| Literature DB >> 28335490 |
Astrid M Knoblauch1,2, Mark J Divall3, Milka Owuor4, Colleen Archer5, Kennedy Nduna6, Harrison Ng'uni7, Gertrude Musunka8, Anna Pascall9, Jürg Utzinger10,11, Mirko S Winkler12,13.
Abstract
The epidemiology of malaria, anaemia and malnutrition in children is potentially altered in mining development areas. In a copper extraction project in northwestern Zambia, a health impact assessment (HIA) was commissioned to predict, manage and monitor health impacts. Two cross-sectional surveys were conducted: at baseline prior to project development (2011) and at four years into development (2015). Prevalence of Plasmodium falciparum, anaemia and stunting were assessed in under-five-year-old children, while hookworm infection was assessed in children aged 9-14 years in communities impacted and comparison communities not impacted by the project. P. falciparum prevalence was significantly higher in 2015 compared to 2011 in both impacted and comparison communities (odds ratio (OR) = 2.51 and OR = 6.97, respectively). Stunting was significantly lower in 2015 in impacted communities only (OR = 0.63). Anaemia was slightly lower in 2015 compared to baseline in both impacted and comparison communities. Resettlement due to the project and migration background (i.e., moving into the area within the past five years) were generally associated with better health outcomes in 2015. We conclude that repeated cross-sectional surveys to monitor health in communities impacted by projects should become an integral part of HIA to deepen the understanding of changing patterns of health and support implementation of setting-specific public health measures.Entities:
Keywords: Zambia; anaemia; health impact assessment; hookworm; malaria; migration; stunting
Mesh:
Substances:
Year: 2017 PMID: 28335490 PMCID: PMC5369151 DOI: 10.3390/ijerph14030315
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Selected indicators in children and their relevance in the Trident copper mining project area, Zambia.
| Indicator | Definition and Measurement Methods | Relevance to Children’s Health and the Local Project Context |
|---|---|---|
| Improved local economy, vector control measures implemented by the project and better infrastructure (e.g., roads, health facilities) can improve access to vector control measures and health care [ | ||
| Stunting prevalence in in children aged 0–59 months | Stunting, or low height-for-age, is defined as -2 standard deviation units from the WHO reference population median and measured using a digital scale and portable stadiometer (Seca 877; Seca GmbH, Hamburg, Germany) [ | Improved local economy can improve nutritional status. Reduced access to agricultural land for local populations and food price inflations due to increased purchasing power can increase the burden of malnutrition |
| Anaemia prevalence in children aged 6–59 months | Anaemia is defined as haemoglobin (Hb) < 11 g/dL in capillary blood assessed using a HemoCue® 201+ testing device (HemoCue Hb 201 System; HemoCue AB, Ängelholm, Sweden) [ | Anaemia is used as a proxy indicator for general health and well-being, because of its multifactorial aetiology (e.g., intake and uptake of dietary iron, parasitic infections and prevalence of sickle cell disease) [ |
| Hookworm infection prevalence in children aged 9–14 years | Hookworm infection is defined as detection of hookworm eggs in a single thick-smear of a fresh, morning stool sample prepared and examined by the Kato-Katz technique within 20–40 min after slide preparation (using 41.7 mg templates) [ | Project-induced in-migration may place pressure on existing sanitation, which poses a risk for the transmission of diarrhoeal diseases and intestinal parasites. Increased income coupled with behaviour change can lead to protection through wearing of footwear. First-time inhabitation of native soil (e.g., new settlements or resettlement), increased use of footwear (due to increased income) and intensive circulation of top soil (due to project-associated activities) can lower exposure to hookworm eggs in the environment. |
Figure 1Study area and sentinel sites, Trident project, 2011 and 2015, Zambia.
Figure 2Sentinel site selection, Trident project, 2011 and 2015, Zambia.
Study populations, Trident project, 2011 and 2015, Zambia.
| Sentinel Sites | Households | Children Aged < 6 Months | Children Aged 6–59 Months | School-Going Children Aged 9–14 Years | Proportion of Households that Have Been Resettled due to the Project | Proportion of Migrant Households (in the Area for <5 years) | Proportion of Households that Use Improved Sanitation | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Year | 2011 | 2015 | 2011 | 2015 | 2011 | 2015 | 2011 | 2015 | 2015 | 2015 | 2015 |
| Wanyinwa (2011)/Northern Resettlement (2015) | 35 | 34 | 4 | 7 | 60 | 63 | 35 | 30 | 97.1 | 2.9 | 97.1 |
| Musele 1 | 30 | 66 | 2 | 18 | 43 | 116 | 40 | 59 | 3.0 | 30.3 | 34.9 |
| Chisasa 1 | 66 | 65 | 3 | 16 | 94 | 96 | 44 | 60 | 1.5 | 66.2 | 47.7 |
| Kankonzhi 1 | 36 | 30 | 3 | 7 | 70 | 52 | 35 | 29 | 3.3 | 36.7 | 50.0 |
| Chitungu 1 | 30 | 33 | 1 | 8 | 58 | 43 | 57 | 30 | 0.0 | 0.0 | 21.2 |
| Chovwe 1 | 61 | 32 | 3 | 10 | 91 | 43 | 64 | 30 | 0.0 | 6.3 | 43.8 |
| Kalumbila Town | NA | 30 | NA | 7 | NA | 36 | NA | 30 | 0.0 | 100.0 | 100.0 |
| Shenengene | NA | 32 | NA | 4 | NA | 48 | NA | 30 | 96.9 | 3.1 | 93.8 |
| Kanzanji | NA | 32 | NA | 8 | NA | 51 | NA | 29 | 3.1 | 43.8 | 6.3 |
| Total impacted | 258 | 354 | 16 | 85 | 416 | 548 | 275 | 327 | 19.5 | 34.5 | 52.3 |
| Nkenyawuli 1 | 31 | 32 | 8 | 3 | 43 | 65 | 34 | 30 | 0.0 | 6.3 | 37.5 |
| Wamafwa | NA | 33 | NA | 6 | NA | 66 | NA | 30 | 0.0 | 6.1 | 33.3 |
| Kanzala | NA | 32 | NA | 4 | NA | 52 | NA | 30 | 0.0 | 15.6 | 21.9 |
| Kambishi | NA | 32 | NA | 8 | NA | 51 | NA | 30 | 0.0 | 0.0 | 3.1 |
| Mubenji | NA | 33 | NA | 6 | NA | 55 | NA | 30 | 0.0 | 21.2 | 0.0 |
| Total comparison | 31 | 162 | 8 | 27 | 43 | 289 | 34 | 150 | 0.0 | 9.9 | 19.1 |
1 Sentinel site with data for 2011 BHS and 2015 follow-up; NA: not available.
Prevalences and period effects for P. falciparum infection and stunting, Trident project, 2011 and 2015, Zambia.
| Stunting in Children Aged 0–59 Months | ||||||||
|---|---|---|---|---|---|---|---|---|
| n | Prevalence (%; 95% CI) | OR | n | Prevalence (%; 95% CI) | OR | |||
| Comparison (2011) | 43 | 32.5 (19.0–48.5) | 1.00 | 51 | 39.2 (25.8–53.8) | 1.00 | ||
| Impacted (2011) | 416 | 17.5 (14.0–21.5) | 0.33 (0.05–2.20) | 0.25 | 432 | 49.7 (44.9–54.5) | 1.61 (0.77–3.35) | 0.20 |
| Comparison (2011) | 43 | 32.5 (19.0–48.5) | 1.00 | 51 | 39.2 (25.8–53.8) | 1.00 | ||
| Comparison (2015) | 65 | 70.7 (58.1–81.3) | 6.97 (2.20–22.0) | <0.01 | 68 | 47.0 (34.8–59.5) | 1.41 (0.58–3.46) | 0.44 |
| Impacted (2011) | 416 | 17.5 (14.0–21.5) | 1.00 | 432 | 49.7 (44.9–54.5) | 1.00 | ||
| Impacted (2015) | 413 | 30.9 (26.5–35.6) | 2.51 (1.56–4.02) | <0.01 | 479 | 39.4 (35.0–43.9) | 0.63 (0.46–0.87) | <0.01 |
| Comparison (2011–2015) | n/a | n/a | 1.00 | n/a | n/a | 1.00 | ||
| Impacted (2011–2015) | n/a | n/a | 0.36 (0.10–1.23) | 0.10 | n/a | n/a | 0.44 (0.17–1.15) | 0.09 |
1 Describes the change in prevalence between 2011 and 2015; CI: confidence interval; n: sample size; n/a: not applicable; OR, odds ratio.
Figure 3Prevalence rates per sentinel site, Trident project, 2011 and 2015, Zambia: (a) prevalence of P. falciparum in children aged 6–59 months; (b) prevalence of stunting in children aged 0-59 months; (c) prevalence of anaemia in children aged 6–59 months; and (d) prevalence of hookworm in children aged 9–14 years.
Figure 4Determinants of health outcomes during the 2015 follow-up health survey, with adjusted odds ratios and 95% confidence intervals, Trident project, Zambia: (a) determinants of P. falciparum in children aged 6–59 months; (b) determinants of stunting in children aged 0–59 months; and (c) determinants of anaemia in children aged 6–59 months.
Prevalences and period effects for anaemia and hookworm, Trident project, 2011 and 2015, Zambia.
| Anaemia in Children Aged 6–59 Months | Hookworm in Children Aged 9–14 Years | |||||||
|---|---|---|---|---|---|---|---|---|
| n | Prevalence (%; 95% CI) | OR | n | Prevalence (%; 95% CI) | OR | |||
| Comparison (2011) | 43 | 65.1 (49.0–78.9) | 1.00 | 34 | 58.8 (40.6–75.3) | 1.00 | ||
| Impacted (2011) | 416 | 46.6 (41.7–51.5) | 0.47 (0.22–0.98) | 0.04 | 275 | 62.5 (56.5–68.2) | 1.16 (0.33–4.03) | 0.80 |
| Comparison (2011) | 43 | 65.1 (49.0–78.9) | 1.00 | 34 | 58.8 (40.6–75.3) | 1.00 | ||
| Comparison (2015) | 65 | 50.8 (38.0–63.3) | 0.55 (0.24–1.22) | 0.14 | 30 | 50.0 (31.2–68.7) | 0.69 (0.25–1.88) | 0.47 |
| Impacted (2011) | 416 | 46.6 (41.7–51.5) | 1.00 | 275 | 62.5 (56.5–68.2) | 1.00 | ||
| Impacted (2015) | 413 | 41.9 (37.0–46.8) | 0.79 (0.60–1.05) | 0.11 | 238 | 60.9 (54.4–67.1) | 1.07 (0.73–1.56) | 0.71 |
| Comparison (2011–2015) | n/a | n/a | 1.00 | n/a | n/a | 1.00 | ||
| Impacted (2011–2015) | n/a | n/a | 1.44 (0.62–3.36) | 0.39 | n/a | n/a | 1.54 (0.53–4.46) | 0.42 |
CI, confidence interval; n: sample size; n/a: not applicable; OR, odds ratio; 1 Describes the change in prevalence between 2011 and 2015.