| Literature DB >> 25404069 |
Kebede Deribe, Simon J Brooker, Rachel L Pullan, Heven Sime, Abeba Gebretsadik, Ashenafi Assefa, Amha Kebede, Asrat Hailu, Maria P Rebollo, Oumer Shafi, Moses J Bockarie, Abraham Aseffa, Richard Reithinger, Jorge Cano, Fikre Enquselassie, Melanie J Newport, Gail Davey.
Abstract
Although podoconiosis is one of the major causes of tropical lymphoedema and is endemic in Ethiopia its epidemiology and risk factors are poorly understood. Individual-level data for 129,959 individuals from 1,315 communities in 659 woreda (districts) were collected for a nationwide integrated survey of lymphatic filariasis and podoconiosis. Blood samples were tested for circulating Wuchereria bancrofti antigen using immunochromatographic card tests. A clinical algorithm was used to reach a diagnosis of podoconiosis by excluding other potential causes of lymphoedema of the lower limb. Bayesian multilevel models were used to identify individual and environmental risk factors. Overall, 8,110 of 129,959 (6.2%, 95% confidence interval [CI] 6.1-6.4%) surveyed individuals were identified with lymphoedema of the lower limb, of whom 5,253 (4.0%, 95% CI 3.9-4.1%) were confirmed to be podoconiosis cases. In multivariable analysis, being female, older, unmarried, washing the feet less frequently than daily, and being semiskilled or unemployed were significantly associated with increased risk of podoconiosis. Attending formal education and living in a house with a covered floor were associated with decreased risk of podoconiosis. Podoconiosis exhibits marked geographical variation across Ethiopia, with variation in risk associated with variation in rainfall, enhanced vegetation index, and altitude. © The American Society of Tropical Medicine and Hygiene.Entities:
Mesh:
Year: 2014 PMID: 25404069 PMCID: PMC4288951 DOI: 10.4269/ajtmh.14-0446
Source DB: PubMed Journal: Am J Trop Med Hyg ISSN: 0002-9637 Impact factor: 2.345
Figure 1.Conceptual framework to represent the relationship between environmental, household, and individual-level variables. Environmental variables such as climate, topography, flora, and fauna of the areas are important factors for generation of soil and to determine the characteristics of the soil. Soil physical and chemical properties including type of soil, particle size, morphology, pH, etc., are important factors, which either facilitate the penetration of skin barriers by putative mineral particles or increase exposure to them. Socioeconomic status affects household factors such as floor condition, access to water, and individual factors such as shoe ownership and foot hygiene practices, which in turn affect the risk of podoconiosis. Genetic susceptibility is an important factor in determining the outcome of the exposure, and is best measured by pedigree study. In the current study, we only measured the familial history of a similar condition. The underlined variables are those measured in the current analysis. The framework guided the analysis; principal component analysis was used to identify important covariates, which explained most of the variation among many multicollinear environmental and climate variables. Subsequently, a multilevel mixed-effects logistic regression model was developed using a likelihood-based approach, with random intercepts for village and woreda, for environment and individual variables separately, to identify candidate variables for the geostatistical model. Bayesian hierarchical models were developed to identify and measure the relative contributions of the risk factors for podoconiosis.
Figure 2.Podoconiosis diagnosis algorithm used in the national survey in Ethiopia 2013.
Figure 3.Age and sex disaggregated prevalence of podoconiosis among adults 15 years of age and above in Ethiopia. The two graphs show that as age increases, the prevalence of podoconiosis increases. Higher prevalence is recorded among females in all age categories as compared to males.
Descriptive statistics of people with podoconiosis ≥ 15 years of age in Ethiopia*
| Variable | Number (%) |
|---|---|
| Gender Female | 3045 (58.0) |
| Male | 2208 (42.0) |
| Age group: 15–24 | 538 (10.24) |
| 25–34 | 918 (17.48) |
| 35–44 | 1119 (21.30) |
| 45–54 | 1064 (20.26) |
| 55–64 | 868 (16.52) |
| > = 65 | 746 (14.20) |
| Marital status | |
| Unmarried | 557 (10.6) |
| Married | 3722 (70.9) |
| Divorced | 272 (5.2) |
| Widowed | 702 (13.4) |
| Duration of podoconiosis Mean (SD) | 25.04 (14.58) |
| Shoe wearing duration in years Mean (SD) | 22.42 (14.76) |
| Disease stage | |
| Stage 1 | 875 (16.7) |
| Stage 2 | 2562 (48.8) |
| Stage 3 | 1399 (26.6) |
| Stage 4 | 308 (5.9) |
| Stage 5 | 109 (2.1) |
| Occupation professional | 68 (1.3) |
| Semiskilled | 3488 (66.2) |
| Unemployed | 1705 (32.5) |
| Residence rural | 4467 (85.0) |
| Urban | 786 (15.0) |
| Ever attended school | |
| Yes | 1087 (20.7) |
| No | 4166 (79.3) |
| Literacy no formal education | 4166 (79.3) |
| Primary (1–8) | 906 (17.2) |
| Secondary (9+) | 181 (3.4) |
| Family history of leg swelling | |
| Yes | 1192 (22.7) |
| No | 4061 (77.3) |
| Number in family with leg swelling, dead or alive ( | 1.44 (1.73) |
| 1 | 857 (71.9) |
| 2 | 222 (18.6) |
| 3 | 74 (6.2) |
| >3 | 39 (3.3) |
| Age at first noticing the swelling Mean (SD) | 24.67 (15.06) |
| < 10 | 630 (12.0) |
| 10–19 | 1395 (26.6) |
| 20–29 | 1335 (25.4) |
| 30–39 | 898 (17.1) |
| 40–49 | 567 (10.8) |
| ≥ 50 | 428 (8.1) |
| Years lived with swelling | |
| < 10 | 1817 (34.6) |
| 10–19 | 1478 (28.1) |
| 20–29 | 918 (17.5) |
| 30–39 | 555 (10.6) |
| 40–49 | 318 (6.1) |
| > = 50 | 167 (3.2) |
In total 5,253 individuals with podoconiosis were identified among 129,559 surveyed individuals.
Certified professional.
Not-certified.
Currently not employed and dependent on others for living.
Figure 4.The geographical distribution of the prevalence of podoconiosis among adults ≥ 15 years of age in Ethiopia, 2013.
Summary statistics of the reduced set of climatic and environmental covariates included in model building
| Variable | Median (range) |
|---|---|
| Climate | |
| Mean annual temperature (°C) | 19.0 (10.0–31.0) |
| Annual rainfall (mm) | 1042 (139–2090) |
| Environmental | |
| Altitude (meters) | 1895 (−105 to 3238) |
| Savannah or Grasslands | 27.67% |
| Urban classification (%) | 26.8% urban |
| Population density (km2) | 129.0 (0.82–92863) |
| Enhanced vegetation index (EVI) | 0.27 (0.04–0.56) |
| Distance to nearest surface water (km) | 6.4 (0–144) |
| Fine soil texture (%) | 43.13% |
| pH of the water in the soil | 6.20 (4.60–9.3) |
| Slope of the land (°) | 1.67 (0.01–17.75) |
| Clay content (%) | 35.5 (17–60) |
| Sand content (%) | 30 (10–71) |
| Silt content (%) | 32 (9–50) |
| High activity soil (%) | 76.56% |
Proportion of sites for binary variables (Savannah/Grasslands, urban classification, fine soil texture, clay content, sand content, silt content, heavy activity soil).
Reclassified from global land cover.
Adjusted odds m of individual, household, and geographical risk factors of podoconiosis using a Bayesian model and data from 1,313 villages throughout Ethiopia
| Variable | Category | Adjusted 95% Bayesian credible intervals (BCI) |
|---|---|---|
| OR (95% BCI) | ||
| Sex | Male | 1.0 |
| Female | 1.3 (1.2–1.4) | |
| Age in years (continuous) | 1.02 (1.02–1.03) | |
| Education | No formal education | 1.0 |
| Primary 1–8 | 0.6 (0.6–0.7) | |
| Secondary 9–12 | 0.3 (0.3–0.4) | |
| Post-secondary > 2 | 0.1 (0.1–0.2) | |
| Marital status | Married | 1.0 |
| Unmarried | 1.4 (1.3–1.5) | |
| Religion | Muslim | 1.0 |
| Other | 3.4 (3.1–3.6) | |
| How often do you wash your legs? | Daily or more often | 1.0 |
| Two-three times a week | 0.9 (0.8–1.0) | |
| Weekly or less often | 2.9 (2.4–3.4) | |
| Occupation: | Professional | 1.0 |
| Semiskilled | 2.4 (1.9–3.0) | |
| Unemployed | 2.2 (1.7–2.8) | |
| Type of floor | Mud/earth | 1.0 |
| Cement/wood/plastic | 0.3 (0.3–0.4) | |
| Enhanced vegetation index (EVI) | < 0.2 | 1.0 |
| 0.2–0.4 | 0.6 (0.5–0.6) | |
| > 0.4 | 0.4 (0.3–0.4) | |
| Mean annual rainfall | 1,000 | 1.0 |
| > = 1,000 | 1.1 (1.0–1.1) | |
| Altitude | < 1,000 | 1.0 |
| 1,000–2,800 | 1.3 (1.2–1.4) | |
| > 2,800 | 1.8 (1.5–2.1) | |
| Range of the spatial effect [range in km] | 31.1 (6.1–198.0) | |
| Spatial variance | 0.253 (0.252–0.490) |
Significant.
Figure 5.Graph showing age at first shoe use by age among adults 15 years of age and above in Ethiopia. The graph shows a decreasing secular trend of age at first wearing shoes: the younger age groups tend to start wearing shoes at an earlier age than the older age groups.