Zinc supplementation for the prevention of type 2 diabetes mellitus
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the effect of the zinc supplementation in the primary prevention of type 2 diabetes mellitus.
Background
Diabetes Mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion. insulin action, or both. The chronic hyperglycemia of diabetes is associated with long‐term damage, dysfunction, and failure of various organs, especially the eyes, kidneys, nerves, heart, and blood vessels (ADA 1999). For a detailed overview of diabetes mellitus, please see under 'Additional information' in the information on the Metabolic and Endocrine Disorders Group on The Cochrane Library (see 'About the Cochrane Collaboration', 'Collaborative Review Groups (CRGs)').
There are two major forms of diabetes: insulin‐dependent diabetes mellitus (IDDM, type 1 diabetes) and non‐insulin‐dependent diabetes mellitus (NIDDM, type 2 diabetes) (ADA 1999).Type 2 diabetes the most prevalent form of the disease is often asymptomatic and undiagnosed for many years (ADA 1998).
The prevalence of diabetes around the world has been estimated in around 171.000.000 of people (WHO 2000) reaching 299 million by the year 2025 (WHO 1997) and accounts for over $98 billion in health care costs (Tracey L 2003).
The risk of developing type 2 diabetes increases with age, obesity, and lack of physical activity. Related to this, insulin resistance is a fundamental aspect of the etiology of type 2 diabetes (Barbara B 2000). This way, the majority of patients who develop type 2 diabetes are insulin resistance, and the hyperglycemia occurs when these patients can no longer support the degree of compensatory hyperinsulinemia required to prevent gross decompensation of glucose homeostasis (Tracey L 2003). The insulin resistance has been shown to be associated with prevalent atherosclerosis (Howard 1996), hypertriglyceridemia (Moro 2003), glucose intolerance, dyslipidemia, hyperuricemia, hypertension (Bonora 1998) and polycystic ovarian disease (Barbara B 2000).
The insulin resistance can be measured by using the glucose Clamp technique (DeFronzo 1979) which method is considered the "gold standard" in the assessment of insulin sensitivity ( Karelis 2004), however, this method is laborious, expensive and inadequate for large‐scale or epidemiological studies (Bonora 2000). Matthews Y Cols showed the Homeostasis Model Assessment (HOMA), that derives an estimate of insulin sensitivity by simple of fasting plasma glucose and insulin concentrations. Therefore, the HOMA is a method that evaluates the sensibility or insulin resistance and the function of the ß‐cells. The estimate of insulin resistance is calculated with the formula: fasting serum insulin (µU/ml)X fasting plasma glucose (mmol/L) /22,5 (Matthews 1985). Several studies have investigated the role of zinc status in insulin secretion and metabolism. The zinc seems to stimulate insulin action and insulin receptor tyrosine Kinase (IRTK) activity ( Marchesini 1998;Rossetti 1990).
The daily recommendation of zinc for women is 12 mg and for men 12 mg. The studies suggest an oral supplementation of zinc sulfate from 30 to 200 mg per day. Amounts of 2 g/dia or more can cause gastrointestinal irritation and vomit (Marchesini 1998;Marreiro 2004).
The effect of supplementation with zinc was assessed in 10 patients with cirrhosis, such supplementation corresponds approximately 136 mg zinc per day. The 10 cirrhotic patients presented impaired glucose tolerance and deficiencies in zinc. The study shows that zinc supplementation produces significant improvement in glucose disposal. Probably the action of zinc would the related to the increasing activity of the insulin independent glucose transporters GLUT 1 and GLUT2 (Marchesini 1998).
The Impaired glucose tolerance (IGT) and Impaired fasting glucose ( IFG) are associated with the insulin resistance. IFG and IGT refer to a metabolic stage intermediate between normal glucose homeostasis and diabetes. This stage includes individuals who have IGT and individuals with fasting glucose levels higher or similar to 110 mg/dl but lower than 126 mg/dl or after 2‐h values in the OGTT higher or similar to 140 mg/dl but lower than 200 mg/dl.
The aim of this review is to assess the benefits of the zinc supplementation in patients with insulin resistance in several pathologies with the intention to prevent type 2 diabetes mellitus.
Objectives
To assess the effect of the zinc supplementation in the primary prevention of type 2 diabetes mellitus.
Methods
Criteria for considering studies for this review
Types of studies
All randomised controlled clinical trials and quasi‐randomized.
Types of participants
Adults living in the community, 18 years or older with insulin resistance.
The diabetic patients will be excluded according to the validated parameters.
Diagnostic Criteria:
The insulin resistance will be measured by homeostasis Model Assessment (HOMA) or glucose clamp technique.
Types of interventions
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Zinc versus placebo or no interventions;
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Different doses of zinc versus placebo or no interventions.
Types of outcome measures
Main outcome measures
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Incidence of type 2 diabetes mellitus.
Additional outcome measures
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Decrease of the insulin resistance;
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Quality of life;
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Mortality;
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Costs;
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Adverse effects;
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Cholesterol levels, LDL cholesterol levels, HDL cholesterol levels and/or triglycerides, leptin concentration;
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Metabolic control;
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Others.
Timing of outcome assessment
Time of the decrease of insulin resistance will be assessed: Short (four weeks or less), medium (over four weeks to less than four months) and long term (four months or more) .
Search methods for identification of studies
There will be no language restriction. Trials will be obtained from the following sources:
1. Electronic databases: We will search the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, latest issue), MEDLINE (up to present), Excerpta Médica ‐ EMBASE (up to present), Literatura Latino‐Americana e do Caribe em Ciências da Saúde ‐ LILACS (up to present) for identification of randomised controlled trials and controlled trials.
Ongoing trials
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Current Controlled Trials (www.controlled‐trials.com),
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National Research Register (http://www.update‐software.com/National/) and
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Clinical Research Studies (http://clinicalstudies.info.NIH.gov).
We will search terms for zinc, insulin resistance and diabetes mellitus in order to maximise the sensitivity of the search strategy. As we will search with both subject headings and free text words, this will include all studies about zinc and insulin resistance. Please see Table 1 for the detailed search strategy.
| Database | Search strategy |
| Unless otherwise stated, search terms were free text terms; exp = exploded MeSH: Medical subject heading (Medline medical index term); the dollar sign ($) stands for any character(s); the question mark (?) = to substitute for one or no characters; tw = text word; pt = publication type; sh = MeSH: Medical subject heading (Medline medical index term); adj = adjacency. | |
| Medline (OVID) | (1) exp ZINC/ |
| Lilacs | #1 = Zinc OR (Serum Zinc Level$) #2 = (Adult‐Onset Diabetes Mellitus) OR (Adult Onset Diabetes Mellitus) OR (Ketosis‐Resistant Diabetes Mellitus) OR (Ketosis Resistant Diabetes Mellitus) OR (Maturity‐Onset Diabetes Mellitus) OR (Maturity Onset Diabetes Mellitus) OR (Non Insulin Dependent Diabetes Mellitus) |
2. Reference lists: references of the identified relevant studies will be scrutinized for additional citations.
3. Personal contact: authors of relevant identified studies and other experts will be tried to be contacted in order to obtain additional references, unpublished trials, ongoing trials or obtain missing data not reported in the original trials.
4. Handsearching: we will try to identify additional studies by searching the reference lists of relevant trials and reviews identified. For the search strategy we will use the expertise and assistance of the Cochrane Metabolic and Endocrine Disorders Group.
Data collection and analysis
Trials selection
The evaluation of the studies with potential inclusion will be carried out by two independent reviewers (VB and RPED). They will scan the titles, abstracts and of every record. Full articles will be retrieved for further assessment if the information given suggests that the study: 1. includes patients with insulin resistance, 2. compares zinc intervention with placebo All randomised controlled clinical trials and quasi‐randomized controlled trials. If there is any uncertainty a third party (ANA) will be consulted and a judgement will be made based on consensus. If resolving disagreement is not possible, the article will be added to those 'awaiting assessment' and the authors will be contacted for clarification. If no clarification is supplied, the review group editorial base will be consulted. Interrater agreement for study selection will be measured using the kappa statistic (Cohen 1960).
Quality assessment of trials
The quality of reporting each trial will be assessed based largely on the quality criteria specified by Schulz and by Jadad (Schulz 1995; Jadad 1996). In particular, the following factors will be studied:
1. Minimisation of selection bias ‐ a) was the randomisation procedure adequate? b) was the allocation concealment adequate? Is there systematic difference between comparison groups?
A. Adequate allocation concealment
B. Unclear ‐ not informed in the publication and information impossible to be acquired from the authors of primary studies.
C. Unadequate.
D. Not used
We will not include any studies classified as 'D' in this review.
2. Detection bias
(1) Met: assessors unaware of the assigned treatment when collecting outcome measures;
(2) Unclear: blinding of assessor not reported and cannot be verified by contacting investigators;
(3) Not met: assessors aware of the assigned treatment when collecting outcome measures.
3. Minimisation of attrition bias
(1) Met: less than 20% and equal for both groups;
(2) Unclear: not reported in paper or by authors;
(3) Not met: greater than 20% or/and not equally for both comparison groups.
Although, there are not evidence that a drop‐out rate of less than 20% is a quality criterion, in this review we will use this classification.
4. Minimisation of performance bias ‐ participants, caretakers or responsible for medication administration were blinded to the allocation?
Based on these criteria, studies will be broadly subdivided into the following three categories (see Cochrane Handbook) (Alderson 2004):
Low risk of bias: All quality criteria met:
Moderate risk of bias: one or more of the quality criteria only partly met.
High risk of bias: one or more criteria not met.
Each trial will be assessed independently by two reviewers (VB, RPED). Interrater agreement will be calculated using the kappa statistic. In cases of disagreement, the rest of the group will be consulted and a judgement will be made based on consensus. Additionally, we will explore the influence of individual quality criteria in a sensitivity analysis.
Data extraction
Data which will be extracted will include the following:
1. General information: published / unpublished, title, authors, source, contact address, country, language of publication, year of publication, duplicate publications.
2. Trial characteristics: design, duration, randomisation (and method), allocation concealment (and method), blinding (participants, people administering treatment and outcome assessors), check of blinding.
3. Intervention characteristics: zinc intervention, comparison placebo (method, timing).
4. Patients characteristics: sampling (random / convenience), exclusion criteria, total number and number in comparison groups, gender, age, diagnostic criteria of diabetes, similarity of groups at baseline, assessment of compliance / relapse, withdrawals / losses to follow‐up (reasons / description), subgroups.
5. Outcomes: outcomes specified above, what was the main outcome assessed in the study, other events, length of follow‐up.
6. Results: for outcomes and times of assessment, intention‐to‐treat analysis.
7. The doubled references will be excluded and added in the same document (like a reference list).
Data analysis
The relative risk (RR) will be used as the effect measure for dichotomous data. Estimated effect of continuous data will be assessed by weighted mean difference. For both continuous and dichotomous data, metanalysis will be made when the primary studies report the same outcome measures.
Heterogeneity
Inconsistency among the pooled estimates will be quantified using the I2 = [(Q ‐ df)/Q] x 100% test, where Q is the chi‐squared statistic and df its degrees of freedom. This illustrates the percentage of the variability in effect estimates resulting from heterogeneity rather than sampling error (Handbook 2004; Higgins 2003). If there is significant heterogeneity (I2 > 50%) we will make a qualitative summary of the evidence.
Subgroup analysis
In this review subgroup analyses will be performed, if necessary by personal characteristics such as age, pathology, different doses, time of interventions.
Sensitivity analysis
We will perform sensitivity analyses in order to explore the influence of the following factors on effect size:
1. Repeating the analysis excluding unpublished studies.
2. Repeating the analysis taking account of study quality, as specified above.
3. Repeating the analysis excluding any very long or large studies to establish how much they dominate the results.
4. Repeating the analysis excluding studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), country.
The robustness of the results will also be tested by repeating the analysis using different measures of effects size (risk difference, odds ratio etc.) and different statistic models (fixed and random effects models).
Addressing publication bias
We will attempt to assess publication bias by preparing a funnel plot (trial effect versus trial size) using RevMan Analyses.
| Database | Search strategy |
| Unless otherwise stated, search terms were free text terms; exp = exploded MeSH: Medical subject heading (Medline medical index term); the dollar sign ($) stands for any character(s); the question mark (?) = to substitute for one or no characters; tw = text word; pt = publication type; sh = MeSH: Medical subject heading (Medline medical index term); adj = adjacency. | |
| Medline (OVID) | (1) exp ZINC/ |
| Lilacs | #1 = Zinc OR (Serum Zinc Level$) #2 = (Adult‐Onset Diabetes Mellitus) OR (Adult Onset Diabetes Mellitus) OR (Ketosis‐Resistant Diabetes Mellitus) OR (Ketosis Resistant Diabetes Mellitus) OR (Maturity‐Onset Diabetes Mellitus) OR (Maturity Onset Diabetes Mellitus) OR (Non Insulin Dependent Diabetes Mellitus) |
