Journal articles: 'Longitudinal cohort data'

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Golding, Jean, and Richard Jones. "Sources of data for a longitudinal birth cohort." Paediatric and Perinatal Epidemiology 23 (July 2009): 51–62. http://dx.doi.org/10.1111/j.1365-3016.2008.00996.x.

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Prahl-Andersen, B., and C. Kowalski. "Analysis of Cohort Effects in Mixed Longitudinal Data Sets." International Journal of Sports Medicine 18, S 3 (July 1997): S186—S190. http://dx.doi.org/10.1055/s-2007-972712.

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de Frias, Cindy M., Martin Lövdén, Ulman Lindenberger, and Lars-Göran Nilsson. "Revisiting the dedifferentiation hypothesis with longitudinal multi-cohort data." Intelligence 35, no. 4 (July 2007): 381–92. http://dx.doi.org/10.1016/j.intell.2006.07.011.

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Choi, Kilchan, and Jinok Kim. "Latent Variable Regression Four-Level Hierarchical Model Using Multisite Multiple-Cohort Longitudinal Data." Journal of Educational and Behavioral Statistics 44, no. 5 (July 31, 2019): 597–624. http://dx.doi.org/10.3102/1076998619864538.

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This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of change, arising from individual student over grades, and successive cohorts in the same grade over years. In addition, as an extension of Choi and Seltzer, the LVR coefficients, that is, gap-in-time parameter, capturing the relationships between initial status and rates of changes within each cohort and school, help bring to light the distribution of student growth and differences in the distribution over different cohorts within schools. Advantages associated with the LVR-HM4 can be highlighted in studies on monitoring school performance or evaluations of policies and practices that may target different aspects of student academic performance such as initial status, growth, or gap over time in schools.

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Hsu, Chih-Hsiung, Yu-Jyun Lin, Yong-Chen Chen, I.-Lan Liu, San-Lin You, Je-Ming Hu, Tzu-Chiao Lin, et al. "Human Papillomavirus and Risk of Colorectal Cancer: An Analysis of Nationwide Claims Data." Medicina 58, no. 10 (October 15, 2022): 1461. http://dx.doi.org/10.3390/medicina58101461.

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Background and Objectives: Although human papillomavirus (HPV) is a major etiology of cervical and anogenital cancers, whether it is associated with colorectal carcinogenesis is yet undetermined. Materials and Methods: The longitudinal association of HPV infection with colorectal cancer (CRC) was evaluated using 2000–2013 data from a nationwide Taiwanese claims database. In this retrospective cohort study, 358 patients with primary HPV diagnoses (HPV-infected cohort) and 1432 patients without such a diagnosis (HPV-uninfected cohort) were recruited between 2000 and 2006. Both cohorts were followed up to identify CRC incidences from 2006 to 2013. Hazard ratios (HRs) and their 95% confidence intervals (CIs) derived from Cox proportional hazards models were used to estimate the association between HPV and CRC risk. Results: The HPV-infected cohort had a significantly higher cumulative incidence of CRC than the HPV-uninfected cohort. The presence of HPV was associated with an increased risk of CRC (adjusted HR, 1.63; 95% CI, 1.02–3.62). Furthermore, the significant HPV–CRC risk association was evident in both sexes. Conclusions: This population-based cohort study reveals longitudinal evidence that HPV is associated with an increased risk of CRC. Further studies are required to verify the role of HPV in colorectal carcinogenesis.

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Stasny, Elizabeth A., and Jacques A. Hagenaars. "Categorical Longitudinal Data: Log-Linear Panel, Trend, and Cohort Analysis." Journal of the American Statistical Association 88, no. 421 (March 1993): 377. http://dx.doi.org/10.2307/2290739.

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O’Neill, Dara, Michaela Benzeval, Andy Boyd, Lisa Calderwood, Cyrus Cooper, Louise Corti, Elaine Dennison, et al. "Data Resource Profile: Cohort and Longitudinal Studies Enhancement Resources (CLOSER)." International Journal of Epidemiology 48, no. 3 (February 20, 2019): 675–76. http://dx.doi.org/10.1093/ije/dyz004.

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Alemzadeh, S., U. Niemann, T. Ittermann, H. Völzke, D. Schneider, M. Spiliopoulou, K. Bühler, and B. Preim. "Visual Analysis of Missing Values in Longitudinal Cohort Study Data." Computer Graphics Forum 39, no. 1 (May 21, 2019): 63–75. http://dx.doi.org/10.1111/cgf.13662.

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Eliason, Scott R., and Jacques A. Hagenaars. "Categorical Longitudinal Data: Log-Linear Panel, Trend, and Cohort Analysis." Journal of Educational and Behavioral Statistics 20, no. 1 (1995): 103. http://dx.doi.org/10.2307/1165391.

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Richards, John D. "Categorical longitudinal data; Log-linear panel, trend, and cohort analysis,." Evaluation Practice 14, no. 1 (February 1993): 73–75. http://dx.doi.org/10.1016/0886-1633(93)90039-r.

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Suzman, Richard, and Sarah Harper. "Editorial: Dawning of a New Age for Longitudinal Cohort Data." Journal of Population Ageing 6, no. 1-2 (April 13, 2013): 1–4. http://dx.doi.org/10.1007/s12062-013-9083-2.

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Finkel, Deborah, and Marie Ernsth Bravell. "Cohort by Education Interactions in Longitudinal Changes in Functional Abilities." Journal of Aging and Health 32, no. 3-4 (November 23, 2018): 208–15. http://dx.doi.org/10.1177/0898264318814108.

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Objective: Investigations of cohort differences in relationships between education and health tend to focus on mortality or self-reported health. We report one of the first analyses of cohort differences in relationships between education and objective measures of functional abilities across the lifespan. Method: Up to 26 years of follow-up data were available from 859 adults from the Swedish Adoption/Twin Study of Aging. The sample was divided into two cohorts by birth year: 1900-1924 and 1925-1948. Latent growth curve models (LGCM) were compared across cohort and educational levels. Results: LGCM indicated divergence between adults with lower and higher educational attainment in longitudinal trajectories of change with age in the Balance and Flexibility factors for the later born cohort only. Discussion: Results support the cumulative advantage theory and suggest that education–health disparities are increasing in recent cohorts, even in counties with national health care systems and strong support of education.

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Zvoch, Keith, and Joseph J. Stevens. "Successive Student Cohorts and Longitudinal Growth Models: An Investigation of Elementary School Mathematics Performance." education policy analysis archives 14 (January 20, 2006): 2. http://dx.doi.org/10.14507/epaa.v14n2.2006.

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Mathematics achievement data from three longitudinally matched student cohorts were analyzed with multilevel growth models to investigate the viability of using status and growth-based indices of student achievement to examine the multi-year performance of schools. Elementary schools in a large southwestern school district were evaluated in terms of the mean achievement status and growth of students across cohorts as well as changes in the achievement status and growth of students between student cohorts. Results indicated that the cross and between-cohort performance of schools differed depending on whether the mean achievement status or growth of students was considered. Results also indicated that the cross-cohort indicators of school performance were more reliably estimated than their between-cohort counterparts. Further examination of the performance indices revealed that cross-cohort achievement status estimates were closely related to student demographics while between-cohort estimates were associated with cohort enrollment size and cohort initial performance status. Of the four school performance indices studied, only student growth in achievement (averaged across cohorts) provided a relatively reliable and unbiased indication of school performance. Implications for the No Child Left Behind school accountability framework are discussed.

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Jivraj, Stephen, Alissa Goodman, George B. Ploubidis, and Cesar de Oliveira. "Testing Comparability Between Retrospective Life History Data and Prospective Birth Cohort Study Data." Journals of Gerontology: Series B 75, no. 1 (April 21, 2017): 207–17. http://dx.doi.org/10.1093/geronb/gbx042.

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Abstract Objectives To determine whether comparable prospective and retrospective data present the same association between childhood and life course exposures and mid-life wellbeing. Method Prospective data is taken from the 1958 UK National Child Development Study at age 50 in 2008 and earlier sweeps (n = 8,033). Retrospective data is taken from the English Longitudinal Study of Ageing at ages 50–55 from a life history interview in 2007 (n = 921). Results There is a high degree of similarity in the direction of association between childhood exposures that have been prospectively collected in National Child Development Study and retrospectively collected in English Longitudinal Study of Ageing and wellbeing outcomes in mid-life. However, the magnitude of these associations is attenuated substantially by the inclusion of measurements, which are difficult or impossible to capture retrospectively, and are only available in prospective data, such as childhood poverty, cognitive ability, and indices of social and emotional adjustment. Discussion The findings on the one hand provide some reassurance to the growing literature using life history data to determine life course associations with later life wellbeing. On the other hand, the findings show an overestimation in the retrospective data, in part, arising from the absence in life history data of childhood measures that are not well suited to retrospective collection.

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Gniewosz, Burkhard, and Gabriela Gniewosz. "How to model intraindividual change in cohort data using Mplus’ multi-group approach." International Journal of Behavioral Development 42, no. 3 (January 9, 2018): 373–80. http://dx.doi.org/10.1177/0165025417750282.

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The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus’ multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and predicted by gender. The example data stems from a large German cohort sequential study and comprises 806 children in three birth cohorts (2001, 2000, 1999). Finally, the advantages and disadvantages of this modelling approach are discussed. Annotated syntax is provided online for the models.

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Darke, Philip, Sophie Cassidy, Michael Catt, Roy Taylor, Paolo Missier, and Jaume Bacardit. "Curating a longitudinal research resource using linked primary care EHR data—a UK Biobank case study." Journal of the American Medical Informatics Association 29, no. 3 (December 13, 2021): 546–52. http://dx.doi.org/10.1093/jamia/ocab260.

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Abstract Primary care EHR data are often of clinical importance to cohort studies however they require careful handling. Challenges include determining the periods during which EHR data were collected. Participants are typically censored when they deregister from a medical practice, however, cohort studies wish to follow participants longitudinally including those that change practice. Using UK Biobank as an exemplar, we developed methodology to infer continuous periods of data collection and maximize follow-up in longitudinal studies. This resulted in longer follow-up for around 40% of participants with multiple registration records (mean increase of 3.8 years from the first study visit). The approach did not sacrifice phenotyping accuracy when comparing agreement between self-reported and EHR data. A diabetes mellitus case study illustrates how the algorithm supports longitudinal study design and provides further validation. We use UK Biobank data, however, the tools provided can be used for other conditions and studies with minimal alteration.

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Jamieson, Lisa M., Joanne Hedges, X. Ju, Kostas Kapellas, Cathy Leane, Dandara G. Haag, Pedro Ribeiro Santiago, Davi Manzini Macedo, Rachel M. Roberts, and Lisa G. Smithers. "Cohort profile: South Australian Aboriginal Birth Cohort (SAABC)—a prospective longitudinal birth cohort." BMJ Open 11, no. 2 (February 2021): e043559. http://dx.doi.org/10.1136/bmjopen-2020-043559.

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PurposeThe South Australian Aboriginal Birth Cohort (SAABC) is a prospective, longitudinal birth cohort established to: (1) estimate Aboriginal child dental disease compared with population estimates; (2) determine the efficacy of an early childhood caries intervention in early versus late infancy; (3) examine if efficacy was sustained over time and; (4) document factors influencing social, behavioural, cognitive, anthropometric, dietary and educational attainment over time.ParticipantsThe original SAABC comprised 449 women pregnant with an Aboriginal child recruited February 2011 to May 2012. At child age 2 years, 324 (74%) participants were retained, at age 3 years, 324 (74%) participants were retained and at age 5 years, 299 (69%) participants were retained. Fieldwork for follow-up at age 7 years is underway, with funding available for follow-up at age 9 years.Findings to dateAt baseline, 53% of mothers were aged 14–24 years and 72% had high school or less educational attainment. At age 3 years, dental disease experience was higher among children exposed to the intervention later rather than earlier in infancy. The effect was sustained at age 5 years, but rates were still higher than general child population estimates. Experiences of racism were high among mothers, with impacts on both tooth brushing and toothache. Compared with population estimates, levels of self-efficacy and self-rated oral health of mothers at baseline were low.Future plansOur data have contributed to a better understanding of the environmental, behavioural, dietary, biological and psychosocial factors contributing to Aboriginal child oral and general health, and social and emotional well-being. This is beneficial in charting the trajectory of cohort participants’ health and well-being overtime, particularly in identifying antecedents of chronic diseases which are highly prevalent among Aboriginal Australians. Funding for continued follow-up of the cohort will be sought.Trial registration numberACTRN12611000111976; Post-results.

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Massa, Fernando, Alejandra Marroig, Graciela Muniz Terrera, and Scott Hofer. "NEW EVIDENCE OF HEALTHIER AGING. POSITIVE COHORT EFFECT ON COGNITIVE DECLINE." Innovation in Aging 6, Supplement_1 (November 1, 2022): 821. http://dx.doi.org/10.1093/geroni/igac059.2953.

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Abstract Cross sectional studies have shown cohort effects in cognition, limited research exists about cohort effects on cognitive trajectories. Indeed, most longitudinal research conducted to study aging-related cognitive change focus on the association between risk factors and mean change in cognition, considering individual differences too, but longitudinal norms of cognitive function are less studied. In this study, we aim to test whether cohort effects exist across the distribution of verbal fluency trajectories, that is, whether cohort effects vary across different trajectory quantiles. With this purpose, we estimated norms using data from 9 waves of the English Longitudinal Study of Aging (ELSA). We considered the individuals born in the 1920s, 1930s, and 1940s to assess cohort effects. The methodological framework consisted of quantile mixed models where the effect of age was adjusted using splines. To test for possible cohort effects across the 5th, 50th and 90th quartiles, the coefficients associated with the splines varied among cohorts. Our results suggest that cognitive decline is less pronounced for individuals born in more recent decades (p < 0.001), supporting our hypothesis of cohort effects. Moreover, these results are consistent across quantiles (p-value < 0.001). Additionally, we found that quantiles of verbal fluency at a certain age is higher in participants from more recent cohorts compared to those in older cohorts. Our findings contribute to a better understanding of cognitive decline in older adults, demonstrating population changes over time at different levels of changes in verbal fluency.

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Golding, Jean. "Data organisation and preparation for statistical analysis in a longitudinal birth cohort." Paediatric and Perinatal Epidemiology 23 (July 2009): 219–25. http://dx.doi.org/10.1111/j.1365-3016.2009.01019.x.

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Hoogendijk, Emiel O., Dorly J. H. Deeg, Sascha de Breij, Silvia S. Klokgieters, Almar A. L. Kok, Najada Stringa, Erik J. Timmermans, et al. "The Longitudinal Aging Study Amsterdam: cohort update 2019 and additional data collections." European Journal of Epidemiology 35, no. 1 (July 25, 2019): 61–74. http://dx.doi.org/10.1007/s10654-019-00541-2.

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Lv, Yuebin, Chen Mao, Zhaoxue Yin, Furong Li, Xianbo Wu, and Xiaoming Shi. "Healthy Ageing and Biomarkers Cohort Study (HABCS): a cohort profile." BMJ Open 9, no. 10 (October 2019): e026513. http://dx.doi.org/10.1136/bmjopen-2018-026513.

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PurposeThe Chinese Longitudinal Healthy Longevity Survey Biomarkers Cohort (Healthy Ageing and Biomarkers Cohort Study (HABCS)) was established to investigate the determinants of healthy aging and mortality among the oldest old in China. Besides collecting health status, behavioural and sociodemographic circumstances, the present study also gathers comprehensive data for the elderly by simultaneously collecting, detecting, analysing blood and urine, respectively.ParticipantsHABCS is a community-based longitudinal multiwave study of older men and women aged 65 or above. Baseline survey and the follow-up surveys with replacement for deceased elderly were conducted in eight longevity areas in China, which cover the northern, middle and southern parts of China. Between 2008 and 2017, 6333 participants were included in HABCS, comprising 1385 centenarians, 1350 nonagenarians, 1294 octogenarians, 1577 younger elderly (aged 65–79).Findings to dateWe have found that higher baseline levels of (1) total cholesterol, (2) low-density lipoprotein cholesterol (LDL-C) and (3) superoxide dismutase activity were associated with greater cognitive decline. While (4) higher LDL-C level was associated with lower risk of all-cause mortality. There was a reverse association between (5) plasma vitamin D and cognitive impairment in cross-sectional and prospective study.Future plansWe are currently exploring the relationships between various biomarkers and different outcomes such as cognitive function and mortality. This longitudinal cohort study will be continued in the future.

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Berkers, G., P. van Mourik, S. Heida-Michel, E. Kruisselbrink, U. Roorda, J. M. Beekman, and C. K. van der Ent. "418 The CCFR-cohort: a longitudinal cohort integrating care, research and in-vitro data of CF-patients." Journal of Cystic Fibrosis 16 (June 2017): S169. http://dx.doi.org/10.1016/s1569-1993(17)30748-8.

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Nooyens, Astrid CJ, Tommy LS Visscher, WM Monique Verschuren, A. Jantine Schuit, Hendriek C. Boshuizen, Willem van Mechelen, and Jacob C. Seidell. "Age, period and cohort effects on body weight and body mass index in adults: The Doetinchem Cohort Study." Public Health Nutrition 12, no. 6 (June 2009): 862–70. http://dx.doi.org/10.1017/s1368980008003091.

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AbstractObjectiveTo study the development of body weight with ageing, in a general adult population, taking into account possible period and cohort effects.DesignA prospective cohort study with 11 years of follow-up. At baseline and after 6 and 11 years, body weight and height were measured.SettingThe Doetinchem Cohort Study, consisting of inhabitants of Doetinchem, a town in a rural area of The Netherlands.SubjectsIn total, 4070 healthy men and women aged 20–59 years at baseline.ResultsIncrease in BMI with ageing was less profound based on cross-sectional data than based on longitudinal data. More recent-born cohorts had a higher BMI at a given age than cohorts who were born earlier. Increase in mean BMI with ageing was observed in all age groups and was similar for groups with a different educational level. Highest increase in BMI over 11 years was observed in the youngest group, aged 20–29 years at baseline (2·2 [95 % CL 2·0, 2·3] kg/m2), and lowest increase in the oldest group, aged 50–59 years at baseline (1·1 [1·0, 1·3] kg/m2).ConclusionsFindings of the present study using longitudinal data suggest that increase in BMI with ageing is underestimated in all age groups by studying cross-sectional data only. Further, weight gain is present in all educational levels and does not stop at middle age.

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Kaprio, Jaakko. "The Finnish Twin Cohort Study: An Update." Twin Research and Human Genetics 16, no. 1 (January 8, 2013): 157–62. http://dx.doi.org/10.1017/thg.2012.142.

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In 2002 and 2006, review papers have described the Finnish Twin Cohort and studies conducted on these population-based, longitudinal data sets with extensive follow-up data. Three cohorts have been established: the older twin cohort in the 1970s, and the Finntwin12 and Finntwin16 studies initiated in the 1990s. The present review provides on update on the latest data collections conducted since the previous review. These cover the fourth waves of data collection in the older cohort (twins born before 1958) and Finntwin12 (twins born 1983–1987). The fifth wave of data collection in Finntwin16 (twins born 1975–1979) also included assessments of their spouses/partners. An analysis of mortality in the older cohort from 1975 to 2009 indicates that the mortality of adult twins (as individuals) does not differ from the population at large. Based on the cohorts, many sub-studies with more detailed phenotyping and collection of omics data have been conducted or are in progress. We also contribute to numerous national and international collaborations.

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Jacqmin-Gadda, Hélène, Anaïs Rouanet, Robert D. Mba, Viviane Philipps, and Jean-François Dartigues. "Quantile regression for incomplete longitudinal data with selection by death." Statistical Methods in Medical Research 29, no. 9 (March 17, 2020): 2697–716. http://dx.doi.org/10.1177/0962280220909986.

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Quantile regressions are increasingly used to provide population norms for quantitative variables. Indeed, they do not require any Gaussian assumption for the response and allow to characterize its entire distribution through different quantiles. Quantile regressions are especially useful to provide norms of cognitive scores in the elderly that may help general practitioners to identify subjects with unexpectedly low cognitive level in routine examinations. These norms may be estimated from cohorts of elderly using quantile regression for longitudinal data, but this requires to properly account for selection by death, dropout and intermittent missing data. In this work, we extend the weighted estimating equation approach to estimate conditional quantiles in the population currently alive from mortal cohorts with dropout and intermittent missing data. Suitable weight estimation procedures are provided for both monotone and intermittent missing data and under two missing-at-random assumptions, when the observation probability given that the subject is alive depends on the survival time (p-MAR assumption) or not (u-MAR assumption). Inference is performed through subject-level bootstrap. The method is validated in a simulation study and applied to the French cohort Paquid to estimate quantiles of a cognitive test in the elderly population currently alive. On one hand, the simulations show that the u-MAR analysis is quite robust when the true missingness mechanism is p-MAR. This is a useful result because computation of suitable weights for intermittent missing data under the p-MAR assumption is untractable. On the other hand, the simulations highlight, along with the real data analysis, the usefulness of suitable weights for intermittent missing data. This method is implemented in the R package weightQuant.

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Eschenbeck, Heike, Steffen Schmid, Ines Schröder, Nicola Wasserfall, and Carl-Walter Kohlmann. "Development of Coping Strategies From Childhood to Adolescence." European Journal of Health Psychology 25, no. 1 (January 2018): 18–30. http://dx.doi.org/10.1027/2512-8442/a000005.

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Abstract. Extensive research exists on coping in children and adolescents. However, developmental issues have only recently started to receive more attention. The present study examined age differences and developmental changes in six coping strategies (social support seeking, problem solving, avoidant coping, palliative emotion regulation, anger-related emotion regulation, and media use) assessed by a coping questionnaire (German Stress and Coping Questionnaire for Children and Adolescents, SSKJ 3–8; Lohaus, Eschenbeck, Kohlmann, & Klein-Heßling, 2006 ) in middle/late childhood and early adolescence. At the initial assessment, 917 children from grades 3 to 7 (age range 8–15 years) were included (cross-sectional sample). Three cohorts (grades 3–5 at baseline) were traced longitudinally over 1½ years with four assessments (longitudinal sample: n = 388). The cross-sectional coping data showed significant effects for grade level in four coping strategies. Older children scored higher in problem solving and media use, and lower in avoidant coping. Seventh graders scored lower than fourth and fifth graders in social support seeking. Longitudinal data confirmed time effects and cohort effects indicating developmental changes. Increases over time were found for problem solving and media use; decreases were found for avoidant coping and anger-related emotion regulation. For social support seeking, an increase within the youngest cohort (grades 3–5) was found. Developmental trends (in cross-sectional and longitudinal data), with especially strong increases for problem solving or declines in avoidant coping in the youngest cohort, differed for the two studied stressful situations (social, academic) but were independent of the child’s gender. To conclude, particularly in the age range of 9–11 years relevant developmental changes toward a more active coping seem to appear.

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Brombin, Chiara, Clelia Di Serio, and Paola MV Rancoita. "Joint modeling of HIV data in multicenter observational studies: A comparison among different approaches." Statistical Methods in Medical Research 25, no. 6 (July 11, 2016): 2472–87. http://dx.doi.org/10.1177/0962280214526192.

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Disease process over time results from the combination of event history information and longitudinal process. Commonly, separate analyses of longitudinal and survival outcomes are performed. However, discharging the dependence between these components may cause misleading results. Separate analyses are difficult to interpret whenever one deals with observational retrospective multicenter cohort studies where the biomarkers are poorly monitored over time, while the survival component may be affected by several sources of bias, such as multiple endpoints, multiple time-scales, and informative censoring. We discuss how joint modeling of longitudinal and survival data represents an effective strategy to incorporate all information simultaneously and to provide valid and efficient inferences, thus allowing to produce a better insight into the biological mechanisms underlying the phenomenon under study. Accounting for the whole dynamics of the disease process is crucial in retrospective longitudinal studies. In this work, we present different approaches for modeling longitudinal and time-to-event data, retrieved from 648 HIV-infected patients enrolled in the Italian cohort of the CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) study, one of the largest AIDS collaborative cohort studies. In particular, we evaluate CD4 lymphocyte evolution over time (from the date of seroconversion) and overall survival, CD4 being one of the most important immunologic biomarker for HIV progression. Besides a standard separate modeling approach, we consider two alternative joint models: the traditional joint model and the joint latent class mixed model. Advantages and disadvantages of the different approaches are discussed. To compare the performances of these models, cross-validation procedures are also performed.

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Denton, Frank T., Ross Finnie, and Byron G. Spencer. "The age pattern of retirement: Comparisons of longitudinal, pseudo-cohort, and period measures." Canadian Studies in Population 40, no. 3-4 (November 4, 2013): 193. http://dx.doi.org/10.25336/p6js5s.

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Retirement patterns change. When that happens, measures based on single-period cross-sectional data may provide a misleading picture of cohort retirement behaviour. We offer two cohort-based measures. One draws on income tax records to follow actual cohorts of individuals over time, the other on a time-series of cross-sectional surveys. We find that the retirement patterns based on the two approaches are similar but differ, often substantially, from single-period patterns. While pseudo-cohort measures can be assessed more quickly and at lower cost, knowledge of differences across income groups, income replacement rates, and so on, must rely on full longitudinal records.

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Agogo, George O., Christine M. Ramsey, Danijela Gnjidic, Daniela C. Moga, and Heather Allore. "Longitudinal associations between different dementia diagnoses and medication use jointly accounting for dropout." International Psychogeriatrics 30, no. 10 (April 18, 2018): 1477–87. http://dx.doi.org/10.1017/s1041610218000017.

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ABSTRACTBackground:Longitudinal studies of older adults are characterized by high dropout rates, multimorbid conditions, and multiple medication use, especially proximal to death. We studied the association between multiple medication use and incident dementia diagnoses including Alzheimer's disease (AD), vascular dementia (VD), and Lewy-body dementia (LBD), simultaneously accounting for dropout.Methods:Using the National Alzheimer's Coordinating Center data with three years of follow-up, a set of covariate-adjusted models that ignore dropout was fit to complete-case data, and to the whole-cohort data. Additionally, covariate-adjusted joint models with shared random effects accounting for dropout were fit to the whole-cohort data. Multiple medication use was defined as polypharmacy (⩾ five medications), hyperpolypharmacy (⩾ ten medications), and total number of medications.Results:Incident diagnoses were 2,032 for AD, 135 for VD, and 139 for LBD. Percentages of dropout at the end of follow-up were as follows: 71.8% for AD, 81.5% for VD, and 77.7% for LBD. The odds ratio (OR) estimate for hyperpolypharmacy among those with LBD versus AD was 2.19 (0.78, 6.15) when estimated using complete-case data and 3.00 (1.66, 5.40) using whole-cohort data. The OR reduced to 1.41 (0.76, 2.64) when estimated from the joint model accounting for dropout. The OR for polypharmacy using complete-case data differed from the estimates using whole-cohort data. The OR for dementia diagnoses on total number of medications was similar, but non-significant when estimated using complete-case data.Conclusion:Reasons for dropout should be investigated and appropriate statistical methods should be applied to reduce bias in longitudinal studies among high-risk dementia cohorts.

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Perotte, Adler, Rajesh Ranganath, Jamie S. Hirsch, David Blei, and Noémie Elhadad. "Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis." Journal of the American Medical Informatics Association 22, no. 4 (April 20, 2015): 872–80. http://dx.doi.org/10.1093/jamia/ocv024.

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Abstract Background As adoption of electronic health records continues to increase, there is an opportunity to incorporate clinical documentation as well as laboratory values and demographics into risk prediction modeling. Objective The authors develop a risk prediction model for chronic kidney disease (CKD) progression from stage III to stage IV that includes longitudinal data and features drawn from clinical documentation. Methods The study cohort consisted of 2908 primary-care clinic patients who had at least three visits prior to January 1, 2013 and developed CKD stage III during their documented history. Development and validation cohorts were randomly selected from this cohort and the study datasets included longitudinal inpatient and outpatient data from these populations. Time series analysis (Kalman filter) and survival analysis (Cox proportional hazards) were combined to produce a range of risk models. These models were evaluated using concordance, a discriminatory statistic. Results A risk model incorporating longitudinal data on clinical documentation and laboratory test results (concordance 0.849) predicts progression from state III CKD to stage IV CKD more accurately when compared to a similar model without laboratory test results (concordance 0.733, P<.001), a model that only considers the most recent laboratory test results (concordance 0.819, P < .031) and a model based on estimated glomerular filtration rate (concordance 0.779, P < .001). Conclusions A risk prediction model that takes longitudinal laboratory test results and clinical documentation into consideration can predict CKD progression from stage III to stage IV more accurately than three models that do not take all of these variables into consideration.

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Griffanti, Ludovica, Johannes C. Klein, Konrad Szewczyk-Krolikowski, Ricarda A. L. Menke, Michal Rolinski, Thomas R. Barber, Michael Lawton, et al. "Cohort profile: the Oxford Parkinson’s Disease Centre Discovery Cohort MRI substudy (OPDC-MRI)." BMJ Open 10, no. 8 (August 2020): e034110. http://dx.doi.org/10.1136/bmjopen-2019-034110.

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PurposeThe Oxford Parkinson’s Disease Centre (OPDC) Discovery Cohort MRI substudy (OPDC-MRI) collects high-quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson’s, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson’s and at-risk individuals.ParticipantsParticipants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data are currently available for 290 participants: 119 patients with early idiopathic Parkinson’s, 15 Parkinson’s patients with pathogenic mutations of the leucine-rich repeat kinase 2 or glucocerebrosidase (GBA) genes, 68 healthy controls and 87 individuals at risk of Parkinson’s (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder-RBD).Findings to dateDifferences in brain structure in early Parkinson’s were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson’sand RBD. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease.Future plansOngoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.

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Barros, Aluísio, and Cauane Blumenberg. "Electronic data collection in epidemiological research." Applied Clinical Informatics 07, no. 03 (July 2016): 672–81. http://dx.doi.org/10.4338/aci-2016-02-ra-0028.

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SummaryThis paper describes the use of Research Electronic Data Capture (REDCap) to conduct one of the follow-up waves of the 2004 Pelotas birth cohort. The aim is to point out the advantages and limitations of using this electronic data capture environment to collect data and control every step of a longitudinal epidemiological research, specially in terms of time savings and data quality.We used REDCap as the main tool to support the conduction of a birth cohort follow-up. By exploiting several REDCap features, we managed to schedule assessments, collect data, and control the study workflow. To enhance data quality, we developed specific reports and field validations to depict inconsistencies in real time.Using REDCap it was possible to investigate more variables without significant increases on the data collection time, when comparing to a previous birth cohort follow-up. In addition, better data quality was achieved since negligible out of range errors and no validation or missing inconsistencies were identified after applying over 7,000 interviews.Adopting electronic data capture solutions, such as REDCap, in epidemiological research can bring several advantages over traditional paper-based data collection methods. In favor of improving their features, more research groups should migrate from paper to electronic-based epidemiological research.Citation: Blumenberg C, Barros AJD. Electronic data collection in epidemiological research: The use of REDCap in the Pelotas birth cohorts

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Kaidesoja, Milla, Sari Aaltonen, Leonie H. Bogl, Kauko Heikkilä, Sara Kaartinen, Urho M. Kujala, Ulla Kärkkäinen, et al. "FinnTwin16: A Longitudinal Study from Age 16 of a Population-Based Finnish Twin Cohort." Twin Research and Human Genetics 22, no. 6 (December 2019): 530–39. http://dx.doi.org/10.1017/thg.2019.106.

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AbstractThe purpose of this review is to provide a detailed and updated description of the FinnTwin16 (FT16) study and its future directions. The Finnish Twin Cohort comprises three different cohorts: the Older Twin Cohort established in the 1970s and the FinnTwin12 and FT16 initiated in the 1990s. FT16 was initiated in 1991 to identify the genetic and environmental precursors of alcoholism, but later the scope of the project expanded to studying the determinants of various health-related behaviors and diseases in different stages of life. The main areas addressed are alcohol use and its consequences, smoking, physical activity, overall physical health, eating behaviors and eating disorders, weight development, obesity, life satisfaction and personality. To date, five waves of data collection have been completed and the sixth is now planned. Data from the FT16 cohort have contributed to several hundred studies and many substudies, with more detailed phenotyping and collection of omics data completed or underway. FT16 has also contributed to many national and international collaborations.

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Mond, Casparia, Trevor Duke, and John Vince. "Epilepsy in Papua New Guinea: a longitudinal cohort study." Archives of Disease in Childhood 104, no. 10 (July 19, 2019): 941–46. http://dx.doi.org/10.1136/archdischild-2019-317217.

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Epilepsy affects up to 1-4% of children living in low income and middle countries, however there are few studies of the problems faced by children with epilepsy in such settings. We aimed to document the situation for children with epilepsy in Port Moresby, an urban area in Papua New Guinea, a low-middle income country in the Western Pacific region. We conducted longitudinal cohort study using mixed methods, with serial data collected over 2 years which assessed seizure control, neurodevelopment, and structured interviews with children and parents. For quantitative data descriptive statistics are reported; for qualitative data common responses, themes, experiences and perceptions were grouped and reported in narrative. Forty-seven children with epilepsy were followed for a median of 18 months. Twenty six (55%) children had some associated neurodevelopmental disability. Children gave detailed and vivid descriptions of their experience of seizures. Most children and parents had a positive view of the future but faced many challenges including financial difficulties, fear of having seizures especially at school, restriction of activity that isolated them from peers, and significant stigma and discrimination. Seizure control improved over time for some children, but inconsistent supply of phenobarbitone hindered better control. Comprehensive care for children with epilepsy requires a good knowledge of the individual patient —including their seizure type and comorbidities, their family, and their strengths and vulnerabilities. Children with epilepsy face many problems that can lead to isolation, discrimination and restricted opportunities.

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Celeste, R. K., H. S. Eyjólfsdóttir, C. Lennartsson, and J. Fritzell. "Socioeconomic Life Course Models and Oral Health: A Longitudinal Analysis." Journal of Dental Research 99, no. 3 (February 20, 2020): 257–63. http://dx.doi.org/10.1177/0022034520901709.

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We compared socioeconomic life course models to decompose the direct and mediated effects of socioeconomic status (SES) in different periods of life on late-life oral health. We used data from 2 longitudinal Swedish studies: the Level of Living Survey and the Swedish Panel Study of Living Conditions of the Oldest Old. Two birth cohorts (older, 1925 to 1934; younger, 1944 to 1953) were followed between 1968 and 2011 with 6 waves. SES was measured with 4 indicators of SES and modeled as a latent variable. Self-reported oral health was based on a tooth conditions question. Variables in the younger and older cohorts were grouped into 4 periods: childhood, young/mid-adulthood, mid /late adulthood, late adulthood/life. We used structural equation modeling to fit the following into lagged-effects life course models: 1) chain of risk, 2) sensitive period with late-life effect, 3) sensitive period with early- and late-life effects, 4) accumulation of risks with cross-sectional effects, and 5) accumulation of risks. Chain of risk was incorporated into all models and combined with accumulation, with cross-sectional effects yielding the best fit (older cohort: comparative fit index = 0.98, Tucker-Lewis index = 0.98, root mean square error of approximation = 0.04, weighted root mean square residual = 1.51). For the older cohort, the chain of SES from childhood → mid-adulthood → late adulthood → late life showed the following respective standardized coefficients: 053, 0.92, and 0.97. The total effect of childhood SES on late-life tooth loss (standardized coefficient: –0.23 for older cohort, –0.17 for younger cohort) was mediated by previous tooth loss and SES. Cross-sectional effects of SES on tooth loss were observed throughout the life course, but the strongest coefficients were at young/mid-adulthood (standardized coefficient: –0.41 for older cohort, –0.45 for younger cohort). SES affects oral health cumulatively over the life course and through a chain of risks. Actions to improve socioeconomic conditions in early life might have long-lasting effects on health if they help prevent people from becoming trapped in a chain of risks.

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Deliveira, Thais Lopes, and Sara Hägg. "FUNCTIONAL AGING TRAJECTORIES AND DRUG INTERACTIONS." Innovation in Aging 6, Supplement_1 (November 1, 2022): 243. http://dx.doi.org/10.1093/geroni/igac059.965.

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Abstract Markers of functional aging can be used to track biological aging longitudinally and how it changes in response to the environment, e.g., drugs. We aimed to investigate how different drug classes may alter functional aging trajectories using data from the National E-infrastructure of Aging Research (NEAR) in Sweden. Data were harmonized across several longitudinal cohorts of aging for general cognitive performance, grip strength, walking speed, sensory ability (visual and hearing), lung function and assessment of frailty using the accumulation deficit model known as the frailty index. Selected drug classes were lipid lowering, glucose lowering and blood pressure lowering medications that are commonly used in old adults. Preliminary analysis using data from one longitudinal cohort shows that using glucose lowering drugs was associated with lower frailty. Additional analyses are ongoing to increase sample sizes. We anticipate that several drug classes may be important for changing functional aging trajectories in late life.

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Tilling, Kate, Michael Lawton, Neil Robertson, Helen Tremlett, Feng Zhu, Katharine Harding, Joel Oger, and Yoav Ben-Shlomo. "Modelling disease progression in relapsing–remitting onset multiple sclerosis using multilevel models applied to longitudinal data from two natural history cohorts and one treated cohort." Health Technology Assessment 20, no. 81 (October 2016): 1–48. http://dx.doi.org/10.3310/hta20810.

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BackgroundThe ability to better predict disease progression represents a major unmet need in multiple sclerosis (MS), and would help to inform therapeutic and management choices.ObjectivesTo develop multilevel models using longitudinal data on disease progression in patients with relapsing–remitting MS (RRMS) or secondary-progressive MS (SPMS); and to use these models to estimate the association of disease-modifying therapy (DMT) with progression.DesignSecondary analysis of three MS cohorts.SettingTwo natural history cohorts: University of Wales Multiple Sclerosis (UoWMS) cohort, UK, and British Columbia Multiple Sclerosis (BCMS) cohort, Canada. One observational DMT-treated cohort: UK MS risk-sharing scheme (RSS).ParticipantsThe UoWMS database has > 2000 MS patients and the BCMS database (as of 2009) has > 5900 MS patients. All participants who had definite MS (RRMS/SPMS), who reached the criteria set out by the Association of British Neurologists (ABN) for eligibility for DMT [i.e. age ≥ 18 years, Expanded Disability Status Scale (EDSS) score of ≤ 6.5, occurrence of two or more relapses in the previous 2 years] and who had at least two repeated outcome measures were included: 404 patients for the UoWMS cohort and 978 patients for the BCMS cohort. Through the UK MS RSS scheme, 5583 DMT-treated patients were recruited, with the analysis sample being the 4137 who had RRMS and were eligible and treated at baseline, with at least one valid EDSS score post baseline.Main outcome measuresEDSS score observations post ABN eligibility.MethodsWe used multilevel models in the development cohort (UoWMS) to develop a model for EDSS score with time since ABN eligibility, allowing for covariates and appropriate transformation of outcome and/or time. These methods were then applied to the BCMS cohort to obtain a ‘natural history’ model for changes in the EDSS score with time. We then used this natural history model to predict the trajectories of EDSS score in treated patients in the UK MS RSS database. Differences between the progression predicted by the natural history model and the progression observed at 6 years’ follow-up for the UK MS RSS cohort were used as indicators of the effectiveness of the DMTs. Previously developed utility scores were assigned to each EDSS score, and differences in utility also examined.ResultsThe model best fitting the UoWMS data showed a non-linear increase in EDSS score over time since ABN eligibility. This model fitted the BCMS cohort data well, with similar coefficients, and the BCMS model predicted EDSS score in UoWMS data with little evidence of bias. Using the natural history model predicts EDSS score in a treated cohort (UK MS RSS) higher than that observed [by 0.59 points (95% confidence interval 0.54 to 0.64 points)] at 6 years post treatment.LimitationsOnly two natural history cohorts were compared, limiting generalisability. The comparison of a treated cohort with untreated cohorts is observational, thus limiting conclusions about causality.ConclusionsEDSS score progression in two natural history cohorts of MS patients showed a similar pattern. Progression in the natural history cohorts was slightly faster than EDSS score progression in the DMT-treated cohort, up to 6 years post treatment.Future workLong-term follow-up of randomised controlled trials is needed to replicate these findings and examine duration of any treatment effect.Funding detailsThe National Institute for Health Research Health Technology Assessment programme.

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Di Cara, Nina H., Andy Boyd, Alastair R. Tanner, Tarek Al Baghal, Lisa Calderwood, Luke S. Sloan, Oliver S. P. Davis, and Claire M. A. Haworth. "Views on social media and its linkage to longitudinal data from two generations of a UK cohort study." Wellcome Open Research 5 (March 12, 2020): 44. http://dx.doi.org/10.12688/wellcomeopenres.15755.1.

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Background: Cohort studies gather huge volumes of information about a range of phenotypes but new sources of information such as social media data are yet to be integrated. Participant’s long-term engagement with cohort studies, as well as the potential for their social media data to be linked to other longitudinal data, could provide novel advances but may also give participants a unique perspective on the acceptability of this growing research area. Methods: Two focus groups explored participant views towards the acceptability and best practice for the collection of social media data for research purposes. Participants were drawn from the Avon Longitudinal Study of Parents and Children cohort; individuals from the index cohort of young people (N=9) and from the parent generation (N=5) took part in two separate 90-minute focus groups. The discussions were audio recorded and subjected to qualitative analysis. Results: Participants were generally supportive of the collection of social media data to facilitate health and social research. They felt that their trust in the cohort study would encourage them to do so. Concern was expressed about the collection of data from friends or connections who had not consented. In terms of best practice for collecting the data, participants generally preferred the use of anonymous data derived from social media to be shared with researchers. Conclusion: Cohort studies have trusting relationships with their participants; for this relationship to extend to linking their social media data with longitudinal information, procedural safeguards are needed. Participants understand the goals and potential of research integrating social media data into cohort studies, but further research is required on the acquisition of their friend’s data. The views gathered from participants provide important guidance for future work seeking to integrate social media in cohort studies.

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Di Cara, Nina H., Andy Boyd, Alastair R. Tanner, Tarek Al Baghal, Lisa Calderwood, Luke S. Sloan, Oliver S. P. Davis, and Claire M. A. Haworth. "Views on social media and its linkage to longitudinal data from two generations of a UK cohort study." Wellcome Open Research 5 (August 12, 2020): 44. http://dx.doi.org/10.12688/wellcomeopenres.15755.2.

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Background: Cohort studies gather huge volumes of information about a range of phenotypes but new sources of information such as social media data are yet to be integrated. Participant’s long-term engagement with cohort studies, as well as the potential for their social media data to be linked to other longitudinal data, may give participants a unique perspective on the acceptability of this growing research area. Methods: Two focus groups explored participant views towards the acceptability and best practice for the collection of social media data for research purposes. Participants were drawn from the Avon Longitudinal Study of Parents and Children cohort; individuals from the index cohort of young people (N=9) and from the parent generation (N=5) took part in two separate 90-minute focus groups. The discussions were audio recorded and subjected to qualitative analysis. Results: Participants were generally supportive of the collection of social media data to facilitate health and social research. They felt that their trust in the cohort study would encourage them to do so. Concern was expressed about the collection of data from friends or connections who had not consented. In terms of best practice for collecting the data, participants generally preferred the use of anonymous data derived from social media to be shared with researchers. Conclusion: Cohort studies have trusting relationships with their participants; for this relationship to extend to linking their social media data with longitudinal information, procedural safeguards are needed. Participants understand the goals and potential of research integrating social media data into cohort studies, but further research is required on the acquisition of their friend’s data. The views gathered from participants provide important guidance for future work seeking to integrate social media in cohort studies.

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Ando, Ayaka, Peter Parzer, Michael Kaess, Susanne Schell, Romy Henze, Stefan Delorme, Bram Stieltjes, Franz Resch, Romuald Brunner, and Julian Koenig. "Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence." Brain Structure and Function 226, no. 3 (January 20, 2021): 927–37. http://dx.doi.org/10.1007/s00429-020-02208-1.

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Abstract Background Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence. Methods Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection. Results Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status. Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated. Conclusions Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development.

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Callahan, Alison, Vladimir Polony, José D. Posada, Juan M. Banda, Saurabh Gombar, and Nigam H. Shah. "ACE: the Advanced Cohort Engine for searching longitudinal patient records." Journal of the American Medical Informatics Association 28, no. 7 (March 13, 2021): 1468–79. http://dx.doi.org/10.1093/jamia/ocab027.

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Abstract Objective To propose a paradigm for a scalable time-aware clinical data search, and to describe the design, implementation and use of a search engine realizing this paradigm. Materials and Methods The Advanced Cohort Engine (ACE) uses a temporal query language and in-memory datastore of patient objects to provide a fast, scalable, and expressive time-aware search. ACE accepts data in the Observational Medicine Outcomes Partnership Common Data Model, and is configurable to balance performance with compute cost. ACE’s temporal query language supports automatic query expansion using clinical knowledge graphs. The ACE API can be used with R, Python, Java, HTTP, and a Web UI. Results ACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. ACE enables electronic phenotyping and cohort-building with subsecond response times in searching the data of millions of patients for a variety of use cases. Discussion ACE enables fast, time-aware search using a patient object-centric datastore, thereby overcoming many technical and design shortcomings of relational algebra-based querying. Integrating electronic phenotype development with cohort-building enables a variety of high-value uses for a learning health system. Tradeoffs include the need to learn a new query language and the technical setup burden. Conclusion ACE is a tool that combines a unique query language for time-aware search of longitudinal patient records with a patient object datastore for rapid electronic phenotyping, cohort extraction, and exploratory data analyses.

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Carpenter, Joanne S., Frank Iorfino, Shane Cross, Alissa Nichles, Natalia Zmicerevska, Jacob J. Crouse, Jake R. Palmer, et al. "Cohort profile: the Brain and Mind CentreOptymisecohort: tracking multidimensional outcomes in young people presenting for mental healthcare." BMJ Open 10, no. 3 (March 2020): e030985. http://dx.doi.org/10.1136/bmjopen-2019-030985.

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PurposeThe Brain and Mind Centre (BMC)Optymisecohort assesses multiple clinical and functional domains longitudinally in young people presenting for mental health care and treatment. Longitudinal tracking of this cohort will allow investigation of the relationships between multiple outcome domains across the course of care. Subsets ofOptymisehave completed detailed neuropsychological and neurobiological assessments, permitting investigation of associations between these measures and longitudinal course.ParticipantsYoung people (aged 12–30) presenting to clinics coordinated by the BMC were recruited to a research register (n=6743) progressively between June 2008 and July 2018. To date, 2767 individuals have been included inOptymisebased on the availability of at least one detailed clinical assessment.MeasuresTrained researchers use a clinical research proforma to extract key data from clinical files to detail social and occupational functioning, clinical presentation, self-harm and suicidal thoughts and behaviours, alcohol and other substance use, physical health comorbidities, personal and family history of mental illness, and treatment utilisation at the following time points: baseline, 3, 6, 12, 24, 36, 48, and 60 months, and time last seen.Findings to dateThere is moderate to substantial agreement between raters for data collected via the proforma. While wide variations in individual illness course are clear, social and occupational outcomes suggest that the majority of cohort members show no improvement in functioning over time. Differential rates of longitudinal transition are reported between early and late stages of illness, with a number of baseline factors associated with these transitions. Furthermore, there are longitudinal associations between prior suicide attempts and inferior clinical and functional outcomes.Future plansFuture reports will detail the longitudinal course of each outcome domain and examine multidirectional relationships between these domains both cross-sectionally and longitudinally, and explore in subsets the associations between detailed neurobiological measures and clinical, social and functional outcomes.

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Fernandes, Ana S., Jose M. Fonseca, Ian H. Jarman, Terence A. Etchells, Paulo J. G. Lisboa, Elia Biganzoli, and Chris Bajdik. "Evaluation of missing data imputation in longitudinal cohort studies in breast cancer survival." International Journal of Knowledge Engineering and Soft Data Paradigms 1, no. 3 (2009): 257. http://dx.doi.org/10.1504/ijkesdp.2009.028818.

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Visness, C. M., K. F. Jaffee, A. Calatroni, R. A. Wood, P. J. Gergen, and J. E. Gern. "Novel Analysis Methods for Longitudinal Cytokine Response Data in a Birth Cohort Study." Journal of Allergy and Clinical Immunology 129, no. 2 (February 2012): AB199. http://dx.doi.org/10.1016/j.jaci.2011.12.307.

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Loncke, Justine, Axel Mayer, Veroni I. Eichelsheim, Susan J. T. Branje, Wim H. J. Meeus, Hans M. Koot, Ann Buysse, and Tom Loeys. "Latent State-Trait Models for Longitudinal Family Data." European Journal of Psychological Assessment 33, no. 4 (July 2017): 256–70. http://dx.doi.org/10.1027/1015-5759/a000415.

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Abstract. Support is key to healthy family functioning. Using the family social relations model (SRM), it has already been shown that variability in perceived support is mostly attributed to individual perceiver effects. Little is known, however, as to whether those effects are stable or occasion-specific. Several methods have been proposed within the structural equation modeling (SEM) framework for the investigation of hypotheses on stable and occasion-specific aspects of such psychological attributes. In this paper, we explore the applicability of different models for determining the consistency of SRM effects of perceived support: the multistate model, the singletrait-multistate model, and the trait-state occasion model. We provide a detailed description of the model building process and assumption verification, as well as the supporting R-code. In addition to the methodological contribution on how to combine these models with the SRM, we also provide substantive insights into the consistency of perceived family support. We rely on round robin data on relational support from the Dutch RADAR-Y (Research on Adolescent Development and Relationships – Younger Cohort) study, a 6-year longitudinal study of 500 families with a 13-year-old target adolescent at the start of the study.

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Byrnes, Joshua, Son Nghiem, Clifford Afoakwah, and Paul A. Scuffham. "Queensland Cardiovascular Data Linkage (QCard): A population-based cohort study." F1000Research 9 (April 23, 2020): 282. http://dx.doi.org/10.12688/f1000research.23261.1.

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Queensland is Australia's hotspot for cardiovascular disease (CVD). Critically, beyond modifiable lifestyle risk factors; socio-demographic differences and environmental factors account for significant variations in healthcare use and outcomes among cardiac patients across the country. To better understand the impacts of these factors on the health of cardiac patients, there is a need for a comprehensive and robust longitudinal cohort study that can unpack the underlying dynamics. This paper describes the protocol for the Queensland Cardiovascular Linkage (QCard) Study. The QCard is a longitudinal linkage cohort study of cardiac patients who were first hospitalised with any cardiac condition in 2010, with follow up hospitalisations until December 2015. The primary aim of the QCard is to identify and characterise the nature and impact of socio-demographic inequality among those presenting for the first time with the most common form of CVD in Australia (heart disease) in Queensland from 2010 with minimum 5-years follow-up of subsequent healthcare utilisation and outcomes. A secondary aim is to undertake an exploration of the impact of environmental and specific health service factors on healthcare use and survival time in the same QCard cohort. Administrative public and private hospital inpatient, outpatient and emergency department data for all of Queensland will be linked with individual primary care data and pharmaceutical data. These data will also be linked to regional socio-demographic data and environmental data, as well as data that describes the features of each hospital in the region. The findings from the study will provide critical information for cardiac patients, clinicians and health policymakers. Such information ranges from identifying most vulnerable cardiac patients who may require targeted needs to providing estimates for cost-effective ways of evaluating healthcare interventions that seek to improve the health of cardiac patients.

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Wu, Rongxiu, Xian Wu, Michael R. Peabody, and Thomas R. O'Neill. "A Longitudinal Study of Differences in Canadian and US Medical Student Preparation for Family Medicine." Family Medicine 51, no. 10 (November 7, 2019): 817–22. http://dx.doi.org/10.22454/fammed.2019.840363.

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Background and Objectives: Previous research has found differences in preparation for entry into family medicine training between graduates of US and Canadian medical schools. However, this research was limited in that it utilized cross-sectional data to examine a longitudinal issue. This study aimed to examine these differences with a longitudinal data set. Methods: A comparison of the performance on the American Board of Family Medicine (ABFM) In-Training Exam (ITE) between 2014 and 2016 was conducted by examining the performance of Canadian medical school graduates and US medical school graduates longitudinally, as well as cross-sectionally, using independent t tests. Results: For first-year residents (PGY1), the Canadian 2014/2015 cohort showed significantly higher mean scores than US medical school graduates (USMG) and international medical school graduates (IMG). The Canadian 2015/2016 cohort showed no statistical difference from the USMGs, but did have a significantly higher mean than the IMGs. For second-year residents (PGY2), the Canadian 2014/2015 cohort showed a significantly lower mean than the USMG cohort, but had a significantly higher mean than the IMG cohort. The Canadian 2015/2016 cohort showed a statistically lower mean than the USMG cohort and no difference compared to the IMG cohort. Conclusions: Based on a comparison of ABFM ITE scores between 2014 and 2016, the Canadian medical school graduates performed as well as or better than the US graduates upon entry into residency, but performance was reversed for the second year of training. Our results also suggest an equity value of ACGME residency training independent of location of undergraduate medical training.

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Lyu, Tianchen, Yunli Chen, Yongle Zhan, Yingjie Shi, Hexin Yue, Xuan Liu, Yaohan Meng, et al. "Cohort profile: the Chinese Pregnant Women Cohort Study and Offspring Follow-up (CPWCSaOF)." BMJ Open 11, no. 3 (March 2021): e044933. http://dx.doi.org/10.1136/bmjopen-2020-044933.

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PurposeA multicentre prospective cohort study, known as the Chinese Pregnant Women Cohort Study (CPWCS), was established in 2017 to collect exposure data during pregnancy (except environmental exposure) and analyse the relationship between lifestyle during pregnancy and obstetric outcomes. Data about mothers and their children’s life and health as well as children’s laboratory testing will be collected during the offspring follow-up of CPWCS, which will enable us to further investigate the longitudinal relationship between exposure in different periods (during pregnancy and childhood) and children’s development.Participants9193 pregnant women in 24 hospitals in China who were in their first trimester (5–13 weeks gestational age) from 25 July 2017 to 26 November 2018 were included in CPWCS by convenience sampling. Five hospitals in China which participated in CPWCS with good cooperation will be selected as the sample source for the Chinese Pregnant Women Cohort Study (Offspring Follow-up) (CPWCS-OF).Findings to dateSome factors affecting pregnancy outcomes and health problems during pregnancy have been discovered through data analysis. The details are discussed in the ‘Findings to date’ section.Future plansInfants and children and their mothers who meet the criteria will be enrolled in the study and will be followed up every 2 years. The longitudinal relationship between exposure (questionnaire data, physical examination and biospecimens, medical records, and objective environmental data collected through geographical information system and remote sensing technology) in different periods (during pregnancy and childhood) and children’s health (such as sleeping problem, oral health, bowel health and allergy-related health problems) will be analysed.Trail registration numberCPWCS was registered with ClinicalTrials.gov on 18 January 2018: NCT03403543. CPWCS-OF was registered with ClinicalTrials.gov on 24 June 2020: NCT04444791.

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Haddad, Amir, Suzanne Li, Arane Thavaneswaran, Richard J. Cook, Vinod Chandran, and Dafna D. Gladman. "The Incidence and Predictors of Infection in Psoriasis and Psoriatic Arthritis: Results from Longitudinal Observational Cohorts." Journal of Rheumatology 43, no. 2 (January 15, 2016): 362–66. http://dx.doi.org/10.3899/jrheum.140067.

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Objective.To investigate the rate, type, characteristics, and predictors of infection in a cohort of patients with psoriatic arthritis (PsA) and a cohort of patients with psoriasis without arthritis (PsC).Methods.A cohort of patients with PsA and a cohort of patients with PsC were followed according to a standard protocol and information on the occurrence of infections was recorded. The rate of infection was estimated by fitting an exponential model. A Weibull regression model was fitted to estimate the relative risk of first infection associated with a number of covariates. Risk factors for recurrent infections were investigated using generalized estimating equations.Results.There were 498 and 74 infections reported among 695 and 509 patients with PsA and PsC, respectively, with an incidence rate of 19.6 per 100 person-years in the PsA cohort compared with 12.2 in the PsC cohort. The HR of the time to the first infection in PsA versus PsC was 1.6 (p = 0.002), and higher in patients treated with biologics versus nonbiologics at 1.56 (95% CI 1.22–2.00) in PsA and 1.50 (95% CI 0.64–3.54) in the PsC cohorts. Female sex and treatment with biologics were associated with infection in the PsA cohort, whereas a lower Psoriasis Area and Severity Index score and a higher Functional Comorbidity Index were associated with infection in the PsC cohort. Ultraviolet treatment was protective against infection in both cohorts. No difference in rates of hospitalization was found (p = 0.66). There were no infection-related deaths in either cohort.Conclusion.The incidence rate of infection was higher in the PsA than the PsC cohort and higher among patients treated with biologics. The data confirm the association between infection and biologic treatment in psoriatic disease.

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Avraam, Demetris, Rebecca C. Wilson, and Paul Burton. "Synthetic ALSPAC longitudinal datasets for the Big Data VR project." Wellcome Open Research 2 (August 30, 2017): 74. http://dx.doi.org/10.12688/wellcomeopenres.12441.1.

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Three synthetic datasets - of observation size 15,000, 155,000 and 1,555,000 participants, respectively - were created by simulating eleven cardiac and anthropometric variables from nine collection ages of the ALSAPC birth cohort study. The synthetic datasets retain similar data properties to the ALSPAC study data they are simulated from (co-variance matrices, as well as the mean and variance values of the variables) without including the original data itself or disclosing participant information. In this instance, the three synthetic datasets have been utilised in an academia-industry collaboration to build a prototype virtual reality data analysis software, but they could have a broader use in method and software development projects where sensitive data cannot be freely shared.

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Journal articles on the topic 'Longitudinal cohort data'

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