Regular source of primary care and health services utilisation among Brazilian elderly with mental-physical multimorbidity.

BACKGROUND: In ageing populations, multimorbidity is a complex challenge to health systems, especially when the individuals have both mental and physical morbidities. Although a regular source of primary care (RSPC) is associated with better health outcomes, its relation with health service utilisation in elderly patients with mental-physical multimorbidity (MP-MM) is scarce. OBJECTIVE: This study explored the relations among health service utilisation, presence of RSPC and MP-MM among elderly Brazilians. METHODS: A national cross-sectional study performed with data from national representative samples from the Brazilian National Health Research (PNS, in Portuguese; Pesquisa Nacional de Saúde) carried out in 2013 with 11,177 elderly Brazilian people. MP-MM was defined as the presence of two or more morbidities, including at least one mental morbidity, and was evaluated using a list of 16 physical and mental morbidities. The RSPC was analysed by the presence of regular font of care in primary care and health service utilisation according to the demand for health services ≤ 15 days, medical consultation ≤ 12 months, and hospitalisation ≤ 1 year. Frequency description of variables and bivariate association were performed using Stata v.15.2 software. RESULTS: The majority of individuals was female (56.4%), and their mean age was 69.8 years. The observed prevalence of MP-MM was 12.2%. Individuals with MP-MM had higher utilisation of health services when compared to those without MP-MM. RSPC was present at 36.5% and was higher in women (37.8% vs. 34.9%). There was a lower occurrence of hospitalisation ≤ 1 year among MP-MM individuals with RSPC and without a private plan of health. CONCLUSION: Our findings demonstrate that RSPC can be an important component of care in elderly individuals with MP-MM because it was associated with lower occurrence of hospitalisation, mainly in those that have not a private plan of health. Longitudinal studies are necessary to confirm these findings.

What is the burden of multimorbidity and the factors associated with its occurrence in elderly Brazilians?

OBJECTIVE: To estimate the prevalence of multimorbidity in elderly people and its association with sociodemographic characteristics, lifestyle, and anthropometry. METHODS: This was a cross-sectional study using data from the National Health Survey, 2019. A total of 22,728 elderly individuals from all 27 Brazilian states were randomly selected. Poisson regression models with robust variance were employed, and a significance level of 5% was adopted. RESULTS: The prevalence of multimorbidity was 51.6% (95% CI: 50.4-52.7), with the highest estimates observed in the South and Southeast. Multimorbidity was associated with being female (aPR = 1.33; 95% CI: 1.27-1.39), being 80 years old or older (aPR = 1.12; 95% CI: 1.05-1.19), having low education (aPR = 1.16; 95% CI: 1.07-1.25), past cigarette use (aPR = 1.16; 95% CI: 1.11-1.21), insufficient physical activity (aPR = 1.13; 95% CI: 1.06-1.21), and screen use for 3 hours or more per day (aPR = 1.13; 95% CI: 1.08-1.18). CONCLUSION: Multimorbidity affects more than half of the elderly population in Brazil and is associated with social, demographic, and behavioral factors.

Assessing the relationship between multimorbidity, NCD configurations, frailty phenotypes, and mortality risk in older adults.

BACKGROUND: Older adults are increasingly susceptible to prolonged illness, multiple chronic diseases, and disabilities, which can lead to the coexistence of multimorbidity and frailty. Multimorbidity may result in various noncommunicable disease (NCD) patterns or configurations that could be associated with frailty and death. Mortality risk may vary depending on the presence of specific chronic diseases configurations or frailty. METHODS: The aim was to examine the impact of NCD configurations on mortality risk among older adults with distinct frailty phenotypes. The population was analyzed from the Costa Rican Longevity and Healthy Aging Study Cohort (CRELES). A total of 2,662 adults aged 60 or older were included and followed for 5 years. Exploratory factor analysis and various clustering techniques were utilized to identify NCD configurations. The frequency of NCD accumulation was also assessed for a multimorbidity definition. Frailty phenotypes were set according to Fried et al. criteria. Kaplan‒Meier survival analyses, mortality rates, and Cox proportional hazards models were estimated. RESULTS: Four different types of patterns were identified: 'Neuro-psychiatric', 'Metabolic', 'Cardiovascular', and 'Mixt' configurations. These configurations showed a higher mortality risk than the mere accumulation of NCDs [Cardiovascular HR:1.65 (1.07-2.57); 'Mixt' HR:1.49 (1.00-2.22); ≥3 NCDs HR:1.31 (1.09-1.58)]. Frailty exhibited a high and constant mortality risk, irrespective of the presence of any NCD configuration or multimorbidity definition. However, HRs decreased and lost statistical significance when phenotypes were considered in the Cox models [frailty + 'Cardiovascular' HR:1.56 (1.00-2.42); frailty + 'Mixt':1.42 (0.95-2.11); and frailty + ≥ 3 NCDs HR:1.23 (1.02-1.49)]. CONCLUSIONS: Frailty accompanying multimorbidity emerges as a more crucial indicator of mortality risk than multimorbidity alone. Therefore, studying NCD configurations is worthwhile as they may offer improved risk profiles for mortality as alternatives to straightforward counts.

Diet Quality and Multimorbidity in Older Adults: A Prospective Cohort Study.

BACKGROUND: The role of diet quality in the accumulation of multiple chronic conditions is mostly unknown. This study examined diet quality in association with the number of chronic conditions and the rate of multimorbidity development among community-dwelling older adults. METHODS: We used data from 2 784 adults aged ≥65 years from the Seniors-ENRICA 2 cohort. Diet quality was assessed at baseline (2015-17) with the Alternate Healthy Eating Index-2010 (AHEI-2010) and the Mediterranean Diet Adherence Screener (MEDAS). Information on medical diagnoses was obtained from electronic clinical records up to 2021. RESULTS: Higher adherence to the AHEI-2010 was associated with a lower number of total chronic conditions (ß [95% CI] quartile 4 vs 1: -0.57 [-0.86 to 0.27], p trend < .001] and cardiometabolic conditions (-0.30 [-0.44 to -0.17], p trend < .001) at baseline, while higher adherence to the MEDAS was associated with a lower number of total chronic conditions (-0.30 [-0.58 to -0.02], p trend = .01) and neuropsychiatric and neurodegenerative conditions (-0.09 [-0.17 to -0.01], p trend = .01). After a median follow-up of 5.2 years (range: 0.1-6.1 years) higher adherence to the AHEI-2010 was associated with a lower increase in chronic conditions (ß [95% confidence interval] quartile 4 vs 1: -0.16 [-0.30 to -0.01], p trend = .04) and with lower rate of chronic disease accumulation. CONCLUSIONS: Higher diet quality, as measured by the AHEI-2010, was associated with a lower number of chronic health conditions and a lower rate of multimorbidity development over time.

20-year trends in multimorbidity by race/ethnicity among hospitalized patient populations in the United States.

BACKGROUND: The challenges presented by multimorbidity continue to rise in the United States. Little is known about how the relative contribution of individual chronic conditions to multimorbidity has changed over time, and how this varies by race/ethnicity. The objective of this study was to describe trends in multimorbidity by race/ethnicity, as well as to determine the differential contribution of individual chronic conditions to multimorbidity in hospitalized populations over a 20-year period within the United States. METHODS: This is a serial cross-sectional study using the Nationwide Inpatient Sample (NIS) from 1993 to 2012. We identified all hospitalized patients aged ≥ 18 years old with available data on race/ethnicity. Multimorbidity was defined as the presence of 3 or more conditions based on the Elixhauser comorbidity index. The relative change in the proportion of hospitalized patients with multimorbidity, overall and by race/ethnicity (Black, White, Hispanic, Asian/Pacific Islander, Native American) were tabulated and presented graphically. Population attributable fractions were estimated from modified Poisson regression models adjusted for sex, age, and insurance type. These fractions were used to describe the relative contribution of individual chronic conditions to multimorbidity over time and across racial/ethnic groups. RESULTS: There were 123,613,970 hospitalizations captured within the NIS between 1993 and 2012. The prevalence of multimorbidity increased in all race/ethnic groups over the 20-year period, most notably among White, Black, and Native American populations (+ 29.4%, + 29.7%, and + 32.0%, respectively). In both 1993 and 2012, Black hospitalized patients had a higher prevalence of multimorbidity (25.1% and 54.8%, respectively) compared to all other race/ethnic groups. Native American populations exhibited the largest overall increase in multimorbidity (+ 32.0%). Furthermore, the contribution of metabolic diseases to multimorbidity increased, particularly among Hispanic patients who had the highest population attributable fraction values for diabetes without complications (15.0%), diabetes with complications (5.1%), and obesity (5.8%). CONCLUSIONS: From 1993 to 2012, the secular increases in the prevalence of multimorbidity as well as changes in the differential contribution of individual chronic conditions has varied substantially by race/ethnicity. These findings further elucidate the racial/ethnic gaps prevalent in multimorbidity within the United States. PRIOR PRESENTATIONS: Preliminary finding of this study were presented at the Society of General Internal Medicine (SGIM) Annual Conference, Washington, DC, April 21, 2017.

Redefining Multimorbidity in Older Surgical Patients.

BACKGROUND: Multimorbidity in surgery is common and associated with worse postoperative outcomes. However, conventional multimorbidity definitions (≥2 comorbidities) label the vast majority of older patients as multimorbid, limiting clinical usefulness. We sought to develop and validate better surgical specialty-specific multimorbidity definitions based on distinct comorbidity combinations. STUDY DESIGN: We used Medicare claims for patients aged 66 to 90 years undergoing inpatient general, orthopaedic, or vascular surgery. Using 2016 to 2017 data, we identified all comorbidity combinations associated with at least 2-fold (general/orthopaedic) or 1.5-fold (vascular) greater risk of 30-day mortality compared with the overall population undergoing the same procedure; we called these combinations qualifying comorbidity sets. We applied them to 2018 to 2019 data (general = 230,410 patients, orthopaedic = 778,131 patients, vascular = 146,570 patients) to obtain 30-day mortality estimates. For further validation, we tested whether multimorbidity status was associated with differential outcomes for patients at better-resourced (based on nursing skill-mix, surgical volume, teaching status) hospitals vs all other hospitals using multivariate matching. RESULTS: Compared with conventional multimorbidity definitions, the new definitions labeled far fewer patients as multimorbid: general = 85.0% (conventional) vs 55.9% (new) (p < 0.0001); orthopaedic = 66.6% vs 40.2% (p < 0.0001); and vascular = 96.2% vs 52.7% (p < 0.0001). Thirty-day mortality was higher by the new definitions: general = 3.96% (conventional) vs 5.64% (new) (p < 0.0001); orthopaedic = 0.13% vs 1.68% (p < 0.0001); and vascular = 4.43% vs 7.00% (p < 0.0001). Better-resourced hospitals offered significantly larger mortality benefits than all other hospitals for multimorbid vs nonmultimorbid general and orthopaedic, but not vascular, patients (general surgery difference-in-difference = -0.94% [-1.36%, -0.52%], p < 0.0001; orthopaedic = -0.20% [-0.34%, -0.05%], p = 0.0087; and vascular = -0.12% [-0.69%, 0.45%], p = 0.6795). CONCLUSIONS: Our new multimorbidity definitions identified far more specific, higher-risk pools of patients than conventional definitions, potentially aiding clinical decision-making.

Multimorbidity is associated with the income, education, employment and health domains of area-level deprivation in adult residents in the UK.

Evidence suggests that there are social inequalities in multimorbidity, with a recent review indicating that area levels of deprivation are consistently associated with greater levels of multimorbidity. Definitions of multimorbidity, the most common of which is the co-occurrence of more than one long term condition, can include long term physical conditions, mental health conditions or both. The most commonly used measure of deprivation in England and Wales is the Index of Multiple Deprivation (IMD), an index of seven different deprivation domains. It is unclear which features of IMD may be mediating associations with multimorbidity. Thus, there may be associations because of the individual characteristics of those living in deprived areas, characteristics of the areas themselves or overlap in definitions. Data from over 25,000 participants (aged 16+) of Understanding Society (Wave 10, 1/2018-3/2020) were used to understand the most salient features of multimorbidity associated with IMD and whether physical or mental conditions are differentially associated with the seven domains of IMD. 24% of participants report multimorbidity. There is an increased prevalence of multimorbidity composed of only long-term physical conditions in the most deprived decile of deprivation (22%, 95% CI[19,25]) compared to the least deprived decile (16%, 95% CI[14,18]). Mental health symptoms but not reporting of conditions vary by decile of IMD. Associations with multimorbidity are limited to the health, income, education and employment domains of IMD. We conclude that multimorbidity represents a substantial population burden, particularly in the most deprived areas in England and Wales.

Improving Stroke Risk Prediction in the General Population: A Comparative Assessment of Common Clinical Rules, a New Multimorbid Index, and Machine-Learning-Based Algorithms.

BACKGROUND: There are few large studies examining and predicting the diversified cardiovascular/noncardiovascular comorbidity relationships with stroke. We investigated stroke risks in a very large prospective cohort of patients with multimorbidity, using two common clinical rules, a clinical multimorbid index and a machine-learning (ML) approach, accounting for the complex relationships among variables, including the dynamic nature of changing risk factors. METHODS: We studied a prospective U.S. cohort of 3,435,224 patients from medical databases in a 2-year investigation. Stroke outcomes were examined in relationship to diverse multimorbid conditions, demographic variables, and other inputs, with ML accounting for the dynamic nature of changing multimorbidity risk factors, two clinical risk scores, and a clinical multimorbid index. RESULTS: Common clinical risk scores had moderate and comparable c indices with stroke outcomes in the training and external validation samples (validation-CHADS2: c index 0.812, 95% confidence interval [CI] 0.808-0.815; CHA2DS2-VASc: c index 0.809, 95% CI 0.805-0.812). A clinical multimorbid index had higher discriminant validity values for both the training/external validation samples (validation: c index 0.850, 95% CI 0.847-0.853). The ML-based algorithms yielded the highest discriminant validity values for the gradient boosting/neural network logistic regression formulations with no significant differences among the ML approaches (validation for logistic regression: c index 0.866, 95% CI 0.856-0.876). Calibration of the ML-based formulation was satisfactory across a wide range of predicted probabilities. Decision curve analysis demonstrated that clinical utility for the ML-based formulation was better than that for the two current clinical rules and the newly developed multimorbid tool. Also, ML models and clinical stroke risk scores were more clinically useful than the "treat all" strategy. CONCLUSION: Complex relationships of various comorbidities uncovered using a ML approach for diverse (and dynamic) multimorbidity changes have major consequences for stroke risk prediction. This approach may facilitate automated approaches for dynamic risk stratification in the significant presence of multimorbidity, helping in the decision-making process for risk assessment and integrated/holistic management.

Chronic-Care-Management Programs for Multimorbid Patients with Diabetes in Europe: A Scoping Review with the Aim to Identify the Best Practice.

AIM: This scoping review is aimed at providing a current descriptive overview of care programs based on the chronic care model (CCM) according to E. H. Wagner. The evaluation is carried out within Europe and assesses the methodology and comparability of the studies. METHODS: A systematic search in the databases PubMed, Embase, and MEDLINE via OVID was conducted. In the beginning, 2309 articles were found and 48 full texts were examined, 19 of which were incorporated. Included were CCM-based programs from Belgium, Cyprus, Germany, Italy, Switzerland, and the Netherlands. All 19 articles were presented descriptively whereof 11 articles were finally evaluated in a checklist by Rothe et al. (2020). In this paper, the studies were tabulated and evaluated conforming to the same criteria. RESULTS: Due to the complexity of the CCM and the heterogeneity of the studies in terms of setting and implementation, a direct comparison proved difficult. Nevertheless, the review shows that CCM was successfully implemented in various care situations and also can be useful in single practices, which often dominate the primary care sector in many European health systems. The present review was able to provide a comprehensive overview of the current care situation of chronically ill patients with multimorbidities. CONCLUSIONS: A unified nomenclature concerning the distinction between disease management programs and CCM-based programs should be aimed for. Similarly, homogeneous quality standards and a Europe-wide evaluation strategy would be necessary to identify best practice models and to provide better care for the steadily growing number of chronically multimorbid patients.

Socioeconomic variation of multimorbidity in Colombian older adults.

Multimorbidity (MM) prevalence among older adults is increasing worldwide. Variations regarding the socioeconomic characteristics of the individuals and their context have been described, mostly in high-income settings. However, further research is needed to understand the effect of the coexistence of infectious diseases along with socioeconomic factors regarding MM. This study aims to examine the variation of MM regarding infectious diseases mortality after adjusting for socioeconomic factors. A cross-sectional multilevel study with a nationally representative sample of 17,571 Colombian adults of 60 years of age or older was conducted. Individual socioeconomic, demographic, childhood and health related characteristics, as well as group level variables (multidimensional poverty index and infectious diseases mortality rate) were analyzed. A two-level stepwise structural equation model was used to simultaneously adjust for the individual and contextual effects. Multimorbidity prevalence was 62.3% (95% CI 61.7-62.9). In the multilevel adjusted models, age, female sex, having functional limitations, non-white ethnicity, high body mass index, higher income, physical inactivity and living in urban areas were associated with multimorbidity among the sample for this study. The median odds ratio for multidimensional poverty was 1.18 (1.16-1.19; p = 0.008) and for infectious diseases was 1.25 (1.22-1.28; p = 0.014). This paper demonstrates that MM varies regarding the mortality of infectious diseases and shows a strong association between MM and poverty in a low-middle income country. Differences in the factors involved in the etiology of multimorbidity are expected among wealthy and poor countries regarding availability and prioritization of health services.

National Trends and Outcomes Associated With Presence and Type of Usual Clinician Among Older Adults With Multimorbidity.

Importance: Declining primary care visit rates and increasing specialist visit rates among older adults with multimorbidity raise questions about the presence, specialty, and outcomes associated with usual clinicians of care for these adults. Objective: To examine trends in the presence and specialty of usual clinicians and the association with preventive care receipt and spending. Design, Setting, and Participants: This survey study used repeated cross-sectional analyses of Medicare Current Beneficiary Survey data from 2010, 2013, and 2016. Participants were community-dwelling Medicare Advantage and traditional Medicare members with at least 2 chronic conditions. Data were analyzed from March 1, 2020, to February 5, 2021. Main Outcomes and Measures: Trends and factors associated with self-reported usual clinician presence and specialty. Multivariable regression was used to examine associations between usual clinician presence and specialty with preventive care receipt and spending, controlling for respondent sociodemographic and clinical characteristics. Results: A total of 25 490 unweighted respondent-years were examined, representing 90 324 639 respondent-years across the United States. Overall, 58.4% of respondent-years belonged to women, and the mean (SD) age of respondents was 77.5 (7.5) years. From 2010 to 2016, those reporting usual clinicians dropped from 94.2% to 91.0% (P < .001). Across study years, respondents were more likely to report a usual clinician if they were women (adjusted marginal difference [AMD], 2.5 percentage points; 95% CI, 1.5-3.5 percentage points) or had higher income (≥$50 000 vs <$15 000: AMD, 2.2 percentage points; 95% CI, 1.1-3.4 percentage points) and less likely if they were Black beneficiaries (vs White: AMD, -2.8 percentage points; 95% CI, -4.3 to -1.3 percentage points) or had traditional Medicare (vs Medicare Advantage: AMD, -3.2 percentage points; 95% CI. -4.1 to -2.3 percentage points). Among 23 279 respondents with usual clinicians, those reporting specialists as their usual clinicians decreased from 5.3% to 4.1% (P < .001). Across the study period, respondents were more likely to report specialists as their usual clinicians if they had traditional Medicare (vs Medicare Advantage: AMD, 2.3 percentage points; 95% CI, 1.6 to 2.9 percentage points), were Black or non-White Hispanic (Black vs White: AMD, 1.5 percentage points; 95% CI, 0.2 to 2.8 percentage points; non-White Hispanic vs White: AMD, 3.8 percentage points; 95% CI, 1.9 to 5.7 percentage points), or lived in the Northeast (vs Midwest: AMD, 3.6 percentage points; 95% CI, 2.1 to 5.2 percentage points). Compared with those without usual clinicians, respondents with usual clinicians were more likely to receive all examined preventive services, such as cholesterol screening (AMD, 6.7 percentage points; 95% CI, 5.4 to 8.1 percentage points) and influenza vaccines (AMD, 11.6 percentage points; 95% CI, 9.2 to 14.0 percentage points). Among respondents with usual clinicians, those reporting specialist usual clinicians (vs primary care) were less likely to receive influenza vaccines (AMD, -5.6 percentage points; 95% CI, -9.2 to -2.1). Conclusions and Relevance: In this study, older adults with multimorbidity were less likely to have a usual clinician over the study period, with potential implications for preventive care receipt. Our results suggest a key role for usual clinicians, especially primary care clinicians, in vaccination uptake for this population.

The management of multi-morbidity in elderly patients: Ready yet for precision medicine in intensive care?

There is ongoing demographic ageing and increasing longevity of the population, with previously devastating and often-fatal diseases now transformed into chronic conditions. This is turning multi-morbidity into a major challenge in the world of critical care. After many years of research and innovation, mainly in geriatric care, the concept of multi-morbidity now requires fine-tuning to support decision-making for patients along their whole trajectory in healthcare, including in the intensive care unit (ICU). This article will discuss current challenges and present approaches to adapt critical care services to the needs of these patients.

International comparison of health spending and utilization among people with complex multimorbidity.

OBJECTIVE: The objective of this study was to explore cross-country differences in spending and utilization across different domains of care for a multimorbid persona with heart failure and diabetes. DATA SOURCES: We used individual-level administrative claims or registry data from inpatient and outpatient health care sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States (US). DATA COLLECTION/EXTRACTION METHODS: Data collected by ICCONIC partners. STUDY DESIGN: We retrospectively analyzed age-sex standardized utilization and spending of an older person (65-90 years) hospitalized with a heart failure exacerbation and a secondary diagnosis of diabetes across five domains of care: hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, and outpatient drugs. PRINCIPAL FINDINGS: Sample sizes ranged from n = 1270 in Spain to n = 21,803 in the United States. Mean age (standard deviation [SD]) ranged from 76.2 (5.6) in the Netherlands to 80.3 (6.8) in Sweden. We observed substantial variation in spending and utilization across care settings. On average, England spent $10,956 per person in hospital care while the United States spent $30,877. The United States had a shorter length of stay over the year (18.9 days) compared to France (32.9) and Germany (33.4). The United States spent more days in facility-based rehabilitative care than other countries. Australia spent $421 per person in primary care, while Spain (Aragon) spent $1557. The United States and Canada had proportionately more visits to specialist providers than primary care providers. Across almost all sectors, the United States spent more than other countries, suggesting higher prices per unit. CONCLUSION: Across 11 countries, there is substantial variation in health care spending and utilization for a complex multimorbid persona with heart failure and diabetes. Drivers of spending vary across countries, with the United States being the most expensive country due to high prices and higher use of facility-based rehabilitative care.

Multimorbidity prediction using link prediction.

Multimorbidity, frequently associated with aging, can be operationally defined as the presence of two or more chronic conditions. Predicting the likelihood of a patient with multimorbidity to develop a further particular disease in the future is one of the key challenges in multimorbidity research. In this paper we are using a network-based approach to analyze multimorbidity data and develop methods for predicting diseases that a patient is likely to develop. The multimorbidity data is represented using a temporal bipartite network whose nodes represent patients and diseases and a link between these nodes indicates that the patient has been diagnosed with the disease. Disease prediction then is reduced to a problem of predicting those missing links in the network that are likely to appear in the future. We develop a novel link prediction method for static bipartite network and validate the performance of the method on benchmark datasets. By using a probabilistic framework, we then report on the development of a method for predicting future links in the network, where links are labelled with a time-stamp. We apply the proposed method to three different multimorbidity datasets and report its performance measured by different performance metrics including AUC, Precision, Recall, and F-Score.

Increased chronic disease prevalence among the younger generation: Findings from a population-based data linkage study to inform chronic disease ascertainment among reproductive-aged Australian women.

BACKGROUND: Chronic disease represents an ongoing public health challenge in Australia with women disproportionately affected and at younger ages compared to men. Accurate prevalence and ascertainment of chronic disease among women of reproductive age at the population level is essential for meeting the family planning and reproductive health challenges that chronic diseases pose. This study estimated the prevalence of chronic disease among younger Australian women of reproductive age, in order to ascertain key conditions that would benefit from targeted family planning support strategies. METHODS AND FINDINGS: Population-level survey data from the 1973-78 and 1989-95 cohorts of the Australian Longitudinal Study on Women's Health were linked to health service use, pharmaceutical, cancer and cause of death data to ascertain the prevalence and chronic disease trends for ten chronic health conditions associated with poor maternal and foetal outcomes. Individual chronic disease algorithms were developed for each chronic disease of interest using the available linked datasets. Lifetime prevalence of chronic disease varied substantially based on each individual data source for each of the conditions of interest. When all data sources were considered, all conditions with the exception of mental health conditions were higher among women in the 1973-78 cohort. However, when focused on point prevalence at similar ages (approximately 25-30 years), the chronic disease trend for women in the 1989-95 cohort was substantially higher, particularly for mental health conditions (70.4% vs 23.6%), diabetes (4.5% vs 1.3%) and multimorbidity (17.9% vs 9.1%). CONCLUSIONS: Given the low concordance between individual data sources, the use of multiple data sources are recommended for chronic disease research focused on women of reproductive age. In order to reduce the increasing chronic disease and multimorbidity trend among women, strategic chronic disease interventions are required to be implemented in childhood and adolescence to ensure the long-term health of not only current but also future generations.

Trends of complications in patients with Parkinson's disease in seven major cities of China from 2016 to 2019.

Parkinson's disease (PD) is a neurological disorder involving both motor and nonmotor symptoms. Multimorbidity acts synergistically to heighten the risk of adverse outcomes for patients with PD. Its complications have a major impact on the clinical management of PD. The present retrospective and multicenter study was first performed to describe the epidemiological characteristics of PD patients and assess the incidence of complications. The outpatient prescriptions for PD therapy were collected from hospitals in Beijing, Chengdu, Guangzhou, Hangzhou, Shanghai, Tianjin and Zhengzhou of China over a 40-day period per year, from the first half of 2016 to that of 2019. The survey covered the characteristics and representative complications of the study population. A total of 103 674 outpatient prescriptions for PD treatment from different graded hospitals of China were collected for final data analysis. It showed that 78.15% of PD patients were prescribed in the neurology department. 95.05% of the outpatient prescriptions were from general hospitals. We found that the overall PD prevalence was 0.47%, among which 52.96% of them were men. In addition, 82.10% of PD suffers were older than 60 years and 83.70% of them had complications. The top five highest frequencies of nonmotor complications in PD patients were sleep disorders, Alzheimer's disease, depression, lower urinary tract symptoms and constipation, with the proportions of 6.79, 3.87, 3.72, 3.32 and 2.40%, respectively. Meanwhile, the proportions of sleep disorders, Alzheimer's disease, and constipation were gradually increasing from 2016 to 2019. The characteristics of PD patients and the incidence of its complications were evaluated in the present prescription survey. These updated data provide evidence for further implementation of PD management.

The changing health needs of the UK population.

The demographics of the UK population are changing and so is the need for health care. In this Health Policy, we explore the current health of the population, the changing health needs, and future threats to health. Relative to other high-income countries, the UK is lagging on many health outcomes, such as life expectancy and infant mortality, and there is a growing burden of mental illness. Successes exist, such as the striking improvements in oral health, but inequalities in health persist as well. The growth of the ageing population relative to the working-age population, the rise of multimorbidity, and persistent health inequalities, particularly for preventable illness, are all issues that the National Health Service (NHS) will face in the years to come. Meeting the challenges of the future will require an increased focus on health promotion and disease prevention, involving a more concerted effort to understand and tackle the multiple social, environmental, and economic factors that lie at the heart of health inequalities. The immediate priority of the NHS will be to mitigate the wider and long-term health consequences of the COVID-19 pandemic, but it must also strengthen its resilience to reduce the impact of other threats to health, such as the UK leaving the EU, climate change, and antimicrobial resistance.