Are Neighborhood Greenspaces Associated with Leisure-time Physical Activity? Results from ELSA-Brasil Eight-year Follow-up.

We investigated whether neighborhood greenspaces were associated with physical activity in adulthood over 3 cohort visits after considering perceived safety and neighborhood contextual factors. We also evaluated whether the association with greenspace varied by neighborhood socioeconomic status. Participants (N = 4,800) from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) residing in two Brazilian state capitals were evaluated in Visits 1 (2008-2010), 2 (2012-2014) and 3 (2017-2019). Greenspaces were categorized by quintiles of positive Normalized Difference Vegetation Index (NDVI) scores. Physical activity frequency was given by the number of visits at which participants reported moderate/vigorous physical activity (none, 1 or 2, and 3 visits). We used multinomial logistic regression. After adjustment for age, sex, education, research center, residence in slums, individuals in the 4th and 5th NDVI quintiles showed 73% higher odds of physical activity over 3 visits than those in the 1st quintile (4th quintile: 95%CI = 1.24-2.43; 5th quintile: 95%CI = 1.24-2.41). The strength of the association was attenuated after adjustment for perceived safety. After adjustment for contextual factors quantity of sidewalks and streetlights, the OR for the 4th and 5th NDVI quintiles decreased to 1.66 (95%CI = 1.18-2.33) and 1.62 (95%CI = 1.16-2.28), respectively. Finally, after including average household income per capita, the OR for physical activity in 3 visits for the 4th and 5th NDVI quintiles decreased to 1.48 (95%CI = 1.04-2.12) and 1.43 (95%CI = 1.00-2.04; p = 0.053), respectively. Greater greenspace contributed to sustained physical activity during the eight years of follow-up, indicating the potential contribution of public greenspaces to reducing health-related inequalities.

Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.

BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle influences, and metabolic diseases such as diabetes, and hypertension. While the physiological pathways linking metabolic and cardiovascular diseases have been investigated, the study of the sex and population differences in the CMC have still not been described. METHODS: We present a machine learning approach to model the CMC and investigate sex and population differences in two distinct cohorts: the UK Biobank (17,700 participants) and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) (7162 participants). We consider the following CMDs: hypertension (Hyp), diabetes (DM), heart diseases (HD: angina, myocardial infarction, or heart failure), and stroke (STK). For the identification of the CMC patterns, individual trajectories with the time of disease occurrence were clustered using k-means. Based on clinical, sociodemographic, and lifestyle characteristics, we built multiclass random forest classifiers and used the SHAP methodology to evaluate feature importance. RESULTS: Five CMC patterns were identified across both sexes and cohorts: EarlyHyp, FirstDM, FirstHD, Healthy, and LateHyp, named according to prevalence and disease occurrence time that depicted around 95%, 78%, 75%, 88% and 99% of individuals, respectively. Within the UK Biobank, more women were classified in the Healthy cluster and more men in all others. In the EarlyHyp and LateHyp clusters, isolated hypertension occurred earlier among women. Smoking habits and education had high importance and clear directionality for both sexes. For ELSA-Brasil, more men were classified in the Healthy cluster and more women in the FirstDM. The diabetes occurrence time when followed by hypertension was lower among women. Education and ethnicity had high importance and clear directionality for women, while for men these features were smoking, alcohol, and coffee consumption. CONCLUSIONS: There are clear sex differences in the CMC that varied across the UK and Brazilian cohorts. In particular, disadvantages regarding incidence and the time to onset of diseases were more pronounced in Brazil, against woman. The results show the need to strengthen public health policies to prevent and control the time course of CMD, with an emphasis on women.

[Is socioeconomic residential segregation associated with sleep problems? Insights from ELSA-Brasil]. / A segregação residencial socioeconômica está associada aos problemas do sono? Insights do ELSA-Brasil.

Several factors influence sleep, which is essential for health. While the role of neighborhood socioeconomic context on sleep health has been studied in recent years, results are inconsistent. The study aimed to investigate the association between socioeconomic residential segregation and sleep problems, using data from the second evaluation (2012-2014) of 9,918 public servants participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Socioeconomic residential segregation was assessed using the Getis-Ord Local Gi* statistic. Sleep duration and deprivation, complaints of insomnia, and daytime sleepiness were obtained through interviews. Binomial and multinomial logistic regression models were used to estimate the odds ratio (OR). Regarding sleep, 49% had short duration and 3% long duration, 23% reported complaints of insomnia, 45% sleep deprivation, 42% daytime sleepiness, and 48% reported ≥ 2 sleep problems. In the model adjusted for demographic and socioeconomic variables, there was an association between high socioeconomic residential segregation and short sleep duration (OR = 1.22; 95%CI: 1.07; 1.40), sleep deprivation (OR = 1.20; 95%CI: 1.05; 1.37), daytime sleepiness (OR = 1.17; 95%CI: 1.03; 1.34) and ≥ 2 associated sleep problems (OR = 1.24; 95%CI: 1.08; 1.41). Individuals living in neighborhoods with high socioeconomic residential segregation are more likely to have short sleep duration, sleep deprivation, daytime sleepiness, and ≥ 2 associated sleep problems. This information reinforces that public policy measures to reduce socioeconomic inequalities can improve the population's sleep health.

O sono é influenciado por diversos fatores e é essencial para a saúde. O papel do contexto socioeconômico da vizinhança na saúde do sono foi estudado nos últimos anos, mas os resultados são inconsistentes. O objetivo deste estudo foi investigar a associação entre a segregação residencial socioeconômica e os problemas do sono. Utilizou-se dados da 2ª avaliação (2012-2014) de 9.918 servidores públicos participantes do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). A segregação residencial socioeconômica foi avaliada por meio da estatística Getis-Ord Local Gi*, e a duração e privação do sono, as queixas de insônia e a sonolência diurna foram obtidas por meio de entrevistas. Para as estimativas da odds ratio (OR), foram utilizados modelos de regressão logística binomial e multinomial. Em relação ao sono, 49% tinham curta duração e 3% longa duração, 23% relataram queixas de insônia, 45% relataram privação do sono, 42% relataram sonolência diurna e 48% relataram ≥ 2 problemas do sono. No modelo ajustado por variáveis demográficas e socioeconômicas, houve associação entre alta segregação residencial socioeconômica e duração curta do sono (OR = 1,22; IC95%: 1,07; 1,40), privação do sono (OR = 1,20; IC95%: 1,05; 1,37), sonolência diurna (OR = 1,17; IC95%: 1,03; 1,34) e ≥ 2 problemas associados do sono (OR = 1,24; IC95%: 1,08; 1,41). Indivíduos que vivem em vizinhanças com alta segregação residencial socioeconômica apresentam maior chance de terem curta duração, privação do sono, sonolência diurna e ≥ 2 problemas associados ao sono. Essas informações reforçam que políticas públicas para reduzir as desigualdades socioeconômicas podem contribuir para melhorar a saúde do sono da população.

El sueño se influye por varios factores y es esencial para la salud. Se estudió el papel del contexto socioeconómico del barrio en la salud del sueño en los últimos años, pero los resultados son inconsistentes. El objetivo del estudio fue investigar la asociación entre la segregación residencial socioeconómica y los problemas de sueño. Se utilizó datos de la 2ª evaluación (2012-2014) de 9918 servidores públicos participantes del Estudio Longitudinal de Salud del Adulto (ELSA-Brasil). Se evaluó la segregación residencial socioeconómica a través de la estadística Getis-Ord Local Gi*. La duración y privación del sueño, las quejas de insomnio y somnolencia diurna se obtuvieron a través de entrevista. Se utilizaron modelos de regresión logística binomial y multinominal para estimar el odds ratio (OR). Con respecto al sueño, el 49% tenía una duración corta y el 3% tenía una duración larga, el 23% relató quejas de insomnio, el 45% relató privación de sueño, el 42% relató somnolencia diurna y el 48% relató ≥ 2 problemas de sueño. En el modelo ajustado por variables demográficas y socioeconómicas, hubo una asociación entre la alta segregación residencial socioeconómica y la duración corta de sueño (OR = 1,22; IC95%: 1,07; 1,40), la privación de sueño (OR = 1,20; IC95%: 1,05; 1,37), la somnolencia diurna (OR = 1,17; IC95%: 1,03; 1,34) y ≥ 2 problemas asociados con el sueño (OR = 1,24; IC95%: 1,08; 1,41). Personas que viven en barrios con una alta segregación residencial socioeconómica presentan una mayor probabilidad de tener duración corta del sueño, privación de sueño, somnolencia diurna y ≥ 2 problemas asociados con el sueño. Estas informaciones resaltan que medidas de políticas públicas para reducir las desigualdades socioeconómicas pueden contribuir a mejorar la salud del sueño en la población.

Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study.

AIMS: Despite notable population differences in high-income and low- and middle-income countries (LMICs), national guidelines in LMICs often recommend using US-based cardiovascular disease (CVD) risk scores for treatment decisions. We examined the performance of widely used international CVD risk scores within the largest Brazilian community-based cohort study (Brazilian Longitudinal Study of Adult Health, ELSA-Brasil). METHODS: All adults 40-75 years from ELSA-Brasil (2008-2013) without prior CVD who were followed for incident, adjudicated CVD events (fatal and non-fatal MI, stroke, or coronary heart disease death). We evaluated 5 scores-Framingham General Risk (FGR), Pooled Cohort Equations (PCEs), WHO CVD score, Globorisk-LAC and the Systematic Coronary Risk Evaluation 2 score (SCORE-2). We assessed their discrimination using the area under the receiver operating characteristic curve (AUC) and calibration with predicted-to-observed risk (P/O) ratios-overall and by sex/race groups. RESULTS: There were 12 155 individuals (53.0±8.2 years, 55.3% female) who suffered 149 incident CVD events. All scores had a model AUC>0.7 overall and for most age/sex groups, except for white women, where AUC was <0.6 for all scores, with higher overestimation in this subgroup. All risk scores overestimated CVD risk with 32%-170% overestimation across scores. PCE and FGR had the highest overestimation (P/O ratio: 2.74 (95% CI 2.42 to 3.06)) and 2.61 (95% CI 1.79 to 3.43)) and the recalibrated WHO score had the best calibration (P/O ratio: 1.32 (95% CI 1.12 to 1.48)). CONCLUSION: In a large prospective cohort from Brazil, we found that widely accepted CVD risk scores overestimate risk by over twofold, and have poor risk discrimination particularly among Brazilian women. Our work highlights the value of risk stratification strategies tailored to the unique populations and risks of LMICs.

Racial inequalities in the development of multimorbidity of chronic conditions: results from a Brazilian prospective cohort.

BACKGROUND: The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). METHODS: Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models. RESULTS: Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38). CONCLUSIONS: Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.

Using Artificial Intelligence to Predict Heart Failure Risk from Single-lead Electrocardiographic Signals: A Multinational Assessment.

Importance: Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based risk assessment. Objective: To evaluate an artificial intelligence (AI) algorithm to predict HF risk from noisy single-lead ECGs. Design: Multicohort study. Setting: Retrospective cohort of individuals with outpatient ECGs in the integrated Yale New Haven Health System (YNHHS) and prospective population-based cohorts of UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Participants: Individuals without HF at baseline. Exposures: AI-ECG-defined risk of left ventricular systolic dysfunction (LVSD). Main Outcomes and Measures: Among individuals with ECGs, we isolated lead I ECGs and deployed a noise-adapted AI-ECG model trained to identify LVSD. We evaluated the association of the model probability with new-onset HF, defined as the first HF hospitalization. We compared the discrimination of AI-ECG against the pooled cohort equations to prevent HF (PCP-HF) score for new-onset HF using Harrel's C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results: There were 194,340 YNHHS patients (age 56 years [IQR, 41-69], 112,082 women [58%]), 42,741 UKB participants (65 years [59-71], 21,795 women [52%]), and 13,454 ELSA-Brasil participants (56 years [41-69], 7,348 women [55%]) with baseline ECGs. A total of 3,929 developed HF in YNHHS over 4.5 years (2.6-6.6), 46 in UKB over 3.1 years (2.1-4.5), and 31 in ELSA-Brasil over 4.2 years (3.7-4.5). A positive AI-ECG screen was associated with a 3- to 7-fold higher risk for HF, and each 0.1 increment in the model probability portended a 27-65% higher hazard across cohorts, independent of age, sex, comorbidities, and competing risk of death. AI-ECG's discrimination for new-onset HF was 0.725 in YNHHS, 0.792 in UKB, and 0.833 in ELSA-Brasil. Across cohorts, incorporating AI-ECG predictions in addition to PCP-HF resulted in improved Harrel's C-statistic (Δ=0.112-0.114), with an IDI of 0.078-0.238 and an NRI of 20.1%-48.8% for AI-ECG vs. PCP-HF. Conclusions and Relevance: Across multinational cohorts, a noise-adapted AI model with lead I ECGs as the sole input defined HF risk, representing a scalable portable and wearable device-based HF risk-stratification strategy.

Association between leisure-time physical activity and arterial stiffness in adults of the ELSA-Brasil study: a mediation analysis.

OBJECTIVES: We aimed at defining the direct and the mediated pathways for the association between leisure-time physical activity (LTPA) and carotid-to-femoral pulse wave velocity (cf-PWV), and also to identify whether these effects are influenced by sex and age. METHODS: Cross-sectional data from 13 718 adults (35-74 years) were obtained at the baseline of the ELSA-Brasil study. The cf-PWV was obtained by measuring the pulse transit time and the distance traveled by the pulse between the carotid and the femoral, as well as clinical and anthropometric parameters were measured. The levels of LTPA were determined by applying the long form of the International Physical Activity Questionnaire (IPAQ). RESULTS: Classical cardiovascular risk factors were independently associated with cf-PWV. Path analysis showed that increased levels of LTPA were directly associated with lower cf-PWV in both men and women ( ß : -0.123 ±â€Š0.03 vs. 0.065 ±â€Š0.029, P for sex = 0.165), except for diabetes. Also, the mediated effect of LTPA on SBP and DBPs, heart rate, BMI, and fasting glucose, was associated with lower cf-PWV in men and women ( ß : -0.113 ±â€Š0.016 vs. -0.104 ±â€Š0.016, P for sex = 0.692), except for diabetes. When age was tested as a moderator, the direct effect did not change significantly according to participants' age, regardless of sex. However, the mediated effect increases in both men and women over 50 years. CONCLUSION: Our findings support that LTPA in adults reduces cf-PWV by acting in different ways according to age. Physical activity in older individuals improves cardiometabolic risk factors and thus mitigates the stiffening of large arteries.

Adherence to the planetary health diet and cognitive decline: findings from the ELSA-Brasil study.

The EAT-Lancet Commission proposed a planetary health diet to improve human health within planetary boundaries; however, little is known about the association between adherence to this diet and cognitive decline. We used data from three waves of the Brazilian Longitudinal Study of Adult Health to evaluate the association between the planetary health diet and cognitive decline using linear mixed-effects models. Here we show that in 11,737 participants (mean (s.d.) age 51.6 (9.0) years, 54% women and 53% white), higher adherence to the planetary health diet was associated with slower memory decline (P = 0.046) and that income was a modifier in this association (P < 0.001). Adherence to the planetary health diet was associated with slower decline of memory (P = 0.040) and global cognition (P = 0.009) in high-income participants. No association was found among low-income participants. The results of our study highlight that the promotion of healthy dietary patterns should take into consideration income barriers as well as differences in dietary habits to achieve high adherence.

Job stress and chronic low back pain: incidence, number of episodes, and severity in a 4-year follow-up of the ELSA-Brasil Musculoskeletal cohort.

ABSTRACT: We investigated the association between job stress, as assessed by the effort-reward imbalance model, and the incidence of chronic low back pain (CLBP) over a 4-year period. A total of 1733 participants from the ELSA-Brasil Musculoskeletal cohort, who were free from LBP at baseline (2012-2014), were included. Episodes of LBP in the past 30 days, intensity, and the presence of disability were investigated in annual telephone follow-ups (2015-2018). Chronic LBP was defined as episodes of LBP lasting >3 months with at least moderate intensity. We analyzed the incidence of at least one episode of CLBP (yes/no), the number of CLBP episodes (0, 1, ≥2), and CLBP severity/disability (absent, nondisabling, severe/disabling). The association between these outcomes and tertiles of the effort-to-reward ratio, as well as each dimension of the effort-reward imbalance model, was investigated using multinomial logistic and Poisson regression models adjusting for sociodemographic and occupational variables. The cumulative incidence of CLBP over 4 years was 24.8%. High effort-reward imbalance increased the chances of experiencing multiple CLBP episodes and severe/disabling CLBP by 67% (95% confidence interval [CI]: 1.12-2.47) and 70% (95% CI: 1.14-2.53), respectively. High overcommitment increased the incidence of CLBP by 23% (95% CI: 1.01-1.50) and the chances of multiple CLBP episodes and severe/disabling CLBP by 67% (95% CI: 1.11-2.50) and 57% (95% CI: 1.05-2.34), respectively. These results indicate that exposure to job stress is associated with a higher incidence, a greater number of episodes, and increased severity of CLBP over a 4-year period. If this association is causal, measures aimed at reducing exposure to job stress are likely to alleviate the burden of CLBP.