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Background: Chronic physical conditions (e.g., heart diseases, diabetes) increase with population ageing, contributing to psychological and cognitive multimorbidities. Yet, little is known about socioeconomic inequalities in this process. We examined the associations between socioeconomic status (SES) and progression to psychological and cognitive multimorbidities after onset of a physical condition. Methods: We used harmonized individual-level data from five prospective cohort studies across 24 countries in the US, Europe and Asia, with repeated morbidity measurements between 2002 and 2021. Participants with at least one new-onset physical conditions (hypertension, diabetes, heart diseases, stroke, chronic lung diseases, cancer, or arthritis) were followed up for progression to physical-psychological multimorbidity, physical-cognitive multimorbidity, and physical-psychological-cognitive multimorbidity. SES was determined based on educational level and total household wealth at the onset of a physical condition. Time to and incidence rates of progressing psychological and cognitive multimorbidities were estimated in analyses stratified by SES. Fine-Gray subdistribution hazard models and multi-state models were used to estimate the associations between SES and progression to psychological and cognitive multimorbidities. Findings: Among 20,250 participants aged ≥45 years (mean age at a physical condition onset 65.38 years, standard deviation 8.37) with at least one new-onset physical conditions in the analysis, 7928 (39.2%) progressed to psychological and cognitive multimorbidities during a median follow-up of 8.0 years (168,575 person-years). The mean survival time free from physical-psychological-cognitive multimorbidity was 11.96 years (95% confidence interval 11.57-12.34) in low SES individuals, compared to 15.52 years (15.40-15.63) in high SES individuals, with the corresponding incidence rate of 18.44 (16.32-20.82) and 3.15 (2.48-4.01) per 1000 person-years, respectively. The associations of education, household wealth and SES with multimorbidities followed a dose-dependent relation, with subdistribution hazard ratios per decreasing SES category being 1.24 (1.19-1.29) for physical-psychological multimorbidity, 1.47 (1.40-1.54) for physical-cognitive multimorbidity, and 1.84 (1.72-1.97) for physical-psychological-cognitive multimorbidity. The strongest SES-multimorbidities associations were observed in participants with arthritis, hypertension or diabetes. In multi-state models SES was linked to all five transitions from physical condition to physical-psychological multimorbidity, physical-cognitive multimorbidity and physical-psychological-cognitive multimorbidity. Interpretation: Socioeconomic inequalities are associated with the progression of a chronic physical condition, with the lower SES groups had both an earlier time to and a higher incidence of psychological and cognitive multimorbidities. These findings underscore the need for more effective equity-oriented policies and healthcare practices to address reduced psychological wellness and cognitive maintenance among individuals with low SES and physical conditions. Funding: Zhejiang University Hundred Talents Program Research Initiation Fund, Fundamental Research Funds for the Central Universities in China, Wellcome Trust, Medical Research Council, National Institute on Aging, Academy of Finland.
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BACKGROUND: While the new cardiovascular risk score (PREVENT) has improvements, its implementation may lead to significant changes in the distribution of atherosclerotic cardiovascular diseases (ASCVD) in the United States. We aimed to quantify and characterize the distribution of the 10-year predicted absolute ASCVD risk using the Pooled Cohorts Equation (PCE) and PREVENT. METHODS: We utilized the latest (2017-March 2020) round of the National Health and Nutrition Examination Survey (NHANES). Accounting for the complex survey design of the NHANES, we computed the mean predicted ASCVD risk overall and by sex, race, and education; similarly, we computed the prevalence of cardiovascular risk groups (<5%, 5%-7.4%, 7.5%-19.9%, and ≥ 20%). RESULTS: The study included 3845 observations, representing 109,692,509 people. Using the PREVENT calculator resulted in a reduction of the mean 10-year ASCVD absolute risk by half compared to the PCE: 9.1% vs 4.7%. Under the PCE, the high-risk category accounted for 12.5% of the population, whereas under PREVENT it fell to 0.4%. Among those previously classified as high-risk under the PCE, 3.5% would remain in this category with PREVENT, while 93% would be reclassified as intermediate risk. CONCLUSIONS: The adoption of the novel cardiovascular risk score, PREVENT, could lower the average predicted ASCVD risk and reduce the prevalence of high-risk individuals. While this shift might suggest improved cardiovascular health, it could also lead to complacency, potentially undermining ongoing public health efforts aimed at preventing cardiovascular disease.
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In Latin America and the Caribbean (LAC), sociodemographic context, socioeconomic disparities and the high level of urbanization provide a unique entry point to reflect on the burden of cardiometabolic disease in the region. Cardiovascular diseases are the main cause of death in LAC, precipitated by population growth and ageing together with a rapid increase in the prevalence of cardiometabolic risk factors, predominantly obesity and diabetes mellitus, over the past four decades. Strategies to address this growing cardiometabolic burden include both population-wide and individual-based initiatives tailored to the specific challenges faced by different LAC countries, which are heterogeneous. The implementation of public policies to reduce smoking and health system approaches to control hypertension are examples of scalable strategies. The challenges faced by LAC are also opportunities to foster innovative approaches to combat the high burden of cardiometabolic diseases such as implementing digital health interventions and team-based initiatives. This Review provides a summary of trends in the epidemiology of cardiometabolic diseases and their risk factors in LAC as well as context-specific disease determinants and potential solutions to improve cardiometabolic health in the region.
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Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for physiological sounds to classify sociodemographic traits has not been investigated. Exploring this gap is crucial for understanding the implications and ensuring fairness in the field of medical sound analysis. We aimed to develop classifiers to determine gender (men/women) based on heart sound recordings and using machine learning (ML). Data-driven ML analysis. We utilized the open-access CirCor DigiScope Phonocardiogram Dataset obtained from cardiac screening programs in Brazil. Volunteers < 21 years of age. Each participant completed a questionnaire and underwent a clinical examination, including electronic auscultation at four cardiac points: aortic (AV), mitral (MV), pulmonary (PV), and tricuspid (TV). We used Mel-frequency cepstral coefficients (MFCCs) to develop the ML classifiers. From each patient and from each auscultation sound recording, we extracted 10 MFCCs. In sensitivity analysis, we additionally extracted 20, 30, 40, and 50 MFCCs. The most effective gender classifier was developed using PV recordings (AUC ROC = 70.3%). The second best came from MV recordings (AUC ROC = 58.8%). AV and TV recordings produced classifiers with an AUC ROC of 56.4% and 56.1%, respectively. Using more MFCCs did not substantially improve the classifiers. It is possible to classify between males and females using phonocardiogram data. As health-related audio recordings become more prominent in ML applications, research is required to explore if these recordings contain signals that could distinguish sociodemographic features.
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Background: The co-occurrence of chronic diseases and acute infectious events exacerbates disability and diminishes quality of life, yet research in Low- and Middle-Income countries is scarce. We aimed to investigate the relationship between infectious events and multimorbidity in resource-constrained settings. Methods: We conducted a sequential mixed-method study in Lima and Tumbes, Peru, with participants having multimorbidity from the CRONICAS Cohort Study. They completed a questionnaire on the occurrence, treatment, and health-seeking behaviour related to acute infectious events. Qualitative interviews explored the perceptions and links between multimorbidity and acute infectious events for a subgroup of participants. Findings: Among individuals with multimorbidity, low awareness of chronic conditions and poor medication adherence. The cumulative incidence for respiratory and gastrointestinal infections, the most reported acute conditions, was 2.0 [95%CI: 1.8-2.2] and 1.6 [1.2-1.9] events per person per year, respectively. Individuals with cancer (6.4 [1.6-11.2] events per person per year) or gastrointestinal reflux (7.2 [4.4-10.1] events per person per year) reported higher cumulative incidence of infectious events than others, such as those with cardiovascular and metabolic conditions (5.2 [4.6-5.8] events per person per year). Those with three or more chronic conditions had a slightly higher cumulative incidence compared with individuals with two conditions (5.7 [4.4-7.0] vs 5.0 [4.4-5.6] events per person per year). Around 40% of individuals with multimorbidity sought healthcare assistance, while others chose drugstores or didn't seek help. Our qualitative analysis showed diverse perceptions among participants regarding the connections between chronic and acute conditions. Those who recognized a connection emphasized the challenges in managing these interactions. Interpretation: Our study advances understanding of multimorbidity challenges in resource-limited settings, highlighting the impact of acute infections on patients' existing multimorbidity burden.
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AIMS: Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new patients to predict, approximately, how long the new patient may have lived with diabetes unknowingly. We aimed to develop a model to predict self-reported diabetes duration. METHODS: We used the Brazilian Multilabel Ophthalmological Dataset. Unit of analysis was the fundus image and its meta-data, regardless of the patient. We included people 40â¯+ years and fundus images without diabetic retinopathy. Fundus images and meta-data (sex, age, comorbidities and taking insulin) were passed to the MedCLIP model to extract the embedding representation. The embedding representation was passed to an Extra Tree Classifier to predict: 0-4, 5-9, 10-14 and 15â¯+ years with self-reported diabetes. RESULTS: There were 988 images from 563 people (mean ageâ¯=â¯67 years; 64â¯% were women). Overall, the F1 score was 57â¯%. The group 15â¯+ years of self-reported diabetes had the highest precision (64â¯%) and F1 score (63â¯%), while the highest recall (69â¯%) was observed in the group 0-4 years. The proportion of correctly classified observations was 55â¯% for the group 0-4 years, 51â¯% for 5-9 years, 58â¯% for 10-14 years, and 64â¯% for 15â¯+ years with self-reported diabetes. CONCLUSIONS: The machine learning model had acceptable accuracy and F1 score, and correctly classified more than half of the patients according to diabetes duration. Using large foundational models to extract image and text embeddings seems a feasible and efficient approach to predict years living with self-reported diabetes.
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Diabetes Mellitus , Fundus Oculi , Machine Learning , Predictive Value of Tests , Self Report , Humans , Female , Male , Aged , Middle Aged , Time Factors , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Brazil/epidemiology , Adult , Databases, Factual , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/epidemiology , Data Mining/methods , Reproducibility of Results , Image Interpretation, Computer-AssistedABSTRACT
Background: We aimed to examine the national and subnational prevalence of vulnerable newborn phenotypes in Peru, 2012-2021. Methods: Newborn phenotypes were defined using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight [LBW], non-LBW) using the Peruvian National Birth Registry as six (by excluding birthweight) and ten newborn phenotypes (using all three outcomes). Small phenotypes (with at least one classification of PT, SGA, or LBW) were further considered. Using individual-level data, we stratified the phenotypes by maternal educational level, maternal age, healthcare insurance, altitude of residence, and geographic region (Coast, Andes, and Amazon). Findings: The prevalence of the five vulnerable newborn phenotypes for the study period was LGA+T (15.2%), AGA+PT (5.2%), SGA+T (4.6%), LGA+PT (0.8%), and SGA+PT (0.7%). The Coast had a higher prevalence of newborns with large phenotypes (19.4%) and the Highlands a higher prevalence of newborns with small phenotypes (12.5%). Mothers with poor socioeconomic status, extreme ages and living at high altitude had a higher prevalence of newborns with small phenotypes, and mothers who were wealthier, more educated, and older had a higher prevalence of infants with large phenotypes. Interpretation: Our findings cautiously suggest that socioeconomic and geographic disparities may play a crucial role in shaping vulnerable newborn phenotypes at national and subnational level in Peru. Further studies using longitudinal data are needed to corroborate our findings and to identify individual-level risk factors. Funding: Ter Meulen Grant from the KNAW Medical Sciences Fund of the Royal Netherlands Academy of Arts and Sciences (KNAWWF/1085/TMB406, KNAWWF/1327/TMB202116), Fogarty Program (D43TW011502).
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AIMS: To estimate the proportion of people with self-reported diabetes receiving eye and foot examinations in Latin America and the Caribbean (LAC). METHODS: Cross-sectional analysis of national health surveys in nine countries. Adults aged 25-64 years with self-reported diabetes. We quantified the proportion who reported having an eye examination in the last two years or a foot examination in the last year. We fitted multilevel Poisson regressions to assess socio-demographic (age and sex) and clinical (oral hypoglycemic medication and insulin treatment) variables associated with having had examinations. RESULTS: There were 7435 people with self-reported diabetes included in the analysis. In three countries (Chile [64%; 95% CI: 56%-71%], British Virgin Islands [58%; 95% CI: 51%-65%], and Brazil [54%; 95% CI: 50%-58%]), >50% of people with diabetes reported having had an eye examination in the last two years. Fewer participants (<50% across all countries) reported having had a foot examination in the last year, with Ecuador having the lowest proportion (12%; 95% CI: 8%-17%). Older people, and those taking oral medication or insulin, were more likely to have eye/foot examinations. CONCLUSIONS: The proportion of eye and foot examinations in people with self-reported diabetes across nine countries in LAC is low.
Subject(s)
Diabetic Foot , Health Care Surveys , Self Report , Humans , Cross-Sectional Studies , Middle Aged , Adult , Male , Female , Caribbean Region/epidemiology , Latin America/epidemiology , Diabetic Foot/epidemiology , Diabetic Foot/diagnosis , Diabetic Foot/prevention & control , Patient Compliance , Diabetes Mellitus/epidemiology , Diabetes Mellitus/diagnosis , Hypoglycemic Agents/therapeutic use , Diabetic Retinopathy/epidemiology , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/prevention & control , Preventive Health Services , Health Knowledge, Attitudes, PracticeABSTRACT
BACKGROUND: Future demographic changes will increase the number of people living with non-communicable diseases. We projected the number of people with type 2 diabetes mellitus (T2DM) in 2035 and 2050 at the global and country levels. METHODS: We pooled T2DM prevalence estimates from the Global Burden of Disease Study and population estimates from the United Nations for 188 countries. We computed the absolute number of people with T2DM in 2020 and predicted the future number in 2035 and 2050 under four scenarios for the T2DM prevalence: 1) It held constant, 2) It increased by 50%, 3) It decreased by 10%, and 4) It followed 1990-2019 country-specific past trends. RESULTS: The global number of people with T2DM was 445 million in 2020, and it is projected to increase in 2050 to 730 million if prevalence remains unchanged, 1,095 million if prevalence increases by 50%, 657 million if prevalence decreases by 10%, and 1,153 million if prevalence follows country-specific 1990-2019 past trends. Under all scenarios, Sub-Saharan Africa and lowincome countries had the highest relative increase in the number of people with T2DM. The share of people with T2DM aged <60 years is expected to drop from 5 out of 10 in 2020 to 4 out of 10 people in 2050 under all scenarios. CONCLUSIONS: There will be a massive growth in the number of people living with T2DM, and low-income countries and countries in Sub-Saharan Africa will be the most affected. Health systems must be strengthened to ensure optimal care for the future population with T2DM.
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BACKGROUND: Screening for type 2 diabetes mellitus (T2DM) targets people aged 35+ years and those with overweight/obesity. With mounting evidence on young-onset T2DM and T2DM patients with lean phenotypes, it is worth revising the screening criteria to include younger and leaner adults. We quantified the mean age and body mass index (BMI; kg/m2 ) at T2DM diagnosis in 56 countries. METHODS: Descriptive cross-sectional analysis of WHO STEPS surveys. We analysed adults (25-69 years) with new T2DM diagnosis (not necessarily T2DM onset) as per fasting plasma glucose ≥126 mg/dL measured during the survey. For people with new T2DM diagnosis, we summarized the mean age and the proportion of each five-year age group; also, we summarized the mean BMI and the proportion of mutually exclusive BMI categories. RESULTS: There were 8695 new T2DM patients. Overall, the mean age at T2DM diagnosis was 45.1 years in men and 45.0 years in women; and the mean BMI at T2DM diagnosis was 25.2 in men and 26.9 in women. Overall, in men, 10.3% were 25-29 years and 8.5% were 30-34 years old; in women, 8.6% and 12.5% were 25-29 years and 30-34 years old, respectively. 48.5% of men and 37.3% of women were in the normal BMI category. CONCLUSIONS: A non-negligible proportion of new T2DM patients were younger than 35 years. Many new T2DM patients were in the normal weight range. Guidelines for T2DM screening may consider revising the age and BMI criteria to incorporate young and lean adults.
Subject(s)
Diabetes Mellitus, Type 2 , Adult , Child, Preschool , Female , Humans , Male , Body Mass Index , Cross-Sectional Studies , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiology , Mass Screening , Risk Factors , Age of OnsetABSTRACT
BACKGROUND: Many physical, psychological, and cognitive disorders are highly clustered among populations with low socioeconomic status. However, the extent to which socioeconomic status is associated with different combinations of these disorders is unclear, particularly outside high-income countries. We aimed to evaluate these associations in 33 countries including high-income countries, upper-middle-income countries, and one lower-middle-income country. METHODS: This cross-sectional multi-region study pooled individual-level data from seven studies on ageing between 2017 and 2020. Education and total household wealth were used to measure socioeconomic status. Physical disorder was defined as having one or more of the self-reported chronic conditions. Psychological and cognitive disorders were measured by study-specific instruments. The outcome included eight categories: no disorders, physical disorder, psychological disorder, cognitive disorder, and their four combinations. Multivariable-adjusted logistic regression models were used to estimate odds ratios (ORs) and 95% CIs for the associations of socioeconomic status with these outcomes separately for high-income countries, upper-middle-income countries, and the lower-middle-income country. FINDINGS: Among 167 376 individuals aged 45 years and older, the prevalence of multimorbidity was 24·5% in high-income countries, 33·9% in upper-middle-income countries, and 8·1% in the lower-middle-income country (India). Lower levels of education, household wealth, and a combined socioeconomic status score were strongly associated with physical, psychological, and cognitive multimorbidity in high-income countries and upper-middle-income countries, with ORs (low vs high socioeconomic status) for physical-psychological-cognitive multimorbidity of 12·36 (95% CI 10·29-14·85; p<0·0001) in high-income countries and of 23·84 (18·85-30·14; p<0·0001) in upper-middle-income countries. The associations in the lower-middle-income country were mixed. Participants with both a low level of education and low household wealth had the highest odds of multimorbidity (eg, OR for physical-psychological-cognitive multimorbidity 21·21 [15·95-28·19; p<0·0001] in high-income countries, 37·07 [25·66-53·56; p<0·0001] in upper-middle-income countries, and 54·96 [7·66-394·38; p<0·0001] in the lower-middle-income country). INTERPRETATION: In study populations from high-income countries, upper-middle-income countries, and the lower-middle-income country, the odds of multimorbidity, which included physical, psychological, and cognitive disorders, were more than ten times greater in individuals with low socioeconomic status. Equity-oriented policies and programmes that reduce social inequalities in multimorbidity are urgently needed to achieve Sustainable Development Goals. FUNDING: Zhejiang University, Fundamental Research Funds for the Central Universities, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Wellcome Trust, Medical Research Council, National Institute on Aging, and Academy of Finland. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.
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Aging , Multimorbidity , Humans , Middle Aged , Aged , Cross-Sectional Studies , Socioeconomic Factors , CognitionABSTRACT
AIMS: To compare levels of cardiometabolic risk factors in young and old adults with diabetes. METHODS: Pooled analysis of 42 STEPS Surveys (n = 133,717). Diabetes was defined as self-reported diagnosis or fasting plasma glucose ≥ 126 mg/dl. There were two age groups: < 40 and ≥ 40 years. We summarized the mean levels of four cardiometabolic risk factors by country, sex and age group. RESULTS: In 11 (men) and seven countries (women), the mean BMI seemed higher in young versus old adults; largest difference was found in men in Qatar (â¼6 kg/m2). For waist circumference, such pattern was observed in two (men) and in three (women) countries; largest difference in men in Tuvalu (â¼7 cm). Regarding systolic blood pressure, in one country (Myanmar) the mean was higher in young men with â¼8 mmHg difference. Women in the oldest group always had higher mean systolic blood pressure. For total cholesterol, in 13 (men) and five (women) countries the mean was higher in young adults (difference was always <1 mmol/l). CONCLUSIONS: Levels of cardiometabolic risk factors in young versus old adults with diabetes were heterogenous across 42 countries and depended on the risk factor. This calls to monitor cardiometabolic risk factors in young adults with diabetes.
Subject(s)
Cardiovascular Diseases , Diabetes Mellitus , Male , Young Adult , Humans , Female , Adult , Cross-Sectional Studies , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/epidemiology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Risk Factors , Health Surveys , Body Mass IndexABSTRACT
SUMMARY Objective: To quantify the frequency of psychiatric disorders in the outpatient setting in Peru, from 2018 to 2021. Methods: Observational cross-sectional study using outpatient morbidity data from Perú's National Superintendence of Health. Psychiatric diagnoses were identified using ICD-10 codes. The frequency of major psychiatric disorder groups is described by demographic variables. Monthly trends, as well as the number of outpatient visits per 10,000 population at the subnational level, are also presented. Results: Between 2018-2021, psychiatric disorders accounted for 3,142,685 outpatient visits (2.3% of all) in Peru. Across working age groups, anxiety and depressive disorders comprised approximately 6 out of 10 psychiatric outpatient visits in women, and 4 out of 10 in men. Monthly trends showed two peaks in the absolute number of psychiatric outpatient visits during the pre-pandemic period: April-May and September. Provinces in the Highlands had the lowest outpatient visits per 10,000 population. Conclusions: Psychiatric disorders represent a small fraction of the outpatient visits in Peru, with anxiety and depressive disorders as the most frequent. National strategies targeting outpatients with psychiatric disorders should consider demographic differences, monthly trends, and the impact of the COVID-19 pandemic.
RESUMEN Objetivo: Cuantificar la frecuencia de trastornos psiquiátricos en el ámbito ambulatorio en Perú, del 2018 al 2021. Métodos: Estudio observacional transversal utilizando información de la Superintendencia Nacional de Salud del Perú. Los diagnósticos psiquiátricos se identificaron mediante códigos de CIE-10. La frecuencia de trastornos psiquiátricos mayores se describe mediante variables demográficas. También se presentan las tendencias mensuales, así como el número de visitas ambulatorias por cada 10.000 habitantes a nivel subnacional. Resultados: Entre 2018-2021, los trastornos psiquiátricos presentaron 3.142.685 visitas ambulatorias (2,3% del total) en el Perú. En todos los grupos de edad laboral, los trastornos de ansiedad y depresión representaron aproximadamente 6 de cada 10 visitas ambulatorias psiquiátricas en mujeres y 4 de cada 10 en hombres. Las tendencias mensuales mostraron dos picos en el número absoluto de visitas ambulatorias psiquiátricas durante el período prepandémico: abril-mayo y septiembre. Las provincias de la sierra tuvieron la frecuencia más baja de visitas ambulatorias por cada 10.000 habitantes. Conclusiones: Los trastornos psiquiátricos representan una pequeña fracción de las consultas ambulatorias en el Perú, con los trastornos de ansiedad y depresivos como los más frecuentes. Estrategias nacionales en relación a pacientes ambulatorios con trastornos psiquiátricos deben considerar diferencias demográficas, tendencias mensuales y el impacto de la pandemia COVID-19.
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BACKGROUND: Five modifiable risk factors are associated with cardiovascular disease and death from any cause. Studies using individual-level data to evaluate the regional and sex-specific prevalence of the risk factors and their effect on these outcomes are lacking. METHODS: We pooled and harmonized individual-level data from 112 cohort studies conducted in 34 countries and 8 geographic regions participating in the Global Cardiovascular Risk Consortium. We examined associations between the risk factors (body-mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, current smoking, and diabetes) and incident cardiovascular disease and death from any cause using Cox regression analyses, stratified according to geographic region, age, and sex. Population-attributable fractions were estimated for the 10-year incidence of cardiovascular disease and 10-year all-cause mortality. RESULTS: Among 1,518,028 participants (54.1% of whom were women) with a median age of 54.4 years, regional variations in the prevalence of the five modifiable risk factors were noted. Incident cardiovascular disease occurred in 80,596 participants during a median follow-up of 7.3 years (maximum, 47.3), and 177,369 participants died during a median follow-up of 8.7 years (maximum, 47.6). For all five risk factors combined, the aggregate global population-attributable fraction of the 10-year incidence of cardiovascular disease was 57.2% (95% confidence interval [CI], 52.4 to 62.1) among women and 52.6% (95% CI, 49.0 to 56.1) among men, and the corresponding values for 10-year all-cause mortality were 22.2% (95% CI, 16.8 to 27.5) and 19.1% (95% CI, 14.6 to 23.6). CONCLUSIONS: Harmonized individual-level data from a global cohort showed that 57.2% and 52.6% of cases of incident cardiovascular disease among women and men, respectively, and 22.2% and 19.1% of deaths from any cause among women and men, respectively, may be attributable to five modifiable risk factors. (Funded by the German Center for Cardiovascular Research (DZHK); ClinicalTrials.gov number, NCT05466825.).
Subject(s)
Cardiovascular Diseases , Heart Disease Risk Factors , Female , Humans , Male , Middle Aged , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/mortality , Diabetes Mellitus , Risk Factors , Smoking/adverse effects , InternationalityABSTRACT
BACKGROUND: Little is known about the relationship between early life body size and occurrence of life-course multiple chronic diseases (multimorbidity). We aim to evaluate associations of birth weight, childhood body size, and their changes with the risks of chronic diseases and multimorbidity. METHODS: This prospective cohort study included 246,495 UK Biobank participants (aged 40-69 years) who reported birth weight and childhood body size at 10 years old. Birth weight was categorized into low, normal, and high; childhood body size was reported as being thinner, average, or plumper. Multimorbidity was defined as having two or more of 38 chronic conditions retrieved from inpatient hospital data until 31 December, 2020. The Cox regression and quasi-Poisson mixed effects models were used to estimate the associations. RESULTS: We show that 57,071 (23.2%) participants develop multimorbidity. Low birth weight (hazard ratio [HR] 1.29, 95% confidence interval [CI] 1.26-1.33), high birth weight (HR 1.02, 95% CI > 1.00-1.05), thinner (HR 1.21, 95% CI 1.18-1.23) and plumper body size (HR 1.06, 95% CI 1.04-1.09) are associated with higher risks of multimorbidity. A U-shaped relationship between birth weight and multimorbidity is observed. Changing to be thinner or plumper is associated with multimorbidity and many conditions, compared to changing to be average. CONCLUSIONS: Low birth weight, being thinner and changing to have a thinner body size in childhood are associated with higher risks of developing multimorbidity and many chronic conditions in adulthood. Early monitoring and maintaining a normal body size in childhood could have life-course benefits for preventing multimorbidity above and beyond individual conditions.
Little is known about the relationship between childhood body size and the risk of developing more than one chronic disease later in life. Using data from the UK, we found that low birth weight, high birth weight, and being thinner or plumper than average during childhood were all associated with higher risks of developing more than one chronic disease in adulthood. In addition, changing body shape during childhood to be either thinner or plumper, was associated with being more likely to develop more than one chronic disease later in life. Our results highlight the importance of early monitoring and maintenance of average body size in childhood, as this might prevent the occurrence of chronic diseases later in life.
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AIMS: Establishing whether fasting plasma glucose (FPG), postprandial glucose (PPG), and HbA1c have the same diagnostic accuracy in NAFLD versus otherwise healthy people could inform T2DM screening recommendations for those with NAFLD. METHODS: Cross-sectional analysis of the Third National Health and Nutrition Examination Survey (NHANES III) 1989-1994. T2DM was defined as PPG ≥ 200 mg/dL, FPG ≥ 126 mg/dL, or HbA1c ≥ 6.5 %. We estimated sensitivity and specificity between the six pairwise combinations between the three T2DM definitions in people with and without NAFLD. With Poisson regressions, we investigated if people with NAFLD were more likely to have T2DM with two diagnostic criteria yet not with the third one. RESULTS: There were 3652 people with mean age 55.6 years and 49.4 % were men; 673 (18.4 %) people had NAFLD. Compared to NAFLD-free individuals, those with NAFLD had lower specificity in all pairwise comparisons except when PPG was the reference vs HbA1c [98.28 % (95 % CI: 97.73 %-98.72 %) in people without NAFLD vs 96.15 % (95 % CI: 94.28 %-97.54 %)]. The sensitivity of FPG was slightly superior to PPG and HbA1c in people without NAFLD; for example, 64.62 % (95 % CI: 55.75 %-72.80 %) for FPG vs 56.58 % (95 % CI: 44.71 %-67.92 %) for HbA1c. People with NAFLD were more likely to be diagnosed with FPG and PPG yet not with HbA1c (PR=2.15; p = 0.020). CONCLUSIONS: While these T2DM diagnostic criteria may capture different patients both in people with and without NAFLD, in the NAFLD population FPG appears to have the best sensitivity and there were no differences between PPG and HbA1c in terms of specificity.
Subject(s)
Diabetes Mellitus, Type 2 , Non-alcoholic Fatty Liver Disease , Male , Humans , Middle Aged , Female , Non-alcoholic Fatty Liver Disease/diagnosis , Non-alcoholic Fatty Liver Disease/epidemiology , Nutrition Surveys , Glycated Hemoglobin , Blood Glucose , Cross-Sectional Studies , Sensitivity and Specificity , Glucose , Fasting , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiologyABSTRACT
BACKGROUND: The burden of chronic conditions associated with sugary beverages is increasing but little is known about the role of different types of sugary beverages in the co-occurrence of multiple chronic conditions ('multimorbidity'). To inform future sugar-reduction guidelines, we aimed to examine the associations of sugar-sweetened beverages (SSB), artificially sweetened beverages (ASB) and natural juices (NJ) with multimorbidity. METHODS: This prospective cohort study included 184â093 UK Biobank participants aged 40-69 years at baseline who completed at least one occasion of 24-h dietary recall between 2009 and 2012. Daily consumptions of SSB, ASB and NJ were assessed using 24-h dietary recall. Participants were followed from the first 24-h assessment until the onset of two or more new chronic conditions, or the end of follow-up (31 March 2017), whichever occurred first. Logistic regression models, Cox proportional hazard models and quasi-Poisson mixed effects models were used to estimate the association of beverages intakes with chronic conditions and multimorbidity. RESULTS: A total of 19â057 participants had multimorbidity at baseline and 19â968 participants developed at least two chronic conditions during follow-up. We observed dose-response relationships of SSB and ASB consumptions with the prevalence and incidence of multimorbidity. For example, the adjusted hazard ratios (HRs) and 95% CIs of the incidence of developing at least two chronic conditions ranged from 1.08 (1.01-1.14) for SSB intake of 1.1-2 units/day to 1.23 (1.14-1.32) for >2 units/day compared with 0 units/day. Also, the adjusted HRs (95% CIs) of ASB consumption ranged from 1.08 (1.03-1.13) for 0.1-1 unit/day to 1.28 (1.17-1.40) for >2 units/day compared with non-consumers. Conversely, moderate consumption of NJ was associated with a smaller risk of the prevalence and incidence of multimorbidity. Moreover, higher intakes of SSB and ASB were positively associated whereas moderate intake of NJ was inversely associated with increased number of new-onset chronic conditions during follow-up. CONCLUSIONS: Higher SSB and ASB intakes were positively associated whereas moderate NJ intake was inversely associated with the higher risk of multimorbidity and increased number of chronic conditions. Current and intended policy options to decrease the burden of chronic conditions and multimorbidity need a formulation of SSB and ASB reduction strategies.
ABSTRACT
Stroke is a recurrent and well-known cardiovascular event and a leading cause of death worldwide. We identified reliable epidemiological evidence of stroke in Latin America and the Caribbean (LAC) and estimated the prevalence and incidence of stroke, overall and by sex, in that region. A systematic search in OVID (Medline, Embase and Global Health) and in the Latin America and Caribbean Health Sciences Literature (LILACS) until the end of 2020 was made for all cross-sectional or longitudinal studies estimating (or allowing the estimation of) the prevalence or incidence of stroke among individuals of the general population ≥ 18 years from LAC countries. No language restriction was applied. Studies were assessed for methodological quality and risk of bias. Pooled estimates were calculated using random effect meta-analysis as high heterogeneity was expected. A total of 31 papers for prevalence and 11 papers for incidence were included in the review for analysis. The overall pooled stroke prevalence was 32 (95% CI 26-38) per 1000 subjects and were similar among men (21; 95% CI 17-25) and women (20; 95% CI 16-23) per 1000 subjects. The overall pooled stroke incidence was 255 (95% CI 217-293) per 100 000 person-years, being higher in men (261; 95% CI 221-301) compared to women (217; 95% CI 184-250) per 100 000 person-years. Our results highlight the relevance of the prevalence and incidence of stroke in the LAC region. The estimates were similar in stroke prevalence by sex, but with higher incidence rates among males than females. Subgroup analyses highlight the need for standardized methodologies to obtain appropriate prevalence and incidence estimates at the population level in a region with a great burden of cardiovascular events.
Subject(s)
Stroke , Male , Humans , Female , Latin America/epidemiology , Incidence , Prevalence , Cross-Sectional Studies , Caribbean Region/epidemiology , Stroke/epidemiologyABSTRACT
BACKGROUND: Multimorbidity poses an immense burden on the healthcare systems globally, whereas the management strategies and guidelines for multimorbidity are poorly established. We aim to synthesize current evidence on interventions and management of multimorbidity. METHODS: We searched four electronic databases (PubMed, Embase, Web of Science, and the Cochrane Database of Systematic Reviews). Systematic reviews (SRs) on interventions or management of multimorbidity were included and evaluated. The methodological quality of each SR was assessed by the AMSTAR-2 tool, and the quality of evidence on the effectiveness of interventions was assessed by the grading of recommendations assessment, development and evaluation (GRADE) system. RESULTS: A total of 30 SRs (464 unique underlying studies) were included, including 20 SRs of interventions and 10 SRs summarizing evidence on management of multimorbidity. Four categories of interventions were identified: patient-level interventions, provider-level interventions, organization-level interventions, and combined interventions (combining the aforementioned two or three- level components). The outcomes were categorized into six types: physical conditions/outcomes, mental conditions/outcomes, psychosocial outcomes/general health, healthcare utilization and costs, patients' behaviors, and care process outcomes. Combined interventions (with patient-level and provider-level components) were more effective in promoting physical conditions/outcomes, while patient-level interventions were more effective in promoting mental conditions/outcomes and psychosocial outcomes/general health. As for healthcare utilization and care process outcomes, organization-level and combined interventions (with organization-level components) were more effective. The challenges in the management of multimorbidity at the patient, provider and organizational levels were also summarized. CONCLUSION: Combined interventions for multimorbidity at different levels would be favored to promote different types of health outcomes. Challenges exist in the management at the patient, provider, and organization levels. Therefore, a holistic and integrated approach of patient-, provider- and organization- level interventions is required to address the challenges and optimize care of patients with multimorbidity.