Old and new cluster designs in emergency field surveys: in search of a one-fits-all solution

<p>Abstract</p> <p>Introduction</p> <p>Cluster surveys are frequently used to measure key nutrition and health indicators in humanitarian emergencies. The survey design of 30 clusters of 7 children (30 × 7) was initially proposed by the World Health Organization for measuring vaccination coverage, and later a design of 30 clusters of 30 children (30 × 30) was introduced to measure acute malnutrition in emergency settings. Recently, designs of 33 clusters of 6 children (33 × 6) and 67 clusters of 3 children (67 × 3) have been proposed as alternatives that enable measurement of several key indicators with sufficient precision, while offering substantial savings in time. This paper explores expected effects of using 67 × 3, 33 × 6, or 30 × 7 designs instead of a "standard" 30 × 30 design on precision and accuracy of estimates, and on time required to complete the survey.</p> <p>Analysis</p> <p>The 67 × 3, 33 × 6, and 30 × 7 designs are expected to be more statistically efficient for measuring outcomes having high design effects (e.g., vaccination coverage, vitamin A distribution coverage, or access to safe water sources), and less efficient for measuring outcomes with more within-cluster variability, such as global acute malnutrition or anemia. Because of small sample sizes, these designs may not provide sufficient levels of precision to measure crude mortality rates. Given the small number (3 to 7) of survey subjects per cluster, it may be hard to select representative samples of subjects within clusters.</p> <p>The smaller sample size in these designs will likely result in substantial time savings. The magnitude of the savings will depend on several factors, including the average travel time between clusters. The 67 × 3 design will provide the least time savings. The 33 × 6 and 30 × 7 designs perform similarly to each other, both in terms of statistical efficiency and in terms of time required to complete the survey.</p> <p>Conclusion</p> <p>Cluster designs discussed in this paper may offer substantial time and cost savings compared to the traditional 30 × 30 design, and may provide acceptable levels of precision when measuring outcomes that have high intracluster homogeneity. Further investigation is required to determine whether these designs can consistently provide accurate point estimates for key outcomes of interest. Organizations conducting cluster surveys in emergency settings need to build their technical capacity in survey design to be able to calculate context-specific sample sizes individually for each planned survey.</p

Development of a dichotomous indicator for population-level assessment of the dietary diversity of women of reproductive age

Background: Dietary diversity is a key element of diet quality but diets of women of reproductive age (WRA; 15-49 y) in resource-poor settings are often deficient in a range of micronutrients. Previous work demonstrated relationships between simple food group diversity indicators (FGI) and micronutrient adequacy among WRA. For operational and advocacy purposes, however, there is strong demand for a dichotomous indicator reflecting an acceptable level of dietary diversity. Objective: To develop a dichotomous indicator of dietary diversity among WRA. Methods: We performed a secondary analysis of 9 data sets containing quantitative dietary data from WRA in resource-poor settings (N total = 4,166). From the raw dietary data we calculated an individual "mean probability of adequacy" (MPA) across 11 micronutrients. Several candidate FGI were constructed. Indicator performance in predicting MPA > 0.60 was assessed within each data set using receiver-operating characteristics (ROC) analysis and sensitivity/specificity analysis at various FGI cut-offs. The analysis was performed separately for non-pregnant and non-lactating (NPNL) and for lactating women. Results: We identified 2 "best candidate" dichotomous indicators based on 9- or 10-point food group scores (FGI-9 and FGI-10) with a cut-off of 5 food groups or more. Both were significantly correlated to MPA in each site (P 5 of 10 defined food groups reflects "Minimum dietary diversity for women of reproductive age" (MDD-W). According to the conclusions of a consensus meeting of experts, this indicator is well suited for population-level assessment, advocacy, and maybe also for tracking of change in dietary diversity across time

The limits of instrumentalism: Informal work and gendered cycles of food insecurity in Mozambique

The instrumentalist literature suggests that women can help achieve household food security if they have access to productive resources but do not become overburdened as a result. This paper seeks to assess the relevance of this literature by exploring the gendered cycles of food insecurity in the context of women’s informal labour in northern Mozambique. It considers the relation between women and food security as embedded in the broader socio-economic setting, and finds that the interaction of different forms of deprivation, such as lack of secure employment and conflicting labour demands, generates food insecurity

Household factors and gestational age predict diet quality of pregnant women.

Adequate diet during pregnancy has positive effects on the mother and pregnancy outcome. Assessment of diet quality during pregnancy is particularly important in areas where household food security is suboptimal, to enable appropriate targeting and intervention. This study assessed diet quality and identified predicting factors among pregnant women in northern Ghana. A cross-sectional study involving 403 pregnant women was conducted in May 2018. Pregnant women attending antenatal care clinics (ANC) were selected using simple random sampling technique. We assessed socio-demographic characteristics, 24-h recall and household food security. The minimum dietary diversity for women (MDD-W) was used as a proxy measure for diet quality based on Food and Agricultural Organization (FAO) guidelines. Logistic regression models were fitted to determine the predictors of diet quality. The mean dietary diversity score (DDS) of 10 food groups was 4.4 ± 1.1 (95% CI: 4.3-4.5). Logistic regression showed that women of high educational level (adjusted odds ratio [AOR] = 2.42; 95% confidence interval [CI] [1.21-4.84]; P = 0.01), women of high household wealth index (AOR = 1.78; 95% CI [1.14-2.77]; P = 0.01], none/mild household hunger (AOR = 2.71; 95% CI [1.26-5.82]; P = 0.01), medium household size (6-15 members) (AOR = 1.66; 95% CI [1.04-2.66]; P = 0.03) and women of gestational age 20-35 weeks (AOR = 1.89; 95% CI [1.05-3.40]; P = 0.03) were more likely to have quality diets after adjusting for potential confounding variables. Diet quality among pregnant women was low and was predicted by educational level, household wealth, gestational age and food security. Women education and improvements in household food security could impact diets of pregnant women in northern Ghana

Whom and Where Are We Not Vaccinating? Coverage after the Introduction of a New Conjugate Vaccine against Group A Meningococcus in Niger in 2010

MenAfriVac is a new conjugate vaccine against Neisseria meningitidis serogroup A developed for the African “meningitis belt”. In Niger, the first two phases of the MenAfriVac introduction campaign were conducted targeting 3,135,942 individuals aged 1 to 29 years in the regions of Tillabéri, Niamey, and Dosso, in September and December 2010. We evaluated the campaign and determined which sub-populations or areas had low levels of vaccination coverage in the regions of Tillabéri and Niamey. After Phase I, conducted in the Filingué district, we estimated coverage using a 30×15 cluster-sampling survey and nested lot quality assurance (LQA) analysis in the clustered samples to identify which subpopulations (defined by age 1–14/15–29 and sex) had unacceptable vaccination coverage (<70%). After Phase II, we used Clustered Lot Quality Assurance Sampling (CLQAS) to assess if any of eight districts in Niamey and Tillabéri had unacceptable vaccination coverage (<75%) and estimated overall coverage. Estimated vaccination coverage was 77.4% (95%CI: 84.6–70.2) as documented by vaccination cards and 85.5% (95% CI: 79.7–91.2) considering verbal history of vaccination for Phase I; 81.5% (95%CI: 86.1–77.0) by card and 93.4% (95% CI: 91.0–95.9) by verbal history for Phase II. Based on vaccination cards, in Filingué, we identified both the male and female adult (age 15–29) subpopulations as not reaching 70% coverage; and we identified three (one in Tillabéri and two in Niamey) out of eight districts as not reaching 75% coverage confirmed by card. Combined use of LQA and cluster sampling was useful to estimate vaccination coverage and to identify pockets with unacceptable levels of coverage (adult population and three districts). Although overall vaccination coverage was satisfactory, we recommend continuing vaccination in the areas or sub-populations with low coverage and reinforcing the social mobilization of the adult population

Health and Human Rights in Chin State, Western Burma: A Population-Based Assessment Using Multistaged Household Cluster Sampling

Sollom and colleagues report the findings from a household survey study carried out in Western Burma; they report a high prevalence of human rights violations such as forced labor, food theft, forced displacement, beatings, and ethnic persecution

Iron deficiency was not the major cause of anemia in rural women of reproductive age in Sidama zone, southern Ethiopia: A cross-sectional study

Background Anemia, which has many etiologies, is a moderate/severe public health problem in young children and women of reproductive age in many developing countries. The aim of this study was to investigate prevalence of iron deficiency, anemia, and iron deficiency anemia using multiple biomarkers and to evaluate their association with food insecurity and food consumption patterns in non-pregnant women from a rural area of southern Ethiopia. Methods A cross-sectional study was conducted in 202 rural women of reproductive age in southern Ethiopia. Anthropometrics and socio-demographic data were collected. A venipuncture blood sample was analyzed for hemoglobin (Hb) and for biomarkers of iron status. Biomarkers were skewed and were log transformed before analysis. Mean, median, Pearson\u27s correlations and ordinary least-squares regressions were calculated. Results Median (IQR) Hb was 138 (127, 151) g/L. Based on an altitude-adjusted (1708 m) cutoff of 125 g/L for Hb, 21.3% were anemic. Plasma ferritin was \u3c15 μg/L in 18.6% of the women. Only one woman had α-1-acid glycoprotein (AGP) \u3e1.0 g/L; four women (2%) had \u3e 5 mg/L of C-reactive protein (CRP). Of the 43 women who were anemic, 23.3% (10 women) had depleted iron stores based on plasma ferritin. Three of these had elevated soluble transferring receptors (sTfR). Hemoglobin (Hb) concentration was negatively correlated with sTfR (r = -0.24, p = 0.001), and positively correlated with ferritin (r = 0.17, p = 0.018), plasma iron (r = 0.15, p = 0.046), transferrin saturation (TfS) (r = 0.15, p = 0.04) and body iron (r = 0.14, p = 0.05). Overall prevalence of iron deficiency anemia was only 5%. Conclusion Iron deficiency anemia was not prevalent in the study population, despite the fact that anemia would be classified as a moderate public health problem

Co-causation of reduced newborn size by maternal undernutrition, infections, and inflammation.

More than 20 million babies are born with low birthweight annually. Small newborns have an increased risk for mortality, growth failure, and other adverse outcomes. Numerous antenatal risk factors for small newborn size have been identified, but individual interventions addressing them have not markedly improved the health outcomes of interest. We tested a hypothesis that in low-income settings, newborn size is influenced jointly by multiple maternal exposures and characterized pathways associating these exposures with newborn size. This was a prospective cohort study of pregnant women and their offspring nested in an intervention trial in rural Malawi. We collected information on maternal and placental characteristics and used regression analyses, structural equation modelling, and random forest models to build pathway maps for direct and indirect associations between these characteristics and newborn weight-for-age Z-score and length-for-age Z-score. We used multiple imputation to infer values for any missing data. Among 1,179 pregnant women and their babies, newborn weight-for-age Z-score was directly predicted by maternal primiparity, body mass index, and plasma alpha-1-acid glycoprotein concentration before 20 weeks of gestation, gestational weight gain, duration of pregnancy, placental weight, and newborn length-for-age Z-score (p < .05). The latter 5 variables were interconnected and were predicted by several more distal determinants. In low-income conditions like rural Malawi, maternal infections, inflammation, nutrition, and certain constitutional factors jointly influence newborn size. Because of this complex network, comprehensive interventions that concurrently address multiple adverse exposures are more likely to increase mean newborn size than focused interventions targeting only maternal nutrition or specific infections