PRAMS Maternal Attitudes Data

US Pregnancy Risk Assessment Monitoring, 2009

By Health [source]

About this dataset

This dataset provides a fascinating glimpse into the attitudes and experiences of women before, during, and after pregnancy in the United States. Produced by the Centers for Disease Control and Prevention (CDC) as part of the Pregnancy Risk Assessment Monitoring System (PRAMS), this population-based data contains insights into maternal abuse, alcohol use, contraception, breastfeeding habits, mental health issues, morbidity rates, obesity rates, preconception care patterns , pregnancy history data , prenatal care trends , sleep behaviors , smoke exposure rates , stress levels , tobacco use , WIC involvement Medicaid utilization infant health outcomes and unintended pregnancies. State health departments can use this information to devise strategies to improve the overall wellbeing of mothers and infants throughout all phases of prenatal care. Discover new perspectives on maternal habits while you explore this diverse set of columns including LocationAbbv., LocationDesc., Class., Topic,. Question., DataSource., Response,. DataValueUnit,, DataValueType,. FootnoteSymbol. DataValueStdErr., SampleSize,, BreakOut,,,, BreakOutCategory.. Geolocation. With annual updates available from PRAMS project as new results are available don't be out of the loop - dive in today!

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How to use the dataset

This dataset contains population-based data on maternal attitudes and experiences before, during, and shortly after pregnancy in the US. It is provided by the Centers for Disease Control and Prevention (CDC). This dataset offers valuable insights into the individual experiences of mothers in the US, which could be used for a variety of purposes.

The PRAMS dataset contains data from 2009 onwards. The entries include year, location ID, location description, question type classabbreviation topicquestion response source unit value typevalue symbol standard error sample size break out category geolocation . In order to make better use of this dataset, it is important to understand how each entry relates to one another.

Year:The year indicates when the data was collected.

Location Abbr: This field provides an abbreviated region or state id where the data was collected.

Location Desc: The description provides a more detailed geographic area where the data was collected such as city or county that can help pinpoint more exact locations than a broad regional viewpoint provides.

Class : This is what PIDSS considers a “question type” and can range from asked directly to respondents or sentinel events often recorded within insurance claims-based datasets such as emergency room visits specific questions about smoking habits are also included in this section along with questions about family history as part of an overall health status assessment/risk categorization depiction done retrospectively on participants/respondents who already have experienced some level of health issue arising from their situation whether pre-pregnancy postpartum etc..

Topic : Each question references an umbrella topic so answers can be compared across various aspects related to difficulty experienced during pregnancy expectancy time frames protocols that should have been followed etc..

Question – Wordsmithing for clarity aims increase accuracy when deciphering causality links meaning by increasing terminology clarification which becomes essential when determining statistically significant correlations at different subgroups where appropriate additional information—including sensitivity may exist regarding certain politically or religiously charged topics answered within survey settings etc…

Data Source - These are static character strings HDDHCPPVPCDAODMBMTXNCVwhatever whichever methodology employed answer gathering-- telephone interviews focus groups electronic surveys abstractions from records found at provider lab radiology sites whatever descriptors saved intended capture magnitude relevant details having meaningful impact upon analysis discussions . . .also encompass elements incidenceprevalence cummulative extents seasonality temporal trends individual contributory factors identified linkages with confounders if any…..

Response

Research Ideas

• Analyzing trends in maternal attitudes and experiences among different states in the US to inform policy-making.
• Identifying associations between pregnancy health outcomes and specific behaviors, like alcohol consumption o...

Postpartum contraceptive use by experience of physical IPV during pregnancy or 12 months before pregnancy in the United States, PRAMS 2016–2021.

Characteristics of women with a recent live birth, stratified by self-reported exposure to physical IPV during pregnancy or 12 months before last pregnancy in the United States, PRAMS 2016–2021b'*'.

Association of IPV with postpartum contraceptive use, unadjusted and adjusted Logistic Regression Models [unweighted N = 165,204], PRAMS 2016–2021.