Birthweight productivity of prenatal care.

AuthorWarner, Geoffrey
  1. Introduction

    This paper investigates the health of newborns, using the approach of Mark Rosenzweig and Paul Schultz (1982, 1983). They acknowledged the influence of population heterogeneity in unobserved characteristics on child health and the possible influence on parental behavior. The heterogenous characteristic in question is the innate level of health stock or health endowment. I extend their work by incorporating the number of visits and a visits delay interaction term into the measure of prenatal care and including measures of maternal anthropometry in the birthweight production equation. In addition, I include maternal education in the birthweight equation to test the Rosenzweig and Schultz hypothesis that education influences birthweight exclusively through input demand. The goal of this paper is to obtain consistent estimates of the prenatal care parameters in the birthweight production function that can then be used to assess the effectiveness of prenatal care in reducing the incidence of low-weight births.

    Section 2 of this paper discusses the development of the model. Section 3 discusses the data set and estimation method. Section 4 discusses the results of the regressions. Section 5 summarizes the main conclusions and mentions some policy implications.

  2. Analytical Framework

    Rosenzweig and Schultz (1982, 1983) investigated the role of parental behaviors in the production of birthweight and the determination of the fetal growth rate. They correctly reasoned that parental expectations about the child's "health endowment" can influence parental behavior. For example, if a woman's previous children were full term and normal weight, she may not feel the need to start prenatal care as early for subsequent children as for the first child. Because the child's health endowment is unobserved and also affects his or her birthweight, an ordinary least squares regression of birthweight on parental inputs will yield inconsistent coefficients.

    In their model, Rosenzweig and Schultz use parental behaviors (prenatal care delay, maternal smoking, maternal age, and parity) as almost exclusive explanators of birthweight and fetal growth. Only the mother's race, metropolitan residence (Standard Metropolitan Statistical Area [SMSA]), and the SMSA size are nonbehavioral variables. Epidemiological research (Kelly et al. 1996) indicates that maternal anthropometric characteristics have a strong influence on birthweight. In particular, the mother's height is seen as a limiting factor of fetal growth (Institute of Medicine 1985).

    I assume that maternal anthropometry is an important determinant of birthweight and fetal growth and have included the mother's height, prepregnancy weight, pregnancy weight gain (adjusted for gestation),(1) and the mother's own birthweight in the birthweight equation. I estimate the following equation where the x variables are the noncare variables including the maternal anthropometry variables. (The exponent a takes on the values 0, 2, and 0.5.)

    b = [[Delta].sub.1]x + [[Delta].sub.2]m + [[Delta].sub.3]n + [[Delta].sub.4](n/m) + [[Delta].sub.5][m.sup.a] + [[Delta].sub.6][n.sup.a] + e (1)

    The Rosenzweig and Schultz framework is further expanded by giving prenatal care two measures. The first, m, is the time interval, in weeks, between the last normal menstrual period and the first prenatal care visit. The second, n, the standardized number of prenatal care visits, is the observed number of visits adjusted for the length of the pregnancy. Gestation is controlled for by comparing the observed number of visits a mother made to the number recommended by the American College of Obstetrics and Gynecology (ACOG), for the length of her pregnancy.(2) The standardized number of visits (the number of visits a mother would have made in a full-term pregnancy) is calculated by multiplying the recommended number of visits associated with a full-term pregnancy (15) by the proportion of recommended visits made (the observed number of visits divided by the recommended number of visits for that gestation).(3) This dual continuous variable method of measuring prenatal care is preferable to a single categorical index because it allows identification of the independent effects of delay and visits on birthweight.

    Except for Warner (1995), there has not been any empirical research focusing on whether subsequent frequent visits can compensate for extended delay in initiating prenatal care, or whether early initiation of prenatal care needs frequent follow-up visits to be beneficial. I again include an interaction term, the n/m variable, in the birthweight production equation to measure the degree of substitution or complementarity, if any exists. It is constructed to increase or decrease as prenatal care use increases or decreases, respectively. A positive coefficient in the birthweight regression would indicate complementarity, a negative one substitution, and an insignificant coefficient would indicate neutrality. With regard to policy, substitution implies an either/or option: start prenatal care early or visit the obstetrician often. Complementarity implies the lack of options: start prenatal care early and visit the obstetrician often.

    The marginal birthweight product of a prenatal care variable will be composed of a direct, independent effect measured by its own coefficients and an indirect effect dependent on the levels of the prenatal care variables and the coefficient on the interaction term, as follows:

    [Delta]b/[Delta]m = [[Delta].sub.2] + [[Delta].sub.4](-n/[m.sup.2]) + a[[Delta].sub.5][m.sup.a-1] (2)

    [Delta]b/[Delta]n = [[Delta].sub.3] + [[Delta].sub.4](1/m) + a[[Delta].sub.6][n.sup.a-1] (3)

    As previously stated, using the observed values of prenatal care will yield inconsistent coefficients due to the correlation between prenatal care use and unobserved factors such as the health endowment. A variable that is correlated with prenatal care use but uncorrelated with the unobserved health endowment is needed, and such a variable is provided by the first stage of the two-stage least squares method of estimation, a regression of observed prenatal care on an appropriate set of instrumental variables. These are reduced form prenatal care demand equations and have been reported by Rosenzweig and Schultz (1982, 1983), Joyce (1994), and Warner (1995). The prenatal care instruments are the traditional demand determinants: measures of income and availability. The variables used to measure income are household income, source of income, parental education, and method of financing prenatal care. The variables that measure availability are descriptors of the health infrastructure of the state of residence of the mother. The number of physicians, registered nurses, and hospital beds and the amount of expenditures on health and hospitals, all per capita at the state level, are the variables I use to describe the health infrastructure producing the prenatal care available for a mother to receive. I also include state environmental expenditures per capita to capture any effects that air and water quality may have on prenatal care utilization. The state tax on cigarettes is included to capture any effect public policy toward smoking has on prenatal care utilization. Other variables included as prenatal care demand determinants are parental education, number of children in the household, work status (raises the mother's price of time), and urban residence (medical facilities and physicians are concentrated in cities). A mother's marital status and cohabitation status are included because care provided by a husband or relatives may substitute for some purchased care. Attendance at birthing classes and participation in the Women's, Infants', and Children's program (WIC) may also influence prenatal care utilization through greater contact with health professionals. Foreign maternal birth is included because some cultures view pregnancy and childbirth as a normal condition of womanhood that does not require the intensive intervention of medical professionals. Pregnancy wantedness is included because mothers may demand less care for an unwanted pregnancy.

    The determination of observed birthweight has two paths: the rate per unit time at which the fetus grows (fetal growth rate) and the amount of time spent in the uterus (gestation). If all observations had the same gestation, comparing birthweights would be equivalent to comparing fetal growth rates. Comparing observed birthweights having different gestations will confound fetal growth rate with gestation. Rosenzweig and Schultz estimate birthweight as a function of gestation and normalize it by dividing observed weight by predicted weight. The normalized value indicates the degree to which the newborn is small (index [less than] 1), appropriate (index = 1), or large (index [greater than] 1) for gestational age.(4)

    Like Rosenzweig and Schultz, I standardize birthweight so that it is comparable across gestations. The methodology I have chosen for controlling for gestation is similar to the Rosenzweig and Schultz method in that it involves the estimation of a birthweight/gestation function. It differs in that this function will not be used to compare observed birthweight to predicted birthweight but rather to calculate the predicted fetal weight gain over the remaining period from observed gestation to term delivery.(5) This predicted weight gain is then added to observed birthweight. My method makes the resulting birthweight value and its underlying fetal growth rate a weighted average of two values: observed birthweight at the individual level and observed birthweight at the sample level. The weights are observed gestation and remaining gestation to term. For births that are close to term, this adjustment will be very small and will have an extremely limited impact on the regression estimates. Appreciable adjustments will occur with preterm infants. It is this group...

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