to assess local context and barriers to implementation, we first describe three approaches that can be effectively used to elucidate organizational routines and processes, followed by a description of how these approaches were applied in our study. We conclude with a discussion of lessons learned and recommendations for how these approaches can be applied and improved upon by other IS researchers.
Results/Conclusions
Multiple methods used iteratively and collaboratively with implementation partners can enhance our understanding of nuanced organizational routines and better inform efforts to adapt and implement evidence-based interventions in complex organizational settings.
{"title":"Integrating existing and novel methods to understand organizational context: A case study of an academic-public health department partnership","authors":"Larry R. Hearld , Madeline C. Pratt , Donna Smith , Mariel Parman , Rendi Murphree , Kevin P. Michaels , Stephanie Woods-Crawford , Aadia I. Rana , Lynn T. Matthews","doi":"10.1016/j.annepidem.2024.10.005","DOIUrl":"10.1016/j.annepidem.2024.10.005","url":null,"abstract":"<div><h3>Purpose</h3><div>In this manuscript we illustrate how implementation science (IS) researchers and practitioners can deploy and integrate existing and novel methods to develop a more comprehensive understanding of organizational context, particularly organizational routines and processes, to inform adaptation and implementation of evidence-based interventions.</div></div><div><h3>Methods</h3><div>The work reported here was part of a broader investigation of how to adapt and implement a three-component combination intervention in a county health department in Mobile, Alabama. Based on pre-implementation efforts to assess local context and barriers to implementation, we first describe three approaches that can be effectively used to elucidate organizational routines and processes, followed by a description of how these approaches were applied in our study. We conclude with a discussion of lessons learned and recommendations for how these approaches can be applied and improved upon by other IS researchers.</div></div><div><h3>Results/Conclusions</h3><div>Multiple methods used iteratively and collaboratively with implementation partners can enhance our understanding of nuanced organizational routines and better inform efforts to adapt and implement evidence-based interventions in complex organizational settings.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 34-41"},"PeriodicalIF":3.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.annepidem.2024.10.008
Liming Li , Shengmei Yang , Ruming Li , Jungang Su , Xiaorong Zhou , Xiao Zhu , Ronghua Gao
Background
The gut microbiota has emerged as a pivotal factor in the etiology of uterine-related diseases. This study aims to elucidate the genetic causal link between gut microbiota composition and these conditions, focusing on the systemic impact and uterine pathology to better understand the "Gut-Uterus Axis."
Methods
We utilized pooled data from two different GWAS databases, including data from 209 gut microbiota traits and data from four uterus-related diseases. Bidirectional Mendelian Randomization (MR) approaches, incorporating Bayesian weighting and traditional inverse variance weighting (IVW) methods, were employed to explore causal relationships. The robustness of findings was ensured through sensitivity analyses, outlier testing, and MR-PRESSO analysis.
Results
Seventeen significant associations were identified between gut microbiota traits and uterine-related diseases, suggesting potential causal links. These associations were consistent across sensitivity analyses, affirming the reliability of our results. Conversely, reverse MR analyses did not reveal statistically significant associations between uterine diseases and bacterial traits, indicating a unidirectional influence of gut microbiota on uterine health. These findings highlight the complex interplay within the "Gut-Uterus Axis."
Conclusion
This research establishes a causal relationship between gut microbiota and uterine diseases, advocating for targeted interventions to mitigate associated risks. It underscores the interconnectedness of gut and reproductive health, promoting a holistic approach to management and treatment within the "Gut-Uterus Axis".
{"title":"Unraveling shared and unique genetic causal relationship between gut microbiota and four types of uterine-related diseases: Bidirectional Mendelian inheritance approaches to dissect the \"Gut-Uterus Axis\"","authors":"Liming Li , Shengmei Yang , Ruming Li , Jungang Su , Xiaorong Zhou , Xiao Zhu , Ronghua Gao","doi":"10.1016/j.annepidem.2024.10.008","DOIUrl":"10.1016/j.annepidem.2024.10.008","url":null,"abstract":"<div><h3>Background</h3><div>The gut microbiota has emerged as a pivotal factor in the etiology of uterine-related diseases. This study aims to elucidate the genetic causal link between gut microbiota composition and these conditions, focusing on the systemic impact and uterine pathology to better understand the \"Gut-Uterus Axis.\"</div></div><div><h3>Methods</h3><div>We utilized pooled data from two different GWAS databases, including data from 209 gut microbiota traits and data from four uterus-related diseases. Bidirectional Mendelian Randomization (MR) approaches, incorporating Bayesian weighting and traditional inverse variance weighting (IVW) methods, were employed to explore causal relationships. The robustness of findings was ensured through sensitivity analyses, outlier testing, and MR-PRESSO analysis.</div></div><div><h3>Results</h3><div>Seventeen significant associations were identified between gut microbiota traits and uterine-related diseases, suggesting potential causal links. These associations were consistent across sensitivity analyses, affirming the reliability of our results. Conversely, reverse MR analyses did not reveal statistically significant associations between uterine diseases and bacterial traits, indicating a unidirectional influence of gut microbiota on uterine health. These findings highlight the complex interplay within the \"Gut-Uterus Axis.\"</div></div><div><h3>Conclusion</h3><div>This research establishes a causal relationship between gut microbiota and uterine diseases, advocating for targeted interventions to mitigate associated risks. It underscores the interconnectedness of gut and reproductive health, promoting a holistic approach to management and treatment within the \"Gut-Uterus Axis\".</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 16-26"},"PeriodicalIF":3.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-21DOI: 10.1016/j.annepidem.2024.10.006
Samuel H. Nyarko PhD , Lucy T. Greenberg MS , George R. Saade MD , Ciaran S. Phibbs PhD , Jeffrey S. Buzas PhD , Scott A. Lorch MD , Jeannette Rogowski PhD , Molly Passarella MS , Nansi S. Boghossian PhD
Purpose
We examined the association between iron deficiency anemia (IDA) and severe maternal morbidity (SMM) during delivery and up to 1-year postpartum.
Methods
In a retrospective cohort study across 3 states, we computed adjusted relative risks (aRR) for SMM comparing individuals with IDA versus those without, using modified Poisson regression models.
Results
Among 2459,106 individuals, 10.3 % (n = 252,240) had IDA. Individuals with IDA experienced higher rates of blood transfusion and non-transfusion SMM (329 and 122 per 10,000 deliveries, respectively) than those without IDA (33 and 46 per 10,000 deliveries, respectively). The risk of blood transfusion (aRR: 8.2; 95 % CI 7.9–8.5) and non-transfusion SMM (aRR: 1.9; 95 % CI: 1.8–2.0) were higher among individuals with IDA. The attributable risk per 10,000 deliveries due to IDA for blood transfusion and non-transfusion SMM during delivery were 29.5 (95 % CI: 28.9–30.0) and 5.7 (95 % CI: 5.3–6.2), respectively. Within 1-year postpartum, the relative risk of non-transfusion SMM (aRR:1.3; 95 % CI: 1.2–1.3) was 30 % higher among individuals with IDA.
Conclusion
IDA is associated with increased SMM risk. Addressing IDA in pregnant individuals may reduce SMM rates.
{"title":"Association between iron deficiency anemia and severe maternal morbidity: A retrospective cohort study","authors":"Samuel H. Nyarko PhD , Lucy T. Greenberg MS , George R. Saade MD , Ciaran S. Phibbs PhD , Jeffrey S. Buzas PhD , Scott A. Lorch MD , Jeannette Rogowski PhD , Molly Passarella MS , Nansi S. Boghossian PhD","doi":"10.1016/j.annepidem.2024.10.006","DOIUrl":"10.1016/j.annepidem.2024.10.006","url":null,"abstract":"<div><h3>Purpose</h3><div>We examined the association between iron deficiency anemia (IDA) and severe maternal morbidity (SMM) during delivery and up to 1-year postpartum.</div></div><div><h3>Methods</h3><div>In a retrospective cohort study across 3 states, we computed adjusted relative risks (aRR) for SMM comparing individuals with IDA versus those without, using modified Poisson regression models.</div></div><div><h3>Results</h3><div>Among 2459,106 individuals, 10.3 % (n = 252,240) had IDA. Individuals with IDA experienced higher rates of blood transfusion and non-transfusion SMM (329 and 122 per 10,000 deliveries, respectively) than those without IDA (33 and 46 per 10,000 deliveries, respectively). The risk of blood transfusion (aRR: 8.2; 95 % CI 7.9–8.5) and non-transfusion SMM (aRR: 1.9; 95 % CI: 1.8–2.0) were higher among individuals with IDA. The attributable risk per 10,000 deliveries due to IDA for blood transfusion and non-transfusion SMM during delivery were 29.5 (95 % CI: 28.9–30.0) and 5.7 (95 % CI: 5.3–6.2), respectively. Within 1-year postpartum, the relative risk of non-transfusion SMM (aRR:1.3; 95 % CI: 1.2–1.3) was 30 % higher among individuals with IDA.</div></div><div><h3>Conclusion</h3><div>IDA is associated with increased SMM risk. Addressing IDA in pregnant individuals may reduce SMM rates.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"100 ","pages":"Pages 10-15"},"PeriodicalIF":3.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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