[Evaluation of maternal parameters as risk factors for premature birth (individual and combined effects)].
OBJECTIVE
We aimed to examine the individual and combined effects of nine maternal parameters (biological, medical, and social) on rates of prematurity. Our objective was to provide obstetricians with a way of screening women for likely premature deliveries.


METHODS
We conducted a retrospective analysis on the data of about 2.3 million pregnancies taken from the German perinatal statistics of 1995-2000. Rates of prematurity were calculated with single and multi-dimensional analyses on the basis of nine maternal parameters (age, weight, height, number of previous live births, stillbirths, miscarriages and terminations of pregnancy, smoking status, previous premature delivery). The following combinations of parameters were investigated in particular: rates of prematurity according to the number of previous stillbirths, miscarriages, and terminations; rates of prematurity according to the number of previous live births and maternal age, height and weight. We also included daily cigarette consumption and previous premature deliveries in our analyses.


RESULTS
The rate of prematurity (< or =36 weeks of gestation) in our population was 7.0%; the rate of moderately early premature deliveries (32-36 weeks) was 5.9%, and the rate of very early premature deliveries (< or =31 weeks) was 1.1%. Our multi-dimensional analyses revealed rates of prematurity (< or =36 weeks) between 5.1% and 27.5% depending on the combination of parameters. We found the highest rate of prematurity of 27.5% in women with the following combination of parameters: > or =1 stillbirth, > or =2 terminations of pregnancy and > or =2 miscarriages. A rather high risk of premature delivery (>11%) was also found for elderly (> or =40 years) grand multiparous women as well as small (< or =155 cm) and slim women (< or =45 kg).


CONCLUSIONS
We have shown that certain combinations of maternal parameters are associated with a high risk of premature deliveries (>10%). The risk table that we present here may assist in predicting premature delivery.
Voigt
M
M
Institut für Perinatale Auxologie am Klinikum Südstadt, Rostock. manfred.voigt@kliniksued-rostock.de
Briese
V
V
Pietzner
V
V
Kirchengast
S
S
Schneider
K T M
KT
Straube
S
S
Jorch
G
G
D000028:Abortion, Induced / Q000706:statistics & numerical data*; D000022:Abortion, Spontaneous / Q000453:epidemiology*; D017677:Age Distribution; D001835:Body Weight; D015897:Comorbidity; D005260:Female; D005858:Germany / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D011247:Pregnancy; D047928:Premature Birth / Q000453:epidemiology*; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*