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Quarterly Provisional Estimates - Technical Notes - Natality, 2016–Quarter 1, 2018

Nature and sources of data

Provisional estimates are based on all complete birth records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. National provisional estimates include events occurring to U.S. residents within the 50 states and District of Columbia. NCHS receives the birth records and monthly provisional occurrence counts from state vital registration systems through the Vital Statistics Cooperative Program. Provisional quarterly estimates are compared with final data when available (3).

Individual records are weighted, when necessary, to independent provisional counts of births occurring in each state by month. These monthly state-specific provisional counts serve as control totals and are the basis for the record weights used for computing provisional estimates. If the number of complete records is greater than the provisional count received from the state, the state-specific number of complete records is used instead, and the weight is set at 1.

Table I shows the percent completeness of the provisional data by month for the United States and each jurisdiction based on where the births occurred. The percent completeness is obtained by dividing the number of complete records from each state for each month by the corresponding provisional count and multiplying by 100. The record weights described above are calculated by taking the inverse of the percent completeness (divided by 100) by state and month. Although data by place of occurrence are used to compute the weights, all rate estimates are for the residents of the 50 states and District of Columbia.


Table I. Natality data completeness as a percentage of monthly provisional count: United States, each state, District of Columbia, and New York City, Quarter 1, 2018
Area 2018-Jan 2018-Feb 2018-Mar
Total U.S. 100 100 100
Alabama 100 100 99.9
Alaska 100 100 99.9
Arizona 100 100 100
Arkansas 99.9 99.9 99.9
California 100 100 99.9
Colorado 100 100 100
Connecticut 100 100 100
Delaware 99.9 100 99.9
District of Columbia 100 100 100
Florida 100 100 100
Georgia 100 100 100
Hawaii 99.8 99.9 99.9
Idaho 99.9 100 99.9
Illinois 100 100 100
Indiana 100 100 99.8
Iowa 100 100 99.9
Kansas 100 100 100
Kentucky 99.8 100 99.8
Louisiana 99.8 99.9 99.5
Maine 100 100 100
Maryland 100 100 99.9
Massachusetts 100 100 100
Michigan 100 100 100
Minnesota 100 100 100
Mississippi 100 100 100
Missouri 99.9 99.9 99.9
Montana 100 100 99.9
Nebraska 99.8 100 99.9
Nevada 100 100 100
New Hampshire 99.9 99.7 99.9
New Jersey 100 100 99.2
New Mexico 99.9 99.9 99.6
New York1 100 100 99.9
New York City 100 100 100
North Carolina 100 100 99.9
North Dakota 100 100 100
Ohio 100 100 100
Oklahoma 100 100 100
Oregon 100 100 100
Pennsylvania 99.9 100 99.7
Rhode Island 100 100 100
South Carolina 100 100 100
South Dakota 100 100 100
Tennessee 99.9 99.9 99.8
Texas 100 100 100
Utah 100 100 100
Vermont 100 100 100
Virginia 99.9 100 99.8
Washington 100 100 100
West Virginia 99.9 100 99.7
Wisconsin 99.9 99.9 99.9
Wyoming 100 100 100

1 Excludes New York City.

NOTE: The percent completeness is obtained by dividing the number of complete records from each state for each month by the corresponding provisional count and multiplying by 100. NCHS receives the birth records and monthly provisional occurrence counts from state vital registration systems through the Vital Statistics Cooperative Program.


Population denominators

Population estimates used for computing rates are postcensal estimates, which originate from the U.S. Census Bureau and are based on the 2010 census (5). All population estimates used for a single data year are based on population estimates of the same vintage (i.e., the same reference year). Changes in rates between years in part reflect differences between vintages of the population estimates. Quarterly rates are based on the population estimates for the month in the midpoint of the quarter. Rates for 12-month periods are based on the midyear population estimate.


Computing rates

The “12 months ending with quarter” birth rates are on an annual basis per 1,000 estimated population within specified age groups. The general fertility rate refers to the total number of births per 1,000 women aged 15-44. Birth rates for women aged 50 and over have historically been too small to compute reliable age-specific birth rates. Consistent with other reports, birth rates to women aged 45 and over are computed by including all births to women aged 45 and over in the numerator, while the denominator includes population estimates of women aged 44-49 years (1-3). For comparability to the annual birth rate estimates, quarterly birth rates (i.e., a 3-month period) have been annualized to represent births per year per 1,000 population that would be expected if the quarter-specific rate prevailed for the year.

Other rates (e.g., preterm birth rates, term birth rates, cesarean delivery rates) are presented as per 100 births. It is not necessary to annualize these quarterly rates as described above because they reflect percentages of births occurring in a given quarter. Estimates of birth rates at 42 weeks gestation or later (post-term) are not presented due to the small number of births in this group.


Accuracy of estimates

Provisional estimates are subject to some nonrandom sampling error. The quarterly provisional estimates are based on data that is potentially more incomplete for the most recent months. Data are weighted to independent control counts of births, and no imputations have been performed, because it is assumed that the data are missing at random (i.e., the degree of missing data is unrelated to estimates of reproductive health). Estimates of completion rates by month were all above 95% for the United States. However, certain states may have more delayed reporting, and it is unknown whether indicators of reproductive health may be different for these states compared with states having complete reporting. Even if no differential delay occurred, some sampling error would still exist for rate estimates, because they are based on incomplete data. A guideline for the size of this sampling error is given by deriving the variation that would occur if the data were missing at random (6); standard errors for birth rates have been calculated according to these methods, accounting for sampling error.

Partly because of the factors discussed above, provisional estimates of birth rates are rarely higher than the true rate. Historically, provisional estimates of birth rates track closely with estimates based on final data (7). Based on simulations of various levels of data completeness, ranging from 50% through 90%, both quarterly and 12 month-ending estimates of the indicators included in this release can be expected to be within 1-2% of the estimates based on complete data. Exceptions were noted for birth rates among women aged 10-14 and 45 and over under scenarios where data completeness was 80% or lower. For these two age groups, the percent differences between estimates based on complete data and those based on various levels of incomplete data were larger than 1% because the birth rates are small (0.2 and 0.9 per 1,000, respectively).  However, the absolute differences between the rates across various levels of data completeness was approximately 0.1 for both of these age groups. For example, estimated birth rates for females aged 10–14 under various levels of completeness ranged from 0.2 through 0.3 per 1,000, while those for women aged 45 and over ranged from 0.8 through 0.9 per 1,000. Notably, these simulations assumed data were missing at random.

Because the timeliness of birth reporting has been improving, accuracy of the estimates may change over time. Estimates for previously released quarters are revised based on new data and updates received since the previous release.  As a result, the reliability of estimates for a specific quarter will improve with each quarterly release, and estimates for previous quarters may change with the addition of updated data. Estimates may differ from previously published preliminary data due to rounding, application of different record weights, or the use of updated population estimates.


Interpretation of changes over time

Unless otherwise specified, a difference in age-specific birth rates is reported only if statistically significant at the 0.05 level by the test given in reference 6. That test uses a variance estimate that includes both the random fluctuation in the true number of births and the random sampling error. Similarly, differences in percentages (e.g., cesarean delivery and preterm birth) between the most recent quarter and the same quarter of the preceding year are reported only if statistically significant at the 0.05 level according to methods outlined in reference 8.



The interactive dashboard was designed by Anthony Lipphardt.



  1. Martin JA, Hamilton BE, Osterman MJK et al. Births: Final data for 2015. National vital statistics reports; vol 66, no 1. Hyattsville, MD: National Center for Health Statistics. 2017.
  2. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018.
  3. Hamilton BE, Martin JA, Osterman MJK, Driscoll AK, Rossen LM. Births: Provisional data for 2017. Vital Statistics Rapid Release; no 4. Hyattsville, MD: National Center for Health Statistics. May 2018.
  4. National Center for Health Statistics, National Vital Statistics System. Guide to completing the facility worksheets for the certificate of live birth and report of fetal death (2003 revision). 2016 update.
  5. U.S. Census Bureau. Population estimates: 2014 monthly national population estimates.
  6. Hamilton BE, Martin JA, Ventura SJ. Births: Preliminary data for 2005. National vital statistics reports; vol 55 no 11. Hyattsville, MD: National Center for Health Statistics. 2006.
  7. Hamilton BE, Sutton PD. Recent trends in births and fertility rates through June 2012. Health E-Stats. 2012.
  8. National Center for Health Statistics. User guide to the 2010 natality public-use file. Hyattsville, MD.