Hemoglobin Levels and the Risk of Malaria in Papua New Guinean Infants: A Nested Cohort Study

Risk Association, Linkage Disequilibrium, and Haplotype Analyses of β-Like Globin Gene Polymorphisms with Malaria Risk in the Sabah Population of Malaysian Borneo

Single nucleotide polymorphisms (SNPs) in the β-like globin gene of the human hosts to the risk of malaria are unclear. Therefore, this study investigates these associations in the Sabah population, with a high incidence of malaria cases. In brief, DNA was extracted from 188 post-diagnostic blood samples infected with Plasmodium parasites and 170 healthy controls without a history of malaria. Genotyping of the β-like globin C-158T, G79A, C16G, and C-551T SNPs was performed using a polymerase chain reaction-restriction fragment length polymorphism approach. Risk association, linkage disequilibrium (LD), and haplotype analyses of these SNPs were assessed. This study found that the variant allele in the C-158T and C16G SNPs were protective against malaria infections by 0.5-fold, while the variant allele in the G79A SNP had a 6-fold increased risk of malaria infection. No SNP combination was in perfect LD, but several haplotypes (CGCC, CGCT, and CGGC) were identified to link with different correlation levels of malaria risk in the population. In conclusion, the C-158T, G79A, and C16G SNPs in the β-like globin gene are associated with the risk of malaria. The haplotypes (CGCC, CGCT, and CGGC) identified in this study could serve as biomarkers to estimate malaria risk in the population. This study provides essential data for the design of malaria control and management strategies.

Factors associated with hospital length of stay in patients admitted with suspected malaria in Kenya: secondary analysis of a cross-sectional survey

OBJECTIVES

To investigate factors associated with hospital length of stay (LOS) in patients admitted with suspected malaria using a competing risk approach.

SETTING

County government referrals and major faith-based hospitals in Kenya in 2018.

DESIGN

Secondary analysis of a cross-sectional survey data.

PARTICIPANTS

Data were extracted from 2396 medical records of patients admitted with suspected malaria at 90 hospitals.

OUTCOME MEASURES

LOS, defined as time to discharge, was the primary event of interest, and time to death was the competing event against patient factors assessed during admission and hospitalisation.

RESULTS

Among the patients analysed, 2283 were discharged, 49 died and 64 were censored. The median LOS was 4 days (IQR: 3-6 days). The cumulative incidence of discharge significantly decreased (p<0.05) by 12.7% (subdistribution-HR (SDHR): 0.873; 95% CI 0.789 to 0.967) when the respiratory rate was assessed, by 14.1% (SDHR 0.859; 95% CI 0.754 to 0.978) when oxygen saturation was monitored, by 23.1% (SDHR 0.769; 95% CI 0.709 to 0.833) and 23.4% (SDHR 0.766; 95% CI 0.704 to 0.833) when haemoglobin/haematocrit and glucose/random blood sugar were performed, respectively, and by 30.4% (SDHR 0.696; 95% CI 0.626 to 0.774) when patients had at least one clinical feature of severe malaria. Conversely, patients with confirmed severe malaria and those treated with injectable artesunate had a significantly increased cumulative incidence of discharge by 21.4% (SDHR 1.214; 95% CI 1.082 to 1.362) and 33.9% (SDHR 1.339; 95% CI 1.184 to 1.515), respectively.

CONCLUSIONS

Factors of inpatient clinical processes that influence hospital LOS were identified. These can be targeted during quality improvement interventions to enhance health service delivery in Kenya. Early recognition and appropriate management of the signs of malaria severity could greatly affect beneficial outcomes. Strengthening clinical practices and nursing care according to national case management guidelines should be a priority for malaria control managers in Kenya.

Revisiting the malaria hypothesis: accounting for polygenicity and pleiotropy

The malaria hypothesis predicts local, balancing selection of deleterious alleles that confer strong protection from malaria. Three protective variants, recently discovered in red cell genes, are indeed more common in African than European populations. Still, up to 89% of the heritability of severe malaria is attributed to many genome-wide loci with individually small effects. Recent analyses of hundreds of genome-wide association studies (GWAS) in humans suggest that most functional, polygenic variation is pleiotropic for multiple traits. Interestingly, GWAS alleles and red cell traits associated with small reductions in malaria risk are not enriched in African populations. We propose that other selective and neutral forces, in addition to malaria prevalence, explain the global distribution of most genetic variation impacting malaria risk.

Factors Associated with Anemia Status Among Children Aged 6-59 months in Ghana, 2003-2014

Background

In 2008, 78% of Ghanaian children under 5 years old were anemic versus 48% of children globally. In this study, we identified proximal and distal determinants of severe–moderate anemia and mild anemia related to socioeconomic status, nutrition, and health access.

Methods

Using data from the 2003, 2008, and 2014 Ghana Demographic and Health Surveys (GDHS), the odds of severe–moderate anemia and mild anemia compared to no anemia, in relation to various hypothesized risk factors, were assessed using a multivariable, multinomial logistic regression, which accounted for survey design.

Results

From among 7739 households sampled, severe–moderate anemia was found in approximately 52%, 56%, and 40% of children during 2003, 2008, and 2014, respectively. The proportion of children diagnosed as not anemic was 26% in 2003, 22% in 2008, and 33% in 2014. There are large disparities in anemia prevalence among regions and between urban and rural areas. In 2014, children who were younger (aged 6–24 months), had a recent fever, were from poorer families, and whose mothers were less educated had greater odds of being severely–moderately anemic. These results remained significant when controlling for other risk factors. Predictors of anemia in Ghana remained relatively consistent among the three time periods when the GDHS was administered.

Conclusions

The prevalence of anemia in Ghana among children aged 6–59 months has remained unacceptably high. To reduce anemia in these children, the Ghanaian government should concentrate on educating women through both the traditional school system and antenatal care visits.

Iron Status and Associated Malaria Risk Among African Children

BACKGROUND

It remains unclear whether improving iron status increases malaria risk, and few studies have looked at the effect of host iron status on subsequent malaria infection. We therefore aimed to determine whether a child's iron status influences their subsequent risk of malaria infection in sub-Saharan Africa.

METHODS

We assayed iron and inflammatory biomarkers from community-based cohorts of 1309 Kenyan and 1374 Ugandan children aged 0-7 years and conducted prospective surveillance for episodes of malaria. Poisson regression models were fitted to determine the effect of iron status on the incidence rate ratio (IRR) of malaria using longitudinal data covering a period of 6 months. Models were adjusted for age, sex, parasitemia, inflammation, and study site.

RESULTS

At baseline, the prevalence of iron deficiency (ID) was 36.9% and 34.6% in Kenyan and Ugandan children, respectively. ID anemia (IDA) affected 23.6% of Kenyan and 17.6% of Ugandan children. Malaria risk was lower in children with ID (IRR, 0.7; 95% confidence interval [CI], 0.6, 0.8; P < .001) and IDA (IRR, 0.7; 95% CI, 0.6, 0.9; P = .006). Low transferrin saturation (<10%) was similarly associated with lower malaria risk (IRR, 0.8; 95% CI, 0.6, 0.9; P = .016). However, variation in hepcidin, soluble transferrin receptors (sTfR), and hemoglobin/anemia was not associated with altered malaria risk.

CONCLUSIONS

ID appears to protect against malaria infection in African children when defined using ferritin and transferrin saturation, but not when defined by hepcidin, sTfR, or hemoglobin. Additional research is required to determine causality.

CLINICAL TRIALS REGISTRATION

ISRCTN32849447.