| Literature DB >> 22944364 |
Amanda C Jones1, Robert Geneau.
Abstract
INTRODUCTION: Action is urgently needed to curb the rising rates of non-communicable diseases (NCDs) in low- and middle-income countries (LMICs) and reduce the resulting social and economic burdens. There is global evidence about the most cost-effective interventions for addressing the main NCD risk factors such as tobacco use, unhealthy diets, physical inactivity, and alcohol misuse. However, it is unknown how much research is focused on informing the local adoption and implementation of these interventions.Entities:
Mesh:
Year: 2012 PMID: 22944364 PMCID: PMC3427597 DOI: 10.3402/gha.v5i0.18847
Source DB: PubMed Journal: Glob Health Action ISSN: 1654-9880 Impact factor: 2.640
Non-communicable disease interventions identified as ‘priority interventions’ and examined in bibliometric analysis
| 1. Tobacco control |
| Tobacco price increases |
| Legislation of health warnings |
| Work and public places smoking bans |
| Bans on tobacco advertising and promotion |
| 2. Healthy diets and physical activity |
| Food reformulation to reduce salt content |
| Mass-media campaigns to reduce salt consumption |
| Food reformulation to exclude saturated and trans fats |
| Food labelling |
| Restrictions on marketing of unhealthy foods and beverages |
| Fiscal measures that increase the price of unhealthy foods or decrease the price of healthy foods |
| Modification of built environment to promote physical activity |
| 3. Reducing harmful alcohol use |
| Alcohol price increases |
| Restricting availability of alcohol (minimum purchase age, restricting locations and hours, government monopoly) |
| Legislation to ban alcohol marketing and sponsorship |
Coding categories for included articles
| Intervention by risk factor: the risk factor(s) that the article focused on | Three options: tobacco control, healthy diets and physical activity, and reducing harmful alcohol use If the article focused on more than one risk factor, article was coded for all applicable options |
| Country of focus: the low- or middle-income country(ies) that the research publication focused on | If the article focused on more than one country (e.g. two LMICs or one LMIC and one HIC), article was coded as ‘Multiple Countries’ |
| Region of focus: the region where the country of focus is found | Regional classification is determined by the World Bank's country classification list If the article was a ‘Multiple Countries’ study and all the countries were in the same region, it was coded for that region. If the multiple countries were in more than one region or and the countries are in different regions, the article was coded as ‘Multiple Regions.’ However, a ‘Multiple Countries’ study where all the countries are in the same region was coded as that region There were seven regional groups: East Asia & Pacific, Europe & Central Asia, Latin America & Caribbean, Middle East & North Africa, South Asia, Sub-Saharan Africa and Multiple Regions |
| First author's country: the country of the first author's institutional affiliation | Could be any country in the world Each country was designated as either a low- or middle-income country (LMIC) or a high-income country (HIC), according to the World Bank's listing, permitting authors to be coded as either an ‘LMIC author’ or 'HIC author’ |
Fig. 1Number of included research articles published between 2000 and 2011. Each research article addressed one or more non-communicable disease priority intervention and focused on one or more low- or middle-income country. Results include articles published as of February 13, 2012.
Fig. 2Percent of articles set in a low- or middle-income country within a particular geographical region. Of the total number of included research articles, the percentage of them (and number) focusing on one or more low- or middle-income country within a particular geographical region. Articles focusing on more than one region are classified as ‘Multiple Regions.’
Yearly articles for each intervention group as a percentage of total number of included articles
| Year | Percent of articles for tobacco control ( | Percent of articles for healthy diets and physical activity ( | Percent of articles for reducing harmful alcohol use ( |
|---|---|---|---|
| 2000 | 1.3 (7) | 0.8 (4) | 2.3 (12) |
| 2001 | 1.1 (6) | 0.2 (1) | 0.6 (3) |
| 2002 | 2.1 (11) | 1.1 (6) | 1.0 (5) |
| 2003 | 2.3 (12) | 0.8 (4) | 0.6 (3) |
| 2004 | 4.4 (23) | 1.3 (7) | 1.0 (5) |
| 2005 | 3.8 (20) | 1.0 (5) | 1.3 (7) |
| 2006 | 5.5 (29) | 2.3 (12) | 1.3 (7) |
| 2007 | 5.7 (30) | 2.7 (14) | 2.5 (13) |
| 2008 | 8.4 (44) | 2.7 (14) | 1.0 (5) |
| 2009 | 6.9 (36) | 3.0 (16) | 1.1 (6) |
| 2010 | 14.5 (76) | 4.0 (21) | 3.2 (17) |
| 2011 | 13.5 (71) | 5.0 (26) | 2.1 (11) |
| Grand total | 69.5 (365) | 24.9 (130) | 18.0 (94) |
Fig. 3Percent of articles on each intervention by risk factor for geographical regions. Of the total number of included research articles, the percentage of them (and number) addressing a non-communicable disease priority intervention. Interventions are grouped in three categories: tobacco control, healthy diets and physical activity, and reducing harmful alcohol use. Articles are organised by geographical region of focus. An article may be classified in more than one intervention type. Articles focusing on countries from more than one region are classified as ‘Multiple Regions.’
Yearly articles by country income classification for each article's first author country of institutional affiliation
| Year | Percent of articles with first author high-income country institutional affiliation ( | Percent of articles with first author low- or middle-income country institutional affiliation ( |
|---|---|---|
| 2000 | 3.0 (16) | 0.8 (4) |
| 2001 | 0.6 (3) | 0.8 (4) |
| 2002 | 2.3 (12) | 1.7 (9) |
| 2003 | 2.5 (13) | 0.6 (3) |
| 2004 | 4.4 (23) | 1.7 (9) |
| 2005 | 2.7 (14) | 2.9 (15) |
| 2006 | 4.0 (21) | 3.4 (18) |
| 2007 | 5.9 (31) | 3.4 (18) |
| 2008 | 5.5 (29) | 5.3 (28) |
| 2009 | 4.2 (22) | 6.1 (32) |
| 2010 | 8.2 (43) | 11.8 (62) |
| 2011 | 8.0 (42) | 10.3 (54) |
| Grand total | 51.2 (269) | 48.8 (256) |
Annexe 1The number of included articles by first author's country of institutional affiliation. Articles are grouped by which country the first author's institutional affiliation lists. Countries are organised by income classification (high-income country affiliation or low- or middle-income country affiliation) and then alphabetically.
Fig. 4Comparison of country income classification for first authors’ countries of institutional affiliation. For each geographical region of focus, a comparison of the percent of first authors who have an institutional affiliation in a low- or middle-income country versus the percent of first authors with a high-income country institutional affiliation. The number of articles associated with each region is listed.