Investigating Maternal Health
CDC PRAMStat Survey Data 2004
@kaggle.thedevastator_investigating_maternal_health
CDC PRAMStat Survey Data 2004
@kaggle.thedevastator_investigating_maternal_health
By Health [source]
The CDC PRAMStat survey of 2004 provides a comprehensive lens into the thoughts, experiences, and behaviors of pregnant women throughout the United States. Data collected through this survey captures issues around abuse, alcohol use, contraception, breastfeeding, mental health, morbidity rates and beyond. This data can be used by state health departments to inform programs and policies which are intended to improve maternal and infant health outcomes.
PRAMStat includes population-based data from all 50 states on topics such as preconception health, WIC utilization rates and smoking habits during pregnancy as well as information on unintended pregnancies. The completeness of this data set makes it an invaluable resource for researchers who are seeking insight into maternal attitudes before, during and shortly after pregnancy so that they can work alongside state health officials in order to strive for healthier outcomes in the future.
This dataset contains a variety of columns providing important information necessary to understand the context in which these data were collected – year/location of birth/class/topic/question et al – along with responses each corresponding with particular units or footnotes specified in further columns. The PRAMStat survey is more than just numbers – it gives us powerful insights into how we define motherhood today
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This dataset is a great resource for those looking to investigate maternal health. It contains data from the CDC PRAMStat survey in 2004 and provides information on maternal attitudes and experiences before, during, and shortly after pregnancy. Here are some tips for using this dataset:
- First, take a look at the data columns to get better acquainted with the types of information available in this dataset. All of the column titles are provided above with an * indicating that it is required for any analysis.
- Once you have identified which columns will be relevant to your investigation, decide what question you want to answer with this data set and create a query statement utilizing whichever columns necessary.
- With your query statement prepared you can then search for answers by filtering or sorting through each column depending on what type of research you planing on doing such as separating questions into different classes or sorting by location with LocationAbbr or LocationDesc columns respectively..
- Depending on type of questions being asked there may be additional sub-categories within responses so make sure include Break_Out and Break_Out_Category fields when needed so that are not missing out important information were possible measure precise responses accurately by including Data _Value_Footnote_Symbol field (if available).
5 This data set also includes Sample Size which must not be overlooked as it will help determine if collected data statistically relevant while Data Value Std Err allows examining deficiencies present sample standard deviation from normal distributions mean value + / - allow further precision evaluation quality accuracy results verification . Lastly GeoLocation field allows researchers examine potential correlations location possibilities .6 Finally , once have extracted desired datasets , can begin viewing individual responses more thoroughly analyze differences between surveys check connections View multiple attributes at same time other display mapping packages allow even further exploration possibilities analyzing statistics regarding geolocations etc .
By following these steps you should be able find meaningful insights about topics related to maternal health from this dataset!
- Creating a predictive model to forecast maternal health and well-being in a particular area based on data such as location, class, topic, response and demographics.
- Using the data to create heat maps and other visuals that illustrate correlations between geographic region and certain maternal health outcomes or topics.
- Analyzing the data to identify regional trends in maternal behaviors before, during, and after pregnancy (e.g., alcohol consumption trends)
If you use this dataset in your research, please credit the original authors.
Data Source
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.
File: CDC_PRAMStat_Data_for_2004.csv
| Column name | Description |
|---|---|
| Year | The year the data was collected. (Integer) |
| LocationAbbr | The abbreviation of the location where the data was collected. (String) |
| LocationDesc | The full name of the location where the data was collected. (String) |
| Class | The broad topic of the data. (String) |
| Topic | The specific topic of the data. (String) |
| Question | The question asked in the survey. (String) |
| DataSource | The source of the data. (String) |
| Response | The response to the survey question. (String) |
| Data_Value_Unit | The unit of measurement for the data value. (String) |
| Data_Value_Type | The type of data value (e.g. mean, median, etc.). (String) |
| Data_Value_Footnote_Symbol | The footnote symbol associated with the data value. (String) |
| Data_Value_Std_Err | The standard error associated with the data value. (Float) |
| Sample_Size | The sample size of the data. (Integer) |
| Break_Out | The breakdown of the data (e.g. by gender, race, etc.). (String) |
| Break_Out_Category | The category of the breakdown. (String) |
| Geolocation | The geographic location of the data. (String) |
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Health.
CREATE TABLE cdc_pramstat_data_for_2004 (
"index" BIGINT,
"year" BIGINT,
"locationabbr" VARCHAR,
"locationdesc" VARCHAR,
"class" VARCHAR,
"topic" VARCHAR,
"question" VARCHAR,
"datasource" VARCHAR,
"response" VARCHAR,
"data_value_unit" VARCHAR,
"data_value_type" VARCHAR,
"data_value" DOUBLE,
"data_value_footnote_symbol" VARCHAR,
"data_value_footnote" VARCHAR,
"data_value_std_err" VARCHAR,
"low_confidence_limit" DOUBLE,
"high_confidence_limit" DOUBLE,
"sample_size" DOUBLE,
"break_out" VARCHAR,
"break_out_category" VARCHAR,
"geolocation" VARCHAR,
"classid" VARCHAR,
"topicid" VARCHAR,
"questionid" VARCHAR,
"locationid" DOUBLE,
"breakoutid" VARCHAR,
"breakoutcategoryid" VARCHAR,
"responseid" VARCHAR
);Anyone who has the link will be able to view this.