The number of maternal deaths and maternal mortality rates for selected causes, 2000 to most recent year.

Maternal mortality is widely considered an indicator of overall population health and the status of women in the population. DOHMH uses multiple methods including death certificates, vital records linkage, medical examiner records, and hospital discharge data to identify all pregnancy-associated deaths (deaths that occur during pregnancy or within a year of the end of pregnancy) of New York state residents in NYC each year. DOHMH convenes the Maternal Mortality and Morbidity Review Committee (M3RC), a multidisciplinary and diverse group of 40 members that conducts an in-depth, expert review of each pregnancy-associated death of New York state residents occurring in NYC from both clinical and social determinants of health perspectives. The data in this table come from vital records and the M3RC review process. Data are not cross-classified on all variables: cause of death data are available by the relation to pregnancy (pregnancy-related, pregnancy-associated but not related, unable to determine), race/ethnicity and borough of residence data are each separately available for the total number of pregnancy-associated deaths and pregnancy-related deaths only.

Each year, there are audits to assess maternal & foetal outcomes across the UK. In 2016-18, 217 women died during or up to six weeks after pregnancy, from causes associated with their pregnancy, among 2,235,159 women giving birth in the UK. 9.7 women per 100k died during pregnancy or up to six weeks after childbirth or the end of pregnancy. There was an increase in the overall maternal death rate in the UK between 2013-15 & 2016-18. Assessors judged that 29% of women who died had good care. However, improvements in care which may have made a difference to the outcome were identified for 51% of women who died. Birmingham has a higher than average maternal & foetal death rate. This dataset includes detailed information about the reasons pregnant women seek acute care, & their care pathways & outcomes. PIONEER geography: The West Midlands (WM) has a population of 5.9m & includes a diverse ethnic, socio-economic mix. There is a higher than average % of minority ethnic groups. WM has the youngest population in the UK with a higher than average birth rate. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. 51.2% of babies born in Birmingham have at least one parent born outside of the UK, this compares with 34.7% for England. Each day >100k people are treated in hospital, see their GP or are cared for by the NHS. EHR: University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Scope: Pregnant or post-partum women from 2015 onwards who attended A&E in Queen Elizabeth hospital. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes highly granular patient demographics (including gestation & postpartum period), co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (admissions, wards, practitioner changes & discharge outcomes), presenting complaints, physiology readings (temperature, blood pressure, NEWS2, SEWS, AVPU), referrals, all prescribed & administered treatments & all outcomes. Available supplementary data: More extensive data including granular serial physiology, bloods, conditions, interventions, treatments. Ambulance, 111, 999 data, synthetic data. Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Maternal mortality ratio is defined as the number of female deaths due to obstetric causes (ICD-10 codes: A34, O00-O95, O98-O99) while pregnant or within 42 days of termination of pregnancy. The maternal mortality ratio indicates the likelihood of a pregnant person dying of obstetric causes. It is calculated by dividing the number of deaths among birthing people attributable to obstetric causes in a calendar year by the number of live births registered for the same period and is presented as a rate per 100,000 live births. The number of live births used in the denominator approximates the population of pregnant and birthing people who are at risk. Data are not presented for geographies with number of maternal deaths less than 11.Compared to other high-income countries, women in the US are more likely to die from childbirth or problems related to pregnancy. In addition, there are persistent disparities by race and ethnicity, with Black pregnant persons experiencing a much higher rate of maternal mortality compared to White pregnant persons. Improving the quality of medical care for pregnant individuals before, during, and after pregnancy can help reduce maternal deaths.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

CDC Maternal Health Survey

Attitudes and Experiences Before, During, and After Pregnancy

By Health [source]

About this dataset

The Centers for Disease Control and Prevention (CDC) is proud to present PRAMS, the Pregnancy Risk Assessment Monitoring System. This survey provides valuable insights and analysis on maternal health, mindset, and experiences pre-pregnancy through postpartum phase. Statistically representative data is gathered from mothers all over the United States concerning issues such as abuse, alcohol use, contraception, breastfeeding, mental health, obesity and many more.

This survey provides an invaluable source of information which is key in targeting areas that need improvement when it comes to maternal wellbeing. Armed with PRAMS data state health officials are able to work towards promoting a healthy environment for mothers and their babies during this important period of life. Rich in data points ranging from smoking exposure to infant sleep behavior trends can be identified across states as well as nationally with this unique system supported by CDC's partnership with state health departments.

Here you will find a-mazing datasets containing columns such like Year or LocationAbbr or Response allowing you analyze some really meaningful stuff like: Are women in certain parts of the US more likely compared to others to breastfeed? What about rates at which pregnant mothers take prenatal care? Dive into the 2019 CDC PRAMStat dataset today!

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How to use the dataset

In order to make full use of this dataset it’s important that you understand what each column contains so that you can extract the most relevant data for your purposes. Here are some tips for understanding how to maximize this dataset: - Look through each column carefully – take note of which columns contain numerical information (Data_Value_Unit), categorical responses (Response) or location descriptions (Location Desc). - Make sure that you are aware of any standard errors that may be associated with data values (Data_Value_Std_Err). - It’s useful to know the source(DataSource)of your data so if possible check out who has collected it.
- Check what classifications have been used in BreakOut columns – this can give additional insight into how subjects were divided up within datasets.
- Understand how pregnancies were grouped together geographically by taking a look at LocationAbbr and Geolocation columns - understanding where surveys have been done can help break down regional differences in responses.
With these steps will help you navigate through your dataset so that you can accurately interpret questions posed by pregnant women from different locations across the U.S.

Research Ideas

• Using this dataset, public health officials could analyze maternal attitudes and experiences over a period of time to develop targeted strategies to improve maternal health.
• This dataset can be used to create predictive models of maternal behavior based on the amount of prenatal care received and other factors such as alcohol use, sleep behavior and tobacco use.
• Analyzing this dataset would also allow researchers to identify trends in infant wellbeing outcomes across various states/municipalities with different policies/interventions in place which can then be replicated in other areas with similar characteristics

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: rows.csv | Column name | Description ...

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

In 2023, non-Hispanic Black women had the highest rates of maternal mortality among select races/ethnicities in the United States, with 50.3 deaths per 100,000 live births. The total maternal mortality rate in the U.S. at that time was 18.6 per 100,000 live births, a decrease from a rate of almost 33 in 2021. This statistic presents the maternal mortality rates in the United States from 2018 to 2023, by race and ethnicity.

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

Listening to Mothers™ surveys (2002 - to present) investigate women's childbearing experiences from pregnancy (and sometimes earlier) through the postpartum period, and their views about these matters. National Listening to Mothers surveys to date were led by Childbirth Connection, which became a core program of the National Partnership for Women & Families in 2014. Listening to Mothers in California, led by the National Partnership for Women & Families, is the first state-level Listening to Mothers survey. This population-based survey of women who gave birth in California hospitals in 2016 was carried out by core Listening to Mothers investigators at the National Partnership for Women & Families and at Boston University School of Public Health, joined by investigators at what is now known as the University of California San Francisco Center for Health Equity, in collaboration with the survey research firm Quantum Market Research. California Health Care Foundation and Yellow Chair Foundation funded the survey. As investigators had access to selected birth certificate items for sampling, contacting sampled women, data weighting and data analyses, the methodology of this survey differs from the methodology used in national Listening to Mothers surveys. Other differences between past national surveys and this state-level survey include the ability to participate in the state survey in either English or Spanish and to participate on any device, as well as with a trained interviewer. Eligible women could participate in past national surveys in English only and either on their own with a laptop or desktop computer or by telephone with a trained interviewer. The Listening to Mothers in California survey questionnaire retained some core items that had been included in previous surveys, adapted others (including for mobile-first display), and included new items developed to explore the evolving U.S. health and maternity care environment and topics relevant to the California context. Topics included care arrangements, maternity care (and especially care during the hospital stay for giving birth), mode of birth, respectful and disrespectful treatment, postpartum experiences, and perinatal mental health (especially anxiety and depression). The public dataset is limited to items provided by survey participants while completing the survey, exclusive of personally identifiable information. For their analyses, the survey investigators have access to two additional sources of information about survey participants that cannot be made public: selected items on participants’ birth certificates and selected items abstracted from the California Department of Health Care Services Management Information System/Decision Support System Warehouse. Much information about the California survey is available at either www.nationalpartnership.org/LTMCA or www.chcf.org/listening-to-mothers-CA. Information about national surveys (including a bibliography of analyses carried out to date and other reports) is available at www.nationalpartnership.org/listeningtomothers/.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2022-23, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2023. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019 the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fourth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with breakdowns including the baby's first feed type, birthweight, place of birth, and breastfeeding activity; and the mothers' ethnicity and age at booking. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. The count of Total Babies includes both live and still births, and previous changes to how Total Babies and Total Deliveries were calculated means that comparisons between 2019-20 MSDS data and later years should be made with care. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

Analysis of ‘🤰 Pregnancy, Birth & Abortion Rates (1973 - 2016)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/pregnancy-birth-abortion-rates-in-the-united-stae on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

Source: OSF | Downloaded on 29 October 2020

This data source is a subset of the original data source. The data has been split by State, Metric and Age Range. It has been limited to pregnancy rate, birth rate and abortion rate per 1,000 women. The original data contains many more measures.

The data was prepared with Tableau Prep.

Summary via OSF -

A data set of comprehensive historical statistics on the incidence of pregnancy, birth and abortion for people of all reproductive ages in the United States. National statistics cover the period from 1973 to 2016, the most recent year for which comparable data are available; state-level statistics are for selected years from 1988 to 2016. For a report describing key highlights from these data, as well as a methodology appendix describing our methods of estimation and data sources used, see https://guttmacher.org/report/pregnancies-births-abortions-in-united-states-1973-2016.

​

This dataset was created by Andy Kriebel and contains around 20000 samples along with Age Range, Events Per 1,000 Women, technical information and other features such as: - State - Year - and more.

How to use this dataset

• Analyze Metric in relation to Age Range
• Study the influence of Events Per 1,000 Women on State
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

The fifth round of the Global Reproductive, Maternal, Newborn, Child and Adolescent Health Policy Survey was conducted in 2018-2019. For this survey, the questionnaire was administered online to each member state via World Health Organization (WHO) regional offices. Each WHO country office was asked to coordinate completion of the survey with the Ministry of Health and other UN partners. Respondents from each country shared original source documents including national policies, strategies, laws, guidelines, reports that are relevant to the areas of sexual and reproductive health, maternal and newborn health, child health, adolescent health, gender-based violence and cross-cutting issues. Cross cutting issues include policies, guidelines and legislation for human right to healthcare, financial protection, and quality of care.The WHO Maternal and Newborn Health page can be found here, and the WHO data can also be accessed on their data portal page, here. Maternal and Newborn Health Policy data, provided by the WHO, show the below data attributes for countries that have an International Confederation of Midwives (ICM) membership and have completed the required surveys. Essential Medicines List Includes: Magnesium sulfate for use during pregnancy, childbirth and postpartum careOxytocin for use during pregnancy, childbirth and postpartum careMisoprostol tablets for use during pregnancy, childbirth and postpartum careAmpicillin or Amoxicillin injections for use during pregnancy, childbirth and postpartum careGentamicin injectionMetronidazole injectionProcaine penicillin injectionBenzathine penicillin injectionDexamethasone injectionChlorhexidineCeftriaxoneIntravenous tranexamic acidNational list of Commodities Includes:Obstetric ultrasound machineSelf-inflating bag with neonatal and paediatric masks of different sizes and valves Oxygen supplyVaccuum aspiratorHealth Access Policy: User fee exemptions for antenatal care services for women of reproductive ageUser fee exemptions for normal childbirth services for women of reproductive ageUser fee exemptions for postnatal care for mothersUser fee exemptions for postnatal care for newbornsMaternal and Newborn Health Policies: Policy/legislation on free access to health services for newborns (0-4 weeks)Policy on free access to health services for pregnant womenNational policy on childbirthNational policy/guideline on right of every women to have access to skilled care at childbirthNational policy on postnatal care for mothers and newbornsNational policy on management of low birth weight and preterm newbornsNational standards for management of newborn infants with severe illnessContinuous professional education system in place for primary health-care clinicians and/or nurses to receive specific training for maternal and newborn healthNational policy on regulation of midwifery care providers based on ICMNational policy recommending midwife-led care for pregnancyNational policy recommending midwife-led care for childbirthNational policy recommending midwife-led care for the postnatal periodNational policy/law on maternal death notification within 24 hoursNational policy/law on maternal death reviewNational panel to review maternal deathsFrequency of meetings of national panel to review maternal deathsNational policy/law to review stillbirthsFacility stillbirth review process in placeNational policy/law to review neonatal deathsFacility neonatal death review process in placeThis data set is just one of the many datasets on the Global Midwives Hub, a digital resource with open data, maps, and mapping applications (among other things), to support advocacy for improved maternal and newborn services, supported by the International Confederation of Midwives (ICM), UNFPA, WHO, and Direct Relief.

Background: In 2020, 287,000 mothers died from complications of pregnancy or childbirth; one-third of these deaths (30%) occur during the first 6 weeks after birth. Precision public health approaches leverage risk prediction to identify the most vulnerable patients and inform decisions around use of scarce resources, including the frequency, intensity, and type of postnatal care follow-up visits. However, these approaches may not accurately or precisely predict risk for specific sub-groups of women who are statistically underrepresented in the total population, such as women who experience stillbirths. Methods: We leverage our existing dataset of sociodemographic and clinical variables and health outcomes for mother and baby dyads in Uganda to generate a synthetic dataset to enhance our risk prediction model for identifying women at a high-risk of death or readmission in the 6 weeks after a hospital delivery. Data Collection Methods: The original mom and baby project data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). Following delivery and obtaining informed written consent, trained study nurses collected data grouped according to four periods of care; admission, delivery, discharge, and six-week post-discharge follow up. Data from admission and delivery were captured from the hospital medical record where possible and by direct observation, direct measurement or patient interview when not. Discharge and post-discharge data were collected by observation, measurement or interview. Six-weeks after delivery, field officers contacted every mother and/or caregivers of newborns who survived to discharge to determine vital status, readmission and care seeking for illnesses and routine postnatal care. In-person visits were completed in situations where participants could not be reached by phone. Mothers who had experienced a stillbirth were filtered from the overall dataset. The synthetic dataset was subsequently based off the stillbirth cohort and evaluated it to ensure its statistical properties were maintained. Data Processing Methods: Synthetic data and evaluation metrics were generated using the synthpop R package. The first variable (column) in the dataset is generated via random sampling with replacement with subsequent variables generated conditioned on all previously synthesized variables using a pre-specified algorithm. We used the classification and regression tree (CART) algorithm as it is non-parametric and compatible with all data types (continuous, categorical, ordinal). Additional setup for generating the synthetic dataset included identifying eligible and relevant variables for synthesis and outlining rules for variables that have branching logic (i.e., variables that are only entered if a previous variable has a specific response). For evaluation, we used the utility metric recommended by the authors of the synthpop package, the standardized propensity-score mean squared error (pMSE) ratio which measures how easy it is to tell whether a data point comes from the original data or the synthetic dataset. All the standardized pMSE ratios were below 10, which is the suggested cut-off for acceptable utility as proposed by the synthpop authors. Plots were also generated to visually compare the univariate distribution of each variable in the synthetic dataset against the original dataset. Ethics Declaration: Ethics approvals have been obtained from the Makerere University School of Public Health (MakSPH) Institutional Review Board (SPH-2021-177), the Uganda National Council of Science and Technology (UNCST) in Uganda (HS2174ES) and the University of British Columbia in Canada (H21-03709). This study has been registered at clinicaltrials.gov (NCT05730387). Abbreviations: JRRH: Jinja Regional Referral Hospital MRRH: Mbarara Regional Referral Hospital PNC: Post-natal care SES: Socio-economic index SpO2: Oxygen saturation Study Protocol & Supplementary Materials: Smart Discharges for Mom & Baby 2.0: A cohort study to develop prognostic algorithms for post-discharge readmission and mortality among mother-infant dyads NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

Abstract Background: The improvement in surgical techniques has contributed to an increasing number of childbearing women with complex congenital heart disease (CCC). However, adequate counseling about pregnancy in this situation is uncertain, due to a wide variety of residual cardiac lesions. Objectives: To evaluate fetal and maternal outcomes in pregnant women with CCC and to analyze the predictive variables of prognosis. Methods: During 10 years we followed 435 consecutive pregnancies in patients (pts) with congenital heart disease. Among of them, we selected 42 pregnancies in 40 (mean age of 25.5 ± 4.5 years) pts with CCC, who had been advised against pregnancy. The distribution of underlying cardiac lesions were: D-Transposition of the great arteries, pulmonary atresia, tricuspid atresia, single ventricle, double-outlet ventricle and truncus arteriosus. The surgical procedures performed before gestation were: Fontan, Jatene, Rastelli, Senning, Mustard and other surgical techniques, including Blalock, Taussing, and Glenn. Eight (20,0%) pts did not have previous surgery. Nineteen 19 (47.5%) pts had hypoxemia. The clinical follow-up protocol included oxygen saturation recording, hemoglobin and hematocrit values; medication adjustment to pregnancy, anticoagulation use, when necessary, and hospitalization from 28 weeks, in severe cases. The statistical significance level considered was p < 0.05. Results: Only seventeen (40.5%) pregnancies had maternal and fetal uneventful courses. There were 13 (30.9%) maternal complications, two (4.7%) maternal deaths due to hemorrhage pos-partum and severe pre-eclampsia, both of them in women with hypoxemia. There were 7 (16.6%) stillbirths and 17 (40.5%) premature babies. Congenital heart disease was identified in two (4.1%) infants. Maternal and fetal complications were higher (p < 0.05) in women with hypoxemia. Conclusions: Pregnancy in women with CCC was associated to high maternal and offspring risks. Hypoxemia was a predictive variable of poor maternal and fetal outcomes. Women with CCC should be advised against pregnancy, even when treated in specialized care centers.

In order to assess the possible effects of lifestyle on fertility and pregnancy outcome, the PALS (Pregnancy and Lifestyle study) collected extensive data on a broad range of parameters termed 'lifestyle' from couples who were planning a natural (non-assisted) pregnancy in the coming months. There was no intervention. Participants were recruited over a six year period from 1988 to 1993 in response to extensive promotion in the local media. Male and female partners were interviewed independently and all interviews were conducted prospectively before the couple attempted to conceive. The result of each month of 'trying' was recorded and pregnancies were confirmed by urine tests and by ultrasound. The length of gestation of each pregnancy was recorded and pregnancies at term were classified with respect to weight. Multiple pregnancies and/or babies with congenital abnormalities have been excluded from the dataset. The data is stored as an xls file and each variable has a codename. For each of 582 couples there are 355 variables, the codes for which are described in a separate metadata file. The questionnaire based data includes information about households, occupation, chemical exposures at work and home, diet, smoking, alcohol use, hobbies, exercise and health. Recorded observations include monthly pregnancy tests and pregnancy outcomes.

Data resulting from a collaborative study between UK and Burkina Faso researchers into the impact of severe obstetric complications and their treatment on economic, social and physical well-being, and sustained ill-health and impoverishment over a 4 year period. It builds on a previous study of 1014 women in Burkina Faso which compares the consequences of severe (“near-miss”) complications with normal facility-based births up to one year postpartum.This ESRC-Hewlett study re-interviewed the women at home during the third and fourth years postpartum, using qualitative and quantitative methods to assess long-term economic, social and health effects. We added a new comparison group of women from the same neighbourhood to gain broader insights. This dataset includes: • year 3 interviews with women interviewed in IMMPACT study, consisting of 2 datasets with 145 variables and 192 variables resp. (n=763); • year 3 interviews with new control group of women, consisting of 2 datasets with 295 variables and 195 variables resp. (n=360); • year 3 interviews with head of household dataset with 301 variables (n=907); • child development assessment dataset with 89 variables (n=515); • year 4 interviews with women, consisting of 2 datasets with 219 variables and 187 variables resp. (n=994); • dataset on migration and loss of surveyed women to follow-up (12 variables) containing all women interviewed at one point or the other (n=1331). Women in Africa face the risk that something can go wrong in childbirth many times over during the course of their lives. Emergency obstetric care (such as caesarean section) may save their lives, but their health and ability to work afterwards may be affected, and the high costs of the hospital treatment can cause great financial difficulties, pushing families into poverty. The study will document the long-term impact of complications on the economic and social well-being of women and their families. It will build on a recent study of 1013 women in Burkina Faso which investigated the health, economic and social consequences of obstetric complications and normal births in health facilities up to one year after birth. The study will re-contact the participants at 3 and 4 years after birth, and include an additional group of women from the community who delivered around the same time. Information will be collected on what has happened since the index birth to household income, belongings, debts and consumption, to women’s mental and physical health and social situation, to their ability to earn money, work in production and in the home, the survival and development of the children, and to decisions about future pregnancies. The study took place in the catchment areas (30 km radius) of 7 referral hospitals in 6 towns in Burkina Faso. We collected quantitative data on 1331 women (some of these are from a dataset which we collected but is already open-access with IMMPACT, University of Aberdeen). We contacted 1014 women again in year 3 (June-December 2008) and year 4 postpartum (September-December 2009) and were able to re-interview 73% of the original sample. We recruited an additional comparison group of 310 women In addition, we interviewed 820 heads of households, and assessed the heath of 896 surviving children. We also conducted child development tests with a sub-sample of 514 children. In addition, we carried out qualitative interviews. In order to examine changes over time, we selected a sub-sample of women who had taken part in in-depth interviews in the original study who had received a near-miss diagnosis and who resided in two of the peri-urban study sites. 16 women were traced and re-interviewed. To investigate the impact of specifically traumatic experiences, we selected a sample including all cohort women classified as having received a near-miss diagnosis and delivery by emergency c-section in three of the study sites, as well as a randomly generated sample of women from one of the two largest study sites who fulfilled the selection criteria. This sample included 21 women. Study design: cohort study, with as components: • baseline data collected at hospital discharge, 3 months, 6 months and 12 months postpartum (IMMPACT Open Access Dataset); • follow-up data collected in years 3 and 4 postpartum (Hewlett/ESRC Dataset) Instruments used are: • Face to face structured interviews with women and heads of household, including biological samples (haemoglobin), and use of GPS; • Child development assessment with children; • In depth interviews.

This statistical release makes available the most recent monthly data on NHS-funded maternity services in England, using data submitted to the Maternity Services Data Set (MSDS). This is the latest report from the newest version of the data set, MSDS.v.2, which has been in place since April 2019. The new data set was a significant change which added support for key policy initiatives such as continuity of carer, as well as increased flexibility through the introduction of new clinical coding. This was a major change, so data quality and coverage initially reduced from the levels seen in earlier publications. MSDS.v.2 data completeness improved over time, and we are looking at ways of supporting further improvements. This publication also includes the National Maternity Dashboard. Recently, Statistical Process Control (SPC) charts were included in the National Maternity Dashboard. These can be accessed via the CQIM+ page in the dashboard. Data derived from SNOMED codes is used in some measures such as those for smoking at booking and delivery, and birth weight, and others will follow in later publications. SNOMED data is also included in some of the published Clinical Quality Improvement Metrics (CQIMs), where rules have been applied to ensure measure rates are calculated only where data quality is high enough. System suppliers are at different stages of development and delivery to trusts. In some cases, this has limited the aspects of data that can be submitted in the MSDS. To help Trusts understand to what extent they met the Clinical Negligence Scheme for Trusts (CNST) Maternity Incentive Scheme (MIS) Data Quality Criteria for Safety Action 2, we have been producing a CNST Scorecard Dashboard showing trust performance against this criteria. This month, this dashboard has been updated following the release of CNST Y6 criteria, and can be accessed via the link below. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website. The percentages presented in this report are based on rounded figures and therefore may not total to 100%.

Hospital-based recruitment of females seeking termination of pregnancy or post-abortion care at a Zambian government health facility. The research used an innovative mixed methods interview which combined quantitative and qualitative techniques in one interview. Each participant was interviewed by two research assistants (RAs). One RA led the interview, using a conventional interview schedule in the manner of a qualitative semi-structured interview, while the second RA listened and, where possible, completed the quantitative ‘data sheet’. When the first RA has completed the qualitative part of the interview, interviewer two took over and asked the participant any remaining questions not yet answered on the data sheet. This technique allowed us to capture both the individual fine-grained narratives, which are not easily captured in a questionnaire-type survey, especially on such a sensitive area, as well as survey data. Rather than conducting an in-depth qualitative interview and a survey, our method reduced the burden on the respondent, avoiding repetition of questions and reducing the time taken. The quantitative data was used to establish the distribution of out-of-pocket expenses, for women and their households, incurred using hospital-based safe abortion and PAC services. Qualitative data established the range of reasons why women sought abortion, and why they used or did not use safe abortion services, and explored the social costs and benefits of their trajectories, and the policy implications. Unsafe abortion is a significant, preventable, cause of maternal mortality and morbidity and is both a cause and a consequence of poverty. Unsafe abortion is the most easily prevented cause of maternal death. Post-abortion care (PAC) is a strategy to address the problem of the outcomes of unsafe abortion.This research aims to establish how investment in safe abortion services impacts on the socio-economic conditions of women and their households, and the implications for policy-making and service provision in Zambia. The microeconomic impact of out-of-pocket health expenditure for reproductive health and abortion care, have received little attention.The data available for sub-Saharan Africa are particularly scanty and poor quality. The approach is multi-disciplinary, with primary data collection of both qualitative and quantitative data, including a quantitative survey and in-depth qualitative interviews with women who have sought PAC, and policymaker interviews. Zambia's relatively liberal legal context, and the existence of PAC provision facilitates research on issues related to abortion which can have broader lessons for developments elsewhere in the region.The majority of women seeking abortion-related care in Zambia do so for PAC following an unsafe abortion, and have not accessed safe abortion services.This demands better understanding and analysis. Over a 12 month period, all women identified as having undergone either a safe abortion or having received PAC following an attempted induced abortion at a Zambian government health facility were approached for inclusion in the study. We did not interview women identified as having received PAC following a spontaneous abortion. Undoubtedly, some women claiming to have had a spontaneous abortion had in fact attempted to induce an abortion, and at times medical evidence suggested so, however we could not interview them about the attempt as they were not willing to disclose any information on an attempted abortion. As part of the research team we employed two midwives working on the obstetrics and gynaecology ward to act as gatekeepers, identifying suitable women for recruitment and asking them to participate in the study. The research used an innovative mixed methods interview which combined quantitative and qualitative techniques in one interview. Each participant was interviewed by two research assistants (RAs). One RA led the interview, using a conventional interview schedule in the manner of a qualitative semi-structured interview, while the second RA listened and, where possible, completed the quantitative ‘data sheet’. When the first RA has completed the qualitative part of the interview, interviewer two took over and asked the participant any remaining questions not yet answered on the data sheet. This technique allowed us to capture both the individual fine-grained narratives, which are not easily captured in a questionnaire-type survey, especially on such a sensitive area, as well as survey data. Rather than conducting an in-depth qualitative interview and a survey, our method reduced the burden on the respondent, avoiding repetition of questions and reducing the time taken.

Introduction: Respectful and dignified healthcare is a fundamental right for every woman. However, many women seeking childbirth services, especially those in low-income countries such as Pakistan, are mistreated by their birth attendants. The aim of this epidemiological study was to estimate the prevalence of mistreatment and types of mistreatment among women giving birth in facility- and home-based settings in Pakistan in order to address the lack of empirical evidence on this topic. The study also examined the association between demographics (socio-demographic, reproductive history and empowerment status) and mistreatment, both in general and according to birth setting (whether home- or facility-based). Material and methods: In phase one, we identified 24 mistreatment indicators through an extensive literature review. We then pre-tested these indicators and classified them into seven behavioural types. During phase two, the survey was conducted (April-May 2013) in 14 districts across Pakistan. A total of 1,334 women who had given birth at home or in a healthcare facility over the past 12 months were interviewed. Linear regression analysis was employed for the full data set, and for facility- and home-based births separately, using Stata version 14.1. Results: There were no significant differences in manifestations of mistreatment between facility- and home-based childbirths. Approximately 97% of women reported experiencing at least one disrespectful and abusive behaviour. Experiences of mistreatment by type were as follows: non-consented care (81%); right to information (72%); non-confidential care (69%); verbal abuse (35%); abandonment of care (32%); discriminatory care (15%); and physical abuse (15%). In overall analysis, experience of mistreatment was lower among women who were unemployed (β = -1.17, 95% CI -1.81, -0.53); and higher among less empowered women (β = 0.11, 95% CI 0.06, 0.16); and those assisted by a traditional birth attendant as opposed to a general physician (β = 0.94, 95% CI 0.13, 1.75). Sub-group analyses for home-based births identified the same significant associations with mistreatment, with ethnicity included. In facility-based births, there was a significant relationship between women's employment and empowerment status and mistreatment. Women with prior education on birth preparedness were less likely to experience mistreatment compared to those who had received no previous birth preparedness education. Conclusion: In order to promote care that is woman-centred and provided in a respectful and culturally appropriate manner, service providers should be cognisant of the current situation and ensure provision of quality antenatal care. At the community level, women should seek antenatal care for improved birth preparedness, while at the interpersonal level strategies should be devised to leverage women's ability to participate in key household decisions. Mistreatment dataThe survey was conducted (April-May 2013) in 14 districts across Pakistan. A total of 1,334 women who had given birth at home or in a healthcare facility over the past 12 months were interviewed.