Hand-Washing Practices among Adolescents Aged 12–15 Years from 80 Countries
by
, , , , , , , and
Lee Smith
1,*
,
Laurie Butler
2,
Mark A Tully
3
,
Louis Jacob
4,
Yvonne Barnett
5,
Guillermo F. López-Sánchez
6
,
Rubén López-Bueno
7
,
Jae Il Shin
8,
Daragh McDermott
9,
Briona A. Pfeifer
1, 
Damiano Pizzol
10 and
Ai Koyanagi
11,* 1
The Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, Cambridge CB1 1PT, UK
2
Faculty of Science and Engineering, Anglia Ruskin University, Cambridge CB1 1PT, UK
3
Institute of Mental Health Sciences, School of Health Sciences, Ulster University, Newtownabbey BT37 0QB, UK
4
Faculty of Medicine, University of Versailles Saint-Quentin-en-Yvelines, 78180 Montigny-le-Bretonneux, France
5
Faculty of Science and Technology, Anglia Ruskin University, Cambridge CB1 1PT, UK
6
Vision and Eye Research Institute, School of Medicine, Faculty of Health, Education, Medicine and Social Care, Anglia Ruskin University-Cambridge Campus, Cambridge CB1 1PT, UK
7
Department of Physical Medicine and Nursing, University of Zaragoza, 50009 Zaragoza, Spain
8
Department of Pediatrics, Yonsei University College of Medicine, Yonsei-ro 50, Seodaemun-gu, C.P.O. Box 8044, Seoul 120-752, Korea
9
School of Psychology and Sport, Anglia Ruskin University, Cambridge CB1 1PT, UK
10
Italian Agency for Development Cooperation, Khartoum 79371, Sudan
11
Research and Development Unit, Parc Sanitari Sant Joan de Déu, CIBERSAM, ICREA, Sant Boi de Llobregat, 08830 Barcelona, Spain
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(1), 138; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18010138
Submission received: 28 November 2020
/
Revised: 18 December 2020
/
Accepted: 24 December 2020
/
Published: 27 December 2020
(This article belongs to the Special Issue Health-Related Behaviours during the COVID-19 Pandemic)
Abstract
:The objectives were to (1) assess the prevalence of hand-washing practices across 80 countries and (2) assess frequency of hand-washing practice by economic status (country income and severe food insecurity), in a global representative sample of adolescents. Cross-sectional data from the Global School-based Student Health Survey 2003–2017 were analyzed. Data on age, sex, hand-washing practices in the past 30 days, and severe food insecurity (i.e., proxy of socioeconomic status) were self-reported. Multivariable logistic regression and meta-analysis with random effects based on country-wise estimates were conducted to assess associations. Adolescents (n = 209,584) aged 12–15 years [mean (SD) age 13.8 (1.0) years; 50.9% boys] were included in the analysis. Overall, the prevalence of hand-washing practices were as follows: never/rarely washing hands before eating (6.4%), after using toilet (5.6%), or with soap (8.8%). The prevalence of never/rarely washing hands after using the toilet (10.8%) or with soap (14.3%) was particularly high in low-income countries. Severe food insecurity was associated with 1.34 (95%CI = 1.25–1.43), 1.61 (95%CI = 1.50–1.73), and 1.44 (95%CI = 1.35–1.53) times higher odds for never/rarely washing hands before eating, after using the toilet, and with soap, respectively. A high prevalence of inadequate hand washing practices was reported, particularly in low-income countries and those with severe food insecurity. In light of the present COVID-19 pandemic and the rapid expansion being observed in low- and middle-income locations, interventions that disseminate good hand-washing practices are urgently required. Such interventions may also have cross-over benefits in relation to other poor sanitation-related diseases.
1. Introduction
Hand-washing with soap has been found to be an effective prevention strategy against the contraction of infectious diseases, including respiratory infections and gastrointestinal diseases. For example, findings from meta-analyses suggest that hand-washing with soap can reduce respiratory infections by 21% to 23% [1,2] and diarrheal disease by 23% to 48% [3,4,5].
In March 2020, the World Health Organization (WHO) declared the COVID-19 outbreak a global pandemic. COVID-19 is caused by SARS-CoV-2, a variant of coronavirus. As of 17 April 2020 (10:00 am CET), more than 2,160,170 cases have been diagnosed globally, with over 145,593 directly reported fatalities globally [6]. COVID-19 is a respiratory virus that is transmitted by large respiratory droplets and direct contact with infected secretions. One very important measure to prevent contraction is to wash hands with soap regularly and this is at the heart of current public health guidance, amongst other strategies (e.g., self-isolating and social distancing). The WHO states “regularly and thoroughly clean your hands with an alcohol-based hand rub or wash them with soap and water” [7].
However, despite this, limited data exists on the prevalence of hand-washing in different countries. One systematic review investigated the global prevalence of hand washing with soap after potential fecal contact and found that this stood at approximately 26%. Moreover, in regions with high access to hand-washing facilities, hand-washing with soap was performed by about 51%, and in regions with more limited access, by about 22% after events of potential fecal contact [8]. Finally, the review concluded that important gaps exist for country-representative data on presence of designated hand-washing facilities and on hand-washing behavior at household level, for all regions of the world and particularly for high-income countries (HICs) [8]. Before interventions on hand-washing practice can be implemented with confidence to prevent the spread of infection, such as in the case of SARS-CoV-2, levels of hand-washing practices by country are required, in order to appropriately inform public health information campaigns.
In addition, to promote effective hand-washing practices, vulnerable populations need to be identified. Previous studies have shown that those from poorer socio-economic backgrounds engage in particularly inadequate hand-washing practices. This may be explained by lack of adequate washing facilities or soap, or lack of knowledge on the importance of maintaining hygiene. One study in 6971 children participants residing in urban Bangladesh found that hand-washing indicators were strongly influenced by socio-economic status. For example, those in the poorest wealth category washed hands with soap significantly less before eating and after defecation when compared to those in higher wealth categories [9]. In another study of 800 Kenyan households those with the lowest level of education washed their hands markedly less than the majority of households [10]. Other studies from low- and middle-income countries (LMICs) have found similar findings [11,12]. However, studies investigating the association between socio-economic status and hand washing from a global perspective including HICs are lacking. There are markedly different socio-cultural norms, occupational and family structures, societal norms, environmental features (e.g., housing types, availability of hand washing facilities) between settings (e.g., LMICs and HICs). Therefore, there is a need for context-specific research [13]. Moreover, multi-country studies, which include both LMICs and HICs, are important, as they provide a platform to investigate between-country differences utilizing standardized data.
Furthermore, adolescents in particular may play an important role in the transmission of infectious diseases during pandemic times owing to high levels of risk taking behavior [14]. Adolescents may be less likely to follow government guidance, such as in the case of COVID-19, making good hand-washing practices even more essential in this population to prevent the spread and acquisition of infectious disease [14]. However, there are currently only a few studies which have specifically focused on hand-washing practices among adolescents.
Given the above-mentioned gaps in the literature, the present study aimed to (1) assess the prevalence of hand-washing practices across 80 countries and (2) assess frequency of hand-washing practice by socio-economic status (country income and severe food insecurity), in a globally representative sample of adolescents.
2. Methods
Publicly available data from the GSHS were analyzed. Details of this survey can be found at http://www.who.int/chp/gshs and http://www.cdc.gov/gshs. Briefly, the GSHS was jointly developed by the WHO and the US Centers for Disease Control and Prevention (CDC), and other UN allies. The core aim of this survey was to assess and quantify risk and protective factors of major non-communicable diseases. The survey draws content from the CDC Youth Risk Behavior Survey (YRBS) for which test-retest reliability has been established [15]. The survey used a standardized two-stage probability sampling design for the selection process within each participating country. For the first stage, schools were selected with probability proportional to size sampling. The second stage involved the random selection of classrooms which included students aged 13–15 years within each selected school. All students in the selected classrooms were eligible to participate in the survey regardless of age. Data collection was performed during one regular class period. The questionnaire was translated into the local language in each country and consisted of multiple choice response options; students recorded their response on computer scannable sheets. All GSHS surveys were approved, in each country, by both a national government administration (most often the Ministry of Health or Education) and an institutional review board or ethics committee. Student privacy was protected through anonymous and voluntary participation, and informed consent was obtained as appropriate from the students, parents and/or school officials. Data were weighted for non-response and probability selection.
From all publicly available data, we selected all nationally representative datasets that included the variables used in the current analysis. If there were more than two datasets from the same country, we chose the most recent dataset. A total of 80 countries were included in the current study, and consisted of 12 low-income, 34 lower middle-income, 21 upper middle-income, and 13 high-income countries based on the World Bank classification at the time of the survey. The characteristics of each country or survey are provided in Table 1. For the included countries, the survey was conducted between 2003 and 2017.
2.1. Hand-Washing Practices
Three questions about hand-washing practices in the past 30 days were asked: (a) how often did you wash your hand before eating? (b) how often did you wash your hands after using the toilet or latrine?; and (c) how often did you use soap when washing your hands? Each of these questions had as answer options: ‘Never’, ‘Rarely’, ‘Sometimes’, ‘Most of the time’, and ‘Always’. In line with a previous GSHS publication, we dichotomized this variable as ‘Never/rarely’ (Coded 1) and others (Coded 0) [16].
2.2. Food Insecurity (Proxy of Socioeconomic Status)
Since the GSHS does not have a question on socioeconomic status, we used food insecurity as a proxy of this condition [17]. Food insecurity was assessed by the question “During the past 30 days, how often did you go hungry because there was not enough food in your home?” with answer options ‘Never’, ‘Rarely’, ‘Sometimes’, ‘Most of the time’, and ‘Always’. As in a previous GSHS study, we considered those who answered ‘Most of the time’ or ‘Always’ as having severe food insecurity [18].
2.3. Statistical Analysis
Statistical analyses were performed with Stata 14.1 (Stata Corp LP, College station, TX, USA). The analysis was restricted to those aged 12–15 years as most students were within this age group while information on exact age outside of this age range was not available. The prevalence of hand-washing practices was calculated using the overall sample, and by country or country-income level. The associations between severe food insecurity and each type of hand-washing practice were assessed by country-wise multivariable logistic regression analysis adjusting for age and sex. Pooled estimates were obtained by meta-analysis with random effects based on country-wise estimates. In order to assess the level of between-country heterogeneity in the association between severe food insecurity and hand-washing practices, we also calculated the Higgins’s I2 which represents the degree of heterogeneity that is not explained by sampling error. I2 values of 25%, 50%, and 75% are often considered low, moderate, and high level of heterogeneity, respectively [19]. Sampling weights and the clustered sampling design of the surveys were taken into account in all analyses. Results from the logistic regression analyses are presented as odds ratios (ORs) with 95% confidence intervals (CIs).
3. Results
A total of 209,584 adolescents aged 12–15 years [mean (SD) age 13.8 (1.0) years; 50.9% boys] were included in the analysis. Overall, the prevalence of hand-washing practices was as follows: never/rarely washing hands before eating (6.4%), after using toilet (5.6%), and with soap (8.8%). The country-wise prevalence is shown in Table 2 and Figure 1. The prevalence of never/rarely washing hands before eating was highest in Tuvalu (38.5%), followed by East Timor (20.9%), and Kiribati (20.6%). In terms of this figure for never/rarely washing hands after using the toilet, the highest figures were observed in East Timor (27.5%), Mauritania (24.4%), and Tuvalu (17.7%), with a high prevalence generally in Africa. As for never or rarely using soap when washing hands, Honduras had the highest prevalence (58.6%), followed by Sudan (20.9%), and Zambia (20.8%), with most countries with the highest prevalence being found in Sub-Saharan Africa. The prevalence of hand-washing practices by country-income level is shown in Figure 2. The prevalence of never or rarely washing hands before eating was higher in high- and upper middle-income countries, while that of never/rarely washing hands after using the toilet and with soap was particularly high in low-income countries. The associations between severe food insecurity and hand-washing practices assessed by meta-analysis based on country-wise estimates are shown in Table 3. Severe food insecurity was associated with 1.34 (95% CI = 1.25–1.43) times higher odds for never/rarely washing hands before eating overall, with the estimates being similar between different country-income levels. The corresponding figure for never/rarely washing hands after using the toilet was 1.61 (95%CI = 1.50–1.73), with higher ORs being observed in countries with higher income. As for never/rarely using soap when washing hands, this figure was 1.44 (95%CI = 1.35–1.53) with the highest ORs being observed in upper middle- and high-income countries. A moderate level of heterogeneity was observed for all overall estimates. The country-wise estimates from which these estimates were derived can be found in Figure A1, Figure A2 and Figure A3 of the Appendix A.
4. Discussion
In this large sample of adolescents aged 12–15 years across 80 countries, prevalence of poor hand-washing practices was found to be high: never/rarely washing hands before eating (6.4%), after using toilet (5.6%), and with soap (8.8%). The highest prevalence of never/rarely washing hands after using the toilet and with soap were found in low-income countries. However, the prevalence of never/rarely washing hands before eating was higher in upper middle-income countries and HICs. Generally, those from a low socio-economic status (using severe food insecurity as a proxy) were less likely to engage in good hand washing practices. Findings were similar for each hand-washing scenario (i.e., before eating and after using the toilet, or using soap).
Findings from the present study supports previous literature which has reported a low prevalence of good hand-washing practices particularly in LMICs [9,10,11,12]. This may be owing to lack of knowledge relating to benefits and how to appropriately wash hands. For example, in one study carried out on 90 health care professionals in Northeast Ethiopia, 36.1% had no knowledge of good hand-washing practices [20]. Moreover, poor hand-washing practices may be due to a lack of hand washing facilities, access to clean water supplies or soap in low-income countries [21]. Indeed, in sub-Saharan Africa, 63 percent of people in urban areas–258 million people–lack access to hand washing, according to the UNICEF figures. In central and south Asia this figure is 22 percent, or 153 million people [22]. However, the finding that hand-washing before eating was more common in lower income countries points to the fact that not all hand-washing practices may be linked with poverty. Although the reason for this finding is unknown, it may be explained by the fact that eating with hands is common in some LMICs and it is considered important to wash hands before eating in these settings.
Although the first confirmed COVID-19 cases occurred later in West Africa than in Europe, once these first cases were confirmed the expansion in the number of confirmed COVID-19 was rapid [23]. Based on our findings that the prevalence of never/rarely washing hands after using the toilet or with soap was particularly high in low-income countries and in particular, Sub-Saharan Africa, it is possible that this may have partly expedited the spread of the SARS-Cov-2 in these locations and potentially other contemporaneous locations. Therefore, a strong dissemination of good hand-washing practices especially in low-income countries may help curb the rapid expansion of COVID-19 cases. In addition, such a message may also have a cross-over effect, that is, we may observe reductions in other diseases linked to poor sanitation conditions such as pneumonia, gastroenteritis, diarrhea, dysentery, hepatitis A, cholera, typhoid, polio and skin infection.
The present study found that severe food insecurity (a proxy for low socio-economic status) was significantly associated with poor hand-washing practices across LMICs and HICs. It is likely that this is due to similar reasons that explain a low prevalence of good hand-washing practice in LMICs, that is lack of knowledge and availability of appropriate facilities. Of note, severe food insecurity was associated with never/rarely washing hands after using the toilet or with soap more strongly in upper middle-income countries and HICs than countries with lower income pointing to the fact that, even within wealthier nations, individuals with lower levels of socioeconomic status are more likely to engage in inadequate hygiene and are possibly at a higher risk for various types of infections.
Clear strengths of this study include the large global sample of adolescents from 80 countries and the inclusion of high-, middle-, and low-income countries. However, finding must be interpreted in light of the study limitations. First, the study relied on self-reported data, thus some degree of bias may exist. Second, our study only included adolescents who attend school, and the results may therefore not be generalizable to all adolescents in the respective countries especially in countries where school attendance rates are low. Third, we did not have information on whether the student was not able to engage in adequate handwashing practices due to lack of facilities or whether this was due to personal choice. Given that these two different underlying reasons may require different interventions, future studies should also investigate the exact reason why some students do not engage in adequate handwashing practices. Finally, data were collected between 2003 and 2017 and thus, our results may not reflect the current situation in some countries.
5. Conclusions
In conclusion, in this large representative global sample of adolescents, a low prevalence of good hand-washing practices was reported, particularly in low-income countries, and those with a low socio-economic status regardless of country-income level. In light of the present COVID-19 pandemic and the rapid expansion globally, interventions that disseminate good hand-washing practices and, ideally, provision of soap in areas in need are urgently required. Moreover, such a message may also have a cross-over effect, that is, we may observe reductions in other diseases linked to poor sanitation conditions such as pneumonia, gastroenteritis, diarrhea, dysentery, hepatitis A, cholera, typhoid, polio and skin infection. Our data show that some good hand-washing practices (e.g., washing hands before eating) may be less common in HICs, and that those with severe food insecurity in HICs have particularly high odds for never/rarely washing hands after using the toilet or with soap. Thus, interventions to promote effective hand-washing to reduce risk for various types of infections are needed worldwide regardless of country-income level and focusing on the socially underprivileged within a country may be important.
Author Contributions
Writing—original draft, L.S., L.B., M.A.T., L.J., Y.B., G.F.L.-S., R.L.-B., J.I.S., D.M., B.A.P., D.P., A.K.; Writing—review & editing, L.S., L.B., M.A.T., L.J., Y.B., G.F.L.-S., R.L.-B., J.I.S., D.M., B.A.P., D.P., A.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
All GSHS surveys were approved, in each country, by both a national government administration (most often the Ministry of Health or Education) and an institutional review board or ethics committee.
Informed Consent Statement
Student privacy was protected through anonymous and voluntary participation, and informed consent was obtained as appropriate from the students, parents and/or school officials.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author, upon reasonable request.
Acknowledgments
This research was based on data from the Global School-Based Student.
Conflicts of Interest
Authors declare no conflict of interest.
Appendix A
Figure A1.
Country-wise association between severe food insecurity and never/rarely washing hands before eating estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
Figure A1.
Country-wise association between severe food insecurity and never/rarely washing hands before eating estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
Figure A2.
Country-wise association between severe food insecurity and never/rarely washing hands after using toilet estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
Figure A2.
Country-wise association between severe food insecurity and never/rarely washing hands after using toilet estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
Figure A3.
Country-wise association between severe food insecurity and never/rarely using soap when washings hands estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
Figure A3.
Country-wise association between severe food insecurity and never/rarely using soap when washings hands estimated by multivariable logistic regression adjusted for age and sex; Abbreviation: OR Odds ratio; CI Confidence interval; overall estimates were calculated by meta-analysis with random effects.
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Figure 1.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country. (A) Prevalence of adolescents who never or rarely wash hands before eating; (B) Prevalence of adolescents who never or rarely wash hands after using the toilet; (C) Prevalence of adolescents who rarely or never use soap when washing hands.
Figure 1.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country. (A) Prevalence of adolescents who never or rarely wash hands before eating; (B) Prevalence of adolescents who never or rarely wash hands after using the toilet; (C) Prevalence of adolescents who rarely or never use soap when washing hands.
Figure 2.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country-income level. Bars denote 95% confidence interval.
Figure 2.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country-income level. Bars denote 95% confidence interval.
Table 1.
Sample characteristics.
| Country-Income | Country | Year | Response Rate (%) | N a | Male (%) | Age (Years) Mean (SD) |
|---|---|---|---|---|---|---|
| Low | Afghanistan | 2014 | 79 | 1493 | 53.4 | 14.0 (0.9) |
| Benin | 2016 | 78 | 717 | 65.6 | 14.2 (0.9) | |
| Cambodia | 2013 | 85 | 1812 | 48.4 | 14.1 (0.8) | |
| Kenya | 2003 | 84 | 2971 | 47.5 | 13.9 (1.0) | |
| Liberia | 2017 | 71 | 541 | 50.1 | 14.0 (0.9) | |
| Malawi | 2009 | 94 | 2224 | 51.5 | 14.0 (0.8) | |
| Mozambique | 2015 | 80 | 668 | 49.6 | 14.1 (0.8) | |
| Nepal | 2015 | 69 | 4616 | 47.3 | 13.8 (1.0) | |
| Senegal | 2005 | 60 | 2666 | 60.2 | 13.9 (1.0) | |
| Tanzania | 2014 | 87 | 2615 | 46.8 | 13.6 (1.0) | |
| Uganda | 2003 | 69 | 1904 | 47.4 | 14.3 (0.8) | |
| Zambia | 2004 | 70 | 1365 | 50.3 | 13.9 (1.0) | |
| Low middle | Bangladesh | 2014 | 91 | 2753 | 63.4 | 14.0 (0.8) |
| Belize | 2011 | 88 | 1600 | 48.4 | 13.6 (1.1) | |
| Bolivia | 2012 | 88 | 2804 | 49.7 | 14.0 (0.9) | |
| Djibouti | 2007 | 83 | 962 | 59.5 | 14.3 (0.8) | |
| East Timor | 2015 | 79 | 1631 | 46.3 | 14.1 (1.0) | |
| Egypt | 2011 | 85 | 2364 | 49.2 | 13.5 (0.9) | |
| El Salvador | 2013 | 88 | 1615 | 50.6 | 14.0 (0.9) | |
| Eswatini | 2013 | 97 | 1318 | 39.1 | 14.1 (0.8) | |
| Ghana | 2012 | 82 | 1110 | 49.1 | 13.8 (1.0) | |
| Guatemala | 2015 | 82 | 3611 | 50.9 | 13.9 (0.9) | |
| Guyana | 2010 | 76 | 1973 | 48.6 | 14.1 (0.8) | |
| Honduras | 2012 | 79 | 1486 | 46.1 | 13.6 (1.0) | |
| India | 2007 | 83 | 7330 | 57.4 | 13.9 (0.9) | |
| Indonesia | 2015 | 94 | 8806 | 49.2 | 13.5 (1.0) | |
| Jordan | 2007 | 99.8 | 1648 | 47.3 | 14.3 (0.7) | |
| Kiribati | 2011 | 85 | 1340 | 45.5 | 14.0 (0.9) | |
| Laos | 2015 | 70 | 1644 | 47.8 | 14.5 (0.8) | |
| Maldives | 2009 | 80 | 1981 | 47.9 | 14.4 (0.7) | |
| Mauritania | 2010 | 70 | 1285 | 53.2 | 14.2 (0.9) | |
| Mongolia | 2013 | 88 | 3707 | 49.4 | 13.7 (1.0) | |
| Morocco | 2016 | 91 | 3975 | 50.9 | 13.6 (1.1) | |
| Myanmar | 2016 | 86 | 2237 | 46.3 | 13.6 (0.9) | |
| Northern Macedonia | 2007 | 93 | 1550 | 51.6 | 13.9 (0.9) | |
| Pakistan | 2009 | 76 | 4998 | 60.8 | 14.1 (0.8) | |
| Philippines | 2015 | 79 | 6162 | 48.1 | 13.9 (0.9) | |
| Samoa | 2011 | 79 | 2200 | 47.4 | 14.0 (0.8) | |
| Solomon Islands | 2011 | 85 | 925 | 52.1 | 14.1 (0.9) | |
| Sri Lanka | 2016 | 89 | 2254 | 49.3 | 13.9 (0.9) | |
| Sudan | 2012 | 77 | 1401 | 51.9 | 14.2 (0.8) | |
| Syria | 2010 | 97 | 2929 | 51.2 | 13.6 (1.0) | |
| Tunisia | 2008 | 83 | 2549 | 49.7 | 13.6 (1.0) | |
| Vanuatu | 2016 | 57 | 1288 | 47.8 | 14.1 (0.9) | |
| Vietnam | 2013 | 96 | 1743 | 46.6 | 14.5 (0.6) | |
| Yemen | 2014 | 75 | 1553 | 56.3 | 13.8 (1.0) | |
| Upper middle | Algeria | 2011 | 98 | 3484 | 45.8 | 13.6 (1.1) |
| Antigua & Barbuda | 2009 | 67 | 1235 | 51.4 | 13.9 (0.9) | |
| Argentina | 2012 | 71 | 21,528 | 47.7 | 13.9 (0.9) | |
| Botswana | 2005 | 95 | 1397 | 46.2 | 14.3 (0.8) | |
| Costa Rica | 2009 | 72 | 2265 | 49.6 | 14.0 (0.9) | |
| Dominican Republic | 2016 | 63 | 954 | 48.6 | 14.3 (1.0) | |
| Grenada | 2008 | 78 | 1299 | 42.7 | 13.7 (1.1) | |
| Iraq | 2012 | 88 | 1533 | 54.7 | 13.9 (1.0) | |
| Lebanon | 2017 | 82 | 3347 | 47.4 | 13.6 (1.0) | |
| Libya | 2007 | 98 | 1891 | 49.2 | 13.6 (1.0) | |
| Malaysia | 2012 | 89 | 16,273 | 49.5 | 14.0 (0.9) | |
| Mauritius | 2017 | 84 | 1955 | 45.8 | 13.9 (0.8) | |
| Namibia | 2013 | 89 | 1936 | 42.9 | 14.1 (0.9) | |
| Paraguay | 2017 | 87 | 1972 | 47.5 | 13.9 (1.0) | |
| Peru | 2010 | 85 | 2359 | 49.9 | 14.1 (0.8) | |
| St. Lucia | 2007 | 82 | 1072 | 44.5 | 13.7 (1.1) | |
| St. Vincent & the Grenadines | 2007 | 84 | 1188 | 46.2 | 13.5 (1.0) | |
| Suriname | 2016 | 83 | 1453 | 46.1 | 13.8 (1.0) | |
| Thailand | 2015 | 89 | 4132 | 49.6 | 13.7 (1.0) | |
| Tonga | 2017 | 90 | 2067 | 51.4 | 13.6 (1.1) | |
| Tuvalu | 2013 | 90 | 679 | 48.9 | 13.3 (1.1) | |
| High | Bahamas | 2013 | 78 | 1308 | 47.3 | 13.4 (1.0) |
| Barbados | 2011 | 73 | 1504 | 51.1 | 14.1 (0.8) | |
| Brunei Darussalam | 2014 | 65 | 1824 | 48.2 | 14.0 (0.9) | |
| Cayman Islands | 2007 | 79 | 1147 | 52.0 | 13.5 (1.0) | |
| Curaçao | 2015 | 83 | 1498 | 49.8 | 13.9 (1.1) | |
| French Polynesia | 2015 | 70 | 1902 | 49.7 | 13.7 (1.0) | |
| Kuwait | 2015 | 78 | 2034 | 49.4 | 14.1 (0.9) | |
| Oman | 2015 | 92 | 1669 | 47.1 | 14.2 (0.8) | |
| Qatar | 2011 | 87 | 1781 | 47.2 | 13.4 (1.0) | |
| St. Kitts & Nevis | 2011 | 70 | 1471 | 50.2 | 14.1 (0.8) | |
| Trinidad & Tobago | 2017 | 89 | 2763 | 48.3 | 13.6 (1.1) | |
| United Arab Emirates | 2016 | 80 | 3471 | 48.1 | 13.9 (1.0) | |
| Uruguay | 2012 | 77 | 2869 | 46.3 | 14.1 (0.8) |
Abbreviation: SD Standard deviation; a Based on sample aged 12–15 years.
Table 2.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country.
Table 2.
Prevalence of never/rarely washing hands before eating, after using toilet, and with soap by country.
| Country-Income | Country | % | 95%CI | % | 95%CI | % | 95%CI |
|---|---|---|---|---|---|---|---|
| Low | Afghanistan | 6.0 | [4.4,8.2] | 5.6 | [3.6,8.6] | 11.6 | [8.0,16.6] |
| Benin | 6.4 | [4.3,9.2] | 10.6 | [5.6,19.2] | 18.5 | [13.2,25.3] | |
| Cambodia | 2.1 | [1.5,3.0] | 3.0 | [2.2,4.2] | 2.9 | [2.2,3.7] | |
| Kenya | 8.6 | [7.0,10.5] | 13.9 | [11.9,16.1] | 16.6 | [14.1,19.5] | |
| Liberia | 12.3 | [9.2,16.4] | 6.3 | [4.1,9.6] | 9.6 | [6.9,13.3] | |
| Malawi | 4.1 | [2.2,7.6] | 5.3 | [3.3,8.4] | 16.7 | [13.5,20.4] | |
| Mozambique | 7.4 | [4.9,11.1] | 7.8 | [4.9,12.1] | 11.7 | [7.1,18.7] | |
| Nepal | 4.0 | [2.8,5.7] | 4.4 | [3.3,5.8] | 4.8 | [3.8,6.2] | |
| Senegal | 10.2 | [4.9,20.0] | 10.0 | [4.8,19.7] | 14.7 | [9.4,22.4] | |
| Tanzania | 7.3 | [6.1,8.7] | 17.3 | [14.3,20.8] | 20.7 | [18.2,23.4] | |
| Uganda | 6.3 | [5.0,8.0] | 8.0 | [6.1,10.5] | 14.7 | [12.2,17.7] | |
| Zambia | 12.5 | [10.3,15.1] | 15.4 | [12.9,18.3] | 20.8 | [18.1,23.8] | |
| Lower middle | Bangladesh | 3.1 | [1.8,5.2] | 1.9 | [0.8,4.4] | 5.0 | [2.8,8.6] |
| Belize | 3.7 | [3.1,4.4] | 1.6 | [1.2,2.2] | 4.6 | [3.6,5.8] | |
| Bolivia | 10.8 | [9.4,12.4] | 7.3 | [6.1,8.7] | 16.0 | [13.8,18.5] | |
| Djibouti | 6.0 | [4.6,7.7] | 12.9 | [11.4,14.6] | 11.7 | [9.4,14.5] | |
| East Timor | 20.9 | [18.8,23.2] | 27.5 | [24.5,30.8] | 18.9 | [16.4,21.6] | |
| Egypt | 12.9 | [10.5,15.7] | 9.3 | [6.9,12.5] | 7.8 | [5.7,10.6] | |
| El Salvador | 5.3 | [4.1,6.8] | 4.0 | [2.7,6.1] | 5.7 | [4.5,7.3] | |
| Eswatini | 3.6 | [2.3,5.5] | 2.8 | [2.3,3.5] | 11.6 | [10.0,13.4] | |
| Ghana | 7.5 | [4.6,12.2] | 7.8 | [5.0,11.8] | 10.6 | [8.6,13.1] | |
| Guatemala | 4.5 | [2.8,7.1] | 2.7 | [1.5,4.7] | 5.7 | [4.2,7.6] | |
| Guyana | 9.2 | [7.4,11.3] | 6.4 | [4.8,8.4] | 10.7 | [8.5,13.3] | |
| Honduras | 7.5 | [6.4,8.7] | 5.2 | [4.0,6.7] | 58.6 | [54.9,62.3] | |
| India | 5.9 | [5.0,7.1] | 3.3 | [2.7,4.1] | 13.0 | [11.4,14.7] | |
| Indonesia | 2.5 | [2.0,3.0] | 2.3 | [1.8,2.9] | 3.9 | [3.3,4.7] | |
| Jordan | 6.8 | [5.5,8.3] | 7.0 | [5.0,9.7] | 9.2 | [7.4,11.5] | |
| Kiribati | 20.6 | [16.3,25.7] | 16.1 | [13.1,19.5] | 15.4 | [13.2,17.9] | |
| Laos | 1.9 | [1.1,3.2] | 3.8 | [2.5,5.9] | 8.5 | [6.7,10.7] | |
| Maldives | 8.5 | [7.1,10.1] | 4.7 | [3.7,5.8] | 7.2 | [5.9,8.8] | |
| Mauritania | 7.6 | [6.2,9.2] | 24.4 | [17.8,32.4] | 12.1 | [9.4,15.6] | |
| Mongolia | 6.9 | [5.9,8.0] | 10.5 | [8.9,12.3] | 3.0 | [2.4,3.8] | |
| Morocco | 4.8 | [4.1,5.5] | 6.2 | [5.1,7.6] | 10.4 | [8.6,12.5] | |
| Myanmar | 6.7 | [5.5,8.2] | 8.4 | [6.8,10.4] | 5.8 | [4.7,7.1] | |
| Northern Macedonia | 2.1 | [1.5,3.0] | 2.1 | [1.4,3.2] | 3.8 | [2.7,5.3] | |
| Pakistan | 3.4 | [2.7,4.4] | 3.4 | [2.5,4.6] | 8.0 | [6.3,10.2] | |
| Philippines | 7.7 | [4.9,11.8] | 6.3 | [3.9,10.0] | 7.9 | [5.4,11.5] | |
| Samoa | 14.6 | [12.9,16.4] | 17.1 | [14.9,19.5] | 19.3 | [17.1,21.7] | |
| Solomon Islands | 8.6 | [7.2,10.2] | 8.9 | [6.9,11.5] | 10.3 | [7.4,14.0] | |
| Sri Lanka | 2.7 | [1.9,3.9] | 3.0 | [2.1,4.1] | 7.1 | [5.6,9.0] | |
| Sudan | 7.5 | [6.0,9.4] | 11.9 | [9.9,14.1] | 20.9 | [16.7,25.9] | |
| Syria | 9.2 | [7.5,11.3] | 3.8 | [2.5,5.8] | 6.7 | [5.1,8.8] | |
| Tunisia | 6.0 | [5.2,6.9] | 4.0 | [3.2,4.9] | 4.7 | [3.7,5.9] | |
| Vanuatu | 4.2 | [3.3,5.5] | 5.1 | [3.9,6.6] | 6.4 | [5.1,8.1] | |
| Vietnam | 7.0 | [5.4,9.0] | 2.2 | [1.5,3.3] | 8.5 | [6.5,10.9] | |
| Yemen | 7.2 | [5.1,10.1] | 11.2 | [9.6,13.0] | 15.3 | [12.7,18.4] | |
| Upper middle | Algeria | 5.6 | [4.9,6.4] | 3.1 | [2.5,3.8] | 5.1 | [4.4,5.8] |
| Antigua & Barbuda | 12.2 | [10.5,14.2] | 5.1 | [3.9,6.7] | 7.1 | [5.7,8.9] | |
| Argentina | 11.2 | [10.1,12.4] | 5.9 | [5.0,7.0] | 6.2 | [5.5,7.1] | |
| Botswana | 4.5 | [3.3,6.1] | 5.1 | [4.3,6.2] | 17.0 | [13.9,20.7] | |
| Costa Rica | 9.6 | [8.3,11.1] | 2.2 | [1.7,2.8] | 5.4 | [4.5,6.5] | |
| Dominica | 14.1 | [10.1,19.2] | 5.3 | [3.7,7.7] | 8.6 | [5.8,12.6] | |
| Grenada | 11.4 | [9.5,13.6] | 3.5 | [2.8,4.4] | 10.1 | [8.4,12.1] | |
| Iraq | 7.3 | [5.6,9.6] | 8.1 | [6.3,10.3] | 4.0 | [3.0,5.4] | |
| Lebanon | 4.1 | [3.3,5.0] | 1.6 | [1.1,2.4] | 2.2 | [1.9,2.7] | |
| Libya | 8.1 | [6.3,10.4] | 6.8 | [5.5,8.5] | 7.4 | [5.9,9.1] | |
| Malaysia | 5.0 | [4.5,5.6] | 6.0 | [5.3,6.7] | 13.6 | [12.7,14.6] | |
| Mauritius | 13.9 | [11.1,17.4] | 4.0 | [2.7,6.0] | 8.2 | [6.1,10.8] | |
| Namibia | 5.5 | [4.4,6.8] | 6.4 | [5.1,8.0] | 10.8 | [8.8,13.1] | |
| Paraguay | 8.0 | [6.6,9.7] | 2.6 | [1.9,3.5] | 6.1 | [5.0,7.4] | |
| Peru | 4.9 | [3.8,6.2] | 6.6 | [5.5,7.9] | 7.5 | [6.0,9.4] | |
| St. Lucia | 16.5 | [14.0,19.3] | 4.4 | [3.4,5.6] | 11.1 | [9.1,13.4] | |
| St. Vincent & the Grenadines | 8.7 | [6.7,11.3] | 4.1 | [3.0,5.5] | 8.3 | [6.6,10.3] | |
| Suriname | 11.2 | [8.8,14.2] | 4.3 | [3.0,6.1] | 8.1 | [6.7,9.9] | |
| Thailand | 14.9 | [12.5,17.7] | 6.5 | [5.4,7.9] | 14.4 | [12.3,16.9] | |
| Tonga | 14.9 | [12.9,17.0] | 7.8 | [6.5,9.4] | 20.2 | [18.2,22.4] | |
| Tuvalu | 38.5 | [34.9,42.4] | 17.7 | [15.0,20.8] | 18.0 | [15.2,21.0] | |
| High | Bahamas | 15.6 | [13.5,18.0] | 4.5 | [3.4,5.8] | 8.7 | [7.2,10.4] |
| Barbados | 14.3 | [11.9,17.1] | 1.7 | [1.2,2.5] | 7.9 | [6.4,9.7] | |
| Brunei Darussalam | 3.5 | [2.7,4.5] | 2.9 | [1.9,4.4] | 9.7 | [8.1,11.5] | |
| Cayman Islands | 10.8 | [9.1,12.8] | 4.4 | [3.4,5.8] | 5.9 | [4.7,7.5] | |
| Curaçao | 12.2 | [10.2,14.4] | 3.6 | [2.6,4.8] | 6.5 | [5.1,8.3] | |
| French Polynesia | 8.4 | [6.5,10.7] | 5.7 | [4.2,7.8] | 11.5 | [9.8,13.6] | |
| Kuwait | 10.7 | [9.0,12.7] | 6.2 | [4.8,8.0] | 7.4 | [5.6,9.8] | |
| Oman | 7.9 | [5.9,10.4] | 8.8 | [6.8,11.2] | 7.4 | [5.6,9.8] | |
| Qatar | 17.0 | [13.8,20.8] | 15.1 | [12.3,18.4] | 16.4 | [13.0,20.4] | |
| St. Kitts & Nevis | 11.6 | [10.1,13.4] | 2.9 | [2.1,3.9] | 6.7 | [5.5,8.1] | |
| Trinidad & Tobago | 14.7 | [12.9,16.7] | 3.5 | [2.2,5.5] | 11.7 | [9.4,14.5] | |
| United Arab Emirates | 8.1 | [6.9,9.6] | 3.2 | [2.5,4.3] | 4.3 | [3.5,5.3] | |
| Uruguay | 12.5 | [10.8,14.5] | 6.9 | [5.5,8.5] | 3.6 | [2.7,4.8] |
Abbreviation: CI Confidence interval.
Table 3.
Association between severe food insecurity and never/rarely washing hands before eating, after using toilet, and with soap estimated by meta-analysis with random effects based on country-wise estimates.
Table 3.
Association between severe food insecurity and never/rarely washing hands before eating, after using toilet, and with soap estimated by meta-analysis with random effects based on country-wise estimates.
| Outcome | Country-Income | OR (95%CI) | I2 (%) |
|---|---|---|---|
| Before eating | Low | 1.36 [1.12,1.66] | 14.8 |
| Lower middle a | 1.29 [1.17,1.43] | 50.8 | |
| Upper middle | 1.39 [1.22,1.57] | 59.7 | |
| High | 1.38 [1.17,1.62] | 45.7 | |
| Overall | 1.34 [1.25,1.43] | 48.2 | |
| After using toilet | Low | 1.42 [1.19,1.70] | 54.8 |
| Lower middle | 1.49 [1.34,1.66] | 35.8 | |
| Upper middle | 1.82 [1.58,2.09] | 51.3 | |
| High | 2.00 [1.62,2.49] | 0.0 | |
| Overall | 1.61 [1.50,1.73] | 41.3 | |
| Soap | Low | 1.34 [1.17,1.52] | 62.8 |
| Lower middle b | 1.26 [1.13,1.40] | 50.4 | |
| Upper middle | 1.63 [1.45,1.84] | 67.7 | |
| High | 1.82 [1.52,2.18] | 0.0 | |
| Overall | 1.44 [1.35,1.53] | 57.4 |
Abbreviation: OR Odds ratio; CI Confidence interval; Country-wise estimates were adjusted for age and sex; a Laos was not included because estimates could not be obtained due to small numbers; b Laos and Northern Macedonia were not included because estimates could not be obtained due to small numbers.
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Smith, L.; Butler, L.; Tully, M.A.; Jacob, L.; Barnett, Y.; López-Sánchez, G.F.; López-Bueno, R.; Shin, J.I.; McDermott, D.; Pfeifer, B.A.; et al. Hand-Washing Practices among Adolescents Aged 12–15 Years from 80 Countries. Int. J. Environ. Res. Public Health 2021, 18, 138. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18010138
AMA Style
Smith L, Butler L, Tully MA, Jacob L, Barnett Y, López-Sánchez GF, López-Bueno R, Shin JI, McDermott D, Pfeifer BA, et al. Hand-Washing Practices among Adolescents Aged 12–15 Years from 80 Countries. International Journal of Environmental Research and Public Health. 2021; 18(1):138. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18010138
Chicago/Turabian StyleSmith, Lee, Laurie Butler, Mark A Tully, Louis Jacob, Yvonne Barnett, Guillermo F. López-Sánchez, Rubén López-Bueno, Jae Il Shin, Daragh McDermott, Briona A. Pfeifer, and et al. 2021. "Hand-Washing Practices among Adolescents Aged 12–15 Years from 80 Countries" International Journal of Environmental Research and Public Health 18, no. 1: 138. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18010138
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