Abstract
Introduction
Unidentified small for gestational age (SGA) pregnancies have an increased risk for stillbirth. The risk of stillbirth is increased in women born abroad or with low socioeconomic status (SES). The aim of this study was to evaluate potential inequalities in antenatal screening and identification of SGA by examining whether a foreign background or indicators of low SES were associated with unidentified SGA.
Material and Methods
This was a register‐based cohort study of all pregnancies delivered in Stockholm in the year 2014 and 2017, including 5487 SGA pregnancies. Data from maternal medical records were linked to nationwide Swedish registers. Exposures were educational level, family income level, recent immigration, social security benefits, civil status, Swedish/foreign background, municipal affiliation, and country of birth. Outcome was unidentified SGA, defined as born SGA with no or normal growth scans performed at or after week 24 + 0 of pregnancy. We used unadjusted and adjusted logistic regression analyses to assess the associations between socioeconomic factors and unidentified SGA. Additionally, an intersectional regression analysis was performed to explore predefined combinations of the exposure factors.
Results
Neither educational level, family income level, Swedish/foreign background, or any combination of these factors, nor recent immigration or civil status was associated with unidentified SGA in the adjusted model. Women receiving social security benefits had decreased odds of unidentified SGA, adjusted odds ratio 0.73, 95% confidence interval 0.55–0.97.
Conclusions
Foreign background or indicators of low SES were not positively associated with unidentified SGA. These findings suggest that antenatal screening and identification of SGA are provided on equal terms.
Keywords: antenatal identification, health inequality, small for gestational age, socioeconomic status
The risk of stillbirth is increased in unidentified small for gestational age (SGA) pregnancies. Women with a foreign background or low socioeconomic status have an increased risk of stillbirth. However, we found no positive association between a foreign background or indicators of low socioeconomic status and unidentified SGA that can explain the increased risk of stillbirth in these groups.
Abbreviations
- BMI
body mass index
- CI
confidence interval
- EFW
estimated fetal weight
- OR
odds ratio
- PIN
personal identity number
- SES
socioeconomic status
- SGA
small for gestational age
Key message.
Women with a foreign background or indicators of low socioeconomic status do not have increased odds of unidentified SGA. The previously reported higher risk of stillbirth in these groups does not appear to be explained by inequalities in antenatal screening and identification of SGA.
1. INTRODUCTION
Fetal growth restriction (FGR) is a major contributor to adverse perinatal and childhood outcomes. 1 , 2 , 3 , 4 , 5 Antenatal identification of small for gestational age (SGA) fetuses at risk of FGR is associated with a near 5‐fold decreased risk of stillbirth. 6 , 7 Ultrasound screening detects 19–57% of SGA. 8 , 9 Selective screening, i.e., ultrasound examinations performed only in high‐risk pregnancies or if clinically indicated, reaches the lower ranges of identification. 9 However, universal screening, with two routinely performed ultrasounds in the third trimester, does not perform better than selective screening in preventing adverse perinatal outcomes. 9
A large prospective study investigated characteristics associated with unidentified SGA in a setting using selective screening. 10 The authors concluded that a body mass index (BMI) of 25.0–29.9 kg/m2, less severe SGA and absence of a clinical indication for growth scans increased the risk of unidentified SGA. Nevertheless, almost half of pregnancies with unidentified SGA had no ultrasound performed, despite one‐third of them having a clinical indication. Conversely, most pregnancies with identified SGA had no indication for an ultrasound examination. 10 This raises questions about the equality of antenatal care. Socioeconomic status (SES) and healthcare‐related factors are known to be important explanations of health inequalities. 11 , 12 It is plausible that well‐educated Swedish women with a high income are more likely to have a growth scan performed than women with less favorable conditions.
Reducing health inequalities is a prioritized goal of Swedish health authorities. 13 Health inequalities are known to be associated with adverse perinatal outcomes. 12 , 14 , 15 Being born abroad, particularly in sub‐Saharan countries, and living in deprived areas are known risk factors for stillbirth and adverse pregnancy outcomes. 16 , 17 , 18 , 19 Individual socioeconomic factors and suboptimal antenatal care have been suggested as possible explanations for these associations. 14 , 17 , 20 Antenatal identification of SGA pregnancies prevents stillbirth and can be regarded as a quality indicator of antenatal maternal health care. 6 , 7
We hypothesize that women with a foreign background or indicators of low SES are less likely to have their SGA pregnancies identified with ultrasound before birth, causing their increased risk of stillbirth. Hence, this study aimed to evaluate potential inequalities in antenatal screening and identification of SGA by examining whether a foreign background or indicators of low SES were associated with unidentified SGA.
2. MATERIAL AND METHODS
This was a register‐based cohort study of all women giving birth in the Stockholm Region in 2014 and 2017. The cohort was described in detail in a previous publication. 7 Cases were identified in the regional computerized chart for maternity and delivery (Obstetrix, Cerner Sverige AB, Lund, Sweden), which retains data on maternal and infant anthropometrics, medical diagnoses, and the personal identity number (PIN), uniquely allocated to all citizens. 21 The PIN was used to cross‐link the data to Statistic Sweden's Longitudinal Integrated Database for Health Insurance and Labor Market Studies (LISA) and Total Population Register (TPR) for information on maternal socioeconomic data. 22 , 23 LISA contains detailed information on civil status, education, occupation, income, sick leave, disability and unemployment benefits, and social welfare payments. 22 TPR includes data on country of birth, foreign background and dates of immigration and emigration. 23 Participation in LISA and TPR, as in all Swedish government‐administrated registers, is compulsory and the quality is regarded as high. 22 , 23
Inclusion criteria were singleton pregnancies, without known fetal chromosomal aberrations or structural abnormalities, delivered between 24 + 0 and 43 + 0 weeks of gestation. Only one pregnancy per woman, that is, the first recorded pregnancy, was included. Cases were excluded when data on birthweight or gestational age at birth were missing, or when no or an inaccurate PIN was available. Without the PIN, socioeconomic data could not be retrieved. For this study, we also excluded newborns born large for gestational age (LGA).
In the Stockholm region, antenatal care is free of charge and highly accessible. All pregnant women were offered regular visits according to a standard protocol and additional visits on indication. Maternity care units were run by midwives and followed the same internet‐based guidelines. A selective ultrasound screening was used to identify SGA, that is, ultrasound examinations were performed only in high‐risk pregnancies, if pregnancy complications occurred or if there was a deviation in the symphysis‐fundal height. Ultrasounds were performed exclusively by midwives and physicians certified in ultrasound examinations. Ultrasound dating was based on crown‐rump length or biparietal diameter, and performed in the first or early second trimester. 24 In Sweden, 92% of all pregnancies are dated by ultrasound, 6.2% by embryo transfer date, 1.2% by the last menstrual period, and 0.2% by other methods. 25 Estimated fetal weight (EFW) and the deviation from the expected mean weight were calculated based on established formulas. 26 , 27
Weight deviation at birth was calculated based on the actual birthweight as (birthweight – expected birthweight by gestational age)/expected birthweight by gestational age, and expressed as a percentage. The expected birthweight by gestational age was assessed using the formula for intrauterine expected fetal weight. 27 Newborns with a birth weight of ≤−15% of the expected mean, approximately corresponding to the <10th percentile, were defined as SGA. Ultrasound reports of all SGA newborns were reviewed. SGA pregnancies were considered identified if an ultrasound examination was performed at or after gestational week 24 + 0, presenting an EFW of ≤−15%, roughly corresponding to the <10th percentile.
2.1. Exposures
The socioeconomic factors studied included educational level, family income, immigrated less than 5 years before delivery, social security benefits, civil status, Swedish/foreign background, municipal affiliation, and country of birth. Data on educational level, family income, social security benefits, civil status and municipal affiliation were retrieved from the LISA register for the years 2014 and 2017, corresponding to the respective year of delivery. Family income was defined as the disposable income per consumption unit of the family, where disposable income means total income received, including allowances, minus taxes paid. The consumption units were calculated based on the number of adults and children in the family. 22 Social security benefits are welfare payments received by families with an income lower than considered necessary for a decent standard of living. Information on country of birth, date of immigration, and Swedish/foreign background was retrieved from TPR. Country of birth was classified into Sweden, Europe/North America, Asia/Oceania/South America, and Africa. Swedish background was defined as being born in Sweden with at least one Swedish‐born parent. Foreign background was defined as being born abroad or born in Sweden with two foreign‐born parents.
2.2. Outcome
The outcome was unidentified SGA, defined as born SGA with no or normal growth scans performed at or after week 24 + 0 of pregnancy. SGA was defined as a birth weight of ≤−15% of the expected mean, roughly corresponding to the <10th percentile.
2.3. Covariates
Maternal age, BMI, smoking, and parity were considered confounders. Preeclampsia/hypertension, diabetes and weight deviation at birth were considered mediators. BMI was based on measured weight and self‐reported height in the first trimester. Smoking was defined as smoking in early pregnancy, and hypertension was defined as a blood pressure of >140/90 at two separate measurements before or during pregnancy. Preeclampsia was defined as pregnancy‐related hypertension and proteinuria ≥300 mg/24 h after 20 weeks of gestation. Diabetes included type 1 diabetes, type 2 diabetes, and gestational diabetes, defined as fasting venous plasma glucose of ≥7 mmol/L and/or a 2‐h value of ≥9 mmol/L after a 75 g oral glucose tolerance test. Weight deviation at birth was calculated based on the actual birthweight and expected birth weight by gestational age and expressed as percentage. 27 Information on maternal age, BMI, smoking status, parity, preeclampsia, hypertension, diabetes, and birthweight were obtained from the medical chart for maternity and delivery.
2.4. Statistics
Maternal background characteristics, pregnancy complications, socioeconomic factors, and country of birth of women with SGA pregnancies were compared with those of appropriate for gestational age (AGA) pregnancies. Identified and unidentified SGA pregnancies were then compared, using the same variables. Continuous variables were compared using Student's t‐test if normally distributed and the Mann–Whitney test if non‐normally distributed, and expressed as means with standard deviations (SD) or medians with interquartile ranges. Categorical variables were analyzed using the Chi‐square test or Fisher's exact test, as appropriate, and expressed as numbers and proportions.
Logistic regression analyses were used to investigate the association between socioeconomic factors and nonidentification of SGA. Risk estimates for each socioeconomic factor were presented as crude odds ratios (cOR) and adjusted odds ratios (aOR), with 95% confidence intervals (CI). The exposure variables were categorized as follows: educational level (<9 years, 9–12 years (ref), >12 years), family income (low = <25th percentile, middle = 25th–75th percentile (ref), high = >75th percentile), immigrated less than 5 years before delivery (yes or no (ref)), social security benefits (yes or no (ref)), civil status (married/registered partner (ref), not married, divorced/widowed), and Swedish/foreign background (Swedish (ref) or foreign). We adjusted for age (continuous), BMI (<18.5, 18.5–24.9, 25–30, >30), smoking (yes or no), nulliparity (yes or no), and all other socioeconomic factors. Preeclampsia/hypertension (yes or no), diabetes (yes or no), and weight deviation at birth (continuous) were considered mediators and were adjusted for in cases of a significant association in the original model.
Country of birth and municipal affiliation were not included in the regression model. Instead, the numbers and proportions of unidentified SGA pregnancies according to country of birth and municipal affiliation were calculated. The unemployment rate of the municipalities was used to describe the level of deprivation. Data on unemployment were retrieved from the Swedish public employment service. We then assessed the correlation between unemployment rate and the proportion of unidentified SGA.
To assess whether certain combinations of socioeconomic factors were associated with nonidentification of SGA we performed an intersectional logistic regression analysis. Educational level, family income level, and Swedish/foreign background were considered the most appropriate variables to include in the analyses. A new exposure variable was created and categorized into all unique combinations of these variables, resulting in 18 (3 × 3 × 2) categories or strata. The same data/individuals were used repeatedly in different strata, which increased the risk of random error. Therefore, we chose a significance level of <0.01 for this analysis. For all other analyses a p‐value of <0.05 was considered statistically significant.
The data were analyzed using SPSS software (IBM SPSS Statistics for Windows, Version 29.0, Armonk, NY: IBM Corp).
The study was reported according to the STROBE guidelines (https://www.equator‐network.org/reporting‐guidelines/strobe/).
3. RESULTS
After excluding 7481 pregnancies, the final study population consisted of 46 690 pregnancies who met the inclusion criteria (Figure 1). There were 41 203 AGA pregnancies and 5487 SGA pregnancies. Of these, SGA was not identified antenatally in 3641 (66.4%) cases. Maternal characteristics, including background information, pregnancy complications, socioeconomic factors, and country of birth for AGA versus SGA pregnancies and unidentified versus identified SGA pregnancies, are presented in Table 1. SGA pregnancies had a higher proportion of low education, low family income, recent immigration, receiving social security benefits, and non‐Swedish background, compared to AGA pregnancies. Unidentified SGA pregnancies were characterized by a lower proportion of women who had immigrated within the last 5 years before delivery and receiving social security benefits, compared to identified SGA pregnancies. There were no differences in educational level, family income, civil status, Swedish/foreign background, and country of birth between unidentified and identified SGA pregnancies (Table 1).
FIGURE 1.
Flowchart of the study population.
TABLE 1.
Maternal, perinatal, and socioeconomic characteristics of AGA versus SGA pregnancies and unidentified versus identified SGA pregnancies.
| SGA pregnancies | ||||||
|---|---|---|---|---|---|---|
| Characteristics | AGA | SGA | Unidentified SGA | Identified SGA | ||
| n = 41 203 | n = 5487 | p‐value | n = 3641 | n = 1846 | p‐value | |
| Age (years) | 31.9 (5.0) | 31.6 (5.2) | <0.001 | 31.6 (5.1) | 31.5 (5.3) | 0.884 |
| Age >35 years, yes | 12 589 (30.6) | 1609 (29.3) | 0.063 | 1062 (29.2) | 547 (29.6) | 0.721 |
| BMI (kg/m2) | 23.3 (21.2, 26.2) | 22.8 (20.7, 25.7) | <0.001 | 22.8 (20.8, 25.7) | 22.5 (20.4, 25.8) | 0.011 |
| BMI (kg/m2) | <0.001 | <0.001 | ||||
| <18.5 | 1060 (2.6) | 240 (4.4) | 127 (3.5) | 113 (6.1) | ||
| 18.5–24.9 | 25 189 (61.1) | 3345 (61.0) | 2264 (62.2) | 1081 (58.6) | ||
| 25–30 | 9358 (22.7) | 1100 (20.0) | 747 (20.5) | 353 (19.1) | ||
| >30 | 3885 (9.4) | 437 (8.0) | 279 (7.7) | 158 (8.6) | ||
| Missing | 1711 (4.2) | 365 (6.7) | 224 (6.2) | 141 (7.6) | ||
| Smoking | <0.001 | 0.001 | ||||
| Yes | 1380 (3.3) | 279 (5.1) | 163 (4.5) | 116 (6.3) | ||
| Missing | 1358 (3.3) | 314 (5.7) | 191 (5.2) | 123 (6.7) | ||
| Nulliparous, yes | 18 311 (44.4) | 3302 (60.2) | <0.001 | 2244 (61.6) | 1058 (57.3) | 0.002 |
| Preeclampsia/hypertension, yes | 1960 (4.8) | 655 (11.9) | <0.001 | 318 (8.7) | 337 (18.3) | <0.001 |
| Diabetes, yes | 486 (1.2) | 43 (0.8) | 0.009 | 16 (0.4) | 27 (1.5) | <0.001 |
| Weight‐deviation at birth (%) | 0.1 (−6.3, 7.3) | −19.4 (−23.4–16.9) | <0.001 | −18.4 (−21.6, −16.5) | −22.0 (−27.1–18.4) | <0.001 |
| Education | <0.001 | 0.589 | ||||
| ≤9 years | 3559 (8.6) | 579 (10.6) | 384 (10.5) | 195 (10.6) | ||
| 10–12 years | 11 814 (28.7) | 1570 (28.6) | 1026 (28.2) | 544 (29.5) | ||
| >12 years | 24 752 (60.1) | 3139 (57.2) | 2104 (57.8) | 1035 (56.0) | ||
| Missing | 1078 (2.6) | 199 (3.6) | 127 (3.5) | 72 (3.9) | ||
| Family income | <0.001 | 0.257 | ||||
| Low | 10 099 (24.5) | 1562 (28.5) | 1010 (27.7) | 552 (29.9) | ||
| Middle | 20 686 (50.2) | 2565 (46.7) | 1706 (46.9) | 859 (46.5) | ||
| High | 10 350 (25.1) | 1351 (24.6) | 918 (25.2) | 433 (23.5) | ||
| Missing | 68 (0.2) | 9 (0.2) | 7 (0.2) | 2 (0.1) | ||
| Immigrated <5 years before delivery | 5490 (13.3) | 1000 (18.2) | <0.001 | 636 (17.5) | 364 (19.7) | 0.041 |
| Social security benefits | 1349 (3.3) | 284 (5.2) | <0.001 | 165 (4.5) | 119 (6.4) | 0.002 |
| Civil status | 0.634 | 0.612 | ||||
| Married/registered partner | 21 403 (51.9) | 2848 (51.9) | 1868 (51.3) | 980 (53.1) | ||
| Not married | 17 842 (43.3) | 2357 (43.0) | 1583 (43.5) | 774 (41.9) | ||
| Divorced/widow | 1890 (4.6) | 273 (5.0) | 183 (5.0) | 90 (4.9) | ||
| Missing | 68 (0.2) | 9 (0.2) | 7 (0.2) | 2 (0.1) | ||
| Background | <0.001 | 0.406 | ||||
| Swedish | 24 497 (59.5) | 2744 (50.0) | 1843 (50.6) | 901 (48.8) | ||
| Foreign | 16 703 (40.5) | 2739 (49.9) | 1795 (49.3) | 945 (51.1) | ||
| Missing | 3 (0.0) | 4 (0.1) | 3 (0.1) | 1 (0.1) | ||
| Country of birth | <0.001 | 0.412 | ||||
| Sweden | 27 313 (66.3) | 3189 (58.2) | 2141 (58.9) | 1048 (56.8) | ||
| Europe or North America | 4951 (12.0) | 682 (12.4) | 447 (12.3) | 235 (12.7) | ||
| Asia, Oceania, South America | 6294 (15.3) | 1168 (21.3) | 768 (21.1) | 400 (21.7) | ||
| Africa | 2635 (6.4) | 444 (8.1) | 282 (7.8) | 162 (8.8) | ||
Note: Continuous variables are presented as means with standard deviation or medians with interquartile range, as appropriate, and categorical variables as numbers and proportions. Background: Swedish = born in Sweden with at least one Swedish‐born parent, foreign = born abroad or born in Sweden with two foreign‐born parents. Family income: High >75th percentile, Middle 25th–75th percentile, Low <25th percentile, weight deviation at birth: deviation from expected mean weight, in percentage.
Abbreviations: AGA, appropriate for gestational age; BMI, body mass index; SGA, small for gestational age.
In the adjusted logistic regression analysis, there was no association between educational level, family income, civil status, immigration within the last 5 years before delivery, or Swedish/foreign background and unidentified SGA. Receiving social security benefits was negatively associated with unidentified SGA (aOR 0.70, 95% CI 0.53–0.91). Adding the mediating variables, i.e., preeclampsia/hypertension, gestational diabetes, and weight deviation at birth, did not significantly affect the association (aOR 0.73, 95% CI 0.55–0.97) (Table 2). The proportion of women receiving social security benefits was significantly higher in women with a foreign background (8.3%) compared to those with a Swedish background (1.9%), p‐value <0.001. Women born in Africa had a proportion of social security benefit receivers of 20.5%, compared to 9.2% of women born in Asia/Oceania/South America, 2.2% of women born in Europe/North America, and 2.1% of women born in Sweden.
TABLE 2.
Logistic regression for the associations between socioeconomic factors and maternal origin, and unidentified SGA.
| Included, n = 5478 | Unidentified SGA | |||
|---|---|---|---|---|
| n = 3641 | cOR (95%CI) | aOR (95%CI) | p‐value | |
| Education | 0.457 | |||
| ≤9 years | 384 (66.3) | 0.97 (0.80–1.17) | 1.14 (0.92–1.42) | |
| 10–12 years | 1026 (65.4) | 0.93 (0.82–1.05) | 0.96 (0.84–1.10) | |
| >12 years | 2104 (67.0) | Ref | ||
| Missing | 127 (63.8) | 0.87 (0.64–1.17) | 0.97 (0.70–1.35) | |
| Family income | 0.938 | |||
| Low | 1010 (64.7) | 0.92 (0.81–1.05) | 1.01 (0.87–1.17) | |
| Middle | 1706 (66.5) | Ref | ||
| High | 918 (67.9) | 1.07 (0.93–1.23) | 1.03 (0.89–1.19) | |
| Missing | 7 (77.8) | a | a | |
| Immigrated <5 years before deliviery | 0.130 | |||
| Yes | 636 (63.6) | 0.86 (0.75–0.99) | 0.88 (0.74–1.04) | |
| No | 3005 (67.0) | Ref | Ref | |
| Social security benefits | 0.009 | |||
| Yes | 165 (58.1) | 0.69 (0.54–0.88) | 0.73 (0.55–0.97) b | |
| No | 3476 (66.8) | Ref | Ref | |
| Civil status | 0.615 | |||
| Married/registered partner | 1868 (65.6) | Ref | Ref | |
| Not married | 1583 (67.2) | 1.07 (0.96–1.20) | 1.04 (0.91–1.18) | |
| Divorced/widow | 183 (67.0) | 1.07 (0.82–1.39) | 1.14 (0.86–1.49) | |
| Missing | 7 (77.8) | a | a | |
| Background | 0.885 | |||
| Swedish | 1843 (67.2) | Ref | Ref | |
| Foreign | 1795 (65.5) | 0.93 (0.83–1.04) | 1.01 (0.88–1.16) | |
| Missing | 3 (75.0) | a | a | |
Note: Adjusted for age (continuous), body mass index (<18.5, 18.5–24.9, 25–30, >30, missing), smoking (yes, no, missing), nulliparity (yes, no), and for all other socioeconomic factors.
Abbreviations: SGA, small for gestational age; cOR, crude odds ratio; CI, confidence interval; aOR, adjusted odds ration.
Not included in the analyses.
Adjusted for the above variables and preeclampsia/hypertension (yes/no), gestational diabetes (yes/no), and weight deviation at birth (continuous), as mediators.
The proportion of unidentified SGA did not vary significantly between different countries of birth: Sweden (67.1%), Europe/North America (65.5%), Asia/Oceania/South America (65.7%), and Africa (63.5%), p‐value 0.412.
The proportion of unidentified SGA varied between municipalities, ranging from 51.9% to 76.7%. There was no correlation between the proportion of unidentified SGA and the unemployment rate in the municipalities in the region, with a correlation coefficient of 0.015 and a p‐value of 0.943. For a geographical presentation of municipalities with high (>75th percentile), middle (25th–75th percentile), and low (<25th percentile) proportions of (1) unidentified SGA and (2) unemployment, see Figure 2.
FIGURE 2.
Geographical comparison of the proportion of unidentified SGA pregnancies and the unemployment rate in the municipalities in the Stockholm Region. High, middle, and low levels were based on percentiles; low = <25th percentile, middle = 25th–75th percentile, high = >75th percentile. Data on unemployment were retrieved from the Swedish Public Employment Service. Presented proportions of unemployment were the mean values of the unemployment rate of the municipality in 2014 and 2017.
In the intersectional analysis, no associations were found between any of the possible combinations of educational level, level of family income per unit and Swedish/foreign background, and unidentified SGA (Table 3).
TABLE 3.
Intersectional logistic regression analysis for the association between all possible combinations of education level, income level, Swedish/foreign background, and unidentified SGA.
| Education | Family income | Background | OR | 99% CI | aOR | 99% CI | Subjects per | Nonidentified | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| High | Middle | Low | High | Middle | Low | Swedish | Foreign | stratum | SGA, n (%) | ||||
| x | x | x | Ref | Ref | 854 | 575 (67.3) | |||||||
| x | x | x | 0.98 | 0.75–1.29 | 0.96 | 0.73–1.27 | 783 | 524 (66.9) | |||||
| x | x | x | 1.06 | 0.65–1.73 | 1.06 | 0.65–1.72 | 153 | 105 (68.6) | |||||
| x | x | x | 1.18 | 0.81–1.71 | 1.21 | 0.83–1.78 | 305 | 216 (70.8) | |||||
| x | x | x | 0.94 | 0.71–1.24 | 1.01 | 0.75–1.36 | 674 | 444 (65.9) | |||||
| x | x | x | 0.90 | 0.64–1.26 | 1.02 | 0.71–1.48 | 370 | 240 (64.9) | |||||
| x | x | x | 0.97 | 0.23–4.03 | 0.93 | 0.22–3.86 | 15 | 10 (66.7) | |||||
| x | x | x | 0.81 | 0.41–1.61 | 0.85 | 0.42–1.71 | 64 | 40 (62.5) | |||||
| x | x | x | 0.80 | 0.42–1.52 | 1.06 | 0.52–2.13 | 74 | 46 (62.2) | |||||
| x | x | x | 1.21 | 0.14–10.55 | 1.29 | 0.15–11.42 | 7 | 5 (71.4) | |||||
| x | x | x | 1.59 | 0.86–2.91 | 1.80 | 0.97–3.35 | 111 | 85 (76.6) | |||||
| x | x | x | 0.87 | 0.61–1.25 | 1.10 | 0.73–1.65 | 308 | 198 (64.3) | |||||
| x | x | x | 1.11 | 0.70–1.77 | 1.10 | 0.69–1.75 | 178 | 124 (69.7) | |||||
| x | x | x | 1.07 | 0.78–1.48 | 1.06 | 0.76–1.47 | 452 | 311 (68.8) | |||||
| x | x | x | 0.86 | 0.54–1.35 | 0.96 | 0.60–1.54 | 166 | 106 (63.9) | |||||
| x | x | x | 0.68 | 0.31–1.48 | 0.70 | 0.32–1.54 | 48 | 28 (58.3) | |||||
| x | x | x | 0.75 | 0.53–1.06 | 0.80 | 0.56–1.14 | 341 | 207 (60.7) | |||||
| x | x | x | 0.90 | 0.64–1.25 | 1.02 | 0.71–1.46 | 385 | 250 (64.9) | |||||
Note: Number included in the analyses: 5288, 3.6% missing (education). Family income: Low ≤25th percentile (149 700 kr), middle 25th‐75th percentile (149 800–297 700 kr), high >75th percentile (297 800 kr). Education: Low <9 years, Middle 9–12 years, High >12 years. Background: Swedish = born in Sweden with at least one domestic born parent, foreign = born abroad or with two foreign born parents, adjusted for age (continous), BMI (<18.5, 18.5–24.9, 25–30, >30, missing), smoking (yes, no, missing), nulliparity (yes, no), immigrated <5 years before delivery (yes, no), social security benefits (yes, no), civil status (married, unmarried, divorced/widow). Color shades improve the table's readability and comprehension.
Abbreviations: aOR, adjusted odds ratio; cOR, crude odds ratio; SGA, small for gestational age.
Missing data on BMI (6.7%), smoking (5.7%), and educational level (3.6%) were assumed not to be missing randomly. In the logistic regression analyses, individuals with missing data on these variables were included and analyzed as separate categories. In the intersectional regression analysis, individuals with missing data on education were excluded. The proportion of missing data for other variables was minimal, and only individuals with complete information were included in the regression models.
4. DISCUSSION
In this register‐based cohort study of pregnancies in Stockholm in 2014 and 2017, neither a foreign background nor any indicator of low SES was positively associated with unidentified SGA. None of the possible combinations of educational level, family income level and Swedish/foreign background in the intersectional analysis were associated with unidentified SGA. Women receiving social security benefits had decreased odds of an unidentified SGA pregnancy.
To the best of our knowledge, this is the first study to examine the association between individual socioeconomic factors, one by one, and unidentified SGA pregnancies. Relph et al. examined risk factors for unidentified SGA in the UK and found no association between socioeconomic deprivation and unidentified SGA. 10 However, the authors used indices of multiple deprivation (IMD) to measure SES. IMD is an area‐level measure based on information on income, education, employment, health, crime, and living environment in the area where the person lives. 28 The studies are therefore not fully comparable. In the present study, individual socioeconomic data were accounted for, which improves accuracy. Yet, we lacked individual information on living environment, that is, if the included women lived in a deprived area or not. Hesselman et al. reported that living in a severely deprived area was associated with an increased risk of SGA. 20 A high crime rate has been associated with adverse birth outcomes, possibly reflecting an indirect behavioral effect on care‐seeking. 29 Still, our results indicate that, on a group level, living in a less privileged area does not affect the identification of SGA. Using unemployment rate as a proxy for deprivation, we found no correlation between unemployment rate and the proportion of unidentified SGA at the municipal level.
A study by Andreasen et al. showed that being screened for risk factors by an experienced midwife in early pregnancy and having access to multiple midwife consultations improved the antenatal identification of FGR. 30 However, the authors did not include socioeconomic factors in their analyses. In the present study, we did not have access to healthcare provider characteristics or number of antenatal care visits. The results are therefore not comparable. Nevertheless, even though we cannot rule out a healthcare provider effect on the identification of SGA, our results indicate that such potential effect is at least not influenced by social inequality. Interestingly, women receiving social security benefits had decreased odds of having an unidentified SGA. We speculate that midwives somehow recognize the vulnerability and compensate with extra awareness. Moreover, it is possible that unemployed women, irrespective of origin, may have more spare time to visit healthcare units than women working full‐time, which could favor the identification of SGA.
Although equality is a complex concept that cannot be fully assessed, our findings suggest that antenatal screening and identification of SGA are provided on equal terms. A possible explanation for the equality regarding the identification of SGA in the Stockholm Region is the structure of the Swedish antenatal program. Antenatal care in Sweden is highly available, free of charge, and regulated by careful national guidelines, which facilitate equality. 31 Nevertheless, we cannot rule out inequities in the subsequent management. A previous study showed that perinatal care differed by maternal ethnicity when guidelines and expert recommendations were missing. 32 Once diagnosed, the counseling of SGA/FGR pregnancies is more individualized and comprehensive, placing high demands on both the physician and the patient. Therefore, it is possible that socioeconomic and demographic inequities render more impact at a later stage of the care process.
The strengths of this study were the population‐based design and the use of nation‐wide registers with high validity and coverage, which provided detailed individual information on demographic and socioeconomic factors. All data were collected prospectively. Ultrasound reports were manually reviewed, ensuring high data validity of the outcome. The results are generalizable to similar settings with a well‐organized, highly accessible antenatal care that is free of charge. We assessed individual data on indicators of low SES one by one. In addition, to further penetrate the possible association between low SES and unidentified SGA, we tested all possible combinations of educational level, income levels and Swedish/foreign background in relation to the outcome, using intersectional regression analyses.
A limitation of the study was that women without a PIN had to be excluded. Individuals without a PIN are not included in the nationwide Swedish registers. Consequently, we had no access to their socioeconomic data. All persons who reside in Sweden on a permanent basis are assigned a PIN; hence, only recently immigrated women lacked a PIN. 21 However, these women were presumably at the highest risk of being exposed to health inequalities. There was a non‐negligible proportion of missing data on BMI, smoking, and education. Individuals with missing data on these variables were included in the analyses as separate categories; however, the precision of the estimates will still be reduced. Civil status was categorized into married, unmarried, and divorced/widowed. Today, many couples live together without being married. A better categorization would have been living alone, with a partner, or in another situation. However, marital status is a proxy for a stable relationship, which may be of importance. Another limitation was the lack of information on the postal codes of the included women, which made it impossible to individually evaluate the impact of environmental stress, that is, living in a deprived area, on the identification of SGA. This aspect would have added valuable information to our study, although we do report group‐level information on the correlation between unemployment and the proportion of unidentified SGA by municipality.
5. CONCLUSION
In settings where antenatal care is free, accessible, and guided by established protocols, women with a foreign background or those with indicators of low SES do not have increased odds of unidentified SGA pregnancies. These findings indicate that antenatal screening and identification of SGA are provided in an equitable and consistent manner. Further research is needed to clarify the underlying causes of the persisting disparities in stillbirth rates.
AUTHOR CONTRIBUTIONS
E. Hertting, L. Herling, P.G Lindqvist, and E. Wiberg‐Itzel: conceptualization; E. Hertting and P.G Lindqvist: data curation; E. Hertting and E. Wiberg‐Itzel: funding acquisition; E. Hertting, L. Herling, P.G Lindqvist, and E. Wiberg‐Itzel: methodology; L. Herling, P.G Lindqvist, and E. Wiberg‐Itzel: supervision; L. Herling, P.G Lindqvist, and E. Wiberg‐Itzel: validation; E. Hertting: formal analysis, visualization, writing—original data; L. Herling, P.G Lindqvist, and E. Wiberg‐Itzel: writing—review and editing.
FUNDING INFORMATION
This study was funded by Spädbarnsfonden (Swedish Infant Death Foundation) and by grants provided by the Stockholm County Council (ALF project). LH was funded by the Centre for Innovative Medicine (CIMED) and by the Stockholm Region.
CONFLICT OF INTEREST STATEMENT
Emma Hertting: none to declare. Lotta Herling: none to declare. Pelle G Lindqvist: none to declare. Eva Wiberg‐Itzel: none to declare.
ETHICS STATEMENT
The study was approved by the Swedish Ethical Review Authority on February 12, 2020 (Dnr 2019–04920), with amendments approved on November 6, 2020 (Dnr 2020–05295) and February 11, 2021 (Dnr 2021–00315). The data were analyzed anonymously; oral or written consent was not required.
ACKNOWLEDGMENTS
We are grateful for the professional statistical support and data management provided by Hans Pettersson and Thomas Olsson at Karolinska Institutet.
Hertting E, Herling L, Lindqvist PG, Wiberg‐Itzel E. The importance of socioeconomic factors on antenatal identification of small for gestational age pregnancies: Exploring health inequalities in the antenatal care in Sweden. Acta Obstet Gynecol Scand. 2026;105:125‐135. doi: 10.1111/aogs.70091
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author, after an approval of the Swedish Ethical Review Authority. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author, after an approval of the Swedish Ethical Review Authority. The data are not publicly available due to privacy or ethical restrictions.