OBJECTIVES: This paper presents consensus work conducted with an international group of expert stroke recovery and rehabilitation researchers, clinicians, and people living with stroke to identify and define criteria and measurable indicators for Centers of Clinical Excellence (CoCE) in stroke recovery and rehabilitation. These were intentionally developed to be ambitious and internationally relevant, regardless of a country's development or income status, to drive global improvement in stroke services.
METHODS: Criteria and specific measurable indicators for CoCE were collaboratively developed by an international panel of stroke recovery and rehabilitation experts from 10 countries and consumer groups from 5 countries.
RESULTS: The criteria and associated indicators, ranked in order of importance, focused upon (i) optimal outcome, (ii) research culture, (iii) working collaboratively with people living with stroke, (iv) knowledge exchange, (v) leadership, (vi) education, and (vii) advocacy. Work is currently underway to user-test the criteria and indicators in 14 rehabilitation centers in 10 different countries.
CONCLUSIONS: We anticipate that use of the criteria and indicators could support individual organizations to further develop their services and, more widely, provide a mechanism by which clinical excellence can be articulated and shared to generate global improvements in stroke care.
SETTING: Adults interviewed during house-to-house surveys.
PARTICIPANTS: Women (15-45 years) and men (15-49 years) surveyed in four Nepal Demographic and Health Surveys done in 2001, 2006, 2011 and 2016.
OUTCOME MEASURE: Current tobacco use (in any form).
RESULTS: The prevalence of tobacco use for men declined from 66% in 2001 to 55% in 2016, and declined from 29% to 8.4% among women. Across both education and wealth quintiles for both men and women, the prevalence of tobacco use generally declines with increasing education or wealth. We found persistently larger absolute inequalities by education than by wealth among men. Among women we also found larger educational than wealth-related gradients, but both declined over time. For men, the Slope Index of Inequality (SII) for education was larger than for wealth (44% vs 26% in 2001) and changed very little over time. For women, the SII for both education and wealth were similar in magnitude to men, but decreased substantially between 2001 and 2016 (from 44% to 16% for education; from 37% to 16% for wealth). Women had a larger relative index of inequality than men for both education (6.5 vs 2.0 in 2001) and wealth (4.8 vs 1.5 in 2001), and relative inequality increased between 2001 and 2016 for women (from 6.5 to 16.0 for education; from 4.8 to 12.0 for wealth).
CONCLUSION: Increasing relative inequalities indicates suboptimal reduction in tobacco use among the vulnerable groups suggesting that they should be targeted to improve tobacco control.
METHODS: We analysed Demographic and Health Survey data on tobacco use collected from large nationally representative samples of men and women in 54 LMICs. We estimated the weighted prevalence of any current tobacco use (including smokeless tobacco) in each country for 4 educational groups and 4 wealth groups. We calculated absolute and relative measures of inequality, that is, the slope index of inequality (SII) and relative index of inequality (RII), which take into account the distribution of prevalence across all education and wealth groups and account for population size. We also calculated the aggregate SII and RII for low-income (LIC), lower-middle-income (lMIC) and upper-middle-income (uMIC) countries as per World Bank classification.
FINDINGS: Male tobacco use was highest in Bangladesh (70.3%) and lowest in Sao Tome (7.4%), whereas female tobacco use was highest in Madagascar (21%) and lowest in Tajikistan (0.22%). Among men, educational inequalities varied widely between countries, but aggregate RII and SII showed an inverse trend by country wealth groups. RII was 3.61 (95% CI 2.83 to 4.61) in LICs, 1.99 (95% CI 1.66 to 2.38) in lMIC and 1.82 (95% CI 1.24 to 2.67) in uMIC. Wealth inequalities among men varied less between countries, but RII and SII showed an inverse pattern where RII was 2.43 (95% CI 2.05 to 2.88) in LICs, 1.84 (95% CI 1.54 to 2.21) in lMICs and 1.67 (95% CI 1.15 to 2.42) in uMICs. For educational inequalities among women, the RII varied much more than SII varied between the countries, and the aggregate RII was 14.49 (95% CI 8.87 to 23.68) in LICs, 3.05 (95% CI 1.44 to 6.47) in lMIC and 1.58 (95% CI 0.33 to 7.56) in uMIC. Wealth inequalities among women showed a pattern similar to that of men: the RII was 5.88 (95% CI 3.91 to 8.85) in LICs, 1.76 (95% CI 0.80 to 3.85) in lMIC and 0.39 (95% CI 0.09 to 1.64) in uMIC. In contrast to men, among women, the SII was pro-rich (higher smoking among the more advantaged) in 13 of the 52 countries (7 of 23 lMIC and 5 of 7 uMIC).
INTERPRETATION: Our results confirm that socioeconomic inequalities tobacco use exist in LMIC, varied widely between the countries and were much wider in the lowest income countries. These findings are important for better understanding and tackling of socioeconomic inequalities in health in LMIC.