METHODS: Men from Dolakha, Nepal, who had ever migrated outside of Nepal for work were interviewed on their experiences, from predeparture to return (n=194). Forced labour was assessed among those who returned within the past 10 years (n=140) using the International Labour Organization's forced labour dimensions: (1) unfree recruitment; (2) work and life under duress; and (3) impossibility to leave employer. Forced labour is positive if any one of the dimensions is positive.
RESULTS: Participants had worked in India (34%), Malaysia (34%) and the Gulf Cooperation Council countries (29%), working in factories (29%), as labourers/porters (15%) or in skilled employment (12%). Among more recent returnees (n=140), 44% experienced unfree recruitment, 71% work and life under duress and 14% impossibility to leave employer. Overall, 73% experienced forced labour during their most recent labour migration.Forced labour was more prevalent among those who had taken loans for their migration (PR 1.23) and slightly less prevalent among those who had migrated more than once (PR 0.87); however the proportion of those who experienced forced labour was still high (67%). Age, destination and duration of stay were associated with only certain dimensions of forced labour.
CONCLUSION: Forced labour experiences were common during recruitment and at destination. Migrant workers need better advice on assessing agencies and brokers, and on accessing services at destinations. As labour migration from Nepal is not likely to reduce in the near future, interventions and policies at both source and destinations need to better address the challenges migrants face so they can achieve safer outcomes.
METHODS: A prospective, multi-centre, multi-country study including patients hospitalized with AHF was conducted. Clinical characteristics, echocardiogram, BNP (B-type natriuretic peptide), socioeconomic status, management, 1-month, and 1-year outcomes are reported.
RESULTS: Between April 2019 and June 2020, a total of 1258 adults with AHF from 16 Arab countries were recruited. Their mean age was 63.3 (±15) years, 56.8% were men, 65% had monthly income ≤US$ 500, and 56% had limited education. Furthermore, 55% had diabetes mellitus, 67% had hypertension; 55% had HFrEF (heart failure with reduced ejection fraction), and 19% had HFpEF (heart failure with preserved ejection fraction). At 1 year, 3.6% had a heart failure-related device (0-22%) and 7.3% used an angiotensin receptor neprilysin inhibitor (0-43%). Mortality was 4.4% per 1 month and 11.77% per 1-year post-discharge. Compared with higher-income patients, lower-income patients had a higher 1-year total heart failure hospitalization rate (45.6 vs 29.9%, p=0.001), and the 1-year mortality difference was not statistically significant (13.2 vs 8.8%, p=0.059).
CONCLUSION: Most of the patients with AHF in Arab countries had a high burden of cardiac risk factors, low income, and low education status with great heterogeneity in key performance indicators of AHF management among Arab countries.
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 (pinteraction<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 (pinteraction<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 (pinteraction<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).
METHODS: A cross-section of 163,397 adults aged 35 to 70 years were recruited from 661 urban and rural communities in selected low-, middle- and high-income countries (complete data for this analysis from 151,619 participants). Using blood pressure measurements, self-reported health and household data, concentration indices adjusted for age, sex and urban-rural location, we estimate the magnitude of wealth-related inequalities in the levels of hypertension awareness, treatment, and control in each of the 21 country samples.
RESULTS: Overall, the magnitude of wealth-related inequalities in hypertension awareness, treatment, and control was observed to be higher in poorer than in richer countries. In poorer countries, levels of hypertension awareness and treatment tended to be higher among wealthier households; while a similar pro-rich distribution was observed for hypertension control in countries at all levels of economic development. In some countries, hypertension awareness was greater among the poor (Sweden, Argentina, Poland), as was treatment (Sweden, Poland) and control (Sweden).
CONCLUSION: Inequality in hypertension management outcomes decreased as countries became richer, but the considerable variation in patterns of wealth-related inequality - even among countries at similar levels of economic development - underscores the importance of health systems in improving hypertension management for all. These findings show that some, but not all, countries, including those with limited resources, have been able to achieve more equitable management of hypertension; and strategies must be tailored to national contexts to achieve optimal impact at population level.
Materials and Methods: The 500 individuals of both males and females aged 40 years and older with missing posterior teeth and not rehabilitated with any prosthesis were gone through a clinical history, intraoral examination, and anthropometric measurement to get information regarding age, sex, socioeconomic status, missing posterior teeth, and body mass index (BMI). Subjects were divided into five groups according to BMI (underweight > 18.5 kg/m2, normal weight 18.5-23 kg/m2, overweight 23-25 kg/m2, obese without surgery 25-32.5 kg/m2, obese with surgery < 32.5 kg/m2). Multivariate logistic regression was used to adjust data according to age, sex, number of missing posterior teeth, and socioeconomic status.
Results: People with a higher number of tooth loss were more obese. Females with high tooth loss were found to be more obese than male. Low socioeconomic group obese female had significantly higher tooth loss than any other group. No significant relation between age and obesity was found with regard to tooth loss.
Conclusion: The BMI and tooth loss are interrelated. Management of obesity and tooth loss can help to maintain the overall health status.