posure to environmental tobacco smoke contributes to respiratory illness among children.1-3 Residential exposure to such smoke, particularly in the first 2 years ...
Maternal Smoking and Medical Expenditures for Childhood Respiratory Illness
.IXw oEec- i 1i,7 7. ..... . .
Jeffrey J. Stoddard, MD, and Bradley Gray
Methods
dar year 1987. Respondents provided information about sociodemographic factors, health insurance coverage, use of medical care, self-reported health status, and health risk behaviors including smoking. Analyses presented in this paper are restricted to the subsample of 2624 children aged 5 years and under. Our results are weighted with the weighing factors intrinsic to the national survey to reflect 1987 national population estimates. Children aged 5 years and younger were selected for our primary analysis because, being of prekindergarten age, they are most likely to have been exposed to environmental tobacco smoke from parental smoking and because prior evidence indicates that younger children represent the group most at risk for environmental tobacco smoke-associated respiratory illness.2 The dependent variable used in this analysis is expenditures for medical encounters (including hospital care, outpatient services, emergency department care, physician services, and prescription medications resulting from such encounters) in which a respiratory illness was coded as a diagnosis. Expenditures are defined as actual payments made for services (regardless of source) and are to be distinguished from charges. Expenditure data in the National Medical Expenditure Survey were collected from administrative records; however, the survey inferred costs for health maintenance organizations and other services not paid for on a fee-for-
The National Medical Expenditure Survey is a population-based nationwide survey that was designed to yield estimates of health service usage and expenditures by the civilian, noninstitutionalized US population. A cohort of approximately 35 000 persons in 14 000 households were interviewed four times during calen-
Jeffrey J. Stoddard is with the Departments of Pediatrics and Preventive Medicine at the University of Wisconsin Medical School, and Bradley Gray is with the Department of Economics at the University of Wisconsin, Madison. Requests for reprints should be sent to Jeffrey J. Stoddard, MD, Meriter Hospital, 202 S Park St-6 Center, Madison, WI 53715. This paper was accepted July 29, 1996.
Introduction well established that exenvironmental tobacco smoke contributes to respiratory illness among children.1-3 Residential exposure to such smoke, particularly in the first 2 years of life, has been shown to constitute a risk factor for several acute respiratory conditions, including upper and lower respiratory tract illnesses.47 Exposure to environmental tobacco smoke has also been shown to be a significant risk factor for new cases of childhood asthma, and to be associated with additional episodes and increased severity of symptoms in asthmatic children.2'5','9 Finally, it has also been linked to impaired development of pulmonary function during childhood.20'21 The expenditures associated with the medical care of childhood respiratory illnesses are high. Recent estimates indicate that such spending for children under 15 years of age amounted to more than $8 billion annually in 1993 dollars.22 Although direct medical expenditures attributable to active and past smoking among adults have been estimated at $50 billion (again, in 1993 dollars),23 no study has estimated the expenditures associated with environmental tobacco smokeattributable disease among children. To determine such expenditures, we used family-level data contained in the 1987 National Medical Expenditure Survey. It is
now
posure to
American Journal of Public Health 205
Stoddard and Gray
TABLE 1-Sample Sizes and Weighted Population Estimates of Children, by Maternal Smoking Habits: Original Tabulations of the 1987 National Medical Expenditure Survey Child's Age 3-5 y 0-2 y Nonsmoking mother Sample cases Population estimate, in thousands Smoking mother Sample cases Population estimate, in thousands
service basis. Each individual health service expenditure in the national survey is a single record. For the current study, expenditures for emergency transport, medical supplies and equipment, allied health services, and overhead costs were excluded. Conditions included in the national survey were defined according to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD9-CM) coding recorded at the time of the medical encounter. Up to four diagnoses were recorded. Because diagnoses were not reported to reflect their order of clinical significance, this analysis counted as respiratory related any encounters in which a respiratory illness (ICD-9-CM codes 460 to 519) was coded. Exposure to environmental tobacco smoke has been linked to a wide variety of respiratory conditions, so a broad definition that encompassed all respiratory ICD-9-CM categories was used. This approach was taken to compare differential usage and expenditure rates among exposed and unexposed children for conditions that might reasonably be linked to environmental tobacco smoke exposure, while at the same time excluding extraneous conditions. To compare the two groups (exposed vs unexposed) according to their general medical care usage pattems, the expenditure levels for both groups for all other nonrespiratory conditions (all ICD9-CM codes other than 460 to 519) were also analyzed. The independent variable of interest used in this analysis is mother's smoking status, which was defined by self-report and coded as a dichotomous variable (current smoker or nonsmoker). Eliminated from our sample were those mothers whose smoking status was not ascertained; this reduced our sample size by 7%. Although the National Medical Ex206 American Journal of Public Health
Total
861 6 090
932 6 518
1 793 12 608
401 2 628
430 2 797
831 5 425
penditure Survey questionnaire asked respondents to quantify their smoking, the current study also performed more refined analyses detailing the number of cigarettes smoked per day; these results are not presented here, however, because the validity of self-reported smoking habits may be in question. Other independent variables in our multivariate models include child's age, sex, and race/ethnicity; census region of residence; urbanicity; family size and income; child's health insurance type; and maternal education. In addition to the larger sample, separate subsamples were created by age group for the multivariate analyses. All results presented in the text and tables have been statistically weighted to reflect 1987 national population estimates. Standard errors used to estimate statistical significance were derived through the Taylor series linearization method, which takes into account the National Medical Expenditure Survey's complex (stratified, multistage, and clustered) sampling design.24 To contemporize figures, the national survey's 1987 dollars were inflated into 1995 dollars with the use of the medical care inflation indices published by the Bureau of Labor Statistics.25 an unacceptably large percent(34.1%) of our sample, patemal smoking status was not ascertained. Because this nonresponse rate might introduce bias, fathers' smoking was not incorporated into our primary results as an independent variable. However, analyses were performed with the use of the subsample with available paternal smoking data. Our analysis includes a large number of children with no respiratory-related medical expenditures. Accordingly, a truncated regression technique was used: the
For
age
Tobit model. The Tobit model
assumes a
truncated or censored dependent variable and uses all observations, both those at the lower limit and those above it, to estimate independent effects.26'27 With the use of this approach, potentially confounding factors were modeled that could affect both the level of expenditures and the likelihood that a medical encounter for respiratory illness would occur. In addition, a standard approach was used to correct for heteroskedasticity common in cross-sectional analysis.28 To estimate the independent impact of matemal smoking on the level of expenditures for exposed children, estimated coefficients derived from our Tobit model were used to calculate both the probability of having an encounter for respiratory illness and the level of expenditures assuming at least one such encounter, holding all other independent variables constant at their mean levels. Expenditures per child per year were estimated by multiplying the estimated probability of an encounter by the expenditure amount given an encounter. Finally, estimated expenditures per child associated with environmental tobacco smoke were determined by taking the difference between predicted expenditures for children of smoking mothers and those for children of nonsmoking mothers.
Results The numbers of cases in our sample, the corresponding population estimates, and breakdown by maternal smoking status are all shown in Table 1. As demonstrated in this table, in 1987 approximately 5.4 million children aged 5 years and under had mothers who smoked. Percentages of children experiencing at least one episode of medical care for respiratory illness according to maternal smoking are shown in Table 2. These data are not adjusted for any other factors and only show differences according to maternal smoking status. For all children aged 5 years and under, 55% of those whose mothers smoked had at least one medical encounter for respiratory illness, compared with 50% of those whose mothers did not smoke. Table 2 also shows mean individuallevel medical expenditures for respiratory illness according to maternal smoking status. These results are expressed as average medical expenditure levels (per child per year) for children of smoking and nonsmoking mothers. The figures demonstrate that, without controlling for any other factors, children of smoking February 1997, Vol. 87, No. 2
Smoking and Medical Costs
mothers incur health expenditures for respiratory illness at a rate more than two and one-half times that of children of nonsmoking mothers. Table 3 exhibits estimated coefficients, standard errors, and P values from the Tobit model. As shown in Table 3, mother's smoking status is statistically significant (P < .05) as a positive predictor of increased expenditures. Additional analyses using the sample for which paternal smoking data were available revealed no statistically significant (P > .20) relationship between father's smoking habits and expenditures (data not shown). Applying the same model but including paternal smoking in this subsample did, however, result in a modest decrease (10%) in the maternal smoking coefficient. This may indicate that the estimated impact of matemal smoking in the full model partially reflects the impact of paternal smoking. We also undertook analyses designed to elucidate whether a doseresponse relationship existed between maternal smoking and respiratory expenditures. Using quantitative self-reported maternal smoking data, we observed no statistically significant dose-response relationship (dosage coefficient P > .30, data not shown). Using the same Tobit model, we did find a large, negative, but statistically insignificant (P > .10) relationship between maternal smoking and nonrespiratory expenditures. The magnitude of this coefficient is more than twice that estimated in the respiratory model but is opposite in direction (-358 as compared with 164). Table 4 shows the estimated independent effects of maternal smoking on the likelihood of experiencing a medical encounter and on overall medical expenditures for respiratory disease. The first row shows the independent impact of maternal smoking on the probability of experiencing a medical encounter related to a respiratory illness. The second row shows the estimated effect of maternal smoking on individual-level medical expenditures for respiratory illness, conditional upon having at least one medical encounter in which a respiratory illness was coded. The final row shows the combined effects of the increased probability of experiencing an episode of illness and the expenditures for the care for such illnesses. This table reveals the degree to which both the estimated likelihood of experiencing a medical encounter for a diagnosed respiratory condition and the medical expendiFebruary 1997, Vol. 87, No. 2
TABLE 2-Unadjusted, Weighted Medical Encounters (%) and Direct Medical Expenditures (per Child per Year)a for Childhood Respiratory Illness, by Maternal Smoking and Age Child's Age
Nonsmoking mother (n = 7376) Encounters, % Expenditures, $ Smoking mother (n = 3444) Encounters, % Expenditures, $
0-2 y
3-5 y
Total
58.2 149
42.6 106
50.1 127
63.7 412
46.0 274
54.5 341
Note. Data are from the 1987 National Medical Expenditure Survey. aThe expenditure totals are in 1995 dollars (rounded to nearest dollar) and include all expenditures for inpatient and outpatient medical care, physician services, and prescription drugs.
TABLE 3-Multivariate Regression Results (Tobit Model) of Medical Expenditures for Childhood Respiratory lllnessa: Newborn to 5 Years Variable Mother smokes Family characteristics Mother a college graduate (.16 years) Family income/family size Child's age -2 years Race/ethnicity Black non-Hispanic
Coefficient
Standard Error
P
164.1
73.6
.026
-81.9 0.0100
40.6 0.0045
.044 .028
172.0
52.1
.001
-242.0
118.0
.041
Note. Data are from the 1987 National Medical Expenditure Survey. aStatistically significant coefficient estimates (P < .05) only, controlled for insurance type (Medicaid, private, uninsured), maternal education (
