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Socioeconomic Inequalities in Low Birth Weight in the United States, the United Kingdom, Canada, and Australia Melissa L. Martinson, PhD, and Nancy E. Reichman, PhD Objectives. To compare associations between socioeconomic status and low birth weight across the United States, the United Kingdom, Canada, and Australia, countries that share cultural features but differ in terms of public support and health care systems. Methods. Using nationally representative data from the United States (n = 8400), the United Kingdom (n = 12 018), Canada (n = 5350), and Australia (n = 3452) from the early 2000s, we calculated weighted prevalence rates and adjusted odds of low birth weight by income quintile and maternal education. Results. Socioeconomic gradients in low birth weight were apparent in all 4 countries, but the magnitudes and patterns differed across countries. A clear graded association between income quintile and low birth weight was apparent in the United States. The relevant distinction in the United Kingdom appeared to be between low, middle, and high incomes, and the distinction in Canada and Australia appeared to be between mothers in the lowest income quintile and higher-income mothers. Conclusions. Socioeconomic inequalities in low birth weight were larger in the United States than the other countries, suggesting that the more generous social safety nets and health care systems in the United Kingdom, Canada, and Australia played buffering roles. (Am J Public Health. 2016;106:748–754. doi:10.2105/AJPH.2015.303007)
S
ocioeconomic inequalities in health are pervasive in the developed world, a fact that has led to questions about the extent of health inequalities across countries. Yet, despite a developing literature on health across Organisation for Economic Co-operation and Development countries, relatively little is known about inequalities in health across countries or at what point during the life course socioeconomic inequalities in heath emerge. A few studies have compared income gradients in parent-reported child health status in the United States with those in the United Kingdom, Canada, or Australia, but the purpose of those studies was not to document cross-country comparisons.1–5 Other studies incorporating objective health measures have shown that socioeconomic gradients in health are very similar in the United States and United Kingdom throughout the life course, despite better
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overall population health in the United Kingdom; however, health measures for young children were limited in those studies.6,7 As such, little is known about how socioeconomic gradients in health at very young ages compare across countries. Low birth weight (LBW) is an important measure of health at the “starting gate” because it is a leading risk factor for infant mortality as well as a marker for subsequent child morbidity among infants who survive8; it is also an important predictor of health and socioeconomic status over the life course and across generations.9 In the United States, there is clear evidence of a socioeconomic
gradient in LBW, although patterns vary by race/ethnicity.10,11 Little is known about the magnitude of socioeconomic gradients in health at birth in other developed countries. We used nationally representative data from 4 countries—the United States, the United Kingdom, Canada, and Australia—to compare socioeconomic gradients in LBW across English-speaking countries that share cultural features but differ in terms of public support and health care systems. The United Kingdom, Canada, and Australia enjoy better overall population health than the United States 12 and also have more generous health care and social support systems.12,13 All 4 countries are diverse, with relatively large immigrant populations but different racial/ ethnic mixes.14 Canada and Australia have lower income inequality than the United States and United Kingdom, as measured by Gini coefficients,13 and there is increasing evidence that income inequality adversely affects population health.15 For most of these reasons, we expected that socioeconomic gradients in LBW would be largest in the United States.
METHODS We used data on singleton births from 4 nationally representative data sets: the Early Childhood Longitudinal Study–Birth Cohort (ECLS-B) for the United States, the Millennium Cohort Study (MCS) for the United Kingdom, the National Longitudinal Survey of Children and Youth (NLSCY) for Canada,
ABOUT THE AUTHORS Melissa L. Martinson is with the School of Social Work, University of Washington, Seattle. Nancy E. Reichman is with the Department of Pediatrics, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ. Correspondence should be sent to Melissa L. Martinson, University of Washington, School of Social Work, 4101 15th Ave NE, Seattle, WA 98105 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted November 21, 2015. doi: 10.2105/AJPH.2015.303007
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and the Longitudinal Study of Australian Children–Birth Cohort (LSAC) for Australia. The ECLS-B is a restricted-use, nationally representative sample of approximately 10 700 children who were born in 2001 to mothers aged 15 years or older and who were alive and residing in the United States at 9 months of age.16,17 As a result of confidentiality requirements, all sample sizes in the ECLS-B were rounded to the nearest 50. The MCS is a representative sample of approximately 20 000 UK births occurring between 2000 and 2002.18 The LSAC was modeled on the ECLS-B and includes a representative sample of approximately 5000 children born in 2003 and 2004 taken from the Health Insurance Commission Medicare database.19,20 The restricted-use NLSCY is not a birth cohort study but, rather, a longitudinal study of children of all ages in Canada.21,22 We used data on the 5000 children in waves 3 and 4 of the NLSCY who were born between 1998 and 2001 to create a sample that resembled those from the birth cohort studies in the other countries.
Measures Low birth weight. LBW was defined as less than 2500 grams (approximately 5.5 pounds), the threshold used internationally. Birth weight was based on maternal reports in the United Kingdom, Canada, and Australia and taken from birth certificates for the United States. Maternal reports of birth weight have been shown to be very accurate, even retrospectively after many years.23,24 Socioeconomic status. The primary measure of socioeconomic status was weighted income quintile calculated from total family income, available in each country, adjusted for family size via the Organisation for Economic Co-operation and Development’s equivalency scale.25 We also considered maternal education, the other measure of socioeconomic status used in the relevant literature. On the basis of previous comparative research in the countries of interest,26–28 maternal education was coded as follows: less than high school or equivalent, high school or equivalent, some postsecondary education or college, and at least a college education. Covariates. We controlled for important compositional differences that were
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comparable across the data sets. Maternal age at birth was coded as younger than 20 years, 20 to 34 years, and 35 years or older. Marital status was characterized by whether the mother was married at the time of the birth. Parity was characterized as first versus higher-order birth. Mother’s nativity was classified as foreign-born versus native-born in the country of interest. All models controlled for the child’s sex. An indicator of any prenatal smoking (based on maternal retrospective reports) was included in supplementary models to allow a broad look at the contribution of smoking, which is a strong risk factor for low birth weight,29 to the observed socioeconomic gradients in birth weight. We conducted sensitivity analyses that included a measure of race/ethnicity and region of origin. Race/ethnicity was assessed very differently across countries. For the United States, we included the frequently used categories of non-Hispanic White, non-Hispanic Black, Hispanic, Asian, American Indian/Alaska Native, and other race/ethnicity. For the United Kingdom, we used categories that are representative of the major groups in that country: White, Black (Black Caribbean or Black African), Asian (South Asian including Indian, Pakistani, and Bangladeshi), and other.30 In Canada, race was assessed only for a subsample in one survey wave, limiting the available sample for analyses that incorporated this information. The categories included White, Asian, Black, First Nations, and other. The LSAC data for Australia did not include a measure of race/ethnicity but did include region of origin, which we used as a proxy measure. The categories for region of origin included Australian, Aboriginal Australian, Asian immigrants, immigrants from English-speaking countries, and other immigrants. The majority of the Australian-born population is of White ancestry.31 We conducted supplementary analyses of the White-only (or, for Australia, the Australianborn) samples for each country to remove potential confounding effects of race/ ethnicity.
Analysis Strategy For each country, we calculated sample characteristics as well as rates of LBW by each
of the sample characteristics. We also estimated logistic regression models to obtain adjusted odds ratios for LBW as a function of income quintile or, alternatively, maternal education within each country. All statistical comparisons were within countries. We used the svy procedures in Stata SE version 13 to adjust for the complex sampling design in each data set, allowing us to obtain nationally representative results.32 The NLSCY analysis was conducted through Statistics Canada via a restricted data protocol; the output was generated with SAS version 9.4.33
RESULTS In the United Kingdom, half of births were first births, whereas in the other countries the rates of first births were lower (approximately 40%; Table 1). Adolescent childbearing was most common in the United States, followed by the United Kingdom and then Australia and Canada. In the United Kingdom, the percentage of mothers who were married at the time of the birth was 60.3%; the rate of marital childbearing was closer to 70% in the other countries. Mothers in the United States and United Kingdom were less likely to smoke during their pregnancy than those in Australia and Canada. All 4 countries are major immigrant destination countries, but the proportions of births to foreign-born mothers in the United States and Australia were about twice those in the United Kingdom and Canada. This pattern resembles national immigrant population rates.13 Racial/ethnic patterns differed across countries, with mothers giving birth in the United States being much less likely to be White than those in the other countries. In Australia, the majority of mothers were Australian-born. Finally, there was noticeable variation in maternal education. Mothers were most likely to have less than a high school education or equivalent in Australia, whereas they were most likely to have a college education or more in Canada. Overall, the rate of LBW was lowest in Australia (4.8%), followed by Canada (5.5%); the rate was highest in the United Kingdom (6.0%) and the United States (5.8%) (Table 2). There was a very clear graded association between income quintile and LBW in the United States, whereas the relevant
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TABLE 1—Characteristics of the US, UK, Canadian, and Australian Samples United States (n = 8400), %
Characteristic
United Kingdom (n = 12 018), %
Canada (n = 5350), %
Australia (n = 3452), %
Maternal education < high school or equivalent
19.6
11.2
14.1
35.9
High school or equivalent
28.5
40.1
17.6
12.7
Some college or equivalent
27.5
20.0
23.9
20.2
‡ bachelor’s degree
24.4
28.8
44.4
31.3
40.7
49.8
42.1
40.5
First birth Female child
48.7
49.3
49.7
48.5
Mother foreign-born
21.6
10.4
11.5
21.2
Mother married
66.8
60.3
71.2
73.3
Maternal age at birth, y < 20
11.0
6.9
3.7
3.7
20–34
75.3
75.6
81.3
75.8
‡ 35
13.8
17.5
15.0
20.5
White
57.4
89.6
90.0
Black
13.8
3.0
1.3
Asian
3.5
6.4
4.2
22.9 1.8
1.0
Maternal race/ethnicity
Hispanic Other Native American/indigenous
0.6
1.6 2.9
Country of origin (Australia) Australian-born
76.2
Indigenous
2.6
English-speaking immigrant
7.6
Asian immigrant
5.5
Other immigrant Mother smoked during pregnancy
8.1 14.8
14.8
21.7
18.8
Note. Figures are weighted to be nationally representative of each country. Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998– 2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
distinction in the United Kingdom appeared to be between low, middle, and high incomes; in both Canada and Australia, the distinction appeared to be between the lowest income quintile and higher-income mothers. In the United States, the rate of LBW in the bottom income quintile (8.0%) was 2.41 times the rate in the highest quintile (3.3%); the corresponding figures for the United Kingdom, Canada, and Australia were 1.74, 1.61, and 1.87, respectively. The patterns by education were slightly different than the patterns by income. In the United States, there appeared to be a graded association between education and LBW that spanned from low education (highest LBW rate) to high education (lowest LBW rate). A
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similar pattern was evident for the United Kingdom, where the rate of LBW was extremely high in the lowest education category. This high rate might reflect the fact that the percentage of mothers in this group was only 11.2%, suggesting that they may have thus been particularly disadvantaged. Interestingly, no LBW education gradient was apparent in Canada. Finally, although LBW varied by maternal education in Australia (LBW was most likely among mothers with no high school diploma and some college), there was no clear graded association apparent in our unadjusted results. In all 4 countries, first-born infants were more likely than their higher-order counterparts to be LBW. In the United States,
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younger and older mothers are more likely to have LBW infants than mothers 20 to 34 years of age, a finding well established in the literature.34 However, this pattern was not present in the other countries. Whereas infants born to married mothers were less likely than those born to unmarried mothers to be LBW in the United States, the United Kingdom, and Australia, this did not appear to be the case in Canada. As noted, however, the NLSCY is not a birth cohort study, making it more difficult to pinpoint marital status specifically at the time of the birth. As expected on the basis of a rich multidisciplinary literature, prenatal smoking increased the likelihood of LBW in all 4 countries. Compared with the relevant native-born populations, foreign-born status was associated with a higher rate of LBW in Australia and a lower rate in the United Kingdom, although these differences were not statistically significant. In the United States and Canada, there were minimal differences in LBW rates by nativity. Racial/ethnic or country-of-origin disparities in LBW were apparent in all 4 countries. Multivariate logistic regression models of associations between income quintile and LBW included all variables in Table 1 other than maternal education, race/ethnicity (for the United States, the United Kingdom, and Canada), country of origin (for Australia), and smoking (Table 3). Inclusion of the race/ ethnicity and country-of-origin variables did not change the substantive results (available on request from the authors), but those factors were excluded here to enhance the comparability of measures across countries. The estimates, presented as odds ratios, reveal a pattern similar to that observed in the unadjusted results in Table 2 for the United States, where there was a clear and significant income gradient in LBW. Likewise, inclusion of the controls in Table 3 did not alter the pattern of unadjusted associations between income quintile and LBW in the United Kingdom, with 3 distinct income groups vis-`a-vis LBW risk. Finally, although Table 2 shows that low-income mothers in Canada and Australia were twice as likely to have an LBW infant as higher-income mothers, in Canada this relationship was not statistically significant at a conventional level in the multivariate context (Table 3), perhaps owing to the smaller sample in that country.
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TABLE 2—Low Birth Weight by Sample Characteristics: United States, United Kingdom, Canada, and Australia Characteristic
United States (n = 8400), %
United Kingdom (n = 12 018), %
Canada (n = 5350), %
Australia (n = 3452), %
5.8
6.0
5.5
4.8
Bottom
8.0*
8.3*
7.0
7.0*
Second
7.1*
6.3*
7.0
5.7
Middle
6.0*
6.3*
4.7
4.2
Fourth
4.6*
4.8
4.8
3.2
Top
3.3
4.8
4.3
3.7
< high school or equivalent
7.3*
10.1*
4.5
6.7*
High school or equivalent
6.9*
6.2*
5.3
2.4
Some college or equivalent
5.4*
5.3
5.2
5.2*
‡ bachelor’s degree
3.6
4.5
5.5
3.2
First birth
7.2*
7.1*
6.5
5.9*
Higher-order birth
4.8
4.8
4.8
4.0
Total low birth weight rate Income quintile
Maternal education
Parity
Child sex Female
6.2*
6.5*
5.9
5.0
Male
5.3
5.4
5.1
4.6
Foreign-born
5.9
7.1
5.7
5.7
Native-born
5.7
5.8
5.5
4.5
Married
4.6*
5.1*
5.5
4.2*
Unmarried
8.2
7.2
5.4
6.3
Maternal nativity
Mother’s marital status at birth
Maternal age at birth, y < 20
8.7*
7.3
3.7
5.7
20–34
5.2
5.8
5.7
4.9
6.6*
6.1
5.2
4.1
White
4.7
5.4
4.6
Black
10.4*
8.8*
Asian
6.0*
12.8*
2.1*
Hispanic
5.6*
Other
7.1*
2.7
7.8*
Native American/indigenous
2.9
‡ 35 Maternal race/ethnicity
a
7.2*
Country of origin (Australia) Australian-born
4.2
Indigenous
12.9*
English-speaking immigrant
2.4
Asian immigrant
6.5
Other immigrant
8.3*
Maternal prenatal smoking status Smoked
6.1*
8.8*
6.6
8.2*
Did not smoke
3.9
4.5
5.1
4.0
Note. Figures are weighted to be nationally representative of each country. Reference categories were top income quintile, bachelor’s degree or more, higherorder birth, male child, mother native-born, mother unmarried, maternal age at birth 20–34 years, White race/ethnicity or Australian-born (Australia), and nonsmoker during pregnancy. Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004). a Race/ethnicity was available only for a subsample in Canada. *P < .05 (within-country difference).
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TABLE 3—Odds of Low Birth Weight by Income Quintile: United States, United Kingdom, Canada, and Australia Income Quintile
United States (n = 8400), OR (95% CI)
United Kingdom (n = 12 018), OR (95% CI)
Canada (n = 5350), OR (95% CI)
Australia (n = 3452), OR (95% CI)
Bottom
2.37 (1.80, 3.11)
1.78 (1.30, 2.44)
2.07 (0.94, 4.53)
2.11 (1.12, 3.99)
Second
2.21 (1.68, 2.90)
1.42 (1.04, 1.93)
1.55 (0.83, 2.87)
1.76 (0.97, 3.20)
Middle
1.88 (1.44, 2.46)
1.40 (1.07, 1.84)
1.28 (0.64, 2.56)
1.37 (0.74, 2.54)
Fourth
1.45 (1.11, 1.88)
1.07 (0.80, 1.42)
1.16 (0.61, 2.22)
0.86 (0.44, 1.68)
1
1
1
1
Top (Ref)
Note. CI = confidence interval; OR = odds ratio. Figures are weighted to be nationally representative of each country. Models controlled for parity, child sex, maternal nativity, marital status, and maternal age at birth. The full models are available in Table A (available as a supplement to the online version of this article at http://www.ajph.org). Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
A number of other patterns that were apparent in Table 2 persisted in the multivariate analyses. First births were associated with increased odds of LBW in all 4 countries. Being married at the time of the birth was protective against LBW only in the United States; it fell on the margins of significance in the United Kingdom. We also found country-specific associations between maternal age and LBW. Being an older mother (aged 35 years or older) was associated with LBW only in the United States and the United Kingdom (Table A, available as a supplement to the online version of this article at http://www.ajph.org). Supplementary analyses limited the sample to Whites (in Australia, proxied by Australianborn) in all 4 countries, providing a sensitivity check for the estimates in Table 3 in which there was no control for potential confounding effects of race/ethnicity (Table B, available as a supplement to the online version of this article at http://www.ajph. org). The patterns of associations between income quintile and LBW were similar to those in Table 3 for the United States, the United Kingdom, and Australia. In Canada, however, there was no association between income quintile and LBW among Whites. Logistic regression estimates of associations between our alternative measure of socioeconomic status—maternal education—and LBW revealed patterns that differed somewhat from those for income and LBW (Table 4). In the United States, lower education was associated with higher rates of LBW, but a graded pattern was not as apparent as it was for income quintiles. Mothers with a high school education and those who had not completed high school were most likely to
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have an LBW infant, with no difference between these 2 categories, followed by mothers with some college. In the United Kingdom, mothers with less than a high school education were significantly more likely to have an LBW infant than mothers in any other education category, mirroring the unadjusted results from Table 2. In Australia, although mothers with less than a high school education were most at risk for having LBW infants, mothers with some college education but not a bachelor-degree equivalent were also at increased risk (albeit with marginal statistical significance). In Canada, there were no significant differences in LBW by maternal education. The associations between all control variables and LBW were similar when maternal education (Table C, available as a supplement to the online version of this article at http://www. ajph.org), rather than income quintile, was included in the models. Again, supplementary analyses limited the sample to Whites only (in Australia, proxied by Australian-born), providing a sensitivity check for the LBW analyses by education in Table 4 that did not include racial/ethnic variables (Table D, available as a supplement to the online version of this article at http:// www.ajph.org). For the United States, a clear graded association between education and LBW was now apparent, with a significant difference between mothers who had not completed high school and those with a high school education. This finding is consistent with previous research showing that socioeconomic gradients in LBW in the United States are more apparent for White mothers than for mothers in other racial/ethnic groups.11
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In other analyses (data not shown), we calculated adjusted LBW proportions to supplement the logistic regression models in Tables 3 and 4. The patterns of results were unchanged. Another set of models included an indicator of any prenatal smoking, and the results were similar to those shown in Tables 3 and 4, suggesting that socioeconomic gradients in LBW did not reflect maternal smoking behavior (as we were able to measure it) in any of the countries. Finally, models for the United States, the only country of the 4 without universal health insurance, were estimated with a measure of maternal health insurance (private insurance, Medicaid, none, other); the results were not sensitive to this alternative specification, suggesting that differences in access to health insurance do not explain socioeconomic gradients in LBW in the United States.
DISCUSSION Socioeconomic gradients in LBW were apparent in all 4 of the countries we assessed, but magnitudes and patterns differed across the countries. There was a clear graded association between income quintile and LBW in the United States, whereas the relevant distinction in the United Kingdom appeared to be between low, middle, and high incomes and the distinction in both Canada and Australia appeared to be between mothers in the lowest income quintile and higherincome mothers. When the sample was limited to Whites (in Australia, proxied by Australian-born), the patterns were similar to the overall patterns for the United States, the United Kingdom, and Australia; however,
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TABLE 4—Odds Ratios of Low Birth Weight by Maternal Education: United States, United Kingdom, Canada, and Australia United States (n = 8400), OR (95% CI)
United Kingdom (n = 12 018), OR (95% CI)
Canada (n = 5350), OR (95% CI)
Australia (n = 3452), OR (95% CI)
< high school or equivalent
1.89 (1.45, 2.46)
2.42 (1.78, 3.30)
0.85 (0.48, 1.50)
2.32 (1.39, 3.87)
High school or equivalent
1.90 (1.51, 2.39)
1.42 (1.11, 1.83)
0.96 (0.55, 1.70)
0.75 (0.37, 1.51)
Some college or equivalent
1.54 (1.23, 1.92)
1.20 (0.91, 1.58)
0.78 (0.48, 1.26)
1.65 (0.99, 2.76)
1
1
1
1
Maternal Education
‡ bachelor’s degree (Ref)
Note. CI = confidence interval; OR = odds ratio. Figures are weighted to be nationally representative of each country. Models controlled for parity, child sex, maternal nativity, marital status, and maternal age at birth. The full models are available in Table C (available as a supplement to the online version of this article at http://www.ajph.org). Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
there was no association between income quintile and LBW in Canada. When we used maternal education instead of income, inequalities were evident in all countries other than Canada but with less clear gradients; in the United States, a graded relationship was clearly apparent for Whites. Overall, gradients in health at birth were most pronounced in the United States but were also present to varying degrees in the other countries. It appears that socioeconomic inequalities are less consequential for LBW in the United Kingdom, Canada, and Australia than they are in the United States, suggesting that the more generous social support and health care systems in those 3 countries play buffering roles. The observed cross-national patterns of socioeconomic gradients in LBW are consistent with dominant theoretical frameworks of health disparities. According to one, differences in resources, including living conditions, underlie health inequalities.35 Another posits that relative deprivation or social position is more important than levels of resources.36 We found that low income and low education were associated with increased risk of LBW in all 4 countries, even those with universal health care (suggesting that relative deprivation is important), although disparities and gradients were smaller in countries with a commitment to universal health care (suggesting that levels of resources are also important). In the case of the United States and the United Kingdom, our LBW results add to findings from previous research indicating that health gradients are apparent throughout the life course in those 2 countries.7 It is noteworthy that the United States has an
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overall LBW rate that is on par with the rates in other countries examined here (United Kingdom and Canada) but has higher rates of later-life morbidity.6,12,37 Future research is needed to identify the roles of income inequality, social safety nets, and health care systems in shaping health disparities throughout the life course. Our finding that health insurance coverage appeared to play no role in explaining socioeconomic gradients in LBW in the United States may reflect the fact that prenatal care is widely available in that country.38 However, socioeconomic differences in the quality and continuity of prenatal care that women receive or their use of preconceptional care, which is not universal in the United States, may play a role. It is also possible that the large US gradients reflect poverty-related factors that are not directly associated with health insurance coverage, such as food insecurity, income instability, and residential segregation, all of which represent pervasive problems in the United States.
Limitations and Strengths Although our study provides important documentation of socioeconomic inequalities in health at birth across 4 countries, it is not without limitations, some of which point to potentially fruitful directions for future research. First, we were limited in our ability to characterize infant health. LBW is a useful, well-documented indicator of infant health, particularly for international comparisons,8 but more nuanced measures (e.g., very low birth weight, preterm birth, macrosomia) were not available either owing to limited power or because they were not available in all data sets.
Second, unlike the data sets from the other 3 countries, the nationally representative NLSCY in Canada was not a birth sample and, thus, may not be fully representative of births in that country. It appears that there are no nationally representative data on births in Canada that include measures of socioeconomic status, perhaps explaining why we were unable to find any prior documentation of socioeconomic inequalities in health at birth in that country. The official LBW rate in Canada in 2000 was 5.6%,39 as compared with our rate from the NLSCY of 5.5% for births occurring between 1998 and 2001, giving us confidence in our estimates. As such, despite its limitations (e.g., incomplete race data and potentially imprecise measures of marital status), we view our use of the NLSCY to produce national estimates of socioeconomic inequalities in LBW as a contribution of this study. Third, as a result of lack of power, we were not able to conduct analyses for racial/ethnic groups other than Whites, which has been a pervasive limitation in the literature.6 Finally, although not a limitation of our study per se, future research that includes more countries might permit an exploration of the role of country-level factors in shaping health disparities at birth.
Conclusions Socioeconomic inequalities in low birth weight are larger in the United States than in the United Kingdom, Canada, and Australia, and income inequality is on the rise globally, with the United States leading the way.15 Countries have varying policy responses to inequality that include income transfers,
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visiting nurses for mothers and children, and expansions in health care coverage and quality. The predicted increase in income inequality across the globe does not bode well for poor residents of the United States, given the historically weak US social and health care safety nets. The Affordable Care Act, which has increased rates of health insurance coverage in the United States, may help mitigate potential adverse health effects associated with rising income inequality; however, the stability of LBW in the United States over the past half century, despite large expansions in provision of prenatal care, dramatic decreases in smoking, and increases in assisted reproductive technologies, obstetric interventions, and obesity, suggests that this improvement will take time and that health care reform alone may not be enough.
9. Johnson RC, Schoeni RF. The influence of early-life events on human capital, health status, and labor market outcomes over the life course. B E J Econom Anal Policy. 2011;11(3):2521. 10. Finch BK. Socioeconomic gradients and low birthweight: empirical and policy considerations. Health Serv Res. 2003;38(6):1819–1842. 11. Nepomnyaschy L. Socioeconomic gradients in infant health across race and ethnicity. Matern Child Health J. 2009;13(6):720–731. 12. Organisation for Economic Co-Operation and Development. Health at a glance 2013: OECD indicators. Available at: http://dx.doi.org/10.1787/health_glance2013-en. Accessed December 23, 2015. 13. Organisation for Economic Co-Operation and Development. OECD factbook 2014: economic, environmental and social statistics. Available at: http://www. oecd-ilibrary.org/economics/oecd-factbook2014_factbook-2014-en. Accessed December 23, 2015. 14. Central Intelligence Agency. The world factbook: 2015. Available at: https://www.cia.gov/library/ publications/the-world-factbook/fields/2075.html. Accessed December 23, 2015.
CONTRIBUTORS
15. Pickett KE, Wilkinson RG. Income inequality and health: a causal review. Soc Sci Med. 2015;128:316–326.
M. L. Martinson conceived the study, designed and conducted all analyses, and wrote the article. N. E. Reichman contributed to the conception of the article, the interpretation of the findings, and the writing of the article.
16. Bethel J, Green J, Kalton G, Nord C. Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), Sampling. Washington, DC: US Department of Education, National Center for Education Statistics; 2005.
ACKNOWLEDGMENTS Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant (R24 HD042828) to the Center for Studies in Demography & Ecology at the University of Washington.
HUMAN PARTICIPANT PROTECTION No protocol approval was needed for this study because secondary data were used and no human participants were involved.
REFERENCES
17. Snow K, Thalji L, Derecho A, et al. User’s Manual for the ECLS-B Longitudinal 9-Month–Preschool Restricted-Use Data File and Electronic Codebook. Washington, DC: US Department of Education, National Center for Education Statistics; 2007. 18. Plewis I, Calderwood L, Hawkes D, Hughes G, Joshi H. Millennium Cohort Study: Technical Report on Sampling. 3rd ed. London, England: Institute of Education; 2004. 19. Soloff C, Lawrence D, Misson S, Johnstone R. LSAC Technical Paper No. 3: Wave 1 Weighting and Non-Response. Melbourne, Victoria, Australia: Australian Institute of Family Studies; 2006.
1. Case A, Lubotsky D, Paxson C. Economic status and health in childhood: the origins of the gradient. Am Econ Rev. 2002;92(5):1308–1334.
20. Longitudinal Study of Australian Children: An Australian Government Initiative Data User Guide. Melbourne, Victoria, Australia: Australian Institute of Family Studies; 2009.
2. Currie J, Stabile M. Socioeconomic status and child health: why is the relationship stronger for older children? Am Econ Rev. 2003;93(5):1813–1823.
21. National Study of Children and Youth: Overview of Survey Instruments Cycle 3. Ottawa, Ontario, Canada: Statistics Canada; 1999.
3. Currie A, Shields MA, Price SW. The child health/ family income gradient: evidence from England. J Health Econ. 2007;26(2):213–232.
22. National Study of Children and Youth: Overview of Survey Instruments Cycle 4. Ottawa, Ontario, Canada: Statistics Canada; 2001.
4. Case A, Lee D, Paxson C. The income gradient in children’s health: a comment on Currie, Shields and Wheatley Price. J Health Econ. 2008;27(3):801–807.
23. McCormick MC, Brooks-Gunn J. Concurrent child health status and maternal recall of events in infancy. Pediatrics. 1999;104(5):1176–1181.
5. Khanam R, Nghiem HS, Connelly LB. Child health and the income gradient: evidence from Australia. J Health Econ. 2009;28(4):805–817.
24. O’Sullivan JJ, Pearce MS, Parker L. Parental recall of birth weight: how accurate is it? Arch Dis Child. 2000;82 (3):202–203.
6. Banks J, Marmot M, Oldfield Z, Smith JP. Disease and disadvantage in the United States and in England. JAMA. 2006;295(17):2037–2045.
25. Organisation for Economic Co-Operation and Development. What are equivalence scales? Available at: http://www.oecd.org/eco/growth/OECD-NoteEquivalenceScales.pdf. Accessed December 23, 2015.
7. Martinson ML. Income inequality in health at all ages: a comparison of the United States and England. Am J Public Health. 2012;102(11):2049–2056. 8. Reichman NE. Low birth weight and school readiness. Future Child. 2005;15(1):91–116.
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27. Choi KH, Tienda M, Cobb-Clark D, Sinning M. Immigration and status exchange in Australia and the United States. Res Soc Stratif Mobil. 2012;30(1):49–62. 28. Washbrook E, Waldfogel J, Bradbury B, Corak M, Ghanghro AA. The development of young children of immigrants in Australia, Canada, the United Kingdom, and the United States. Child Dev. 2012;83(5):1591–1607. 29. US Department of Health and Human Services. The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta, GA: Centers for Disease Control and Prevention; 2004. 30. Teitler JO, Reichman NE, Nepomnyaschy L, Martinson ML. A cross-national comparison of racial and ethnic disparities in low birth weight in the United States and England. Pediatrics. 2007;120(5):e1182–e1189. 31. Australian Bureau of Statistics. Census of Population and Housing, 2001. Available at: http://www.abs.gov.au/AUSSTATS/abs@. nsf/bb8db737e2af84b8ca2571780015701e/ af5129cb50e07099ca2570eb0082e462!OpenDocument. Accessed December 23, 2015. 32. Stata: Release 11. College Station, TX: StataCorp LP; 2013. 33. SAS, Version 9.4. Cary, NC: SAS Institute Inc; 2013. 34. Reichman NE, Pagnini D. Maternal age and birth outcomes: data from New Jersey. Fam Plann Perspect. 1997;29(6):268–272, 295. 35. Lynch JW, Smith GD, Kaplan GA, House JS. Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ. 2000;320(7243):1200–1204. 36. Marmot M, Wilkinson RG. Psychosocial and material pathways in the relation between income and health: a response to Lynch et al. BMJ. 2001;322(7296): 1233–1236. 37. Martinson ML, Teitler JO, Reichman NE. Health across the life span in the United States and England. Am J Epidemiol. 2011;173(8):858–865. 38. Currie J, Reichman N. Policies to promote child health: introducing the issue. Future Child. 2015;25(1): 3–9. 39. Statistics Canada. Health: low birth weight. Available at: http://www4.hrsdc.gc.ca/[email protected]? iid=4. Accessed December 23, 2015.
26. Pilkauskas N, Martinson ML. Three-generation family households in early childhood: comparisons between the United States, the United Kingdom, and Australia. Demogr Res. 2014;30:1639–1652.
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Socioeconomic Inequalities in Low Birth Weight in the United States, the United Kingdom, Canada, and Australia Melissa L. Martinson, PhD, and Nancy E. Reichman, PhD Objectives. To compare associations between socioeconomic status and low birth weight across the United States, the United Kingdom, Canada, and Australia, countries that share cultural features but differ in terms of public support and health care systems. Methods. Using nationally representative data from the United States (n = 8400), the United Kingdom (n = 12 018), Canada (n = 5350), and Australia (n = 3452) from the early 2000s, we calculated weighted prevalence rates and adjusted odds of low birth weight by income quintile and maternal education. Results. Socioeconomic gradients in low birth weight were apparent in all 4 countries, but the magnitudes and patterns differed across countries. A clear graded association between income quintile and low birth weight was apparent in the United States. The relevant distinction in the United Kingdom appeared to be between low, middle, and high incomes, and the distinction in Canada and Australia appeared to be between mothers in the lowest income quintile and higher-income mothers. Conclusions. Socioeconomic inequalities in low birth weight were larger in the United States than the other countries, suggesting that the more generous social safety nets and health care systems in the United Kingdom, Canada, and Australia played buffering roles. (Am J Public Health. 2016;106:748–754. doi:10.2105/AJPH.2015.303007)
S
ocioeconomic inequalities in health are pervasive in the developed world, a fact that has led to questions about the extent of health inequalities across countries. Yet, despite a developing literature on health across Organisation for Economic Co-operation and Development countries, relatively little is known about inequalities in health across countries or at what point during the life course socioeconomic inequalities in heath emerge. A few studies have compared income gradients in parent-reported child health status in the United States with those in the United Kingdom, Canada, or Australia, but the purpose of those studies was not to document cross-country comparisons.1–5 Other studies incorporating objective health measures have shown that socioeconomic gradients in health are very similar in the United States and United Kingdom throughout the life course, despite better
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overall population health in the United Kingdom; however, health measures for young children were limited in those studies.6,7 As such, little is known about how socioeconomic gradients in health at very young ages compare across countries. Low birth weight (LBW) is an important measure of health at the “starting gate” because it is a leading risk factor for infant mortality as well as a marker for subsequent child morbidity among infants who survive8; it is also an important predictor of health and socioeconomic status over the life course and across generations.9 In the United States, there is clear evidence of a socioeconomic
gradient in LBW, although patterns vary by race/ethnicity.10,11 Little is known about the magnitude of socioeconomic gradients in health at birth in other developed countries. We used nationally representative data from 4 countries—the United States, the United Kingdom, Canada, and Australia—to compare socioeconomic gradients in LBW across English-speaking countries that share cultural features but differ in terms of public support and health care systems. The United Kingdom, Canada, and Australia enjoy better overall population health than the United States 12 and also have more generous health care and social support systems.12,13 All 4 countries are diverse, with relatively large immigrant populations but different racial/ ethnic mixes.14 Canada and Australia have lower income inequality than the United States and United Kingdom, as measured by Gini coefficients,13 and there is increasing evidence that income inequality adversely affects population health.15 For most of these reasons, we expected that socioeconomic gradients in LBW would be largest in the United States.
METHODS We used data on singleton births from 4 nationally representative data sets: the Early Childhood Longitudinal Study–Birth Cohort (ECLS-B) for the United States, the Millennium Cohort Study (MCS) for the United Kingdom, the National Longitudinal Survey of Children and Youth (NLSCY) for Canada,
ABOUT THE AUTHORS Melissa L. Martinson is with the School of Social Work, University of Washington, Seattle. Nancy E. Reichman is with the Department of Pediatrics, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ. Correspondence should be sent to Melissa L. Martinson, University of Washington, School of Social Work, 4101 15th Ave NE, Seattle, WA 98105 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted November 21, 2015. doi: 10.2105/AJPH.2015.303007
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and the Longitudinal Study of Australian Children–Birth Cohort (LSAC) for Australia. The ECLS-B is a restricted-use, nationally representative sample of approximately 10 700 children who were born in 2001 to mothers aged 15 years or older and who were alive and residing in the United States at 9 months of age.16,17 As a result of confidentiality requirements, all sample sizes in the ECLS-B were rounded to the nearest 50. The MCS is a representative sample of approximately 20 000 UK births occurring between 2000 and 2002.18 The LSAC was modeled on the ECLS-B and includes a representative sample of approximately 5000 children born in 2003 and 2004 taken from the Health Insurance Commission Medicare database.19,20 The restricted-use NLSCY is not a birth cohort study but, rather, a longitudinal study of children of all ages in Canada.21,22 We used data on the 5000 children in waves 3 and 4 of the NLSCY who were born between 1998 and 2001 to create a sample that resembled those from the birth cohort studies in the other countries.
Measures Low birth weight. LBW was defined as less than 2500 grams (approximately 5.5 pounds), the threshold used internationally. Birth weight was based on maternal reports in the United Kingdom, Canada, and Australia and taken from birth certificates for the United States. Maternal reports of birth weight have been shown to be very accurate, even retrospectively after many years.23,24 Socioeconomic status. The primary measure of socioeconomic status was weighted income quintile calculated from total family income, available in each country, adjusted for family size via the Organisation for Economic Co-operation and Development’s equivalency scale.25 We also considered maternal education, the other measure of socioeconomic status used in the relevant literature. On the basis of previous comparative research in the countries of interest,26–28 maternal education was coded as follows: less than high school or equivalent, high school or equivalent, some postsecondary education or college, and at least a college education. Covariates. We controlled for important compositional differences that were
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comparable across the data sets. Maternal age at birth was coded as younger than 20 years, 20 to 34 years, and 35 years or older. Marital status was characterized by whether the mother was married at the time of the birth. Parity was characterized as first versus higher-order birth. Mother’s nativity was classified as foreign-born versus native-born in the country of interest. All models controlled for the child’s sex. An indicator of any prenatal smoking (based on maternal retrospective reports) was included in supplementary models to allow a broad look at the contribution of smoking, which is a strong risk factor for low birth weight,29 to the observed socioeconomic gradients in birth weight. We conducted sensitivity analyses that included a measure of race/ethnicity and region of origin. Race/ethnicity was assessed very differently across countries. For the United States, we included the frequently used categories of non-Hispanic White, non-Hispanic Black, Hispanic, Asian, American Indian/Alaska Native, and other race/ethnicity. For the United Kingdom, we used categories that are representative of the major groups in that country: White, Black (Black Caribbean or Black African), Asian (South Asian including Indian, Pakistani, and Bangladeshi), and other.30 In Canada, race was assessed only for a subsample in one survey wave, limiting the available sample for analyses that incorporated this information. The categories included White, Asian, Black, First Nations, and other. The LSAC data for Australia did not include a measure of race/ethnicity but did include region of origin, which we used as a proxy measure. The categories for region of origin included Australian, Aboriginal Australian, Asian immigrants, immigrants from English-speaking countries, and other immigrants. The majority of the Australian-born population is of White ancestry.31 We conducted supplementary analyses of the White-only (or, for Australia, the Australianborn) samples for each country to remove potential confounding effects of race/ ethnicity.
Analysis Strategy For each country, we calculated sample characteristics as well as rates of LBW by each
of the sample characteristics. We also estimated logistic regression models to obtain adjusted odds ratios for LBW as a function of income quintile or, alternatively, maternal education within each country. All statistical comparisons were within countries. We used the svy procedures in Stata SE version 13 to adjust for the complex sampling design in each data set, allowing us to obtain nationally representative results.32 The NLSCY analysis was conducted through Statistics Canada via a restricted data protocol; the output was generated with SAS version 9.4.33
RESULTS In the United Kingdom, half of births were first births, whereas in the other countries the rates of first births were lower (approximately 40%; Table 1). Adolescent childbearing was most common in the United States, followed by the United Kingdom and then Australia and Canada. In the United Kingdom, the percentage of mothers who were married at the time of the birth was 60.3%; the rate of marital childbearing was closer to 70% in the other countries. Mothers in the United States and United Kingdom were less likely to smoke during their pregnancy than those in Australia and Canada. All 4 countries are major immigrant destination countries, but the proportions of births to foreign-born mothers in the United States and Australia were about twice those in the United Kingdom and Canada. This pattern resembles national immigrant population rates.13 Racial/ethnic patterns differed across countries, with mothers giving birth in the United States being much less likely to be White than those in the other countries. In Australia, the majority of mothers were Australian-born. Finally, there was noticeable variation in maternal education. Mothers were most likely to have less than a high school education or equivalent in Australia, whereas they were most likely to have a college education or more in Canada. Overall, the rate of LBW was lowest in Australia (4.8%), followed by Canada (5.5%); the rate was highest in the United Kingdom (6.0%) and the United States (5.8%) (Table 2). There was a very clear graded association between income quintile and LBW in the United States, whereas the relevant
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TABLE 1—Characteristics of the US, UK, Canadian, and Australian Samples United States (n = 8400), %
Characteristic
United Kingdom (n = 12 018), %
Canada (n = 5350), %
Australia (n = 3452), %
Maternal education < high school or equivalent
19.6
11.2
14.1
35.9
High school or equivalent
28.5
40.1
17.6
12.7
Some college or equivalent
27.5
20.0
23.9
20.2
‡ bachelor’s degree
24.4
28.8
44.4
31.3
40.7
49.8
42.1
40.5
First birth Female child
48.7
49.3
49.7
48.5
Mother foreign-born
21.6
10.4
11.5
21.2
Mother married
66.8
60.3
71.2
73.3
Maternal age at birth, y < 20
11.0
6.9
3.7
3.7
20–34
75.3
75.6
81.3
75.8
‡ 35
13.8
17.5
15.0
20.5
White
57.4
89.6
90.0
Black
13.8
3.0
1.3
Asian
3.5
6.4
4.2
22.9 1.8
1.0
Maternal race/ethnicity
Hispanic Other Native American/indigenous
0.6
1.6 2.9
Country of origin (Australia) Australian-born
76.2
Indigenous
2.6
English-speaking immigrant
7.6
Asian immigrant
5.5
Other immigrant Mother smoked during pregnancy
8.1 14.8
14.8
21.7
18.8
Note. Figures are weighted to be nationally representative of each country. Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998– 2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
distinction in the United Kingdom appeared to be between low, middle, and high incomes; in both Canada and Australia, the distinction appeared to be between the lowest income quintile and higher-income mothers. In the United States, the rate of LBW in the bottom income quintile (8.0%) was 2.41 times the rate in the highest quintile (3.3%); the corresponding figures for the United Kingdom, Canada, and Australia were 1.74, 1.61, and 1.87, respectively. The patterns by education were slightly different than the patterns by income. In the United States, there appeared to be a graded association between education and LBW that spanned from low education (highest LBW rate) to high education (lowest LBW rate). A
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similar pattern was evident for the United Kingdom, where the rate of LBW was extremely high in the lowest education category. This high rate might reflect the fact that the percentage of mothers in this group was only 11.2%, suggesting that they may have thus been particularly disadvantaged. Interestingly, no LBW education gradient was apparent in Canada. Finally, although LBW varied by maternal education in Australia (LBW was most likely among mothers with no high school diploma and some college), there was no clear graded association apparent in our unadjusted results. In all 4 countries, first-born infants were more likely than their higher-order counterparts to be LBW. In the United States,
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younger and older mothers are more likely to have LBW infants than mothers 20 to 34 years of age, a finding well established in the literature.34 However, this pattern was not present in the other countries. Whereas infants born to married mothers were less likely than those born to unmarried mothers to be LBW in the United States, the United Kingdom, and Australia, this did not appear to be the case in Canada. As noted, however, the NLSCY is not a birth cohort study, making it more difficult to pinpoint marital status specifically at the time of the birth. As expected on the basis of a rich multidisciplinary literature, prenatal smoking increased the likelihood of LBW in all 4 countries. Compared with the relevant native-born populations, foreign-born status was associated with a higher rate of LBW in Australia and a lower rate in the United Kingdom, although these differences were not statistically significant. In the United States and Canada, there were minimal differences in LBW rates by nativity. Racial/ethnic or country-of-origin disparities in LBW were apparent in all 4 countries. Multivariate logistic regression models of associations between income quintile and LBW included all variables in Table 1 other than maternal education, race/ethnicity (for the United States, the United Kingdom, and Canada), country of origin (for Australia), and smoking (Table 3). Inclusion of the race/ ethnicity and country-of-origin variables did not change the substantive results (available on request from the authors), but those factors were excluded here to enhance the comparability of measures across countries. The estimates, presented as odds ratios, reveal a pattern similar to that observed in the unadjusted results in Table 2 for the United States, where there was a clear and significant income gradient in LBW. Likewise, inclusion of the controls in Table 3 did not alter the pattern of unadjusted associations between income quintile and LBW in the United Kingdom, with 3 distinct income groups vis-`a-vis LBW risk. Finally, although Table 2 shows that low-income mothers in Canada and Australia were twice as likely to have an LBW infant as higher-income mothers, in Canada this relationship was not statistically significant at a conventional level in the multivariate context (Table 3), perhaps owing to the smaller sample in that country.
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TABLE 2—Low Birth Weight by Sample Characteristics: United States, United Kingdom, Canada, and Australia Characteristic
United States (n = 8400), %
United Kingdom (n = 12 018), %
Canada (n = 5350), %
Australia (n = 3452), %
5.8
6.0
5.5
4.8
Bottom
8.0*
8.3*
7.0
7.0*
Second
7.1*
6.3*
7.0
5.7
Middle
6.0*
6.3*
4.7
4.2
Fourth
4.6*
4.8
4.8
3.2
Top
3.3
4.8
4.3
3.7
< high school or equivalent
7.3*
10.1*
4.5
6.7*
High school or equivalent
6.9*
6.2*
5.3
2.4
Some college or equivalent
5.4*
5.3
5.2
5.2*
‡ bachelor’s degree
3.6
4.5
5.5
3.2
First birth
7.2*
7.1*
6.5
5.9*
Higher-order birth
4.8
4.8
4.8
4.0
Total low birth weight rate Income quintile
Maternal education
Parity
Child sex Female
6.2*
6.5*
5.9
5.0
Male
5.3
5.4
5.1
4.6
Foreign-born
5.9
7.1
5.7
5.7
Native-born
5.7
5.8
5.5
4.5
Married
4.6*
5.1*
5.5
4.2*
Unmarried
8.2
7.2
5.4
6.3
Maternal nativity
Mother’s marital status at birth
Maternal age at birth, y < 20
8.7*
7.3
3.7
5.7
20–34
5.2
5.8
5.7
4.9
6.6*
6.1
5.2
4.1
White
4.7
5.4
4.6
Black
10.4*
8.8*
Asian
6.0*
12.8*
2.1*
Hispanic
5.6*
Other
7.1*
2.7
7.8*
Native American/indigenous
2.9
‡ 35 Maternal race/ethnicity
a
7.2*
Country of origin (Australia) Australian-born
4.2
Indigenous
12.9*
English-speaking immigrant
2.4
Asian immigrant
6.5
Other immigrant
8.3*
Maternal prenatal smoking status Smoked
6.1*
8.8*
6.6
8.2*
Did not smoke
3.9
4.5
5.1
4.0
Note. Figures are weighted to be nationally representative of each country. Reference categories were top income quintile, bachelor’s degree or more, higherorder birth, male child, mother native-born, mother unmarried, maternal age at birth 20–34 years, White race/ethnicity or Australian-born (Australia), and nonsmoker during pregnancy. Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004). a Race/ethnicity was available only for a subsample in Canada. *P < .05 (within-country difference).
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TABLE 3—Odds of Low Birth Weight by Income Quintile: United States, United Kingdom, Canada, and Australia Income Quintile
United States (n = 8400), OR (95% CI)
United Kingdom (n = 12 018), OR (95% CI)
Canada (n = 5350), OR (95% CI)
Australia (n = 3452), OR (95% CI)
Bottom
2.37 (1.80, 3.11)
1.78 (1.30, 2.44)
2.07 (0.94, 4.53)
2.11 (1.12, 3.99)
Second
2.21 (1.68, 2.90)
1.42 (1.04, 1.93)
1.55 (0.83, 2.87)
1.76 (0.97, 3.20)
Middle
1.88 (1.44, 2.46)
1.40 (1.07, 1.84)
1.28 (0.64, 2.56)
1.37 (0.74, 2.54)
Fourth
1.45 (1.11, 1.88)
1.07 (0.80, 1.42)
1.16 (0.61, 2.22)
0.86 (0.44, 1.68)
1
1
1
1
Top (Ref)
Note. CI = confidence interval; OR = odds ratio. Figures are weighted to be nationally representative of each country. Models controlled for parity, child sex, maternal nativity, marital status, and maternal age at birth. The full models are available in Table A (available as a supplement to the online version of this article at http://www.ajph.org). Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
A number of other patterns that were apparent in Table 2 persisted in the multivariate analyses. First births were associated with increased odds of LBW in all 4 countries. Being married at the time of the birth was protective against LBW only in the United States; it fell on the margins of significance in the United Kingdom. We also found country-specific associations between maternal age and LBW. Being an older mother (aged 35 years or older) was associated with LBW only in the United States and the United Kingdom (Table A, available as a supplement to the online version of this article at http://www.ajph.org). Supplementary analyses limited the sample to Whites (in Australia, proxied by Australianborn) in all 4 countries, providing a sensitivity check for the estimates in Table 3 in which there was no control for potential confounding effects of race/ethnicity (Table B, available as a supplement to the online version of this article at http://www.ajph. org). The patterns of associations between income quintile and LBW were similar to those in Table 3 for the United States, the United Kingdom, and Australia. In Canada, however, there was no association between income quintile and LBW among Whites. Logistic regression estimates of associations between our alternative measure of socioeconomic status—maternal education—and LBW revealed patterns that differed somewhat from those for income and LBW (Table 4). In the United States, lower education was associated with higher rates of LBW, but a graded pattern was not as apparent as it was for income quintiles. Mothers with a high school education and those who had not completed high school were most likely to
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have an LBW infant, with no difference between these 2 categories, followed by mothers with some college. In the United Kingdom, mothers with less than a high school education were significantly more likely to have an LBW infant than mothers in any other education category, mirroring the unadjusted results from Table 2. In Australia, although mothers with less than a high school education were most at risk for having LBW infants, mothers with some college education but not a bachelor-degree equivalent were also at increased risk (albeit with marginal statistical significance). In Canada, there were no significant differences in LBW by maternal education. The associations between all control variables and LBW were similar when maternal education (Table C, available as a supplement to the online version of this article at http://www. ajph.org), rather than income quintile, was included in the models. Again, supplementary analyses limited the sample to Whites only (in Australia, proxied by Australian-born), providing a sensitivity check for the LBW analyses by education in Table 4 that did not include racial/ethnic variables (Table D, available as a supplement to the online version of this article at http:// www.ajph.org). For the United States, a clear graded association between education and LBW was now apparent, with a significant difference between mothers who had not completed high school and those with a high school education. This finding is consistent with previous research showing that socioeconomic gradients in LBW in the United States are more apparent for White mothers than for mothers in other racial/ethnic groups.11
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In other analyses (data not shown), we calculated adjusted LBW proportions to supplement the logistic regression models in Tables 3 and 4. The patterns of results were unchanged. Another set of models included an indicator of any prenatal smoking, and the results were similar to those shown in Tables 3 and 4, suggesting that socioeconomic gradients in LBW did not reflect maternal smoking behavior (as we were able to measure it) in any of the countries. Finally, models for the United States, the only country of the 4 without universal health insurance, were estimated with a measure of maternal health insurance (private insurance, Medicaid, none, other); the results were not sensitive to this alternative specification, suggesting that differences in access to health insurance do not explain socioeconomic gradients in LBW in the United States.
DISCUSSION Socioeconomic gradients in LBW were apparent in all 4 of the countries we assessed, but magnitudes and patterns differed across the countries. There was a clear graded association between income quintile and LBW in the United States, whereas the relevant distinction in the United Kingdom appeared to be between low, middle, and high incomes and the distinction in both Canada and Australia appeared to be between mothers in the lowest income quintile and higherincome mothers. When the sample was limited to Whites (in Australia, proxied by Australian-born), the patterns were similar to the overall patterns for the United States, the United Kingdom, and Australia; however,
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TABLE 4—Odds Ratios of Low Birth Weight by Maternal Education: United States, United Kingdom, Canada, and Australia United States (n = 8400), OR (95% CI)
United Kingdom (n = 12 018), OR (95% CI)
Canada (n = 5350), OR (95% CI)
Australia (n = 3452), OR (95% CI)
< high school or equivalent
1.89 (1.45, 2.46)
2.42 (1.78, 3.30)
0.85 (0.48, 1.50)
2.32 (1.39, 3.87)
High school or equivalent
1.90 (1.51, 2.39)
1.42 (1.11, 1.83)
0.96 (0.55, 1.70)
0.75 (0.37, 1.51)
Some college or equivalent
1.54 (1.23, 1.92)
1.20 (0.91, 1.58)
0.78 (0.48, 1.26)
1.65 (0.99, 2.76)
1
1
1
1
Maternal Education
‡ bachelor’s degree (Ref)
Note. CI = confidence interval; OR = odds ratio. Figures are weighted to be nationally representative of each country. Models controlled for parity, child sex, maternal nativity, marital status, and maternal age at birth. The full models are available in Table C (available as a supplement to the online version of this article at http://www.ajph.org). Source. United States: Early Childhood Longitudinal Study–Birth Cohort (2001); United Kingdom: Millennium Cohort Study (2000–2002); Canada: National Longitudinal Survey of Children and Youth (1998–2001); Australia: Longitudinal Study of Australian Children–Birth Cohort (2003–2004).
there was no association between income quintile and LBW in Canada. When we used maternal education instead of income, inequalities were evident in all countries other than Canada but with less clear gradients; in the United States, a graded relationship was clearly apparent for Whites. Overall, gradients in health at birth were most pronounced in the United States but were also present to varying degrees in the other countries. It appears that socioeconomic inequalities are less consequential for LBW in the United Kingdom, Canada, and Australia than they are in the United States, suggesting that the more generous social support and health care systems in those 3 countries play buffering roles. The observed cross-national patterns of socioeconomic gradients in LBW are consistent with dominant theoretical frameworks of health disparities. According to one, differences in resources, including living conditions, underlie health inequalities.35 Another posits that relative deprivation or social position is more important than levels of resources.36 We found that low income and low education were associated with increased risk of LBW in all 4 countries, even those with universal health care (suggesting that relative deprivation is important), although disparities and gradients were smaller in countries with a commitment to universal health care (suggesting that levels of resources are also important). In the case of the United States and the United Kingdom, our LBW results add to findings from previous research indicating that health gradients are apparent throughout the life course in those 2 countries.7 It is noteworthy that the United States has an
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overall LBW rate that is on par with the rates in other countries examined here (United Kingdom and Canada) but has higher rates of later-life morbidity.6,12,37 Future research is needed to identify the roles of income inequality, social safety nets, and health care systems in shaping health disparities throughout the life course. Our finding that health insurance coverage appeared to play no role in explaining socioeconomic gradients in LBW in the United States may reflect the fact that prenatal care is widely available in that country.38 However, socioeconomic differences in the quality and continuity of prenatal care that women receive or their use of preconceptional care, which is not universal in the United States, may play a role. It is also possible that the large US gradients reflect poverty-related factors that are not directly associated with health insurance coverage, such as food insecurity, income instability, and residential segregation, all of which represent pervasive problems in the United States.
Limitations and Strengths Although our study provides important documentation of socioeconomic inequalities in health at birth across 4 countries, it is not without limitations, some of which point to potentially fruitful directions for future research. First, we were limited in our ability to characterize infant health. LBW is a useful, well-documented indicator of infant health, particularly for international comparisons,8 but more nuanced measures (e.g., very low birth weight, preterm birth, macrosomia) were not available either owing to limited power or because they were not available in all data sets.
Second, unlike the data sets from the other 3 countries, the nationally representative NLSCY in Canada was not a birth sample and, thus, may not be fully representative of births in that country. It appears that there are no nationally representative data on births in Canada that include measures of socioeconomic status, perhaps explaining why we were unable to find any prior documentation of socioeconomic inequalities in health at birth in that country. The official LBW rate in Canada in 2000 was 5.6%,39 as compared with our rate from the NLSCY of 5.5% for births occurring between 1998 and 2001, giving us confidence in our estimates. As such, despite its limitations (e.g., incomplete race data and potentially imprecise measures of marital status), we view our use of the NLSCY to produce national estimates of socioeconomic inequalities in LBW as a contribution of this study. Third, as a result of lack of power, we were not able to conduct analyses for racial/ethnic groups other than Whites, which has been a pervasive limitation in the literature.6 Finally, although not a limitation of our study per se, future research that includes more countries might permit an exploration of the role of country-level factors in shaping health disparities at birth.
Conclusions Socioeconomic inequalities in low birth weight are larger in the United States than in the United Kingdom, Canada, and Australia, and income inequality is on the rise globally, with the United States leading the way.15 Countries have varying policy responses to inequality that include income transfers,
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visiting nurses for mothers and children, and expansions in health care coverage and quality. The predicted increase in income inequality across the globe does not bode well for poor residents of the United States, given the historically weak US social and health care safety nets. The Affordable Care Act, which has increased rates of health insurance coverage in the United States, may help mitigate potential adverse health effects associated with rising income inequality; however, the stability of LBW in the United States over the past half century, despite large expansions in provision of prenatal care, dramatic decreases in smoking, and increases in assisted reproductive technologies, obstetric interventions, and obesity, suggests that this improvement will take time and that health care reform alone may not be enough.
9. Johnson RC, Schoeni RF. The influence of early-life events on human capital, health status, and labor market outcomes over the life course. B E J Econom Anal Policy. 2011;11(3):2521. 10. Finch BK. Socioeconomic gradients and low birthweight: empirical and policy considerations. Health Serv Res. 2003;38(6):1819–1842. 11. Nepomnyaschy L. Socioeconomic gradients in infant health across race and ethnicity. Matern Child Health J. 2009;13(6):720–731. 12. Organisation for Economic Co-Operation and Development. Health at a glance 2013: OECD indicators. Available at: http://dx.doi.org/10.1787/health_glance2013-en. Accessed December 23, 2015. 13. Organisation for Economic Co-Operation and Development. OECD factbook 2014: economic, environmental and social statistics. Available at: http://www. oecd-ilibrary.org/economics/oecd-factbook2014_factbook-2014-en. Accessed December 23, 2015. 14. Central Intelligence Agency. The world factbook: 2015. Available at: https://www.cia.gov/library/ publications/the-world-factbook/fields/2075.html. Accessed December 23, 2015.
CONTRIBUTORS
15. Pickett KE, Wilkinson RG. Income inequality and health: a causal review. Soc Sci Med. 2015;128:316–326.
M. L. Martinson conceived the study, designed and conducted all analyses, and wrote the article. N. E. Reichman contributed to the conception of the article, the interpretation of the findings, and the writing of the article.
16. Bethel J, Green J, Kalton G, Nord C. Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), Sampling. Washington, DC: US Department of Education, National Center for Education Statistics; 2005.
ACKNOWLEDGMENTS Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant (R24 HD042828) to the Center for Studies in Demography & Ecology at the University of Washington.
HUMAN PARTICIPANT PROTECTION No protocol approval was needed for this study because secondary data were used and no human participants were involved.
REFERENCES
17. Snow K, Thalji L, Derecho A, et al. User’s Manual for the ECLS-B Longitudinal 9-Month–Preschool Restricted-Use Data File and Electronic Codebook. Washington, DC: US Department of Education, National Center for Education Statistics; 2007. 18. Plewis I, Calderwood L, Hawkes D, Hughes G, Joshi H. Millennium Cohort Study: Technical Report on Sampling. 3rd ed. London, England: Institute of Education; 2004. 19. Soloff C, Lawrence D, Misson S, Johnstone R. LSAC Technical Paper No. 3: Wave 1 Weighting and Non-Response. Melbourne, Victoria, Australia: Australian Institute of Family Studies; 2006.
1. Case A, Lubotsky D, Paxson C. Economic status and health in childhood: the origins of the gradient. Am Econ Rev. 2002;92(5):1308–1334.
20. Longitudinal Study of Australian Children: An Australian Government Initiative Data User Guide. Melbourne, Victoria, Australia: Australian Institute of Family Studies; 2009.
2. Currie J, Stabile M. Socioeconomic status and child health: why is the relationship stronger for older children? Am Econ Rev. 2003;93(5):1813–1823.
21. National Study of Children and Youth: Overview of Survey Instruments Cycle 3. Ottawa, Ontario, Canada: Statistics Canada; 1999.
3. Currie A, Shields MA, Price SW. The child health/ family income gradient: evidence from England. J Health Econ. 2007;26(2):213–232.
22. National Study of Children and Youth: Overview of Survey Instruments Cycle 4. Ottawa, Ontario, Canada: Statistics Canada; 2001.
4. Case A, Lee D, Paxson C. The income gradient in children’s health: a comment on Currie, Shields and Wheatley Price. J Health Econ. 2008;27(3):801–807.
23. McCormick MC, Brooks-Gunn J. Concurrent child health status and maternal recall of events in infancy. Pediatrics. 1999;104(5):1176–1181.
5. Khanam R, Nghiem HS, Connelly LB. Child health and the income gradient: evidence from Australia. J Health Econ. 2009;28(4):805–817.
24. O’Sullivan JJ, Pearce MS, Parker L. Parental recall of birth weight: how accurate is it? Arch Dis Child. 2000;82 (3):202–203.
6. Banks J, Marmot M, Oldfield Z, Smith JP. Disease and disadvantage in the United States and in England. JAMA. 2006;295(17):2037–2045.
25. Organisation for Economic Co-Operation and Development. What are equivalence scales? Available at: http://www.oecd.org/eco/growth/OECD-NoteEquivalenceScales.pdf. Accessed December 23, 2015.
7. Martinson ML. Income inequality in health at all ages: a comparison of the United States and England. Am J Public Health. 2012;102(11):2049–2056. 8. Reichman NE. Low birth weight and school readiness. Future Child. 2005;15(1):91–116.
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Research
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27. Choi KH, Tienda M, Cobb-Clark D, Sinning M. Immigration and status exchange in Australia and the United States. Res Soc Stratif Mobil. 2012;30(1):49–62. 28. Washbrook E, Waldfogel J, Bradbury B, Corak M, Ghanghro AA. The development of young children of immigrants in Australia, Canada, the United Kingdom, and the United States. Child Dev. 2012;83(5):1591–1607. 29. US Department of Health and Human Services. The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta, GA: Centers for Disease Control and Prevention; 2004. 30. Teitler JO, Reichman NE, Nepomnyaschy L, Martinson ML. A cross-national comparison of racial and ethnic disparities in low birth weight in the United States and England. Pediatrics. 2007;120(5):e1182–e1189. 31. Australian Bureau of Statistics. Census of Population and Housing, 2001. Available at: http://www.abs.gov.au/AUSSTATS/abs@. nsf/bb8db737e2af84b8ca2571780015701e/ af5129cb50e07099ca2570eb0082e462!OpenDocument. Accessed December 23, 2015. 32. Stata: Release 11. College Station, TX: StataCorp LP; 2013. 33. SAS, Version 9.4. Cary, NC: SAS Institute Inc; 2013. 34. Reichman NE, Pagnini D. Maternal age and birth outcomes: data from New Jersey. Fam Plann Perspect. 1997;29(6):268–272, 295. 35. Lynch JW, Smith GD, Kaplan GA, House JS. Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ. 2000;320(7243):1200–1204. 36. Marmot M, Wilkinson RG. Psychosocial and material pathways in the relation between income and health: a response to Lynch et al. BMJ. 2001;322(7296): 1233–1236. 37. Martinson ML, Teitler JO, Reichman NE. Health across the life span in the United States and England. Am J Epidemiol. 2011;173(8):858–865. 38. Currie J, Reichman N. Policies to promote child health: introducing the issue. Future Child. 2015;25(1): 3–9. 39. Statistics Canada. Health: low birth weight. Available at: http://www4.hrsdc.gc.ca/[email protected]? iid=4. Accessed December 23, 2015.
26. Pilkauskas N, Martinson ML. Three-generation family households in early childhood: comparisons between the United States, the United Kingdom, and Australia. Demogr Res. 2014;30:1639–1652.
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