Choosing a method to reduce selection bias: A tool for researchers

Selection bias is well known to affect surveys and epidemiological studies. There have been numerous methods proposed to reduce its effects, so many that researchers may be unclear which method is most suitable for their study; the wide choice may even deter some researchers, for fear of choosing a sub-optimal approach. We propose a straightforward tool to inform researchers of the most promising methods available to reduce selection bias and to assist the search for an appropriate method given their study design and details. We demonstrate the tool using three exam- ples where selection bias may occur; the tool quickly eliminates inappropriate methods and guides the researcher towards those to consider implementing. If more studies con- sider selection bias and adopt methods to reduce it, valuable time and resources will be saved, and should lead to more focused research towards disease prevention or cure

Placental blood transfusion in newborn babies reaches a plateau after 140 s: Further analysis of longitudinal survey of weight change

Objective: With the introduction of active management of the third stage of labour in the 1960s, it became usual practice to clamp and cut the umbilical cord immediately following birth. The timing of this cord clamping is controversial, as blood may beneficially be transferred to the baby if clamping of the cord is delayed slightly. There is no agreement, however, on how long the delay should be before clamping the cord. This study aimed to establish when blood ceased to flow in the umbilical cord to determine how long to delay clamping of the umbilical cord following delivery of the term newborn to maximise placental transfusion. Methods: This observational study collected longitudinal weight measurements set in a hospital labour ward. A total of 26 mothers at term and their singleton babies participated in the study. In this reanalysis, the velocity of weight change over the first minutes of life determined by functional data analysis was estimated. Results: We found that the flow velocity in the umbilical cord was on average 0 at 125 s after placing the baby on the scales, which was typically 140 s after birth. Conclusions: To maximise placental transfusion, cord clamping should be delayed for at least 140 s following birth of the baby

Development of two socioeconomic indices for Saudi Arabia

Background: Health and socioeconomic status (SES) are linked in studies worldwide. Measures of SES exist for many countries, however not for Saudi Arabia (SA). We describe two indices of area-based SES for SA. Methods: Routine census data has been used to construct two indices of SES at the geographically-delimited administrative region of Governorates in SA (n = 118). The data used included indicators of educational status, employment status, car and material ownership. A continuous measure of SES was constructed using exploratory factor analysis (EFA) and a categorical measure of SES using latent class analysis (LCA). Both indices were mapped by Governorates. Results: The EFA identified three factors: The first explained 51.58% of the common variance within the interrelated factors, the second 15.14%, and the third 14.26%. These proportions were used in the formulation of the standard index. The scores were fixed to range from 100 for the affluent Governorate and 0 for the deprived. The LCA found a 4 class model as the best model fit. Class 1 was termed "affluent" and included 11.01% of Governorates, class 2 "upper middle class" (44.91%), class 3 "lower middle class" (33.05%) and class 4 "deprived" (11.01%). The populated urbanised Governorates were found to be the most affluent whereas the smaller rural Governorates were the most deprived. Conclusion: This is the first description of measures of SES in SA at a geographical level. Two measures have been successfully constructed and mapped. The maps show similar patterns suggesting validity. Both indices support the common perception of SES in SA

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results

The importance of full participation: lessons from a national case-control study.

Differential participation between cases and controls can lead to biased estimates of risk. However, the effects of participation are often ignored. We report a detailed analysis of locations of residence for participants and non-participants in a large, national case-control study of childhood cancer in Great Britain, using the 1991 census. The initial selection of 7669 controls, taken from lists of those registered with a General Practitioner, was representative of the British population in respect to an areal-based index of material deprivation. However, parents of controls agreeing to participate were living in more affluent areas than initially selected controls and their matched 3838 cases. The three components of the deprivation index, persons unemployed, households not owning a car or their home were similarly associated with participation. Other census characteristics, such as proportion of flat dwellers and centrally heated households were also associated with control participation. Population density of the local area was not different between participating controls and their matched cases. However, initially selected controls lived in more urban areas than their cases. Such differences are not unique to this study, as they are an inevitable consequence of incomplete participation. The implications of these differences are discussed, in relation to the difficulty this imposes in the interpretation of studies of disease aetiology

Emerging technologies for the management of Type 1 diabetes in pregnancy

Purpose of Review: The purpose of the study is to discuss emerging technologies available in the management of type 1 diabetes in pregnancy. Recent Findings: The latest evidence suggests that continuous glucose monitoring (CGM) should be offered to all women on intensive insulin therapy in early pregnancy. Studies have additionally demonstrated the ability of CGM to help gain insight into specific glucose profiles as they relate to glycaemic targets and pregnancy outcomes. Despite new studies comparing insulin pump therapy to multiple daily injections, its effectiveness in improving glucose and pregnancy outcomes remains unclear. Sensor-integrated insulin delivery (also called artificial pancreas or closed-loop insulin delivery) in pregnancy has been demonstrated to improve time in target and performs well despite the changing insulin demands of pregnancy. Summary: Emerging technologies show promise in the management of type 1 diabetes in pregnancy; however, research must continue to keep up as technology advances. Further research is needed to clarify the role technology can play in optimising glucose control before and during pregnancy as well as to understand which women are candidates for sensor-integrated insulin delivery

Population mixing and incidence of cancers in adolescents and young adults between 1990 and 2013 in Yorkshire, UK

Purpose: Epidemiological evidence suggests a role for an infectious etiology for cancers in teenagers and young adults (TYAs). We investigated this by describing associations between infection transmission using the population mixing (PM) proxy and incidence of cancers in TYAs in Yorkshire, UK. Methods: We extracted cancer cases from the Yorkshire Specialist Register of Cancer in Children and Young People from 1990 to 2013 (n = 1929). Using multivariable Poisson regression models (adjusting for effects of deprivation and population density), we investigated whether PM was associated with cancer incidence. We included population mixing–population density interaction terms to examine for differences in effects of PM in urban and rural populations. Results: Nonsignificant IRRs were observed for leukemias (IRR 1.20, 95% CI 0.91–1.59), lymphomas (IRR 1.09, 95% CI 0.90–1.32), central nervous system tumors (IRR 1.06, 95% CI 0.80–1.40) and germ cell tumors (IRR 1.14, 95% CI 0.92–1.41). The association between PM and cancer incidence did not vary in urban and rural areas. Conclusions: Study results suggest PM is not associated with incidence of cancers among TYAs. This effect does not differ between rural and urban settings