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  • What is fertility and infertility?
    • Fertility is the ability to conceive a child. Infertility means not being able to become pregnant.

  • How does WI EPHT measure fertility?
    • The WI EPHT uses the Total Fertility Rate (TFR) as a measure that compares fertility across different groups. It is the percent of average number of births to a group of 1,000 women if they experienced the age-specific birth rates observed in a given year. TFR = Sum of age-specific fertility rates * 5

  • Why is total fertility rate used as a measure of fertility and infertility for WI EPHT?
    • Rates can provide background into how fertility varies geographically in relation to changes in potentially related environmental risk factors and how it has varied over time within the United States.

      Several measures have been used to track fertility from the global down to the local level. Typically, the general fertility rate (GFR) (# of live births/women of reproductive age 15-44) and the total fertility rate (TFR) are used. The total fertility rate differs from the general fertility rate because it adjusts for age-specific differences in fertility and allows for a more true comparison of rates across time and place.

      Similar to the GFR, the TFR may not be specific enough to track specific changes related to environmental risk factors; however, if the estimate of 10% is correct, then this measure can be used with other measures including measures of ambient concentrations of pollutants to look for potential associations with population level changes in fertility and generate some well informed hypothesis or areas for future investigations.

  • What is the relationship between infertility and the environment?
    • Approximately 10% of problems with fertility are unknown, but some have thought environmental contaminants are a major contributor. Environmental contamination can have multi-generational impacts on reproduction that need to be studied and tracked long term.

      There are many studies that suggest environmental exposure effects infertility:
      * In 2006, a study by Barrett found exposures to a number of compounds, such as materials found in some plastics (phthalates), persistent contaminants produced as flame retardants and degreasers, polychlorinated biphenyls (PCBs), dioxin, and other pesticides may be affecting human fertility.
      * In 2005, a study by Windham found environmental effects on menstrual/ovulatory function.
      * In 2001, Skakkebaek hypothesized that two male reproductive birth defects-mislocation of the uretha opening on the penis (hypospadias) and undescended testicles (cryptorchidism), and testicular cancer are related to exposure to endocrine disrupting compounds in the environment such as DDE and DDT, both pesticides previously used for mosquito control among other things in the United States and currently used in some areas around the world.

      According to the American Society of Reproductive Medicine, about one-third of infertility is caused by male factors, one-third by female factors, and one-third by both male and female. Male factors include low sperm count and sperm abnormalities, while female factors include ovulation disorder, a blocked fallopian tubes and birth defects in the mom.

  • What are the risk factors for women?
    • The cause of infertility can rest in the woman or the man, or can be from unknown factors or a combination of factors listed below:

      * age

      * stress

      * poor diet

      * athletic training

      * being overweight or underweight

      * tobacco smoking

      * alcohol use

      * sexually transmitted diseases (STDs)

      * health problems that cause hormonal changes

      Some health issues also increase the risk of fertility problems.

      * irregular periods or no menstrual periods

      * stress

      * very painful periods

      * endometriosis

      * pelvic inflammatory disease

      * more than one miscarriage

      What are the risk factors for men?

      The number and quality of a man's sperm can be affected by his overall health and lifestyle. Some things that may reduce sperm number and/or quality include:

      * alcohol use

      * drug use

      * exposure to environmental toxins, including pesticides and lead

      * tobacco smoking

      * medicines

      * radiation treatment and chemotherapy for cancer

      * age

  • How can infertility be prevented?
    • Infertility is a complex problem - it does not have a single cause because getting pregnant is a multi-step chain of events. Most healthy women under the age of 30 shouldn't worry about infertility unless they've been trying to get pregnant for at least a year. At this point, women should talk to their doctors about a fertility evaluation. Men should also talk to their doctors if this much time has passed.

      In some cases, women should talk to their doctors sooner. Women in their 30s who've been trying to get pregnant for six months should speak to their doctors as soon as possible. A woman's chances of having a baby decrease rapidly every year after the age of 30. So getting a complete and timely fertility evaluation is especially important.

      No matter how old you are, it is always a good idea to talk to a doctor before you start trying to get pregnant. Doctors can help you prepare your body for a healthy baby. They can also answer questions on fertility and give tips on conceiving.

All external hyperlinks are provided for your information and for the benefit of the general public. The Department of Health Services does not testify to, sponsor, or endorse the accuracy of the information provided on externally linked pages.

Last Revised: January 28, 2014

Data

Data Query

Total Fertility Rate

Access the fertility rate data in the WI EPHT online database.

The WI EPHT online database has data about other reproductive outcomes. Review the Data Details below to learn about interpreting the data.

Data Details

What is the data source?

The website provides data from the statistical resident birth and death files, maintained by the Wisconsin Vital Statistics Records Office, Wisconsin Department of Health Services. This office also provides reproductive outcomes data on the Wisconsin Interactive Statistics on Health.

How does WI EPHT measure reproductive outcomes?

The WI EPHT website includes the following measures:

  • Annual percent of singleton premature babies by state by gender by age by race
    • Annual count of singleton premature babies by state by gender by age by race
    • Annual percent of singleton very premature babies by state by gender by age by race
    • Annual count of singleton very premature babies by state by gender by age by race
    • Annual percent of low birth weight babies by state by gender by age by race
    • Annual percent of singleton low birth weight babies by state by gender by age by race
    • Annual birth rate per 1,000 babies by state by gender by age by race
    • Annual infant mortality rate per 1,000 babies by state by gender by age by race
    • Annual perinatal mortality rate per 1,000 babies by state
    • Annual perinatal mortality counts by state
    • Multi-year neonatal mortality rate per 1,000 babies by state by gender by age by race
    • Multi-year neonatal mortality count of babies by state by gender by age by race
    • Annual neonatal mortality rate per 1,000 babies by state
    • Annual neonatal mortality count of babies by state
    • Multi-year post-neonatal mortality rate per 1,000 babies by state by gender by age by race
    • Multi-year post-neonatal mortality count of babies by state by gender by age by race
    • Annual post-neonatal mortality rate per 1,000 babies by state
    • Annual post-neonatal mortality count of babies by state
    • Annual singleton birth count by state by gender by age by race
    • Annual singleton birth rate per 1,000 babies by state by gender by age by race
    • Annual total birth count by state by gender by age by race
    • Annual total fertility rate by state
    • Annual singleton sex ratio by state

    • Annual percent of low birth weight babies by county
    • Annual percent of singleton low birth weight babies by county
    • Annual percent of singleton premature babies by county
    • Annual count of singleton premature babies by county
    • Annual percent of singleton very premature babies by county
    • Annual count of singleton very premature babies by county
    • Annual birth rate per 1,000 babies by county
    • Annual singleton birth count by county
    • Annual singleton birth rate per 1,000 babies by county
    • Annual total birth count by county
    • Annual total fertility rate by county
    • Multiple years of infant mortality rate per 1,000 babie by county
    • Multiple years of infant mortality count by county
    • Multiple years of perinatal mortality rate per 1,000 babies by county
    • Multiple years of perinatal mortality counts by county
    • Multiple years of neonatal mortality rate per 1,000 babies by county
    • Multiple years of neonatal mortality counts by county
    • Multiple years of post-neonatal mortality rate per 1,000 babies by county
    • Multiple years of post-neonatal mortality counts by county
    • Annual singleton sex ratio by county
  • What are some considerations for interpreting the data?

    While significant effort is made to ensure the accuracy and completeness of the data, there are limitations that are listed below:

    • There are cooperative exchange procedures in place to help ensure data are included for Wisconsin residents born in other states, but it is possible not all other states have provided complete information at the time this report was created. The numbers are likely quite small, and thus the incompleteness probably has limited impact on the measures provided from the EPHT program.
    • The measures are based on responses recorded on the birth certificate. There is not separate reporting specific to these reproductive outcomes.

    There are many factors that can contribute to a disease and should be considered when interpreting the data. Some of these include:

    • Demographics, e.g., race, gender, age
    • Socioeconomic Status, e.g., income level, education
    • Geographic, e.g., urban vs. rural
    • Changes in the medical field, e.g., diagnosis patterns, reporting requirements
    • Individual behavior, e.g., diet, smoking