Routine Life-Course Health Records in Infancy Predict Being Overweight in Childhood and Adolescence: The TMM BirThree

Genki Shinoda1,2, Mami Ishikuro1,2, Taeka Matsubara3

  • 1Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba, Sendai 980-8573, Japan.

Insights

Early identification of childhood overweight risk is possible using health records from 18-23 months. This model predicts overweight status through adolescence, aiding early intervention strategies.

Area of Science:

  • Pediatrics
  • Public Health
  • Biostatistics

Background:

  • Childhood overweight predicts adult obesity and related health issues.
  • Early identification of at-risk children is crucial for intervention.
  • Predicting overweight status requires analyzing longitudinal health data.

Purpose of the Study:

  • To develop a predictive model for childhood and adolescent overweight.
  • To utilize routine health records from 18-23 months of age for prediction.
  • To assess the model's performance across different age groups.

Main Methods:

  • Analysis of 1581 participants from the Tohoku Medical Megabank Cohort Study.
  • Multivariable logistic regression models predicting overweight status at various ages.
  • Evaluation using Area Under the Curve (AUC), calibration, Brier scores, and cross-validation.

Main Results:

  • Overweight status at 18-23 months strongly predicted later overweight.
  • Model discrimination was moderate to high in childhood (AUC 0.873-0.772) and modest in adolescence (AUC 0.720-0.692).
  • Cross-validation confirmed stable predictive performance and acceptable accuracy across all ages.

Conclusions:

  • Routine early life-course health records can moderately predict overweight risk.
  • The developed model shows practical potential for early preventive interventions.
  • Early identification facilitates timely interventions to mitigate long-term health consequences.

Related Concept Videos

Lifestyle Factors and Health01:20

Lifestyle Factors and Health

Lifestyle factors play a critical role in maintaining overall health and preventing chronic diseases. Key elements, such as regular physical activity, a nutritious diet, and abstinence from smoking, can significantly enhance physical, mental, and emotional well-being while reducing the risk of several life-threatening conditions.
Benefits of Physical Activity
Physical activity, whether through structured exercise or casual activities like walking, biking, or dancing, is a cornerstone of a...
592
Obesity01:24

Obesity

The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
1.5K
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
13.7K
Purpose of Health Records II01:19

Purpose of Health Records II

Health records serve various essential purposes in the healthcare system. Here are some key purposes:
1.5K
Purpose of Health Records I01:11

Purpose of Health Records I

The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.9K
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.3K