About the birth defects & folic acid data

This page provides general information about the birth defects and folic acid data and measures developed by the Minnesota Environmental Public Health Tracking (MN EPHT) Program. For more information about these data, contact MNPH Data Access.

Information on this page:

Birth defects data:

  • Statewide numbers and prevalence rates of select birth defects in Minnesota, by five-year cohorts, race/ethnicity of mother, and age of mothe. Prior to the 2013-2017 cohort, data included only Hennepin and Ramsey counties. Race is defined as the classification of humans into populations or groups based on various sets of characteristics and is often self-identified. Ethnicity is a term that represents a group based on their cultural and social affiliation, common history and origin, and sense of identification within the group. It is also often self-identified.
  • If a segment of a population is at higher risk for select birth defects. Risk is the probability that an event will occur to a group or individual, such as harm or disease.

Folic acid data:

  • The percent of Minnesota mothers who reported they take daily folic acid vitamins during the month before pregnancy by race and Hispanic ethnicity, WIC participant status, education level, and poverty level.
  • Disparities in folic acid intake-Minnesota mothers who reported they were less likely to take daily vitamins.

Birth defects data:

  • To inform the public about select birth defects.

Folic acid data:

  • For program planning and evaluation by state and local partners.
  • Public health planners use PRAMS data to help understand maternal behaviors and experiences and their relationship to pregnancy outcomes.

Birth defects data:

  • These data cannot tell us what causes birth defects, or factors that lead to changes in birth defect rates.
  • MN Tracking birth defects measures are prevalence rates of 12 selected birth defects per 10,000 live births. The incidence of birth defects would be the ideal measure for birth defects, but it cannot be determined as it requires information that is difficult to determine, such as the number of conceptions and the number of cases "lost" through miscarriages and terminations.
  • Prior to 2013, MN Tracking birth defects measures are for only Hennepin and Ramsey counties in Minnesota.

Folic acid data:

  • How much folate or folic acid Minnesotan women are actually consuming.
  • Whether consuming folic acid prevented a birth defect for that particular individual.

Birth defects data:

  • The Minnesota Department of Health (MDH) Birth Defects Program uses a multi-source active surveillance methodology with program and clinical review of all cases. Data is reported from hospital and clinic systems in Minnesota as well as other MDH programs; Vital Statistics sources (e.g. birth certificates) are also used. The program uses National Birth Defects Prevention Network (NBDPN) guidelines for validating each birth defect diagnosis and tracks about sixty birth conditions, including most of the birth defects recommended by NBDPN and the Centers for Disease Control and Prevention (CDC). The program uses CDC/BPA codes to categorize these conditions. The conditions must be diagnosed before one year of age to be entered into the Minnesota Birth Defects Information System (BDIS).
  • BDIS started with children born to mothers who resided in Hennepin and Ramsey counties at the time of delivery for 2006 births and went statewide starting with 2013 births. • BDIS started with children born to mothers who resided in Hennepin and Ramsey counties at the time of delivery for 2006 births and went statewide starting with 2013 births.

Folic acid data:

  • The MDH Birth Defects Program uses multiple data sources to help ensure that all cases are identified. In addition to the primary case finding source of hospital medical records, they use birth certificates, death certificates, and newborn screening data for case finding.
  • The Birth Defects Program performs active surveillance with program and clinical review of cases. Trained abstractors review and abstract medical records to make sure all reported potential cases meet rigorous case definitions established by both Minnesota and national experts. A data quality specialist ensures data quality for selected cases, and nurses ensure that clinical information, including birth defect diagnoses, is accurate.   
  • Case ascertainment of birth defects was limited to live births through 2018. Starting with 2019, birth defects among stillbirths were included. Birth defects among pregnancy terminations are not currently collected. The addition of stillbirths will not be reflected until the 2019-2023 birth cohort.
  • Because cases may be abstracted through one year of age and then quality control analysis must be performed, there is a 2-3 year data reporting lag.
  • There are 12 birth defects reported by MN EPHT: Anencephaly, Spina Bifida, Hypoplastic Left Heart Syndrome, Tetralogy of Fallot, Transposition of the Great Arteries, Cleft lip with Cleft palate, Cleft lip without Cleft palate, Cleft palate without Cleft lip, Hypospadias, Gastroschisis, Limb deficiencies, and Trisomy 21. These conditions were selected because they are potential linked to suspected environmental risk factors and they are also conditions that are tracked by most birth defects programs across the U.S.

Folic acid data:

  • Each month, approximately 200 mothers are selected from the Minnesota Vital Statistics file of birth certificates of babies born in Minnesota during the preceding 2–4 months. Mothers must be Minnesota residents and have delivered a live–born infant. A PRAMS questionnaire is mailed to these mothers with instructions for completing and returning the information. Some surveys are completed by a telephone interview. Minnesota uses the standardized data collection methods developed by CDC.

Birth defects data:

Number

  • The number indicates the total number of birth defects, not the number of people with birth defects.
  • To understand the magnitude or what the overall burden is, use the number.

Rate

  • A rate is a ratio between two measures with different units. A ratio is defined as a comparison between two numbers and are typically separated by a colon or “:” or a fraction.
  • In our analysis, a rate is calculated using the number of events as the numerator (the number of birth defects during a period of time) divided by the number of people at risk as the denominator (the number of live births during the same period of time). This fraction is then multiplied by a constant to make the number more legible. The constant is 10,000 for birth defect measures.
  • To understand the probability or what the underlying risk in a population is, use a rate.
  • Rates have been rounded to the nearest tenth of a percent.

Birth defects data:

  • MN Tracking birth defects measures are aggregated using the most recent 5 year grouping. Because birth defect rates are based on only five years of aggregated data, the rates may be suppressed or vary considerably when compared with data from other states that have been collecting birth defects information for a longer time period.
  • For five-year birth cohorts starting before 2013, birth defects data is only reported for Hennepin and Ramsey counties. About one-third of all births in the state are among residents of these two counties. Starting with the 2013-2017 birth cohort, birth defects data is reported by region.
  • In Minnesota, an "opt-out" clause that allows a parent to remove any personally identifying information on that child from the system makes it impossible to generate population-based measures in areas smaller than county. Since birth defects are rare and rates based on small case numbers are unstable, regions are the smallest area for which 5-year population-based measures are provided.
  • Residential information is very important when examining environmental exposures that occur before birth. A limitation of the data source is that the place of residence during pregnancy may not be represented by maternal residence at time of birth. Address data at conception would be a more relevant time period for birth defects-related exposure than address data at delivery. In cases of adoption, information about the birth mother (e.g. age, race/ethnicity, county of residence) are collected and retained when possible.

Folic Acid data:

  • There are some limitations in the PRAMS data: recall bias and non-response bias.
  • PRAMS respondents are contacted within 2-6 months after giving birth and questions are asked about behaviors throughout the perinatal period. Due to this long time frame it is possible that the accuracy of the data may be impacted by the mother's ability to recall all of the past events.
  • PRAMS surveys are mailed based on address information collected from the birth certificate files and other sources. Surveys are only printed in English and Spanish. Surveys administered by the telephone are only in English and Spanish. Therefore, populations with language barriers may not complete the survey. It is possible that the results in the non-response population could differ from those of the respondents. To compensate, PRAMS includes a non-response weight for each group based on specific demographic information of non-respondents.
  • Approximately 200 women are selected each month to participate in the survey.  During 2009-2011, the overall response rate ranged from 66-70% (CDC PRAMS requires a minimum of 65% response rate to report data at the national PRAMS level). Response rates for the oversampled groups of U.S.-born African-American and American Indian mothers are lower and could results in potential non-response bias.

Folic acid data:

  • Poverty was determined using the federal poverty levels or guidelines issued annually by the U.S. Department of Health and Human Services (HHS). The FPL is often used by federal programs to determine financial eligibility of individuals (based on the total number of persons in a household) for public benefit programs, such as Children's Health Insurance Program, Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), and Supplemental Nutrition Assistance Program (SNAP) (formerly Food Stamp Program). The HHS poverty guidelines, or percentage multiples of them (such as 125% FPL, 150% FPL, or 185% FPL), are used as an eligibility criterion by a number of federal programs. For example, WIC uses less than or equal to 185% FPL or receiving Medicaid as an eligibility criterion for women and children to enroll. The poverty level (at 100% FPL) for a four person family was $22,050 in 2009, $22,050 in 2010, and $22,350 in 2011 in the 48 contiguous states (which represents the data in the folic acid and poverty chart). To learn more, go to: HHS Poverty Guidelines.

  • PRAMS data was displayed using three categories of poverty. "Poor" includes households whose incomes are within 0-100% of the federal poverty level. "Near-poor" poverty includes households whose incomes are within 101-185% of the federal poverty level and "Not poor" are those with household incomes greater than 185% of the federal poverty level.

Folic acid data:

  • A weighted percent is an adjustment of the crude percent (which is just the count divided by sample size or N) and takes into account variables like sampling design and characteristics of survey respondents (e.g. age, sex, race/ethnicity) to make the percentage generalizable to all Minnesota mothers that had a live birth during that time period. Sample weighting is done so that unbiased population estimates can be calculated using the results of a survey.
  • Minnesota PRAMS statistics are based on weighted data. The weights are adjusted to account for sample design, nonresponse patterns, and omissions from the sampling frame. Weighting is necessary to give unbiased estimates.

Folic acid data:

  • For some surveys, it is important to ensure that there are enough members of a certain subgroup in the population so that more reliable estimates can be reported for that group. To do this, members of a specific subgroup of interest are oversampled by selecting more people from this group than would typically be done if everyone in the sample had an equal chance of being selected.
  • PRAMS data are essential to implementing Minnesota´s goal of eliminating health disparities. In Minnesota, African American (U.S.–born) and American Indian mothers have poorer birth outcomes than other mothers. Therefore, African American and American Indian mothers are oversampled in order to obtain estimates that are more precise for these maternal populations.

To learn more about birth defects, contact the MDH Birth Defects Program. To learn more about folic acid, contact the Minnesota PRAMS program. For more about the birth defects data and measures developed by the MN Environmental Public Health Tracking Program, contact MN Public Health Data Access.