Human Reproduction, Vol.25, No.4 pp. 1044– 1050, 2010
Advanced Access publication on February 3, 2010 doi:10.1093/humrep/deq004
ORIGINAL ARTICLE Reproductive epidemiology
Parental occupation and risk of smallfor-gestational-age births: a nationwide
epidemiological study in Sweden
X. Li1,4, J. Sundquist 1,2, and K. Sundquist3
1
Center for Primary Health Care Research, Lund University, Malmo, Sweden 2Stanford Prevention Research Center, Stanford University
School of Medicine, CA, USA 3Center for Family and Community Medicine, Karolinska Institutet, Stockholm, Sweden
4
Correspondence address. Tel: þ46-40-391381; Fax: þ46-40-391370; E-mail: [email protected]
Submitted on June 9, 2009; resubmitted on December 28, 2009; accepted on January 6, 2010
background: Although evidence suggests that some occupations may be a risk factor for small-for-gestational age (SGA) birth, associations between a wide range of maternal and paternal occupations and risk of SGA births remain unclear. Our objective was to analyze the
risk of SGA births by parental occupation, including the entire Swedish population of mothers (20 years) and fathers.
methods: We linked nationwide data (1990– 2004) on singletons born to employed mothers to nationwide data on maternal and
paternal occupation and other individual-level variables. Information on parental occupations was obtained from the 1990 census. Approximately 95% of SGA births (calculated using normative data) were defined on the basis of ultrasound. Odds ratios of SGA birth were calculated with 95% confidence intervals. Women and men were analyzed separately.
results: There were 816 310 first singleton live births during the study period, of which 29 603 were SGA events. Families with low
incomes had an increased risk of SGA births. After accounting for maternal age at the infant’s birth, period of birth, family income,
region of residence, marital status and smoking habits, several maternal occupational groups (including ‘mechanics and iron and metalware
workers’ and ‘packers, loaders and warehouse workers’) had a significantly higher risk of SGA birth than the reference group (all women in
the study population). Among paternal occupational groups, only waiters had an increased risk of SGA birth.
conclusions: This large-scale follow-up study shows that maternal occupation affects risk of SGA birth, whereas paternal occupation
does not seem to have an impact on SGA birth. Further studies are required to examine the specific agents in those maternal occupations
that are associated with an increased risk of SGA birth.
Key words: family income / follow-up study / occupational exposure / small for gestational age
Introduction
Small-for-gestational age (SGA) is a term used to describe an infant who
is smaller than expected on the basis of the number of weeks of completed pregnancy and typically refers to an infant who is below the
tenth percentile of length and weight for gestational age (World
Health Organization, 2007). The causes of SGA are still partly
unknown. Some of the known risk factors include a maternal age of
less than 20 or more than 35 years (Zeitlin et al., 2001; Canadian Institute for Health Information, 2009), shorter maternal stature (Clausson
et al., 1998; Thompson et al., 2001), primiparity (Thompson et al.,
2001; Canadian Institute for Health Information, 2009), smoking
(Thompson et al., 2001; Cnattingius, 2004), maternal undernutrition
(Thompson et al., 2001; Hobel and Culhane, 2003), low maternal
BMI (Clausson et al., 1998; Zeitlin et al., 2001), high maternal BMI
(Zeitlin et al., 2001), preexisting hypertension (Thompson et al.,
2001; Canadian Institute for Health Information, 2009), gestational
hypertension (Canadian Institute for Health Information, 2009), preeclampsia (Clausson et al., 1998; Ananth et al., 1999; Thompson
et al., 2001) and vascular lesions (Zeitlin et al., 2001).
Research has also shown that ethnicity is associated with SGA births
(Thompson et al., 2001), as are neighborhood socioeconomic characteristics, and living in an urban as opposed to a rural area (Canadian
Institute for Health Information, 2009). Another factor that may be
associated with SGA births is maternal stress. Maternal stress is
known to be associated with low birthweight (Hobel and Culhane,
2003). Low birthweight can result from intrauterine growth retardation, which causes SGA, or from premature birth.
There is also a growing body of evidence that suggests that
individual-level socioeconomic status (SES) is a risk factor for SGA
birth (Parker et al., 1994; Koupilova et al., 1998, Fairley and Leyland,
2006; Luo et al., 2006). Low SES may influence the risk of SGA
& The Author 2010. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved.
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1045
Occupation and small-for-gestational-age births
birth in multiple ways. For example, exposure to harmful agents may
result from residential, lifestyle or occupational factors, all of which
may be related to SES.
Although a person’s job is often associated with his or her SES,
occupation can also be a proxy for occupational exposure. At least
one occupational study has found increased risks of SGA birth in
mothers whose occupations involved exposure to organic solvents
(Ahmed and Jaakkola, 2007a). A few studies have reported associations between broader occupational categories and risk of SGA
birth (Savitz et al., 1996b; Ahmed and Jaakkola, 2007b) and a few
have reported associations between specific parental occupations
and incidence of SGA birth (Savitz et al., 1996a; Rylander and
Kallen, 2005; Ahmed and Jaakkola, 2007b; Meyer et al., 2008,
Simcox and Jaakkola, 2008). However, the association between a
wider range of specific occupations and risk of SGA birth remains
unclear, and to the best of our knowledge, no previous nationwide
study has investigated the association between a wide range of
maternal and paternal occupational groups and risk of SGA births,
which was the purpose of the present study.
Data on SGA births were obtained from the nationwide Medical
Birth Register, which allowed us to analyze large sample sizes in
each occupational category. The use of nationwide birth data and
data from other nationwide registers permitted almost complete
follow-up of all women and men during the study period. The aim
of this study was to analyze risks of first singleton SGA birth in the
employed Swedish population by maternal and paternal occupation,
controlling for potential confounding variables.
Materials and Methods
Data sources
We linked nationwide data (1990– 2004) on singletons born to employed
mothers to nationwide data on maternal and paternal occupation and
other individual-level variables. One important reason for choosing the
year 1990 as the start of the study period was that since that year, ultrasound examination has been offered to all pregnant women in Sweden.
Data used in this study were retrieved from the nationwide WomMed II
Database, located at the Center for Primary Health Care Research at Lund
University. This database contains information from the Swedish Medical
Birth Register, which covers 99% of all births in Sweden beginning in
1973, and includes both birth records and prenatal care data such as prospectively collected information about complications during pregnancy and
delivery (The Swedish Centre for Epidemiology, 2003). The WomMed II
database also contains nationwide, individual-level hospital diagnoses and
death register data from the National Board of Health and Welfare, as
well as the population register (census) data from Statistics Sweden, the
Swedish Government-owned statistics bureau.
Outcome variable: small-for-gestational-age
births
Babies with a birthweight of more than 2 standard deviations below the
mean for gestational age (i.e. the 2.5th percentile) according to the
Swedish references curve for estimated fetal weight were categorized as
SGA. This corresponds to more than 24% (approximately 850 g) lower
birthweight than expected for a full-term baby. Information on birthweight
and gestational age was gathered from the Medical Birth Register. When
available, ultrasound performed during the second trimester was used
to estimate the gestational age; otherwise gestational age was estimated
from the date of the last menstrual period. All pregnant women in
Sweden are offered free antenatal care. At the first visit, usually in gestational weeks 10 – 12, information on date of the last menstrual period is
obtained. Since 1990, between gestational weeks 16 and 18, women
have been offered an ultrasound examination to date their pregnancy
and calculate the expected date of delivery. A total of 95% accepted
the offer since 1990 (Swedish Council on Technology Assessment in
Health Care, 1999). Once an expected date of delivery is obtained
from ultrasound, this date is used in all medical files and birth records
regardless of the date of the last menstrual period.
The ultrasound examinations were performed by trained midwives. In
ultrasound examinations conducted prior to gestational week 14, gestational age was assessed using biparietal diameter (Robinson and Fleming,
1975; Saltvedt et al., 2004; Sladkevicius et al., 2005). In examinations conducted during weeks 16 through 18, the midwives relied on femur length
and biparietal diameter to estimate gestational age (Persson and Weldner,
1986).
Predictor variable: parental occupation
We used parental occupation as the predictor variable in this study because
it was the best proxy for parental occupational exposure that was available to
us. Moreover, occupation has been used as a proxy for occupational
exposures in previous studies of SGA birth and low birthweight (Savitz
et al., 1996a; Rylander and Kallen, 2005; Ahmed and Jaakkola, 2007b,
Meyer et al., 2008; Simcox and Jaakkola, 2008). Information on parental
occupations was obtained from the 1990 census, from which fairly complete
(92%) individual-level employment data were available for the entire population. Census data include a numerical occupational code for each
employed individual. These occupational codes were created by Statistics
Sweden on the basis of a national adaptation of the Nordic Occupational
Classification (NYK) (Swedish National Central Bureau of Statistics, 1982).
Because many of the occupational groups defined by the census codes
contain too few individuals for a meaningful statistical analysis, we used 53
NYK-based occupational groups that have been used in several large-scale
epidemiological studies from the Nordic countries (Andersen et al., 1999;
Mutanen and Hemminki, 2001; Pukkala et al., 2009; Li et al., in press).
These occupational groups were combined on the basis of occupational
similarities. A detailed list of the Swedish Census codes included in each of
the 53 occupational groups can be found in Appendix A of a recent article
by Pukkala et al. (2009).
Occupation was assessed separately for mothers and fathers. An infant
was excluded from the analysis of both parental categories if its mother
was categorized as unemployed or as a student in the 1990 census, or if
maternal employment information was missing from the census. If an
infant’s father was categorized as unemployed or a student in the 1990
census, or if paternal employment information was missing, that infant
was included only in the analysis of maternal occupation.
Individual-level sociodemographic variables
Maternal age at infant’s birth was divided into 5-year age groups as follows:
20 – 24, 25 – 29, 30 – 34 and 35 years. Only mothers aged 20 years at
the birth of their child were included in the analysis. Period of birth was
divided into 5-year groups from 1990 to 2004. The variable family
income was defined as the mother’s family income from the year of childbirth divided by the number of people in the family; that is, individual family
income per capita. This variable was provided by Statistics Sweden. The
income parameter also took into consideration the ages of people in
the family and used a weighted system whereby small children were
given lower weights than adolescents and adults. The calculation procedure was performed as follows: the sum of all family members’
incomes was multiplied by the individual’s consumption weight divided
1046
by the family members’ total consumption weight. The final variable was
calculated as empirical quartiles from the distribution. Region of residence
was categorized on the basis of Statistics Sweden’s ‘H-regions,’ which
are regions with homogenous populations (Swedish National Central
Bureau of Statistics, 2003). We used three categories, all of which were
based on Statistics Sweden’s 1990 H-regions. The first category was
‘large cities.’ This category included Stockholm/Södertälje, Gothenburg,
Malmö/Lund/Trelleborg, plus counties in which more than 90 000 inhabitants lived within a 30-km radius of the center of the county. The second
category was ‘middle-size towns.’ This category included counties in which
more than 27 000 and less than 90 000 inhabitants lived within a 30-km
radius of the center of the county and in which more than 300 000 inhabitants lived within a 100-km radius of the same point. The third category
was ‘small towns/rural areas.’ This category included counties with
fewer than 27 000 inhabitants within a 30-km radius of the center of
the county. Mother’s region of residence was used to define the region
of residence. Marital status was defined as mother’s marital status during
the year of childbirth and was divided into two groups: (i) married or cohabiting with a partner or (ii) unmarried, divorced or widowed. We chose to
include the variable marital status, although many women in Sweden
cohabit with a partner without being married. For example, data from
the time period 1991– 1998 showed that only 35 – 40% of all women
were registered as being married. Non-married, cohabiting women
without children are not classified as cohabiting in Swedish national
census data. This means that potentially increased risks in the unmarried
group would be diluted because this group also includes women who
are cohabiting with a partner. Mothers were divided into two groups by
smoking habits: non-smokers and smokers. Smoking data were obtained
from the Medical Birth Register and represented the mother’s smoking
habits at the first visit to the maternal clinic.
Statistical analysis
Using logistic regression analysis, we estimated risk of giving birth to a singleton who was SGA by family income, region of residence, marital status,
smoking habits and parental occupation (the reference group was composed of all women or all men in the study population). All risk estimates
were adjusted for maternal age at infant’s birth and period of birth (in 5
year periods). The risk estimates of SGA birth by occupational status
were also adjusted for family income, region of residence, marital status
and smoking habits. We also conducted an ancillary analysis of the risk
of term SGA birth and preterm SGA birth by family income, region of residence and marital status. The sex of the infant showed no specific effects;
data are therefore given for female and male infants together. We used
SAS version 9.1 for the statistical analyses (SAS, 2003).
Ethical considerations
This study was approved by the Ethics Committee of Lund University.
Results
During the study period, there were 816 310 first singleton live births
in Sweden in which mothers were employed (according to the 1990
Census) and linkable to their infants in the Medical Birth Register.
Of these, 29 603 (3.6%) were SGA births. Table I shows the risk of
SGA birth for first singleton live births by family income, region of residence, mother’s marital status and mother’s smoking habits. All risks
are also adjusted for maternal age at infant’s birth and period of birth
(in 5-year groups). Statistically significant differences between the subcategories and the reference group were found for most variables.
Li et al.
The strongest associations with SGA were found for the variables
smoking habits and family income.
A total of 79% of all SGA events were term SGA events. The results
of an ancillary analysis showed no major difference between risk of
term SGA birth and risk of preterm SGA birth. For example, low
income affected risk of term and preterm SGA birth in a similar way
(data not shown).
Table II shows the odds ratio (ORs) for singleton SGA births by
mother’s and father’s occupation after adjustment for maternal age
at infant’s birth, period of birth (in 5-year groups), family income,
region of residence, marital status and smoking habits. Significantly
increased ORs of singleton SGA births were found in mothers who
worked as ‘textile workers,’ ‘mechanics and iron and metalware
workers,’ ‘electrical workers,’ ‘wood workers,’ ‘beverage manufacture
workers,’ ‘glass, ceramic and tile workers,’ or ‘packers, loaders and
warehouse workers.’ Only fathers who worked as ‘waiters’ had significantly increased ORs of singleton SGA births.
Discussion
To the best of our knowledge, this is the first large-scale study to
investigate the association between a wide range of maternal and
paternal occupation groups and SGA birth; in total over 800 000
live births were included in the study. The main finding of this study
was that specific maternal occupations carried a significantly increased
risk of SGA birth, whereas among paternal occupational groups, only
waiters had an increased risk of SGA birth.
We also found that singletons whose mothers had a low level of
family income, which can be seen as a proxy for low SES, had an
increased risk of SGA. Our results are in agreement with the results
of earlier studies from Sweden and the USA (Parker et al., 1994;
World Health Organization, 1995; Kramer et al., 2000), which
found a positive association between lower SES and an increased
risk of SGA birth. Low SES may be a risk factor for SGA birth
because social and economic deprivation is associated with occupational exposure (Savitz et al., 1996a; Ahmed and Jaakkola, 2007b;
Meyer et al., 2008; Simcox and Jaakkola, 2008), low social participation
(Dejin-Karlsson and Ostergren, 2003), smoking (Horta et al., 1997;
Cnattingius, 2004; Bell et al., 2008) and poor nutrition (Hobel and
Culhane, 2003, Mitchell et al., 2004).
Previous studies have found that some maternal occupations are
associated with an increased risk of SGA birth. A recent study from
Finland, which included 2568 singleton newborns, found that
mothers employed in the fields of farming and forestry, factory
work and mining and construction had a higher risk of giving birth
to an SGA infant than housewives (Ahmed and Jaakkola, 2007b).
Other previous studies have also reported associations between
specific maternal occupations and incidence or risk of SGA birth
(Savitz et al., 1996a; Simcox and Jaakkola, 2008; Jakobsson and
Mikoczy, 2009); for example, in newborns of nurses (Simcox and
Jaakkola, 2008), food service workers (Savitz et al., 1996a; Meyer
et al., 2008), electrical equipment operators (Savitz et al., 1996a),
hairdressers (Rylander and Kallen, 2005) and rubber workers
(Jakobsson and Mikoczy, 2009).
There are several mechanisms through which parental occupation
might affect intrauterine growth during pregnancy (Ahmed and
Jaakkola, 2007a), including direct exposure of harmful agents
1047
Occupation and small-for-gestational-age births
Table I Population sizes, number of mothers with SGA events and risk of SGA birth by family income, region of
residence, marital status and smoking habits.
Population
Mothers with
SGA events
OR
95% CI
.............................................................................................................................................................................................
Family income
Low income
226 762
9895
1.22
1.19
1.24
Middle-low income
217 996
7874
1.02
1.00
1.04
Middle-high income
186 703
6187
0.95
0.93
0.97
High income
184 849
5647
0.85
0.81
0.88
Region of residence
Large cities
255 385
9400
1.02
1.00
1.04
Middle-sized towns
275 351
9621
0.97
0.95
0.98
Small towns/rural areas
285 574
10 582
1.01
0.99
1.04
Married/cohabiting
416 092
14 526
1.00
0.99
1.02
Unmarried, divorced, or widowed
400 218
15 077
1.00
0.98
1.01
Non-smoker
684 884
21 601
0.69
0.69
0.70
Smoker
131 426
8002
1.44
1.42
1.46
All
816 310
29 603
Marital status
Smoking habits
Reference
Reference group is all women in the study population.
SGA, small-for-gestational age; OR, odds ratio; CI, confidence interval. All analyses are adjusted maternal age at infant’s birth and period of birth.
Bold type: 95% CI does not include 1.00.
through the placenta, exposure to parents’ clothing (which might
contain various agents from work) and possible additional exposure
from living in close proximity to an industrial workplace. The data in
the present study did not include information about specific occupational exposures. It is, however, likely that many of the maternal
occupations associated with an increased risk of SGA birth in the
present study included occupational exposures associated with
increased risk of SGA birth in previous research. For example, previous research indicates that exposure to specific chemicals at work
is associated with SGA births (Seidler et al., 1999) and other
adverse birth outcomes (Zhang et al., 1992). Moreover, maternal
exposure to welding fumes and metal dusts or fumes during pregnancy
is associated with reduced fetal growth (Quansah and Jaakkola, 2009).
Additionally, an occupational cohort study from Taiwan showed that
increased levels of lead in the blood were associated with SGA birth
(Chen et al., 2006). The association between environmental lead
exposure and SGA birth has also been found in other parts of the
world (Pietrzyk et al., 1996; Jelliffe-Pawlowski et al., 2006).
It is also likely that many of the maternal occupations that were
associated with an increased risk of SGA in the present study included
strenuous physical activity such as heavy lifting (e.g. among packers,
loaders and warehouse workers). Previous research has shown that
strenuous physical activity is associated with SGA birth (Artal and
O’Toole, 2003).
An important limitation of our study is that in our population-based
database, information was not available on detailed job tasks or on
potential exposure to chemicals on the job. It was therefore necessary
to use occupation as a proxy for occupational exposure, and occupational group is an imperfect measure of occupational exposure.
Furthermore, we had no information on exposure to harmful agents
outside the workplace. Collapsing occupations into broader occupational categories, moreover, creates the potential for bias caused
by misclassification. The 53 occupational groups used in our study
have, however, been used in several large-scale epidemiological
studies from the Nordic countries. A further considerable limitation
of this study is that a proportion of parents are likely to have
changed occupational category during the study period, and a
number of parents of SGA infants will have been classified as students
in the 1990 census, and therefore excluded from this study. It is likely
that the errors introduced into the data set by this problem are
greater for births later in the study period than for births earlier in
the study period because the time elapsed between exposure and
birth is larger toward the end of the study period. Furthermore, as
the study population was of childbearing age, they would most likely
obtain ‘better’ jobs with time, i.e. jobs with less exposure to potentially harmful agents. Misclassification of younger subjects to the potentially more demanding or highly exposed jobs held at younger ages
would likely result in an underestimation of risk for SGA in some occupations, although the magnitude of this misclassification is uncertain.
This study also has a number of strengths. Approximately 95% of
SGA births were classified as such on the basis of ultrasound examination (Swedish Council on Technology Assessment in Health Care,
1999). A further strength was the use of the civic registration
number (changed to a serial number to ensure anonymity) assigned
to each individual in Sweden, which made it possible to track the
records of every individual during the whole follow-up period. This
ensured that there was no loss to follow-up. Furthermore, the 1990
data on occupational status used in this study were 92% complete.
1048
Li et al.
Table II Number of SGA events and risk of SGA birth by parental occupation.
Occupational categories (based on the Nordic
Occupational Classification)
Mother’s occupation
Father’s occupation
..................................................
.....................................................
SGA
events
SGA
events
OR
95% CI
OR
95% CI
.............................................................................................................................................................................................
Technical, science research related workers and physicians
Dentists
Nurses
536
1.15
0.95
1.40
1850
0.94
0.88
1.00
27
1.12
0.73
1.70
29
1.00
0.70
1.44
605
1.06
0.87
1.28
112
0.97
0.81
1.18
1958
1.09
0.91
1.30
227
1.00
0.87
1.14
Other health and medical workers
341
1.10
0.90
1.36
66
1.16
0.91
1.48
Teachers
983
1.08
0.90
1.31
412
0.87
0.79
0.97
Assistant nurses
Religious, juridical and other social-science-related workers
Artistic workers
Journalists
Administrators and managers
Clerical workers
1001
1.14
0.95
1.38
924
0.99
0.92
1.06
150
1.10
0.87
1.40
151
0.83
0.71
0.98
58
0.96
0.70
1.32
66
0.89
0.70
1.14
242
1.20
0.97
1.49
274
0.86
0.76
0.97
2675
1.13
0.95
1.36
596
0.96
0.88
1.05
Sales agents
488
1.07
0.88
1.31
1101
0.95
0.88
1.02
Shop managers and assistants
948
1.04
0.86
1.25
508
0.95
0.87
1.05
Farmers
60
0.74
0.54
1.00
284
0.82
0.72
0.92
Gardeners and related workers
77
0.98
0.73
1.30
147
0.95
0.81
1.12
Fishermen, whalers and sealers
-*
–
31
1.05
0.74
1.49
Forestry workers
-*
–
141
0.87
0.73
1.03
Miners and quarry workers
–*
–
64
1.07
0.84
1.37
1.55
Seamen
-*
–
29
1.08
0.75
Transport workers
65
1.22
0.90
1.65
173
1.09
0.94
1.27
Drivers
126
1.05
0.82
1.35
1005
0.95
0.89
1.02
Postal and communication workers
394
1.19
0.97
1.46
296
0.99
0.88
1.12
Textile workers
150
1.31
1.03
1.66
92
1.07
0.87
1.32
17
1.25
0.78
2.00
Shoe and leather workers
-*
–
Smelters and metal foundry workers
23
1.36
0.86
2.14
200
1.02
0.88
1.18
337
1.29
1.05
1.58
2295
1.05
0.99
1.11
1.09
Mechanics and iron and metalware workers
Plumbers
-*
–
223
0.95
0.83
Welders
21
0.97
0.61
1.54
357
1.05
0.94
1.17
193
1.28
1.02
1.60
928
0.99
0.92
1.06
Wood workers
93
1.51
1.15
1.99
1018
0.95
0.89
1.02
Painters and wall paperhangers
23
0.93
0.59
1.46
Other construction workers
-*
–
Electrical workers
Bricklayers
–
0.95
0.85
1.06
0.91
0.83
0.99
106
1.09
0.90
1.32
122
1.27
0.99
1.64
202
1.02
0.88
1.18
Chemical process workers
49
1.16
0.83
1.62
205
0.99
0.86
1.14
Food manufacture workers
157
1.20
0.95
1.53
302
1.06
0.94
1.20
Beverage manufacture workers
13
2.02
1.12
3.64
13
0.97
0.57
1.66
Glass, ceramic and tile workers
180
1.32
1.04
1.66
366
1.11
0.99
1.24
Packers, loaders and warehouse workers
1.10
Printers and related workers
-*
345
586
342
1.24
1.01
1.52
730
1.02
0.94
Engine and motor operator workers
36
1.02
0.70
1.48
471
1.02
0.92
1.12
Public safety and protection workers
124
0.98
0.76
1.25
308
0.85
0.75
0.95
Cooks and stewards
647
1.13
0.93
1.37
272
1.05
0.92
1.19
Home helpers
2012
1.08
0.90
1.30
125
1.02
0.86
1.22
Waiters
225
0.95
0.76
1.18
106
1.24
1.02
1.51
Building caretakers and cleaners
787
1.15
0.95
1.39
481
1.06
0.96
1.17
Continued
1049
Occupation and small-for-gestational-age births
Table II Continued
Occupational categories (based on the Nordic
Occupational Classification)
Mother’s occupation
Father’s occupation
..................................................
.....................................................
SGA
events
SGA
events
OR
95% CI
OR
95% CI
.............................................................................................................................................................................................
Chimney sweeps
14
0.61
0.36
1.01
Hairdressers
210
-*
1.21
–
0.97
1.51
19
1.27
0.81
1.99
Launderers and dry cleaners
256
0.99
0.80
1.22
131
0.92
0.78
1.10
Reference group is all women or men in the study population.
SGA, small-for-gestational age; OR, odds ratio; CI, confidence interval. All analyses are adjusted for family income, region of residence, marital status, smoking habits, maternal age at
infant’s birth and period of birth. Bold type: 95% CI does not include 1.00. -* Cases ,10 are not shown.
The quality of data on occupational titles in the Swedish census has
been assessed and found to be reasonable (Warnryd et al., 1989).
The proportion of concordant occupational titles was 72%. In terms
of reliability, the coding showed that about 10% of occupations
were misclassified. A further strength of this study was the availability
of family income for the year of birth. Finally, we had individual-level
data on smoking, which is a major risk factor for SGA birth (Horta
et al., 1997; Cnattingius, 2004; Bell et al., 2008). It was also possible
to compare parental occupations that were associated with high risk
of SGA in singleton births with parental occupations that carry a
high risk of lung cancer for the parents (Hemminki and Li, 2003; Ji
and Hemminki, 2005).
Conclusion
The present study showed that several maternal occupations carried a
significantly higher risk of SGA than the risk in the reference group (all
women in the study population). Father’s occupation had a minor
effect on risks. Further studies are needed to examine the causative
agents in those maternal occupations that are associated with an
increased risk of having an SGA infant.
Acknowledgements
We thank Scientific Editor Kimberly Kane for useful comments on the
text.
Funding
The project described was supported by grant number R01
HD052848-01 A1 from the National Institute of Child Health and
Human Development, and its contents are solely the responsibility
of the authors and do not necessarily represent the official views of
the National Institute of Child Health and Human Development.
This work was also supported by grants to Drs Kristina and Jan
Sundquist from the Swedish Research Council, the Swedish Council
for Working Life and Social Research, the Swedish Research Council
Formas and the Region of Skåne in Sweden. The grantors played no
role in the formulation of the research questions, choice of research
design, data collection and analyses, preparation of the manuscript
or the decision to publish.
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