Several empirical studies have documented the effects of residential segregation on health inequalities between the US African-American and white populations. However, the majority of such studies have not explained the pathways that link residential segregation and specific health outcomes. This paper presents a conceptual framework of the role that residential segregation may play in the epidemiology of tuberculosis (TB) and other infectious diseases. This is an important issue given the concentration of TB cases among US racial/ethnic minorities and the increasing gap in the incidence of infectious diseases between minorities and the white majority. Segregation may have an indirect effect on the transmission of TB because of its negative impact on the quality of neighborhood environment in segregated communities. Segregation concentrates poverty, overcrowded and dilapidated housing and social disintegration in minority areas, and results in limited access to health care. Furthermore, two dimensions of residential segregation (isolation and concentration) may have direct effects on TB transmission. The isolation of minorities confines TB to segregated areas and prevents transmission to the rest of the population. High-density levels in minority areas increase the probability of transmission within the segregated group. In order to operationalize the above pathways, health researchers may rely on the segregation literature, which has conceptualized various dimensions of residential segregation and proposed ways to measure them. The indirect pathways that link segregation and TB can be captured through exposure indices, which quantify the concentration of risk factors for TB for various racial and ethnic groups. The direct pathways can be captured through the isolation index (which is a proxy for the degree of interaction between the segregated group and the rest of the population) and two proposed measures of density (which are proxies for the likelihood of transmission within the segregated group and from the segregated group to the rest of the population).
This research output has an Altmetric Attention Score of 32. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2025.
All research outputs
#1,543,397
of 34,277,148 outputs
Outputs from Social Science & Medicine
#1,467
of 13,994 outputs
Outputs of similar age
#1,115
of 57,664 outputs
Outputs of similar age from Social Science & Medicine
#3
of 49 outputs
Altmetric has tracked 34,277,148 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,994 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 57,664 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.
