scholarly journals Agreement between maternal recall of distant first birth events with hospital birth records: A cohort study

Author(s):  
Mindy Ebrahimoff

Abstract BACKGROUND Inter and intra-generational birth cohorts could be particularly useful for predicting the likelihood of labour and birth events for nulliparous women. However, maternal recall of their first childbirth may be imprecise, and hospital records can be inaccurate. Establishing the extent of agreement between mothers’ recall and hospital reports of historical first birth events could be the basis of a prediction tool that could contribute to better health care practices during daughter’s perinatal period. METHODS In 2015, women who had their first baby between 1967 and 1997 were asked to recall gravidity, method of labour onset, type of pain relief, length of labour, birth outcome, and infant’s gender, birthweight and gestational age ≥17 years postpartum. Responses were compared to hospital birth records. Agreement was evaluated using Bland-Altman’s plots and Kappa statistics (k). Logistic regression modeling was used to determine factors influencing discrepant recall. RESULTS Of 150 questionnaires distributed, 101 records were complete. Up to 49 years after birth there was strong agreement for birthweight measured at interval (mean discrepancy -28.69g, SD =170.91g, Bland-Altman 95% limits of agreement (-363.66g, 306.28g)) and category level birthweight k=0.83, good agreement for gestational age (GA) in weeks, at interval level (mean difference=0, SD =0.90, Bland-Altman 95% limits of agreement (-1.766, 1.766)) and at category level GA k=0.56. There was moderate agreement for labour length (≤10hrs/>10hrs) k=0.54; 43% of records did not record this information. For gravidity k=0.43, labour onset k=0.79; any pain relief k=0.61; and birth outcome k=0.91. Univariate logistic regression showed better agreement on infant birthweight in women with higher levels of education, lower agreement for onset of labour method with increasing maternal age at birth, and higher agreement for use of pethidine, but lower agreement for use of epidural in women who had their first babies more recently. CONCLUSIONS Mothers accounts of first birth events generally agree with hospital records. Familial birth data may contribute to more individualised care for nulliparous women, and may limit rising interventions based on population level guidelines. Future research in other settings is warranted before diagnostic criteria may be used in clinical settings.

2021 ◽  
pp. bmjsrh-2020-200795
Author(s):  
Blair G Darney ◽  
Evelyn Fuentes-Rivera ◽  
Biani Saavedra-Avendano ◽  
Patricio Sanhueza-Smith ◽  
Raffaela Schiavon

IntroductionWe examined parity and age among women seeking an abortion in Mexico City’s public first-trimester abortion programme, Interrupcion Legal de Embarazo (ILE). We hypothesised that younger women, especially students, used abortion to prevent first births while older women used abortion to limit births.MethodsWe used clinical data from a sample of 47 462 women who had an abortion between 2007 and 2016 and classified them as nulliparous or parous according to previous births prior to the abortion. We used logistic regression to identify sociodemographic and clinical factors associated with using abortion to prevent a first birth (nulliparous) versus limiting births (parous) and calculated absolute multivariable predicted probabilities.ResultsOverall, 41% of abortions were in nulliparous women seeking to prevent a first birth, and 59% were in women who already had one or more children. The adjusted probability of using abortion to prevent a first birth was 80.4% (95% CI 78.3 to 82.4) for women aged 12–17 years and 54.3% (95% CI 51.6 to 57.0) for women aged 18–24 years. Adolescents (aged 12–17 years) who were employed or students had nearly 90% adjusted probability of using abortion to prevent a first birth (employed 87.8%, 95% CI 82.9 to 92.8; students 88.5%, 95% CI 82.9 to 94.1). At all ages, employed women and students had higher probabilities of using abortion to prevent a first birth compared with unemployed women and women who work in the home.ConclusionLegal first-trimester abortion services in Mexico can help prevent first births in adolescents, especially students.


Polar Biology ◽  
2018 ◽  
Vol 42 (2) ◽  
pp. 433-440 ◽  
Author(s):  
Daniel Cárcamo ◽  
Marlene Pizarro ◽  
Muriel Orellana ◽  
Lily Muñoz ◽  
Guido Pavez ◽  
...  

2018 ◽  
Vol 134 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Elizabeth MacQuillan ◽  
Amy Curtis ◽  
Kathleen Baker ◽  
Rajib Paul

Objectives: The incidence of gestational diabetes mellitus (GDM) in the United States has increased during the past several decades. The objective of this study was to use birth records and a combination of statistical and geographic information system (GIS) analyses to evaluate GDM rates among subgroups of pregnant women in Michigan. Materials and Methods: We obtained data on maternal demographic and health-related characteristics and regions of residence from 2013 Michigan birth records. We geocoded (ie, matched to maternal residence) the birth data, calculated proportions of births to women with GDM, and used logistic regression models to determine predictors of GDM. We calculated odds ratios (ORs) from the exponentiated beta statistic of the logistic regression test. We also used kernel density estimations and local indicators of spatial association (LISA) analyses to determine GDM rates in regions in the state and identify GDM hot spots (ie, areas with a high GDM rate surrounded by areas with a high GDM rate). Results: We successfully geocoded 104 419 of 109 168 (95.6%) births in Michigan in 2013. Of the geocoded births, 5185 (5.0%) were to mothers diagnosed with GDM. LISA maps showed a hot spot of 8 adjacent counties with high GDM rates in southwest Michigan. Of 11 064 births in the Southwest region, 829 (7.5%) were to mothers diagnosed with GDM, the highest rate in the state and a result confirmed by geospatial analyses. Practice Applications: Birth data and GIS analyses may be used to measure statewide pregnancy-associated disease risk and identify populations and geographic regions in need of targeted public health and maternal–child health interventions.


1995 ◽  
Vol 10 (7) ◽  
pp. 326-330 ◽  
Author(s):  
E Franzek ◽  
G Stöber

SummaryOn the basis of 24 maternity hospital records, the current study investigated the validity of maternal recall and the relationship of maternal infections during pregnancy and obstetric complications (OCs) to different diagnostic subgroups of endogenous psychoses on which we reported previously in this journal. Maternal recall showed good agreement to maternity hospital records in the Lewis and Murray scale (ϑ = 0.74). With regard to infectious diseases during pregnancy maternal recall and records showed a weaker, but also good correlation (ϑ = 0.18). Psychoses with low genetic loading had more OCs than psychoses with high genetic loading. Maternal infectious diseases, especially during the fourth or fifth month of gestation, were significantly allocated to Leonhard's systematic schizophrenias. Data from maternity hospital records support our report that infectious diseases during midgestation and further perinatal complications seem to be important etiologic factors in systematic forms of schizophrenia without marked familial loading.


1990 ◽  
Vol 20 (1) ◽  
pp. 89-94 ◽  
Author(s):  
Eadbhard O'Callaghan ◽  
Conall Larkin ◽  
John L. Waddington

SYNOPSISThe significance of the excess of obstetric complications which appears to characterize the histories of schizophrenic patients is critically dependent on the validity of the source of obstetric information, especially when this is obtained by maternal recall. Twenty-one biological mothers of 17 schizophrenic and four other patients were interviewed for their recollections of individual events characterizing the pregnancy and delivery relating to each patient. These were then compared with those events documented in maternity hospital records. Only in two of the 21 instances (9·5%) were inconsistencies of detail apparent which would have affected the designation of the relevant patient as having, or as not having, experienced major obstetric complication(s). It is concluded that maternal recall can be a surprisingly accurate source of obstetric information in relation to research on schizophrenia.


2020 ◽  
Author(s):  
Mayssa Traboulsi ◽  
Zainab El Alaoui Talibi ◽  
Abdellatif Boussaid

Abstract Background: Preterm Birth (PTB) can negatively affect the health of mothers as well as infants. Prediction of this gynecological complication remains difficult especially in Middle and Low-Income countries because of limited access to specific tests and data collection scarcity. Multiparous women in our study presented a higher PTB prevalence compared to nulliparous women. Methods: In a cohort study from Northern Lebanon of 1996 women, 922 were multiparous presenting a PTB prevalence of 8%. We analyzed the personal, demographic, and health indicators available for this group of women. We compared 4 modified logistic regression models (up-sampling, lasso penalized regression) to develop a nomogram that can screen for preterm in multi-parous women. The models were trained and validated on different data sets.Results: The best PTB prediction of the Logistic regression model reached around 88%. This was obtained using a Logistic Regression Model trained on up-sampled datasets and LASSO (Least Absolute Shrinkage and Selection Operator) penalized. The regression coefficients of the 6 selected variables (Pre-hemorrhage, Social status, Residence, Age, BMI, and Weight gain) were used to create a nomogram to screen multiparous women for PTB risk. Conclusions: The nomogram based on readily available indicators for multiparous women reasonably predicted most of the at PTB risk women. This tool will allow physicians to screen women that represent a high risk for spontaneous preterm birth and run furthermore adequate additional tests leading to better medical surveillance that can reduce PTB incidence.


2017 ◽  
Vol 2 (4) ◽  
pp. 178-183
Author(s):  
Faegheh Golalizadeh Bibalan ◽  
Fatemeh Shobeiri ◽  
Akram Ranjbar ◽  
Pooran Hagian

Introduction: One of the health system concerns is the use of medications for pain relief during labor and its side effects. Therefore, the aim of this study was to investigate the effect of epiduralspinal anesthesia (combined anesthesia [CA]) on labor outcome and satisfaction in pregnant women. Methods: In this randomized controlled trial study, we included 80 nulliparous women who had been admitted to Fatemieh hospital (Hamadan, Iran) during 2015-2016 due to spontaneous onset of labor. They were randomly assigned into 2 groups of 40, one group with CA versus normal vaginal delivery (NVD) group. Data were collected by using of demographic questionnaire, satisfaction questionnaire, and baby truck scales. Data were analyzed by descriptive and analytical statistics in SPSS version 16.0. Results: Average maternal age (mean ± SD) in the CA group was 26.94 ± 4.34 and in the NVD group was 25.89 ±5.18, respectively. There was a significant difference between the 2 groups in terms of length of second stage of labor (P=0.001), headache (P=0.04), and Apgar score (first minute) (P=0.001). Chi-square test showed a significant difference between the 2 groups in terms of satisfaction with childbirth (P=0.004). Conclusion: In this study, labor pain relief by using the spinal-epidural anesthesia (CA) increased the labor satisfaction. Nevertheless, this approach was associated with some maternal and neonatal complications such as: headaches, length of third stage of labor, and low Apgar score. It seems that the use of this method for painless delivery requires further studies.


Author(s):  
K. A. Asosega ◽  
K. Opoku-Ameyaw ◽  
D. Otoo ◽  
M. K. Mac-Ocloo ◽  
R. Ayinzoya

Population increases with time through birth, and researchers have often used either Logistic regression model or Discriminant analysis to study and classify birth outcomes. In this paper, the authors sought to investigate the sensitivity of the two methods used separately to explain and classify birth outcomes under different training and test samples. Out of 5000 birth outcomes data comprising of 1250 stillbirth cases and 3750 live births and with four test samples (50%, 40%, 30% and 25%). The Discriminant Analysis averagely correctly classified 89.8% of birth outcome cases compared to 82.4% for the logistic regression. The Discriminant analysis on the average correctly predicted 94.2% of live births compared to 83.1% for the Logistic regression. On stillbirth, 75.7% and 80.9% success rates were recorded for Discriminant Analysis and Logistic regression respectively. All predictors (Maternal Age, Gestational period, fetus weight, parity and Gravida) were statistically significant (p-value < 0.01) in determining birth outcomes of pregnancies in both methods. The results showed that, both techniques are almost similar in predicting birth outcome. However, the Discriminant analysis is preferred for the 25% and 50% test samples whiles, the logistic regression performed well under the 30% and 40% test sample data.


2020 ◽  
Vol 8 (9) ◽  
pp. 358-367
Author(s):  
O. Akangoziri ◽  
C. N. Okoli

This study examined comparison of the Multiple logistic regression, Linear discriminant analysis and Quadratic discriminant in estimating the infant birth outcome and misclassification error rate of birth outcomes with factors of infant mortality in Anambra State, Nigeria. The birth outcomes of interest were the Neonatal death, Still birth and Alive. Secondary source of data were obtained from the records department of General Hospital Onitsha from 2007-2016. The data comprises of Status of infant birth, Mothers parity, Age of mother, Weight of baby, Mothers Education Status, Number of Bookings before gestation and Gestation Age. The data analysis is performed using R-software. The result of the findings from the multiple logistic regression showed that Mothers Education Status (MES) and Booking contributed significantly on the logistic model while factors of Parity, Sex, Age of Mother (AOM), Year, GA and Birth Weight (BW) were found to be insignificant on birth outcomes. Also observed that the misclassification error rate for birth outcome for the said approach is found to be 0.5992 (59.92%). More so, findings of the study equally showed that the prior probabilities of the groups for the linear and quadratic discriminant analysis were 0.228503, 0.40168 and 0.36981 for Alive, Neonatal death and Still birth respectively. Further findings revealed that the Mothers Education Status and Bookings Status have the greatest impact for first and second linear function respectively. In addition, the result of the misclassification error rate for birth outcome using the linear discriminant analysis is 0.5931 (59.31%). The misclassification error rate for birth outcome based on   quadratic discriminant analysis is 0.5956 (59.56%). Based on the findings of this study, linear discriminant approach is the best alternative in estimating misclassification error rate of infant birth outcome followed by quadratic discriminant analysis and the least is multiple logistic regression. The findings clearly confirmed that the linear discriminant analysis is the best with misclassification error rate of 59.31%.


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