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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
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While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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Related Experiment Video

Updated: May 24, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
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Identifying predictors for food insecurity in England: a cross-sectional database analysis.

Adam K Stanley1,2, Yasir Hadi3, David Newbold4

  • 1East Lancashire NHS Hospitals Trust, Blackburn, UK. Adam.stanley@elht.nhs.uk.

Journal of Health, Population, and Nutrition
|February 28, 2025
PubMed
Summary

Food insecurity in England is linked to younger age, larger households, having children, low income, unemployment, minority ethnicities, and chronic conditions. Identifying these risk factors is crucial for targeted support.

Keywords:
Food insecurityFood povertyFood securityInequalityInequityNutrition

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Area of Science:

  • Public Health
  • Nutrition Science
  • Socioeconomic Determinants of Health

Background:

  • Nutrition is a key modifiable risk factor for non-communicable diseases globally.
  • Food security, defined as access to sufficient healthy food, is a growing concern in the UK, with rising prices impacting low-income households.
  • UK food insecurity rates are among the highest in Europe.

Purpose of the Study:

  • To identify predictors of household food insecurity in England.
  • To analyze nationally representative data to understand factors contributing to food insecurity.

Main Methods:

  • Analysis of the 'Food and You 2: Wave 6' cross-sectional dataset.
  • Utilized the USDA Household Food Security Survey Module to define food security status.
  • Calculated risk ratios for food insecurity based on demographics, socioeconomic status, and health conditions.

Main Results:

  • 23.4% of households experienced food insecurity.
  • Increased risk associated with younger age groups (<65), larger households (≥5), presence of young children (<16 and <6), income <£64,000, unemployment, student status, Asian/African ethnicities, chronic conditions, and high deprivation (IMD=1).

Conclusions:

  • Age, household size, presence of children, income, employment, ethnicity, and Index of Multiple Deprivation (IMD) are significant predictors of food insecurity.
  • Further research is needed to develop screening tools for identifying at-risk populations.
  • Effective support provision requires understanding these complex relationships.