Multiple risk factor interventions for primary prevention of cardiovascular disease in low- and middle-income countries

  • Protocol
  • Intervention



This is the protocol for a review and there is no abstract. The objectives are as follows:

To determine the effectiveness of multiple risk factor interventions (with or without pharmacological treatment) aimed at modifying major cardiovascular risk factors for the primary prevention of cardiovascular disease in low- and middle-income countries (LMICs).


Description of the condition

Non-communicable diseases, also known as chronic diseases, are not passed from person to person; they are of long duration and generally slow progression (Hunter 2013; WHO 2014). The four main types of non-communicable disease are cardiovascular disease, cancer, chronic respiratory disease and diabetes (Hunter 2013; WHO 2014). In many low- and middle-income countries (LMICs) the morbidity and mortality associated with non-communicable diseases have grown exponentially over recent years (WHO 2005; WHO 2011). It is estimated that about 80% of non-communicable disease deaths occur in LMICs, which is a reflection of both the size of this population and epidemiological changes (WHO 2005; WHO 2011). In 2010, it was estimated that more than nine million of all deaths attributed to non-communicable diseases occurred before the age of 60; 90% of these 'premature' deaths occurred in low- and middle-income countries (Lim 2012). LMICs are now experiencing epidemiological transition, the change from a burden of infectious diseases to chronic diseases (Omran 1971), due to dramatic changes in diet and lifestyle. The epidemiological transition in these regions is compressed into a shorter time frame than that experienced historically by high-income countries (Miranda 2008). Urbanisation and changing behaviour practices, such as sedentary lifestyles and consumption of diets high in saturated fat, salt and sugar, are increasingly cited as the main drivers for this epidemic in LMICs (BeLue 2009; Miranda 2008; WHO 2011). In addition, LMICs are not only dealing with the emerging burden of non-communicable diseases, but also the current burden of infectious diseases (Perel 2006; Reddy 2004; Yusuf 2001a; Yusuf 2001b).

Cardiovascular diseases account for most non-communicable disease deaths, or 17.3 million people annually, followed by cancers (7.6 million), respiratory diseases (4.2 million) and diabetes (1.3 million) (Lim 2012). It is estimated that these four groups of diseases account for around 80% of all non-communicable disease deaths and they share four risk factors: tobacco use, physical inactivity, the harmful use of alcohol and unhealthy diets (Ezzati 2013; Lim 2012). Cardiovascular diseases are a group of disorders of the heart and blood vessels and they include: coronary heart disease (disease of the blood vessels supplying the heart muscle); cerebrovascular disease (disease of the blood vessels supplying the brain); peripheral arterial disease (disease of the blood vessels supplying the arms and legs); rheumatic heart disease (damage to the heart muscle and heart valves from rheumatic fever, caused by streptococcal bacteria); congenital heart disease (malformations of the heart structure existing at birth); and deep vein thrombosis and pulmonary embolism (blood clots in the leg veins, which can dislodge and move to the heart and lungs). People in LMICs are more exposed to cardiovascular risk factors (such as tobacco), often do not have the benefit of the prevention programmes available to people in high-income countries and have less access to effective and equitable healthcare services that respond to their needs (including early detection services) (WHO 2014b).

Description of the intervention

Multiple risk factor interventions (health promotion activities) are defined as interventions that address more than one cardiovascular disease risk factor at the same time, in addition to, or instead of, pharmacological treatments, in order to modify major cardiovascular risk factors. The components of multiple risk factor interventions include, but are not limited to, the following: (a) dietary advice to modify the individual's eating habits in order to reduce the percentage of calories from saturated fats, decrease the dietary cholesterol intake and increase the percentage of calories from polyunsaturated fats; (b) reducing harmful alcohol intake; (c) advice on the cessation of cigarette smoking; (d) advice on increasing daily physical activity; (e) reducing body weight; and (f) stepped care treatment of hypertension (Benfari 1981; Davey 2005; Kornitzer 1985). Since the incidence of cardiovascular disease is mainly explained by the presence of modifiable risk factors (blood lipid levels, blood pressure and cigarette smoking), reducing these risk factors through health promotion that focuses on lifestyles has been suggested as a logical way to prevent cardiovascular disease (Ebrahim 2011).

Therapeutic lifestyle modification, including increasing physical activity, changing eating habits and eliminating addictions, has been seen as a cornerstone of therapy for managing patients with metabolic syndrome (Marquez-Celedonio 2009), a clinical entity characterised by a constellation of metabolically relevant abnormalities and cardiovascular risk factors, including obesity, insulin resistance/glucose intolerance, dyslipidaemia and hypertension (Grundy 2005; Magkos 2009). Several intervention trials have reported the effects of lifestyle intervention programmes among high-risk populations (Ebrahim 2011; Mattila 2003; Muto 2001; Nilsson 2001). Some studies have recently shown a 58% decrease in the incidence of diabetes in individuals with impaired glucose tolerance (Knowler 2002; Tuomilehto 2001). Others have reported the beneficial effects of lifestyle modification on blood pressure control (Appel 2003; Appel 2003a; Elmer 2006).

Lifestyle modification has an important role to play in the lives of hypertensive and non-hypertensive individuals (Cakir 2006). In hypertensive individuals, it can serve as initial treatment before the start of drug therapy and as an adjunct to medication in persons already on drug therapy (Appel 2003a; JNC-VII 2003; Svetkey 2005; Vestfold Heartcare Study Group 2003). Lifestyle modification has been found to improve and optimise glycaemic control (Beyazit 2011). It has been documented that for optimal diabetes control outcomes, daily self management, including diet, exercise and regular self monitoring of blood glucose, is required (Beyazit 2011). Therapeutic lifestyle interventions have been found to be at least as effective as pharmacotherapies (Gillies 2007), at little cost and with minimum risk (Appel 1997). In contrast to most pharmacotherapies, lifestyle modifications can also prevent or control other chronic conditions (Knowler 2002; Stamler 1989). However, it has been suggested that in order for therapeutic lifestyle modification to be effective, it is important to pay attention not only to one single cardiovascular risk factor but to several factors simultaneously (Tuomilehto 2011). Therefore, it is generally recommended that lifestyle modifications should be implemented as a group (JNC-VII 2003).

How the intervention might work

The majority of the models of health behaviour change that are currently used as a basis for multiple risk factor interventions for preventing cardiovascular disease are derived from traditional cognitive theory (Bandura 1977a). They include the health belief model (Maimen 1974), health promotion model (Pender 1988), theory of reasoned action (Ajzen 1980; Ajzen 1985; Ajzen 1991), theory of planned behaviour (Ajzen 1980; Ajzen 1985; Ajzen 1991), self efficacy theory (Bandura 1977), and stages of change model (Norcross 2011; Prochaska 1979; Prochaska 1983). The theory of planned behaviour proposes that a person's intention to perform a behaviour is the immediate determinant of that behaviour as it reflects the level of motivation a person is willing to exert to perform the behaviour (Ajzen 1991). Another widely applied cognitive model is the stages of change model (also referred to as the transtheoretical model) (Chouinard 2007; Mochari-Greenberger 2010; Salmela 2009). The transtheoretical model sub-divides individuals into five categories (Norcross 2011; Prochaska 1979; Prochaska 1983); these represent different milestones or 'levels of motivational readiness' along a continuum of behaviour change (Heimlich 2008). These stages are: (i) pre-contemplation (the individual is unaware of the problem and there is no intention to change behaviour in the foreseeable future); (ii) contemplation (the individual is aware of the problem and there is a serious consideration of change in behaviour); (iii) preparation (the individual is willing to take action); (iv) actionable (the individual modifies their behaviour, experiences and/or environment in order to overcome the problem); and (v) maintenance (the individual works to prevent relapse and consolidate gains).

Joshi and colleagues conducted a cluster-randomised trial in rural Andhra Pradesh to develop, implement and evaluate two cardiovascular disease prevention strategies (Chow 2009; Joshi 2012). The health promotion intervention included posters, street theatre, rallies and community presentations designed to increase the knowledge of the adult population about stopping tobacco use, heart-healthy eating and physical activity (Chow 2009; Joshi 2012). The main aim of the clinical intervention was to increase the identification of people at high risk of cardiovascular events, who could benefit from proven preventive pharmacotherapies (Chow 2009; Joshi 2012). The trial found no detectable effect of the health promotion interventions on the primary outcome of knowledge about six lifestyle factors affecting cardiovascular disease risk or on either systolic or diastolic blood pressures (Joshi 2012).

The Isfahan Healthy Heart Program (IHHP) is a comprehensive, integrated, community-based programme for cardiovascular disease prevention and control, aiming to reduce cardiovascular disease risk factors and improve cardiovascular health behaviour among Iranians (Sarraf-Zadegan 2003). The IHHP advocated prevention and control of high blood pressure and diabetes, healthy eating patterns to lower cholesterol, non-smoking and regular physical activity (Sarraf-Zadegan 2003). Sarraf-Zadegan and colleagues reported that the prevalence of abdominal obesity, hypertension, hypercholesterolaemia and hypertriglyceridaemia decreased significantly in the intervention areas compared with reference areas in both sexes (Sarrafzadegan 2013).

Jeemon and colleagues examined the impact of a comprehensive cardiovascular risk reduction programme on risk factor clustering associated with elevated blood pressure using a sentinel surveillance study in an Indian industrial population (SSIP), using a population-based approach (Jeemon 2012; Prabhakaran 2009; Reddy 2006). The components of the SSIP intervention included: 1) workplace-organised individual and group counselling sessions, health displays, cooking competitions and dance classes; 2) posters, banners, handouts, booklets and real-time videos with simple, captivating messages translated into seven Indian languages for health education; 3) initiation of changes by management and employees (e.g. increasing salads and decreasing salty and fried foods on canteen menus, and enforcing smoking bans); and 4) identifying high-risk individuals through screening who were referred to the on-site health facilities for risk management (individual and group counselling was also offered). The results of the SSIP programme showed that a comprehensive cardiovascular disease risk reduction programme significantly reduced the cardiovascular risk burden (Jeemon 2012).

Why it is important to do this review

There is a comprehensive Cochrane review that has examined the effectiveness of multiple risk factor interventions in all settings, predominantly high-income countries (Ebrahim 2011). Ebrahim 2011 pooled data from 14 trials that randomised 139,256 participants and reported clinical event endpoints. They found that counselling and education interventions designed to change health behaviours do not reduce total or coronary heart disease mortality or clinical events in general populations, but they may be effective in reducing mortality in high-risk hypertensive and diabetic populations (Ebrahim 2011). The Ebrahim review, in which most studies were based in developed countries, concluded that health promotion interventions have limited use in general populations. Caution is needed in generalising evidence from high-income countries to the current LMIC context because of the differences in settings and the nature of the communities, as well as the targeted population.

One vital element in improving this situation is a comprehensive and relevant evidence base, which would equip LMICs to take informed action. To the best of our knowledge, no systematic review has been undertaken that specifically examines the effectiveness of multiple risk factor interventions for preventing cardiovascular disease in LMICs; such a review is therefore needed.


To determine the effectiveness of multiple risk factor interventions (with or without pharmacological treatment) aimed at modifying major cardiovascular risk factors for the primary prevention of cardiovascular disease in low- and middle-income countries (LMICs).


Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials (RCTs) of at least six months duration of follow-up conducted in low- and middle-income countries. The trials' randomisation units could either be individuals or clusters (such as family, workplace site). We will only include trials conducted in LMICs as defined in the World Bank Country Income Groups at the time of the trial's data collection (World Bank 2014).

Types of participants

We will include adult populations (≥ 18 years). We will include workforce populations, population-based studies that include high-risk groups (such as hypertension, obesity, hyperlipidaemia, type 2 diabetes or a combination of these) or individuals without high risk of developing cardiovascular disease.

We will exclude trials where there is evidence that more than 25% of the participants have diagnosed cardiovascular disease at baseline.

Types of interventions

Health promotion interventions to achieve behaviour change (i.e. smoking cessation, dietary advice, increasing activity levels), with or without pharmacological treatments, which aim to alter more than one cardiovascular risk factor (i.e. diet, blood pressure, smoking, total blood cholesterol or physical activity).

Comparison: no intervention control.

Types of outcome measures

Primary outcomes
  1. Combined fatal and non-fatal cardiovascular disease events (including myocardial infarction, unstable angina, need for coronary bypass grafting or percutaneous coronary intervention, stroke, peripheral artery disease).

  2. Adverse events.

Secondary outcomes
  1. All cause-mortality.

  2. Changes in cardiovascular disease risk factors (blood pressure, lipid levels, diabetes, obesity).

  3. Changes in health knowledge, attitudes and intention.

Search methods for identification of studies

Electronic searches

We will identify trials through systematic searches of the following bibliographic databases:

  • Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library;

  • MEDLINE (Ovid);

  • EMBASE (Ovid);

  • Science Citation Index Expanded (SCI-EXPANDED);

  • Conference Proceedings Citation Index – Science (CPCI-S) on Web of Science (Thomson Reuters);

  • DARE, HTA, EED in The Cochrane Library;

  • LILACS (Bireme);

  • Global Health (OVID); and

  • ELDIS (

We will adapt the preliminary search strategy for MEDLINE (Ovid) for use in the other databases (Appendix 1). We will apply the Cochrane sensitivity-maximising RCT filter to the MEDLINE (Ovid) strategy and adaptations of it to the other databases (except CENTRAL) (Lefebvre 2011).

We will also conduct a search of ( and the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal (

We will search all databases from their inception to the present. We will impose no restriction on language of publication.

Searching other resources

We will check the reference lists of all primary studies and review articles for additional references.

Data collection and analysis

Selection of studies

Two authors (OAU and LH) will independently screen the titles and abstracts of all the potential studies we identify as a result of the search and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. If there are any disagreements, we will ask a third author to arbitrate (KR). We will retrieve the full-text study reports/publications and two authors (OAU and LH) will independently screen these to identify studies for inclusion. We will identify and record reasons for the exclusion of ineligible studies. We will resolve any disagreements through discussion or, if required, we will consult a third author (KR). We will identify and exclude duplicates and collate multiple reports of the same study, so that each study rather than each report is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table.

Data extraction and management

We will use a data collection form for study characteristics and outcome data, which has been piloted on at least one study in the review. One author (OAU) will extract study characteristics from the included studies. We will extract the following characteristics.

  1. Methods: study design, total duration of study, details of any 'run-in' period, number of study centres and location, study setting, withdrawals and date of study.

  2. Participants: number, mean age, age range, gender, severity of condition, diagnostic criteria, baseline measures of physiological functioning (e.g. cardiovascular function, blood pressure, body mass index, blood glucose, HbA1C, smoking history), inclusion and exclusion criteria.

  3. Interventions: intervention, comparison, concomitant medications and excluded medications.

  4. Outcomes: primary and secondary outcomes specified and collected, and time points reported.

  5. Notes: funding for trial and notable conflicts of interest of trial authors.

Two authors (OAU and LH) will independently extract outcome data from the included studies. We will note in the 'Characteristics of included studies' table if outcome data were not reported in a usable way. We will resolve disagreements by consensus or by involving a third author (LH). One author (OAU) will transfer data into the Review Manager software (RevMan 2012). We will double-check that data are entered correctly by comparing the data presented in the systematic review with the study reports. A second author (LH) will spot-check study characteristics for accuracy against the trial report.

Assessment of risk of bias in included studies

Two authors (OAU and LH) will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreements by discussion or by involving another author (KR). We will assess the risk of bias according to the following domains.

  1. Random sequence generation.

  2. Allocation concealment.

  3. Blinding of participants and personnel.

  4. Blinding of outcome assessment.

  5. Incomplete outcome data.

  6. Selective outcome reporting.

  7. Other bias.

We will grade each potential source of bias as high, low or unclear and provide a quote from the study report together with a justification for our judgement in the 'Risk of bias' table. We will summarise the 'Risk of bias' judgements across different studies for each of the domains listed.

For cluster-randomised trials, we will assess the following cluster-specific risks of bias as outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

  1. Recruitment bias.

  2. Baseline imbalance.

  3. Loss of clusters.

  4. Incorrect analysis.

  5. Comparability with individually randomised trials.

When considering treatment effects, we will take into account the risk of bias of the studies that contribute to that outcome.

Assessment of bias in conducting the systematic review

We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

We will use Review Manager 5 to manage the data and to conduct the analysis. We will report dichotomous outcomes as risk ratios (RR) with 95% confidence intervals (CI). For continuous outcomes, we will calculate mean differences (MDs) with 95% CI when the studies use the same scale and standardised mean differences (SMD) with 95% CI when the studies use different scales.

Unit of analysis issues

The unit of analysis in meta-analysis will be individual participants. If the participant is not the unit of randomisation, such as is the case in cluster-randomised trials, we will make adjustments for clustering following the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Where multiple trial arms are reported in a single trial, we will only include the relevant arms.

Dealing with missing data

We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when a study is identified as an abstract only). Where this is not possible and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis.

Assessment of heterogeneity

We will use the I2 statistic to measure heterogeneity among the trials in each analysis. If we identify substantial heterogeneity (I2 value greater than 50%, i.e. more than 50% of the variation is due to heterogeneity rather than chance (Schroll 2011)), we will report it and explore possible causes by prespecified subgroup analysis.

Assessment of reporting biases

If we are able to pool more than 10 trials, we will create and examine a funnel plot to explore possible small study biases for the primary outcomes.

Data synthesis

We will summarise and analyse all eligible studies in Review Manager 5. Two authors will extract the data (OU and LH); the first author will enter all data and the second author will recheck all entries. We will resolve disagreements by discussion. We will undertake meta-analyses only where this is meaningful, i.e. if the treatments, participants and the underlying clinical question are similar enough for pooling to make sense. We will combine the data using a random-effects model, due to anticipated heterogeneity that may result from the differences in methodology and study settings. Where the rating scales used in the studies have a reasonably large number of categories (more than 10) we will treat the data as continuous variables arising from a normal distribution. We will use the MD when the pooled studies use the same rating scale or test, and the SMD, the absolute mean difference divided by the standard deviation, when they use different rating scales or tests. When the rating scales used are fewer than 10 and more than two, we will concatenate the data into two categories that best represent the contrasting states of interest and treat the outcome measure as binary. We will express study results for dichotomous data as RR and 95% CI. We will express time-to-event outcomes or generic inverse variance outcomes, such as survival time and time to development of cardiovascular disease, as the log hazard ratio and 95% CI.

When studies cannot be combined for meta-analysis due to diversity of interventions, we will conduct narrative syntheses and display the results of individual studies graphically to enable a more succinct summary of the evidence. We will also narratively describe skewed data reported as medians and interquartile ranges.

Subgroup analysis and investigation of heterogeneity

The following subgroups are planned.

  • Evidence of prescribed drug treatment (prescribed medication during trial and no prescribed medication or drug treatment not stated).

  • Low-income countries compared with low-middle-income countries.

  • Co-morbidity (diabetes, hypertension, obesity, no co-morbidity).

  • Age.

  • Sex.

We will use sensitivity analysis to explore heterogeneity.

  • Method of randomisation (clustered, clustered analyses as individual, individual).

  • Age of trial (publication year: before 2000 versus after 2000).

We will use meta-regression methods to examine the effects of baseline mean values for age, sex and blood pressure, if sufficiently reported.

Sensitivity analysis

We will carry out sensitivity analyses by excluding studies of low methodological quality. We will create funnel plots and undertake tests of asymmetry to assess possible publication bias (Egger 1997).

'Summary of findings' table

We will assess the quality of the evidence for the primary outcomes using the GRADE approach (Guyatt 2008), and present the results in 'Summary of findings' tables. The GRADE system considers 'quality' to be a judgement of the extent to which we can be confident that the estimates of effect are correct. We will judge the level of 'quality' on a four-point scale:

  1. High quality: further research is very unlikely to change our confidence in the estimate of effect.

  2. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.

  3. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.

  4. Very low quality: we are very uncertain about the estimate.

We will initially grade the evidence from the included RCTs as high and downgrade it by either one, two or three levels after full consideration of any limitations in the design of the studies, the directness (or applicability) of the evidence, the consistency and precision of the results, and the possibility of publication bias.




Appendix 1. MEDLINE search strategy

1. exp Cardiovascular Diseases/
2. cardio*.tw.
3. cardia*.tw.
4. heart*.tw.
5. coronary*.tw.
6. angina*.tw.
7. ventric*.tw.
8. myocard*.tw.
9. pericard*.tw.
10. isch?em*.tw.
11. emboli*.tw.
12. arrhythmi*.tw.
13. thrombo*.tw.
14. atrial fibrillat*.tw.
15. tachycardi*.tw.
16. endocardi*.tw.
17. (sick adj sinus).tw.
18. exp Stroke/
19. (stroke or stokes).tw.
20. cerebrovasc*.tw.
21. cerebral
23. (brain adj2 accident*).tw.
24. ((brain* or cerebral or lacunar) adj2 infarct*).tw.
25. exp Hypertension/
26. hypertensi*.tw.
27. peripheral arter* disease*.tw.
28. ((high or increased or elevated) adj2 blood pressure).tw.
29. exp Hyperlipidemias/
30. hyperlipid*.tw.
31. hyperlip?emia*.tw.
32. hypercholesterol*.tw.
33. hypercholester?emia*.tw.
34. hyperlipoprotein?emia*.tw.
35. hypertriglycerid?emia*.tw.
36. exp Arteriosclerosis/
37. exp Cholesterol/
39. Blood Pressure/
40. blood
41. multiple risk factor*.tw.
42. or/1-41
43. exp Health Promotion/
44. exp Health Education/
45. exp Health Behavior/
46. exp Counseling/
47. Primary Prevention/
48. (multifactor* adj5 (interven* or prevent*)).tw.
49. ((lifestyle or life-style or behavio?r*) adj3 (interven* or educat* or advice* or alter* or change* or inform*)).tw.
50. (primary adj3 prevent*).tw.
51. (risk factor* adj3 (reduc* or manage* or managing or interven* or program*)).tw.
52. (educat* adj3 (program* or patient*)).tw.
53. ((health* or wellness or weight or diet* or smok*) adj2 (promot* or program* or campaign* or advic* or educat*)).tw.
54. (nonpharmacologic* or non-pharmacologic*).tw.
55. ((lifestyle or life style or life-style or behavio?r* or risk factor*) adj3 modif*).tw.
56. or/43-55
57. 42 and 56
58. randomized controlled
59. controlled clinical
60. randomized.ab.
61. placebo.ab.
62. drug therapy.fs.
63. randomly.ab.
64. trial.ab.
65. groups.ab.
66. 58 or 59 or 60 or 61 or 62 or 63 or 64 or 65
67. exp animals/ not
68. 66 not 67
69. 57 and 68
70. Developing,kf.
71. ((developing or less* developed or under developed or underdeveloped or middle income or low* income or underserved or under served or deprived or poor*) adj (countr* or nation? or population? or world)).ti,ab.
72. ((developing or less* developed or under developed or underdeveloped or middle income or low* income) adj (economy or economies)).ti,ab.
73. (low* adj (gdp or gnp or gross domestic or gross national)).ti,ab.
74. (low adj3 middle adj3 countr*).ti,ab.
75. (lmic or lmics or third world or lami countr*).ti,ab.
76. transitional countr*.ti,ab.
77. Cambodia/
78. (cambodia* or Kampuchea).cp,in,jw,mp.
79. "Democratic People's Republic of Korea"/
80. (north korea* or (democratic people* republic adj2 korea)).cp,in,jw,mp.
81. Myanmar/
82. (myanmar or burma or burmese).cp,in,jw,mp.
83. Fiji/
84. fiji*.cp,in,jw,mp.
85. Indonesia/
86. indonesia*.cp,in,jw,mp.
87. Micronesia/
88. (Micronesia* or Kiribati).cp,in,jw,mp.
89. Laos/
90. (laos or (lao adj1 democratic republic) or (lao adj2 people) or marshall island*).cp,in,jw,mp.
91. Mongolia/
92. mongolia*.cp,in,jw,mp.
93. Papua New Guinea/
94. Papua New Guinea.cp,in,jw,mp.
95. Philippines/
96. (Philippines or filipino*).cp,in,jw,mp.
97. samoa/ or "independent state of samoa"/
98. samoa*.cp,in,jw,mp.
99. Melanesia/
100. (Solomon Islands or Timor-Leste or Melanesia*).cp,in,jw,mp.
101. Tonga/
102. tonga*.cp,in,jw,mp.
103. Vanuatu/
104. Vanuatu.cp,in,jw,mp.
105. Vietnam/
106. Vietnam*.cp,in,jw,mp.
107. exp China/
108. (china or chinese).cp,in,jw,mp.
109. Malaysia/
110. Malaysia*.cp,in,jw,mp.
111. Palau/
112. (Palau or Belau or Pelew).cp,in,jw,mp.
113. Thailand/
114. (Thailand or thai*).cp,in,jw,mp.
115. (tuvalu or ellice islands).cp,in,jw,mp.
116. Kyrgyzstan/
117. (kyrgyzstan or kyrgyz or kirghizia or kirghiz).cp,in,jw,mp.
118. Tajikistan/
119. (tajikistan or tadzhik or tadzhikistan or tajikistan).cp,in,jw,mp.
120. Albania/
121. Albania*.cp,in,jw,mp.
122. Armenia/
123. Armenia*.cp,in,jw,mp.
124. "Georgia (Republic)"/
125. georgia*.cp,in,jw,mp.
126. Yugoslavia/
127. (Jugoslavija* or Yugoslavia* or serbo-croat* or macedonia* or sloven* or kosovo).cp,in,jw,mp.
128. Moldova/
129. Moldova*.cp,in,jw,mp.
130. Ukraine/
131. Ukrain*.cp,in,jw,mp.
132. Uzbekistan/
133. Uzbekistan.cp,in,jw,mp.
134. Azerbaijan/
135. Azerbaijan*.cp,in,jw,mp.
136. "Republic of Belarus"/
137. (belarus or byelarus or belorussia).cp,in,jw,mp.
138. Bosnia-Herzegovina/
139. bosnia*.cp,in,jw,mp.
140. Bulgaria/
141. Bulgaria*.cp,in,jw,mp.
142. Kazakhstan/
143. (Kazakhstan or kazakh).cp,in,jw,mp.
144. Latvia/
145. Latvia*.cp,in,jw,mp.
146. Lithuania/
147. Lithuania*.cp,in,jw,mp.
148. "Macedonia (Republic)"/
149. Macedonia*.cp,in,jw,mp.
150. Montenegro/
151. Montenegro.cp,in,jw,mp.
152. Romania/
153. Romania*.cp,in,jw,mp.
154. exp Russia/
155. USSR/
156. (russia* or ussr or soviet or cccp).cp,in,jw,mp.
157. Serbia/
158. serbia*.cp,in,jw,mp.
159. Turkey/
160. turk*.cp,in,jw,mp. not animal/
161. Turkmenistan/
162. Haiti/
163. Haiti.cp,in,jw,mp.
164. Belize/
165. Belize.cp,in,jw,mp.
166. Bolivia/
167. Bolivia*.cp,in,jw,mp.
168. El Salvador/
169. El Salvador.cp,in,jw,mp.
170. Guatemala/
171. Guatemala*.cp,in,jw,mp.
172. Guyana/
173. Guyana*.cp,in,jw,mp.
174. Honduras/
175. Hondura*.cp,in,jw,mp.
176. Nicaragua/
177. Nicaragua.cp,in,jw,mp.
178. Paraguay/
179. Paraguay.cp,in,jw,mp.
180. "Antigua and Barbuda"/
181. (Antigua or Barbuda).cp,in,jw,mp.
182. Argentina/
183. Argentin*.cp,in,jw,mp.
184. Brazil/
185. Brazil*.cp,in,jw,mp.
186. Chile/
187. Chile*.cp,in,jw,mp.
188. Colombia/
189. Colombia*.cp,in,jw,mp.
190. Costa Rica/
191. Costa Rica*.cp,in,jw,mp.
192. Cuba/
193. Cuba*.cp,in,jw,mp.
194. Dominica/
195. Dominican Republic/
196. Dominica*.cp,in,jw,mp.
197. Ecuador/
198. Ecuador*.cp,in,jw,mp.
199. Grenada/
200. Grenad*.cp,in,jw,mp.
201. Jamaica/
202. Jamaica*.cp,in,jw,mp.
203. Mexico/
204. Mexic*.cp,in,jw,mp.
205. exp Panama/
206. Panama*.cp,in,jw,mp.
207. Peru/
208. Peru*.cp,in,jw,mp.
209. Saint Lucia/
210. (St Lucia* or Saint Lucia*).cp,in,jw,mp.
211. "Saint Vincent and the Grenadines"/
212. Grenadines.cp,in,jw,mp.
213. Suriname/
214. Surinam*.cp,in,jw,mp.
215. Uruguay/
216. Uruguay.cp,in,jw,mp.
217. Venezuela/
218. Venezuela*.cp,in,jw,mp.
219. Djibouti/
220. Djibouti.cp,in,jw,mp.
221. Egypt/
222. Egypt*.cp,in,jw,mp.
223. Iraq/
224. Iraq*.cp,in,jw,mp.
225. Morocco/
226. Morocc*.cp,in,jw,mp.
227. Syria/
228. (Syria* or gaza*).cp,in,jw,mp.
229. Yemen/
230. yemen*.cp,in,jw,mp.
231. Algeria/
232. Algeria*.cp,in,jw,mp.
233. Iran/
234. Iran*.cp,in,jw,mp.
235. Jordan/
236. jordan*.cp,in,jw,mp.
237. Lebanon/
238. Leban*.cp,in,jw,mp.
239. Libya/
240. Libya*.cp,in,jw,mp.
241. Tunisia/
242. Tunisia*.cp,in,jw,mp.
243. Afghanistan/
244. Afghan*.cp,in,jw,mp.
245. Bangladesh/
246. Bangladesh*.cp,in,jw,mp.
247. Nepal/
248. Nepal*.cp,in,jw,mp.
249. Bhutan/
250. Bhutan*.cp,in,jw,mp.
251. exp India/
252. india*.cp,in,jw,mp.
253. Pakistan/
254. Pakistan*.cp,in,jw,mp.
255. Sri Lanka/
256. Sri Lanka*.cp,in,jw,mp.
257. Indian Ocean Islands/
258. Maldiv*.cp,in,jw,mp.
259. Benin/
260. (Benin or Dahomey).cp,in,jw,mp.
261. Burkina Faso/
262. (Burkina Faso or Burkina Fasso or Upper Volta).cp,in,jw,mp.
263. Burundi/
264. Burundi*.cp,in,jw,mp.
265. Central African Republic/
266. (Central African Republic or Ubangi-Shari or african*).cp,in,jw,mp.
267. Chad/
268. Chad.cp,in,jw,mp.
269. Comoros/
270. (comoros or comores).cp,in,jw,mp.
271. "Democratic Republic of the Congo"/
272. (congo* or zaire).cp,in,jw,mp.
273. Eritrea/
274. Eritrea*.cp,in,jw,mp.
275. Ethiopia/
276. Ethiopia*.cp,in,jw,mp.
277. Gambia/
278. Gambia*.cp,in,jw,mp.
279. Guinea/
280. (Guinea* not (New Guinea or Guinea Pig* or Guinea Fowl)).cp,in,jw,mp.
281. Guinea-Bissau/
282. (Guinea-Bissau or Portuguese Guinea).cp,in,jw,mp.
283. Kenya/
284. Kenya*.cp,in,jw,mp.
285. Liberia/
286. Liberia*.cp,in,jw,mp.
287. Madagascar/
288. (Madagasca* or Malagasy Republic).cp,in,jw,mp.
289. Malawi/
290. (Malawi* or Nyasaland).cp,in,jw,mp.
291. Mali/
292. Mali*.cp,in,jw,mp.
293. Mauritania/
294. Mauritania*.cp,in,jw,mp.
295. Mozambique/
296. (Mozambi* or Portuguese East Africa).cp,in,jw,mp.
297. Niger/
298. (Niger not (Aspergillus or Peptococcus or Schizothorax or Cruciferae or Gobius or Lasius or Agelastes or Melanosuchus or radish or Parastromateus or Orius or Apergillus or Parastromateus or Stomoxys)).cp,in,jw,mp.
299. Rwanda/
300. (Rwanda* or Ruanda*).cp,in,jw,mp.
301. Sierra Leone/
302. Sierra Leone*.cp,in,jw,mp.
303. Somalia/
304. Somali*.cp,in,jw,mp.
305. Tanzania/
306. Tanzania*.cp,in,jw,mp.
307. Togo/
308. Togo*.cp,in,jw,mp.
309. Uganda/
310. Uganda*.cp,in,jw,mp.
311. Zimbabwe/
312. (Zimbabwe* or Rhodesia*).cp,in,jw,mp.
313. Cameroon/
314. Cameroon*.cp,in,jw,mp.
315. Cape Verde/
316. Cape Verde*.cp,in,jw,mp.
317. Congo/
318. (congo* not ((democratic republic adj3 congo) or congo red or crimean-congo)).cp,in,jw,mp.
319. Cote d'Ivoire/
320. (Cote d'Ivoire or Ivory Coast).cp,in,jw,mp.
321. Ghana/
322. (Ghan* or Gold Coast).cp,in,jw,mp.
323. Lesotho/
324. (Lesotho or Basutoland).cp,in,jw,mp.
325. Nigeria/
326. Nigeria*.cp,in,jw,mp.
327. Atlantic Islands/
328. (sao tome adj2 principe).cp,in,jw,mp.
329. Senegal/
330. Senegal*.cp,in,jw,mp.
331. Sudan/
332. Sudan*.cp,in,jw,mp.
333. Swaziland/
334. Swazi*.cp,in,jw,mp.
335. Zambia/
336. (Zambia* or Northern Rhodesia*).cp,in,jw,mp.
337. Angola/
338. Angola*.cp,in,jw,mp.
339. Botswana/
340. (Botswana* or Bechuanaland or Kalahari).cp,in,jw,mp.
341. Gabon/
342. Gabon*.cp,in,jw,mp.
343. Mauritius/
344. (Mauriti* or Agalega Islands).cp,in,jw,mp.
345. Namibia/
346. Namibia*.cp,in,jw,mp.
347. Seychelles/
348. Seychelles.cp,in,jw,mp.
349. South Africa/
350. South Africa*.cp,in,jw,mp.
351. or/70-350
352. 69 and 351

Contributions of authors

All authors contributed to the protocol development.

Declarations of interest

None to declare.

Sources of support

Internal sources

  • Warwick Medical School, UK.

  • Liverpool School of Tropical Medicine, UK.

  • London School of Hygiene and Tropical Medicine, UK.

  • Center for Evidence-based Health Care, Stellenbosch University, South Africa.

External sources

  • NIHR Cochrane Programme Grant, UK.