Twin Peaks: A spatial and temporal study of twinning rates in Brazil

<div><p>Twin births are an important public health issue due to health complications for both mother and children. While it is known that contemporary factors have drastically changed the epidemiology of twins in certain developed countries, in Brazil, relevant data are still scarce. Thus, we carried out a population-based study of live births in spatial and temporal dimensions using data from Brazil's Live Birth Information System, which covers the entire country. Over 41 million births registered between 2001 and 2014 were classified as singleton, twin or multiple. Twinning rates (TR) averaged 9.41 per 1,000 for the study period and a first-order autoregressive model of time-series analysis revealed a global upward trend over time; however, there were important regional differences. In fact, a Cluster and Outlier Analysis (Anselin Local Moran's I) was performed and identified clusters of high TR in an area stretching from the south of Brazil's Northeast Region to the South Region (Global Moran Index = 0.062, <i>P</i> < 0.001). Spearman's correlation coefficient and a Wilcoxon matched pairs test revealed a positive association between Human Development Index (HDI) and TRs in different scenarios, suggesting that the HDI might be an important indicator of childbearing age and assisted reproduction techniques in Brazil. Furthermore, there was a sharp increase of 26.42% in TR in women aged 45 and over during study period. The upward temporal trend in TRs is in line with recent observations from other countries, while the spatial analysis has revealed two very different realities within the same country. Our approach to TR using HDI as a proxy for underlying socioeconomic changes can be applied to other developing countries with regional inequalities resembling those found in Brazil.</p></div

Cluster and Outlier analysis.

<p>(A) Distribution of average Twinning Rates (TRs) across Brazilian municipalities. (B) Distribution of Human Development Index (HDI) figures from the 2000 census across Brazilian municipalities. (C) Spatial correlation index from normalized average TR and 2010's HDI across Brazilian municipalities. The cartographic database used for the construction of the map is publicly accessible on the IBGE website [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0200885#pone.0200885.ref019" target="_blank">19</a>].</p

Brazilian twinning rates for the period from 2001 to 2014.

<p>In addition to the individual values for 2001 and 2014, the average value, percentage variation, standard deviation and the parameters estimated in the autoregressive (AR) models are also shown.</p

Geographical features of Brazil.

<p>The map follows the geographical division, including regions and states mentioned in the paper, of the Brazilian Institute of Geography and Statistics–IBGE (Instituto Brasileiro de Geografia e Estatística). The underlying cartographic database is publicly accessible on the IBGE website [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0200885#pone.0200885.ref019" target="_blank">19</a>].</p

Maternal age and twinning.

<p>TRs among different classes of maternal age in Brazil, 2001–2014.</p

Temporal distribution.

<p>Singleton, twin and multiple birth rates per 1,000 births in Brazil, 2001–2014.</p

Multiple linear regression of the difference (Δ) between self-perceived and genetically estimated ancestry for the three continental components.

<p>NOTE: Δ refers to self-perception (bands 1 to 5, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#s4" target="_blank">Methods</a>) minus continental ancestry proportions (0–100%) estimated from the genetic data. Sex and country of sampling were incorporated in the analyses as factors while the other variables were treated as quantitative. For ease of interpretation, the regression coefficient and p-value for Δ AMERICA (*) refer to Native American (not European) ancestry.</p><p>Multiple linear regression of the difference (Δ) between self-perceived and genetically estimated ancestry for the three continental components.</p

Bar plots contrasting skin pigmentation (Melanin Index) to proportion of European genetic ancestry across four self-identified ethno/racial categories in samples from Brazil, Chile, Colombia, México and Perú.

<p>Sample sizes and all estimates of pigmentation and ancestry, are presented in Table S4. In Perú no individual self-identified as “Black”.</p

Sample size, proportion of women, age, estimated admixture proportions and phenotypic features of the study sample.

<p>Note: Values shown are medians except for categorical traits where the numbers indicate percentages in that category. Data for women is shown in the numerator (except for Male pattern baldness). For the regression analyses (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#pgen-1004572-t002" target="_blank">Tables 2</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#pgen-1004572-t003" target="_blank">3</a> below) categorical phenotypes 15–17 were considered ordinal variables with 4 or 5 ordered integer levels as specified here (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#s4" target="_blank">Methods</a>). Individual ancestry histograms for each country are presented in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#pgen.1004572.s011" target="_blank">Text S1</a>.</p><p>Sample size, proportion of women, age, estimated admixture proportions and phenotypic features of the study sample.</p

Multiple linear regression of physical appearance traits on European and African ancestry.

<p>Note: All regressions account for age, sex, country, education and wealth. Regressions for facial features (traits 13 to 18) also account for BMI and height. %R² refers to trait variance explained by a regression model incorporating European and African ancestry (being proportions, European, African and American ancestries sum up to 1 and since in this sample African ancestry is very low (median of 7%), we use Native American ancestry as a baseline). %Δ R² refers to the difference in variance explained by this full model and a model without ancestry as a predictor. P-Values <10⁻³ are shown in bold italic. The facial features (traits 13 to 18) refer to morphogeometric summaries of face variation derived from 3D landmark coordinates (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004572#s4" target="_blank">Methods</a>). PC = Principal Components of the procrustes 3D landmark coordinates (% in parenthesis refer to variance explained by that PC).</p><p>Multiple linear regression of physical appearance traits on European and African ancestry.</p