Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: An observational cohort study using the OpenSAFELY platform.

BACKGROUND: Obesity and rapid weight gain are established risk factors for noncommunicable diseases and have emerged as independent risk factors for severe disease following Coronavirus Disease 2019 (COVID-19) infection. Restrictions imposed to reduce COVID-19 transmission resulted in profound societal changes that impacted many health behaviours, including physical activity and nutrition, associated with rate of weight gain. We investigated which clinical and sociodemographic characteristics were associated with rapid weight gain and the greatest acceleration in rate of weight gain during the pandemic among adults registered with an English National Health Service (NHS) general practitioner (GP) during the COVID-19 pandemic. METHODS AND FINDINGS: With the approval of NHS England, we used the OpenSAFELY platform inside TPP to conduct an observational cohort study of routinely collected electronic healthcare records. We investigated changes in body mass index (BMI) values recorded in English primary care between March 2015 and March 2022. We extracted data on 17,742,365 adults aged 18 to 90 years old (50.1% female, 76.1% white British) registered with an English primary care practice. We estimated individual rates of weight gain before (δ-prepandemic) and during (δ-pandemic) the pandemic and identified individuals with rapid weight gain (>0.5 kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period (δ-change = δ-pandemic-δ-prepandemic) and defined extreme accelerators as the 10% of individuals with the greatest increase in their rate of weight gain (δ-change ≥1.84 kg/m2/year) between these periods. We estimated associations with these outcomes using multivariable logistic regression adjusted for age, sex, index of multiple deprivation (IMD), and ethnicity. P-values were generated in regression models. The median BMI of our study population was 27.8 kg/m2, interquartile range (IQR) [24.3, 32.1] in 2019 (March 2019 to February 2020) and 28.0 kg/m2, IQR [24.4, 32.6] in 2021. Rapid pandemic weight gain was associated with sex, age, and IMD. Male sex (male versus female: adjusted odds ratio (aOR) 0.76, 95% confidence interval (95% CI) [0.76, 0.76], p < 0.001), older age (e.g., 50 to 59 years versus 18 to 29 years: aOR 0.60, 95% CI [0.60, 0.61], p < 0.001]); and living in less deprived areas (least-deprived-IMD-quintile versus most-deprived: aOR 0.77, 95% CI [0.77, 0.78] p < 0.001) reduced the odds of rapid weight gain. Compared to white British individuals, all other ethnicities had lower odds of rapid pandemic weight gain (e.g., Indian versus white British: aOR 0.69, 95% CI [0.68, 0.70], p < 0.001). Long-term conditions (LTCs) increased the odds, with mental health conditions having the greatest effect (e.g., depression (aOR 1.18, 95% CI [1.17, 1.18], p < 0.001)). Similar characteristics increased odds of extreme acceleration in the rate of weight gain between the prepandemic and pandemic periods. However, changes in healthcare activity during the pandemic may have introduced new bias to the data. CONCLUSIONS: We found female sex, younger age, deprivation, white British ethnicity, and mental health conditions were associated with rapid pandemic weight gain and extreme acceleration in rate of weight gain between the prepandemic and pandemic periods. Our findings highlight the need to incorporate sociodemographic, physical, and mental health characteristics when formulating research, policies, and interventions targeting BMI in the period of post pandemic service restoration and in future pandemic planning.

Prevalence of multimorbidity in survivors of 28 cancer sites: an English nationwide cross-sectional study.

Multimorbidity, the presence of a chronic condition in addition to cancer, is of particular importance to cancer survivors. It has an impact on the progression, stage at diagnosis, prognosis, and treatment of cancer patients. Evidence is scarce on the prevalence of specific comorbidities in survivors of different cancers to inform prevention and management of multimorbidity. The objective of this study is to address this evidence gap by using large scale electronic health data from multiple linked UK healthcare databases to examine the prevalence of multimorbidity in 28 cancer sites. For this population-based cross-sectional study, we linked primary and secondary healthcare data from the UK Clinical Research Practice Datalink (CPRD) GOLD dataset and Hospital Episode Statistics (HES). We identified survivors of 28 common cancers aged 18 years or older at diagnosis who survived 2 years of cancer and compared their multimorbidity with matched controls without a history of cancer. To compare prevalence of individual comorbidity, multivariable logistic regression models, adjusted for confounding factors were used. Between January 1, 2010 and December 31, 2020, we identified 347,028 cancer survivors and 804,299 controls matched on age, sex and general practice. Cancer survivors had a higher prevalence of multimorbidity compared to non-cancer controls across all the cancer sites. Hypertension (56.2%), painful conditions (39.8%), osteoarthritis (38.0%), depression (31.8%) and constipation (31.4%) were the five most frequent chronic conditions reported. Compared to the controls, higher odds of constipation were found in survivors of 25 of the 28 cancer sites and higher odds of anaemia were found in 23 cancer sites. Prevalence of constipation, anaemia and painful conditions were higher after cancer diagnosis compared to before diagnosis. Since these comorbidities are not uniformly assessed as part of any of the comorbidity scales, they tend to be underreported among cancer survivors. The elevated risk of certain comorbidities in cancer survivors suggests the potential for preventative efforts in this population to lower disease burden and improve quality of life. Long-term conditions should not be viewed as the inevitable result of cancer diagnosis and treatment. We need to consider integrated management of chronic conditions tailored to specific cancers to improve cancer survivorship.

Weight trends amongst adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY.

BACKGROUND: COVID-19 pandemic restrictions may have influenced behaviours related to weight. AIMS: To describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and Setting With the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. METHOD: We investigated clinical and sociodemographic characteristics associated with rapid weight gain (>0·5kg/m2/year) using multivariable logistic regression. RESULTS: We extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median δ = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.95[0.92, 0.98]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median δ = 0.0kg/m2/year [ -0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. CONCLUSION: Amongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health condition.

Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: A cross-sectional study using clustering in the UK Clinical Practice Research Datalink.

BACKGROUND: The population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions [LTCs] in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes. METHODS AND FINDINGS: Using linked primary and secondary care data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), we conducted a cross-sectional study of 837,869 individuals with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) registered with an English general practice between 2010 and 2020. The study population included 777,906 people of White ethnicity (93%), 33,915 people of South Asian ethnicity (4%), and 26,048 people of Black African/Caribbean ethnicity (3%). A total of 204 LTCs were considered. Latent class analysis stratified by ethnicity identified 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity was more common among South Asian (59%, 33,915) and Black (56% 26,048) groups compared to the White population (42%, 777,906). Latent class analysis revealed physical and mental health conditions that were common across all ethnic groups (i.e., hypertension, depression, and painful conditions). However, each ethnic group also presented exclusive LTCs and different sociodemographic profiles: In White groups, the cluster with the highest rates/odds of the outcomes was predominantly male (54%, 44,150) and more socioeconomically deprived than the cluster with the lowest rates/odds of the outcomes. On the other hand, South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. At the end of the study, 4% (34,922) of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black early onset multimorbidity populations (535 and 570, respectively); however, the latter groups died younger and lost more years of life. The 3 ethnic groups each displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. Study limitations include the exclusion of individuals with missing ethnicity information, the age of diagnosis not reflecting the actual age of onset, and the exclusion of people from Mixed, Chinese, and other ethnic groups due to insufficient power to investigate associations between multimorbidity and health-related outcomes in these groups. CONCLUSIONS: These findings emphasise the need to identify, prevent, and manage multimorbidity early in the life course. Our work provides additional insights into the excess burden of early onset multimorbidity in those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity and highlights the need to ensure healthcare improvements are equitable.

Unravelling the potential of social prescribing in individual-level type 2 diabetes prevention: a mixed-methods realist evaluation.

BACKGROUND: Social prescribing (SP) usually involves linking patients in primary care with services provided by the voluntary and community sector. Preliminary evidence suggests that SP may offer a means of connecting patients with community-based health promotion activities, potentially contributing to the prevention of long-term conditions, such as type 2 diabetes (T2D). METHODS: Using mixed-methods realist evaluation, we explored the possible contribution of SP to individual-level prevention of T2D in a multi-ethnic, socio-economically deprived population in London, UK. We made comparisons with an existing prevention programme (NHS Diabetes Prevention Programme (NDPP)) where relevant and possible. Anonymised primary care electronic health record data of 447,360 people 18+ with an active GP registration between December 2016 and February 2022 were analysed using quantitative methods. Qualitative data (interviews with 11 primary care clinicians, 11 social prescribers, 13 community organisations and 8 SP users at high risk of T2D; 36 hours of ethnographic observations of SP and NDPP sessions; and relevant documents) were analysed thematically. Data were integrated using visual means and realist methods. RESULTS: People at high risk of T2D were four times more likely to be referred into SP than the eligible general population (RR 4.31 (95% CI 4.17-4.46)), with adjustment for socio-demographic variables resulting in attenuation (RR 1.33 (95% CI 1.27-1.39)). More people at risk of T2D were referred to SP than to NDPP, which could be explained by the broad referral criteria for SP and highly supportive (proactive, welcoming) environments. Holistic and sustained SP allowed acknowledgement of patients' wider socio-economic constraints and provision of long-term personalised care. The fact that SP was embedded within the local community and primary care infrastructure facilitated the timely exchange of information and cross-referrals across providers, resulting in enhanced service responsiveness. CONCLUSIONS: Our study suggests that SP may offer an opportunity for individual-level T2D prevention to shift away from standardised, targeted and short-term strategies to approaches that are increasingly personalised, inclusive and long-term. Primary care-based SP seems most ideally placed to deliver such approaches where practitioners, providers and commissioners work collectively to achieve holistic, accessible, sustained and integrated services.

Fatores associados a não adesão medicamentosa entre idosos de um ambulatório filantrópico do Espírito Santo / Pharmacological non-adherence therapy and associated factors among elderly from a philanthropic outpatient unit of Espírito Santo state, Brazil

OBJETIVOS: Estimar a frequência da não adesão ao tratamento medicamentoso entre idosos acompanhados ambulatorialmente, bem como analisar seus fatores associados. METODOLOGIA: Foi conduzido estudo transversal com 263 idosos atendidos no ambulatório de especialidades médicas de um hospital filantrópico, localizado no município de Vitória-ES. Foi realizada entrevista utilizando roteiro estruturado em três blocos que contemplavam questões sociodemográficas, condições de saúde e estilo de vida e medicamentos em uso. Para verificar a não adesão ao tratamento medicamentoso, foi aplicado o instrumento de Medida de Adesão Terapêutica (MAT). Os dados foram analisados por meio do teste Qui-quadrado para variáveis categóricas. Foram consideradas significativas as variáveis com valor de p<0,05 no modelo final de regressão múltipla de Poisson. RESULTADOS: Os resultados mostraram uma frequência de não adesão ao tratamento medicamentoso de 26,7% da amostra. A não adesão ao tratamento medicamentoso nessa população se mostrou positivamente associada à ausência de vínculo empregatício anterior a aposentadoria (RP=1,12; p<0,010); presença de declínio cognitivo (RP=1,13; p<0,010) e hábitos alimentares inadequados (RP=1,12; p<0,005). CONCLUSÃO: Com o estudo, foi possível identificar os fatores associados à não adesão medicamentosa nos idosos investigados e assim contribuir para o conhecimento do perfil sociodemográfico, condições de saúde e estilo de vida e características relacionadas à utilização de medicamentos por parte dessa população.

OBJECTIVES: To estimate the non-adherence frequency of drug treatment among elderly outpatients and to analyze associated factors. METHODS: A cross-sectional study was conducted with 263 elderly patients from the medical specialties outpatient of a philanthropic hospital, located in the city of Vitoria, Espirito Santo state, Brazil. Interview was conducted using a structured script in three blocks that contemplated sociodemographic, health and lifestyle and medications used. To check the non-adherence to drug treatment, Measurement of Treatment Adherence (MTA) was applied. Data were analyzed using the chi-square test for categorical variables. The variables with p<0.05 in the final model of multiple Poisson regression were considered significant. RESULTS: The results showed a frequency of non-adherence to drug treatment in 26.7% of the sample. Non-adherence to drug treatment in this population was positively associated with lack of employment prior to retirement (PR=1.12; p<0.010); the presence of cognitive decline (PR=1.13; p<0.010) and poor eating habits (PR=1.12; p<0.005). CONCLUSION: With this study, it was possible to identify the factors associated with non-adherence to drug treatment in the investigated elderly and thus contribute to the knowledge of the socio-demographic profile, health and lifestyle and characteristics related to the use of drugs by this population.

Active and sedentary behaviours in children aged 7 to 10 years old: the urban and rural contexts, Brazil.

BACKGROUND: Although the effects of physical activity (PA) on health and wellness are well-established, incorporating sedentary behaviours in the daily lives of populations from high- and medium-income countries is becoming increasingly common. Regardless of other factors, the area of residence can influence the physical activity level and sedentary behaviours. The aim of this study was to identify and analyse active and sedentary behaviours and factors associated with physical activity in two different geographical areas in south-eastern Brazil. METHODS: 1.770 schoolchildren aged 7-10 years old were studied. Parents or caregivers completed a validated questionnaire on PA and sedentary behaviours. Screen time (ST) was calculated from the time spent watching television, playing video games and using the computer. The level of active PA (>300 minutes per week) was identified and compared between the areas of study. Parametric and non-parametric tests and Poisson regression model with robust variance were used for statistical analysis. RESULTS: Compared to schoolchildren from the urban area, those from the rural area showed a higher percentage of compliance with the PA recommendations (87 vs. 69.7%) and screen time <2 h (34.8 vs. 18.8%) and less participation in supervised PA. Active commuting to school was more common among schoolchildren from urban areas, although using a bicycle was more common in rural areas. The characteristics of children who do not meet the recommended weekly PA are as follows: being female, living in urban areas, being overweight, not using video games or performing supervised PA. Total ST as well as daily use of television and the computer was not associated with physical activity level in the present sample. Participation in supervised physical activities in both areas was found to increase the prevalence of being active in the areas studied. CONCLUSIONS: The results of the present study suggest that while schoolchildren from rural areas are more active and spend less time on sedentary activities than those from the urban area, the time spent in sedentary behaviors, such as watching television, playing video games and using the computer, is high in both contexts, and it is not associated with physical activity recommendation compliance.