A substantial number of births occurred during the study years at the eight study areas (Table ). The percent of preterm births ranged from 7.0 to 14.3%, and the low birth weight percentage ranged from 4.8 to 11.9%. Baltimore City had the highest while Montgomery County had the lowest outcome proportions of adverse birth outcomes. The proportion of black women delivering singleton births varied across the study areas, from 79.7% in Prince George’s County to 26.0% in Wake County. Michigan had the fewest births to women ≥35 years of age (8.3%) while Montgomery County had the most (31.1%). Maternal education varied by site. Uniformly, the fewest singleton mothers obtained <12 years, and the most obtained >12 years, but the relative percentages differed geographically. Baltimore City had the highest percent who received <12 years (31.7%) compared with 4.1% in Montgomery County. In Wake County 73.5% of women had >12 years of school compared with 33.6% in Michigan.
Tracts had varying population counts, ranging from a mean of 3,009 for Michigan-16 cities to 5,979 in Wake County, NC (Table ). Significant variability was also observed for the census socio-demographic descriptors. On average, Montgomery County, MD, had the wealthiest tracts according to the census characteristics (i.e., 14.6% of the population had income less than $30,000 compared with 51.3% of Baltimore city residents). The three urban study areas—Baltimore City, Philadelphia, and MI-16 cities—were characterized as the “most deprived,” based on these socio-demographic indicators. The Michigan 16-city site appeared to be the poorest according to poverty-related indicators such that, on average, 24.9% lived below the poverty level, and 25.2% were female-headed households with dependent children. Philadelphia had the largest percent of households with no vehicle (34.8%). Prince George’s County, MD, had the lowest percentage of white population (24.4%) compared to Baltimore City, MD, with the highest proportion (75.6%) in these data. Thus, these eight urban and suburban regions demonstrated considerable socio-demographic variability.
Mean (standard deviation) of sociodemographic data of each MODE-PTD study area, Year 2000 U.S. census data
The index resulting from the principal components analysis accounted for 51 to 73% of the total variance in the variables that were included in the eight study areas and 67% of the total variance for the combined all-site neighborhood deprivation index. The second component added 7 to 10% to the explained variance and so was not retained. The higher the score on the standardized deprivation index, the more area-level deprivation associated with the census tract.
Three important patterns emerged from the site specific and all-site first principal component score loadings (Table ). The first was the consistency within each site of variable loadings that comprised the first principal component, which were used to produce the deprivation score with loadings ranging, for example, from 0.22 to 0.40 in Philadelphia. These results suggested that each component contributed almost equally to the neighborhood deprivation index. Second, the component loadings were quite consistent across the study areas; for example, poverty loadings ranged from 0.35 to 0.41, despite significant geographic and socio-demographic variability. The consistency of the loadings across units suggested these variables function similarly across geography, despite meaningful heterogeneity in demographics and economic status. Unemployment, for instance, made as important a contribution to this deprivation index in Philadelphia as it did in Durham County. The third important pattern emerging from these analyses was the consistency of the factor loadings on the all-site deprivation score. The all-site weights were of similar magnitude to each other and to each site’s loadings. The all-site deprivation index represented a weighted average of the component variables from diverse geographic and socioeconomic units, the loadings for which could be reasonably applied to census variables from virtually any area to produce a comparable deprivation index.
Site specific and all-site first principal component deprivation score loadings for each study area
Figure graphically demonstrates the significant socioeconomic heterogeneity in the distribution of the all-site deprivation scores across the eight study areas. Philadelphia had the largest range in deprivation score, ranging from −1.8 to 3.7, followed by Michigan-16 cities. Particularly noteworthy is Montgomery County, with deprivation index values ranging from −1.7 to 0.7, suggesting that this area is relatively not deprived. Along with Montgomery County, most tracts in Maryland (Baltimore and Prince George’s County) and North Carolina (Wake and Durham Counties) were at the affluent end of the all-site deprivation continuum, compared to the three most urban study areas (Michigan-16 cities, Baltimore City, and Philadelphia), which were clearly at the more deprived end of the range.
Box plot of all-site deprivation index by MODE-PTD study area.
Among white women, there was a gradient in the relationship between deprivation and adverse birth outcomes in at least two-thirds of the sites: Larger percentages of LBW (Table ) and PTB (data not shown) occurred at higher levels of deprivation. For instance, Baltimore County, one of the more affluent study areas, had LBW percentages that ranged from 4.0 to 7.6% and PTB percentages that ranged from 6.0 to 9.2%, respectively, in the first to third quartiles of deprivation (no Baltimore County tracts fell into the fourth quartile of all-site deprivation). In a more deprived area these rates were similar; the LBW percentages in the Michigan-16 cities site increased from 3.8 to 7.6% while the PTB percentages increased from 6.1 to 8.8%, respectively. Risk differences indicated the contrast of adverse birth proportions for women living in quartiles four or three compared with those living in the lowest quartile of deprivation. Across the socio-demographically diverse study areas, the relationship between adverse birth outcomes and neighborhood deprivation appeared fairly consistent among white women.
Percentage of white non-Hispanic low birth weight [LBW] (total number of births) and Q4–Q1, Q3–Q1 risk differences [RD] (95% confidence intervals [CI]) in each quartile [Q] of deprivation by MODE-PTD study area
The relationship between deprivation and adverse birth outcomes for black women was slightly less clear (Table ). While the PTB and LBW percentages in the highest quartile of deprivation were consistently large, we found high levels of adverse outcomes throughout the continuum. Among black women delivering singleton infants, we found increasing percentages of LBW associated with increasing deprivation in five of the study areas, even if some of the increases were modest (e.g., Baltimore City’s LBW percentages increased from 12.0 to 14.0% from the second to fourth quartile). In Philadelphia, for instance, the percent LBW ranged from 9.0 to 13.8% in the first compared with fourth quartile. The pattern of association was similar for PTB where, in Durham County, for instance, the percent PTB increased from 11.6 to 17.7% (data not shown). The pattern of increasing proportion PTB with increasing deprivation was observed in six of the study areas. The relationship between deprivation and adverse birth outcomes among black women in these data was not quite as consistent with the hypothesized pattern of monotonically increasing risk.
Percentage of black non-Hispanic low birth weight [LBW] (total number of births) and Q4–Q1, Q3–Q1 risk differences [RD] (95% confidence intervals [CI]) in each quartile [Q] of deprivation by MODE-PTD study area