| Literature DB >> 33925753 |
Samuel Kwasi Opoku1, Walter Leal Filho1, Fudjumdjum Hubert1, Oluwabunmi Adejumo2.
Abstract
Climate change is a global problem, which affects the various geographical regions at different levels. It is also associated with a wide range of human health problems, which pose a burden to health systems, especially in regions such as Africa. Indeed, across the African continent public health systems are under severe pressure, partly due to their fragile socioeconomic conditions. This paper reports on a cross-sectional study in six African countries (Ghana, Nigeria, South Africa, Namibia, Ethiopia, and Kenya) aimed at assessing their vulnerabilities to climate change, focusing on its impacts on human health. The study evaluated the levels of information, knowledge, and perceptions of public health professionals. It also examined the health systems' preparedness to cope with these health hazards, the available resources, and those needed to build resilience to the country's vulnerable population, as perceived by health professionals. The results revealed that 63.1% of the total respondents reported that climate change had been extensively experienced in the past years, while 32% claimed that the sampled countries had experienced them to some extent. Nigerian respondents recorded the highest levels (67.7%), followed by Kenya with 66.6%. South Africa had the lowest level of impact as perceived by the respondents (50.0%) when compared with the other sampled countries. All respondents from Ghana and Namibia reported that health problems caused by climate change are common in the two countries. As perceived by the health professionals, the inadequate resources reiterate the need for infrastructural resources, medical equipment, emergency response resources, and technical support. The study's recommendations include the need to improve current policies at all levels (i.e., national, regional, and local) on climate change and public health and to strengthen health professionals' skills. Improving the basic knowledge of health institutions to better respond to a changing climate is also recommended. The study provides valuable insights which may be helpful to other nations in Sub-Saharan Africa.Entities:
Keywords: climate change impacts; health professionals; health systems; preparedness African countries
Year: 2021 PMID: 33925753 PMCID: PMC8124714 DOI: 10.3390/ijerph18094672
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Relations between climate change and some of its health impacts. Source: authors.
Figure 2Africa map highlighting the countries studied.
A systematic review of the sampled countries’ literature to determine their vulnerabilities to the five significant climate change impacts: their exposure to climate drivers, the study location, and the potential resulting outcome from the exposure (see Appendix A). This was developed as a measure of the sampled country’s intensity to climate impacts on human health and the health systems’ preparedness against the impacts through the survey.
| Impacts | Author (Year) | Study Period (Year) | City/Country | Study Population | Study Design/Statistical Model | Exposure | Outcome |
|---|---|---|---|---|---|---|---|
|
| [ | 2012 | Jamestown/Agbogbloshie (Ghana) | 401 Households | Cross-sectional Descriptive, bivariate, and Multivariate | Floods | Reported cases of diarrheal diseases. A strong correlation between flooding and diarrheal disease. |
| [ | 1990–2011 | North-West | Morbidity and mortality dataset on cholera cases | Ecological. Stepwise multiple regression, G.A.M. | Min/Max temp, annual Temp and RH | A significant correlation between cholera and annual min/max temperature and rainfall with 1716 deaths from 41,784 cases in 2010 in 18 states. | |
| [ | 2012–2014 | Cape Town (South Africa) | Surveillance database on 58,617 children under five years. | Poisson regression | Min and Max temp | A 32% to 40% increase in diarrhoea incidence at 5 oC increase in Min and Max Temp. | |
| [ | 2013–2015 | Amhara region | Retrospective data on children under five years | Ecological | Average monthly Temp and rainfall | A monthly incidence rate of childhood diarrhoea at 11.4 per 1000 (95% Cl) was significantly associated with mean average temperature and rainfall. | |
| [ | 1991–1993 | Hospital-Based (Malindi). (Kenya). | 862 children under five years old | Case-control | Rainfall and Temperature | A strong positive correlation between rainfall, temperature, and childhood bloody diarrhoea. | |
| [ | 1995–2006 | National | Reported cases of malaria ranging from 5054 to 347,000 per 100,000 | Ecological | Rainfall, temperature, and humidity | A statistically significant correlation between temperature, humidity, and malaria incidence with a less significant association with rainfall as it only predicted malaria prevalence. | |
| [ | 1998–2008 | Ondo state | Data on weather variability; cases of malaria in 18 government hospitals | Ecological | Air and sea surface temp. | The occurrence of monthly malaria of 53.4% and 29% at 1 oC increase in air and sea surface temp. | |
| [ | 1998–2017 | Mutale (Limpopo province) | Malaria and climate data | Ecological | Temp. Rainfall | A positive significant association malaria incidence and total monthly rainfall, min and max temp., average temp., and mean relative humidity. | |
| [ | 1989–2009 | Amhara, SNNPR, Tigray, Oromia (Ethiopia) | Data on cases of visceral leishmaniasis cases and meteorological data | Ecological | Annual average Temp. and rainfall | 94.7% of | |
| [ | 2004–2014 | Baringo county. | Malaria data from 10 health facilities; meteorological data | Ecological | Rainfall and Temp. | Rainfall increased malaria transmission across four zones at a time lag of 2 months while temp. increased cases of malaria in riverine and highland zones at time lad of 0 and one month. | |
|
| [ | Secondi-Takoradi | 207 heads of households | Mixed cross-sectional | Floods | Report of psychological, environmental, and economic problems; disease outbreaks (malaria, cholera, and dysentery). | |
| (Eludoyin et al., 2013 [ | 1951–2009; 2003–2012 | National | Secondary data | Ecological | Extreme temperature | Population experience of thermal stress since year 2000 and a significant heat rash among the population between September and December from 2003 to 2012. | |
| [ | 2011–2012 | Ohangwena, Oshana, Omusata | 282 households | Cross-sectional | Floods | A remarkable but unspecified number of deaths, injuries, illness from resulting floods. | |
| [ | 2006–2010 | Cape Town, Durban, J’berg | Ambient temperature-all-cause mortality | Case-cross over epidemiological design | Ambient Temp. | Increased temperature above the city-specific threshold significantly increased the general population risk of death (number not specified). | |
| [ | 2009–2014 | National survey | 55,219 children under five years old | Meta-analysis | Drought | Minimal food-insecure areas showed elevated U5DR compared to stressed food-insecure areas as death rate increases as the prevalence of acute malnutrition increases. | |
|
| [ | 2016 | Bongo District | 246 Mother–child pairs | Mixed-method cross-sectional | Drought | Malnutrition and food insecurity resulted from drought impact, 97.2% being food insecure; children stunting (42.3%), underweight (24.4%) and wasting (17.5%). |
| [ | 2015 | National data | Food and crop production index, population density, annual average temp, and rainfall. | Ecological | Floods, drought, land use and cover change. | Country’s food deficit due to low agricultural production; hence the country’s dependence on food import. Malnutrition resulting from food insecurity. | |
| [ | 2013–2014 | Dubana and Kwathehle | Children between 24 and 59 months and their caregivers | Cross-sectional | Summer and winter season | Hunger due to food insecurity was reported in the summer rather than in the winter though their difference in food consumption score was not statistically significant. | |
| [ | 2014 | All regions | National | Ecological study | Drought | A frequent drought increased population food insecurity from 10% to 15%. | |
| [ | 2009–2013 | Marsabit district | Children under five years old; 924 households | Panel study | Drought | Approximately 20% of the children under study were malnourished. | |
|
| [ | 2015 | Kwaebibrim (History of a flood), West Akyem (no history of a flood) | 400 respondents; 200 from each district | Retrospective cohort study | Floods | Flood victims more likely to experience symptoms of mental health problems than the non-victims. Reports of significantly higher levels of obsessive compulsion, depression, anxiety, and other global severity indexes. |
| [ | 2012 | Urban areas affected by floods. | 100 victims of flood-induced crime | Cross-sectional | Flooding | Flood-induced crime harms human health and wellbeing with possible effects of anxiety, depression, social dysfunction, and loss of confidence. | |
| [ | 2018 | National | Whole population | Systematic review | Extreme weather events | Population affected by multiple health and social stressors. |
Source: From authors.
The number of respondents from the sampled countries.
| Country | Number of Respondents | % of the Total |
|---|---|---|
| Ghana | 31 | 25.4% |
| Nigeria | 31 | 25.4% |
| South Africa | 18 | 14.8% |
| Namibia | 11 | 9.0% |
| Ethiopia | 19 | 15.6% |
| Kenya | 12 | 9.8% |
| Total | 122 | 100% |
Source: From authors.
Respondents’ workplaces.
| Country | Government Agencies | Higher Institutions | Non-Governmental Agencies | Research Institutions | Total within the Country |
|---|---|---|---|---|---|
| Ethiopia | 21.0% | 47.4% | 31.6% | 0.0% | 100.0% |
| Ghana | 46.6% | 26.7% | 6.7% | 20.0% | 100.0% |
| Kenya | 27.2% | 36.4% | 0.0% | 36.4% | 100.0% |
| Namibia | 45.4% | 27.3% | 27.3% | 0.0% | 100.0% |
| Nigeria | 21.2% | 45.5% | 21.2% | 12.1% | 100.0% |
| South Africa | 22.2% | 44.4% | 5.6% | 27.8% | 100.0% |
| % of the total | 30.3% | 38.5% | 15.6% | 15.6% | 100.0% |
Source: From authors.
Respondents’ understanding of climate change and human health impacts.
| Country | Yes, a Lot | Yes, Some | Yes, Little | Total within the Country |
|---|---|---|---|---|
| Ghana | 19.4% | 61.3% | 19.3% | 100% |
| Nigeria | 42.0% | 54.8% | 3.2% | 100% |
| South Africa | 22.2% | 44.5% | 33.3% | 100% |
| Namibia | 0.0 | 72.7% | 27.3% | 100% |
| Ethiopia | 52.6% | 42.1% | 5.3% | 100% |
| Kenya | 16.7% | 75.0% | 8.3% | 100% |
| % of Total | 28.7% | 56.6% | 14.7% | 100% |
Source: From authors.
Sampled countries’ diseases trend from the past until now as perceived by respondents.
| Country | Increased | No Changes | Decreased | I Do Not Know | Total within the Country |
|---|---|---|---|---|---|
| Ghana | 71.0% | 16.1% | 9.7% | 3.2% | 100% |
| Nigeria | 80.6% | 19.4% | 0.0% | 0.0% | 100% |
| South Africa | 66.7% | 16.7% | 5.5% | 11.1% | 100% |
| Namibia | 81.8% | 9.1% | 9.1% | 0.0% | 100% |
| Ethiopia | 68.5% | 10.5% | 10.5% | 10.5% | 100% |
| Kenya | 75.0% | 0% | 16.7% | 8.3% | 100% |
| % of Total | 73.8% | 13.9% | 7.4% | 4.9% | 100% |
Source: From authors.
Respondents’ perceptions of the health system’s preparedness in dealing with the health impacts of climate (CI) change in sampled countries. Numbers are assigned to their respective survey questions on top of the table. Even though percentages summed up to 100, this table’s options are of greater importance to this study (see Appendix A). This applies to all other subsequent tables with similar instances. All percentages are recorded within each country’s number of respondents to identify specific features better.
| Country | 1. Preparedness a Priority in the Country | Yes, but a Little | No, Not at All |
|---|---|---|---|
| 7. Preparedness to Respond to Extreme Events | Fairly Well Prepared | Not so Much Prepared | |
|
| 1. | 58.1% | 22.6% |
| 2. | 61.3% | 22.6% | |
| 3. | 77.4% | 6.5% | |
| 4. | 83.9% | 12.9% | |
| 5. | 67.7% | 16.1% | |
| 6. | 83.9% | 12.9% | |
| 7. | 45.2% | 48.4% | |
|
| 1. | 58.1% | 25.8% |
| 2. | 51.6% | 22.6% | |
| 3. | 64.5% | 29.0% | |
| 4. | 67.7% | 19.4% | |
| 5. | 67.7% | 22.6% | |
| 6. | 61.3% | 25.8% | |
| 7. | 25.8% | 71.0% | |
|
| 1. | 33.3% | 16.7% |
| 2. | 66.7% | 5.6% | |
| 3. | 55.6% | 27.8% | |
| 4. | 50.0% | 27.8% | |
| 5. | 72.2% | 16.7% | |
| 6. | 55.6% | 16.7% | |
| 7. | 44.4% | 44.4% | |
|
| 1. | 45.5% | 27.3% |
| 2. | 45.5% | 27.3% | |
| 3. | 54.5% | 9.1% | |
| 4. | 63.6% | 27.3% | |
| 5. | 36.4% | 45.5% | |
| 6. | 45.5% | 45.5% | |
| 7. | 19.2% | 72.7% | |
|
| 1. | 57.9% | 10.5% |
| 2. | 78.9% | 0.0% | |
| 3. | 94.7% | 0.0% | |
| 4. | 73.7% | 21.1% | |
| 5. | 52.6% | 42.1% | |
| 6. | 52.6% | 36.8% | |
| 7. | 47.4% | 47.4% | |
|
| 1. | 41.7% | 41.7% |
| 2. | 66.7% | 16.7% | |
| 3. | 75.0% | 8.3% | |
| 4. | 66.7% | 25.0% | |
| 5. | 50.0% | 33.3% | |
| 6. | 50.0% | 25.0% | |
| 7. | 50.0% | 47.1% |
Source: From authors.
Sampled countries’ intervention programs to deal with the health impacts of climate change as perceived by respondents.
| Country | Control of Climate Impacts | Available, but Not | Not |
|---|---|---|---|
|
| 1. | 77.4% | 3.2% |
|
| 1. | 45.2% | 16.1% |
|
| 1. | 66.7% | 0.0% |
|
| 1. | 63.6% | 0.00% |
|
| 1. | 52.6% | 00% |
|
| 1. | 58.3% | 16.7% |
Source: From authors.
Respondents’ perception of sampled country’s disaster relief agencies/organisations helps victims of extreme food distribution and shelter victims.
| Country | Percentages of ‘Not Enough’ as Reported by Respondents |
|---|---|
| Ghana | 77.4% |
| Nigeria | 64.5% |
| South Africa | 50.0% |
| Namibia | 81.8% |
| Ethiopia | 78.9% |
| Kenya | 58.3% |
Source: From authors.
Technical support from sampled countries’ government and the needed funding/budget in developing preparedness plans and communicating with the public about climate change’s health effects, as perceived by respondents.
| Country | 1. Climate Change Incorporated into Public Health Interventions | Yes, but a Little | No, Not at All |
|---|---|---|---|
| 2. Technical Support from the Government | |||
| 3. Budget/Funding Needed | Perceived Percentage Funding/Budget Needed | ||
|
| 83.9% | 12.9% | |
|
| 77.4% | 16.1% | |
|
| 90.3% | ||
|
|
| 41.9% | 32.3% |
|
| 64.5% | 22.6% | |
|
|
| ||
|
|
| 38.9% | 22.2% |
|
| 22.2% | 44.4% | |
|
|
| ||
|
|
| 54.5% | 27.3% |
|
| 27.3% | 27.3% | |
|
|
| ||
|
|
| 63.2% | 21.1% |
|
| 47.4% | 42.1% | |
|
|
| ||
|
|
| 58.3% | 25.0% |
|
| 50.0% | 25.0% | |
|
|
| ||
Source: From authors.
Respondents’ perceptions about the health system’s available resources and those needed to curb climate change (CC) impact human health in the sampled countries.
| Country | 1. Available Resources to Deal with Health Impact of CC | Limited Availability (%) |
|---|---|---|
| 2. Expand and Construct More Hospital and Health Centres. | Needed Resources Perceived (% within a Country) | |
|
| 1. | 61.9% |
| 2. | 83.9% | |
| 3. | 74.2% | |
| 4. | 83.9% | |
| 5. | 83.9% | |
| 6. | 77.4% | |
| 7. | 90.3% | |
|
| 1. | 61.3% |
| 2. | 80.6% | |
| 3. | 77.4% | |
| 4. | 90.3% | |
| 5. | 90.3% | |
| 6. | 87.1% | |
| 7. | 93.5% | |
|
| 1. | 66.7% |
| 2. | 61.1% | |
| 3. | 55.6% | |
| 4. | 94.4% | |
| 5. | 55.5% | |
| 6. | 44.4% | |
| 7. | 66.7% | |
|
| 1. | 90.9% |
| 2. | 66.6% | |
| 3. | 72.7% | |
| 4. | 81.8% | |
| 5. | 81.8% | |
| 6. | 72.7% | |
| 7. | 63.6% | |
|
| 1. | 68.4% |
| 2. | 78.9% | |
| 3. | 89.5% | |
| 4. | 94.7% | |
| 5. | 84.2% | |
| 6. | 78.9% | |
| 7. | 84.4% | |
|
| 1. | 75.0% |
| 2. | 75.0% | |
| 3. | 66.7% | |
| 4. | 91.7% | |
| 5. | 75.0% | |
| 6. | 75.0% | |
| 7. | 66.7% |
Source: From authors.