Intracluster correlation coefficients for the Brazilian Multicenter Study on Preterm Birth (EMIP): methodological and practical implications

Does it decay? Obtaining decaying correlation parameter values from previously analysed cluster randomised trials

A frequently applied assumption in the analysis of data from cluster randomised trials is that the outcomes from all participants within a cluster are equally correlated. That is, the intracluster correlation, which describes the degree of dependence between outcomes from participants in the same cluster, is the same for each pair of participants in a cluster. However, recent work has discussed the importance of allowing for this correlation to decay as the time between the measurement of participants in a cluster increases. Incorrect omission of such a decay can lead to under-powered studies, and confidence intervals for estimated treatment effects can be too narrow or too wide, depending on the characteristics of the design. When planning studies, researchers often rely on previously reported analyses of trials to inform their choice of intracluster correlation. However, most reported analyses of clustered data do not incorporate a correlation decay. Thus, often all that is available are estimates of intracluster correlations obtained under the potentially incorrect assumption of no decay. In this article, we show that it is possible to use intracluster correlation values obtained from models that incorrectly omit a decay to inform plausible choices of decaying correlations. Our focus is on intracluster correlation estimates for continuous outcomes obtained by fitting linear mixed models with exchangeable or block-exchangeable correlation structures. We describe how plausible values for decaying correlations may be obtained given these estimated intracluster correlations. An online app is presented that allows users to obtain plausible values of the decay, which can be used at the trial planning stage to assess the sensitivity of sample size and power calculations to decaying correlation structures.

The spatial-temporal effect of air pollution on individuals' reported health and its variation by ethnic groups in the United Kingdom: a multilevel longitudinal analysis

BACKGROUND

Air pollution is associated with poor health; though it is unclear whether this association is stronger for ethnic minorities compared to the rest of the population. This study uses longitudinal data to investigate the spatial-temporal effect of air pollution on individuals' reported health and its variation by ethnicity in the United-Kingdom (UK).

METHODS

Longitudinal individual-level data from Understanding Society: the UK Household Longitudinal Study including 67,982 adult individuals with 404,264 repeated responses over 11 years (2009-2019) were utilized and were linked to yearly concentrations of NO₂, SO₂, and particulate-matter (PM10, PM2.5) pollution once at the local authority and once at the census Lower Super Output Area (LSOA) of residence for each individual. This allows for analysis at two geographical scales over time. The association between air pollution and individuals' health (Likert scale: 1-5, Excellent to poor) and its variation by ethnicity was assessed using three-level mixed-effects ordered logistic models. Analysis distinguished between spatial (between areas) and temporal (across time within each area) effects of air pollution on health.

RESULTS

Higher concentrations of NO₂, SO₂, PM10, and PM2.5 pollution were associated with poorer health. Decomposing air pollution into between (spatial: across local authorities or LSOAs) and within (temporal: across years within each local authority or LSOA) effects showed a significant between effect for NO₂ and SO₂ pollutants at both geographical scales, while a significant between effect for PM10 and PM2.5 was shown only at the LSOAs level. No significant within effects were detected at an either geographical level. Indian, Pakistani/Bangladeshi, Black/African/Caribbean and other ethnic groups and non-UK-born individuals reported poorer health with increasing concentrations of NO₂, SO₂, PM10, and PM2.5 pollutants in comparison to the British-white and UK-born individuals.

CONCLUSION

Using longitudinal data on individuals' health linked with air pollution data at two geographical scales (local authorities and LSOAs), this study supports the presence of a spatial-temporal association between air pollution and poor self-reported health, which is stronger for ethnic minorities and foreign-born individuals in the UK, partly explained by location-specific differences. Air pollution mitigation is necessary to improve individuals' health, especially for ethnic minorities who are affected the most.

Repeated assessments and predictors of nurses' shift-specific perceived workload

BACKGROUND

Workload perception is of interest to researchers and policymakers as it captures subjective assessments of nurses' workload which has implications for staffing and patient outcomes.

AIMS

We aimed to describe repeated assessments of nurses' perceived workload among registered nurses (RNs) in day and night shifts and to examine the association of perceived workload with workdays, units, and nurse-staffing.

METHODS

Repeated data on the indictors of interest were collected from 90 RNs across 91 shifts in a Lebanese acute-care hospital. Perceived workload was assessed using the NASA-Task-Load Index (NASA-TLX). Linear mixed-effect models were used for analysis.

RESULTS

Mean perceived workload was high reaching 6.63 (95% confidence interval [CI] = 6.34, 6.92) in day and 5.90 (95% CI = 5.43, 6.36) in night shifts. In mixed-effect models, perceived workload was lower on weekends/holidays as compared to weekdays in day (ß = -.32; 95% CI = -0.53, -0.12) and night (ß = -.46; 95% CI = -0.85, -0.07) shifts. Higher perceived workload (ß = .19; 95% CI = 0.04, 0.33) was associated with higher patient-to-nurse ratio in the day but not night shifts.

CONCLUSION

Repeated workload assessments support the presence of elevated perceived workload among RNs which is related to weekdays and higher patient-to-nurse ratio. Future investigations would benefit from better characterization of workload particularities to address perceived burden and improve organizational and management decisions.

Evaluation of the Growth Assessment Protocol (GAP) for antenatal detection of small for gestational age: The DESiGN cluster randomised trial

BACKGROUND

Antenatal detection and management of small for gestational age (SGA) is a strategy to reduce stillbirth. Large observational studies provide conflicting results on the effect of the Growth Assessment Protocol (GAP) in relation to detection of SGA and reduction of stillbirth; to the best of our knowledge, there are no reported randomised control trials. Our aim was to determine if GAP improves antenatal detection of SGA compared to standard care.

METHODS AND FINDINGS

This was a pragmatic, superiority, 2-arm, parallel group, open, cluster randomised control trial. Maternity units in England were eligible to participate in the study, except if they had already implemented GAP. All women who gave birth in participating clusters (maternity units) during the year prior to randomisation and during the trial (November 2016 to February 2019) were included. Multiple pregnancies, fetal abnormalities or births before 24+1 weeks were excluded. Clusters were randomised to immediate implementation of GAP, an antenatal care package aimed at improving detection of SGA as a means to reduce the rate of stillbirth, or to standard care. Randomisation by random permutation was stratified by time of study inclusion and cluster size. Data were obtained from hospital electronic records for 12 months prerandomisation, the washout period (interval between randomisation and data collection of outcomes), and the outcome period (last 6 months of the study). The primary outcome was ultrasound detection of SGA (estimated fetal weight <10th centile using customised centiles (intervention) or Hadlock centiles (standard care)) confirmed at birth (birthweight <10th centile by both customised and population centiles). Secondary outcomes were maternal and neonatal outcomes, including induction of labour, gestational age at delivery, mode of birth, neonatal morbidity, and stillbirth/perinatal mortality. A 2-stage cluster-summary statistical approach calculated the absolute difference (intervention minus standard care arm) adjusted using the prerandomisation estimate, maternal age, ethnicity, parity, and randomisation strata. Intervention arm clusters that made no attempt to implement GAP were excluded in modified intention to treat (mITT) analysis; full ITT was also reported. Process evaluation assessed implementation fidelity, reach, dose, acceptability, and feasibility. Seven clusters were randomised to GAP and 6 to standard care. Following exclusions, there were 11,096 births exposed to the intervention (5 clusters) and 13,810 exposed to standard care (6 clusters) during the outcome period (mITT analysis). Age, height, and weight were broadly similar between arms, but there were fewer women: of white ethnicity (56.2% versus 62.7%), and in the least deprived quintile of the Index of Multiple Deprivation (7.5% versus 16.5%) in the intervention arm during the outcome period. Antenatal detection of SGA was 25.9% in the intervention and 27.7% in the standard care arm (adjusted difference 2.2%, 95% confidence interval (CI) -6.4% to 10.7%; p = 0.62). Findings were consistent in full ITT analysis. Fidelity and dose of GAP implementation were variable, while a high proportion (88.7%) of women were reached. Use of routinely collected data is both a strength (cost-efficient) and a limitation (occurrence of missing data); the modest number of clusters limits our ability to study small effect sizes.

CONCLUSIONS

In this study, we observed no effect of GAP on antenatal detection of SGA compared to standard care. Given variable implementation observed, future studies should incorporate standardised implementation outcomes such as those reported here to determine generalisability of our findings.

TRIAL REGISTRATION

This trial is registered with the ISRCTN registry, ISRCTN67698474.

Air pollution and individuals' mental well-being in the adult population in United Kingdom: A spatial-temporal longitudinal study and the moderating effect of ethnicity

BACKGROUND

Recent studies suggest an association between ambient air pollution and mental well-being, though evidence is mostly fragmented and inconclusive. Research also suffers from methodological limitations related to study design and moderating effect of key demographics (e.g., ethnicity). This study examines the effect of air pollution on reported mental well-being in United Kingdom (UK) using spatial-temporal (between-within) longitudinal design and assesses the moderating effect of ethnicity.

METHODS

Data for 60,146 adult individuals (age:16+) with 349,748 repeated responses across 10-data collection waves (2009-2019) from "Understanding-Society: The-UK-Household-Longitudinal-Study" were linked to annual concentrations of NO2, SO2, PM10, and PM2.5 pollutants using the individuals' place of residence, given at the local-authority and at the finer Lower-Super-Output-Areas (LSOAs) levels; allowing for analysis at two geographical scales across time. The association between air pollution and mental well-being (assessed through general-health-questionnaire-GHQ12) and its modification by ethnicity and being non-UK born was assessed using multilevel mixed-effect logit models.

RESULTS

Higher odds of poor mental well-being was observed with every 10μg/m3 increase in NO2, SO2, PM10 and PM2.5 pollutants at both LSOAs and local-authority levels. Decomposing air pollution into spatial-temporal (between-within) effects showed significant between, but not within effects; thus, residing in more polluted local-authorities/LSOAs have higher impact on poor mental well-being than the air pollution variation across time within each geographical area. Analysis by ethnicity revealed higher odds of poor mental well-being with increasing concentrations of SO2, PM10, and PM2.5 only for Pakistani/Bangladeshi, other-ethnicities and non-UK born individuals compared to British-white and natives, but not for other ethnic groups.

CONCLUSION

Using longitudinal individual-level and contextual-linked data, this study highlights the negative effect of air pollution on individuals' mental well-being. Environmental policies to reduce air pollution emissions can eventually improve the mental well-being of people in UK. However, there is inconclusive evidence on the moderating effect of ethnicity.

Variability, shift-specific workloads and rationed care predictors of work satisfaction among Registered nurses providing acute care: A longitudinal study

Aims

The aim of this study was to explore nurses’ shift‐work satisfaction variability across time and its shift‐specific predictors: perceived workload, patient‐to‐nurse ratio and rationing of nursing care.

Design

Longitudinal study of 90 Registered nurses (N = 1,303 responses) in a Lebanese hospital over 91 days of data collection.

Methods

Intraclass correlation coefficients (ICCs) were computed to determine shift‐work satisfaction variability between individual nurses and working‐unit clusters. Generalized linear mixed models were used to explore the workloads and rationed care predictors of nurses’ shift‐work satisfaction separately for day and night shifts.

Results

Variability in shift‐work satisfaction was noted between individual nurses in day (ICC = 0.43) and night shifts (ICC = 0.37), but not between medical/surgical units. Nurses satisfied with their shift‐specific work were less probably to ration necessary nursing care (OR = 0.68; 95% CI = 0.60–0.77) in day shifts and to perceive high workload demands in both, day (OR = 0.29; 95% CI = 0.23–0.37) and night (OR = 0.29; 95% CI = 0.18–0.47) shifts. Monitoring and lowering workload demands while observing rationing of care is necessary to improve nurses’ shift‐work satisfaction.

Sample sizes for cluster-randomised trials with continuous outcomes: Accounting for uncertainty in a single intra-cluster correlation estimate

Sample size calculations for cluster-randomised trials require inclusion of an inflation factor taking into account the intra-cluster correlation coefficient. Often, estimates of the intra-cluster correlation coefficient are taken from pilot trials, which are known to have uncertainty about their estimation. Given that the value of the intra-cluster correlation coefficient has a considerable influence on the calculated sample size for a main trial, the uncertainty in the estimate can have a large impact on the ultimate sample size and consequently, the power of a main trial. As such, it is important to account for the uncertainty in the estimate of the intra-cluster correlation coefficient. While a commonly adopted approach is to utilise the upper confidence limit in the sample size calculation, this is a largely inefficient method which can result in overpowered main trials. In this paper, we present a method of estimating the sample size for a main cluster-randomised trial with a continuous outcome, using numerical methods to account for the uncertainty in the intra-cluster correlation coefficient estimate. Despite limitations with this initial study, the findings and recommendations in this paper can help to improve sample size estimations for cluster randomised controlled trials by accounting for uncertainty in the estimate of the intra-cluster correlation coefficient. We recommend this approach be applied to all trials where there is uncertainty in the intra-cluster correlation coefficient estimate, in conjunction with additional sources of information to guide the estimation of the intra-cluster correlation coefficient.

Imputing intracluster correlation coefficients from a posterior predictive distribution is a feasible method of dealing with unit of analysis errors in a meta-analysis of cluster RCTs

BACKGROUND

Incorporating cluster randomized trials (CRTs) into meta-analyses is challenging because appropriate standard errors of study estimates accounting for clustering are not always reported. Systematic reviews of CRTs often use a single constant external estimate of the intraclass correlation coefficient (ICC) to adjust study estimate standard errors and facilitate meta-analyses; an approach that fails to account for possible variation of ICCs among studies and the imprecision with which they are estimated. Using a large systematic review of the effects of diabetes quality improvement interventions, we investigated whether we could better account for ICC variation and uncertainty in meta-analyzed effect estimates by imputing missing ICCs from a posterior predictive distribution constructed from a database of relevant ICCs.

METHODS

We constructed a dataset of ICC estimates from applicable studies. For outcomes with two or more available ICC estimates, we constructed posterior predictive ICC distributions in a Bayesian framework. For a selected continuous outcome, glycosylated hemoglobin (HbA1c), we compared the impact of incorporating a single constant ICC versus imputing ICCs drawn from the posterior predictive distribution when estimating the effect of intervention components on post treatment mean in a case study of diabetes quality improvement trials.

RESULTS

Using internal and external ICC estimates, we were able to construct a database of 59 ICCs for 12 of the 13 review outcomes (range 1-10 per outcome) and estimate the posterior predictive ICC distribution for 11 review outcomes. Synthesized results were not markedly changed by our approach for HbA1c.

CONCLUSION

Building posterior predictive distributions to impute missing ICCs is a feasible approach to facilitate principled meta-analyses of cluster randomized trials using prior data. Further work is needed to establish whether the application of these methods leads to improved review inferences for different reviews based on different factors (e.g., proportion of CRTs and CRTs with missing ICCs, different outcomes, variation and precision of ICCs).

Intra-cluster correlations from the CLustered OUtcome Dataset bank to inform the design of longitudinal cluster trials

BACKGROUND

Sample size calculations for longitudinal cluster randomised trials, such as crossover and stepped-wedge trials, require estimates of the assumed correlation structure. This includes both within-period intra-cluster correlations, which importantly differ from conventional intra-cluster correlations by their dependence on period, and also cluster autocorrelation coefficients to model correlation decay. There are limited resources to inform these estimates. In this article, we provide a repository of correlation estimates from a bank of real-world clustered datasets. These are provided under several assumed correlation structures, namely exchangeable, block-exchangeable and discrete-time decay correlation structures.

METHODS

Longitudinal studies with clustered outcomes were collected to form the CLustered OUtcome Dataset bank. Forty-four available continuous outcomes from 29 datasets were obtained and analysed using each correlation structure. Patterns of within-period intra-cluster correlation coefficient and cluster autocorrelation coefficients were explored by study characteristics.

RESULTS

The median within-period intra-cluster correlation coefficient for the discrete-time decay model was 0.05 (interquartile range: 0.02-0.09) with a median cluster autocorrelation of 0.73 (interquartile range: 0.19-0.91). The within-period intra-cluster correlation coefficients were similar for the exchangeable, block-exchangeable and discrete-time decay correlation structures. Within-period intra-cluster correlation coefficients and cluster autocorrelations were found to vary with the number of participants per cluster-period, the period-length, type of cluster (primary care, secondary care, community or school) and country income status (high-income country or low- and middle-income country). The within-period intra-cluster correlation coefficients tended to decrease with increasing period-length and slightly decrease with increasing cluster-period sizes, while the cluster autocorrelations tended to move closer to 1 with increasing cluster-period size. Using the CLustered OUtcome Dataset bank, an RShiny app has been developed for determining plausible values of correlation coefficients for use in sample size calculations.

DISCUSSION

This study provides a repository of intra-cluster correlations and cluster autocorrelations for longitudinal cluster trials. This can help inform sample size calculations for future longitudinal cluster randomised trials.

The DESiGN trial (DEtection of Small for Gestational age Neonate), evaluating the effect of the Growth Assessment Protocol (GAP): study protocol for a randomised controlled trial

Background

Stillbirth rates in the United Kingdom (UK) are amongst the highest of all developed nations. The association between small-for-gestational-age (SGA) foetuses and stillbirth is well established, and observational studies suggest that improved antenatal detection of SGA babies may halve the stillbirth rate. The Growth Assessment Protocol (GAP) describes a complex intervention that includes risk assessment for SGA and screening using customised fundal-height growth charts. Increased detection of SGA from the use of GAP has been implicated in the reduction of stillbirth rates by 22%, in observational studies of UK regions where GAP uptake was high. This study will be the first randomised controlled trial examining the clinical efficacy, health economics and implementation of the GAP programme in the antenatal detection of SGA.

Methods/design

In this randomised controlled trial, clusters comprising a maternity unit (or National Health Service Trust) were randomised to either implementation of the GAP programme, or standard care. The primary outcome is the rate of antenatal ultrasound detection of SGA in infants found to be SGA at birth by both population and customised standards, as this is recognised as being the group with highest risk for perinatal morbidity and mortality. Secondary outcomes include antenatal detection of SGA by population centiles, antenatal detection of SGA by customised centiles, short-term maternal and neonatal outcomes, resource use and economic consequences, and a process evaluation of GAP implementation. Qualitative interviews will be performed to assess facilitators and barriers to implementation of GAP.

Discussion

This study will be the first to provide data and outcomes from a randomised controlled trial investigating the potential difference between the GAP programme compared to standard care for antenatal ultrasound detection of SGA infants. Accurate information on the performance and service provision requirements of the GAP protocol has the potential to inform national policy decisions on methods to reduce the rate of stillbirth.

Trial registration

Primary registry and trial identifying number: ISRCTN 67698474. Registered on 2 November 2016.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3242-6) contains supplementary material, which is available to authorized users.

Health related quality of life of preterm born children at three years in a sub urban district in Sri Lanka: a retrospective cohort study

Background

Preterm birth leads to multiple morbidities affecting the health of a child. Lack of information on the health impact of prematurity hinders the possibility of any effective public health interventions in this regard. Our aim was to determine the association between preterm birth and Health-Related Quality of Life (HRQOL) among 3 years old children in the Gampaha district, Sri Lanka.

Methods

A community-based retrospective cohort study was conducted among 790 preterm and term born children who were 03 years old. Multi-stage cluster sampling technique was used to identify children. The exposure status, a preterm birth, was established using the maternal pregnancy records. Outcome status was measured using a validated health related quality of life questionnaire (prepared in Sinhala) for preschool-aged children. Mothers of the children responded to an interviewer-administered questionnaire which had variables on the exposure status, outcome and additional variables such as child development status and birth related information. Quality of life was measured in twelve different domains of health (subscales). The impact was analyzed using the multiple linear regression.

Results

Response rate was 95.5% (n = 379) for preterm group and 95.2% (n = 378) for term-born group. Health-Related Quality of Life scores obtained by preterm children were lower than the term born children in eight subscales. Preterm birth showed statistically significant association with subscales on sleep wellbeing, general wellbeing and abdominal symptoms in the adjusted analysis (p < 0.05). Among preterm children prolonged illness, delayed development status, socio economic status and maternal perception on the health status of the child were common predictors of quality of life.

Conclusion

Preterm birth affected health related quality of life of preschool aged children.

EXPERIENCE WITH THE BRAZILIAN NETWORK FOR STUDIES IN REPRODUCTIVE AND PERINATAL HEALTH: THE POWER OF COLLABORATION IN POSTGRADUATE PROGRAMS

The scientific collaboration in networks may be developed among countries, academic institutions and among peer researchers. Once established, they contribute for knowledge dissemination and a strong structure for research in health. Several advantages are attributed to working in networks: the inclusion of a higher number of subjects in the studies; generation of stronger evidence with a higher representativeness of the population (secondary generalization and external validity); higher likelihood of articles derived from these studies to be accepted in high impact journals with a wide coverage; a higher likelihood of obtaining budgets for sponsorship; easier data collection on rare conditions; inclusions of subjects from different ethnic groups and cultures, among others. In Brazil, the Brazilian Network for Studies on Reproductive and Perinatal Health was created in 2008 with the initial purpose of developing a national network of scientific cooperation for the surveillance of severe maternal morbidity. Since the establishment of this Network, five studies were developed, some of them already finished and others almost being completed, and two new ones being implemented. Results of the activities in this Network have been very productive and with a positive impact on not only the Postgraduate Program of Obstetrics and Gynecology from the University of Campinas, its coordinating center, but also on other participating centers. A considerable number of scientific articles was published, master´s dissertations and PhD theses were presented, and post-doctorate programs were performed, including students from several areas of health, from distinct regions and from several institutions of the whole country. This represents a high social impact taking into account the relevance of the studied topics for the country. As colaborações científicas em rede podem ocorrer entre países, instituições acadêmicas e entre pares de pesquisadores e, uma vez estabelecidas, contribuem para a disseminação do conhecimento e estruturação da pesquisa em saúde. Diversas vantagens são atribuídas ao trabalho em rede como: a inclusão de maior número de participantes nos estudos; gerar evidências mais fortes e com maior representatividade da população (generalização secundária e validade externa); maior facilidade das publicações oriundas dos estudos serem aceitas em periódicos de impacto e abrangência; maior probabilidade de obtenção de verbas para financiamento; maior facilidade na coleta de dados sobre condições raras; inclusão de participantes de diferentes grupos étnicos e culturas, entre outras. No Brasil a Rede Brasileira de Estudos em Saúde Reprodutiva e Perinatal foi criada em 2008 com o objetivo inicial de desenvolver rede nacional de cooperação científica para vigilância da morbidade materna grave. Desde sua formação, cinco estudos foram desenvolvidos, alguns já encerrados e outros em fase de finalização, com outros dois em fase final de implantação. Os resultados das atividades desta Rede têm sido bastante produtivos e impactaram positivamente não apenas no Programa de Pós-Graduação em Tocoginecologia da Universidade Estadual de Campinas, seu centro coordenador, mas também o de outros centros participantes, uma vez que expressivo número de artigos científicos foi publicado, mestrados e doutorados foram defendidos e pós-doutorados finalizados, de alunos de diversas áreas da saúde, de diferentes regiões e de várias instituições de todo o país, com alto impacto social dada a relevância dos temas estudados para o país.

The Burden of Provider-Initiated Preterm Birth and Associated Factors: Evidence from the Brazilian Multicenter Study on Preterm Birth (EMIP)

Background

About 15 million children are born under 37 weeks of gestation worldwide. Prematurity is the leading cause of neonatal deaths and short/long term morbidities, entailing consequences not only for the individual, but also their family, health agencies, facilities and all community. The provider-initiated preterm birth is currently one of the most important obstetric conditions related to preterm births, particularly in middle and high income countries, thus decreasing the need for therapeutic preterm birth is essential to reduce global prematurity. Therefore detailed knowledge on the factors associated with provider-initiated preterm birth is essential for the efforts to reduce preterm birth rates and its consequences. In this current analysis we aimed to assess the proportion of provider-initiated (pi-PTB) among preterm births in Brazil and identify associated factors.

Methods and Findings

This is an analysis of a multicenter cross-sectional study with a nested case-control component called Brazilian Multicenter Study on Preterm Birth (EMIP). EMIP was conducted in 20 referral obstetric hospitals located in the three most populated of the five Brazilian regions. We analysed data of women with pi-PTB, defined as childbirth occurring at less than 37 weeks, medically indicated for maternal/fetal compromise or both; and women with term birth, childbirth at or after 37 weeks. Maternal, sociodemographic, obstetric, prenatal care, delivery, and postnatal characteristics were assessed as possible factors associated with pi-PTB, compared to term births. The overall prevalence of preterm births was 12.3%. Of these, approximately one-third of cases were initiated by the provider. Hypertensive disorders, placental abruption, and diabetes were the main maternal conditions leading to pi-PTB. Caesarean section was the most common mode of delivery. Chronic hypertension (OR 7.47; 95%CI 4.02–13.88), preeclampsia/eclampsia/HELLP syndrome (OR 15.35; 6.57–35.88), multiple pregnancy (OR 12.49; 4.86–32.05), and chronic diabetes (OR 5.24; 2.68–10.25) were the most significant factors independently associated with pi-PTB.

Conclusions

pi-PTB is responsible for about one-third of all preterm births, requiring special attention. The decision-making process relative to the choice of provider-initiated birth is complex, and many factors should be elucidated to improve strategies for its prevention, including evidence-based guidelines on proper management of the corresponding clinical conditions.

Methodological issues on planning and running the Brazilian Multicenter Study on Preterm Birth

OBJECTIVES

Assuming that the occurrence of preterm births and their maternal and neonatal associated conditions in Brazil are not completely known, a multicenter study was proposed. The purpose of this paper is to describe the methods used, its processes, achievements, and challenges.

STUDY DESIGN

A multicenter cross-sectional study on preterm births in Brazilian facilities plus a nested case-control study to assess their associated factors. A description of all steps of planning and implementing such a nationwide study, including strategies for dealing with problems arising during the process, is presented.

RESULTS

20 referral hospitals in different regions of Brazil participated in the study. A detailed questionnaire for data collection, an electronic platform for data transcription and monitoring, research materials, and specific monitoring tools were developed; then data management and analyses were performed. Finally, we got information on 4,150 preterm births and 1,146 term births.

CONCLUSIONS

This study represented the first step of a planned comprehensive assessment of preterm birth in Brazil, with detailed information that will lead to several analyses and further studies, bringing the knowledge to improve screening, diagnosis, and treatment practices in maternal and perinatal health with the final purpose of reducing the burden of this condition in the country.

Brazilian multicentre study on preterm birth (EMIP): prevalence and factors associated with spontaneous preterm birth

BACKGROUND

Preterm birth rate is increasing and is currently a worldwide concern. The purpose of this study was to estimate the prevalence of preterm birth in a sample of health facilities in Brazil and to identify the main risk factors associated with spontaneous preterm births.

METHODS AND FINDINGS

This was a multicentre cross sectional study on preterm births in 20 referral obstetric hospitals with a case-control component to identify factors associated with spontaneous preterm birth. Surveillance was implemented at all centres to identify preterm births. For eligible consenting women, data were collected through a post-delivery questionnaire completed with information from all mother-newborn medical records until death or discharge or at a maximum of 60 days post-delivery, whichever came first. The risk of spontaneous preterm birth was estimated with OR and 95%CI for several predictors. A non-conditional logistic regression analysis was then performed to identify independently associated factors. The overall prevalence of preterm birth was 12.3%. Among them, 64.6% were spontaneous and 35.4% therapeutic. In the case-control component, 2,682 spontaneous preterm births were compared to a sample of 1,146 term births. Multivariate analyses identified the following as risk factors for spontaneous preterm birth among women with at least one previous birth: a previous preterm birth (ORadj = 3.19, 2.30-4.43), multiple pregnancy (ORadj = 29.06, 8.43-100.2), cervical insufficiency (ORadj = 2.93, 1.07-8.05), foetal malformation (ORadj = 2.63, 1.43-4.85), polyhydramnios (ORadj = 2.30, 1.17-4.54), vaginal bleeding (ORadj = 2.16, 1.50-3.11), and previous abortion (ORadj = 1.39, 1.08-1.78). High BMI (ORadj = 0.94, 0.91-0.97) and weight gain during gestation (ORadj = 0.92, 0.89-0.95) were found to be protective factors.

CONCLUSIONS

The preterm birth rate in these health facilities in Brazil is high and spontaneous preterm births account for two thirds of them. A better understanding of the factors associated with spontaneous preterm birth is of utmost importance for planning effective measures to reduce the burden of its increasing rates.