Abstract
Objectives. We examined the contribution of hospital type and quality of care to perinatal mortality rates in the city of Belo Horizonte, Brazil.
Methods. We used a cohort study of all births (40953) and perinatal deaths (826) in Belo Horizonte in1999. After adjusting for maternal education and birthweight, we compared mortality rates according to hospital category—defined by a hospital’s relation to the national Universal Public Health System (SUS)—and quality of care. We used the Wigglesworth Classification to examine perinatal deaths.
Results. After we controlled for birthweight and maternal education, the highest perinatal death rates were observed in private and philanthropic SUS-contracted hospitals (relative to private, non-SUS-contracted hospitals). Hospital quality was also directly associated with perinatal death rates. Mortality rates were especially high for normal-birthweight babies born in private SUS-contracted hospitals. Intrapartum asphyxia was the leading cause of preventable death.
Conclusions. In a class-segregated health care system, such as Brazil’s, disparities in quality of care between SUS-contracted and non-SUS-contracted hospitals contribute to the unacceptably high rates of perinatal mortality.
Brazil has a persistently high infant mortality rate (22.5 deaths/1000 live births in 2003)1 that disproportionately affects the disadvantaged population. Most of the country’s infant and perinatal deaths are because of conditions originating during the perinatal period that are considered preventable through access to quality health care. Although there are important regional disparities, most births (97%) take place in hospitals, and 77% are assisted by doctors. A high proportion of perinatal and infant deaths occur within the first hours after birth (30% in the first 24 hours of life), which suggests the importance of the level of hospital care.
Brazil’s Universal Public Health System (Sistema Único de Saúde, or SUS), which covers the medical expenses of almost 80% of the country’s population, relies on private hospitals contracted to SUS (37%), as well as hospitals run by the philanthropic sector (27%) and the government (36%).2 Private hospitals not contracted to SUS (non-SUS) provide care for the remaining minority who can afford private health insurance or direct payment. Consequently, there is a clear association between socioeconomic status and the type of health facility used. Hospital type can therefore be a marker for socioeconomic status,3,4 and it can also be an indicator of health care quality.5 Socioeconomic disparities in the quality of hospital care may in turn explain perinatal mortality differentials. Few studies have examined socioeconomic inequalities in perinatal mortality in Brazil, however, and quality of hospital care has not yet been systematically assessed.
We analyzed the role of hospital quality at the time of delivery and birth and its contribution to the high perinatal mortality rates in the city of Belo Horizonte. Situated in the more developed southeast region of Brazil, Belo Horizonte is the country’s fourth largest city, with 2.2 million inhabitants. We focused on the differential in perinatal mortality rate between hospital categories (SUS vs non-SUS hospitals) and quality of hospital care. Our ultimate goal was to provide public health policymakers with information that can guide the planning and implementation of measures to improve the health care system and reduce disparities in infant and perinatal mortality.
METHODS
This study is based on a 1999 cohort study involving surveillance of all births (n = 40 953) and perinatal deaths (n = 826) in the city of Belo Horizonte.6 Perinatal deaths comprise fetal deaths, defined as all stillbirths with birthweights of 500 g or more or gestation age of 22 weeks or more, and early neonatal deaths, defined as all infant deaths up to 7 days of life in which the infant weighed 500 g or more at birth or had a gestational age of 22 weeks or more.7 For our analysis, data were collected by hospital chart review and linkage of individual records to the National Live Birth Information System and the National Death Information System, yielding 775 perinatal deaths in 27 hospitals. Information gathered by 1 of the authors (S. L.) and by trained medical students included maternal education (from birth and death certificates), birthweight (from chart review when available or from birth or death certificates), cause of death (from charts and review of birth and death certificates; deaths were categorized by the Wigglesworth Classification),8 and hospital category (from death certificates and chart review for perinatal deaths and from birth certificates).
Each hospital was categorized according to its relation to the SUS system and by its quality of care. There were 20 hospitals contracted to SUS (hereafter called SUS hospitals; 12 private SUS hospitals, 4 philanthropic SUS hospitals, and 4 public SUS hospitals) and 7 private non-SUS hospitals. Quality assessment was conducted only in Belo Horizonte hospitals (n = 24); each hospital received a standardized score of 0 to 2000 (assigned by Costa et al.9), which related to its structural ability to assist the mother and the baby.9 Ten hospitals were scored 1000 or lower, indicating that they lacked the conditions for such basic health care as neonatal resuscitation (low quality); 7 hospitals were scored between 1001 and 1500 (intermediate quality), while 7 were scored above 1500 (adequate quality). Further details of the development and validation of the scoring system have been described previously.9
Maternal education (< 4 years, 4–7 years, 8–11 years, or ≥ 12 years) was used as an indicator of socioeconomic status. Using the Wigglesworth system,8 we classified the causes of perinatal death as antepartum, severe congenital malformation, immaturity (i.e., gestational period less than 37 weeks), intrapartum asphyxia, and other specific causes.
We analyzed perinatal death rates according to hospital category, adjusting for 2 major confounders: maternal education and birthweight. Multivariable regression analysis was carried out to determine the association between hospital category and perinatal death. We excluded 231 (29.8%) antepartum deaths (those that happened before the onset of labor) because hospital obstetric care during labor could not affect birth outcomes in these cases. We also excluded nonhospital births (n = 85 [0.2%]) and deaths (n = 19 [2.5%]) and 3 deaths (0.4%) that took place in nonmaternity hospitals. In the case of newborn transfers between hospitals (17 of the deaths [2.2%]), death was attributed to the hospital of birth. Data entry, processing, and analyses were conducted with the software programs Epi Info 6.0 (Centers for Disease Control and Prevention, Atlanta, Ga) and Stata version 8 (StataCorp LP, College Station, Tex).
RESULTS
The vast majority of the births took place in hospitals, although 19 (2.5%) of the deaths occurred outside a hospital, either at home, on the streets, during transfer to a hospital, or at another health facility (Table 1 ▶). This information could be ascertained only by hospital chart surveillance, because the babies’ birth and death certificates were registered as if they were born and had died in the hospitals. A total of 10.9% of all live births were low birthweight (<2500 g), and 2.0% were very low birthweight (<1500 g). By contrast, 74.2% of the deaths occurred among babies born with low birthweight and 50.7% among babies with very low birthweight. However, a quarter of all perinatal deaths (25.8%) occurred among babies with normal birthweight.
TABLE 1—
Distribution of Births and Perinatal Deaths by Selected Variables: Belo Horizonte, Brazil, 1999
Variable | Births, no. (%) | Deaths, no. (%) | Perinatal Mortality Rate | Rate Ratio (95% CI) |
Birthplace | ||||
Hospital | 40 075 (97.9) | 753 (97.2) | 18.7 | 1.0 |
Other | 85 (0.2) | 19 (2.5) | 223.5 | 11.9 (7.8, 17.8) |
Missing data | 793 (1.9) | 0 (0.0) | . . . | . . . |
Total | 40 953 (100.0) | 775 (99.6) | 18.9 | 1.0 (0.9, 1.1) |
Birthweight,a g | ||||
500–1499 | 818 (2.0) | 382 (50.7) | 466.9 | 87.8 (75.0, 102.9) |
1500–2499 | 3648 (8.9) | 177 (23.5) | 48.5 | 9.1 (7.5, 11.2) |
≥ 2500 | 36 487 (89.1) | 194 (25.8) | 5.3 | 1.0 |
Total | 40 953 (100.0) | 753 (100.0) | 18.3 | 3.5 (3.0, 4.1) |
Pregnancy | ||||
Singleton | 40 093 (97.9) | 678 (90.1) | 16.9 | 1.0 |
Multiple | 838 (2.0) | 56 (7.4) | 66.8 | 4.0 (3.0, 5.1) |
Missing data | 22 (0.1) | 19 (2.5) | . . . | . . . |
Total | 40 953 (100.0) | 753 (100.0) | 18.3 | 1.1 (1.0, 1.2) |
Delivery | ||||
Cesarean | 17 002 (41.6) | 252 (32.5) | 14.8 | 1.0 |
Vaginal | 23 922 (58.3) | 497 (62.0) | 20.7 | 1.4 (1.2, 1.6) |
Missing data | 29 (0.1) | 4 (5.5) | . . . | . . . |
Total | 40 953 (100.0) | 753 (100.0) | 18.4 | 1.2 (1.1, 1.4) |
Maternal education, y | ||||
< 4 | 514 (1.3) | 40 (5.3) | 77.8 | 7.2 (5.1, 10.2) |
4–7 | 21 536 (52.6) | 358 (47.5) | 16.6 | 1.5 (1.3, 1.9) |
8–11 | 11 338 (27.7) | 122 (16.2) | 10.8 | 1.0 |
≥ 12 | 5616 (13.7) | 74 (9.8) | 13.2 | 1.2 (0.9, 1.6) |
Missing data | 1949 (4.8) | 159 (21.2) | . . . | . . . |
Total | 40 953 (100.0) | 753 (100.0) | 18.4 | 1.7 (1.4, 2.1) |
Hospital SUS category | ||||
Private non-SUS | 8970 (21.9) | 95 (12.6) | 10.6 | 1.0 |
Private SUS | 16 194 (39.5) | 220 (29.2) | 13.6 | 1.3 (1.0, 1.6) |
Philanthropic SUS | 8816 (21.6) | 166 (22.1) | 18.8 | 1.8 (1.4, 2.3) |
Public SUS | 6180 (15.1) | 272 (36.1) | 44.0 | 4.2 (3.3, 5.2) |
Missing data | 793 (1.9) | 0 (0.0) | . . . | . . . |
Total | 40 953 (100.0) | 753 (100.0) | 18.4 | 1.7 (1.4, 2.1) |
Hospital quality of careb | ||||
Low | 18 206 (44.5) | 260 (35.3) | 14.3 | 0.6 (0.5, 0.7) |
Intermediate | 10 558 (25.7) | 239 (32.4) | 22.6 | 0.9 (0.8, 1.1) |
Adequate | 9688 (23.7) | 238 (32.3) | 24.6 | 1.0 |
Missing data | 2501 (6.1) | 0 (0.0) | . . . | . . . |
Total | 40 953 (100.0) | 737 (100.0) | 18.0 | 1.3 (1.1, 1.4) |
Note. CI = confidence interval; SUS = Universal Public Health System (Sistema Único de Saúde); non-SUS = private hospitals not contracted to SUS. Nineteen domiciliary deaths (2.5%) and 3 nonmaternity hospital deaths (0.4%) were excluded for all variables except birthplace.
aBirthweight was missing for 4 deaths (0.5%) and 22 live births (0.05%).
bQuality care assessment for 24 Belo Horizonte hospitals. Hospital quality of care was determined by giving each hospital a standardized score (assigned according to Costa et al.9) between 0 to 2000, related to its structural ability to assist mothers and babies. Hospitals with scores of ≤ 1000 were considered low quality, 1001–1500 intermediate quality, and > 1500 adequate quality.
Risk of perinatal mortality increased as birthweight decreased, but mortality rates were still high for babies with normal birthweight (5.3/1000 live births) and for those weighing between 1500 g and 2500 g (48.5/1000). A gradient in perinatal mortality rates according to maternal education was found (Table 1 ▶). Mothers with 4 to 7 years of schooling accounted for 52.6% of live births and 47.5% of infant deaths. The babies of the few mothers with less than 4 years of schooling experienced the highest perinatal mortality rate (77.8/1000). A higher proportion of missing data on maternal education was observed for perinatal death (21.2%) than for live births (4.8%).
Most of the births (76.2%) and deaths (87.4%) occurred in SUS hospitals. While private SUS hospitals accounted for 39.5% of births, deaths were more concentrated in public SUS hospitals (36.1%). The crude perinatal mortality rate was highest in public SUS hospitals and lowest in private non-SUS hospitals. Compared with private non-SUS hospitals, the crude rate ratios for perinatal mortality ranged from 1.3 (private SUS hospitals) to 4.2 (public SUS hospitals). A higher risk of perinatal mortality was observed for multiple births and vaginal delivery.
When the Wigglesworth Classification was used, significant differences in causes of perinatal death by type of hospital were observed (Table 2 ▶). While antepartum deaths and deaths from immaturity prevailed in private non-SUS hospitals, intrapartum asphyxia was much more common in SUS hospitals. Rates for asphyxia were 2.0 (public SUS hospitals) to 4.0 (private SUS hospitals) times higher than that seen at private non-SUS hospitals; these rates were especially high for normal-birthweight babies in private SUS and philanthropic SUS hospitals. Severe congenital malformation represented 7% to 10% of the perinatal deaths, and these rates were higher for low-birthweight babies in public SUS and philanthropic SUS hospitals than in other types of hospitals. Other causes (such as infection in full-term babies), although small in number, were also more frequent in SUS hospitals.
TABLE 2—
Perinatal Mortality (per 1000 Live Births) by Cause of Death, Birthweight, and Maternal Education According to Hospital Category: Belo Horizonte, Brazil, 1999
Hospital Category | |||||
Private non-SUS | Private SUS | Public SUS | Philanthropic SUS | Total | |
Cause of death (Wigglesworth Classification)a | |||||
Antepartum | |||||
< 2500 g | 25.1 | 35.2 | 58.1 | 39.5 | 40.5 |
≥ 2500 g | 1.0 | 1.1 | 3.1 | 1.3 | 1.4 |
Severe congenital malformation | |||||
< 2500g | 7.6 | 8.8 | 13.6 | 15.4 | 11.4 |
≥ 2500 g | 0.4 | 0.5 | 0.4 | 1.0 | 0.4 |
Immaturityb | |||||
< 2500 g | 31.6 | 33.2 | 48.0 | 25.1 | 34.3 |
≥ 2500 g | 0.0 | 0.6 | 0.2 | 0.3 | 0.3 |
Asphyxia | |||||
< 2500 g | 18.5 | 42.0 | 50.2 | 32.8 | 36.7 |
≥ 2500 g | 0.9 | 3.6 | 2.7 | 3.3 | 2.7 |
Other | |||||
< 2500 g | 1.1 | 2.0 | 1.4 | 1.9 | 1.6 |
≥ 2500 g | 0.0 | 0.6 | 0.4 | 1.0 | 0.5 |
Birthweight and maternal education | |||||
Birthweight,c g | |||||
500–1499 | 288.7 | 679.0 | 349.9 | 398.3 | 376.3 |
1500–2499 | 17.3 | 36.4 | 39.1 | 35.3 | 32.1 |
≥ 2500 | 1.2 | 5.1 | 3.8 | 4.6 | 3.9 |
Maternal education,d y | |||||
<8 | 6.2 | 11.9 | 23.3 | 13.3 | 14.1 |
≥8 | 6.6 | 7.9 | 21.7 | 8.5 | 8.8 |
Note. SUS = Universal Public Health System (Sistema Único de Saúde); non-SUS = private hospitals not contracted to SUS.
aEach cause of death is categorized as low birthweight (< 2500 g) or normal birthweight (≥ 2500 g).
bDefined as gestational period less than 37 weeks.
cExcluded are 8 live births (0.02%) and 2 deaths (0.3%) with birthweight missing as well as 231 antepartum deaths (30.6%).
dExcluded are 1863 births for which maternal education was missing (4.6%), 73 deaths for which maternal education was missing (14.0%), 793 births with missing hospital category (1.9%), and 231 antepartum deaths (30.6%).
Public SUS hospitals had the highest percentage of low-birthweight (21.6%) and very-low-birthweight (5.6%) babies, but they also had the lowest perinatal death rates for very-low-birthweight and normal-birthweight babies. Private SUS hospitals had the lowest percentage of low-birthweight babies (6.1%), but they had the highest birthweight-specific mortality rates for babies weighing 500 g to 1499 g or weighing 2500 g or more. Among babies weighing 1500 g to 2499 g, perinatal death rates were similar for the different types of SUS hospitals, but these rates were at least twice as high as those for the private non-SUS hospitals. Among normal-birthweight babies, perinatal mortality rates at SUS hospitals were 3.0 times higher (public SUS) to 4.1 times higher (private SUS) than in private non-SUS hospitals (Table 2 ▶).
In SUS hospitals, 68.6% of mothers had less than 8 years of schooling, compared with private non-SUS hospitals, where 85.3% of the mothers reported 8 or more years of schooling. For both less-educated (< 8 years of schooling) and more-educated (≥ 8 years) mothers, perinatal mortality rates were higher in public SUS hospitals (23.3/1000 and 21.7/1000, respectively) than in private non-SUS hospitals (6.2/1000 and 6.6/1000). With private non-SUS hospitals used as the reference, rate ratios varied from 1.2 (more-educated mothers at private SUS hospitals) to 3.5 (less-educated mothers at public SUS hospitals).
When data were stratified for both maternal education (< 8 years vs ≥ 8 years of schooling) and birthweight, private SUS hospitals showed the highest mortality rates for normal-birthweight babies in both strata of maternal education (Table 3 ▶). Once again, private non-SUS hospitals showed the lowest mortality rates. Public SUS hospitals had the highest mortality rates for low-birthweight babies. Relative risks for low-birthweight babies, adjusted by maternal education, were 1.5 (private non-SUS hospitals) and 1.7 (public SUS hospitals), with private non-SUS hospitals used as the reference. It was not possible to estimate the relative risk for the normal-birth-weight group adjusted by maternal education, because the death rate in the reference category (private non-SUS hospitals) was zero.
TABLE 3—
Perinatal Mortality Rate (MR) and Relative Risk (RR) by Hospital Category, Maternal Education, and Birthweight: Belo Horizonte, Brazil, 1999
Low Birthweight (< 2500 g) | Normal Birthweight (≥ 2500 g ) | |||||||||
Maternal Education, < 8 y | Maternal Education, ≥ 8 y | Maternal Education, < 8 y | Maternal Education, ≥ 8 y | |||||||
Hospital Description | MR | RR (95% CI ) | MR | RR (95% CI ) | RRa (95% CI ) | MR | RRa (95% CI ) | MR | RR (95% CI ) | RRa (95% CI) |
SUS category | ||||||||||
Private SUS | 93.4 | 1.8 (0.8, 4.5) | 85.1 | 1.5 (0.9, 2.5) | 1.6 (1.1, 2.3) | 6.1 | NAb (. . .) | 3.9 | 2.7 (1.2, 5.8) | NA (. . .) |
Philanthropic SUS | 74.2 | 1.4 (0.7, 2.8) | 55.8 | 1.0 (0.6, 1.8) | 1.2 (0.7, 1.8) | 4.9 | NA (. . .) | 3.7 | 2.5 (1.0, 6.1) | NA (. . .) |
Public SUS | 98.2 | 1.8 (0.9, 3.6) | 96.3 | 1.7 (1.1, 2.6) | 1.7 (1.2, 2.5) | 3.1 | NA (. . .) | 3.7 | 2.5 (0.9, 7.4) | NA (. . .) |
Private non-SUS | 52.6 | 1.0 (. . . ) | 55.3 | 1.0 (. . .) | 1.0 | 0.0 | 1.0 (. . .) | 1.5 | 1.0 (. . .) | NA (. . .) |
Total | 84.5 | 1.6 (0.8, 3.3) | 67.8 | 1.2 (0.8, 1.8) | 1.3 (1.0, 1.9) | 4.8 | NA (. . .) | 2.7 | 1.9 (0.9, 3.7) | NA (. . .) |
Quality of careb | ||||||||||
Low | 87.2 | 1.0 (0.8, 1.5) | 71.9 | 1.1(0.7, 1.9) | 1.1 (0.8, 1.4) | 5.8 | 2.3 (1.2, 4.3) | 4.5 | 3.0 (1.3) | 2.5 (1.5, 4.0) |
Intermediate | 81.0 | 1.0 (. . .) | 62.9 | 1.0 (. . .) | 2.6 | 1.0 (. . .) | 1.5 | 1.0 (. . .) | NA (. . .) | |
Adequate | 100.7 | 1.2 (0.9, 1.7) | 74.7 | 1.2 (0.8, 1.8) | 1.2 (0.9, 1.6) | 4.9 | 1.9 ( 0.9, 4.2) | 2.2 | 1.5 (0.6, 3.7) | 1.7 (0.9, 3.1) |
Total | 85.3 | 1.1(0.8, 1.4) | 71.1 | 1.1 (0.8, 1.7) | 1.1 (0.9, 1.3) | 4.8 | 1.9 (1.0, 3.5) | 2.7 | 1.8 (0.8, 4.0) | 1.8 (1.1, 3.0) |
Note. CI = confidence interval; SUS = Universal Public Health System (Sistema Único de Saúde). NA = mean not possible to calculate (RR = 0). Birthweights are categorized by years of maternal education. Excluded from the data are 231 antepartum deaths (29.8%) for hospital SUS category, 227 antepartum deaths (30.8%) for hospital quality-of-care category, 19 domiciliary deaths (2.5%), and 3 nonmaternity hospital deaths (0.4%). Also excluded are 73 deaths (14.0%) and 1863 births (4.6%) with missing maternal education and 793 births (1.9%) with missing hospital category.
aAdjusted relative risk (Mantel-Haenszel).
bQuality care assessment for 24 Belo Horizonte hospitals. Hospital quality of care was determined by giving each hospital a standardized score (assigned according to Costa et al.9) between 0 to 2000, related to its structural ability to assist mothers and babies. Hospitals with scores of ≤ 1000 were considered low quality, 1001–1500 intermediate quality, and above 1500 adequate quality.
When we controlled for birthweight (model 2) and both birthweight and maternal education (model 3) using a multiple logistic regression analysis (Table 4 ▶), private SUS and philanthropic SUS hospitals remained independently associated with perinatal death. When we compared all SUS hospitals and non-SUS hospitals, the difference in perinatal mortality rate was 51.3% higher in the former (rate ratio [RR] for perinatal mortality rate = 2.1); when we compared less-educated and more-educated mothers, the difference in rate was 31.2% higher among the former (RR for perinatal mortality rate = 1.4). The population attributable risk for perinatal deaths was 42.4% for SUS hospitals and 36.9% for low maternal education.
TABLE 4—
Relative Risk (RR) and 95% Confidence Intervals (CIs) for Perinatal Deaths and Selected Variables: Belo Horizonte, Brazil, 1999
Variables | Model 1 RR (95% CI) | Model 2 RRa (95% CI) | Model 3 RRa (95% CI) |
Group 1 variables | |||
Hospital SUS category | |||
Private SUS | 1.3 (1.0, 1.6) | 2.9 (2.1, 3.7) | 3.1 (2.2, 4.4) |
Public SUS | 4.3 (3.4, 5.4) | 1.9 (1.4, 2.5) | 1.4 (1.0, 2.0) |
Philanthropic SUS | 1.8 (1.4, 2.3) | 2.2 (1.6, 3.0) | 2.1(1.5, 2.9) |
Private non-SUS | 1.0 | 1.0 | 1.0 |
Birthweight, g | |||
500–1499 | . . . | 185.5 (149.1, 230.8) | 202.9 (159.0, 259.0) |
1500–2499 | . . . | 10.0 (8.1, 12.4) | 9.4 (7.4, 11.9) |
≥ 2500 | . . . | 1.0 | 1.0 |
Maternal education, y | |||
< 4 | . . . | . . . | 3.4 (2.0, 5.7) |
4–7 | . . . | . . . | 0.8 (0.6, 1.1) |
8–11 | . . . | . . . | 0.7 (0.5, 1.0) |
≥ 12 | . . . | . . . | 1.0 |
Group 2 variables | |||
Hospital quality of careb | |||
Low | 0.6 (0.5, 0.7) | 1.7 (1.4, 2.1) | 1.9 (1.5, 2.4) |
Intermediate | 0.9 (0.8, 1.1) | 1.1 (0.9,1.4) | 0.8 (0.7, 1.1) |
Adequate | 1.0 | 1.0 | 1.0 |
Birthweight, g | |||
500–1499 | . . . | 199.5 (160.3, 248.2) | 198.0 (155.0, 253.0) |
1500–2499 | . . . | 10.3 (8.3, 12.7) | 9.1 (7.2, 11.5) |
≥ 2500 | . . . | 1.0 | 1.0 |
Maternal education, y | |||
< 4 | . . . | . . . | 4.0 (2.4, 6.7) |
4–7 | . . . | . . . | 1.1 (0.8, 1.4) |
8–11 | . . . | . . . | 0.8 (0.6, 1.1) |
≥ 12 | . . . | . . . | 1.0 |
Note. SUS = Universal Public Health System (Sistema Único de Saúde). There were no control factors in model 1, we controlled for birthweight in model 2, and was controlled for birthweight and maternal education in model 3.
aAdjusted relative risk.
bQuality care assessment for 24 Belo Horizonte hospitals. Hospital quality of care was determined by giving each hospital a standardized score (assigned according to Costa et al.9) between 0 to 2000, related to its structural ability to assist mothers and babies. Hospitals with scores of ≤ 1000 were considered low quality, 1001–1500 intermediate quality, and above 1500 adequate quality.
Regarding hospital quality, a high proportion of the births (44.5%) took place in low-quality hospitals, and deaths were more equally distributed between the remaining 2 categories (Table 1 ▶). The crude perinatal mortality rate was lower in low-quality hospitals. However, when we adjusted for birthweight and maternal education and excluded antepartum deaths (Table 3 ▶), perinatal mortality rates were actually higher in low-quality hospitals for normal-birthweight babies, with an adjusted relative risk of 2.5 compared with intermediate-quality hospitals. Low-quality hospital status was also an independent risk factor for perinatal death in the multiple logistic regression model (Table 4 ▶).
DISCUSSION
The high perinatal mortality rate (19/1000) in Belo Horizonte is paradoxical given that, as in the rest of the country, most births took place in hospitals and were assisted by physicians. It is also of major concern that 19 deaths (2.5%) still took place outside of hospitals, even though there was no shortage of obstetrical beds in the city. We also observed important differences in data quality—for example, there was a higher prevalence of missing information on maternal education for babies that died than for live births.
Outcomes for SUS hospitals were worse than for private non-SUS hospitals, which had the lowest mortality rates. This finding could indicate inadequate capacity to intervene during labor and birth and after birth, for low-birthweight as well as for normal-birthweight babies. Important differences in birthweight-specific mortality rates between SUS hospitals and non-SUS hospitals were observed. Within the very-low-birthweight stratum (500–1499 g), rates were high for all types of SUS hospitals, but especially for private SUS hospitals, where almost 70% of the babies died. This situation reflects a disorganized perinatal health care system that allows women with high-risk pregnancies to deliver their babies in inadequate facilities, as well as barriers to accessing intensive care once the babies are born.
Almost half of the deaths that took place in private SUS hospitals were normal-birthweight babies. The observed mortality rates for normal-birthweight babies alone (underestimated here because antepartum deaths were excluded) are comparable to the overall perinatal mortality rates in developed countries in the 1990s. According to the literature, the leading causes of mortality in this group of babies are birth complications and intrapartum asphyxia (50%), antepartum death (25%), and infection (10%), suggesting that differences in risk and access to efficacious interventions—such as appropriate obstetric management during pregnancy, labor, and newborn care—contribute to disparities in perinatal mortality rates.10–12 By contrast, within the most developed countries, disparities in mortality are mainly encountered among newborns weighing less than 750 g.13
Among hospitals connected to the SUS system, public SUS hospitals had the lowest mortality rates for very-low-birthweight and normal-birthweight babies and the highest proportion of low-birthweight babies and very-low-birthweight deaths (68.2%). However, although public SUS hospitals were not associated with perinatal death in the final logistic regression model, they showed the highest mortality rates among low-birthweight babies in the stratified analysis. By contrast, private SUS hospitals had the lowest proportion of low-birthweight babies, but the highest mortality rates for very-low-birthweight and normal-birthweight babies. This is an important discrepancy from what would be expected for health facilities that deal mainly with low-risk pregnancies and babies. Non-timely health care access and low-quality care during delivery and the neonatal period could explain the worse outcomes in these settings. These hospitals are associated with low health care quality, which was an independent risk factor for perinatal mortality as reported in a previous study.14 Birthweight-specific mortality rates are influenced by access to quality obstetric and neonatal care, particularly among very-low-birthweight babies, but it is also a determinant for child survival when birth complications occur. Birth complications are expected—but not predictable—in nearly 15% of all childbirths and occur predominantly among low-risk and full-term pregnancies.
Hospital audits conducted by the Perinatal Commission of Belo Horizonte City and 2 independent studies consistently revealed poor-quality care at private SUS hospitals and the low-quality category hospitals.9,14,15 Most of the mothers were not adequately assisted during labor: 80% were not assessed at least every hour while in labor, partographs (a graph that records the progress of labor and assists in identifying when intervention is necessary) were not used in 75% of the deliveries, and there was a very low percentage of corticosteroid use for mothers in premature labor or surfactant therapy for premature newborns.14
Previous studies in Brazil provided evidence of low-quality hospital care during labor and delivery16–18 as well as barriers to prompt access to hospital care.19,20 Inadequate use of corticosteroids for immaturity was observed in most of the public SUS tertiary-care hospitals across different states of the country.21 Another study showed underuse of surfactant therapy for premature babies, especially among low socioeconomic groups: use was only 12.5% for SUS patients compared with 76.6% among non-SUS patients.22 More recently, lower-quality care has been reported for Black women, who are also concentrated in public hospitals. This factor contributes to the fact that infant mortality is 66% higher among Blacks than for Whites in Brazil.16,23,24
Other studies have reported higher neonatal and infant mortality rates in public SUS hospitals than in private non-SUS hospitals; they have attributed the disparity to hospital case mix—that is, a higher proportion of poor mothers who use SUS facilities.3,4,25 Residual confounding could explain in part the high mortality rates at public SUS hospitals—as well in higher-quality hospitals—because they are referral facilities for high-risk pregnancies and for seriously ill and very-low-birthweight babies. Nevertheless, in our analyses, birth-weight was taken into account precisely because it is a major predictor for child survival.
Preventable Causes of Perinatal Deaths
The Wigglesworth Classification highlighted disparities between hospitals in perinatal causes of death. Intrapartum causes of death were a major problem at SUS hospitals. Asphyxia, which accounted for 30% of the perinatal mortality, similar to rates in other developing countries,26–28 is highly preventable; it requires action based on timely low-cost intervention during labor, including appropriate interpersonal assistance. Every setting should be prepared to respond adequately in situations such as birth complications, which could lead to a significant reduction in mortality, especially in private SUS hospitals.
Higher rates of severe congenital malformation at public SUS and philanthropic SUS hospitals may reflect a client selection effect. The observed differential between SUS and non-SUS hospitals could be explained by background differences in exposures to risks in the housing and work environment, as well as difficulties in accessing efficacious interventions before and during pregnancy, after birth, and during pregnancy termination.13 Important differences between SUS and non-SUS hospitals were also observed for specific conditions, mainly represented by congenital or acquired infections in full-term babies. Better management of newborn infectious diseases—during prenatal or neonatal care—could reduce these preventable deaths.
One noteworthy point concerns the contribution of rates of cesarean delivery to the differences in hospital perinatal mortality, as it is the predominant mode of delivery in non-SUS hospitals (33.0% of all births at SUS hospitals vs 72.0% in non-SUS hospitals in 1999). We found that, compared with vaginal delivery, cesarean delivery was a protective factor for perinatal mortality in both non-SUS hospitals (RR = 0.54; 95% confidence interval [CI] = 0.36, 0.81) and SUS hospitals (RR = 0.88; 95% CI = 0.74, 1.04), although the difference was not significant for the latter hospitals, similar to previous findings.4,5 Cesarean delivery might therefore be a confounder in the relationship between hospital category and perinatal mortality, because the procedure is a marker for high socioeconomic status. However, when cesarean deliveries were taken into account, there was still an important differential in perinatal mortality between SUS and non-SUS hospitals (18.7/1000 and 8.5/1000, respectively; RR = 2.2; 95% CI = 1.6, 2.9), suggesting an effect modification between cesarean delivery and SUS hospitals. As pointed out by Barros et al., rates of cesarean delivery are lower for high-risk women than for lower-risk women, and women with the greatest need may still fail to receive it even though rates of cesarean delivery are high in Brazil.29
Although the SUS system undoubtedly represents a huge improvement in health care delivery in Brazil, there is no systematic monitoring of hospital quality. The system still depends on private SUS hospitals, which account for approximately 30% of the obstetrics beds and deliver questionable quality of care. The private sector contracted under SUS is a mixture of public and private models “with differing expectations and reward systems, unduly distorting overall health-care patterns.”30(p853) Routine audits of hospital quality are urgently needed to scale up maternal, perinatal, and neonatal care. Alternatively, public services could be increased within the SUS system. In addition, public health policies should consider expanding intermediate-quality hospitals, as these facilities have demonstrated outcomes for perinatal mortality similar to those of adequate-quality hospitals.14
It is noteworthy that interventions introduced by the Belo Horizonte Health Department after 1999 decreased early neonatal mortality by 30% in 2 years, together with smaller decreases in maternal and fetal mortality. In this period, there were improvements in timely access to hospital admission during labor and to intensive care units, and 5 private SUS hospitals with low quality scores were closed down. Those outcomes reinforce the importance of hospital care in reducing perinatal mortality.15
Belo Horizonte’s health system is segregated, with the more disadvantaged segments of the population relying on SUS facilities while the better off mainly use private non-SUS hospitals; patterns of quality and practices differ greatly, contributing to inequalities in health outcomes. Our findings illustrate the inverse equity hypothesis: child health inequities increase with greater access to medical technology by those of higher socioeconomic status.31–33
Brazil must urgently address the paradox of persistently high maternal and neonatal mortality rates that occur in the presence of the medicalization of birth. While simple, effective, and low-cost practices are poorly deployed, more elaborate techniques, such as cesarean delivery and induction of labor, are often misused.30 As pointed out by Daniels and colleagues, the country has “achieved a rapid economic growth but lagged behind in health improvements,”34(p32) in contrast to other developing countries, which have prioritized the provision of social services that reduce mortality and improve quality of life. Organization of perinatal care in a regionalized and integrated system and improvement in quality care is fundamental not only at the community level but at the hospital level as well. An ethical and legal approach that guarantees a standard quality of care for all, as well as access to available technology, is a challenge for the SUS system.35,36 It can occur only when budget and market constraints, and the common practice of low-quality care for poor people, are overcome.37
Conclusions
We point out important disparities in perinatal mortality in Belo Horizonte and emphasize the role of hospital care in producing and maintaining the unacceptably high rates of perinatal and neonatal mortality in Brazil. We argue that, besides intervening on socioeconomic factors that contribute to inequities in perinatal mortality, it is important to improve the quality of health care delivered to women and their babies at the health system level.
Acknowledgments
This study was funded by the Pan American Health Organization/World Health Organization (grant AMR/99/078643-01) and CNPQ-Brazil (grant 200338/2004-8).
Human Participant Protection This study was approved by the institutional review board of the Federal University of Minas Gerais, Brazil (137/99).
Peer Reviewed
Contributors S. Lansky originated the study and supervised all aspects of its implementation. E. França assisted with the study and analyses. I. Kawachi synthesized analyses and writing. All authors helped to conceptualize ideas, interpret findings, and review drafts of the manuscript.
References
- 1.Saúde Brasil 2005—uma Análise da Situação de Saúde. Brasília, Brazil: Ministério da Saúde; 2004: 120–134.
- 2.Parto, Aborto e Puerpério—Assistência Humanizada a Saúde. Brasília, Brazil: Ministério da Saúde; 2003: 17–25.
- 3.Neto OLM, Barros MBA. Risk factors for neonatal and post-neonatal mortality in the Central-West region of Brazil: linked use of life births and infant deaths records [in Portuguese]. Cad Saude Publica. 2000;16(2): 477–485. [DOI] [PubMed] [Google Scholar]
- 4.Almeida MF, Novaes HMD, Alencar GP, Rodrigues LC. Neonatal mortality: socioeconomic factors, health services risk factors and birth weight in the City of São Paulo [in Portuguese]. Rev Bras Epidemiol. 2002;5:93–107. [Google Scholar]
- 5.Becerra JE, Atrash HK, Perez N, Saliceti JA. Low birth weight and infant mortality in Puerto Rico. Am J Public Health. 1993;83:1572–1576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lansky S, França E, Leal MC. Perinatal avoidable deaths in Belo Horizonte, Minas Gerais, 1999 [in Portuguese]. Cad Saude Publica. 2002;18:139–151. [DOI] [PubMed] [Google Scholar]
- 7.International Classification of Diseases, 10th Revision. Geneva, Switzerland: World Health Organization; 1994.
- 8.Keeling JW, MacGillivray I, Golding J, Wigglesworth J, Berry J, Dunn PM. Classification of perinatal death. Arch Dis Child. 1989;64:1345–1351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Costa JO, Xavier CC, Proietti FA, Delgado MS. Evaluation of hospital resources for perinatal assistance in Brazil [in Portuguese]. Rev Saude Publica. 2004; 38(5):701–708. [DOI] [PubMed] [Google Scholar]
- 10.Bryce J, Boschi-Pinto C, Shibuya K, Black RE, WHO Child Health Epidemiology Reference Group. WHO estimates of the causes of death in children. Lancet. 2005;365:1147–1152. [DOI] [PubMed] [Google Scholar]
- 11.Lawn JE, Cousens S, Zupan J, Lancet Neonatal Survival Steering Team. 4 million neonatal deaths: when? Where? Why? Lancet. 2005;365:891–900. [DOI] [PubMed] [Google Scholar]
- 12.Lawn J, Shibuya K, Stein C. No cry at birth: global estimates of intrapartum stillbirths and intrapartum-related neonatal deaths. Bull World Health Organ. 2005; 83(6):409–417. [PMC free article] [PubMed] [Google Scholar]
- 13.Wise P. Disparities in infant mortality. Annu Rev Public Health. 2003;24:341–362. [DOI] [PubMed] [Google Scholar]
- 14.Lansky S, Franca E, Comini CC, Neto LMC, Leal MC. Perinatal deaths and health care evaluation in maternity hospitals of the Public Health System in Belo Horizonte, Brazil, 1999 [in Portuguese]. Cad Saude Publica. 2006;22(1):117–128. [DOI] [PubMed] [Google Scholar]
- 15.Porto D. Perinatal Health Commission of Belo Horizonte, Brazil [in Portuguese]. In: Lotta GS, Barboza HB, Teixeira MCAC, Pinto V, eds. Twenty Experiences of Public Policies and Citizenship. Rio de Janeiro, Brazil: Getúlio Vargas Foundation/BNDES/FORD Foundation; 2003:89–102.
- 16.Leal MC, Gama SGN, Cunha CB. Racial, sociodemographic and prenatal and childcare inequalities in Brazil, 1999–2001 [in Portuguese]. Rev Saude Publica. 2005;39(1):100–107. [DOI] [PubMed] [Google Scholar]
- 17.Rosa MLGR, Hortale VA. Avoidable perinatal deaths and obstetric health care structure in the public health care system: a case study in a city in Greater Metropolitan Rio de Janeiro [in Portuguese]. Cad Saude Publica. 2000;16(3):773–783. [DOI] [PubMed] [Google Scholar]
- 18.Silva AAM, Coimbra LC, Silva RA, et al. Perinatal health and mother–child health care in the municipality of Sao Luiz, Maranhao, Brazil [in Portuguese]. Cad Saude Publica. 2001;17(6):1413–1423. [PubMed] [Google Scholar]
- 19.Leal MC, Gama SGN, Campos M. Factors associated with perinatal morbidity and mortality in a sample of public and private maternity centers in the City of Rio de Janeiro, 1999–2001 [in Portuguese]. Cad Saude Publica. 2004;20(S1):20–34. [DOI] [PubMed] [Google Scholar]
- 20.Almeida MF, Alencar GP, Novaes MHD, et al. Accidental home deliveries in southern Sao Paulo, Brazil [in Portuguese]. Rev Saude Publica. 2005;39(3): 366–375. [DOI] [PubMed] [Google Scholar]
- 21.Rede Brasileira de Pesquisas Neonatais. Antenatal corticosteroids use and clinical evolution of preterm newborn infants [in Portuguese]. J Pediatr (Rio J). 2004;80(4):277–284. [DOI] [PubMed] [Google Scholar]
- 22.Marques S. Neonatal Mortality and Surfactant Use in Premature Babies [master’s thesis; in Portuguese]. Goiânia, Brazil: Federal University of Goiás; 2002.
- 23.Barros FC, Victora CG, Horta BL. Ethnicity and infant health in southern Brazil: a birth cohort study. Int J Epidemiol. 2001;30:1001–1008. [DOI] [PubMed] [Google Scholar]
- 24.PNUD Brasil. Atlas racial brasileiro. 2004. Available at: http://www.pnud.org.br/publicacoes/atlas_racial/index.php. Accessed July 7, 2005.
- 25.Almeida SDM, Barros MBA. Health care and neonatal mortality [in Portuguese]. Rev Bras Epidemiol. 2004;7(1):22–35. [Google Scholar]
- 26.Wen SW, Lei H, Kramer MS, Sauve R. Determinants of intrapartum fetal deaths in a remote and indigent population in China. J Perinatol. 2004;24:77–81. [DOI] [PubMed] [Google Scholar]
- 27.Pattinson RC. Challenges in saving babies—avoidable factors, missed opportunities and substandard care in perinatal deaths in South Africa. S Afr Med J. 2003;93(6):450–455. [PubMed] [Google Scholar]
- 28.Azad K, Abdullah AH, Nahar N. Use of Wigglesworth classification for the assessment of perinatal mortality in Bangladesh—a preliminary study. Bangladesh Med Res Counc Bull. 2003;29:38–47. [PubMed] [Google Scholar]
- 29.Barros FC, Vaughan JP, Victora CG. Why so many cesarean sections? The need for a further policy change in Brazil. Health Policy Plan. 1986;1:19–29. [DOI] [PubMed] [Google Scholar]
- 30.Barros FC, Victora CG, Barros AJD, et al. The challenge of reducing neonatal mortality in middle-income countries: findings from three Brazilian birth cohorts in 1982, 1993 and 2004. Lancet. 2005; 365(9462):847–854. [DOI] [PubMed] [Google Scholar]
- 31.Victora CG, Vaughan JP, Barros FC, Silva AC, Tomasi E. Explaining trends in inequities: evidence from Brazilian child health studies. Lancet. 2000;356: 1093–1098. [DOI] [PubMed] [Google Scholar]
- 32.Gwatkin DR, Bhuiya A, Victora CG. Making health systems more equitable. Lancet. 2004;364: 1273–1280. [DOI] [PubMed] [Google Scholar]
- 33.Wise PH, Kotelchuck M, Wilson ML, Mills M. Racial and socioeconomic disparities in childhood mortality in Boston. N Engl J Med. 1985;313:360–366. [DOI] [PubMed] [Google Scholar]
- 34.Daniels N, Kennedy B, Kawachi I. Justice is good for our health. In: Cohen J, Rogers J, eds. Is Inequality Bad for Our Health? Boston, Mass: Beacon Press; 2000:3–33.
- 35.Andrade CLT, Szwarcwald CL, Gama SGN, Leal MC. Socioeconomic inequalities and low birth weight and perinatal mortality in Rio de Janeiro, Brazil [in Portuguese]. Cad Saude Publica. 2004;20(suppl 1):44–51. [DOI] [PubMed] [Google Scholar]
- 36.Wise PH. Reconciling science and politics. Am J Prev Med. 1993;9(6 suppl):7–16. [PubMed] [Google Scholar]
- 37.Victora CG, Wagstaff A, Schellenberg JA, Gwatkin D, Claeson M, Habicht J. Applying an equity lens to child health and mortality: more of the same is not enough. Lancet. 2003;362(9379):233–241. [DOI] [PubMed] [Google Scholar]