Associations of single versus multiple anthropometric failure with mortality in children under 5 years: A prospective

Jewel Gausman1, Rockli Kim2,3,4, S V Subramanian4,5

  • 1Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

SSM - Population Health
|December 6, 2021
PubMed

Insights

Concurrent anthropometric failures (AF) in children, specifically stunted and underweight (SU) or stunted, underweight, and wasted (SUW), significantly increase mortality risk. These combined failures account for a substantial percentage of child deaths, highlighting the need for targeted interventions.

Area of Science:

  • Pediatric Nutrition
  • Global Health
  • Child Mortality Studies

Background:

  • Current nutritional status indicators like stunting, underweight, and wasting do not fully capture children with multiple concurrent anthropometric failures (AF).
  • Identifying children with combined nutritional deficits is crucial for accurate risk assessment and intervention.

Purpose of the Study:

  • To estimate the association between various categories of AF and mortality in children aged 1-5 years.
  • To determine the proportion of child deaths attributable to single versus multiple anthropometric failures.

Main Methods:

  • A prospective, longitudinal study of 3605 children in Ethiopia and India was conducted.
  • Mortality risk was analyzed using conventional definitions and mutually exclusive AF categories (stunted only, underweight only, wasted only, SU, underweight and wasted, SUW).
  • Socioeconomic status and demographic variables were adjusted for, and population attributable fractions were calculated.

Main Results:

  • Children with stunted and underweight (SU) and stunted, underweight, and wasted (SUW) had significantly higher odds of death (3.20 and 5.52 times, respectively) compared to children with no AF.
  • No increased mortality risk was observed for children with single anthropometric failures.
  • SUW and SU categories accounted for approximately 42.69% of all child deaths, representing nearly 80% of deaths attributed to AF.

Conclusions:

  • Concurrent anthropometric failures, particularly SUW and SU, are critical indicators of malnutrition-related mortality risk in children.
  • Findings offer valuable insights for public health programs and policies to better identify and support at-risk children.
Abstract

Related Concept Videos

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
775
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
297
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
215
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
147
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
13
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
336