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Background: Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status-wealth and education-differ among high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management., Methods: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family., Findings: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (p interaction <0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (p interaction <0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (p interaction <0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries., Interpretation: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education., Funding: Full funding sources are listed at the end of the paper (see Acknowledgments)., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: The associations between the extent of forced expiratory volume in 1 s (FEV 1 ) impairment and mortality, incident cardiovascular disease, and respiratory hospitalisations are unclear, and how these associations might vary across populations is unknown., Methods: In this international, community-based cohort study, we prospectively enrolled adults aged 35-70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV 1 . FEV 1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV 1 value (FEV 1 %). FEV 1 % was categorised as no impairment (FEV 1 % ≥0 SD from country-specific mean), mild impairment (FEV 1 % <0 SD to -1 SD), moderate impairment (FEV 1 % <-1 SD to -2 SDs), and severe impairment (FEV 1 % <-2 SDs [ie, clinically abnormal range]). Follow-up was done every 3 years to collect information on mortality, cardiovascular disease outcomes (including myocardial infarction, stroke, sudden death, or congestive heart failure), and respiratory hospitalisations (from chronic obstructive pulmonary disease, asthma, pneumonia, tuberculosis, or other pulmonary conditions). Fully adjusted hazard ratios (HRs) were calculated by multilevel Cox regression., Findings: Among 126 359 adults with acceptable spirometry data available, during a median 7·8 years (IQR 5·6-9·5) of follow-up, 5488 (4·3%) deaths, 5734 (4·5%) cardiovascular disease events, and 1948 (1·5%) respiratory hospitalisation events occurred. Relative to the no impairment group, mild to severe FEV 1 % impairments were associated with graded increases in mortality (HR 1·27 [95% CI 1·18-1·36] for mild, 1·74 [1·60-1·90] for moderate, and 2·54 [2·26-2·86] for severe impairment), cardiovascular disease (1·18 [1·10-1·26], 1·39 [1·28-1·51], 2·02 [1·75-2·32]), and respiratory hospitalisation (1·39 [1·24-1·56], 2·02 [1·75-2·32], 2·97 [2·45-3·60]), and this pattern persisted in subgroup analyses considering country income level and various baseline risk factors. Population-attributable risk for mortality (adjusted for age, sex, and country income) from mildly to moderately reduced FEV 1 % (24·7% [22·2-27·2]) was larger than that from severely reduced FEV 1 % (3·7% [2·1-5·2]) and from tobacco use (19·7% [17·2-22·3]), previous cardiovascular disease (5·5% [4·5-6·5]), and hypertension (17·1% [14·6-19·6]). Population-attributable risk for cardiovascular disease from mildly to moderately reduced FEV 1 was 17·3% (14·8-19·7), second only to the contribution of hypertension (30·1% [27·6-32·5])., Interpretation: FEV 1 is an independent and generalisable predictor of mortality, cardiovascular disease, and respiratory hospitalisation, even across the clinically normal range (mild to moderate impairment)., Funding: Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Ontario Ministry of Health and Long-Term Care, AstraZeneca, Sanofi-Aventis, Boehringer Ingelheim, Servier, and GlaxoSmithKline, Novartis, and King Pharma. Additional funders are listed in the appendix., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)