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Historical Perspective and Risk of Multiple Neglected Tropical Diseases in Coastal Tanzania: Compositional and Contextual Determinants of Disease Risk.

Armah FA, Quansah R, Luginaah I, Chuenpagdee R, Hambati H, Campbell G - PLoS Negl Trop Dis (2015)

Bottom Line: The results show that the effect size in decreasing order of magnitude for non-binary predictors of NTD risks is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity.First, it suggests that localities of high burden of NTDs are likely to diminish within statistical averages at higher (regional or national) levels.Second, it indicates that curative or preventive interventions will become more efficient provided they can be focused on the localities, particularly as populations in these localities are likely to be burdened by several NTDs simultaneously, further increasing the imperative of multi-disease interventions.

View Article: PubMed Central - PubMed

Affiliation: Environmental Health and Hazards Laboratory, Department of Geography, University of Western Ontario, London, Ontario, Canada.

ABSTRACT

Background: In the past decade, research on neglected tropical diseases (NTDs) has intensified in response to the need to enhance community participation in health delivery, establish monitoring and surveillance systems, and integrate existing disease-specific treatment programs to control overlapping NTD burdens and detrimental effects. In this paper, we evaluated the geographical distribution of NTDs in coastal Tanzania.

Methods and findings: We also assessed the collective (compositional and contextual) factors that currently determine risks to multiple NTDs using a cross sectional survey of 1253 individuals in coastal Tanzania. The results show that the effect size in decreasing order of magnitude for non-binary predictors of NTD risks is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity. The multivariate analysis explained 95% of the variance in the relationship between NTD risks and the theoretically-relevant covariates. Compositional (biosocial and sociocultural) factors explained more variance at the neighbourhood level than at the regional level, whereas contextual factors, such as access to health services and household quality, in districts explained a large proportion of variance at the regional level but individually had modest statistical significance, demonstrating the complex interactions between compositional and contextual factors in generating NTD risks.

Conclusions: NTD risks were inequitably distributed over geographic space, which has several important policy implications. First, it suggests that localities of high burden of NTDs are likely to diminish within statistical averages at higher (regional or national) levels. Second, it indicates that curative or preventive interventions will become more efficient provided they can be focused on the localities, particularly as populations in these localities are likely to be burdened by several NTDs simultaneously, further increasing the imperative of multi-disease interventions.

No MeSH data available.


Related in: MedlinePlus

Map of Tanzania showing the study areas.
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pntd.0003939.g002: Map of Tanzania showing the study areas.

Mentions: Tanzania is a coastal country lying between longitude 29° and 49° East and latitude 1° and 12° south of the Equator [20] (Fig 2). The marine waters comprise 64 000 km2 as territorial waters and 223 000 km2 as offshore waters (EEZ) [21]. Tanzania’s coastline stretches for 800km. It has five coastal regions-Tanga, Pwani, Dar-es-Salaam, Lindi and Mtwara. The five coastal regions cover about 15 percent of the country’s total land area and are home to approximately 25 percent of the country’s population [22]. According to the 2012 Population and Housing census, the total population was 44,928,923 compared to 12,313,469 in 1967 [23], reflecting an annual growth rate of 2.9 percent. The under 15 age group represented 44.1 percent of the population, with 35.5 percent being in the 15–35 age group, 52.2 percent being in the 15–64 age group, and 3.8 percent being older than 64 [23]. Overall Tanzania on average is sparsely populated with population density of 51 persons per square kilometer, lower significant variation exists across regions. The population density varies from 1 person per square kilometre in arid regions to 51 per square kilometre in the mainland's well-watered highlands to 134 per square kilometre in Zanzibar [24]. The population density for the Dar es Salaam region is 3,133 persons per km2 (the most densely populated) and that of Lindi is only 13.1 persons per km2 [23]. This suggests wide disparities in population density across regions. This study specifically focuses on Dar-es-Salaam, Pwani and Tanga. The 3 coastal regions selected for analysis were chosen for two main reasons. First, the three regions are of historical significance to the Indian Ocean World project. Second, these regions were selected because of the 5 regions, they are the most ethnically diverse (that is, representative of the different geographical locations) and thus, had better prospects of providing heterogeneous survey responses. Dar es Salaam is the capital of the Dar es Salaam Region, which is one of Tanzania's 26 administrative regions. The Dar es Salaam Region consists of three local government areas or administrative districts: Kinondoni to the north, Ilala in the center of the region, and Temeke to the south. Pwani (coast) is the 21st most densely populated region. It is bordered to the north by the Tanga Region, to the east by the Dar es Salaam Region and the Indian Ocean, to the south by the Lindi Region, and to the west by the Morogoro Region. Tanga region has a population of 2,045,205 [24]. It is bordered by Kenya and Kilimanjaro Region to the north; Manyara Region to the west; and Morogoro and Pwani regions to the south. Its eastern border is formed by the Indian Ocean.


Historical Perspective and Risk of Multiple Neglected Tropical Diseases in Coastal Tanzania: Compositional and Contextual Determinants of Disease Risk.

Armah FA, Quansah R, Luginaah I, Chuenpagdee R, Hambati H, Campbell G - PLoS Negl Trop Dis (2015)

Map of Tanzania showing the study areas.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4524715&req=5

pntd.0003939.g002: Map of Tanzania showing the study areas.
Mentions: Tanzania is a coastal country lying between longitude 29° and 49° East and latitude 1° and 12° south of the Equator [20] (Fig 2). The marine waters comprise 64 000 km2 as territorial waters and 223 000 km2 as offshore waters (EEZ) [21]. Tanzania’s coastline stretches for 800km. It has five coastal regions-Tanga, Pwani, Dar-es-Salaam, Lindi and Mtwara. The five coastal regions cover about 15 percent of the country’s total land area and are home to approximately 25 percent of the country’s population [22]. According to the 2012 Population and Housing census, the total population was 44,928,923 compared to 12,313,469 in 1967 [23], reflecting an annual growth rate of 2.9 percent. The under 15 age group represented 44.1 percent of the population, with 35.5 percent being in the 15–35 age group, 52.2 percent being in the 15–64 age group, and 3.8 percent being older than 64 [23]. Overall Tanzania on average is sparsely populated with population density of 51 persons per square kilometer, lower significant variation exists across regions. The population density varies from 1 person per square kilometre in arid regions to 51 per square kilometre in the mainland's well-watered highlands to 134 per square kilometre in Zanzibar [24]. The population density for the Dar es Salaam region is 3,133 persons per km2 (the most densely populated) and that of Lindi is only 13.1 persons per km2 [23]. This suggests wide disparities in population density across regions. This study specifically focuses on Dar-es-Salaam, Pwani and Tanga. The 3 coastal regions selected for analysis were chosen for two main reasons. First, the three regions are of historical significance to the Indian Ocean World project. Second, these regions were selected because of the 5 regions, they are the most ethnically diverse (that is, representative of the different geographical locations) and thus, had better prospects of providing heterogeneous survey responses. Dar es Salaam is the capital of the Dar es Salaam Region, which is one of Tanzania's 26 administrative regions. The Dar es Salaam Region consists of three local government areas or administrative districts: Kinondoni to the north, Ilala in the center of the region, and Temeke to the south. Pwani (coast) is the 21st most densely populated region. It is bordered to the north by the Tanga Region, to the east by the Dar es Salaam Region and the Indian Ocean, to the south by the Lindi Region, and to the west by the Morogoro Region. Tanga region has a population of 2,045,205 [24]. It is bordered by Kenya and Kilimanjaro Region to the north; Manyara Region to the west; and Morogoro and Pwani regions to the south. Its eastern border is formed by the Indian Ocean.

Bottom Line: The results show that the effect size in decreasing order of magnitude for non-binary predictors of NTD risks is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity.First, it suggests that localities of high burden of NTDs are likely to diminish within statistical averages at higher (regional or national) levels.Second, it indicates that curative or preventive interventions will become more efficient provided they can be focused on the localities, particularly as populations in these localities are likely to be burdened by several NTDs simultaneously, further increasing the imperative of multi-disease interventions.

View Article: PubMed Central - PubMed

Affiliation: Environmental Health and Hazards Laboratory, Department of Geography, University of Western Ontario, London, Ontario, Canada.

ABSTRACT

Background: In the past decade, research on neglected tropical diseases (NTDs) has intensified in response to the need to enhance community participation in health delivery, establish monitoring and surveillance systems, and integrate existing disease-specific treatment programs to control overlapping NTD burdens and detrimental effects. In this paper, we evaluated the geographical distribution of NTDs in coastal Tanzania.

Methods and findings: We also assessed the collective (compositional and contextual) factors that currently determine risks to multiple NTDs using a cross sectional survey of 1253 individuals in coastal Tanzania. The results show that the effect size in decreasing order of magnitude for non-binary predictors of NTD risks is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity. The multivariate analysis explained 95% of the variance in the relationship between NTD risks and the theoretically-relevant covariates. Compositional (biosocial and sociocultural) factors explained more variance at the neighbourhood level than at the regional level, whereas contextual factors, such as access to health services and household quality, in districts explained a large proportion of variance at the regional level but individually had modest statistical significance, demonstrating the complex interactions between compositional and contextual factors in generating NTD risks.

Conclusions: NTD risks were inequitably distributed over geographic space, which has several important policy implications. First, it suggests that localities of high burden of NTDs are likely to diminish within statistical averages at higher (regional or national) levels. Second, it indicates that curative or preventive interventions will become more efficient provided they can be focused on the localities, particularly as populations in these localities are likely to be burdened by several NTDs simultaneously, further increasing the imperative of multi-disease interventions.

No MeSH data available.


Related in: MedlinePlus