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Table 2 Factors related to receiving HIV education for migrants in different regions, pooled Migrants Population Dynamic Monitoring Survey Data 2014–2015

From: Age and regional disparity in HIV education among migrants in China: migrants population dynamic monitoring survey, 2014–2015

 

Model 1

Model 2

Model 3

Model 4

 

OR (CI)

P

OR (CI)

P

OR (CI)

P

OR (CI)

P

Age

.990 (.989–.990)

.000

.990 (.990–.991)

.000

.990 (.990–.991)

.000

.990 (.990–.991)

.000

Region

 East-coast

1.187 (1.159–1.216)

.000

1.217 (1.187–1.247)

.000

1.228 (1.195–1.261)

.000

1.241 (1.208–1.275)

.000

 Central

1.438 (1.400–1.477)

.000

1.349 (1.313–1.386)

.000

1.328 (1.292–1.365)

.000

1.339 (1.302–1.376)

.000

 Northwest

1.138 (1.105–1.172)

.000

1.110 (1.077–1.143)

.000

1.159 (1.125–1.194)

.000

1.174 (1.139–1.209)

.000

 Southwest

3.001 (2.917–3.087)

.000

2.959 (2.874–3.044)

.000

1.977 (1.889–2.066)

.000

2.004 (1.915–2.094)

.000

 West-Tibet

1.717 (1.655–1.781)

.000

1.672 (1.610–1.735)

.000

1.526 (1.467–1.585)

.000

1.556 (1.496–1.617)

.000

 West-Uyghur

3.862 (3.705–4.024)

.000

4.112 (3.939–4.285)

.000

2.479 (2.329–2.629)

.000

2.531 (2.378–2.684)

.000

 Northeast

  1. *Model 1 included age and region;
  2. Model 2 added gender, ethnicity, marital status, education level, monthly income, health record status, and health insurance status;
  3. Model 3 added prevalence of HIV (total number per 100,000 population), density of medical professionals (total number per 1000 population), and density of migration (total number per 100,000 population);
  4. Model 4 added reasons of migration, length of migration, type of household, and whether or not have long-term living preference
  5. **Model 1: P = 0.000 Cox & Snell R2 = 0.035; Model 2: P = 0.000 Cox & Snell R2 = 0.061; Model 3: P = 0.000 Cox & Snell R2 = 0.062; Model 4: P = 0.000 Cox & Snell R2 = 0.063;