Low Birthweight

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Percentage of live births with low birthweight (< 2,500 grams). The 2023 County Health Rankings used data from 2014-2020 for this measure.

Low Birthweight can be due to preterm births (<37 weeks of gestation) and intrauterine growth restrictions that are associated with increased infant morbidity and mortality risks.1 Factors that increase the likelihood of preterm births include multiple births, pre-eclampsia, and infections such as chorioamnionitis, bacterial vaginosis, and sepsis.2,3 Barriers to proper nutrition and adequate prenatal care can result in slowed intrauterine growth. Stress and exposure to pollution are also negatively associated with intrauterine growth.4 Substance misuse during pregnancy also can lead to low birthweight.1,5

Low birthweight is an important public health indicator that can be used to assess maternal health, nutrition, healthcare delivery, and poverty.3 Infants born with low birthweight have approximately 20 times greater chance of dying than those with normal birthweight.1,3 Infants who survive may face adverse health outcomes such as decreased growth, lower IQ, impaired language development, and chronic conditions (e.g., obesity, diabetes, cardiovascular disease) during adulthood.3,4

Data and methods

Data Source

National Center for Health Statistics - Natality files

Data on deaths and births were provided by NCHS and drawn from the National Vital Statistics System (NVSS). These data are submitted to the NVSS by the vital registration systems operated in the jurisdictions legally responsible for registering vital events (i.e., births, deaths, marriages, divorces, and fetal deaths). We requested this data for the first time for the 2018 Rankings. This was done because of the discontinuation of Health Indicators Warehouse. This change also allows to to perform additional analyses for state and national reports which if obtained from CDC WONDER would have numerous missing counties. 

Counties can find the same data from CDC WONDER. However, we use the raw data files. CDC WONDER does not report data for all counties per their missing data criteria.

The methods for calculating the error associated with death rates can be found here:


For counties with fewer than 20 births a missing value for all values is reported. 

For counties with between 20 and 99 births a gamma adjustment from the poisson distribution is used to calculate the CIs. 

For counties with 100 births or more CIs are calulated according to the normal distribution. Standard errors (SE) and birth rates for each age group are calculated. These SEs are squared and multiplied by the square of the weights and then divided by the total number of births over all age groups. The sum of these provides the variance of the estimate for each county. The square root of the variance gives the standard deviation which is then used as estimate +/- 1.96*STDEV. 

Key Measure Methods

Low Birthweight is a percentage

Low Birthweight is the percentage of live births where the infant weighed less than 2,500 grams (approximately 5 lbs., 8 oz.).

Births are counted in the mother's county of residence

Births are counted in the county corresponding to the mother’s address on the child’s birth certificate, regardless of where the child was born.

Some data are suppressed

A missing value is reported for counties with fewer than 10 low birthweight births in the time frame.


The numerator is the number of live births for which the infant weighed less than 2,500 grams (approximately 5 lbs., 8 oz.) over seven years.


The denominator is the total number of live births for which weight was recorded over seven years.

Can This Measure Be Used to Track Progress

This measure can be used to track progress with some caveats. It is important to note that the estimate provided in the County Health Rankings is a 7-year average. However, in most counties, it is relatively simple to obtain single-year estimates from the resource included below. 

Finding More Data

Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:

  • Age
  • Gender
  • Race
  • Education

We recommend starting with the CDC WONDER database, which contains information on birth rates by race, ethnicity, age, and more for counties with populations of 100,000 or more. Please note that demographic information is available both on the mother (age, race, education, income, subcounty area) and infant (gender, race).


1 Hughes, M. M., Black, R. E. & Katz, J. (2017). 2500-g Low birth weight cutoff: History and implications for future research and policy. Maternal and Child Health Journal, 21, 283–289 (2017). https://doi.org/10.1007/s10995-016-2131-9

2 Osterman, M. J. K., Hamilton, B. E., Martin, J. A., Driscoll, A. K., & Valenzuela, C. P. (2022). Births: Final data for 2020. National Vital Statistics Reports, 70(17). https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-17.pdf

3 Cutland, C. L., Lackritz, E. M., Mallett-Moore, T., Bardají, A., Chandrasekaran, R., Lahariya, C., Nisar, M. I., Tapia, M. D., Pathirana, J., Kochhar, S., Muñoz, F. M., & Brighton Collaboration Low Birth Weight Working Group. (2017). Low birth weight: Case definition & guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine35(48 Pt A), 6492–6500. https://doi.org/10.1016/j.vaccine.2017.01.049

4 UNICEF. (2019, May). Low birthweight. Accessed February 24, 2022. https://data.unicef.org/topic/nutrition/low-birthweight/

5 Forray A. (2016). Substance use during pregnancy. F1000Research5, F1000 Faculty Rev-887. https://doi.org/10.12688/f1000research.7645.1