Natasha Simonsen and Professor Stephanie Fugal, Department of Health Science
ABSTRACT
This study identifies the correlation that exists between short birth space intervals and subsequently lower birth weights in newborns. The sample population was taken from the medical records of woman who gave birth in Utah County between 2000-2006. The medical records were analyzed using secondary data retrieved by the Utah Department of Health. A logistic regression model was used to determine the effect that varying birth space intervals have on birth weight of newborn in combination with several other risk factors. The additional factors included in the regression model were mother’s education level, marital status, number of prenatal care visits, gestational age, abnormalities, tobacco use during pregnancy, and obstetrics score. Women who had less than 24 month between births were more at risk (p-value=.000) to deliver a low birth weight infant (less than 2500 grams or 5.5 lbs). Results of this study indicate that a healthy birth weight in newborns is more likely to be achieved when live births are spaced with at least 24 months between deliveries. From this study, the data indicate waiting at least 24 months between deliveries will result in higher birth weights and more positive birth outcomes. The recommendation for Utah County is to educate and encourage women to increase their birth spacing intervals in order to positively affect both birth weight and birth outcomes of their newborns.
INTRODUCTION
A short birth space interval is one of the most significant risk factors for negative birth outcomes in Utah County, most often resulting in low birth weight.1 In 2005, there were over 11,000 live births in Utah County, 18% of which were classified as closed spaced pregnancies (less then 24 months between deliveries); 17% were also categorized as having a low birth weight (less then five and a half pounds).1 The Baby-Your-Baby program, funded and supported by the Utah Department of Health, has successfully assisted Utah residents in reaching the Healthy People 2010 objective of preceding 90% of deliveries with prenatal care. In 2005, Utah led the nation with 91.6% of pregnant women entering prenatal care.1 Although this has been a great success in reproductive health, low birth weight continues to threaten the health of nearly one in five newborns across the state.1 According to recent data, many women in Utah are still placing themselves at high risk for negative birth outcomes by spacing their pregnancies too close together.1 This is becoming increasingly apparent in Utah County, which has the highest birthrate in the nation.2
The Director of the Utah County Division of the Woman Infants and Children’s program (WIC), Doreen Radford (D. Radford, [doreenr@state.ut.us], e-mail, October 12, 2006), expressed in recent communication that “in our clinics, we see many cases of short birth space intervals, but since women do not apply for services until after they are pregnant, it is too late for us to intervene. We are interested in finding effective messages and interventions that could be used to successfully reduce the number of short birth spaced pregnancies.” Thus, the purpose of this research was to identify whether birth space interval is a key predictor of low birth weight among women living in Utah County, where nearly 20% of all pregnancies are classified as closed spaced pregnancies.1 The ability to communicate this message and educate women regarding reproductive health will be beneficial to the residents of Utah County in allowing them to make informed decisions about family planning and birth spacing.
METHODS
Population and Sample
The data in this study was obtained from medical records collected by the Utah Department of Health. Utah statute (26-2-5) requires all live births to be reported to the State Registrar of Vital Statistics within 10 days of birth. The administrator of the birthing facility or the medical attendee to the birth is responsible for registering the birth with the state. Under the current program, hospital birth certificate clerks and medical attendee’s file vital statistics electronically to the state Office of Vital Records. The information on the birth certificate comes from a worksheet completed by the mother, the birth attendant, and the mother’s prenatal medical record, if available. The selected sample included data from all women who gave birth in Utah County between the years 2000-2006. The initial dataset included information from 65,536 births, which was then reduced to 35,905 births by eliminating data that was incomplete. Additional excluded data consisted of births by women who had no previous births, therefore, no birth space interval. The final dataset used in the analyses included 35,905 births where the mother had a previous pregnancy and the birth space interval could be calculated.
Data analysis
A frequency analysis and measure of central tendency and dispersion were carried out to summarize the characteristics of the sample. Logistic regression was used to predict the effect of birth space interval on birth weight of the baby. The birth space interval variable was generated by subtracting the current birth date (month and year) from the last live birth date (month and year). The births were then placed into one of two categories based on the length of the interval since the most recent preceding birth: women who had less than 24 months between births were categorized as closed-spaced pregnancies while any birth spaced by 24 months or more was categorized as appropriately-spaced pregnancies. Birth weight was also grouped into two categories; low birth weight (> 2500 grams) and a healthy birth weight (
Another variable termed “total number of pregnancies” was calculated by adding the number of live births, stillbirths, abortions whether elected or spontaneous, and ectopic pregnancies. The final data included woman between the ages 14-48 and birth spaces ranging from 7-327 months.
A number of variables were considered in the analysis based on a review of reproductive literature and potential confounding factors. These variables included education level of mother (1-17 year in school), marital status (married vs. other), number of prenatal care visits (0-40), number of gestational weeks (16-43), pregnancy abnormalities (yes vs. no), tobacco use during pregnancy (yes vs. no), alcohol use during pregnancy (yes vs. no), and health risks during the pregnancy (yes vs. no), as well as the total number of pregnancies (1-17)
The logistic regression model used in this study was a backward stepwise model in which insignificant variables were eventually dropped from the final model. The two variables dropped from the final model included alcohol use and health risks during pregnancy.
Table 1 presents a summary of the sample characteristics. The mean age of the birth mom was 28.41 (SD= 4.79, range 14-48), and they had on average 13.8 years of education (SD= 2.207, range 1-17) and had 10.12 prenatal visits (SD= 2.559, range 0-40). The majority of the women were married (93.8%), did not use tobacco (96.7%), and did not use alcohol (99.7%). The average birth weight was 3344.5 grams (SD=554.7, range 107-5783) with an average gestational age of 38.41 weeks (SD=1.85, range 16-43). In a little over half of the pregnancies risks were present (53.7%) but in most of the births there were no abnormalities present (88.3%). The average obstetrics score was 2.56 (SD=1.76, range 1-17).
Results from logistic regression analyses for each factor are shown in Table 2 (only significant variables are included). The risk of low birth weight increased as birth space intervals decreased. Woman who spaced their births less than 24 months between deliveries were 0.6 times as likely (p-value = .000) as woman who had at least 24 months between deliveries to have a child with a low birth weight. Woman who had achieved higher levels of education were 1.05 times more likely (p-value = .003) to have a child with a healthy birth weight. In addition, woman who had not received prenatal care were 0.96 times more likely (p-value = .000) to have a low birth-weight child.
As a mothers’ age increased, she was less likely to have a low birth weight infant (p-value = .051). Marital status was also a strong predictor of higher birth weight, where women who were not married were 1.4 times more likely (p-value = .004) to have a low birth weight infants. Woman who used tobacco during their pregnancy were 0.6 times more likely (p-value = .000) to have a low birth weight infant. As total number of pregnancies increased, so did the likelihood of having a low birth weight infant (p-value = .005). Predictably, there was also a strong correlation between gestational age and birth weight, where newborns who were preterm were 3.2 times more likely (p-value = .000) to have a low birth weight and when abnormalities were present at birth, the child was 0.7 times more likely (p-value = .000) more likely to have a low birth weight. Alcohol use and other risks during pregnancy were dropped from the regression model because their p-values deemed them insignificant for the purpose of this study.
DISCUSSION
When a woman becomes pregnant, her body is able to make physiological adjustments to ensure the health of the growing fetus, which may result in rapid depletion of the mothers vital nutrients. Women with closely spaced pregnancies do not allow their bodies the appropriate interval that is needed to replenish the nutritional deprivations of their previous pregnancy. Therefore, a short birth space interval may leave the woman in a compromised nutritional state increasing her risk for a subsequently poor pregnancy outcome. If a woman conceives while she is still breastfeeding, additional nutritional demands on the mother may also increase risks to the unborn fetus.3
There are several factors that can delay the growth of a fetus. Babies with congenital anomalies or chromosomal abnormalities are often associated with low birth weights. Problems with the placenta may pose risks by providing inadequate oxygen and nutrients to the fetus, thus resulting in a lower birth weight. There are also prenatal infections that can affect the developing fetus such as rubella, toxoplasmosis, and syphilis, which can lead to low birth weight. These and other factors may explain an association between abnormalities during pregnancy and low birth weight babies in the population.
Smoking during pregnancy can also lead to premature birth due to a premature rupture of membranes. Women who smoke during pregnancy are more likely deliver early in an effort to protect the baby from harmful smoke which can lead to serious complications for the baby. It is not surprising that there was also a strong correlation between smoking and low birth weight in a population. A smoker’s placenta is also thinner making her more likely to have placenta abruption.4
There are additional medical risks that can lead to low birth weight such as high blood pressure, certain infections, and heart, kidney and lung problems. An abnormal uterus or cervix can likewise increase the mother’s risk of having a premature or low birth weight baby.
However, some risks during pregnancy can increase a woman’s likelihood of having an overweight baby, a common example of this being obesity. Woman who are obese are more likely to have higher birth weight babies.5 Although certain risks are associated with low birth weight, this may have been balanced by risks such as obesity and diabetes that can increase a child’s birth weight which resulted in risks during pregnancy having no significant effect on birth weight in the population.5
Over the years, Utah has remained the top state in the nation for fewest one-parent families and currently holds the title of “fewest births to unwed mothers.”6 Although Utah’s birthrate is highest in the nation, its out-of-wedlock birthrate is the lowest in the nation. Unmarried status has been proven to be strongly associated with social disadvantage and particular risk factors for low birth weight, specifically unemployment, smoking and previous pregnancy terminations, which in turn have an impact on obstetric scores.7
Socioeconomic factors such as low income and lack of education have been strongly associated with increased risk of having a low birth weight baby, although the underlying reasons for this are not well understood. Women under 17 or over 35, unmarried mothers and women who have had a previous preterm birth are at increased risk of having low birth weight babies. Teenagers, in particular, may not have good health habits which can have long-term effects on the unborn child’s health. Lower levels of education are also associated with higher levels of stress which can increase the risk of having a low birth weight baby.8
A significant reduction in birth weight has been found to be associated with average daily alcohol consumption in the literature, but this factor was not supported by this research. This result could possibly be due to low alcohol consumption among the sample population, present in only 0.3% of the cases. Therefore, it did not appear to have a significant effect on birth weight.
CONCLUSION
Although there is a great need to address the possible health threats that are associated with short birth space intervals, little is being done to address the magnitude of this problem. In order to ensure both maternal health and a positive birth outcome, a community intervention is necessary to educate women about the possible adverse health risks associated with short birth space intervals. It is essential to educate and encourage women to make decisions regarding their birth spacing behaviors to increase birth outcomes of their infants. Dissemination of this information must not be delayed and an appropriate target audience must be identified to prevent future poor birth outcome including low birth weight. Most often during pregnancy, health education occurs during prenatal care. However, by the time a woman is participating in prenatal care, the message may be too late due to the lost opportunity for intervention. Individuals and couples should consider health risks and benefits along with other circumstances such as their age and social and economic circumstances when planning for their next pregnancy.
Because the nutritional burden on the mother between pregnancies depends on the extent of breastfeeding, the birth space interval is not always the best measure of whether the mother has had a chance to recover from the pregnancy, in terms of her depleted nutritional status. Therefore, it is necessary to also examine the ‘recuperative interval’ (duration of the non-pregnant, non-lactating interval) instead. Thus, further research with more comprehensive control of potentially confounding variables, such as breastfeeding, is also needed.
References
- Utah Department of Health. 2006 Policy & Procedures, Nutrition Risk Manual [serial online]. October 2006. Available at: www.health.utah.gov/wic/policy Accessed July 10, 2007.
- Deborah Bulkeley. Utah’s birthrate is tops. Deseret Morning News [serial online]. October 2005. Available at: http://deseretnews.com/dn/view/0,1249,635152902,00.html Accessed July 10, 2007.
- Fuentes-Afflick E, Hessol NA. Interpregnancy interval and the risk of premature infants. University of California, San Francisco. March 2000.
- Effects of Maternal Cigarette Smoking on Birth Weight and Preterm Birth [serial online]. September 1990: issue 39;662-665. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/00001782.htm Accessed July 10, 2007.
- Nanci Hellmich, Study: More babies overweight. USA TODAY [serial online]. August 2006. Available at: www.usatoday.com/news/health/2006-08-09-overweight-babies_x.htm Accessed July 10, 2007.
- Utah’s Indicator-Based Information System for Public Health (IBIS-PH), Complete Indicator Profile of Birth Rates. Available at: http://ibis.health.utah.gov/indicator/complete_profile/BrthRat.html. Accessed July 10, 2007.
- Raatikainen K, Heiskanen N, Heinonen S. Marriage still protects pregnancy. Department of Obstetrics and Gynaecology, Kuopio University Hospital, Finland [serial online]. October 2005:112(10):1411-6.
- Arnaud Chevalier and Vincent O’Sullivan. Mother’s education and birth weight. [serial online]. January 2007: issue 2.1. Available at: http://web.econ.uic.edu/espe2007/paper/F42.pdf Accessed July 10, 2007.