RESUMO
Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.
Assuntos
Registro Médico Coordenado , Humanos , Viés , Estudos Epidemiológicos , Bases de Dados Factuais , Brasil/epidemiologiaRESUMO
OBJECTIVES: Dengue is the most common viral mosquito-borne disease, and women of reproductive age who live in or travel to endemic areas are at risk. Little is known about the effects of dengue during pregnancy on birth outcomes. The objective of this study is to examine the effect of maternal dengue severity on live birth outcomes. DESIGN AND SETTING: We conducted a population-based cohort study using routinely collected Brazilian data from 2006 to 2012. PARTICIPATING: We linked birth registration records and dengue registration records to identify women with and without dengue during pregnancy. Using multinomial logistic regression and Firth method, we estimated risk and ORs for preterm birth (<37 weeks' gestation), low birth weight (<2500 g) and small for gestational age (<10thcentile). We also investigated the effect of time between the onset of the disease and each outcome. RESULTS: We included 16 738 000 live births. Dengue haemorrhagic fever was associated with preterm birth (OR=2.4; 95% CI 1.3 to 4.4) and low birth weight (OR=2.1; 95% CI 1.1 to 4.0), but there was no evidence of effect for small for gestational age (OR=2.1; 95% CI 0.4 to 12.2). The magnitude of the effects was higher in the acute disease period. CONCLUSION: This study showed an increased risk of adverse birth outcomes in women with severe dengue during pregnancy. Medical intervention to mitigate maternal risk during severe acute dengue episodes may improve outcomes for infants born to exposed mothers.
Assuntos
Dengue/complicações , Recém-Nascido de Baixo Peso , Nascido Vivo , Complicações Infecciosas na Gravidez/virologia , Nascimento Prematuro/etiologia , Adulto , Brasil , Estudos de Coortes , Feminino , Idade Gestacional , Humanos , Recém-Nascido , Recém-Nascido Pequeno para a Idade Gestacional , Modelos Logísticos , Gravidez , Web Semântica , Adulto JovemRESUMO
BACKGROUND: Linking routinely-collected data provides an opportunity to measure the effects of exposures that occur before birth on maternal, fetal and infant outcomes. High quality linkage is a prerequisite for producing reliable results, and there are specific challenges in mother-baby linkage. Using population-based administrative databases from Brazil, this study aimed to estimate the accuracy of linkage between maternal deaths and birth outcomes and dengue notifications, and to identify potential sources of bias when assessing the risk of maternal death due to dengue in pregnancy. METHODS: We identified women with dengue during pregnancy in a previously linked dataset of dengue notifications in women who had experienced a live birth or stillbirth during 2007-2012. We then linked this dataset with maternal death records probabilistically using maternal name, age and municipality. We estimated the accuracy of the linkage, and examined the characteristics of false-matches and missed-matches to identify any sources of bias. RESULTS: Of the 10,259 maternal deaths recorded in 2007-2012, 6717 were linked: 5444 to a live birth record, 1306 to a stillbirth record, and 33 to both a live and stillbirth record. After identifying 2620 missed-matches and 124 false-matches, our estimated sensitivity was 72%, specificity was 88%, and positive predictive value was 98%. Linkage errors were associated with maternal education and self-identified race; women with more than 7 years of education or who self-declared as Caucasian were more likely to link. Dengue status was not associated with linkage error. CONCLUSION: Despite not having unique identifiers to link mothers and birth outcomes, we demonstrated a high standard of linkage, with sensitivity and specificity values comparable to previous literature. Although there were no differences in the characteristics of dengue cases missed or included in our linked dataset, linkage error occurred disproportionally by some social-demographic characteristics, which should be taken into account in future analyses.
Assuntos
Declaração de Nascimento , Bases de Dados Factuais , Atestado de Óbito , Registro Médico Coordenado , Adulto , Brasil/epidemiologia , Bases de Dados Factuais/estatística & dados numéricos , Dengue/complicações , Dengue/epidemiologia , Dengue/mortalidade , Feminino , Humanos , Recém-Nascido , Nascido Vivo/epidemiologia , Masculino , Morte Materna/estatística & dados numéricos , Mortalidade Materna , Gravidez , Complicações Infecciosas na Gravidez/epidemiologia , Complicações Infecciosas na Gravidez/mortalidade , Resultado da Gravidez , Efeitos Tardios da Exposição Pré-Natal/epidemiologia , Sistema de Registros , Natimorto/epidemiologiaRESUMO
Dengue is a mosquito-borne disease with major public health importance due to its growing incidence and geographical spread. There is a lack of knowledge on its contribution to maternal death. We conducted a population-based cohort study to investigate the association between symptomatic dengue during pregnancy and deaths in Brazil from 2007 to 2012. We did this by linking routine records of confirmed dengue cases to records of deaths of women who had a live birth. Using the Firth method, we estimated odds ratios for maternal deaths associated with dengue during pregnancy. Dengue increased the risk of maternal death by 3 times (95%CI,1.5-5.8) and dengue haemorrhagic fever increased the risk of maternal death by 450 times (95%CI,186.9-1088.4) when compared to mortality of pregnant women without dengue. The increase in risk occurred mostly during acute dengue 71.5 (95%CI,32.8-155.8), compared with no dengue cases. This study showed an increased risk of adverse outcomes in pregnant women with dengue. Therefore in areas where dengue is circulating, the health of pregnant women should be not only a public health priority, but health professionals attending pregnant women with dengue should more closely observe these patients to be able to intervene in a timely way and avoid deaths.
Assuntos
Dengue/mortalidade , Complicações Infecciosas na Gravidez/mortalidade , Adulto , Brasil/epidemiologia , Estudos de Coortes , Feminino , Humanos , Mortalidade Materna , Gravidez , Adulto JovemRESUMO
BACKGROUND: Maternal infections during pregnancy can increase the risk of fetal death. Dengue infection is common, but little is known about its role in fetal mortality. We aimed to investigate the association between symptomatic dengue infection during pregnancy and fetal death. METHODS: We did a nested case-control study using obstetrician-collected data from the Brazilian livebirth information system (SINASC), the mortality information system (SIM), and the national reportable disease information system (SINAN). We identified all pregnancies ending in stillbirth and a random sample of livebirths between Jan 1, 2006, and Dec 31, 2012. We did linkage to determine which mothers were diagnosed with dengue infection during pregnancy. By use of stillbirths as cases and a sample of matched livebirths as a control, we calculated matched odds ratios (mORs) using conditional logistic regression adjusted for maternal age and education. FINDINGS: 275 (0·2%) of 162â188 women who had stillbirths and 1507 (0·1%) of 1â586â105 women who had livebirths were diagnosed with dengue infection during pregnancy. Symptomatic dengue infection during pregnancy almost doubled the odds of fetal death (mOR 1·9, 95% CI 1·6-2·2). The increase in risk was similar when analyses were restricted to laboratory-confirmed cases of dengue infection (1·8, 1·4-2·4). Severe dengue infection increased the risk of fetal death by about five times (4·9, 2·3-10·2). INTERPRETATION: Symptomatic dengue infection during pregnancy is associated with an increased risk of fetal death. We recommend further epidemiological and biological studies of the association between dengue and poor birth outcomes to measure the burden of subclinical infections and elucidate pathological mechanisms. FUNDING: Brazilian National Council for Scientific and Technological Development, Horizon 2020.
Assuntos
Estudos de Casos e Controles , Dengue/complicações , Complicações Infecciosas na Gravidez , Resultado da Gravidez , Adulto , Brasil , Feminino , Morte Fetal , Humanos , Recém-Nascido , Gravidez , Estudos Retrospectivos , Fatores de Risco , NatimortoRESUMO
BACKGROUND: Due to the increasing availability of individual-level information across different electronic datasets, record linkage has become an efficient and important research tool. High quality linkage is essential for producing robust results. The objective of this study was to describe the process of preparing and linking national Brazilian datasets, and to compare the accuracy of different linkage methods for assessing the risk of stillbirth due to dengue in pregnancy. METHODS: We linked mothers and stillbirths in two routinely collected datasets from Brazil for 2009-2010: for dengue in pregnancy, notifications of infectious diseases (SINAN); for stillbirths, mortality (SIM). Since there was no unique identifier, we used probabilistic linkage based on maternal name, age and municipality. We compared two probabilistic approaches, each with two thresholds: 1) a bespoke linkage algorithm; 2) a standard linkage software widely used in Brazil (ReclinkIII), and used manual review to identify further links. Sensitivity and positive predictive value (PPV) were estimated using a subset of gold-standard data created through manual review. We examined the characteristics of false-matches and missed-matches to identify any sources of bias. RESULTS: From records of 678,999 dengue cases and 62,373 stillbirths, the gold-standard linkage identified 191 cases. The bespoke linkage algorithm with a conservative threshold produced 131 links, with sensitivity = 64.4% (68 missed-matches) and PPV = 92.5% (8 false-matches). Manual review of uncertain links identified an additional 37 links, increasing sensitivity to 83.7%. The bespoke algorithm with a relaxed threshold identified 132 true matches (sensitivity = 69.1%), but introduced 61 false-matches (PPV = 68.4%). ReclinkIII produced lower sensitivity and PPV than the bespoke linkage algorithm. Linkage error was not associated with any recorded study variables. CONCLUSION: Despite a lack of unique identifiers for linking mothers and stillbirths, we demonstrate a high standard of linkage of large routine databases from a middle income country. Probabilistic linkage and manual review were essential for accurately identifying cases for a case-control study, but this approach may not be feasible for larger databases or for linkage of more common outcomes.