Comparison of hemoglobin concentrations measured by HemoCue and a hematology analyzer in Indian children and adolescents 1‐19 years of age

Predictors of Incidence and Remission of Anemia among Never-Married Adolescents Aged 10-19 Years: A Population-Based Prospective Longitudinal Study in India

Background

Dynamics of the anemia burden among Indian adolescents are poorly understood because of a lack of population-based longitudinal data.

Objectives

To examine the burden of anemia among never-married adolescents aged 10-19 y from the states of Bihar and Uttar Pradesh, India, and a wide range of predictors of its incidence and remission.

Methods

A sample of 3279 adolescents (male: 1787 and female: 1492) aged 10-19 y were included from baseline (2015-2016) and follow-up (2018-2019) surveys of the UDAYA (Understanding the Lives of Adolescents and Young Adults) project in India. In 2018-2019, all new cases of anemia were considered as incidence, whereas a return to the nonanemic status from being anemic in 2015-2016 was considered remission. Univariate and multivariable modified Poisson regression models with robust error variance were deployed to attain the study objective.

Results

The crude prevalence of anemia among males decreased from 33.9% (95% CI: 30.7%-37.3%) in 2015-2016 to 31.6% (95% CI: 28.6%-34.7%) in 2018-2019 but increased among females from 57.7% (95% CI: 53.5%-61.7%) in 2015-2016 to 63.8% (95% CI: 59.9%-67.5%) in 2018-2019. Anemia incidence was estimated to be 33.7% (95% CI: 30.3%-37.2%), whereas nearly 38.5% (95% CI: 35.1%-42.1%) of adolescents experienced remission of anemia. Older adolescents (aged 15-19 y) were less likely to experience anemia incidence. Consumption of eggs daily or weekly was negatively associated with anemia incidence compared with occasional or never consumption. Females had a higher risk of experiencing an incidence of anemia and decreased risk of experiencing anemia remission. The likelihood of adolescents experiencing anemia increased with an increased patient health questionnaire score. Household size was also associated with an increased risk of anemia incidence.

Conclusions

Interventions that are sensitive to socio-demographic factors and encouraging access to mental health services and nutritious food consumption could be helpful in further anemia mitigation.

Shooting shadows: India's struggle to reduce the burden of anaemia

Despite several efforts by the Government of India, the national burden of anaemia remains high and its growing prevalence (between 2015-2016 and 2019-2021) is concerning to India's public health system. This article reviews existing food-based and clinical strategies to mitigate the anaemia burden and why they are premature and insufficient. In a context where multiple anaemia control programmes are in play, this article proposes a threefold strategy for consideration. First, except the Comprehensive National Nutrition Survey, 2016-2018, which measured Hb concentration among children and adolescents aged 1-19 years using venous blood samples, all national surveys use capillary blood samples to determine Hb levels, which could be erroneous. The Indian government should prioritise conducting a nationwide survey for estimating the burden of anaemia and its clinical determinants for all age groups using venous blood samples. Second, without deciding the appropriate dose of Fe needed for an individual, food fortification programmes that are often compounded with layering of other micronutrients could be harmful and further research on this issue is needed. Same is true for the pharmacological intervention of Fe tablet or syrup supplementation programmes, which is given to individuals without assessing its need. In addition, there is a dire need for robust research to understand both the long-term benefit and side effects of Fe supplementation programmes. Third and final, the WHO is in process of reviewing the Hb threshold for defining anaemia, therefore the introduction of new anaemia control programmes should be restrained.

Comparison of Anemia Screening Methods Using Paired Venous Samples in Women of Reproductive Age in Southern India

BACKGROUND

Anemia is an important public health problem, and accurate estimates may inform policy and programs. Although hemoglobin (Hb) assessment of venous blood via automated hematology analyzers (AHAs) is recommended, most population-based surveys estimate anemia prevalence based on analysis of capillary blood via portable hemoglobinometers.

OBJECTIVES

We aimed to evaluate screening methods for hemoglobin and anemia assessment using paired venous samples.

METHODS

Participants were women 15-40 y who were not pregnant or lactating. Paired venous whole blood samples (n = 896) were analyzed for hemoglobin (Hb) via portable hemoglobinometer (HemoCue 301) and Coulter Counter AHA. Anemia and severe anemia were defined as Hb <12.0g/dL and <8.0 g/dL, respectively. Bland-Altman methods were used to assess the level of agreement for Hb results (mean difference, SD of differences, limits of agreement). Diagnostic accuracy parameters (sensitivity, specificity, positive predictive value, negative predictive value, accuracy) were calculated to evaluate HemoCue performance compared to the AHA reference, overall and by sociodemographic, nutritional, and metabolic characteristics.

RESULTS

The estimated anemia prevalence was significantly lower via HemoCue vs. AHA (36.3% compared with 41.6%; P value < 0.0001). The HemoCue had 84.4% accuracy for anemia screening and 98.8% for severe anemia, compared to the AHA reference. The HemoCue had 74.8% sensitivity and 91.2% specificity, compared to AHA. HemoCue sensitivity was higher in women with iron deficiency [serum ferritin (SF) <15.0 μg/L: 81.6% compared with SF ≥15.0 μg/L: 41.3%], and lower in women with metabolic risk factors, including overweight [BMI ≥25.0 kg/m2: 63.9% vs. BMI <25.0 kg/m2: 78.8%], or elevated CRP (>1.0 mg/L: 67.2% vs. ≤1.0 mg/L: 82.9%), trunk fat (>35%: 62.7% vs. ≤35%: 80.1%), or whole-body fat (>35%: 63.9% vs. ≤35%: 80.3%).

CONCLUSIONS

Findings suggest that women with anemia may be incorrectly identified as not anemic via portable hemoglobinometer, and anemia prevalence may be underestimated at the population level.This study was registered at clinicaltrials.gov as NCT04048330.

Improving the approach to assess impact of anaemia control programs during pregnancy in India: a critical analysis

Around 42.7% of women experience anaemia during pregnancy in low- and middle-income countries. Countries in southeast Asia (with prevalence ranging between 40 and 60%) have reported a modest decline over the past 25 years. Nearly half the pregnant women continue to be anaemic in India between 2005-06 and 2015-16, although severe anaemia has reduced from 2.2% to 1.3%.India has been committed to achieving a target of 32% prevalence of anaemia in pregnant women from 50% by 2022. There are concerns around stagnancy in the prevalence of anaemia in pregnancy despite a strong political commitment. The paper puts forth the arguments that should be considered while introspecting why India might run the risk of not achieving the expected reduction. The reported findings highlight several methodological issues such as hemoglobin cut-offs used to determine anaemia during pregnancy, method of estimation of Hb, and less emphasis on causes other than iron deficiency anemia.

Correction Equation for Hemoglobin Values Obtained Using Point of Care Tests-A Step towards Realistic Anemia Burden Estimates

Digital hemoglobinometers have been used as point-of-care tests (POCT) to estimate the burden of anemia in community-based studies and national-level surveys in India. As the accuracy of hemoglobin estimated in POCT varies, there is a need for adjustments to the POCT-hemoglobin to ensure they are closer to reality and are comparable. We used data (collected between 2016 and 2020) (N = 1145) from four studies from India: three among pregnant women and 6-59-month-old children from Haryana and the fourth from a national nutritional survey among 1-19-year-old children. We compared the same individuals' POCT-hemoglobin (capillary blood) and automated hematology analyzers (AHA) hemoglobin (venous blood) and developed a predictive linear regression model to obtain the correction equation for POCT-hemoglobin. We analyzed paired data from 1145 participants. The correction equation for obtaining the true hemoglobin value = 3.35 + 0.71 × POCT-hemoglobin using capillary blood (adjusted R2-64.4% and mean squared error -0.841 g/dL). In comparison with the AHA-hemoglobin, the mean difference of POCT-hemoglobin was 0.2 g/dL, while with the predicted Hb obtained from the correction equation it was 0.01 g/dL. The correction equation was the first attempt at deriving the true hemoglobin values from the POCTs. There is a need for multi-country collaborative studies to improve the correction equation by adjusting for factors affecting hemoglobin estimation.

Associations between type of blood collection, analytical approach, mean haemoglobin and anaemia prevalence in population-based surveys: A systematic review and meta-analysis

Background

Previous studies have observed that haemoglobin concentrations can be affected by type of blood collection, analysis methods and device, and that near-in-time population-based surveys report substantially different anaemia prevalence. We investigated whether differences in mean haemoglobin or prevalence of anaemia between near-in-time surveys of the same population were associated with differences in type of blood collection or analytic approach to haemoglobin measurement.

Methods

We systematically identified pairs of population-based surveys that measured haemoglobin in the same population of women of reproductive age (WRA) or preschool-aged children (PSC). Surveys were matched on geographic coverage, urban/rural place of residence, inclusion of pregnant women, time of data collection (within 18 months), and, to the extent feasible, age range. Differences in anaemia prevalence were presented graphically. Random-effects meta-analysis and meta-regression of difference in mean haemoglobin were carried out, with subgroups defined by comparison of type of blood collection and analytic approach within each survey pair.

Results

We included 23 survey pairs from 17 countries for PSC and 17 survey pairs from 11 countries for WRA. Meta-regression indicates that surveys measuring haemoglobin with HemoCue® Hb 301 found higher haemoglobin concentrations than near-in-time surveys using HemoCue® Hb 201+ in non-pregnant women ((NPW); 5.8 g/L (95% confidence interval (CI) = 3.2-8.3) mean difference, n = 5 pairs) and PSC (4.3 g/L (1.4-7.2), n = 6). Surveys collecting venous blood found higher haemoglobin concentrations than near-in-time surveys collecting capillary blood in PSC (3.8 g/L (0.8-6.7), n = 8), but not NPW (0.4 g/L (-1.9-2.8), n = 9).

Conclusions

Because this study is observational, differences in haemoglobin concentrations in near-in-time surveys may be caused by other factors associated with choice of analytic approach or type of blood collected. The source or sources of differences should be clarified to improve use of surveys to prioritize and evaluate public health programs.

Registration

PROSPERO CRD42022296553.

Haemoglobin thresholds to define anaemia in a national sample of healthy children and adolescents aged 1-19 years in India: a population-based study

BACKGROUND

WHO's haemoglobin cutoffs to define anemia were based on five studies of predominantly White adult populations, done over 50 years ago. Therefore, a general re-examination of the existing haemoglobin cutoffs is warranted for global application, in representative healthy populations of children and adults. Such data are scarce in low-income and middle-income countries; however, a 2019, large-scale, nationally representative survey of children and adolescents aged 0-19 years in India (Comprehensive National Nutrition Survey [CNNS]) offered an opportunity for this re-examination. Using this survey, we aimed to assess the age-specific and sex-specific percentiles of haemoglobin and cutoffs to define anaemia in the CNNS population.

METHODS

For this population-based study, we constructed age-specific and sex-specific haemoglobin percentiles from values reported for a defined healthy population in the CNNS, which used rigorous quality control measures during sample collection and in the laboratory analyses. To obtain a healthy population, we excluded participants with iron, folate, vitamin B12, and retinol deficiencies; inflammation; variant haemoglobins (haemoglobin A2 and haemoglobin S); and history of smoking. We considered age-specific and sex-specific 5th percentiles of haemoglobin derived for this healthy population as the study cutoff to define anaemia. We compared these with existing WHO cutoffs to assess significant differences between them at each year of age and sex for quantifying the prevalence of anaemia in the entire CNNS sample.

FINDINGS

Between Feb 24, 2016, and Oct 26, 2018, the CNNS survey collected blood samples from 49 486 individuals. 41 210 participants had a haemoglobin value, 8087 of whom were included in our study and comprised the primary analytical sample. Compared with existing WHO cutoffs, the study cutoffs for haemoglobin were lower at all ages, usually by 1-2 g/dL, but more so in children of both sexes aged 1-2 years and in girls aged 10 years or older. Aanemia prevalence with the study cutoffs was 19·2 percentage points lower than with WHO cutoffs in the entire CNNS sample with valid haemoglobin values across all ages and sexes (10·8% with study cutoffs vs 30·0% with WHO cutoffs).

INTERPRETATION

These findings support the re-examination of WHO haemoglobin cutoffs to define anaemia. Our haemoglobin reference percentiles, derived from healthy participants in a large representative Indian survey, are suitable for national use in India. Substantial variations in the 5th percentile of haemoglobin values across the 1-19 years age range and between sexes argue against constructing common cutoffs in stratified age groups for convenience.

FUNDING

None.

TRANSLATIONS

For the Hindi, Punjabi, Tamil and Kannada translations of the abstract see Supplementary Materials section.