| Literature DB >> 31868092 |
Mengdi Guo1, Zheng Zhu2, Tingyue Dong3, Hong Mi1, Bei Wu4.
Abstract
Chronic diseases have become serious threats to public health in China; the risk is particularly high for internal migrants. Chronic disease education is a key to the prevention and control of chronic diseases for such population. The national population-based Migrants Population Dynamic Monitoring Survey (MPSMA) was used to examine the current status and delivery methods of chronic disease education among internal migrants, from both provincial level and individual's level. The study population included 402 587 internal migrants. Multilevel logistic regression was used to investigate factors that were related to chronic diseases education. In total, only 33.9% of the participants received chronic disease education. In the final model, parameter estimates on key variables from both individual and provincial level were significant (P < .001). Participants from provinces with higher level of health care resources and lower density of internal migrants were more likely to receive chronic disease education. The percentage and methods of receiving education varied across different age groups. This study suggests that future chronic disease education in China need to be more focused on areas with high density of internal migrants and younger internal migrants with low level of education and income. Attention should be paid to use tailored education methods to different populations.Entities:
Keywords: chronic disease; health education; health services accessibility; internal migrants; secondary data analysis
Mesh:
Year: 2019 PMID: 31868092 PMCID: PMC6927201 DOI: 10.1177/0046958019895897
Source DB: PubMed Journal: Inquiry ISSN: 0046-9580 Impact factor: 1.730
Demographic Characteristics and Outcomes Among Migrants, Pooled Migrants Population Dynamic Monitoring Survey Data 2014–2015 (N = 402 587).
| Variables | Percentage/Mean (SD) |
|---|---|
| Female (%) | 48.6 |
| Age, mean (SE) | 35.4 (9.7) |
| Marital status (%) | |
| Married | 81.4 |
| Single | 19.6 |
| Educational attainment (%) | |
| <Middle school | 65.8 |
| High school or equivalent | 21.0 |
| College | 12.8 |
| >College degree | 0.4 |
| Monthly income, mean (SD) | 7075.6 (10 160.2) |
| Having health record (%) | 26.1 |
| Having urban resident medical basic insurance (%) | 5.7 |
| Long-term residence inclination (%) | |
| Yes | 56.2 |
| No or unsure | 43.8 |
| Length of migration, mean (SD) | 5.61 (4.89) |
| Reason of migration (%) | |
| Working or studying | 89.8 |
| Others | 10.5 |
| Type of household (%) | |
| Rural | 84.0 |
| Urban | 16.0 |
| Received chronic disease education (%) | 33.9 |
Figure 1.Rate of internal migrants receiving chronic disease education among 31 provinces in China.
Figure 2.(a) Education rate of chronic disease by age among migrants, pooled Migrants Population Dynamic Monitoring Survey Data 2014-2015. (b) Frequencies of using various approaches of receiving chronic diseases by age among migrants, pooled Migrants Population Dynamic Monitoring Survey Data 2014-2015.
Figure 3.(a) Rate of chronic disease education among internal migrants and number of health care professionals per 1000 population in 31 provinces. (b) Rate of chronic disease education among internal migrants and density of internal migrants in 31 provinces.
Fixed-Effect and Random-Effect Estimates for Models of Receiving CHRONIC DISEASES Education, Pooled Migrants Population Dynamic Monitoring Survey Data 2014–2015.
| Model 1 | Model 2 | Model 3 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | CI |
| OR | CI |
| OR | CI |
| |
| Fixed effects | |||||||||
| Intercept, γ00 | 0.514 | 0.510, 0.517 | .000 | 0.237 | 0.223, 0.252 | .000 | 0.169 | 0.158, 0.181 | .000 |
| Individual level | |||||||||
| Age, β1 | 1.011 | 1.010, 1.012 | .000 | 1.010 | 1.009, 1.011 | .000 | |||
| Female, β2 | 0.987 | 0.973, 1.001 | .062 | 0.982 | 0.968, 0.995 | .000 | |||
| Married, β3 | 1.124 | 0.874, 0.908 | .000 | 1.116 | 0.879, 0.914 | .000 | |||
| Educational level, β4 | 1.219 | 1.203, 1.234 | .000 | 1.214 | 1.199, 1.230 | .000 | |||
| Monthly income, β5 | 1.067 | 1.059, 1.074 | .000 | 1.078 | 1.071, 1.086 | .000 | |||
| Having health record, β6 | 2.215 | 2.183, 2.248 | .000 | 2.206 | 2.174, 2.239 | .000 | |||
| Having basic medical insurance, β7 | 1.222 | 0.797, 0.841 | .000 | 1.214 | 0.802, 0.846 | .000 | |||
| Rural household, β8 | 0.917 | 0.899, 0.935 | .000 | 0.937 | 0.918, 0.956 | .000 | |||
| Having long-term preference more than 5 years, β9 | 1.266 | 1.248, 1.285 | .000 | 1.250 | 1.232, 1.268 | .000 | |||
| Migration duration, β10 | 0.939 | 0.933, 0.945 | .000 | 0.934 | 0.927, 0.940 | .000 | |||
| Migrate for working or studying, β11 | 1.020 | 0.961, 1.001 | .058 | 1.036 | 0.941, 0.981 | .000 | |||
| Province level | |||||||||
| Age structure of migrants (number of elderly more than 60 years old per 100 population) γ01 | 1.086 | 1.077, 1.094 | .000 | ||||||
| Density of health care professionals (total number per 1000 population), γ02 | 1.061 | 1.052, 1.070 | .000 | ||||||
| Density of migrants (total number per 100 000), γ03 | 0.626 | 0.581, 0.676 | .000 | ||||||
| Random effects | |||||||||
| Intercept variance, | 0.000 | 0.044 | 0.061 | ||||||
| Level 1 variance, | 3.290 | 3.290 | 3.290 | ||||||
| −2LL | 572 429.6 | 571 999.9 | 571 849.0 | ||||||
Note. OR = odds ratio; CI = confidence interval; LL = log-likelihood ratio test.