Sociodemographic distribution of gonorrhea incidence: implications for prevention and behavioral research.

Rice, Roselyn J.; Roberts, Pacita L.; Handsfield, H. Hunter; Holmes, King K.

doi:10.2105/ajph.81.10.1252

Cited by 109 publications

(48 citation statements)

References 8 publications

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“…26 Moreover, spatial distance between partners in core gonorrhoea areas is shorter than those in non-core zones. 13 Barlow et al showed a similar high level of assortative mixing in heterosexual patients attending a large London GUM clinic when the country of birth of the parents of the index patients is taken into account. 28 The geoclustering of chlamydia in our study, though somewhat less than that observed for gonorrhoea was remarkable.…”

Section: Figure 1 Prevalence Of Infection By Chlamydia Trachomatis (Lmentioning

confidence: 87%

Geomapping of chlamydia and gonorrhoea in Birmingham

Shahmanesh

Gayed²,

Ashcroft³

et al. 2000

Sexually Transmitted Infections

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Objective: To investigate if the core population hypothesis is applicable to patients with genital chlamydia infections. Design: Retrospective cross sectional study. Setting: Two genitourinary medicine (GUM) clinics in the city of Birmingham and eight adjacent clinics. Subjects: All patients with chlamydia (n = 665) or gonorrhoea (n = 584) attending between 1 October 1995 and 30 September 1996 with a postcode within the Birmingham health district. Controls were 727 patients seen in the same period with no infection. Methods: Postcodes were used to calculate population prevalence rates per 100 000 aged 15-65 in the 39 wards of the city and to estimate the socioeconomic status using the Super Profile (SP). Ethnic specific rates were also calculated. Data were obtained on gonorrhoea and chlamydia isolation from all the major laboratories of the city over the same time period. Results: GUM clinic attenders accounted for 67.6% and 82.5% of all chlamydia and gonorrhoea isolates reported by the laboratories and that were available for our epidemiological analysis. Both infections were more common in men and in black ethnic groups. However, patients with gonorrhoea only infection were more likely to be of black ethnicity than those with chlamydia only infection (p = 0.0001) and to have diVerent SP distribution (p = 0.0001). On logistic regression age <20 years, male sex, black ethnicity, and living in neighbourhoods with SP J ("have nots") were predictive of both infections compared with controls. Overall chlamydia and gonorrhoea prevalence rates were 129 and 98.4 per 10 5 respectively. Corresponding rates for whites was 64.7 and 37.2 and for black ethnic groups 1105 and 1183 per 10 5 of each ethnic group. Eight adjacent wards accounted for 41% of the chlamydia and 66.5% of the gonorrhoea. Conclusion: In a large urban setting patients attending GUM clinics with chlamydia belong to core population groups with similar, but not identical, sociodemographic characteristics to patients with gonorrhoea infection. (Sex Transm Inf 2000;76:268-272)

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Section: Figure 1 Prevalence Of Infection By Chlamydia Trachomatis (Lmentioning

confidence: 87%

Geomapping of chlamydia and gonorrhoea in Birmingham

Shahmanesh

Gayed²,

Ashcroft³

et al. 2000

Sexually Transmitted Infections

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“…While we were unable to determine if this association was truly contextual, and we did not find any support for the hypotheses that neighborhood joblessness and the ratio of men to women play important roles in determining sexual network position in this sample, our results suggest that the well-documented association between poverty and STI rates may operate through sexual network structure. [1][2][3][4][5][6]8 Further study of this possible mechanism should attempt to confirm these results in a larger sample, distinguish between contextual and compositional effects, and further elucidate how neighborhood socioeconomic environment may shape network structure. …”

Section: Discussionmentioning

confidence: 99%

“…This variation has been found to be strongly associated with various features of the socioeconomic environment, including income, unemployment, and education, [1][2][3][4][5] family structure, 6,7 community physical disorder, 1 racial/ethnic composition, 3,4,7 social capital, 5,8 racial/ethnic income inequalities, 6 and racial/ethnic residential segregation. 6 In particular, poor neighborhoods with high proportions of African American residents suffer from disproportionately high sexually transmitted infection (STI) rates.…”

Section: Introductionmentioning

confidence: 99%

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Neighborhood Socioeconomic Environment and Sexual Network Position

et al. 2010

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Rates of sexually transmitted infections (STIs) are strongly associated with neighborhood poverty; however, the mechanisms responsible for this association remain unclear. Using a population-based study of sexual networks among urban African American adolescents, we tested the hypothesis that poverty, unemployment, and the sex ratio drive STI rates by affecting sexual network structure. Participants were categorized as being in one of three network positions that had previously been found to be strongly linked to infection with chlamydia and gonorrhea: being in a confirmed dyad (i.e., a monogamous pair), being connected to a larger network through one partner, and being in the center of a larger network. We found that only poverty was statistically significantly associated with sexual network position. Residing in the poorest third of neighborhoods was associated with 85% decreased odds of being in confirmed dyads. There was no association of sexual network position with neighborhood employment. Living in a neighborhood with an unequal number of young men and women appeared to be associated with a higher likelihood of being in a confirmed dyad; however, the differences were not statistically significant. These results suggest that poverty may impact STI rates by shaping sexual network structure, but we did not find any evidence that this association operates through unemployment or the sex ratio.

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“…[1][2][3][4][5][6][7][8] However, STIs are not uniformly distributed in the population, demonstrated amply in geographic analyses of STI incidence, which have shown different incidence rates in different subpopulations, with the highest rates occurring in poor, inner-city, densely populated, contiguous census tracts. [9][10][11][12][13] Therefore, cataloging risk behavior and demographic and socioeconomic characteristics has not provided adequate descriptions of STI risk. 11,[14][15][16] A more convincing explanation has been the hypothesis developed mathematically by disease ecologists that a small proportion of the population (core groups) who have high rates of STI and partner changes contribute disproportionately to STI transmission.…”

Section: Introductionmentioning

confidence: 99%