The need to implement effective tobacco control programs is undeniable due to the significant and well-established health hazards of smoking.1 Tobacco use remains the leading preventable cause of morbidity and mortality from chronic diseases worldwide, resulting in over eight million deaths annually, and the rate of morbidity and mortality is rising globally due to an increase in smoking-related diseases.2,3 Therefore, the first and the most crucial strategy to confront this global pandemic is the comprehensive implementation of effective tobacco control policies and programs.4–7 To achieve this objective, the WHO negotiated the Framework Convention on Tobacco Control (FCTC) in 2003—representing the world’s first public health treaty. As of July 2021, 182 countries representing 90% of the global population have ratified the FCTC.7 The implementation of the FCTC is credited with preventing an estimated 49 million smoking-attributable deaths within the first ten years of its implementation.5,6 In 2008, a policy and program measures package based on critical articles of the FCTC was developed to help promote and guide FCTC implementation. This package includes six main components, namely: Monitor tobacco use and prevention policies, Protect people from tobacco smoke, Offer help to quit tobacco use, Warn people about the dangers of tobacco, Enforce bans on tobacco advertising, promotion and sponsorship, and Raise taxes on tobacco (MPOWER; to empower).8,9 Experience has revealed that implementing the six strategies mentioned above can reliably decrease the consumption and reduce the consequences and complications of tobacco use in middle- and high-income countries.10–13 Some studies have reported that an analysis of MPOWER implementation by countries may create a competitive challenge between countries to improve their status on tobacco control through international peer pressure.14–18

The objectives of this study are to use results from the 2008 to 2018 MPOWER scores to (i) Report national MPOWER scores to allow countries to benchmark, measure, monitor, compare and stimulate MPOWER implementation; and (ii) Identify independent factors that influence MPOWER implementation.

METHODS

Study design

The design of this study was based on previous observational analyses of bi-annual MPOWER reports.14–18 The data for all MPOWER reporting periods from 2008 to 2018 was retrieved from the WHO Global Health Observatory.19 The data for each country was represented using seven measurable variables, reflecting all MPOWER components, including two indicators for Warn (package warnings and mass media campaigns). All variables have a gradient range of 0-4 (5 gradients) except for Monitor, which has a range of 0-3 (4 gradients) for a maximum possible score of 34 (4 + (5×6) = 34). The scoring is based on previously published methodology.13

Variables and data sources

The primary data source was the WHO Global Health Observatory (GHO)20 which includes all the MPOWER national results collected between 2008 and 2018. The GHO also includes national datasets for (1) tobacco smoking prevalence,21 (2) government objectives on tobacco control,22 (3) national cigarette affordability,23 (4) the annual tobacco control budget of each country,24 (5) the existence of a government tobacco control agency,25 and (6) the number of tobacco control staff employed by national governments.25 All variables, except smoking prevalence, were used for the covariate analysis. Smoking prevalence and its relationship to MPOWER scores have been examined and reported by others.

The secondary data source was Our World in Data (OWID),26 an online repository of numerous health, social, political and economic indices and datasets. The OWID indices selected for this study included (1) literacy rates on a scale of 0 to 10027; (2) the political regime scale from a full democracy to full autocracy28; (3) the United Nations human development index which includes life expectancy, education, and gross national income with an aggregate score between 0 and 129; and (4) the World Bank’s four national income classifications including low income, low-middle, upper-middle, and high income.30

Per capita tobacco control budgets for each country were calculated by dividing a country’s annual budget for tobacco control in equivalent U.S. dollars by its total population size. The standard currency reported by the U.S. Department of Treasury was used for any country without its currency reported in the GHO database. The total population for all countries was obtained from the World Development Indicator Databank (WDI) of the World Bank. For all country currencies without a standard average equivalent of 1 USD in the U.S. Department of Treasury database, an average rate (March 31st, June 30th, September 30th, and December 31st) was calculated from historical currency tables.31

Statistical analysis

The results were organized by the six WHO regions and by the four World Bank national income classifications to allow for geopolitical and economic analysis. Missing or incomplete data in the WHO report received a score of zero in our analysis.

The association between MPOWER scores and potential covariates was analysed using chi-square for categorical variables and student t-test and repeated measure ANOVA for continuous variables to check between and within subjects’ differences. Paired tests were used for the difference in the mean between years, and predictive modelling was performed using traditional forecasting methods. Analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 27.0 (IBM SPSS, Armonk, NY).

RESULTS

The WHO regional numerical breakdowns among the 195 countries represented in this study are Europe & Central Asia (51), Sub-Saharan Africa (48), Latin American & Caribbean (33), East Asia & Pacific (32), Middle East & North Africa (21), South Asia (8) and North America (2). The World Bank national income gradients among the 195 countries represented in this study are Low Income (29), Lower Middle Income (50), Upper Middle Income (56) and High Income (60).

MPOWER scoring in 2018

Twenty (20) countries achieved excellence in implementing MPOWER in 2018 by attaining at least 30 points out of a total of possible 34, including Brazil and Turkey (34 = perfect score); Australia, Ireland and New Zealand (33 points); Panama and United Kingdom (32 points); Costa Rica, Pakistan, Seychelles, and Thailand (31 points); Chile, Czechia, El Salvador, Georgia, Luxembourg, Norway, Republic of Moldova, Senegal and Spain (30 points). The total population of these 20 countries is about 800 million out of a total global population of 7.59 billion (10.5% of the world population). The 15 countries with the lowest levels of implementation include South Sudan (11 points); Monaco (12 points); Equatorial Guinea, Guinea-Bissau, Haiti, Malawi and Somalia (13 points); Central African Republic, Saint Kitts and Nevis, and Sierra Leone (14 points); Angola, Dominica, and Saint Vincent and the Grenadines (15 points); and Liberia and Sao Tome and Principe (16 points). Table 1 contains the 2018 scores for each country.

Table 1.MPOWER scores and rankings of 195 countries in 2008 and 2018
Rank* MPOWER score
  2018 2008 2018 2008 Change Relative change
Brazil 1 24 34 23 11 47.8%
Turkey 2 16 34 24 10 41.7%
Ireland 3 5 33 27 6 22.2%
Australia 4 1 33 28 5 17.9%
New Zealand 5 2 33 28 5 17.9%
Panama 6 8 32 26 6 23.1%
United Kingdom 7 6 32 27 5 18.5%
Costa Rica 8 97 31 18 13 72.2%
Pakistan 9 98 31 18 13 72.2%
Seychelles 10 99 31 18 13 72.2%
Thailand 11 17 31 24 7 29.2%
Senegal 12 136 30 16 14 87.5%
El Salvador 13 100 30 18 12 66.7%
Republic of Moldova 14 101 30 18 12 66.7%
Georgia 15 80 30 19 11 57.9%
Luxembourg 16 65 30 20 10 50.0%
Norway 17 25 30 23 7 30.4%
Czechia 18 18 30 24 6 25.0%
Chile 19 10 30 25 5 20.0%
Spain 20 11 30 25 5 20.0%
Russian Federation 21 102 29 18 11 61.1%
Turkmenistan 22 103 29 18 11 61.1%
Argentina 23 81 29 19 10 52.6%
Saudi Arabia 24 82 29 19 10 52.6%
Greece 25 45 29 21 8 38.1%
Vietnam 26 46 29 21 8 38.1%
Austria 27 35 29 22 7 31.8%
Estonia 28 36 29 22 7 31.8%
Bulgaria 29 26 29 23 6 26.1%
Canada 30 12 29 25 4 16.0%
Egypt 31 13 29 25 4 16.0%
Singapore 32 14 29 25 4 16.0%
Cambodia 33 154 28 15 13 86.7%
Suriname 34 123 28 17 11 64.7%
Madagascar 35 83 28 19 9 47.4%
Tonga 36 84 28 19 9 47.4%
Brunei Darussalam 37 66 28 20 8 40.0%
Cyprus 38 47 28 21 7 33.3%
Ecuador 39 48 28 21 7 33.3%
India 40 49 28 21 7 33.3%
Netherlands 41 50 28 21 7 33.3%
Philippines 42 51 28 21 7 33.3%
Denmark 43 37 28 22 6 27.3%
France 44 38 28 22 6 27.3%
Italy 45 39 28 22 6 27.3%
Croatia 46 27 28 23 5 21.7%
Germany 47 28 28 23 5 21.7%
Slovakia 48 29 28 23 5 21.7%
Latvia 49 19 28 24 4 16.7%
Malta 50 20 28 24 4 16.7%
Portugal 51 21 28 24 4 16.7%
Romania 52 22 28 24 4 16.7%
Iran 53 7 28 27 1 3.7%
Mauritius 54 3 28 28 0 0.0%
Uruguay 55 4 28 28 0 0.0%
Timor-Leste 56 190 27 12 15 125.0%
Honduras 57 155 27 15 12 80.0%
Guyana 58 137 27 16 11 68.8%
Namibia 59 138 27 16 11 68.8%
Uganda 60 104 27 18 9 50.0%
Bangladesh 61 85 27 19 8 42.1%
Colombia 62 86 27 19 8 42.1%
Myanmar 63 87 27 19 8 42.1%
Qatar 64 88 27 19 8 42.1%
Belarus 65 67 27 20 7 35.0%
Ukraine 66 68 27 20 7 35.0%
Hungary 67 52 27 21 6 28.6%
Slovenia 68 53 27 21 6 28.6%
Finland 69 40 27 22 5 22.7%
North Macedonia 70 30 27 23 4 17.4%
Poland 71 31 27 23 4 17.4%
Chad 72 139 26 16 10 62.5%
Fiji 73 140 26 16 10 62.5%
Nepal 74 141 26 16 10 62.5%
Palau 75 124 26 17 9 52.9%
Indonesia 76 105 26 18 8 44.4%
Lebanon 77 106 26 18 8 44.4%
Republic of Korea 78 69 26 20 6 30.0%
Samoa 79 54 26 21 5 23.8%
Sweden 80 41 26 22 4 18.2%
Cook Islands 81 32 26 23 3 13.0%
Lithuania 82 33 26 23 3 13.0%
Jordan 83 23 26 24 2 8.3%
Albania 84 15 26 25 1 4.0%
Occupied Palestinian 85 125 25 17 8 47.1%
Niue 86 107 25 18 7 38.9%
United States of America 87 108 25 18 7 38.9%
Kuwait 88 70 25 20 5 25.0%
Yemen 89 71 25 20 5 25.0%
Kazakhstan 90 55 25 21 4 19.0%
Mongolia 91 56 25 21 4 19.0%
Serbia 92 57 25 21 4 19.0%
Switzerland 93 58 25 21 4 19.0%
Sri Lanka 94 42 25 22 3 13.6%
Belgium 95 9 25 26 -1 -3.8%
Saint Lucia 96 156 24 15 9 60.0%
The Gambia 97 142 24 16 8 50.0%
Iraq 98 143 24 16 8 50.0%
Burkina Faso 99 126 24 17 7 41.2%
Bahrain 100 109 24 18 6 33.3%
Jamaica 101 110 24 18 6 33.3%
Peru 102 111 24 18 6 33.3%
China 103 89 24 19 5 26.3%
United Arab Emirates 104 90 24 19 5 26.3%
Kyrgyzstan 105 72 24 20 4 20.0%
Kenya 106 43 24 22 2 9.1%
Malaysia 107 34 24 23 1 4.3%
Antigua and Barbuda 108 170 23 14 9 64.3%
Solomon Islands 109 171 23 14 9 64.3%
Togo 110 172 23 14 9 64.3%
Azerbaijan 111 157 23 15 8 53.3%
Trinidad and Tobago 112 158 23 15 8 53.3%
Barbados 113 144 23 16 7 43.8%
Ghana 114 145 23 16 7 43.8%
Maldives 115 112 23 18 5 27.8%
Papua New Guinea 116 113 23 18 5 27.8%
Bolivia 117 91 23 19 4 21.1%
Congo 118 92 23 19 4 21.1%
Laos 119 93 23 19 4 21.1%
Venezuela 120 94 23 19 4 21.1%
Japan 121 73 23 20 3 15.0%
Montenegro 122 74 23 20 3 15.0%
Vanuatu 123 75 23 20 3 15.0%
Iceland 124 59 23 21 2 9.5%
Morocco 125 60 23 21 2 9.5%
Tunisia 126 61 23 21 2 9.5%
Tajikistan 127 159 22 15 7 46.7%
Kiribati 128 146 22 16 6 37.5%
Cameroon 129 127 22 17 5 29.4%
Armenia 130 114 22 18 4 22.2%
Benin 131 115 22 18 4 22.2%
Tuvalu 132 95 22 19 3 15.8%
Israel 133 62 22 21 1 4.8%
Bhutan 134 173 21 14 7 50.0%
Nauru 135 160 21 15 6 40.0%
Nigeria 136 161 21 15 6 40.0%
Afghanistan 137 147 21 16 5 31.3%
Micronesia 138 148 21 16 5 31.3%
Oman 139 149 21 16 5 31.3%
Paraguay 140 150 21 16 5 31.3%
Libya 141 128 21 17 4 23.5%
The Democratic Republic of the Congo 142 116 21 18 3 16.7%
Eswatini 143 117 21 18 3 16.7%
Bosnia and Herzegovina 144 76 21 20 1 5.0%
Niger 145 63 21 21 0 0.0%
Djibouti 146 44 21 22 -1 -4.5%
Nicaragua 147 184 20 13 7 53.8%
Ethiopia 148 174 20 14 6 42.9%
Gabon 149 175 20 14 6 42.9%
Burundi 150 162 20 15 5 33.3%
Mali 151 163 20 15 5 33.3%
Uzbekistan 152 164 20 15 5 33.3%
Sudan 153 129 20 17 3 17.6%
Botswana 154 118 20 18 2 11.1%
Mexico 155 119 20 18 2 11.1%
South Africa 156 120 20 18 2 11.1%
Marshall Islands 157 77 20 20 0 0.0%
The Syrian Arab Republic 158 78 20 20 0 0.0%
Andorra 159 185 19 13 6 46.2%
Lesotho 160 165 19 15 4 26.7%
Mozambique 161 130 19 17 2 11.8%
United Republic of Tanzania 162 131 19 17 2 11.8%
Zambia 163 132 19 17 2 11.8%
Algeria 164 121 19 18 1 5.6%
Cabo Verde 165 122 19 18 1 5.6%
Cuba 166 96 19 19 0 0.0%
Eritrea 167 79 19 20 -1 -5.0%
Guatemala 168 64 19 21 -2 -9.5%
Côte d'Ivoire 169 176 18 14 4 28.6%
Comoros 170 166 18 15 3 20.0%
Zimbabwe 171 151 18 16 2 12.5%
Dominican Republic 172 133 18 17 1 5.9%
Democratic People's Republic of Korea 173 177 17 14 3 21.4%
Mauritania 174 178 17 14 3 21.4%
Rwanda 175 179 17 14 3 21.4%
Grenada 176 167 17 15 2 13.3%
San Marino 177 168 17 15 2 13.3%
Bahamas 178 152 17 16 1 6.3%
Belize 179 134 17 17 0 0.0%
Guinea 180 135 17 17 0 0.0%
Liberia 181 186 16 13 3 23.1%
Sao Tome and Principe 182 180 16 14 2 14.3%
Angola 183 187 15 13 2 15.4%
Saint Vincent and the Grenadines 184 181 15 14 1 7.1%
Dominica 185 153 15 16 -1 -6.3%
Sierra Leone 186 191 14 12 2 16.7%
Saint Kitts and Nevis 187 182 14 14 0 0.0%
Central African Republic 188 183 14 14 0 0.0%
Guinea-Bissau 189 192 13 12 1 8.3%
Somalia 190 193 13 12 1 8.3%
Equatorial Guinea 191 188 13 13 0 0.0%
Haiti 192 189 13 13 0 0.0%
Malawi 193 169 13 15 -2 -13.3%
Monaco 194 194 12 12 0 0.0%
South Sudan 195 195 11 10 1 10.0%

*Rank is based on 2018 score and relative change to 2008 score

MPOWER rankings of all nations

The WHO regions reporting the highest levels of implementation in 2018 in mean country scores in order of ranking were (1) North America (27.0 points); (2) Europe & Central Asia (26.6 points); (3) East Asia & Pacific (25.4 points); South Asia (25.3 points); the Middle East & North Africa (24.3 points); Latin America & Caribbean (23.1 points) and Sub-Saharan Africa (20.1 points). The mean scores of countries according to national income levels are high-income (26.4 points), upper-middle-income (24.2 points), lower-middle-income (23.2 points), and low-income (19.3 points). MPOWER scoring changes by region appear in Figure 1, scoring changes by income level appear in Figure 2, and MPOWER rankings in 2018 appear in Figure 3.

Figure 1
Figure 1.MPOWER score and country income level.
Figure 2
Figure 2.MPOWER score and WHO regions.
Figure 3
Figure 3.MPOWER score and top 20 and bottom 20 countries.

The highest rates of implementation for the MPOWER variables in 2018 were (1) Warn (package) with a mean score of 3.86 out of a possible 5 points; (2) Enforce (advertising bans) with a mean score of 3.79 out of a possible 5 points; (3) Offer with a mean score of 3.70 out of a possible 5 points and (4) Raise with a mean score of 3.48 out of a possible 5 points. The lowest rates of implementation were (1) Warn (mass media) with a mean score of 2.84 out of a possible 5 points; (2) Protect with a mean score of 3.40 out of a possible 5 points; and (3) Monitor with a mean score of 2.81 out of a possible 4 points. These results can be found in Table 2.

Table 2.MPOWER element scoring change since 2008
MPOWER
2008
MPOWER
2018
Point change
Mean (S.D.) Mean (S.D.) Mean (S.D.) t p-value Relative change
All countries (n=195)
MONITOR 2.78 (1.04) 2.81 (1.10) 0.026 (0.96) 0.373 0.710 0.9%
PROTECT 2.58 (0.95) 3.40 (1.32) 0.815 (1.18) 9.663 <0.001 31.6%
OFFER help to quit 3.36 (0.79) 3.70 (0.85) 0.344 (0.75) 6.372 <0.001 10.2%
WARN - package 2.69 (0.91) 3.86 (1.23) 1.174 (1.07) 15.328 <0.001 43.7%
WARN - mass media 2.74 (1.35) 2.84 (1.37) 0.103 (1.82) 0.787 0.432 3.8%
ENFORCE ad bans 3.14 (1.08) 3.79 (1.06) 0.656 (1.01) 9.074 <0.001 20.9%
RAISE taxes 3.24 (1.08) 3.48 (1.10) 0.246 (0.81) 4.229 <0.001 7.6%
Most improved countries
(n=10)
MONITOR 2.60 (0.83) 3.10 (0.74) 0.50 (0.85) 1.86 0.096 19.2%
PROTECT 2.40 (0.52) 4.80 (0.42) 2.40 (0.52) 14.70 <0.001 100%
OFFER help to quit 3.10 (0.57) 4.10 (0.57) 1.00 (0.67) 4.74 0.001 32.3%
WARN- package 2.10 (0.32) 5.00 (0.00) 2.90 (0.32) 29.00 <0.001 138%
WARN- mass media 2.60 (1.08) 4.40 (0.97) 1.80 (1.48) 3.86 0.004 69.2%
ENFORCE ad bans 2.00 (0.00) 4.30 (0.48) 2.30 (0.48) 15.06 <0.001 115%
RAISE taxes 3.00 (1.05) 3.20 (0.63) 0.20 (0.63) 1.00 0.340 6.7%
Declining countries
(n=6)
MONITOR 3.00 (1.10) 2.00 (0.63) -1.00 (0.89) -2.74 0.041 -33.3%
PROTECT 3.00 (1.27) 2.67 (1.51) -0.33 (0.82) -1.00 0.360 -11.0%
OFFER help to quit 3.17 (1.17) 2.67 (1.03) -0.50 (0.55) -2.24 0.080 -15.8%
WARN - package 3.00 (1.27) 3.17 (1.47) 0.17 (0.41) 1.00 0.360 5.7%
WARN - mass media 2.17 (0.98) 2.17 (0.98) -- -- -- --
ENFORCE ad bans 3.33 (1.51) 3.33 (1.51) -- -- -- --
RAISE taxes 3.50 (1.05) 2.67 (1.63) -0.83 (0.75) -2.71 0.042 -23.7%

Note: Scores for “WARN - mass media” in 2008 were substituted with 2010 data due to the absence of 2008 data. The underlined showed the most and least improved/get worse

Changes from 2008 to 2018

National implementation

Twenty-three (23) countries recorded a minimum MPOWER scoring increase of at least 10 points between 2008 and 2018 (i.e., most improved scores), including Timor-Lest (15); Senegal (14); Costa-Rica, Pakistan, Seychelles, and Cambodia (13); El Salvador, Republic of Moldova, and Honduras (12); Brazil, Georgia, Russian Federation, Turkmenistan, Suriname, Guyana, and Namibia (11); and Turkey, Luxembourg, Argentina, Saudi Arabia, Chad, Fiji, and Nepal (10). Six (6) countries recorded a decline in MPOWER scores between 2008 and 2018 (i.e., least improved scores), including Guatemala and Malawi (-2) and Belgium, Djibouti, Dominica and Eritrea (-1). Thirteen (13) countries recorded no change in scores between 2008 and 2018, including Belize, Central African Republic, Cuba, Equatorial Guinea, Guinea, Haiti, Marshall Islands, Mauritius, Monaco, Niger, Saint Kitts, Syrian Arab Republic, and Uruguay. These results can be found in Table 3.

Table 3.Countries with notable MPOWER scoring change since 2008
Country MPOWER score 2018 MPOWER score 2008 Point change Relative change
Most improved (n=23)
Timor-Leste 27 12 15 125%
Senegal 30 16 14 88%
Cambodia 28 15 13 87%
Costa Rica 31 18 13 72%
Pakistan 31 18 13 72%
Seychelles 31 18 13 72%
Honduras 27 15 12 80%
El Salvador 30 18 12 67%
Republic of Moldova 30 18 12 67%
Guyana 27 16 11 69%
Namibia 27 16 11 69%
Suriname 28 11 11 65%
Russian Federation 29 18 11 61%
Turkmenistan 29 18 11 61%
Georgia 30 19 11 58%
Brazil 34 23 11 48%
Chad 26 16 10 63%
Fiji 26 16 10 63%
Nepal 26 16 10 63%
Argentina 29 19 10 53%
Saudi Arabia 29 19 10 53%
Luxembourg 30 20 10 50%
Turkey 34 24 10 42%
Declining score (n=6)
Malawi 13 15 -2 -13.0%
Guatemala 19 21 -2 -10.0%
Dominica 15 16 -1 -6.0%
Eritrea 19 20 -1 -5.0%
Djibouti 21 22 -1 -5.0%
Belgium 25 26 -1 -4.0%
No change (n=13)
Mauritius 28 28 0 0.0%
Uruguay 28 28 0 0.0%
Niger 21 21 0 0.0%
Marshall Islands 20 20 0 0.0%
The Syrian Arab Republic 20 20 0 0.0%
Cuba 19 19 0 0.0%
Belize 17 17 0 0.0%
Guinea 17 17 0 0.0%
Central African Republic 14 14 0 0.0%
Saint Kitts and Nevis 14 14 0 0.0%
Equatorial Guinea 13 13 0 0.0%
Haiti 13 13 0 0.0%
Monaco 12 12 0 0.0%

The mean point change rankings of WHO regions between 2008 and 2018 are (1) South Asia (7.25 points = 40.3% increase); (2) East Asia and Pacific (6.06 points = 31.3% increase); (3) Europe and Central Asia (5.51 points = 26.2% increase); (4) North America (5.50 points = 25.5% increase); (5) Latin America and Caribbean (5.30 points = 29.8% increase); (6) Middle East and North Africa (4.19 points = 20.9% increase) and (7) Sub-Saharan Africa (3.92 points = 24.3% increase). The mean point change rankings according to income level are (1) lower-middle income (5.7 points = 32% increase); (2) upper-middle income (5.3 points = 28% increase); (3) high income (5.2 points = 24% increase and (4) low income (3.6 points = 23% increase).

Repeated measure analysis showed that the estimated marginal means of MPOWER score has been increasing since 2008. This increase is observed across different levels of income and different WHO regions except for the bottom 20 countries in the 2018 MPOWER rankings. These low-performing countries reported declining scores after an initial increase between 2008 and 2012. However, paired test analysis revealed that the largest increase in MPOWER scoring occurred in the first reporting period following the introduction of the MPOWER measures in 2008. Figure 4 reveals a significant increase in MPOWER score in 2008-2010 (range, 3.5 in the Southeast Asia region to 1.15 in the bottom 20 countries). This increase declined sharply from 2010-2012 (ranging from 1.7 in the top 20 countries to 0.41 in low-income countries). The 2014-2016 and 2016-2018 reveal largely insignificant increases in MPOWER scoring (ranging from 1.25 in the top 20 countries to -0.75 in Southeast Asia) (Figures 4, panels A-C).

Figure 4
Figure 4.A: Trend in difference in mean MPOWER score by country income level. B: The difference in mean MPOWER score by WHO region. C: The difference in mean MPOWER score for top and bottom 20 countries.

Figure 5 shows projected dates for achieving full MPOWER implementation score stratified by countries’ income levels. At the current implementation rate, high- and middle-income countries are projected to achieve full MPOWER implementation by 2040, led by high-income countries, which are forecast to reach the 34-point target by 2036. The projections also reveal that low-income countries are not expected to achieve full MPOWER implementation in the foreseeable future. While these trends are encouraging for most countries, they suggest that full MPOWER implementation is unlikely in many low-income countries.

Figure 5
Figure 5.Estimated dates of full MPOWER implementation by country income level.

Implementation of MPOWER elements

The highest degree of implementation of MPOWER elements between 2008 and 2018 was Warn (packaging), with a 1.17-point increase, reflecting a 10-year improvement of 43.7%. The second highest increase was Protect, with a 0.82-point rise, representing a relative change of 31.6%. The third greatest improvement was 0.66 points for Enforce (advertising ban), reflecting a relative rise of 20.9%. The fourth highest change was 0.34 points for Offer, representing a relative increase of 10.2%. The lowest degree of MPOWER implementation was Monitor, with a relative 10-year increase of 0.9%, reflecting a 0.03-point increase. The second lowest improvement was Warn (mass media), reflecting a 0.10-point rise, or a relative change of 3.8%. The third lowest change was Raise, with a 0.25-point increase, representing a relative improvement of 7.6%. These results can be found in Table 2.

Impact of covariates

Several influential covariates were identified through selective analysis of health, social, political and economic indicators in the WHO Global Health Observatory and the Our World in Data online dataset repository. This study examined these indicators between the 20 best performing MPOWER countries and the 20 worst performing nations (Table 4). Covariates that appear to positively influence MPOWER implementation include lower cigarette affordability (P=0.03; t=-2.30), the overall tax score (P<0.001; t=4.67) the presence of national tobacco control objectives (P=0.001, X2=22.7), the human development index score (P<0.001; t=5.1), the national corruption index score (P<0.001; t=3.96), the political regime index score (P<0.001; t=5.76), and the national literacy rate (P=0.003; t=3.18). Covariates that did not influence MPOWER implementation included a government tobacco control agency (P=0.12; X2=4.28) and the number of tobacco control staff employed by the government (P=0.78; t=1.85).

Table 4.MPOWER scoring comparisons between highest 20 and lowest 20 performing countries
Highest 20
countries
Lowest 20
countries
Measurement
n % n % Chi-square P value
Income 12.93 0.005
Low-income country -- 9 45.0%
Middle-low income 4 20.0% 2 10.0%
Middle-high income 5 25.0% 5 25.0%
High-income country 11 55.0% 4 20.0%
WHO region 12.12 0.02
East Asia & Pacific 3 15.0% 1 5.0%
Europe & Central Asia 9 45.0% 2 10.0%
Latin America & Caribbean 5 25.0% 7 35.0%
South Asia 1 5.0% --
Sub-Sahara Africa 2 10.0% 10 50.0%
Middle East & North Africa -- --
North America -- --
Change in government tobacco control objectives 22.70 <0.001
Never had objectives 1 5.0% 9 45.0%
Always had objectives 17 85.0% 2 10.0%
Newly created objectives 2 10.0% 9 45.0%
National agency for tobacco control 2018 4.28 0.12
Yes 9 45.0% 4 20.0%
No 0 0.0% 2 10.0%
Not reported 11 55.5% 14 70.0%
Covariate Mean SD Mean SD t test P value
Human development index 2008 0.77 0.13 0.55 0.16 4.46 <0.001
Human development index 2016 0.80 0.12 0.57 0.15 5.10 <0.001
Per capita tobacco control budget 0.73 1.76 0.02 0.02* 0.55 0.59
Number of staff employed by national agency (last reported) 12.00 13.86 2.14 1.77§ 1.85 0.78
Affordability 2018 3.26 1.93 6.74 6.41 -2.30 0.03
Affordability 2008 2.63 1.61 7.62 8.06 -2.71 0.01
Corruption 2012 56.55 19.45 34.71 18.26 3.30 <0.001
Corruption 2018 57.05 19.11 32.50 17.72 3.96 <0.001
Literacy rate (last reported) 92.56 13.23 71.72 25.54 3.18 0.003
Political regime 2014 8.68 1.80 2.36 4.20 5.76 <0.001
Overall tax score 2018 2.64 1.13 1.06 0.36 4.67 <0.001

*data from 2 countries, §data from 7 countries

DISCUSSION

For the first time since MPOWER was launched in 2008, two countries achieved a perfect score of 34 in the 2018 MPOWER rankings: Brazil and Turkey. Notably, neither country is ranked as a high-income country, which should motivate middle-income countries and high-income countries to implement MPOWER fully. Of the 20 top performing countries in 2018, 10 were ranked as high-income, seven were rated as upper-middle income, 3 were lower-middle income, and none were low-income nations. Together, these countries represent 10.4% of the world population. This modest degree of high MPOWER implementation is concerning, considering the large number of countries (182) that have ratified the FCTC. Of the 20 countries with the lowest MPOWER scores in 2018, 9 were ranked as low-income, two were rated as low-middle income, 5 were high-middle income, and 4 were high-income countries.

Of the 23 countries that achieved a minimum 10-point increase between 2008 and 2018, 3 were high-income countries, 12 were upper-middle income countries, 7 were lower-middle income, and 1 was a low-income nation. Nineteen (19) middle-income countries were among the 23 most improved nations for MPOWER implementation between 2008 and 2018. All WHO regions realised 10-year improvements in MPOWER scores, with the greatest progress achieved by South Asia, East Asia & Pacific, and Europe & Central Asia (Figure 2). Although high-income countries had the highest MPOWER rankings in 2018, middle-income countries are the top performers in achieving the most improved 10-year scores. MPOWER scores improved among all income gradients. However, lower- and upper-middle-income nations achieved more relative progress than high- and low-income countries. Unfortunately, the gap in MPOWER implementation between low-income and non-low-income countries is growing wider over time, perhaps due to external influences on MPOWER scores, such as compromised human development, more oppressive government regimes, and higher rates of corruption. Given these challenges, more work is justified to assist low-income countries with MPOWER implementation.

Regarding the 10-year implementation of MPOWER elements, Warn (package) was by far the most well-implemented policy measure with a 15.3 point scoring increase reflecting a relative rise of 44%, followed by Protect (smoking ban) (9.7 points = 32% increase) with and Enforce (advertising ban) (9.1 points = 21% increase). The most disappointing results were Monitor with a 1% increase, Warn (mass media) with a 4% increase and Raise (taxes) with an 8% increase in implementation over ten years. Tobacco taxes are the single most effective means of reducing tobacco use. This vital tobacco control measure’s relatively low implementation rate is disturbing and warrants further attention.

Covariates

The relationship between MPOWER and selected covariates was somewhat inconsistent and counter-intuitive. For example, tobacco control objectives and cigarette affordability are positively associated with MPOWER implementation, but the existence of a government tobacco control agency and government funding for tobacco control is not correlated. Similarly, socio-economic indicators such as the human development index, the national corruption index and the political regime index are positively associated with MPOWER implementation. High- and middle-income countries report higher rates of MPOWER implementation, and low-income countries report lower implementation rates. Further analysis of country demographics and social, political, and economic indicators and their relationship to MPOWER implementation is warranted.

Limitations

The MPOWER implementation results were self-reported to the WHO by participating nations and were validated by WHO regional offices in consultation with tobacco control experts in each country.8,9 The scope of this study did not allow for any additional auditing or scrutiny of the national self-reports. Secondly, the MPOWER numerical scoring tables were obtained from the WHO Global Health Observatory. The numerical data does not appear in the MPOWER biannual reports, and there is potential for inconsistencies. Thirdly, MPOWER does not address all the possible influences on tobacco control and smoking behaviour, such as tobacco industry interference, which has been identified as the largest barrier to implementing FCTC globally.32 Article 5.3 of the FCTC addresses tobacco industry interference, and another independent global index measures national adherence to this critical indicator.33 In addition, MPOWER does not address any supply-side tobacco control measures nor the four established elements of the tobacco marketing mix, specifically place (point of sale) and product (design and production).34 Finally, the authors selected the covariates subjectively based on their perceived potential impact on MPOWER scores.

CONCLUSIONS

Twenty-three (23) countries achieved MPOWER scoring improvements of at least 10 points out of a possible 34 between 2008 and 2018. Twenty countries achieved the highest MPOWER rankings in 2019, providing the best models for other countries to follow. Based on this study’s projections, high- and middle-income countries will achieve full MPOWER implementation by 2040 at current adoption rates. Although MPOWER rates are increasing among low-income countries, the projected date of full implementation is uncertain. The approval of a new global strategy to accelerate FCTC implementation at the 8th Conference of the Parties held in Geneva in 2018 holds promise for further progress, especially if it is adequately resourced.35

The relative ranking of nations’ implementation of WHO MPOWER tobacco control measures provides a global performance index to benchmark, monitor, measure, compare and stimulate MPOWER implementation and to promote tobacco use reduction among all countries.

Although this analysis is not exhaustive, it helps to identify common characteristics of countries that have achieved high levels of MPOWER implementation. The analysis also sheds light on independent covariates that influence MPOWER implementation. We encourage others to conduct further analyses. The increasing availability of public domain datasets provides further opportunities to enhance the understanding of MPOWER and tobacco control implementation.


Funding

None.

Authorship contributions

L.H. conceived the study and wrote the draft manuscript based on previous publications by G.H. G.H. assisted with study design and writing. F.H. performed data analysis and assisted with study design and writing.

Competing interests

The authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available upon request from the corresponding author) and declare no conflicts of interest.

Correspondence to:

Les Hagen, ASH Canada, PO Box 52117 RPO Garneau, Edmonton, Alberta, Canada T6G 2T5.