Data – Page 7 – Use It for Good

Locating Dimensions of Women’s Empowerment in Family Planning in Burkina Faso

December 21, 2021November 20, 2020 by mpcblog

By Tayler Nelson

Women’s “empowerment,” defined by Naila Kabeer[1] as “the expansion of people’s ability to make strategic life choices in a context where this ability was previously denied to them,” has been shown[2] to be associated with greater birth spacing, lower fertility, and lower rates of unplanned pregnancy. Yet scholars disagree[3] on how to measure women’s empowerment, and meanings of empowerment can shift across geographic and cultural contexts.

IPUMS PMA’s family planning surveys include variables that can help researchers investigate dimensions of women’s empowerment in family planning. All samples include indicators of women’s knowledge about family planning methods. Many survey rounds dig deeper, collecting data that can be used by researchers and policymakers.

The Burkina Faso 2018 Round 6 survey includes a range of variables measuring family planning attitudes, beliefs, and decision-making dynamics that relate to women’s empowerment. I used a weighted polychoric factor analysis[4] to investigate women’s empowerment in family planning in Burkina Faso. Factor analysis can help researchers reduce a large number of observed variables by identifying similar response patterns among observed variables and grouping them into a smaller set of underlying variables, or factors. Through analyzing how variables are grouped and the strength and signs of coefficients within these groups, researchers can glean insight into which sets of observed variables might be best at measuring an unobserved construct such as women’s empowerment.

IPUMS IHGIS: Unlocking International Population and Agricultural Census Data

December 21, 2021November 5, 2020 by mpcblog

By Tracy Kugler

Nearly all countries throughout the world conduct population and housing censuses at least every ten years, and most also conduct agricultural censuses or surveys regularly. These censuses collect information on demographics, education, employment, housing characteristics, migration, agricultural land ownership, agricultural workforce, livestock, crops, and more. The resulting data can be used to study a wide range of questions, from the character of demographic transitions within and across countries, to utilization of irrigation, to educational trends among women.

Unfortunately, this wealth of data has remained largely inaccessible to researchers. The data are typically published in reports as tables summarizing population characteristics. In recent decades, many of these reports have been published as PDF documents and made available on national statistical office websites. While the reports are available, data from a PDF document cannot be easily imported into a statistical or GIS package. Furthermore, the table structures are highly heterogeneous, both across countries and even within the same report.

The International Historical Geographic Information System (IPUMS IHGIS) is designed to provide easy access to these data in a way that researchers can easily use for analysis. In the early phases, IHGIS was known internally as “Project Mako,” named after the Mako shark, which has a global range, voracious appetite, and a reputation for a broad-ranging diet. Like the shark, IHGIS (née Project Mako) will encompass the world and ingest all kinds of data tables.

What’s new with IPUMS USA? Updates for Industry and Occupation Variables

December 21, 2021October 14, 2020 by mpcblog

By Megan Schouweiler (Senior Data Analyst, IPUMS USA) and Sophia Foster (Data Analyst, IPUMS USA)

The Census Bureau drops ACS 1-year PUMS files tomorrow (October 15, 2020)! Don’t worry, the IPUMS USA team will get right to work to get you some data as soon as possible. In the meantime, let’s talk a little about what’s new with occupation and industry variables on IPUMS USA.

New OCCSOC and INDNAICS Crosswalks Available

You may be familiar with our harmonized occupation (OCC1950, OCC1990, OCC2010) and industry variables (IND1950, IND1990). These variables harmonize occupation/industry codes based on Census Bureau classification systems to a base year, making comparisons across time much easier. Researchers are also interested in using the Standard Occupational Classification (SOC) system and North American Industry Classification System (NAICS) codes that are available in the public use data; IPUMS has not created nifty harmonized variables for these codes. We hope to harmonize these codes someday– until then, we will settle for providing great documentation about how these codes have changed over time. And we’ve recently made the documentation even better!

OCCSOC reports the primary occupation based on the SOC system, and INDNAICS reports the type of establishment of the primary occupation based on the NAICS system. Both of these coding systems are periodically updated. In the past two decades, the OCCSOC codes have been updated six times and the INDNAICS codes have been updated five times, creating a challenge for those utilizing the codes to conduct research across time. Beyond navigating the changes to the coding schemes, there are separate crosswalks for each update. We recently updated each of our crosswalks to include all iterations of the underlying coding systems from 2000 onward in a single table for OCCSOC and INDNAICS, respectively. Instead of a bunch of links to crosswalks that just compare adjacent schemes, we’ve combined all years into one table.

In total, we created four crosswalks: OCC to OCCSOC; IND to INDNAICS; OCCSOC only; and INDNAICS only. These crosswalks include detailed descriptions of how OCCSOC and INDNAICS codes have changed over time from the 2000 Census to present. Examples of changes include one occupation/industry splitting into multiple new categories, multiple categories collapsing into one occupation/industry, and updates to codes and titles. Because these types of changes occur with each new iteration of the coding scheme, it can be difficult to understand how the codes relate to one another across time. We hope that these new crosswalks provide a more comprehensive mapping of the OCCSOC and INDNAICS codes over time and will aid researchers in using these variables. These crosswalks are available to view on the IPUMS USA website and for download in both Excel and CSV format. Trust us, you’ll want to download these crosswalks to make your programming a lot easier.

IPUMS provides demographic data for international COVID-19 research

December 21, 2021September 15, 2020 by mpcblog

By Lara Cleveland

Since the onset of the COVID-19 outbreak, researchers across the globe have been accessing census microdata from IPUMS International for COVID-19-related research. Scholars at universities from the U.S. to Nepal, Columbia to Belgium, Nigeria to China, and elsewhere have used IPUMS data to assess population dynamics contributing to COVID-19 vulnerability or spread. Divisions of the United Nations, World Bank, and other policy research institutes have similarly accessed IPUMS census data for COVID response and relief efforts.

IPUMS International harmonizes and disseminates household-level microdata census samples from more than 100 countries. Access to microdata is essential for rapid response in new areas because of its analytic flexibility. Researchers needing to build custom tables or construct variables for complex modeling suited to specific research questions can only do that with microdata. Of particular interest for research on population dynamics of COVID-19 is information about the age structure of the population, household living arrangements (household size, intergenerational co-residence, etc.), indicators of health vulnerability (age, work status, housing conditions, disability, etc.), healthcare workforce distribution, and migration patterns. IPUMS International census samples also include valuable subnational geographic identifiers at the first and second administrative levels, which are especially useful for highlighting particular regions or localities of vulnerability.

Cite us! Seriously though…

December 21, 2021August 17, 2020 by mpcblog

By Renae Rodgers and Kari Williams

Hi there IPUMS users! Let’s talk about citations. When using our datasets in your insightful, groundbreaking, interesting work, please cite us!

Seriously though.

Cite us.

You wouldn’t steal a car, you wouldn’t rob a little old lady of her handbag, you wouldn’t base work on that of a colleague and not put their paper(s) in your reference section, right?!? Then don’t use IPUMS data and fail to mention it!

To help you on your way, here are some answers to frequently asked questions:

Overview of NHIS Data Collection, 1997-2018

December 21, 2021July 1, 2020 by mpcblog

By Julia A. Rivera Drew, Kari C.W. Williams, and Natalie Del Ponte

The IPUMS NHIS project offers integrated versions of the National Health Interview Survey (NHIS) data, the leading source of nationally representative information on the health of the U.S. population. The National Center for Health Statistics (NCHS) collects the NHIS data through face-to-face interviews covering information about health, health insurance coverage, health care utilization, socioeconomic characteristics, and demographics of all household members. It is representative of the civilian, non-institutionalized U.S. population with annual samples ranging between 30,000-50,000 households and 75,000-100,000 people. NCHS has collected the NHIS annually since 1957 (with digital copies of the data available going back to 1963), making it the longest running annual survey of health in the world.

Periodically, aspects of data collection – such as the sampling frame, oversampled populations, or questionnaire content – change to better capture changes in the most pressing health concerns of Americans or changes in the demographic makeup of Americans and where they reside within the U.S. Most of these changes are modest, reflecting changes in U.S. population composition and distribution detected in the most recent decennial census. However, 2019 heralded the largest change in NHIS data collection since 1997. In fall 2020, the NCHS will release the 2019 public use data files, the first data collected under the newly redesigned NHIS. The upcoming release of the 2019 data warrants a look back at how NCHS collected the NHIS data over the 1997-2018 period.

New survey data from IPUMS PMA allows for exploration of factors in child nutrition status

December 21, 2021June 1, 2020 by mpcblog

By Devon Kristiansen

Last month, when IPUMS PMA released data from nine countries, including the most recent person level and service delivery point level surveys on family planning, we also released data on a new topic for Performance Monitoring for Action (PMA) – nutrition. PMA conducted two survey rounds each in Burkina Faso and Kenya (2017 and 2018) in both in people’s homes (households) and where they received care and medical services (service delivery points). Household surveys contained questions about the diet and nutritional status of children under 5 and women between 10 and 49 years, antenatal care and advice received by currently or recently pregnant women, and other household and demographic questions. Service delivery points were surveyed for medical equipment and services relating to malnutrition and anthropometric monitoring.

A key factor for nutrition status of young children in the low and middle-income country (LMIC) context is incidence of diarrhea. Diarrhea prevents the uptake of nutrients into the child’s body and causes dehydration. According to the World Health Organization¹, diarrhea is the leading cause of malnutrition and second leading cause of death for children under 5 globally. A well-established association in the nutrition literature is the presence of livestock on the homestead and incidence of diarrhea in young children, due to fecal contamination of water and food sources^{2, 3}.