Factors Affecting Exclusive Breastfeeding, Using Adaptive LASSO Regression
Najmeh Maharlouei1, Amirhosein Pourhaghighi2, Hadi Raeisi Shahraki3
1Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Summary
Exclusive breastfeeding (EBF) duration is influenced by maternal education and employment. Promoting EBF programs for educated and working mothers is crucial for community health.
Area of Science:
- Public Health
- Maternal and Child Health
- Pediatrics
Background:
- Exclusive breastfeeding (EBF) for the first six months significantly benefits maternal and child health, particularly in low- and middle-income countries.
- Identifying factors influencing EBF duration is crucial for improving infant health outcomes.
Purpose of the Study:
- To determine the factors affecting the duration of exclusive breastfeeding (EBF) in a sample of Iranian infants.
- To provide evidence for targeted interventions to promote EBF.
Main Methods:
- Prospective study conducted in Fars, Iran (April 2012 - October 2014) with 2640 mothers and healthy term infants.
- Comparison of demographic, medical, and pregnancy-related factors between EBF and non-EBF groups.
- Multivariable analysis using Adaptive Lasso regression to identify significant factors.
Main Results:
- Mean EBF duration was 4.63±1.99 months.
- Maternal education level and employment status (housewife vs. part-time/full-time job) were significantly associated with EBF duration.
- Key factors influencing EBF duration included infant weight gain, pregnancy type (singleton/multiple), maternal perception of milk quantity, postpartum infection, pacifier use, infant irritability, birth place, and mother's employment.
Conclusions:
- Maternal education and employment are significant factors affecting exclusive breastfeeding duration.
- Health policy-makers should promote EBF programs targeting educated and working mothers to improve community health.
- Interventions should address factors like postpartum infection, pacifier use, and infant irritability to support longer EBF duration.
Related Concept Videos
Regression Toward the Mean
7.2K
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...
7.2K
Multiple Regression
4.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.0K
The Pauli Exclusion Principle
59.5K
The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:
59.5K
Correlation and Regression
3.5K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.5K
Regression Analysis
8.4K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.4K
Microsoft Excel: Regression Analysis
1.6K
Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
To perform regression...
1.6K


