Multivariate logistic regression analysis and preventive health measures for children with type 1 diabetes
10.3969/j.issn.1006-2483.2020.01.032
- VernacularTitle:儿童1型糖尿病多因素logistic回归分析及预防保健措施研究
- Author:
Yijie ZHU
1
,
2
,
3
;
Xiaojun WANG
4
,
5
;
Xiaoning FU
1
,
2
,
3
;
Peining YANG
1
,
2
,
3
;
Chunhong CAO
1
,
2
,
3
Author Information
1. Department of Pediatrics, the Third Hospital of Xi'
2. an, Xi'
3. an 710016, China
4. Department of Internal Medicine, Red Cross Hospital, Lianhu District, Xi'
5. an 710002, China
- Publication Type:Journal Article
- Keywords:
Children with type 1 diabetes;
Multivariate logistic regression analysis;
Preventive care
- From:
Journal of Public Health and Preventive Medicine
2020;31(1):138-141
- CountryChina
- Language:Chinese
-
Abstract:
Objective To study and analyze the risk factors in children with type 1 diabetes and formulate preventive health measures. Methods A total of 112 children with type 1 diabetes treated in our hospital from January 2017 to October 2019 were selected as the type 1 diabetes group, and 50 healthy children who underwent physical examination during the same period were selected as the control group. Multifactor logistic regression analysis was used to analyze predisposing factors of type 1 diabetes in children, and preventive health measures was proposed. Results The results of multivariate logistic regression analysis indicated that maternal age, passive smoking during pregnancy, milk feeding time, and children's respiratory infections were independent risk factors for children with type 1 diabetes (OR: 6404, 6.903, 6.417, 8.256, P <0.05). Conclusion Maternal age, passive smoking during pregnancy, milk addition time, and children's respiratory infections were independent risk factors for children with type 1 diabetes. Strengthening health education, breastfeeding as soon as possible, and preventing respiratory infections can help reduce the incidence of children with type 1 diabetes.
