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Register based monitoring shows decreasing socioeconomic differences in Finnish perinatal health
Abstract
Study objective: Several studies on differences in infant outcome by socioeconomic position have been done, but these have usually been based on ad hoc data linkages. The aim of this paper was to investigate whether socioeconomic differences in perinatal health in Finland could be regularly monitored using routinely collected data from one single register. Design and setting: Since October 1990, the Finnish Medical Birth Register (MBR) has included data on maternal occupation. A special computer program that converted the occupation name into an occupational code and into a socioeconomic position was prepared. Perinatal health was measured with five different indicators. The Finnish MBR data for years 1991 to 1999 (n=565 863 newborns) were used in the study. The study period was divided into three, three year periods to study time trends. Results: An occupational code was derived for 95% of women, but it was not possible to define a socioeconomic position for 22% of women, including, for example, students and housewives (the group “Others”). For the rest, the data showed socioeconomic differences in all perinatal health indicators. Maternal smoking explained up to half of the excess risk for adverse perinatal outcome in the lowest socioeconomic group. The socioeconomic differences narrowed during the 1990s: infant outcome improved in the lowest socioeconomic group, but remained at the same level or even deteriorated in other groups. When comparing the lowest group with the highest group, the odds ratios (OR) adjusted for maternal background characteristics at least halved for prematurity (from 1.32 (95% confidence intervals 1.24 to 1.43) in 1991–1993 to 1.16 (1.08 to 1.25) in 1997–1999), for low birth weight (from 1.49 (1.36 to 1.63) to 1.25 (1.17 to 1.40)), and for perinatal mortality (from 1.79 (1.44 to 2.21) to 1.33 (1.07 to 1.66)). Conclusions: Social inequality in perinatal health outcomes exists in Finland, but seems to have diminished in the 1990s. These data showed that routinely collected birth register data provide a good source for studies on socioeconomic health differences in the perinatal period, but that uncertainty, mainly attributable to the large group of women with difficult to classify socioeconomic status, remains.
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“Six separate individual level measures were used; maternal education was the most frequent (n = 7) [33, 34, 46, 47, 49–51], followed by occupation (each n = 3) [43, 48, 52], two used income [35, 45], two used different composite measures [40, 54], and one used perceived lack of time and money [41].”
From Mediators of socioeconomic inequalities in preterm birth: a systematic review (2022) · cites this paper as [52]
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“The temporal nature of measurement of exposure and outcome was unclear in eight studies[33, 34, 36, 37, 48, 52–54].”
From Mediators of socioeconomic inequalities in preterm birth: a systematic review (2022) · cites this paper as [52]
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“Of the cross-sectional studies, three showed low risk of bias, but the others showed potential selection bias (1/8) [52] and response bias (4/8) [37, 39, 41, 45].”
From Mediators of socioeconomic inequalities in preterm birth: a systematic review (2022) · cites this paper as [52]
In the citing paper
“nine explained measurement of preterm birth inadequately [34, 36, 38, 39, 44, 48, 51, 52, 54].”
From Mediators of socioeconomic inequalities in preterm birth: a systematic review (2022) · cites this paper as [52]
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“Two large, lower quality studies (n = 400,752 and n = 548,913) found proportion eliminated was over 40% [52, 53].”
From Mediators of socioeconomic inequalities in preterm birth: a systematic review (2022) · cites this paper as [52]
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Cited by
Mediators of socioeconomic inequalities in preterm birth: a systematic review
McHale, P., Maudsley, G., Pennington, A., Schlüter, D. K., Barr, B., Paranjothy, S., & Taylor-Robinson, D. (2022) · BMC Public Health · doi:10.1186/s12889-022-13438-9 · Cited by 89
Smoking during Pregnancy and Risk of Autism Spectrum Disorder in a Finnish National Birth Cohort
Tran, P. L., Lehti, V., Lampi, K. M., Helenius, H., Suominen, A., Gissler, M., Brown, A. S., & Sourander, A. (2013) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12043 · Cited by 77
Self-citationExplaining educational inequalities in preterm birth: the generation r study
Jansen, P. W., Tiemeier, H., Jaddoe, V. W. V., Hofman, A., Steegers, E. A. P., Verhulst, F. C., Mackenbach, J. P., & Raat, H. (2009) · Archives of Disease in Childhood - Fetal and Neonatal Edition · doi:10.1136/adc.2007.136945 · Cited by 74
Heikkilä, K., Pulakka, A., Metsälä, J., Alenius, S., Hovi, P., Gissler, M., Sandin, S., & Kajantie, E. (2021) · PLOS ONE · doi:10.1371/journal.pone.0261952 · Cited by 33
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Metadata
- Authors
- Gissler, M., Meriläinen, J., Vuori, E., & Hemminki, E.
- Venue
- Journal of Epidemiology and Community Health
- Publisher
- BMJ
- Published
- 2003-06
- Volume
- 57
- Issue
- 6
- Pages
- 433-439
- ISSN
- 0143-005X
- 1470-2738
- Cited by
- 82
- References
- 0
- Language
- en
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