| Literature DB >> 26943124 |
Beatrice Amadi1,2, Mercy Imikendu1, Milika Sakala1, Rosemary Banda1, Paul Kelly2,3.
Abstract
BACKGROUND: While HIV has had a major impact on health care in southern Africa, there are few data on its impact on acute malnutrition in children in the community. We report an analysis of outcomes in a large programme of community management of acute malnutrition in the south of Lusaka. PROGRAMME ACTIVITIES AND ANALYSIS: Over 3 years, 68,707 assessments for undernutrition were conducted house-to-house, and children with severe acute malnutrition (SAM) or moderate acute malnutrition (MAM) were enrolled into either Outpatient Therapeutic Programme (OTP) or Supplementary Feeding Programme (SFP) respectively. Case records were analysed using tabulation and unconditional logistic regression.Entities:
Mesh:
Substances:
Year: 2016 PMID: 26943124 PMCID: PMC4778761 DOI: 10.1371/journal.pone.0149218
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Baseline characteristics.
| MAM (n = 664) | SAM (n = 1195) | ||
|---|---|---|---|
| Sex (M:F) | 368:296 | 602:593 | 0.04 |
| Age on recruitment (months, median, interquartile range IQR) | 15 (10–21) | 16 (11–22) | 0.008 |
| HIV infected | 51/639 (8.0%) | 134/1157 (11.6%) | 0.02 |
| WAZ | |||
| > -2 | 91 (14% | 236 (20%) | <0.0001 |
| < = -2 | 262 (40%) | 302 (25%) | |
| < = -3 | 306 (46%) | 655 (55%) | |
| WHZ | |||
| > -2 | 269 (43%) | 517 (44%) | <0.0001 |
| < = -2 | 351 (57%) | 324 (27%) | |
| < = -3 | 0 | 341 (29%) | |
| HAZ | |||
| > -2 | 160 (24%) | 257 (21%) | <0.0001 |
| < = -2 | 250 (38%) | 343 (29%) | |
| < = -3 | 253 (38%) | 596 (50%) | |
| MUAC (cm, median, IQR) | 12.3 (12.0–12.5) | 12.0 (11.4–13.0) | 0.0002 |
1Children over 10 years of age not included in weight for age z score categories as WHO growth standard charts do not include these age groups; BMI-for-age is used as a measure of wasting. MUAC and weight for height are independent criteria for wasting; not all children who were wasted based on MUAC were necessarily wasted by the WHZ criterion [20]. Characteristics of children with MAM and SAM are described separately as these were important contributors to outcome, and the P values reported refer to the difference between MAM and SAM.
Fig 1Flow of children with MAM through the programme.
Children who were found to have moderate acute malnutrition (MAM) at screening were assessed, treated and followed up and their outcomes are shown. Some deteriorated to severe acute malnutrition (SAM) with or without complications. The colour key shows interventions and outcomes.
Outcomes in children with MAM by year of programme.
| Outcome | YEAR 1 | YEAR 2 | YEAR 3 |
|---|---|---|---|
| Recovered | 135(53%) | 192(84.6%) | 151 (83%) |
| Died | 1 (0.4%) | 2(0.9%) | 0 |
| Defaulted | 113(44.5%) | 26(11.5%) | 18(9.8%) |
| Relocated | 5 (2%) | 7(3%) | 13(7%) |
| Non Responder | 0 | 0 | 1(0.5%) |
Fig 2Flow of children with SAM through the programme.
Children who were found to have severe acute malnutrition (SAM) at screening were assessed, treated and followed up and their outcomes are shown. Some improved to moderate acute malnutrition (MAM). The colour key shows interventions and outcomes.
Outcomes in children with SAM by year of programme.
| Outcome | YEAR 1 | YEAR 2 | YEAR 3 |
|---|---|---|---|
| Recovered | 251 (43.5%) | 225 (70.5%) | 209 (69.9%) |
| Died | 24(4.2%) | 12(3.8%) | 14(4.7%) |
| Defaulted | 289(50%) | 74(23.2%) | 55(18%) |
| Relocated | 13(2.3%) | 8(2.5%) | 21(7%) |
| Non Responder | 0 | 0 | 0 |