| Literature DB >> 22131643 |
Tawanchai Jirapramukpitak, Melanie Abas, Trudy Harpham, Martin Prince.
Abstract
Evidence suggests that certain migrant populations are at increased risk of abusive behaviors. It is unclear whether this may also apply to Thai rural-urban migrants, who may experience higher levels of psychosocial adversities than the population at large. The study aims to examine the association between migration status and the history of childhood sexual, physical, and emotional abuse among young Thai people in an urban community. A population-based cross-sectional survey was conducted in Northern Bangkok on a representative sample of 1052 young residents, aged 16-25 years. Data were obtained concerning: 1) exposures-migration (defined as an occasion when a young person, born in a more rural area moves for the first time into Greater Bangkok) and age at migration. 2) outcomes-child abuse experiences were assessed with an anonymous self report adapted from the Conflict Tactics Scales (CTS). There were 8.4%. 16.6% and 56.0% reporting sexual, physical, and emotional abuse, respectively. Forty six percent of adolescents had migrated from rural areas to Bangkok, mostly independently at the age of 15 or after to seek work. Although there were trends towards higher prevalences of the three categories of abuse among early migrants, who moved to Bangkok before the age of 15, being early migrants was independently associated with experiences of physical abuse (OR 1.9 95%CI 1.1-3.2) and emotional abuse (OR 2.0, 95%CI 1.3-3.0) only. Our results suggest that rural-urban migration at an early age may place children at higher risk of physical and emotional abuse. This may have policy implications for the prevention of childhood abuse particularly among young people on the move.Entities:
Year: 2011 PMID: 22131643 PMCID: PMC3212695 DOI: 10.1007/s10896-011-9397-x
Source DB: PubMed Journal: J Fam Violence ISSN: 0885-7482
Results of univariate analysis of migration and sociodemographic factors
| Demographic variables | Type of Migration |
|
| ||
|---|---|---|---|---|---|
| Non-migrant (%) | Migrant (%) | ||||
| Early | Late | ||||
|
|
|
| |||
| Age | |||||
| - 16–19 | 42.9 | 51.6 | 31.8 | 7.20 | 0.0008 |
| - 20–25 | 57.1 | 48.4 | 68.2 | ||
| Sex | |||||
| - Male | 45.4 | 45.2 | 48.3 | 0.31 | 0.73 |
| - Female | 54.6 | 54.8 | 51.7 | ||
| Qualification | |||||
| - No qualification | 0.9 | 2.3 | 0.6 | 3.16 | 0.0005 |
| - Primary (6 years) | 6.9 | 14.8 | 17.8 | ||
| - Secondary (9 years) | 38.5 | 45.6 | 42.0 | ||
| - Higher secondary (12 years) | 37.4 | 24.0 | 28.3 | ||
| - Higher diploma (14 years) | 7.5 | 5.5 | 4.9 | ||
| - University | 8.8 | 7.8 | 6.6 | ||
| Head of household’s education | |||||
| - None/little | 3.3 | 8.8 | 1.9 | 4.68 | <0.0001 |
| - Primary (4 years) | 33.6 | 41.5 | 39.5 | ||
| - Primary (6 years) | 8.7 | 12.9 | 20.4 | ||
| - Secondary (9 years) | 12.8 | 16.6 | 14.8 | ||
| - Secondary (12 years) | 18.6 | 7.4 | 12.6 | ||
| - Higher diploma (14 years) | 9.7 | 5.5 | 2.8 | ||
| - University | 13.3 | 7.4 | 8.1 | ||
Odds ratios for the associations between the three categories of child abuse and potential confounders
| Variable |
| Sexual abuse | Physical abuse | Emotional abuse | |||
|---|---|---|---|---|---|---|---|
| Prevalence | OR(95%CI) | Prevalence | OR(95%CI) | Prevalence | OR(95%CI) | ||
| Age | |||||||
| - 16–19 | 449 | 9.0 | 1 | 19.5 | 1 | 61.0 | 1 |
| - 20–25 | 603 | 7.9 | 0.9(0.5–1.5) | 14.7 | 0.7(0.5–1.0) | 52.6 | 0.7(0.5–0.9)* |
| Sex | |||||||
| - Male | 467 | 10.2 | 1 | 18.9 | 1 | 58.6 | 1 |
| - Female | 585 | 6.7 | 0.6(0.4–1.1) | 14.7 | 0.7(0.5–1.1) | 53.8 | 0.8(0.6–1.1) |
| Education | |||||||
| - 9 years or less | 558 | 8.3 | 1 | 20.4 | 1 | 59.0 | 1 |
| - >9 years | 494 | 8.4 | 1.0(0.6–1.8) | 12.5 | 0.6(0.4–0.8)* | 52.7 | 0.8(0.6–1.0) |
| Head of household’s education | |||||||
| - 6 years or less | 539 | 8.3 | 1 | 18.0 | 1 | 58.0 | 1 |
| - >6 years | 513 | 8.4 | 1.0(0.6–1.8) | 15.1 | 0.8(0.6–1.2) | 53.8 | 0.8(0.6–1.1) |
*p < 0.02
The associations between migration status and child abuse experiences
| Type of Abuse | Type of Migration |
|
| ||
|---|---|---|---|---|---|
| Non-migrant (%) | Migrant (%) | ||||
| Early | Late | ||||
|
|
|
| |||
| Sexual abuse | |||||
| - No | 92.2 | 89.9 | 91.4 | 0.25 | 0.77 |
| - Yes | 7.8 | 10.1 | 8.6 | ||
| Physical abuse | |||||
| - No | 85.9 | 74.7 | 82.6 | 3.98 | 0.02 |
| - Yes | 14.1 | 25.3 | 17.4 | ||
| Emotional abuse | |||||
| - No | 47.0 | 30.3 | 44.7 | 5.30 | 0.005 |
| - Yes | 53.0 | 69.7 | 55.3 | ||
Odds ratios for the association between migration and type of abuse, stratified by gender
| Type of abuse | Male | Female | Crude odds ratio | Adjusted odds ratio | LR test for interaction |
|
|---|---|---|---|---|---|---|
| Emotional | ||||||
| - Early migrant | 2.1(1.1–4.1) | 2.0(1.1–3.4) | 2.0(1.3–3.1) | 2.0(1.3–3.1) | 1.37 | 0.50 |
| - Late migrant | 1.3(0.8–2.1) | 0.9(0.6–1.4) | 1.1(0.8–1.5) | 1.1(0.8–1.5) | ||
| Physical | ||||||
| - Early migrant | 4.0(1.9–8.4) | 1.0(0.5–2.2) | 2.1(1.2–3.5) | 2.1(1.2–3.5) | 9.02 | 0.01 |
| - Late migrant | 1.7(0.9–3.1) | 1.0(0.6–1.7) | 1.3(0.9–1.9) | 1.3(0.8–1.9) | ||
| Sexual | ||||||
| - Early migrant | 1.2(0.4–3.6) | 1.5(0.6–3.8) | 1.3(0.7–2.7) | 1.3(0.7–2.7) | 0.24 | 0.89 |
| - Late migrant | 1.2(0.4–3.2) | 1.0(0.4–2.4) | 1.1(0.6–2.2) | 1.1(0.6–2.2) | ||
The odds ratios following logistic regression for the association between migration status and each of the three types of child abuse, controlling for potential confounders
| Sexual abuse | Physical abuse | Emotional abuse | ||||
|---|---|---|---|---|---|---|
| Early migrant | Late migrant | Early migrant | Late migrant | Early migrant | Late migrant | |
| Model 1 | 1.3 (0.7–2.7) | 1.1(0.6–2.3) | 2.1(1.3–3.5) | 1.3(0.9–1.9) | 2.1(1.4–3.2) | 1.1(0.8–1.5) |
| Model 2 | 1.3 (0.6–2.7) | 1.1(0.6–2.2) | 2.0(1.2–3.4) | 1.3(0.9–2.0) | 2.0(1.3–3.1) | 1.1(0.8–1.5) |
| Model 3 | 1.4 (0.7–2.9) | 1.2(0.6–2.3) | 1.9(1.1–3.2) | 1.2(0.8–1.9) | 2.0(1.3–3.0) | 1.1(0.8–1.5) |
Non-migrant status was the reference category
Model 1—Main effect of migration
Model 2—Main effect of migration, controlling for age, sex
Model 3—Main effect of migration, controlling for age, sex, years of education, head of household’s education