Is obesity more likely among children sharing a household with an older child with obesity? Cross-sectional study of linked National Child Measurement Programme data and electronic health records.

BACKGROUND/OBJECTIVES: We identified household members from electronic health records linked to National Child Measurement Programme (NCMP) data to estimate the likelihood of obesity among children living with an older child with obesity. METHODS: We included 126 829 NCMP participants in four London boroughs and assigned households from encrypted Unique Property Reference Numbers for 115 466 (91.0%). We categorised the ethnic-adjusted body mass index of the youngest and oldest household children (underweight/healthy weight <91st, ≥91st overweight <98th, obesity ≥98th centile) and estimated adjusted ORs and 95% CIs of obesity in the youngest child by the oldest child's weight status, adjusting for number of household children (2, 3 or ≥4), youngest child's sex, ethnicity and school year of NCMP participation. RESULTS: We identified 19 702 households shared by two or more NCMP participants (% male; median age, range (years)-youngest children: 51.2%; 5.2, 4.1-11.8; oldest children: 50.6%; 10.6, 4.1-11.8). One-third of youngest children with obesity shared a household with another child with obesity (33.2%; 95% CI: 31.2, 35.2), compared with 9.2% (8.8, 9.7) of youngest children with a healthy weight. Youngest children living with an older child considered overweight (OR: 2.33; 95% CI: 2.06, 2.64) or obese (4.59; 4.10, 5.14) were more likely to be living with obesity. CONCLUSIONS: Identifying children sharing households by linking primary care and school records provides novel insights into the shared weight status of children sharing a household. Qualitative research is needed to understand how food practices vary by household characteristics to increase understanding of how the home environment influences childhood obesity.

Are children living with obesity more likely to experience musculoskeletal symptoms during childhood? A linked longitudinal cohort study using primary care records.

OBJECTIVE: To assess whether there is a higher incidence of musculoskeletal consultations in general practice among children with obesity. DESIGN: Longitudinal SETTING: 285 north-east London general practitioners (GPs). PARTICIPANTS: 63 418 (50.9% boys) Reception and 55 364 (50.8% boys) Year 6 National Child Measurement Programme (NCMP) participants, linked to GP electronic health records (EHRs). MAIN OUTCOME MEASURE: A GP consultation with a recorded musculoskeletal symptom or diagnosis. METHODS: We calculated proportions with a musculoskeletal consultation by ethnic-adjusted weight status (underweight <2nd; overweight ≥91st; obese ≥98th centile), sex, ethnicity, and area-level deprivation. We estimated mutually-adjusted hazard ratios (HR) and 95% confidence intervals (95% CI) using Cox's proportional regression models stratified by school year and sex. RESULTS: We identified 1868 (3.0%) Reception and 4477 (8.1%) Year 6 NCMP participants with at least one musculoskeletal consultation. In adjusted analyses, Reception year girls with a body mass index (BMI) classified as overweight (HR 1.24, 95% CI 1.02 to 1.52) or obese (HR 1.67, 95% CI 1.35 to 2.06) were more likely to have at least one musculoskeletal consultation. Year 6 girls with obesity were more likely (HR 1.20, 95% CI 1.07 to 1.35), and boys with a BMI in the underweight range were less likely (HR 0.39, 95% CI 0.21 to 0.73), to have a musculoskeletal consultation. CONCLUSIONS: Girls living with obesity at the start or end of primary school are more likely to attend their GP for a musculoskeletal consultation. Routine linkage of NCMP data to EHRs provides useful insights into childhood health conditions related to excess weight in early childhood. Recognition of obesity as a contributing factor for musculoskeletal symptoms may inform clinical management, particularly in girls.

Effect on life expectancy of temporal sequence in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure among 1·7 million individuals in Wales with 20-year follow-up: a retrospective cohort study using linked data.

BACKGROUND: To inform targeted public health strategies, it is crucial to understand how coexisting diseases develop over time and their associated impacts on patient outcomes and health-care resources. This study aimed to examine how psychosis, diabetes, and congestive heart failure, in a cluster of physical-mental health multimorbidity, develop and coexist over time, and to assess the associated effects of different temporal sequences of these diseases on life expectancy in Wales. METHODS: In this retrospective cohort study, we used population-scale, individual-level, anonymised, linked, demographic, administrative, and electronic health record data from the Wales Multimorbidity e-Cohort. We included data on all individuals aged 25 years and older who were living in Wales on Jan 1, 2000 (the start of follow-up), with follow-up continuing until Dec 31, 2019, first break in Welsh residency, or death. Multistate models were applied to these data to model trajectories of disease in multimorbidity and their associated effect on all-cause mortality, accounting for competing risks. Life expectancy was calculated as the restricted mean survival time (bound by the maximum follow-up of 20 years) for each of the transitions from the health states to death. Cox regression models were used to estimate baseline hazards for transitions between health states, adjusted for sex, age, and area-level deprivation (Welsh Index of Multiple Deprivation [WIMD] quintile). FINDINGS: Our analyses included data for 1 675 585 individuals (811 393 [48·4%] men and 864 192 [51·6%] women) with a median age of 51·0 years (IQR 37·0-65·0) at cohort entry. The order of disease acquisition in cases of multimorbidity had an important and complex association with patient life expectancy. Individuals who developed diabetes, psychosis, and congestive heart failure, in that order (DPC), had reduced life expectancy compared with people who developed the same three conditions in a different order: for a 50-year-old man in the third quintile of the WIMD (on which we based our main analyses to allow comparability), DPC was associated with a loss in life expectancy of 13·23 years (SD 0·80) compared with the general otherwise healthy or otherwise diseased population. Congestive heart failure as a single condition was associated with mean a loss in life expectancy of 12·38 years (0·00), and with a loss of 12·95 years (0·06) when preceded by psychosis and 13·45 years (0·13) when followed by psychosis. Findings were robust in people of older ages, more deprived populations, and women, except that the trajectory of psychosis, congestive heart failure, and diabetes was associated with higher mortality in women than men. Within 5 years of an initial diagnosis of diabetes, the risk of developing psychosis or congestive heart failure, or both, was increased. INTERPRETATION: The order in which individuals develop psychosis, diabetes, and congestive heart failure as combinations of conditions can substantially affect life expectancy. Multistate models offer a flexible framework to assess temporal sequences of diseases and allow identification of periods of increased risk of developing subsequent conditions and death. FUNDING: Health Data Research UK.

Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland.

There is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018. We used linked demographic information, and secondary care electronic health records from 1st January 2000. Individuals with at least two of the 31 Elixhauser Comorbidity Index conditions were identified as having multimorbidity. Market basket analysis was used to cluster the conditions for the whole population and then repeatedly stratified by age, sex and deprivation. 318,235 individuals were included in the analysis, with 67,728 (21·3%) having multimorbidity. We identified five distinct clusters of conditions in the population with multimorbidity: alcohol misuse, cancer, obesity, renal failure, and heart failure. Clusters of long-term conditions differed by age, sex and socioeconomic deprivation, with some clusters not present for specific strata and others including additional conditions. These findings highlight the importance of considering demographic factors during both clustering analysis and intervention planning for individuals with multiple long-term conditions. By taking these factors into account, the healthcare system may be better equipped to develop tailored interventions that address the needs of complex patients.

Are children with obesity at school entry more likely to have a diagnosis of a musculoskeletal condition? Findings from a systematic review.

BACKGROUND: Children with obesity at school entry are at increased risk of persistent obesity throughout childhood and adulthood. Little is known about associations with adverse health outcomes with onset during childhood including those affecting the musculoskeletal system. We examined the association between obesity present at school entry and adverse musculoskeletal diagnoses with onset during childhood. METHODS: We searched three electronic databases to identify longitudinal studies published in English between January 2000 and June 2022 assessing associations between obesity measured at school entry (around age 5 years) and musculoskeletal diagnoses made before age 20 years. Two reviewers screened titles, abstracts and full-text using EPPI-Reviewer software. Bias and quality of eligible studies were appraised using The Quality Assessment tool for Observational Cohort and Cross-sectional studies and findings synthesised. RESULTS: We identified four eligible studies from 291 unique records, three conducted in Spain and one in Scotland. These studies reported on 1 232 895 children (available data: 51.4% boys; none reported ethnic distribution) with study sample sizes ranging from <2000 to 600 000 and length of follow-up from 2 to 13 years. Quantitative synthesis of findings across these four studies was not possible due to differences in outcomes and effect sizes reported. Children with obesity at school entry were more likely to receive diagnoses of slipped capital femoral epiphysis, back pain, fractures and musculoskeletal complaints made in primary care settings. Included studies were assessed as of 'fair' to 'good' quality. CONCLUSION: There is good to fair evidence to suggest children with obesity at school entry are more likely to receive a diagnosis of a musculoskeletal condition during childhood. Further research is needed to replicate these findings in ethnically diverse populations and to investigate whether these are causal associations. The implications of this for children's mobility and quality of life and future musculoskeletal health warrants further assessment.

Impact of the COVID-19 pandemic on timeliness and equity of measles, mumps and rubella vaccinations in North East London: a longitudinal study using electronic health records.

OBJECTIVES: To quantify the effect of the COVID-19 pandemic on the timeliness of, and geographical and sociodemographic inequalities in, receipt of first measles, mumps and rubella (MMR) vaccination. DESIGN: Longitudinal study using primary care electronic health records. SETTING: 285 general practices in North East London. PARTICIPANTS: Children born between 23 August 2017 and 22 September 2018 (pre-pandemic cohort) or between 23 March 2019 and 1 May 2020 (pandemic cohort). MAIN OUTCOME MEASURE: Receipt of timely MMR vaccination between 12 and 18 months of age. METHODS: We used logistic regression to estimate the ORs (95% CIs) of receipt of a timely vaccination adjusting for sex, deprivation, ethnic background and Clinical Commissioning Group. We plotted choropleth maps of the proportion receiving timely vaccinations. RESULTS: Timely MMR receipt fell by 4.0% (95% CI: 3.4% to 4.6%) from 79.2% (78.8% to 79.6%) to 75.2% (74.7% to 75.7%) in the pre-pandemic (n=33 226; 51.3% boys) and pandemic (n=32 446; 51.4%) cohorts, respectively. After adjustment, timely vaccination was less likely in the pandemic cohort (0.79; 0.76 to 0.82), children from black (0.70; 0.65 to 0.76), mixed/other (0.77; 0.72 to 0.82) or with missing (0.77; 0.74 to 0.81) ethnic background, and more likely in girls (1.07; 1.03 to 1.11) and those from South Asian backgrounds (1.39; 1.30 to 1.48). Children living in the least deprived areas were more likely to receive a timely MMR (2.09; 1.78 to 2.46) but there was no interaction between cohorts and deprivation (Wald statistic: 3.44; p=0.49). The proportion of neighbourhoods where less than 60% of children received timely vaccination increased from 7.5% to 12.7% during the pandemic. CONCLUSIONS: The COVID-19 pandemic was associated with a significant fall in timely MMR receipt and increased geographical clustering of measles susceptibility in an area of historically low and inequitable MMR coverage. Immediate action is needed to avert measles outbreaks and support primary care to deliver timely and equitable vaccinations.

Evaluation of the ASSIGN open-source deterministic address-matching algorithm for allocating unique property reference numbers to general practitioner-recorded patient addresses.

INTRODUCTION: Linking places to people is a core element of the UK government's geospatial strategy. Matching patient addresses in electronic health records to their Unique Property Reference Numbers (UPRNs) enables spatial linkage for research, innovation and public benefit. Available algorithms are not transparent or evaluated for use with addresses recorded by health care providers. OBJECTIVES: To describe and quality assure the open-source deterministic ASSIGN address-matching algorithm applied to general practitioner-recorded patient addresses. METHODS: Best practice standards were used to report the ASSIGN algorithm match rate, sensitivity and positive predictive value using gold-standard datasets from London and Wales. We applied the ASSIGN algorithm to the recorded addresses of a sample of 1,757,018 patients registered with all general practices in north east London. We examined bias in match results for the study population using multivariable analyses to estimate the likelihood of an address-matched UPRN by demographic, registration, and organisational variables. RESULTS: We found a 99.5% and 99.6% match rate with high sensitivity (0.999,0.998) and positive predictive value (0.996,0.998) for the Welsh and London gold standard datasets respectively, and a 98.6% match rate for the study population.The 1.4% of the study population without a UPRN match were more likely to have changed registered address in the last 12 months (match rate: 95.4%), be from a Chinese ethnic background (95.5%), or registered with a general practice using the SystmOne clinical record system (94.4%). Conversely, people registered for more than 6.5 years with their general practitioner were more likely to have a match (99.4%) than those with shorter registration durations. CONCLUSIONS: ASSIGN is a highly accurate open-source address-matching algorithm with a high match rate and minimal biases when evaluated against a large sample of general practice-recorded patient addresses. ASSIGN has potential to be used in other address-based datasets including those with information relevant to the wider determinants of health.

Protocol for the development of the Wales Multimorbidity e-Cohort (WMC): data sources and methods to construct a population-based research platform to investigate multimorbidity.

INTRODUCTION: Multimorbidity is widely recognised as the presence of two or more concurrent long-term conditions, yet remains a poorly understood global issue despite increasing in prevalence.We have created the Wales Multimorbidity e-Cohort (WMC) to provide an accessible research ready data asset to further the understanding of multimorbidity. Our objectives are to create a platform to support research which would help to understand prevalence, trajectories and determinants in multimorbidity, characterise clusters that lead to highest burden on individuals and healthcare services, and evaluate and provide new multimorbidity phenotypes and algorithms to the National Health Service and research communities to support prevention, healthcare planning and the management of individuals with multimorbidity. METHODS AND ANALYSIS: The WMC has been created and derived from multisourced demographic, administrative and electronic health record data relating to the Welsh population in the Secure Anonymised Information Linkage (SAIL) Databank. The WMC consists of 2.9 million people alive and living in Wales on the 1 January 2000 with follow-up until 31 December 2019, Welsh residency break or death. Published comorbidity indices and phenotype code lists will be used to measure and conceptualise multimorbidity.Study outcomes will include: (1) a description of multimorbidity using published data phenotype algorithms/ontologies, (2) investigation of the associations between baseline demographic factors and multimorbidity, (3) identification of temporal trajectories of clusters of conditions and multimorbidity and (4) investigation of multimorbidity clusters with poor outcomes such as mortality and high healthcare service utilisation. ETHICS AND DISSEMINATION: The SAIL Databank independent Information Governance Review Panel has approved this study (SAIL Project: 0911). Study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

Timing of singleton births by onset of labour and mode of birth in NHS maternity units in England, 2005-2014: A study of linked birth registration, birth notification, and hospital episode data.

BACKGROUND: Maternity care has to be available 24 hours a day, seven days a week. It is known that obstetric intervention can influence the time of birth, but no previous analysis at a national level in England has yet investigated in detail the ways in which the day and time of birth varies by onset of labour and mode of giving birth. METHOD: We linked data from birth registration, birth notification, and Maternity Hospital Episode Statistics and analysed 5,093,615 singleton births in NHS maternity units in England from 2005 to 2014. We used descriptive statistics and negative binomial regression models with harmonic terms to establish how patterns of timing of birth vary by onset of labour, mode of giving birth and gestational age. RESULTS: The timing of birth by time of day and day of the week varies considerably by onset of labour and mode of birth. Spontaneous births after spontaneous onset are more likely to occur between midnight and 6am than at other times of day, and are also slightly more likely on weekdays than at weekends and on public holidays. Elective caesarean births are concentrated onto weekday mornings. Births after induced labours are more likely to occur at hours around midnight on Tuesdays to Saturdays and on days before a public holiday period, than on Sundays, Mondays and during or just after a public holiday. CONCLUSION: The timing of births varies by onset of labour and mode of birth and these patterns have implications for midwifery and medical staffing. Further research is needed to understand the processes behind these findings.

Impact of asthma on educational attainment in a socioeconomically deprived population: a study linking health, education and social care datasets.

BACKGROUND: Asthma has the potential to adversely affect children's school examination performance, and hence longer term life chances. Asthma morbidity is especially high amongst UK ethnic minority children and those experiencing social adversity, populations which also have poor educational outcomes. We tested the hypothesis that asthma adversely affects performance in national school examinations in a large cohort from an area of ethnic diversity and social deprivation. METHODS AND FINDINGS: With a novel method (using patient and address-matching algorithms) we linked administrative and clinical data for 2002-2005 for children in east London aged 5-14 years to contemporaneous education and social care datasets. We modelled children's performance in school examinations in relation to socio-demographic and clinical variables. The dataset captured examination performance for 12,136 children who sat at least one national examination at Key Stages 1-3. For illustration, estimates are presented as percentage changes in Key Stage 2 results. Having asthma was associated with a 1.1% increase in examination scores (95%CI 0.4 to 1.7)%,p = 0.02. Worse scores were associated with Bangladeshi ethnicity -1.3%(-2.5 to -0.1)%,p = 0.03; special educational need -14.6%(-15.7 to -13.5)%,p = 0.02; mental health problems -2.5%(-4.1 to -0.9)%,p = 0.003, and social adversity: living in a smoking household -1.2(-1.7 to -0.6)%,p<0.001; living in social housing -0.8%(-1.3 to -0.2)% p = 0.01, and entitlement to free school meals -0.8%(-1.5 to -0.1)%,p<0.001. CONCLUSIONS: Social adversity and ethnicity, but not asthma, are associated with poorer performance in national school examinations. Policies to improve educational attainment in socially deprived areas should focus on these factors.