Social Determinants in Chronic Disease in British Columbia

September 19, 2017 updated by: Michael Seear, University of British Columbia

The Influence of Social Determinants and Access to Health Care on the Outcome of Children With Chronic Health Problems in British Columbia

Anyone who practices clinical medicine will understand that socially disadvantaged children will have worse health outcomes, no matter what the underlying condition might be. There is limited prospective data on the effects of social deprivation on children in BC and there is none concerning the effects of social deprivation on children with chronic diseases. In order to generate relevant data for those who manage children with chronic diseases in BC, the investigators wish to perform an observational study of the relationship between questionnaire-derived social variables and measured outcomes in children with cystic fibrosis, type 1 diabetes, and chronic kidney disease.

Our working hypothesis is that there is an association between social determinants of health (income, education, race) and health outcomes in children with cystic fibrosis, type 1 diabetes and chronic renal failure, that is independent of access to health care (assessed by distance to nearest specialty clinic and number of clinic visits in the last year).

Study Overview

Detailed Description

  1. Cystic fibrosis (CF). Cystic fibrosis is a genetic condition that causes slowly progressive lung disease. It occurs in people of all social class so the disease itself is independent of social factors. There is considerable variation in the outcome of CF in different children. There are many potential causes for these differences but the available literature would suggest that a significant part of this variability is due to social factors. While there are no prospective clinical studies, the limited information from database reviews suggest that socially deprived children have significantly worse outcomes. In the US, children living in poverty are twice as likely to be underweight and over three times more likely to die (25). UK data is similar - disadvantaged children have worse growth parameters and lower lung function compared to richer children (26).
  2. Type 1 diabetes (T1D). Type 1 diabetes is a multi-factorial disease. It is not an autosomal recessive disease like CF but genetic predisposition can be one of its predisposing features. As with the data on CF, socio-economic deprivation has been shown to have a significant adverse effect on outcome in type 1 diabetes. In the US, glycemic control amongst young adults was significantly worse amongst disadvantaged young adults (27). A retrospective review of New Zealand children with type 1 diabetes also showed that poor socio-economic status and Polynesian ethnicity were significantly associated with poor glycemic control and long term complications (28).
  3. Chronic kidney disease (CKD). Chronic kidney disease may be due to congenital, acquired, or hereditary causes. Within all these groups, socioeconomic status, gender, and race may influence disease progression and outcomes. It has been shown in children with chronic kidney disease, primarily from the United States, that it was more common in low- and middle- income families to have an abnormal birth history such as prematurity, low birth weight or small for age which predisposes to the development of renal disease (29). In addition, blood pressure control and height deficits improve faster in children of families with higher income. In Canada, Aboriginals have a higher prevalence of severe chronic kidney disease and a 77% increased mortality risk (30,31) and a lower likelihood of nephrology clinic visits (32). Aboriginal children and young adults with chronic kidney disease are more likely to have glomerulonephritis as a cause of kidney disease compared to Caucasians and are more likely to reach end stage renal disease (33). In contrast, lower mortality risks are seen in East Asian and Indo Asian Canadian adults starting dialysis (34). There is still much to be studied on the influence of these various factors in renal health and disease.

STUDY DESIGN.

  1. Study Objective. We wish to determine the influence of education, income, race and access to health care upon health outcomes in children with chronic diseases in British Columbia.
  2. Justification. While the effects of social deprivation on health outcomes are commonly discussed, it is surprising how little prospective research there is to quantify the adverse effects of social inequity. There is limited prospective data on the effects of social deprivation on children in BC and there is none concerning the effects of social deprivation on children with chronic diseases. In order to generate firm data relevant for those who manage children with chronic diseases in BC, we wish to perform a cross sectional observational study of the relationship between social variables and outcome in children with cystic fibrosis, type 1 diabetes and chronic kidney disease.
  3. General design. All families in the three clinics will initially be informed of the study by letter. When the child is due for regular follow-up assessment, the parents will be approached during the clinic visit and invited to join the study. Their participation will only involve the completion of a questionnaire. The research assistant will collect the data at interview and will subsequently (with parental permission) retrieve laboratory results from records of previous clinic visits to assess measured health trends over time. The study protocol does not add any further investigations other than the questionnaire. Apart from the variable time needed for parent information and consent, the questionnaire itself will require no more than about 30 minutes to complete.
  4. Questionnaire. We will use a socio-economic assessment questions that we are already using in our study of quality of life in parents caring for children needing home ventilation. It is a conventional form assessing education level, employment, income, partnership status and ethnicity. This last is very important because of the poorer health outcomes already known to be associated with Aboriginal background. The proxy for access to health care will be distance to the main specialty clinic and number of visits in the last year.
  5. Analysis. The relationship between socio-economic variables plus ethnicity and outcome will be examined using multiple linear regression analysis. In the absence of relevant literature, there are too many unknowns to allow any reliable form of power analysis or patient number calculation to be performed. One accepted 'rule of thumb' is that there should be at least 10 patients for each predictive variable in multiple linear regression analysis. We will concentrate on 6 to 8 of the main social factors and will try to enroll over 100 patients within each sub-specialty - enough to ensure 15 to 20 patient outcomes for each variable.

Study Type

Observational

Enrollment (Anticipated)

300

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • British Columbia
      • Vancouver, British Columbia, Canada, V6H 3V4
        • BC's Children's Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

1 year to 17 years (Child)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Participants will be sampled from the cystic fibrosis clinic (150) patients and the chronic kidney disease clinic (150 patients). For the larger type 1 diabetes clinic the sample will be purposefully stratified. Recruitment will be monitored to ensure adequate representation from all the health authorities in BC.

Description

Inclusion Criteria:

  • Any individual who attends British Columbia Children's Hospital Ambulatory clinics in the following areas: cystic fibrosis, chronic kidney disease, or type 1 diabetes

Exclusion Criteria:

  • Refusal to join the study
  • Acute Medical Instability

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Children with Chronic Medical Conditions
The Social Determinants Questionnaire will be administered to the three groups of children with chronic diseases (cystic fibrosis, diabetes mellitus type I, or chronic renal insufficiency). The questionnaire questions will be asked by a research assistant. Each participant will have the same general and background information questions then will have questions specific to their chronic medical condition.
The questionnaire contains a general background information section common to all medical conditions. It then contains separate sections with medical condition specific questions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Level of glycosylated hemoglobin (HbA1C)
Time Frame: 1 year
The level of glycosylated hemoglobin (HbA1C) is the conventional measure of glycemic control and will be used to assess the diabetic group. Data is measured every 3-6 months and will be collected from previous clinic visits. Measurements performed routinely at clinic visits. The monitoring results will be recorded but the study does not require or involve any testing other than tests associated with routine clinical practice.
1 year
Height/weight
Time Frame: 1 year
Height/weight used to assess cystic fibrosis patients. Measurements performed routinely at clinic visits. The monitoring results will be recorded but the study does not require or involve any testing other than tests associated with routine clinical practice.
1 year
Lung Function Tests
Time Frame: 1 year
Lung function tests used to assess cystic fibrosis patients. Measurements performed routinely at clinic visits. The monitoring results will be recorded but the study does not require or involve any testing other than tests associated with routine clinical practice.
1 year
Glomerular filtration rate (GFR)
Time Frame: 1 year
GFR used to assess renal failure patients. Measurements performed routinely at clinic visits. The monitoring results will be recorded but the study does not require or involve any testing other than tests associated with routine clinical practice.
1 year
Albumin/creatinine ratio
Time Frame: 1 year
Albumin/creatinine ratio used to assess renal failure patients. Measurements performed routinely at clinic visits. The monitoring results will be recorded but the study does not require or involve any testing other than tests associated with routine clinical practice.
1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Mike Seear, MD, BCCH

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

September 1, 2014

Primary Completion (Actual)

June 1, 2017

Study Completion (Actual)

August 1, 2017

Study Registration Dates

First Submitted

July 25, 2014

First Submitted That Met QC Criteria

July 28, 2014

First Posted (Estimate)

July 29, 2014

Study Record Updates

Last Update Posted (Actual)

September 21, 2017

Last Update Submitted That Met QC Criteria

September 19, 2017

Last Verified

September 1, 2017

More Information

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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