Anthropometric measurements can identify small for gestational age newborns: A cohort study in rural Tanzania

listen audio

Study Justification:
– Small-for-gestational-age (SGA) newborns are at increased risk of mortality and morbidity.
– Accurate gestational age is often unknown in low and middle income countries, making it difficult to identify SGA newborns.
– Previous studies have shown that measuring foot length, chest circumference, and mid upper arm circumference (MUAC) can detect low birth weight and prematurity.
– This study aimed to investigate if these anthropometric measurements could also identify SGA newborns.
Study Highlights:
– 376 live newborns in rural Tanzania had foot length, chest circumference, and MUAC measured within 24 hours of birth.
– Gestational age was estimated by transabdominal ultrasound and SGA was diagnosed using a sex-specific weight reference chart.
– Receiver operating characteristic curves were generated for each anthropometric measurement to compare their ability to detect SGA.
– Chest circumference had the highest area under the curve (AUC) for detecting SGA, followed by MUAC and foot length.
– Operational cut-offs were defined for each measurement to balance sensitivity and specificity for identifying SGA.
Study Recommendations:
– In settings with limited availability of accurate gestational age, all three anthropometric measurements can be used to rule out newborns as SGA.
– Chest circumference is the best method for identifying SGA newborns, while foot length and MUAC have lower detection ability.
Key Role Players:
– Researchers and study investigators
– Health professionals and clinicians
– Policy makers and government officials
– Community health workers
Cost Items for Planning Recommendations:
– Training and capacity building for health professionals and community health workers
– Equipment and supplies for measuring foot length, chest circumference, and MUAC
– Data collection and management tools
– Communication and dissemination of study findings
– Monitoring and evaluation of implementation
– Stakeholder engagement and coordination activities

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, with a cohort study design and a large sample size. The study used appropriate statistical analyses and reported the area under the curve (AUC) for each anthropometric measurement. The study also calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for identifying small for gestational age (SGA) newborns. To improve the evidence, the study could have included a comparison group of non-SGA newborns for further validation of the anthropometric measurements.

Background: Small-for-gestational-age (SGA) is associated with increased neonatal mortality and morbidity. In low and middle income countries an accurate gestational age is often not known, making the identification of SGA newborns difficult. Measuring foot length, chest circumference and mid upper arm circumference (MUAC) of the newborn have previously been shown to be reasonable methods for detecting low birth weight (< 2500 g) and prematurity (gestational age  2 years consecutively and having consented to attend all the antenatal care and giving birth at Korogwe District Hospital if they conceived during the study period. In the pregnancy cohort women were included if having a GA ≤14 weeks and based on a 1:1 distribution of maternal anemia (hemoglobin  4 h apart or systolic blood pressure ≥ 160 mmHg and/or diastolic blood pressure ≥ 110 mmHg observed at least once. Preeclampsia was defined as hypertension and proteinuria on at least two occasions after a GA of 20 weeks. Anthropometric measurements included height in centimeters (cm) (only at enrolment) (Stadiometer, SECA GmbH & Co. KG, Hamburg, Germany), and weight without outer garment and shoes recorded to nearest 0.1 kg (Digital weighing scale, SECA GmbH & Co. KG, Hamburg, Germany) [20]. Body mass index was calculated by dividing the body weight with the square of the height. At birth a thorough anthropometric examination of the newborns was performed within 24 h. Birth weight was measured on a nude newborn using a digital baby weighing scale (M107600, ADE, Germany) and noted in grams (g) to the nearest 5 g [21]. The length of the newborn was measured from the vertex to the heel of the right foot using an infantometer (Baby Infantometer 417, SECA GmbH & Co. KG, Hamburg, Germany) [21]. The foot length was measured from the heel to the tip of the longest toe on the right foot using a hard transparent plastic ruler and noted in cm [9, 11, 13]. Chest circumference and MUAC were measured with a flexible non-stretchable tape measure. Chest circumference was measured to the nearest 0.1 cm on a calm baby (mid-expiration) by circling the chest at the level of the nipples [22]. The MUAC was measured to the nearest 0.1 cm at the right upper arm mid-point halfway between the acromion of the scapula and the olecranon of the ulna [20]. All measurements were performed twice. If the difference between two measurements exceeded 50 g for birthweight, 7 mm for length, 5 mm for chest circumference, and 2 mm for foot length or MUAC, a third measurement was done and the two measurements closest to each other were documented. APGAR score, the appearance of amniotic fluid and any congenital malformations were documented as well. A sex-specific weight reference chart previously developed in the same study area [17] was used to define SGA as a birth weight below the 10th percentile. LBW was defined as birth weight < 2500 g [7] and preterm as a GA < 37 weeks [7]. In addition, the premature newborns were defined as extremely preterm (< 28 weeks), very preterm (28 to < 32 weeks) and moderate to late preterm (32 to  22 weeks without severe congenital malformations and with neonatal examination done within 24 h were included in the analysis. The study population was described with mean and standard deviation for parametric continuous data, median and interquartile range for non-parametric data, and proportion for categorical data (number (%)). Finally, for GA at delivery and birth weight the range with minimum and maximum values were reported and the 2.5th and 97.5th percentiles for birth weight were calculated. The association between foot length, chest circumference and MUAC versus birth weight and GA at delivery was calculated with Pearson and Spearman correlations, respectively. Student’s t-test was used for comparison of mean foot length, chest circumference and MUAC for SGA, LBW, and preterm newborns compared to normal weight and term newborns as well as for comparison of mean foot length, chest circumference and MUAC among male and female newborns. Receiver operating characteristics (ROC) analysis was conducted separately for each anthropometric measurement and the area under the curve (AUC) calculated to investigate which measurement best predicted SGA, LBW and prematurity, respectively. For sensitivity analyses, ROC analysis only including newborns with GA estimated ≤14 weeks and ROC analysis stratified by the sex of the newborn were performed. Operational cut-offs for foot length, chest circumference and MUAC were selected based on obtaining the highest sensitivity and specificity for identifying SGA, and positive predictive value (PPV) and negative predictive value (NPV) for SGA were then calculated. Using the same cut-offs; sensitivity, specificity, PPV, and NPV were also calculated for LBW and prematurity. For comparison, operational cut-offs for foot length, chest circumference and MUAC were also selected based on obtaining the highest sensitivity and specificity for identifying either LBW or prematurity. The 95% confidence intervals for all the sensitivities, specificities, PPVs and NPVs were reported. In total, 538 women were enrolled in the pregnancy part of the study, and hereof 401women gave birth to a live singleton newborn without severe congenital malformations. Among these, 376 newborns had foot length, chest circumference and MUAC measured within 24 h and were included in the analyses (Fig. ​(Fig.1).1). The median GA was 40 weeks + 0 days (Interquartile range 38 + 6 to 41 + 1, range 25 + 6 to 45 + 0) and the mean birth weight 3014 g (±486, range 860 to 4360, 2.5th to 97.5th percentiles 2061 to 3968). In total, 68 (18.4%) were born SGA, 39 (10.4%) were LBW, and 17 (4.5%) were born preterm. Among the preterm newborns, 15 (88.2%) were moderate to late preterm, 1 (5.9%) was very preterm and 1 (5.9%) was extremely preterm. The characteristics of the mothers and their newborns are shown in Table 1. Characteristics of the 376 women and their newborns a371 women had age estimated at enrolment, b370 women had body mass index estimated, c316 (84.0%) women had gestational age estimated at ≤14 weeks, 54 (14.4%) women had gestational age estimated between 15 and 24 weeks and 6 (1.6%) had gestational age estimated at 25–28 weeks, d375 had BW estimated, e369 newborns were categorized as either SGA/non-SGA, fSD Standard deviation All three anthropometric measurements of the newborns correlated with birth weight and GA at delivery, showing the best correlation when using chest circumference (Pearson correlation for birth weight 0.86, Spearman correlation for GA 0.41) (Fig. 2). All three anthropometric measurements were also statistical significantly smaller among newborns born SGA, with LBW or preterm as compared to newborn with normal weight and born at term (Table 2). The anthropometric measurements were comparable for boys and girls except for foot length which was significantly shorter for girls (difference = 0.12 cm, p-value = 0.01, 95% confidence interval (CI) (0.02–0.21)) [See Additional file 1]. Association between foot length, chest circumference and MUAC vs. birth weight and gestational age at delivery Differences in foot length, chest circumference and mid-upper-arm-circumference among the 376 newborns aSGA Small for gestational age. bMUAC Mid upper arm circumference ROC curve analyses were used to assess the three different anthropometric measurements’ ability to capture SGA, LBW and prematurity. Chest circumference had the highest AUC for all three outcomes. The highest observed AUC was for chest circumference detecting prematurity (0.94) while foot length detecting SGA had the lowest (0.78) (Fig. ​(Fig.3).3). A minority (60/376, 16%) of the women had GA estimated after 14 weeks of pregnancy. Sensitivity analysis only including newborns where GA was estimated ≤14 weeks yielded similar AUC for all three anthropometric measurements [See Additional file 2]. If stratifying by the sex of the newborn, AUC’s for chest circumference and MUAC were comparable for boys and girls, whereas the AUC for foot length was slightly higher for girls [See Additional file 3 and Additional file 4]. ROC curves for detecting SGA, low birth weight and prematurity, respectively using the three anthropometric measurements The sensitivity and specificity for detecting SGA was calculated for a range of different cut-offs of foot length, chest circumference and MUAC. The operational cut-offs yielding the highest combination of sensitivity and specificity (equivalent to the place on the ROC most to the top left) for detecting SGA newborns were defined as ≤7.7 cm for foot length (sensitivity at 74%, specificity at 69%), ≤31.6 cm for chest circumference (sensitivity at 79%, specificity at 81%) and ≤ 10.1 cm for MUAC (sensitivity at 76%, specificity at 77%) (Table 3). If stratified by sex of the newborn the operational cut-off for foot length for boys yielding the highest combination of sensitivity and specificity for detecting SGA was similar to the already defined operational cut-off. However, for girls the cut-off for foot length was slightly lower (≤ 7.6 cm) [See Additional file 5]. The other anthropometric measurements did not differ significantly for boys and girls. Sensitivity, specificity, PPV and NPV for operational anthropometric cut-offs together with the 95% confidence interval aSGA Small for gestational age, bFL Foot length, cCC Chest circumference, dMUAC Mid upper arm circumference, eCI Confidence interval, fPPV Positive predictive value, gNPV Negative predictive value All three anthropometric measures show high NPVs (0.92–0.95) for identifying SGA, whereas the PPVs were below 0.50 for all (0.35–0.49). The best PPV and NPV were observed when using chest circumference (0.49 and 0.95, respectively) (Table ​(Table3).3). The main objective was to assess the ability of foot length, chest circumference and MUAC in identifying SGA. Since prematurity and LBW are closely related to SGA, sensitivity, specificity, PPV, and NPV for the same operational cutoffs, but using LBW or prematurity as outcome, were also calculated. As compared to when detecting SGA, sensitivity and NPV were higher for both preterm delivery and LBW for all three anthropometric measurements, whereas specificity and PPV were slightly lower (Table ​(Table33). For comparison operational anthropometric cut-offs balancing the sensitivity and specificity for detecting LBW and preterm delivery instead of SGA were also calculated. Cut-offs for all three anthropometric measures were slightly smaller for both LBW and preterm delivery. For both outcomes specificities and PPVs increased, whereas sensitivities and NPV were either comparable or slightly decreased as compared to when using the operational cut-offs defined based on SGA (Table 4). Sensitivity and specificity of operational anthropometric cut-offs to identify Low birth weight and preterm a PPV Positive predictive value, b NPV Negative predictive value, cFL Foot length, dCC Chest circumference, eMUAC Mid upper arm circumference

Based on the study mentioned, here are some potential innovations that can be used to improve access to maternal health:

1. Use of Anthropometric Measurements: The study suggests that measuring foot length, chest circumference, and mid upper arm circumference (MUAC) of newborns can help identify small-for-gestational-age (SGA) newborns. This innovation can be implemented in healthcare facilities to improve the detection of SGA newborns and provide appropriate care.

2. Mobile Health (mHealth) Applications: Develop mobile health applications that can guide healthcare providers in accurately measuring foot length, chest circumference, and MUAC of newborns. These applications can provide step-by-step instructions and reference charts to ensure accurate measurements and improve the identification of SGA newborns.

3. Training and Capacity Building: Conduct training programs for healthcare providers on the importance of anthropometric measurements in identifying SGA newborns. This can help improve their knowledge and skills in accurately measuring and interpreting the results, leading to better identification and management of SGA newborns.

4. Integration into Routine Maternal Health Services: Integrate the measurement of foot length, chest circumference, and MUAC into routine maternal health services, such as antenatal care and postnatal care visits. This can ensure that all newborns are screened for SGA and appropriate interventions are provided.

5. Community-based Screening Programs: Establish community-based screening programs where trained healthcare workers or community health workers can measure foot length, chest circumference, and MUAC of newborns in remote or underserved areas. This can improve access to screening for SGA newborns in areas with limited healthcare facilities.

6. Collaboration and Partnerships: Foster collaboration and partnerships between healthcare providers, researchers, and policymakers to implement and scale up the use of anthropometric measurements for identifying SGA newborns. This can help ensure that the innovation is effectively implemented and reaches a larger population.

It is important to note that these recommendations are based on the information provided in the study and may need to be further evaluated and adapted to specific contexts and healthcare systems.
AI Innovations Description
The recommendation from the study is to use anthropometric measurements, specifically foot length, chest circumference, and mid upper arm circumference (MUAC), to identify small-for-gestational-age (SGA) newborns. These measurements have previously been shown to be effective in detecting low birth weight and prematurity. The study found that all three measurements had a high negative predictive value (NPV), meaning they could be used to rule out newborns as being SGA. However, chest circumference was found to be the best method for identifying SGA newborns, while foot length and MUAC had lower detection ability. The study suggests using operational cutoffs of ≤7.7 cm for foot length, ≤31.6 cm for chest circumference, and ≤10.1 cm for MUAC to identify SGA newborns. These cutoffs provide a balance between sensitivity and specificity for detecting SGA. Overall, the study recommends using these anthropometric measurements as a tool to improve access to maternal health by accurately identifying SGA newborns in settings with limited availability of accurate gestational age information.
AI Innovations Methodology
Based on the study “Anthropometric measurements can identify small for gestational age newborns: A cohort study in rural Tanzania,” the following recommendations can be made to improve access to maternal health:

1. Implement the use of foot length, chest circumference, and mid upper arm circumference (MUAC) measurements as screening tools for identifying small-for-gestational-age (SGA) newborns in low and middle-income countries where accurate gestational age is often not known.

2. Train healthcare providers in rural areas on how to accurately measure foot length, chest circumference, and MUAC of newborns within 24 hours of birth.

3. Develop guidelines and protocols for using foot length, chest circumference, and MUAC measurements to identify SGA newborns, including operational cutoffs that balance sensitivity and specificity.

4. Incorporate the use of foot length, chest circumference, and MUAC measurements into routine antenatal and postnatal care visits to ensure early identification of SGA newborns and appropriate interventions.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Identify a target population in a specific rural area where access to maternal health services is limited.

2. Collect baseline data on the prevalence of SGA newborns and the current methods used to identify them in the target population.

3. Train healthcare providers in the target population on how to measure foot length, chest circumference, and MUAC of newborns and implement the use of these measurements as screening tools.

4. Monitor the implementation of the recommendations and collect data on the number of SGA newborns identified using the new screening tools.

5. Compare the prevalence of SGA newborns and the accuracy of identification before and after the implementation of the recommendations.

6. Analyze the data to determine the impact of the recommendations on improving access to maternal health, including the identification of SGA newborns.

7. Use statistical methods, such as chi-square tests or logistic regression, to assess the significance of the findings and determine the effectiveness of the recommendations.

8. Communicate the results of the simulation to healthcare providers, policymakers, and other stakeholders to inform decision-making and potential scale-up of the recommendations to other areas with similar access to maternal health challenges.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email