Screening high-risk clusters for developing birth defects in mothers in Shanxi Province, China: application of latent class cluster analysis

Table 1 Description of eight indicator variables in latent class cluster analysis to identify latent clusters^a

Indicator variable	Risk factors^b	Min^c	Max^c
Maternal delivery age	Maternal delivery age	14	55
Genetic factors	Parental consanguinity	0	3
	Birth defects in immediate family members
	Birth defects in previous infants
Medical history	Hepatitis	0	6
	Anemia
	Epilepsy
	Heart disease
	Diabetes
	Thyroid disease
	Spontaneous abortion
	Other
Nutrition and folic acid	Meat deficiency	0	3
	Vegetable deficiency
	Folic acid deficiency
Maternal illness	Fever	0	6
	Cold
	Threatened abortion
	Reproductive tract infections
	Hyperemesis gravidarum
	Rash and fever
	Other
Drug use	Cold medicines	0	7
	Antiemetic
	Antibiotic
	Antiepileptic
	Sedative
	Contraceptive
	Abortion prevention agent
	Other
Environmental risk factors	Pesticides	0	6
	Chemical fertilizers
	X-rays
	Computer use
	Pets
	Pollution source in area of residence
Unhealthy lifestyle	Periconceptional smoking	0	4
	Family member smoking
	Periconceptional drinking
	Family member drinking

^aSeries of risk factors were summed as a total risk factor score for each indicator variable
^bAll risk factors were transformed into 0/1 variables: 0 = No, 1 = Yes
^cMin-max values for each indicator variable

ISSN: 1471-2393