Investigation and study on the epidemiology of gestational diabetes mellitus in Guizhou

Table 3 Analysis of binary logistic regression model of general data affecting the occurrence of gestational diabetes mellitus

Impact factors	Grouping	B	Standard error	Wald	OR	95%CI	P value
Age		0.049	0.008	36.97	1.050	1.034-1.067	< 0.001
Age segment	Less than 35 years old
	≥ 35	1.591	0.131	146.888	4.910	3.796-6.351	< 0.001
Ethnicity	Han
	Minority	-0.251	0.153	2.708	0.885	0.753-0.934	< 0.001
Pre-pregnancy BMI		0.124	0.005	684.835	1.883	1.875-2.192	< 0.001
Work conditions	None
	Yes	3.342	0.159	21.387	3.280	2.705-4.627	< 0.001
Gravidity	1			164.439			< 0.001
	2	0.096	0.094	1.042	1.100	0.916-1.322	0.307
	≥ 3	1.295	0.111	135.59	3.651	2.936-4.541	< 0.001
Education level	Junior-senior high school			439.713			< 0.001
	Technical secondary school and junior college	-0.733	0.105	48.348	0.481	0.391-0.591	< 0.001
	Bachelor degree or above	-3.423	0.163	438.66	0.033	0.024-0.045	< 0.001
Diabetes family medical history	None
	Yes	3.132	0.701	19.938	5.833	5.796-90.612	< 0.001
Previous endocrine history	None
	Yes	1.661	1.002	0.536	0.816	0.074-4.638	0.309

P < 0.05 indicates statistical. The Wald test was used to determine the significance of each variable. Binary logistic regression was used to analyze the impact factors for the occurrence of gestational diabetes mellitus. B: Regression coefficient; OR: Odds ratio; CI: Confidence interval; BMI: Body mass index.