Does Maternal Country of Birth Matter for Understanding Offspring's Birthweight? A Multilevel Analysis of Individual Heterogeneity in Sweden

Mapping socio-geographical disparities in the occurrence of teenage maternity in Colombia using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

BACKGROUND

The prevalence of teenage pregnancy in Colombia is higher than the worldwide average. The identification of socio-geographical disparities might help to prioritize public health interventions.

AIM

To describe variation in the probability of teenage maternity across geopolitical departments and socio-geographical intersectional strata in Colombia.

METHODS

A cross-sectional study based on live birth certificates in Colombia. Teenage maternity was defined as a woman giving birth aged 19 or younger. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was applied using multilevel Poisson and logistic regression. Two different approaches were used: (1) intersectional: using strata defined by the combination of health insurance, region, area of residency, and ethnicity as the second level (2) geographical: using geopolitical departments as the second level. Null, partial, and full models were obtained. General contextual effect (GCE) based on the variance partition coefficient (VPC) was considered as the measure of disparity. Proportional change in variance (PCV) was used to identify the contribution of each variable to the between-strata variation and to identify whether this variation, if any, was due to additive or interaction effects. Residuals were used to identify strata with potential higher-order interactions.

RESULTS

The prevalence of teenage mothers in Colombia was 18.30% (95% CI 18.20-18.40). The highest prevalence was observed in Vichada, 25.65% (95% CI: 23.71-27.78), and in the stratum containing mothers with Subsidized/Unaffiliated healthcare insurance, Mestizo, Rural area in the Caribbean region, 29.08% (95% CI 28.55-29.61). The VPC from the null model was 1.70% and 9.16% using the geographical and socio-geographical intersectional approaches, respectively. The higher PCV for the intersectional model was attributed to health insurance. Positive and negative interactions of effects were observed.

CONCLUSION

Disparities were observed between intersectional socio-geographical strata but not between geo-political departments. Our results indicate that if resources for prevention are limited, using an intersectional socio-geographical approach would be more effective than focusing on geopolitical departments especially when focusing resources on those groups which show the highest prevalence. MAIHDA could potentially be applied to many other health outcomes where resource decisions must be made.

Does emigration by itself improve birth weight? Study in European newborns of Indo-Pakistan origin

Objective

Our aim was to evaluate the effect of emigration on fetal birth weight (BW) in a group of pregnant women coming from the Indian subcontinent.

Methods

This was a retrospective study in a mixed population of pregnant women from the Indian subcontinent that either moved to Europe or stayed in their original countries. The influence of emigration along with several pregnancy characteristics: GA at delivery, fetal gender, maternal age, height, weight, body mass index (BMI) and parity on BW was evaluated by means of multivariable linear regression analysis.

Results

According to European standards, babies born to Indo-Pakistan emigrants and babies born to women staying in the Indian subcontinent were similarly small (BW centile 30± 29 and 30.1 ± 28, p<0.68). Multivariable regression demonstrated that emigration by itself did not exert a direct influence on BW (p  = 0.27), being BMI and gestational age at delivery the true determinants of BW (p<0.0001).

Conclusions

Maternal BMI is the most relevant parameter affecting fetal growth regardless of the place of residence.

Offspring birthweight and placental weight in immigrant women from conflict-zone countries; does length of residence in the host country matter? A population study in Norway

INTRODUCTION

We aimed to estimate differences in offspring birthweight and placental weight between Norwegian women and immigrants in Norway from countries with armed conflicts. We also studied whether length of residence in Norway was associated with offspring birthweight and placental weight.

MATERIAL AND METHODS

We included in our study all singleton births in Norway at gestational week 28 or beyond during the years 1999-2014, to mothers who were born in Somalia, Afghanistan, Iraq (total immigrants n = 18 817), or Norway (n = 668 439). Data were obtained from The Medical Birth Registry of Norway and the Central Person Registry of Norway. We estimated the differences between Norwegian and immigrant women in mean offspring birthweight and mean placental weight by applying linear regression analyses. Adjustments were made for maternal age, parity, year of delivery, gestational age at delivery, preeclampsia, and diabetes.

RESULTS

The immigrant women had 206 g (95% CI 199 to 213 g) lower mean offspring birthweight and 16 g (95% CI 14 to 18 g) lower mean placental weight than Norwegian women. Immigrant women with ≥5 years of residence in Norway had higher offspring birthweight (40 g) and higher placental weight (17 g) than immigrant women with <5 years of residence.

CONCLUSIONS

Immigrant mothers from Somalia, Afghanistan, and Iraq gave birth to infants and placentas with lower weight than Norwegian women. However, the difference between Norwegian women and immigrant women was reduced by length of residence in Norway.

Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches

Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health.

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health

BACKGROUND AND AIM

Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between "specific" (measures of association) and "general" (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health.

METHODS

We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics.

RESULTS

For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%.

CONCLUSION

Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood "effects" are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level.

Birth-weight charts and immigrant populations: A critical review

There is an increasing body of literature focusing on differences in newborn size between different population subgroups defined by racial, ethnic, and immigration status. The interpretation of these differences as pathological or as merely reflecting normal variability is not straightforward and may have consequences for the provision of obstetric and neonatal care to minority populations. In this review, we critically assess some methodological issues affecting the assessment of newborn size and their potential implications for minority populations. In particular, we discuss the pros and cons of different types of newborn birth-weight (BW) charts (i.e., single local population-based references, minority-specific references, and a single international standard) to determine abnormal newborn size, with emphasis on immigrant populations. We conclude that size alone is not enough to inform clinical decisions and that all newborn size charts should be used as screening tools, not as diagnostic tools. Parental minority status may be regarded as a marker and used to further inquire about individual risk factors, particularly among immigrants who may not have a complete medical history in the new country. Finally, we outline areas for further research and recommendations for clinical practice.