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O2-S5.01 Bonding, bridging, linking: exploring relationship between social capital and migrants' HIV risk behaviour at destination

2011· article· en· W2314358289 on OpenAlexaff
Dhirendra Kumar Singh, James Blanchard, John O’Neil, Javier Mignone, Stephen Moses

Bibliographic record

VenueSexually Transmitted Infections · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsSimon Fraser UniversityUniversity of Manitoba
Fundersnot available
KeywordsCasualCondomSocial capitalDemographyMedicineImmigrationFemale sexHuman immunodeficiency virus (HIV)Demographic economicsGeographySociologyFamily medicinePolitical scienceSocial science

Abstract

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Background A multidimensional construct of social capital was employed to understand the relationship between social capital and migrants' HIV risk at destination place. Methods The study was undertaken among Rajasthani migrants of age 18 and above in Mumbai and Ahmedabad in India to collect data from 1598 migrants through survey method and from 93 migrants through qualitative methods from January to June 2007. Social capital was measured in terms of three domains: bonding, bridging and linking. HIV risk had three measures: having casual partner in last 12 months in the city; sex with a sex worker in the city in last 12 months; and no or inconsistent condom use with a sex worker in last 12 months. Results Migrants had substantial risk behaviour at destination: 385 respondents (24.1%) reported having one or more casual partners; 218 migrants (13.6%) had had sex with a sex worker; and 123 respondents (7.7%) reported no or inconsistent condom use with a sex worker in the last 12 months in the city. Migrants reported higher risk in Ahmedabad compared to Mumbai for all the three risk measures: 251 (31.6%) vs 134 (16.7%) reported casual partners; 138 (17.4%) vs 80 (10%) reported having had sex with a sex worker; and 96 (12.1%) vs 27 (3.4%). Bonding and linking domains of social capital had higher values for migrants in Ahmedabad than Mumbai. Bridging social capital was higher in migrants in Mumbai as compared to migrants in Ahmedabad. All the components of bridging social capital had higher values for migrants in Mumbai than Ahmedabad. Bonding and linking social capital behaved differently in Mumbai and Ahmedabad. In Mumbai, migrants had lower HIV risk if they had high linking social capital and had higher risk if they had high bonding social capital. In Ahmedabad, bonding social capital at high levels was associated with lower risk behaviour while linking social capital at high level was associated with higher risk. On the other hand, high levels of bridging social capital and components of bridging social capital were protective of HIV risk in both the cities see Abstract O2-S5.01 table 1. Abstract O2-S5.01 Table 1 Multivariate relations of HIV risk with social capital (components) in Mumbai and Ahmedabad Scale Casual partners Sex with commercial sex worker Condom use with CSW Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 OR (CI) AOR (CI) OR (CI) AOR (CI) OR (CI) AOR (CI) Mumbai BO_communitaraian sense (low) 0.53 (0.32 to 0.86) 0.78 (NS) 0.31 (0.17 to 0.60) 0.47 (0.24 to 0.92) BR_particiaption (low) 1.97 (1.19 to 3.27) 1.90 (1.13 to 3.19) 1.60 (NS) 1.71 (NS) LI_personal trust in services (low) 2.33 (1.31 to 4.15) 2.39 (1.29 to 4.44) 2.45 (1.08 to 5.52) 2.84 (1.23 to 6.54) LI_reciprocal trusting relations with services (low) 2.18 (1.11 to 4.28) 2.96 (1.11 to 7.83) 3.10 (1.16 to 8.31) Married or not (ref: married) 0.16 (0.04 to 0.69) No. of working days in a month (ref: low) 3.83 (1.31 to 11.2) Income (ref: low) 1.67 (1.25 to 2.23) 1.84 (1.26 to 2.67) Income steady/fluctuating (ref: fluctuating) 1.93 (1.08 to 3.45) Mode of salary receipt (daily) 1.39 (1.07 to 1.82) Ahmedabad BO_differences in community (low) 2.34 (1.34 to 4.11) 4.65 (2.39 to 9.02) 6.71 (3.31 to 13.6) BO_personal trust and help (low) 0.36 (0.23 to 0.57) 0.36 (0.23 to 0.58) 0.37 (0.19 to 0.72) 0.30 (0.15 to 0.62) 0.29 (0.14 to 0.61) 0.28 (0.13 to 0.64) BO_generalized trust & help (low) 1.96 (1.34 to 2.87) 2.03 (1.36 to 3.03) 2.68 (1.59 to 4.51) 3.35 (1.88 to 5.98) 3.38 (1.83 to 6.23) 4.04 (2.14 to 7.62) BR_generalized trust & help (low) 2.00 (1.17 to 3.42) 1.90 (1.07 to 3.37) 2.51 (1.26 to 4.99) 2.61 (1.27 to 5.37) Living with wife or alone (ref: with wife) 1.77 (1.45 to 2.17) 2.42 (1.76 to 3.33) 2.50 (1.73 to 3.61) Nature of job (ref: daily wage) 1.49 (1.21 to 1.82) No. of working days in a month (ref: low) 2.77 (1.12 to 6.88) Income (ref: low) 1.66 (1.14 to 2.43) 1.90 (1.22 to 2.96) Income steady or fluctuating (ref: steady) 1.78 (1.26 to 2.51) 1.91 (1.18 to 3.10) 2.31 (1.29 to 4.14) Mode of salary receipt (daily) 68 (0.48 to 0.96) 0.61 (0.43 to 0.88) The table has results from the final logistic regression models. The low, medium and high category of social capital were treated as categorical categories and high social capital category for each component was selected as the reference category. Model 1: Social Capital Domains Only; Model 2: Social Capital Domains and Co-factors. Only significant associations shown here. High value of social capital measures is the reference category. BO, Bonding social capital; BR, Bridging Social Capital; LI, Linking social capital. Conclusion This study was able to explore the mediating effect of social capital on migrants' HIV risk at the domain levels. Bridging kind of social capital with the host community and migrants from other states was associated with lower HIV risk behaviour. Further research should be undertaken in different epidemiological contexts to validate the findings of this study.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.287
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2011
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