The Association Between Food Insecurity and Incident Type 2 Diabetes in Canada: A Population-based Cohort Study

NCT03243136 | Completed

• 1 other identifier: PROTOCOL REFERENCE # 32143
• Study Type: observational
• Target: 4,739
• Locations: 0 countries
• Sites: N/A

Brief Summary

A pervasive and persistent finding is the health disadvantage experienced by those in food insecure households. While clear associations have been identified between food insecurity and diabetes risk factors, less is known about the relationship between food insecurity and incident type 2 diabetes. The objective of this study is to investigate the association between household food insecurity and the future development of type 2 diabetes. The investigators used data from Ontario adult respondents to the 2004 Canadian Community Health Survey, linked to health administrative data (n = 4,739). Food insecurity was assessed with the Household Food Security Survey Module and incident type 2 diabetes cases were identified by the Ontario Diabetes Database. Multivariable adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for type 2 diabetes as a function of food insecurity.

Conditions

Type2 Diabetes

Outcome Measures

Primary Outcomes (1)

• Type 2 diabetes

  Incident type 2 diabetes

  2004-2016

Interventions

Exposure of interest is food insecurity OTHER

Households were considered food insecure if any of the following conditions were met in the past 12 months: 1) a member of the household worried that there would not be enough food to eat because of a lack of money, 2) a member's food intake was reduced as a result of there not being enough food to eat, or 3) the desired variety or quality of foods was not eaten because of a lack of money. This exposure variable was operationalized as a binary variable with levels of food secure vs. food insecure.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The investigators used data from Ontario adult respondents to Cycle 2.2 of Canadian Community Health Survey conducted in 2004, deterministically linked to the Ontario Diabetes Database. The Canadian Community Health Survey is a cross-sectional survey administered by Statistics Canada that uses a multi-stage, stratified, clustered probability sample that is representative of 98% of the Canadian population. Those who are full-time members of the Canadian Forces, reside on First Nations Reserves or Crown Lands, are institutionalized, and who reside in certain remote areas reflect the 2% of the population not captured by the survey. Detailed descriptions of the survey methodology have been published elsewhere.

The investigators restricted the analyses to individuals ≥ 18 years of age at baseline who were successfully linked to the Ontario Diabetes Database (n = 5,539). The investigators further excluded pregnant women from the sample to increase the accuracy of body weight measurements (n = 36), prevalent cases of diabetes before respondents' 2004 Canadian Community Health Survey interview date (n = 636), underweight individuals (n = 112), and those who had missing information on food security status (n = 16). After these exclusions, the analytic cohort consists of 4,739 individuals, 2,050 men and 2,689 women.

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Sponsors & Collaborators

• Christopher Tait: lead
• Ontario Agency for Health Protection and Promotion: collaborator

Study Officials

• Christopher Tait, PhD(c)

  University of Toronto - Dalla Lana School of Public Health

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: PhD Candidate

Study Record Dates

• First Submitted: August 4, 2017
• First Posted: August 8, 2017
• Study Start: January 1, 2004
• Primary Completion: March 31, 2016
• Study Completion: March 31, 2016
• Last Updated: August 8, 2017

Record last verified: 2017-08

Data Sharing

• IPD Sharing: Will not share