International Journal of Population Data Science最新文献

Introduction: Linkage of public law family court care proceedings (CP) data to all women giving birth in NHS hospitals in England allows calculation of the cumulative incidence of CP involvement for mothers with first children born.

Objectives: To assess linkage accuracy and determine the 10-year cumulative incidence of CP after a first live birth (FLB) for population subgroups.

Method: NHS England linked records for mothers in Cafcass (Children and Family Court Advisory and Support Service) involved in CP (2007-2021) to all mothers with a delivery in England using Hospital Episode Statistics (HES: 1997-21). We calculated match rates and assessed indirect evidence of potential false positive and missed links. We used survival analyses to estimate cumulative incidence of CP within 10 years overall and for five-year maternal age groups at first live birth.

Results: Of 120,937 mothers involved in CP, 6.6% (n = 8,010) were excluded due to missing postcode or date of birth, or age <15 or >50. Of the remaining 112,927 mothers, 92,891 (82.8%) were linked to a HES delivery record. Match rates were lowest for mothers with an ethnic minority background, older at first case, or residing in Greater London, but improved over time.Of 3,572,737 mothers with a FLB, 38,462 had CP involvement. The cumulative incidence of CP at 10 years from FLB was 1.31% (95% Confidence Interval [CI]; 1.29-1.32) overall and highest in mothers aged 15-19 years (6.79%, 95% CI: 6.69-6.89) and those living in the most deprived areas (2.47%, 95% CI: 2.43-2.51).

Conclusion: One in 77 of all mothers and one in 15 aged less than 20 at first live birth were involved in CP within 10 years. Linkage error may underestimate the incidence of CP for mothers in London or with an ethnic minority background.

Key points: Overall, 82.8% of women recorded as a mother in Cafcass care proceedings were linked to a hospital delivery record.Match rates were lowest for mothers with an ethnic minority background, older age at first child, or residing in Greater London.1.3% of all mothers (1 in 77) with a first birth were involved in care proceedings within 10 years and 6.8% (1 in 15) of mothers aged <20 at first live birth.

Introduction: In the UK, mental disorders are one of the most common reasons for claiming a benefit relating to unemployment, income, sickness and disability. Limited information exists regarding the demographic characteristics and psychiatric profiles of working age individuals claiming benefits in London. Until recently, detailed data on both mental disorders and benefit receipt were unavailable.

Objectives: To establish and describe a cohort of working age adults accessing secondary mental health services and benefits related to unemployment, income, sickness, and disability.

Methods: Using a novel data linkage containing electronic secondary mental health records from the South London and Maudsley (SLaM) NHS Foundation Trust and benefits data from the Department for Work and Pensions (DWP), we present descriptive statistics on sociodemographics, psychiatric diagnoses, and benefits received among a cohort of working age adults. The DWP benefits data window covers the period January 2007-June 2020, the SLaM data window covers the period January 2007-June 2019.

Results: We identified n = 150,348 patients (18-65 years), who had attended SLaM secondary mental health services, 78.3% of which had received a benefit relating to unemployment, income, sickness and disability. Of this group, 68% had a recorded primary psychiatric diagnosis. We found that a much higher percentage of those with a primary psychiatric diagnosis received more than one benefit (69.4%) compared to those who had not received a primary psychiatric diagnosis (30.6%). Almost 70% of claimants who obtained more than one benefit were identified as living within the two quintiles representing the highest levels of deprivation in the South-east London boroughs served by SLaM.

Conclusions: We showed types of benefits received among working age adults accessing secondary mental health services. This cohort will be further examined to explore trajectories of mental health care and benefit receipt and provide evidence that will help to inform both DWP policies and mental health care delivery.

Introduction: The validity of chronic disease case definitions for administrative health data may change over time due to changes in data quality. Trend control charts to identify out-of-control (OOC; i.e., unexpected) observations in a time series may indicate where disease estimates are influenced by changes in data quality.

Objective: Apply and compare trend control charts methods for multiple sclerosis (MS) incidence and prevalence estimates using previously-validated case definitions for Manitoba, Canada.

Methods: Eight case definitions were identified from published literature and applied to Manitoba administrative health data from January 1, 1972 to December 31, 2018. Incidence and prevalence trends were modeled using negative binomial and generalized estimating equation models, respectively. Trend control charts were used to plot predicted case counts against observed case counts. Control limits to identify OOC observations were calculated using two methods: predicted case count ±0.8*standard deviation (0.8*SD) and predicted case count ±2*standard deviation (2*SD). Differences in proportion of OOC observations across case definitions was assessed using McNemar's test.

Results: The proportion of OOC observations ranged from 0.71 to 0.90 for incidence and 0.72 to 0.98 for prevalence when using the 0.8*SD control limits. A lower proportion of OOC observations (0.46 to 0.74 for incidence; 0.30 to 0.74 for prevalence) was observed for the 2*SD control limits. Neither method resulted in significant differences in OOC observations across case definitions.

Conclusions: The proportion of OOC observations in trend control charts varied with the control limit method adopted, but statistical significance did not. Trend control charts are a potentially useful tool for developing surveillance methods, but may benefit from disease-specific calibrated control limits.

Introduction: The Western Australia (WA) Respiratory Infections Linked Data Platform is a population-based cohort established to investigate the epidemiology of RSV and other respiratory infections in children aged 0-10 years, incorporating microbiological testing patterns, hospital admissions, emergency department presentations, and socio-demographic data.

Methods: The cohort was formed through individual linkages between datasets from the WA Department of Health including the Birth and Death Registry, Midwives Notification System (MNS), Hospital Morbidity Data Collection, Emergency Department Data Collection, WA Notifiable Diseases Database, WA Register of Developmental Anomalies, WA Cerebral Palsy Register, WA Antenatal Vaccination Database, WA Family Connections, and PathWest Respiratory Virus Surveillance Data. Hospitalisations and emergency department presentations were temporally linked to routine respiratory viral surveillance data.

Results: The cohort consists of 368,830 WA births between 1 January 2010 and 31 December 2020 with accompanying perinatal and demographic data, and with secondary care follow-up to 30 June 2022. Of these births, 24,660 (6.7%) identify as Aboriginal. A total of 4,077 (1.1%) children died from all causes during the study period (2010-2020), and 9.2% (33,818) of children were born preterm (<37 weeks).

Conclusion: The Respiratory Infections Linked Data Platform enables epidemiological investigations, identifying virus-specific risk groups, risk factors, clinical presentation, viral testing patterns, long-term impacts and accurate measures of viral incidence rates in risk and population sub-groups This will not only aid in the calculation of cost-effectiveness estimates of interventions such as immunisations, but also provide guidance for design and implementation of such programs to priority groups. The Respiratory Infections Linked Data Platform will also enable evaluation of the direct and indirect effects of maternal and infant vaccines and new therapeutics. Analyses using this platform will also generate epidemiological data needed for other respiratory viruses on the vaccine pipeline such as parainfluenza virus and human metapneumovirus.

Introduction: There are two main data sources for perinatal data in Ontario, Canada: the BORN BIS and CIHI-DAD. Such databases are used for perinatal health surveillance and research, and to guide health care related decisions.

Objectives: Our primary objective was to examine the level of agreement between the BIS and CIHI-DAD. Our secondary objectives were to identify the differences between the data sources when identifying a low-risk birth (LRB) cohort and to understand their implications.

Methods: We conducted a population-based cohort study comparing characteristics and clinical outcomes of all linkable births in BIS and CIHI-DAD between 1^st April 2012 and 31^st March 2018. We excluded out-of-hospital births, those with invalid healthcare numbers, non-Ontario residents and gestational age <20 weeks. We compared the portion of the cohort that met the criteria of a provincial definition of LRB based on each data source and compared clinical outcomes between the groups.

Results: During the study period, 779,979 eligible births were linkable between the two data sources. After applying the LRB exclusions, there were 129,908 cases in the BIS and 136,184 cases in CIHI-DAD. Most exclusion criteria had almost perfect, substantial or moderate agreement. The agreement for non-cephalic presentation and BMI ≥ 40 kg/m² (kappa coefficients 0.409 and 0.256, respectively) was fair. Comparison between the two LRB cohorts identified differences in the prevalence of cesarean (14.3% BIS versus 12.0% CIHI-DAD) and NICU admission (8.7% BIS versus 7.5% CIHI-DAD) and only 0.01% difference in the prevalence of ICU admission.

Conclusions: Overall, we found high levels of agreement between the BIS and CIHI-DAD. Identifying a LRB cohort in either database may be appropriate, with the caveat of appropriate understanding of the collection, coding and definition of certain outcomes. The decision for selecting a database may depend on which variables are most important in a particular analysis.

Introduction: The Department of Veterans Affairs (VA) Million Veteran Program (MVP) nutrition data is derived from dietary food/beverage intake information collected through a semiquantitative food frequency questionnaire (SFFQ).

Methods: Estimates of dietary energy, nutrient, and non-nutritive food components intakes data were derived from an extensively validated SFFQ, which assessed the habitual frequency of consumption of 61 food items, added sugar, fried food frequency, and 21 nutritional supplements over the 12 months preceding questionnaire administration.

Results: Complete nutrition data was available for 353,418 MVP participants as of 30^th September 2021. Overall, 91.5% of MVP participants with nutrition data were male with an average age of 65.7 years at enrollment. Participants who completed the SFFQ were primarily White (82.5%), and Blacks accounted for 13.2% of the responders. Mean ± SD energy intake for 353, 418 MVP participants was 1428 ± 616 kcal/day, which was 1434 ± 617 kcal/day for males and 1364 ± 601 kcal/day for females. Energy intake and information on 322 nutrients and non-nutritive food components is available through contact with MVP for research collaborations at www.research.va.gov/mvp.

Conclusions: The energy and nutrient data derived from MVP SFFQ are an invaluable resource for Veteran health and research. In conjunction with the MVP Lifestyle Survey, electronic health records, and genomic data, MVP nutrition data may be used to assess nutritional status and related risk factors, disease prevalence, and determinants of health that can provide scientific support for the development of evidence-based public health policy and health promotion programs and services for Veterans and general population.

Introduction: The World Health Organisation declared a global pandemic in March 2020. The impact of COVID-19 has not been felt equally by all regions and sections of society. The extent to which socio-demographic and deprivation factors have adversely impacted on outcomes is of concern to those looking to 'level-up' and decrease widening health inequalities.

Objectives: In this paper we investigate the impact of deprivation on the outcomes for hospitalised COVID-19 patients in Greater Manchester during the first wave of the pandemic in the UK (30/12/19-2/1/21), controlling for proven risk factors from elsewhere in the literature.

Methods: We fitted Negative Binomial and logistic regression models to NHS administrative data to investigate death from COVID in hospital and length of stay for surviving patients in a sample of adult patients admitted within Greater Manchester (N = 10,372, spell admission start dates from 30/12/2019 to 02/01/2021 inclusive).

Results: Deprivation was associated with death risk for hospitalised patients but not with length of stay. Male sex, co-morbidities and older age was associated with higher death risk. Male sex and co-morbidities were associated with increased length of stay. Black and other ethnicities stayed longer in hospital than White and Asian patients. Period effects were detected in both models with death risk reducing over time, but the length of stay increasing.

Conclusion: Deprivation is important for death risk; however, the picture is complex, and the results of this analysis suggest that the reported COVID related mortality and deprivation linked reductions in life expectancy, may have occurred in the community, rather than in acute settings.

Highlights: Older age and male sex are predictive of longer hospital stays and higher death risk for hospitalised cases in this analysis.Deprivation is associated with death risk but not length of stay for hospitalised patients.Ethnicity is associated with length of stay, but not with death risk.There is a social gradient in health, but these data would suggest that once in the care of an NHS hospital in an acute health episode, outcomes are more equal.

Background: Colorectal cancer (CRC) is the fourth most common type of cancer in the United Kingdom and the second leading cause of cancer death. Despite improvements in CRC survival over time, Scotland lags behind its UK and European counterparts. In this study, we carry out an exploratory analysis which aims to provide contemporary, population level evidence on CRC treatment and survival in Scotland.

Methods: We conducted a retrospective population-based analysis of adults with incident CRC registered on the Scottish Cancer Registry (Scottish Morbidity Record 06 (SMR06)) between January 2006 and December 2018. The CRC cohort was linked to hospital inpatient (SMR01) and National Records of Scotland (NRS) deaths records allowing a description of their demographic, diagnostic and treatment characteristics. Cox proportional hazards regression models were used to explore the demographic and clinical factors associated with all-cause mortality and CRC specific mortality after adjusting for patient and tumour characteristics among people identified as early-stage and treated with surgery.

Results: Overall, 32,691 (73%) and 12,184 (27%) patients had a diagnosis of colon and rectal cancer respectively, of whom 55% and 53% were early-stage and treated with surgery. Five year overall survival (CRC specific survival) within this cohort was 72% (82%) and 76% (84%) for patients with colon and rectal cancer respectively. Cox proportional hazards models revealed significant variation in mortality by sex, area-based deprivation and geographic location.

Conclusions: In a Scottish population of patients with early-stage CRC treated with surgery, there was significant variation in risk of death, even after accounting for clinical factors and patient characteristics.