Calcium supplementation for prevention of primary hypertension
Abstract
Background
Hypertension is a major public health problem that increases the risk of cardiovascular and kidney diseases. Several studies have shown an inverse association between calcium intake and blood pressure, as small reductions in blood pressure have been shown to produce rapid reductions in vascular disease risk even in individuals with normal blood pressure ranges. This is the first update of the review to evaluate the effect of calcium supplementation in normotensive individuals as a preventive health measure.
Objectives
To assess the efficacy and safety of calcium supplementation versus placebo or control for reducing blood pressure in normotensive people and for the prevention of primary hypertension.
Search methods
The Cochrane Hypertension Information Specialist searched the following databases for randomised controlled trials up to September 2020: the Cochrane Hypertension Specialised Register, CENTRAL (2020, Issue 9), Ovid MEDLINE, Ovid Embase, the WHO International Clinical Trials Registry Platform, and the US National Institutes of Health Ongoing Trials Register, ClinicalTrials.gov. We also contacted authors of relevant papers regarding further published and unpublished work. The searches had no language restrictions.
Selection criteria
We selected trials that randomised normotensive people to dietary calcium interventions such as supplementation or food fortification versus placebo or control. We excluded quasi‐random designs. The primary outcomes were hypertension (defined as blood pressure ≥ 140/90 mmHg) and blood pressure measures.
Data collection and analysis
Two review authors independently selected trials for inclusion, abstracted the data and assessed the risks of bias. We used the GRADE approach to assess the certainty of evidence.
Main results
The 2020 updated search identified four new trials. We included a total of 20 trials with 3512 participants, however we only included 18 for the meta‐analysis with 3140 participants. None of the studies reported hypertension as a dichotomous outcome. The effect on systolic and diastolic blood pressure was: mean difference (MD) ‐1.37 mmHg, 95% confidence interval (CI) ‐2.08, ‐0.66; 3140 participants; 18 studies; I2 = 0%, high‐certainty evidence; and MD ‐1.45, 95% CI ‐2.23, ‐0.67; 3039 participants; 17 studies; I2 = 45%, high‐certainty evidence, respectively. The effect on systolic and diastolic blood pressure for those younger than 35 years was: MD ‐1.86, 95% CI ‐3.45, ‐0.27; 452 participants; eight studies; I2 = 19%, moderate‐certainty evidence; MD ‐2.50, 95% CI ‐4.22, ‐0.79; 351 participants; seven studies ; I2 = 54%, moderate‐certainty evidence, respectively. The effect on systolic and diastolic blood pressure for those 35 years or older was: MD ‐0.97, 95% CI ‐1.83, ‐0.10; 2688 participants; 10 studies; I2 = 0%, high‐certainty evidence; MD ‐0.59, 95% CI ‐1.13, ‐0.06; 2688 participants; 10 studies; I2 = 0%, high‐certainty evidence, respectively. The effect on systolic and diastolic blood pressure for women was: MD ‐1.25, 95% CI ‐2.53, 0.03; 1915 participants; eight studies; I2 = 0%, high‐certainty evidence; MD ‐1.04, 95% CI ‐1.86, ‐0.22; 1915 participants; eight studies; I2 = 4%, high‐certainty evidence, respectively. The effect on systolic and diastolic blood pressure for men was MD ‐2.14, 95% CI ‐3.71, ‐0.59; 507 participants; five studies; I2 = 8%, moderate‐certainty evidence; MD ‐1.99, 95% CI ‐3.25, ‐0.74; 507 participants; five studies; I2 = 41%, moderate‐certainty evidence, respectively. The effect was consistent in both genders regardless of baseline calcium intake.
The effect on systolic blood pressure was: MD ‐0.02, 95% CI ‐2.23, 2.20; 302 participants; 3 studies; I2 = 0%, moderate‐certainty evidence with doses less than 1000 mg; MD ‐1.05, 95% CI ‐1.91, ‐0.19; 2488 participants; 9 studies; I2 = 0%, high‐certainty evidence with doses 1000 to 1500 mg; and MD ‐2.79, 95% CI ‐4.71, 0.86; 350 participants; 7 studies = 8; I2 = 0%, moderate‐certainty evidence with doses more than 1500 mg. The effect on diastolic blood pressure was: MD ‐0.41, 95% CI ‐2.07, 1.25; 201 participants; 2 studies; I2 = 0, moderate‐certainty evidence; MD ‐2.03, 95% CI ‐3.44, ‐0.62 ; 1017 participants; 8 studies; and MD ‐1.35, 95% CI ‐2.75, ‐0.05; 1821 participants; 8 studies; I2 = 51%, high‐certainty evidence, respectively.
None of the studies reported adverse events.
Authors' conclusions
An increase in calcium intake slightly reduces both systolic and diastolic blood pressure in normotensive people, particularly in young people, suggesting a role in the prevention of hypertension. The effect across multiple prespecified subgroups and a possible dose response effect reinforce this conclusion. Even small reductions in blood pressure could have important health implications for reducing vascular disease. A 2 mmHg lower systolic blood pressure is predicted to produce about 10% lower stroke mortality and about 7% lower mortality from ischaemic heart disease.
There is a great need for adequately‐powered clinical trials randomising young people. Subgroup analysis should involve basal calcium intake, age, sex, basal blood pressure, and body mass index. We also require assessment of side effects, optimal doses and the best strategy to improve calcium intake.
PICOs
Plain language summary
Extra calcium to prevent high blood pressure
Review question
We wanted to find out the effects of calcium intake on blood pressure in people with normal blood pressure.
Background
Hypertension is a serious health problem that increases the risk of heart and kidney diseases. Several studies have shown that increasing calcium intake lowers blood pressure even in individuals within a normal blood pressure range. Increasing calcium intake also has benefits for pregnancy outcomes, effects which are thought to be mediated also by blood pressure reduction. High blood pressure has been identified as a major risk factor for mortality and even small reductions in blood pressure can decrease the occurrence of coronary artery disease, stroke and death.
Study characteristics
We selected studies that assessed the effect of dietary calcium interventions such as supplementation or food fortification on blood pressure in normotensive people of all ages. Searches were last run in September 2020.
Key findings
This review analysed information from 20 trials of which 18 trials (3140participants) provided date for the effect of the intervention. We found that an increase in calcium intake slightly reduces both systolic and diastolic blood pressure by 1.37 mmHg lower and by 1.45 mmHg lower, respectively. This effect was higher with doses of calcium above 1000 mg/day. Systolic blood pressure was reduced by 1.05 mmHg with doses of calcium 1000 to 1500 mg/day and by 2.79 mmHg with doses of calcium equal to or over 1500 mg/day.
We noted a reduction in blood pressure in both men and women and at ages from 11 to 82 years old, but the reduction was greater among younger people. Systolic blood pressure was reduced by 1.86 mmHg among those less than 35 years and by 0.97 mmHg among those 35 years or older.
None of the studies reported adverse events. We need further research to determine the ideal dosage of supplementation and whether it is more effective and safer as part of the diet or as a supplement.
Quality of the evidence
We found high quality of evidence for systolic and diastolic blood pressure in both men and women. The quality of evidence was also high for participants 35 years or older and moderate for younger people.
The quality of evidence was high for doses of calcium of 1000 to 1500 mg/day and was moderate for lower or higher doses.
Five of the 18 trials were industry funded.
Authors' conclusions
Summary of findings
| Calcium supplementation/fortification compared to control for prevention of primary hypertension | |||||
| Patient or population: People who may be at risk for primary hypertension | |||||
| Outcomes | Illustrative blood pressure in control group b | Mean difference in mmHg (95% CIa) | No of participants | Quality of the evidence | Comments |
|---|---|---|---|---|---|
| Systolic blood pressure (range of follow‐up from 4 weeks to 4 years) | 115.62 | 1.37 lower (2.08 lower to 0.66 lower) | 3140 | ⊕⊕⊕⊕ | Women: ‐1.25 mmHg [95% CI: ‐2.53, 0.03; 8 studies] Men: ‐2.07 mmHg [95% CI: ‐3.56, ‐0.59; 5 studies] Both: ‐1.11 mmHg [95% CI: ‐2.15, ‐0.08; 6 studies] |
| Diastolic blood pressure (range of follow‐up from 4 weeks to 4 years) | 78.17 | 1.45 lower (2.23 lower to 0.67 lower)
| 3039 | ⊕⊕⊕⊕ | Women: ‐1.03 mmHg [95% CI: ‐1.80, ‐0.26; 8 studies] Men: ‐1.91 mmHg [95% CI: ‐2.80, ‐1.02; 5 studies] Both: ‐0.25 mmHg [95% CI: ‐1.08, 0.57; 5 studies] |
| Systolic blood pressure. Dose less than 1000 mg a day (range of follow‐up from 12 weeks to 2 years) | 103.74 | 0.02 lower (2.23 lower to 2.20 higher) | 302 | ⊕⊕⊕⊝ | Subgroup analysis by dose |
| Systolic blood pressure. Dose between 1000 mg a day and less than 1500 mg a day (range from 4 weeks to 2 years) | 116.29 | 1.05 lower (1.91 lower to 0.19 lower) | 2488 | ⊕⊕⊕⊕ | Subgroup analysis by dose |
| Systolic blood pressure. Dose 1500 mg a day or more (range of follow‐up from 4 weeks to 4 years) | 112.85 | 2.79 lower (4.71 lower to 0.86 lower) | 350 | ⊕⊕⊕⊝ | Subgroup analysis by dose |
| Systolic blood pressure. Less than 35 years of age (range of follow‐up from 4 weeks to 22 weeks) | 113.23 | 1.79 lower (3.20 lower to 0.38 lower) | 452 | ⊕⊕⊕⊝ | Subgroup analysis by age |
| Systolic blood pressure. 35 years or older (range of follow‐up from 4 weeks to 4 years) | 124.20 | 0.97 lower (1.83 lower to 0.10 lower) | 2688 | ⊕⊕⊕⊕ | Subgroup analysis by age |
| Adverse events (secondary outcome) |
|
|
|
| One study evaluated side effects, but none were reported. A further two studies mentioned that the supplements were well tolerated. No trials reported any incidence of kidney stone formation, iron deficiency anaemia, anaemia, cardiovascular events, myocardial infarction, stroke or mortality. |
| aCI: Confidence interval; bEstimated using Comprehensive Meta‐Analysis Software Software; cGRADE Working Group grades of evidence |
| ||||
|
High quality: Further research is very unlikely to change our confidence in the estimate of effect. |
| ||||
| 1. Downgraded one level for imprecision due to small number of participants. | |||||
Background
Description of the condition
The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure defines "hypertension" as blood pressure above 139 mmHg systolic or diastolic above 89 mmHg, or both. It also defines blood pressure ranging from 120–139 mmHg systolic or 80–89 mmHg diastolic, or both, as “prehypertension” in order to identify those individuals in whom early intervention by adoption of healthy lifestyles could reduce blood pressure, decrease the rate of progression of blood pressure to hypertensive levels with age, or prevent hypertension entirely (Chobanian 2003).
Primary hypertension may develop as a result of environmental or genetic causes. Secondary hypertension has multiple aetiologies, such as renal, vascular, and endocrine causes. Primary or essential hypertension accounts for 90‐95% of adult cases and secondary hypertension accounts for 2‐10% of cases (Carretero 2000).
Hypertension is a major public health problem that increases the risk of cardiovascular and kidney diseases in both the developed and the developing world. The global prevalence of hypertension and high blood pressure is estimated to be 30% and 26%, respectively (Kearney 2004), and high blood pressure has been estimated to increase to 29% by the year 2025 (Kearney 2005).
High blood pressure has been identified as the leading risk factor for mortality and the third leading risk factor for disease burden globally (Ezzati 2002). In the year 2001, 7.6 million (13.5%) of all deaths were attributable to high blood pressure (Lawes 2008).
While the prevalence of hypertension seems to be stabilising or decreasing in the developed world, it is increasing in developing countries (Kearney 2004). Low‐income and middle‐income regions contribute up to 80% of the attributable burden of disease, affecting the younger age groups more than in high‐income countries (Lawes 2008). While chronic diseases have increased in these countries, problems related to undernutrition such as micronutrient deficiencies persist, causing a double burden of disease (Llanos 2008). These present a challenge to developing interventions, as excess and deficit nutritional problems have to be tackled within the same population and frequently within the same home (Garrett 2005).
Description of the intervention
Several studies have shown an inverse association between calcium intake and blood pressure or hypertension. The hypothesis originated with the observation that indigenous Guatemalan women have a low incidence of oedema‐, proteinuria‐, and hypertension‐gestosis associated with a high calcium intake due to the Mayan habit of treating corn with lime water (Belizan 1980). Based on this hypothesis, a series of studies has been conducted mainly in pregnant women, but also in children, as well as in young and older adults (Belizan 1980; Belizan 1983).
A recent World Health Organization (WHO) review of observational epidemiological and ecological studies found an inverse (protective) association between cardiovascular disease mortality and increased water hardness (measured by calcium carbonate or another hardness parameter and/or the calcium and magnesium content of water) (WHO 2009).
A Cochrane review in 2006 found that calcium supplementation in hypertensive people elicited a small but statistically significant reduction in systolic blood pressure (SBP) (mean difference: ‐2.5 mmHg, 95% confidence interval (CI) ‐4.5 to ‐0.6), but not in diastolic blood pressure (DBP) (mean difference: ‐0.8 mmHg, 95% CI ‐2.1 to 0.4) (Dickinson 2006).
Several reviews have shown an association between calcium intake and blood pressure (Allender 1996; Griffith 1999; Van Mierlo 2006). A review in 2006 found that calcium supplementation (mean daily dose: 1200 mg) reduced SBP by 1.86 mmHg (95% CI 2.91 to 0.81) and DBP by 0.99 mmHg (95% CI 1.61 to 0.37) (Van Mierlo 2006). In people with a relatively low calcium intake (less than 800 mg per day), higher blood pressure reduction was obtained, a mean of 2.63 (95% CI 4.03 to 1.24) for SBP and 1.30 (95% CI 2.13 to 0.47) for DBP.
Furthermore, a Cochrane review has shown that calcium supplementation has an effect on reducing pregnancy hypertensive diseases (Hofmeyr 2018).
How the intervention might work
Calcium intake may regulate blood pressure by modifying intracellular calcium in vascular smooth muscle cells and by varying vascular volume through the renin–angiotensin–aldosterone system. Low calcium intake produces a rise of parathyroid gland activity (Villa‐Etchegoyen 2019). The parathyroid hormone (PTH) increases intracellular calcium in vascular smooth muscles resulting in vasoconstriction. Parathyroidectomised animals did not show an increase in blood pressure when fed a low calcium diet as did sham‐operated animals (Belizan 1984). Low calcium intake also increases the synthesis of calcitriol in a direct manner or mediated by PTH. Calcitriol increases intracellular calcium in vascular smooth muscle cells. Both low calcium intake and PTH may stimulate renin release and consequently angiotensin II and aldosterone synthesis (Villa‐Etchegoyen 2019).
Why it is important to do this review
Small reductions in blood pressure have been predicted to have important health implications, as they have been shown to produce rapid reductions in vascular disease risk even in individuals with normal blood pressure ranges (Lewington 2002). A 2 mmHg‐lower systolic blood pressure is predicted to produce about 10% lower stroke mortality and about 7% lower mortality from ischaemic heart disease, while a 5 mmHg reduction in SBP at the population level is predicted to result in a 14% reduction in stroke death, a 9% reduction in coronary artery disease‐related death and a 7% reduction in total mortality (Whelton 2002). In the same way, a 2 mmHg reduction in SBP in adults is estimated to have the potential to save about 12,000 lives a year in the United States (Stamler 1991).
Due to the high frequency of hypertension, population‐based strategies to reduce blood pressure are more cost‐effective than individual strategies (Kearney 2005).
Calcium supplementation or food fortification are affordable interventions that, if proven effective in reducing blood pressure even by small levels, could have considerable impact at a population level (Cormick 2021). The effects on children and young people are of particular importance, as blood pressure tends to track into adulthood (Williams 2011).
This review explores the efficacy and safety of calcium supplementation or food fortification in preventing hypertensive‐related problems in normotensive people of different ages. It looks at the effect of reducing blood pressure in each population group and of preventing, rather than treating, hypertensive‐related problems. It also provides more information on the effect of increasing calcium intake on blood pressure in non‐pregnant women of reproductive age. Reviewing the effect of calcium in a normotensive population is valuable for assessing whether it could allow women to reach pregnancy with a lower range of blood pressure and a lower risk of developing pre‐eclampsia or eclampsia.
As there have been some concerns about adverse events of calcium supplementation (Bolland 2008; Curhan 2004; Harris 2002), there is a need to assess adverse events such as renal tract stone formation, impaired absorption of other minerals and increased cardiovascular events.
Excess calcium in the body had been implicated as a risk factor for kidney stone formation; however, data suggest that free calcium in the body does not increase the risk and that high calcium intake may actually be a protective factor against the formation of kidney stones (Curhan 2004; Heaney 2006; Jackson 2006; Williams 2001; Cormick 2019a).
The effect of calcium supplementation on cardiovascular events is unclear, as there are currently conflicting data, studies have not been powered to significantly detect cardiac events, and the methodology does not allow the results to be generalisable to a broader population. Two studies that were conducted in cohorts of older women have reported a higher incidence of cardiovascular events such as myocardial infarction and the composite end point of myocardial infarction, stroke, or sudden death in the experimental groups, however, these differences were not statistically significant (Bolland 2008; Sabbagh 2009). More recent meta‐analyses have questioned this evidence (Lewis 2012; Lewis 2015).
Calcium has been shown to interfere with iron absorption in the short term; however, research has also shown that prolonged calcium supplementation has no effect on iron absorption over time (Harris 2002; Ilich‐Ernst 1998; Kalkwarf 1998; Palacios 2021; Sokoll 1992).
It is important to update this review as new evidence has been published since the last publication of our review in 2015.
Objectives
To assess the efficacy and safety of calcium supplementation versus placebo or control for reducing blood pressure in normotensive people and for the prevention of primary hypertension.
Methods
Criteria for considering studies for this review
Types of studies
All published, unpublished and ongoing trials with random allocation to dietary calcium intervention such as supplementation or food fortification versus placebo or control. We excluded quasi‐random designs and the second phase of cross‐over trials from the analysis.
Types of participants
Participants included normotensive people of different ages, but excluding pregnant women.
Types of interventions
We included calcium interventions such as supplementation using pills, tablets or sprinkle powder, or any food or beverage fortification, compared to placebo or control.
Calcium fortification could include salt of calcium carbonate, sulphate, citrate, citrate malate, chloride, hydroxyapatite, phosphate, acetate, lactate, glycerophosphate, gluconate, oxide, or hydroxide. Calcium content in these salts varies from 9% to 70% (Allen 2006).
We excluded studies with no placebo or control. We also excluded interventions where calcium was combined with other macro‐ or micronutrients to assess the effects of both.
Types of outcome measures
We selected the following outcomes. Minimum follow‐up time was two weeks. For multiple time points, we analysed the longest intervention period.
Primary outcomes
-
Hypertension, defined as blood pressure ≥ 140/90 mmHg
-
Systolic and diastolic blood pressure
Secondary outcomes
-
Any adverse event
-
Withdrawals due to adverse events
-
Kidney stone formation
-
Iron deficiency anaemia
-
Anaemia
-
Total mortality
-
Cardiovascular events
-
Myocardial infarction
-
Stroke
-
Sudden death
Search methods for identification of studies
Electronic searches
The Cochrane Hypertension Information Specialist designed strategies for and searched the following databases without language, publication year or publication status restrictions:
-
the Cochrane Hypertension Specialised Register via the Cochrane Register of Studies (to 30 September 2020);
-
the Cochrane Central Register of Controlled Trials (CENTRAL, 2020 Issue 9) via the Cochrane Register of Studies (to 29 September 2020);
-
Ovid MEDLINE(R) and Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations, Daily and Versions(R) (1946 to 29 September 2020);
-
Embase Ovid (1974 to 29 September 2020);
-
US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov) (to 29 September 2020);
-
World Health Organization International Clinical Trials Registry Platform via the Cochrane Register of Studies (to 30 September 2020).
The Information Specialist modelled subject strategies for databases in the search strategy designed for MEDLINE. Where appropriate, they were combined with subject strategy adaptations of the highly sensitive‐ and precision‐maximising search strategy designed by Cochrane for identifying randomised controlled (as described in the Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0, Box 6.4.d. (Higgins 2011)). We present search strategies for major databases in Appendix 1.
Searching other resources
-
The Cochrane Hypertension Information Specialist searched the Hypertension Specialised Register segment (which includes searches of MEDLINE, Embase, and Epistemonikos for systematic reviews) to retrieve existing reviews relevant to this systematic review, so that we could scan their reference lists for additional trials. The Specialised Register also includes searches for controlled trials in CAB Abstracts & Global Health, CINAHL, ProQuest Dissertations & Theses and Web of Science.
-
We checked the bibliographies of included studies and any relevant systematic reviews identified for further references to relevant trials.
-
Where necessary, we contacted authors of key papers and abstracts to request additional information about their trials.
Data collection and analysis
Pairs of review authors (GC, MSC and MLC) independently assessed the methodological quality and other inclusion criteria of the identified trials, resolving disagreements by consensus.
Selection of studies
We imported references and abstracts of searched results to Early Reviewer Organizing Software (EROS) (Ciapponi 2011; Glujovsky 2010), basing selection of studies on the criteria listed above.
Data extraction and management
Pairs of review authors (GC, MSC and MLC) independently extracted data, using a standard form, and then cross‐checked them. A third person (AC) confirmed all numeric calculations and graphic interpolations.
Descriptive data included authors, year of publication, country, time span of the trial, gender, type of placebo, baseline dietary calcium intake, type, dose and duration of calcium‐related intervention, compliance, co‐interventions, trial quality assessments, and numbers randomised and analysed.
The position of the participant during blood pressure measurement may affect the blood pressure‐lowering effect. However, in order to not lose valuable data if only one position was reported, we collected data from that position. When blood pressure measurement data were available in more than one position, sitting blood pressure was the first preference. If both standing and supine measurements were available, we used standing blood pressure.
Assessment of risk of bias in included studies
GC, MSC and MLC independently assessed risks of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We resolved any disagreement through discussion with the whole team. We made explicit judgements about whether studies had high risk of bias, according to the criteria described below. We assessed the magnitude and direction of the bias and whether we considered it was likely to impact on the findings through sensitivity analysis. See Sensitivity analysis below.
(1) Sequence generation (checking for possible selection bias)
We described the method used to generate the allocation sequence for each included study in sufficient detail to allow an assessment of whether it should produce comparable groups.
We assessed the method as:
| • | low risk of bias (any truly random process, e.g. random number table; computer random number generator) |
| • | high risk of bias (any non‐random process, e.g. odd or even date of birth; hospital or clinic record number) |
| • | unclear risk of bias |
(2) Allocation concealment (checking for possible selection bias)
We described the method used to conceal the allocation sequence for each included study and determined whether intervention allocation could have been foreseen in advance of or during recruitment, or changed after assignment.
We assessed the methods as:
| • | low risk of bias (e.g. telephone or central randomisation; consecutively‐numbered sealed opaque envelopes) |
| • | high risk of bias (open random allocation; unsealed or non‐opaque envelopes, alternation; date of birth) |
| • | unclear risk of bias |
(3) Blinding (checking for possible performance and detection bias)
We described for each included study the methods used, if any, to blind study participants and personnel and outcome assesors from knowledge of which intervention a participant received. We considered studies at low risk of bias if they were blinded, or if we judged that the lack of blinding could not have affected the results. We assessed blinding separately for participants and personnel and for outcome assessores and for different outcomes .
We assessed the methods as:
| • | low, high or unclear risk of bias for participants |
| • | low, high or unclear risk of bias for personnel |
| • | low, high or unclear risk of bias for outcome assessors |
(4) Incomplete outcome data (checking for possible attrition bias through withdrawals, dropouts, protocol deviations)
We described for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We stated whether attrition and exclusions were reported, the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information was reported, or was supplied by the trial authors, we re‐included missing data in the re‐analyses.
We assessed methods as:
| • | low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups) |
| • | high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; 'as treated' analysis done with substantial departure of intervention received from that assigned at randomisation) |
| • | unclear risk of bias |
(5) Selective reporting bias
We described for the included study how we investigated the possibility of selective outcome reporting bias and our findings.
We assessed the methods as:
| • | low risk of bias (where it is clear that all of the study’s prespecified outcomes and all expected outcomes of interest to the review have been reported) |
| • | high risk of bias (where not all the study’s prespecified outcomes have been reported; one or more reported primary outcomes were not prespecified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported) |
| • | unclear risk of bias |
(6) Other sources of bias
We described any important concerns we had about other possible sources of bias for each included study.
We assessed whether the study was free of other problems that could put it at risk of bias and recorded our judgement as:
| • | low risk of bias (the study appears to be free of other sources of bias) |
| • | high risk of bias (potential source of bias related to the specific study design used; or has been claimed to have been fraudulent; or had some other problem) |
| • | unclear risk of bias |
Measures of treatment effect
For continuous data, we used the mean difference (MD) if outcomes were measured in the same way between trials. We used the standardised mean difference (SMD) to combine trials that measured the same outcome but used different methods. For dichotomous data, we planned to calculate risk ratios (RR) with 95% confidence intervals (CI). None of the studies reported hypertension as a dichotomous outcome.
Unit of analysis issues
In the case of studies with more than one treatment comparison, we divided the control groups by the number of subgroups.
Dealing with missing data
In the case of missing information in the included studies, we contacted investigators (using email, letter and/or fax) to obtain the missing information. In the case of missing standard deviations of blood pressure change, we imputed the standard deviation based on the information in the same trial or from other trials which assessed calcium‐related interventions. We used the following hierarchy (listed from high to low preference) to impute standard deviation values:
| 1. | standard deviation of change in blood pressure taken in a different position from that of the blood pressure data used |
| 2. | standard deviation of blood pressure at the end of treatment |
| 3. | standard deviation of blood pressure at the end of treatment measured in a different position from that of the blood pressure data used |
| 4. | standard deviation of blood pressure at baseline (except if this measure was used as an entry criterion) |
| 5. | mean standard deviation of change in blood pressure from other trials assessing calcium‐related interventions |
Assessment of heterogeneity
We assessed statistical heterogeneity in each meta‐analysis using the T², I² and Chi² statistics (Higgins 2003; Higgins 2011). We regarded heterogeneity as moderate if T² was greater than zero and either I² was greater than 30% or there was a low P value (less than 0.10) in the Chi² test for heterogeneity. I² values greater than 50% indicate high levels of heterogeneity.
Assessment of reporting biases
We investigated reporting biases (such as publication bias) by producing funnel plots if at least 10 studies were included in the analysis. We assessed funnel plot asymmetry visually. In case of asymmetry suggested by a visual assessment, we planned to perform exploratory analyses to investigate it.
Data synthesis
We carried out statistical analysis using the Review Manager 5 software (RevMan 2014). For continuous data, we used the mean difference (MD) and its 95% confidence interval (CI) if outcomes were measured in the same way between trials. We used the standardised mean difference (SMD) to combine trials that measured the same outcome but using different methods. We compared categorical data using risk ratios (RRs) and their 95% CIs. We used fixed‐effect meta‐analysis for combining data where it was reasonable to assume that studies were estimating the same underlying treatment effect, i.e. where trials were examining the same intervention, and we judged the trials’ populations and methods to be sufficiently similar. If there was clinical heterogeneity sufficient to expect that the underlying treatment effects differed between trials, or if we detected substantial statistical heterogeneity, we used random‐effects meta‐analysis to produce an overall summary where we considered an average treatment effect across trials was clinically meaningful. We treated the random‐effects summary as the average range of possible treatment effects, and we discussed the clinical implications of treatment effects differing between trials.
Subgroup analysis and investigation of heterogeneity
We carried out the following subgroup analyses:
-
We analysed sex and age using recommended nutrient intake age groups (1 to less than 4 years; 4 to less than 6 years; 6 to less than 10 years; 10 to less than 19 years; 19 to less than 50 years; 50 years and over), for men and women.
-
Ethnicity
-
Duration of calcium intervention
-
Dose received
-
Intake of other minerals: where possible we analysed groups according to intakes of minerals involved in blood pressure regulation such as sodium, magnesium, potassium
-
Fat intake
-
Baseline calcium intake: we divided population groups into low or adequate calcium intake, according to WHO Food and Agriculture Organization (FAO) recommendations by age group
-
Baseline blood pressure: blood pressure as defined by trial authors. Ideally, we analysed pre‐hypertension defined as diastolic blood pressure ≥ 80 mmHg (or systolic blood pressure ≥ 120 mmHg).CDC 2021
Sensitivity analysis
We planned sensitivity analyses to explore the effect of risk of bias assessed by concealment of allocation, high attrition rates, or both, excluding the studies with high RoB in theses domains from the analyses in order to assess whether this made any difference to the overall result. We tested the robustness of the results using several sensitivity analyses, including:
| 1. | Trials that were industry‐sponsored versus non‐industry sponsored |
| 2. | Trials with blood pressure data measured in the sitting position versus other measurement positions |
| 3. | Trials with reported standard deviations of blood pressure change versus imputed standard deviations |
| 4. | Risk of bias items |
In order to explore the robustness of the results, we performed four post hoc sensitivity analyses. The first sensitivity analysis was by mean difference and standardised mean difference in those cases when the results came from a combination of final blood pressure values and blood pressure change from baseline. We decided to present the results as mean differences, as they are easier to interpret. However, in order to be more accurate, we compared the mean difference results with the standardised mean differences. We based the other analyses on duration of intervention, on blood pressure methodology (auscultatory and oscillometric method) and on clinic blood pressure measurements and automated ambulatory blood pressure.
Summary of findings and assessment of the certainty of the evidence
We prepared summary of findings tables using GRADEpro and Cochrane methods (GRADEpro GDT 2015; Higgins 2011). These tables evaluated the overall quality of the body of evidence for the main review outcomes and main review comparison . Additional summary of findings tables were also prepared for the main review outcomes for other important comparisons. We assessed the quality of the evidence using GRADE criteria: risk of bias, consistency of effect, imprecision, indirectness and publication bias). Judgements about the quality of the evidence (high, moderate, low or very low) were made by two review authors (GC, AC) working independently, with disagreements resolved by discussion. Judgements were justified, documented, and incorporated into reporting of results for each outcome. We extracted study data, formatted our comparisons in data tables and prepared summary of findings tables before writing the results and conclusions of our review.
Results
Description of studies
See tables 'Characteristics of included studies' and 'Characteristics of excluded studies' for details of individual studies.
Results of the search
We retrieved 1627 references from the electronic searches in 2015. As a result of the updated search, the total number of references retrieved was 6990 (3840 after de‐duplication). Out of the 154 references selected by full text, we finally included 20 studies. See the flow diagram in Figure 1.
Study flow diagram.
Included studies
In this update, we included four new randomised trials (Entezari 2015; Karanja 1987; Yanovski 2009; Yosephin 2015) to the 16 randomised trials identified in 2015, coming from 22 articles (there were two secondary references for Lyle 1987 and Lijnen 1995). See Characteristics of included studies. We also identified 10 ongoing trials (Ongoing studies).
Participants
Most of the studies were performed in adults; five studies were performed in older men and women (Reid 2005; Reid 2010; Thomsen 1987;Yanovski 2009; Van Beresteyn 1986), one study in teenagers (Davis 1996) and one in 11‐year‐old children (Gillman 1995).
We found 14 studies (Belizan 1983; Cutler 1992; Entezari 2015; Gillman 1995; Hilary Green 2000; Johnson 1985; Karanja 1987 Lyle 1992; Reid 2005; Reid 2010; Sacks 1998; Shidfar 2010;Yanovski 2009; Van Beresteyn 1986) reporting baseline mean calcium intake with values ranging from around 400 mg to 1120 mg a day in adult groups. Using this range, we organised the studies into three categories: less than 600 mg a day, 600 to less than 800 mg a day, and 800 mg a day or more for people between 19 and 50 years of age.
We found seven studies that only included women (Entezari 2015; Johnson 1985; Reid 2005; Sacks 1998; Thomsen 1987; Van Beresteyn 1986; Yosephin 2015) and four studies that only included men (Lijnen 1995; Lyle 1987; Reid 2010; Shidfar 2010).
Sample sizes
For most studies, the sample size was fewer than 100 participants; three studies had a sample size between 100 and 200 participants; and the three largest studies had 340 participants (Yanovski 2009) 471 participants (Cutler 1992) and 1471 participants (Reid 2005).
Settings
Most studies were performed in higher‐income countries, with ten set in the USA (Cutler 1992; Davis 1996; Gillman 1995; Johnson 1985; Karanja 1987; Lyle 1987; Lyle 1992; McCarron 1985; Sacks 1998; Yanovski 2009 ), three in New Zeland (Hilary Green 2000; Reid 2005; Reid 2010), and three in Europe (Lijnen 1995 in Belgium; Thomsen 1987 in Denmark; Van Beresteyn 1986 in the Netherlands). Four studies were set in low‐ and middle‐income countries: Belizan 1983 in Guatemala; Yosephin 2015 in Indonesia, and Entezari 2015 and Shidfar 2010 in Iran.
Interventions
The intervention consisted of a supplement tablet in 17 studies, while one study (Hilary Green 2000) evaluated the effect of two servings per day of high‐calcium skim milk versus ordinary skim milk (control), and two studies used a fortified juice (Gillman 1995; Van Beresteyn 1986).
For most studies, the intervention was 1000 to 2000 mg of elemental calcium per day. The intervention in one study was 500 mg of calcium a day (Yosephin 2015); two studies had an intervention group with 600 mg of calcium a day (Gillman 1995; Reid 2010) and another study compared a high‐calcium skim milk containing 1075 mg to 720 mg of the non‐fortified skim milk (Hilary Green 2000).
Nine studies used calcium carbonate for the intervention (Cutler 1992; Johnson 1985; Lyle 1992; Lyle 1987; Shidfar 2010; Sacks 1998; Van Beresteyn 1986; Entezari 2015; Yanovski 2009); three studies used calcium citrate (Gillman 1995; McCarron 1985; Reid 2005), one study used gluconate (Lijnen 1995) and two studies used a combination of calcium salts (Belizan 1983; Thomsen 1987). Five did not report the salt used (Davis 1996; Hilary Green 2000; Karanja 1987; Reid 2010; Yosephin 2015).
We did not specify a minimum intervention time for inclusion of studies. However, the included studies had a median follow‐up intervention period of 3.5 months. After initiation of calcium supplementation, blood pressure seemed to stabilise at between 1.5 and 2.5 months (Belizan 1983). Five studies had interventions that lasted a year or more: Thomsen 1987 one year, Reid 2010 and Yanovski 2009 two years, Reid 2005 two and a half years and Johnson 1985 four years.
Excluded studies
Seventeen studies were first included and then excluded. Four studies were excluded for not having a randomised controlled trial (RCT) design (Luft 1986; Ong 2016; Rahman 2003; Smith 1987), three studies for not reporting the number of participants (Dwyer 1998; Morris 1988; Weinberge 1993), two studies had a co‐intervention that could affect the blood pressure result (Eftekhari 2009; Shalileh 2010), three studies included hypertensive people (Bostick 2000; Hofmeyr 2015; Pan 1993), four studies had a wrong comparator (Das 2017, Ferreira 2016, Sakai 2017, Zhang 2009) and we could not extract data from one study in Chinese (Pan 2000). See Characteristics of excluded studies.
Risk of bias in included studies
See Figure 2; Figure 3. Some information to assess risk of bias was not available for 10 published papers. We found contact details for eight of those studies and obtained the required information from five (Cutler 1992; Gillman 1995; Lyle 1987; Lyle 1992; Sacks 1998).
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
Allocation
Risk of bias for allocation concealment was low for eight of the 20 included studies, and unclear or not described or the remaining 12 studies. For the eight studies classified as low risk, allocation was made by a centralised unit or packets were of identical appearance and were numbered at randomisation.
Blinding
Risk of performance bias from blinding bias was low for 13 of the 20 studies and unclear or not described for the remaining seven studies. For the 13 studies classified as having low risk of performance bias, blinding of participants and personnelwas ensured by a double‐blind design and identical appearance of the food or supplement provided.
Ten studies (Cutler 1992; Davis 1996; Gillman 1995; Hilary Green 2000; Lyle 1987; McCarron 1985; Reid 2005; Reid 2010; Sacks 1998; Van Beresteyn 1986) were at low risk of detection bias as they used a random‐baseline sphygmomanometer, a blood pressure machine that automatically entered the blood pressure data on computer tape, an ambulatory blood pressure monitor, or trained personnel who were blinded to the allocation groups. Detection bias was uncertain for a three studies (Entezari 2015; Lyle 1992; Yosephin 2015) that did not specified the methodology and for five that used a mercury sphygmomanometer (Belizan 1983; Johnson 1985; Lijnen 1995; Shidfar 2010; Thomsen 1987).
Incomplete outcome data
Attrition bias was low for 12 of the 20 studies, while we classified three studies at high risk (Belizan 1983; Entezari 2015; Johnson 1985), as they had more than 10% dropouts. For the remaining four studies, the information was unclear or not described.
Selective reporting
We classified all studies but one (Karanja 1987) at low risk of reporting bias, as all primary outcomes were addressed or there was no evidence of selective reporting bias. Karanja 1987 described blood pressure as an outcome, however, the study does not report results.
Other potential sources of bias
We detected no other bias for 13 of the 20 studies. Davis 1996 did not present baseline characteristics of the population so we rated it as being at unclear risk. We rated four studies as having high risk of bias: baseline characteristics of intervention and placebo groups presented small differences (in different directions) in Hilary Green 2000; in Lyle 1992, the treatment group presented at baseline more men than in the placebo group, although blood pressure values showed no difference; Yosephin 2015 had 79% of women with high Body Mass Index (BMI) in the calcium group while, in the control group, 55% of women had high BMI; finally, Thomsen 1987 placebo participants had higher initial weight and lower systolic blood pressure than in the intervention group.
Effects of interventions
Primary outcomes
Hypertension was defined as blood pressure ≥ 140/90 mmHg. None of the studies reported hypertension as a dichotomous outcome. Out of the 20 included studies 18 were considered in the meta‐analysis as Yanovski 2009 did not report baseline blood pressure and the results were adjusted imputed and Karanja 1987 did not report blood pressure.
Systolic and diastolic blood pressure
-
Effect considering all the studies reporting change or final value of blood pressure
There was a reduction in blood pressure with calcium supplementation/fortification compared with control. The overall effect on systolic blood pressure was a mean difference (MD) of ‐1.37 mmHg (95% confidence interval (CI) ‐2.08 to ‐0.66) reported in 18 trials (N = 3140) with low heterogeneity (P = 0.68; I² = 0%) (Analysis 1.1); the effect on diastolic blood pressure was ‐1.45 mmHg (95% CI ‐2.23 to ‐0.67) in 17 trials (N = 3039) with moderate heterogeneity (P = 0.01; I² = 45%) (Analysis 1.2).
-
Effect considering only the studies reporting change in blood pressure
The estimated effect on change in systolic pressure was ‐1.27 mmHg (95% CI ‐2.02 to ‐0.52), reported in eleven trials (N = 2786) (Analysis 1.3). The estimated effect on change in diastolic pressure was ‐1.62 (95% CI ‐2.61 to ‐0.63 ) reported in ten trials (N = 2685) (Analysis 1.4). Heterogeneity was low for systolic blood pressure (P = 0.67; I² = 0%) and high for diastolic (P = 0.001; I² = 64%).
-
Effect considering only the studies reporting final values of blood pressure
The estimated effect on final systolic blood pressure was ‐1.93 mmHg (95% CI ‐3.72 to ‐0.14), reported in 12 trials (N = 630) (Analysis 1.5) and on diastolic blood pressure ‐1.46 mmHg (95% CI ‐2.82 to ‐0.11), reported in eleven trials (N = 529) (Analysis 1.6). Heterogeneity was low for both systolic (P = 0.26; I² = 18%) and diastolic blood pressure (P = 0.28; I² = 16%).
Subgroup analyses
We reported tests for subgroup differences only when P values were less than 0.1.
Analysis by sex
Of the 18 studies included, 12 studies (Belizan 1983; Johnson 1985; Lijnen 1995; Lyle 1987; Reid 2005; Reid 2010; Sacks 1998; Shidfar 2010; Thomsen 1987; Van Beresteyn 1986) presented the results by sex.
-
Effect considering all the studies reporting change or final value of blood pressure
The overall effect on systolic blood pressure was ‐1.25 mmHg (95% CI ‐2.53 to 0.03) for women, eight studies (N = 1915) with low heterogeneity (P = 0.85; I² = 0%) and ‐2.14 mmHg (95% CI ‐3.71 to ‐0.57) for men, five studies (N = 507) with low heterogeneity (P = 0.37; I² = 8%) (Analysis 1.1). The effect on diastolic blood pressure was ‐1.04, mmHg (95% CI ‐1.86 to ‐0.22) for women, eight studies (N = 1915) with low heterogeneity (P = 0.40; I² = 4%) and ‐1.99 mmHg (95% CI ‐3.25 to ‐0.74) in men, five studies (N = 507) with moderate heterogeneity (P = 0.12; I² = 41%) (Analysis 1.2) (test for subgroup differences: Chi² = 7.15, df = 2 (P = 0.03), I² = 72.0%).
-
Effect considering only the studies reporting change in blood pressure
For those studies showing change in systolic blood pressure, the effect was ‐1.47 mmHg (95% CI ‐2.87 to ‐0.08) for women, five studies (N = 1748) with low heterogeneity (P = 0.84; I² = 0%) and ‐2.01 mmHg (95% CI ‐3.95 to ‐0.08) for men, four studies (N = 432) with low heterogeneity (P = 0.23; I² = 29%) (Analysis 1.3). The effect on diastolic blood pressure was ‐1.87 mmHg (95% CI ‐3.62 to ‐0.12) for women, five studies (N = 1748) with moderate heterogeneity (P = 0.05; I² = 58%) and ‐2.24 mmHg (95% CI ‐3.75 to ‐0.73) for men, four studies (N = 432) with high heterogeneity (P = 0.06; I² = 57%) (Analysis 1.4).
-
Effect considering only the studies reporting final values of blood pressure
In those studies reporting final values, the effect on systolic blood pressure was ‐0.20 mmHg (95% CI ‐3.00 to 2.60) for women, five studies (N = 259) with low heterogeneity (P = 0.86; I² = 0%) and ‐5.36 mmHg (95% CI ‐9.03 to ‐1.70) for men, two studies (N = 124) with low heterogeneity (P = 0.30; I² = 17%) (Analysis 1.5). For diastolic blood pressure, the effect was ‐0.52 mmHg (95% CI ‐2.38 to 1.34) in women, five studies (N = 259) with low heterogeneity (P = 0.43; I² = 0%) and ‐1.88 mmHg (95% CI ‐4.26 to 0.50) in men, two studies (N = 124) with low heterogeneity (P = 0.46; I² = 0%) (Analysis 1.6).
Analysis by age
Although all studies reported the age groups of the population, most of them did not present their results by age group, so it was not possible to do the analysis using the groups originally planned. We divided studies into those that presented a mean age of less than 35 years and those with a mean age of 35 years or more.
-
Effect considering all the studies reporting change or final value of blood pressure
The overall effect on systolic blood pressure was ‐1.86 mmHg (95% CI ‐3.45 to ‐0.27) for those younger than 35 years, eight studies (N = 452) with moderate heterogeneity (P = 0.27; I² = 19%) and ‐0.97 mmHg (95% CI ‐1.83 to ‐0.10) for those aged 35 years or more, ten studies (N = 2688) with low heterogeneity (P = 0.86; I² = 0%) (Analysis 1.7). The overall effect on diastolic blood pressure was ‐2.50 mmHg (95% CI ‐4.22 to ‐0.79) for those younger than 35 years, seven studies (N = 351) with high heterogeneity (P = 0.03; I² = 54%) and ‐0.59 mmHg (95% CI ‐1.13 to ‐0.06) for those aged 35 years or more, ten studies (N = 2688) with low heterogeneity (P = 0.78; I² = 0%) (Analysis 1.8) (test for subgroup differences: Chi² = 11.59, df = 1; P = 0.0007, I² = 91.4%).
-
Effect considering only the studies reporting change in blood pressure
For those studies showing change in systolic blood pressure, the effect was ‐2.34 mmHg (95% CI ‐4.55 to ‐0.13) for those younger than 35 years, three studies (N = 142) with low heterogeneity (P = 0.44; I² = 0%) and ‐0.98 mmHg (95% CI ‐1.87 to ‐0.10) for those aged 35 years or more, six studies (N = 2509) with low heterogeneity (P = 0.453; I² = 0%) (Analysis 1.9). The effect on diastolic blood pressure was ‐4.22 mmHg (95% CI ‐5.68 to ‐2.76) for those younger than 35 years, three studies (N = 142) with low heterogeneity (P = 0.44; I² = 0%) and ‐0.60 mmHg (95% CI ‐1.19 to ‐0.02) for those aged 35 years or more, six studies (N = 2509;) with low heterogeneity (P = 0.37; I² = 7%) (Analysis 1.10).
-
Effect considering all the studies reporting final value of blood pressure
In those studies reporting final values, the effect on systolic blood pressure was ‐1.48 mmHg (95% CI (‐3.57 to 0.62) for those younger than 35 years, six studies (N = 363) with low heterogeneity (P = 0.24; I² = 25%) and ‐3.28 mmHg (95% CI ‐6.77 to ‐0.21) for those aged 35 years or more, six studies (N = 367) with low heterogeneity (P = 0.37; I² = 8%) (Analysis 1.11); diastolic blood pressure was ‐1.39 mmHg (95% CI ‐3.67 to 0.89) in those younger than 35 years, five studies (N = 262) with high heterogeneity (P = 0.05; I² = 54%) and ‐1.52 mmHg (95% CI ‐3.52 to 0.48) in those aged 35 years or more, six studies (N = 267) with low heterogeneity (P = 0.82; I² = 0%) (Analysis 1.12).
Analysis by basal calcium intake
Of the 18 studies included and pooled in meta‐analysis, 11 studies presented results by basal calcium intake. See Description of studies. However, one study (Gillman 1995) was carried out in children, so we excluded it from the analysis as the nutrient recommendations for children are different, and another study (Lyle 1992) gave a range of intakes and could not be classified for this analysis.
-
Effect considering all the studies reporting change or final value of blood pressure
The effect on systolic blood pressure was ‐1.70 mmHg (95% CI ‐6.33 to 2.33) for those that were consuming on average less than 600 mg, one study (N = 58); ‐0.76 mmHg (‐1.75 to 0.22) for those that consumed between 600 and 800 mg of calcium per day, six studies (N = 839) without heterogeneity (P = 0.43; I² = 0%); and ‐1.34 mmHg (95% CI ‐2.80 to 0.13) for those consuming more than 800 mg of calcium per day, four studies (N = 1860) with low heterogeneity (P = 0.78); I² = 0% (Analysis 1.13). The overall effect on diastolic blood pressure was 1.40 mmHg (95% CI ‐1.90 to 4.70) for those that were consuming on average less than 600 mg of calcium per day, one study (N = 58); ‐1.19 mmHg (95% CI ‐2.49 to 0.11) for those that consumed between 600 and 800 mg of calcium per day, six studies (N = 839) with high heterogeneity (P = 0.06; I² = 53%); and ‐1.24 mmHg (95% CI ‐2.29 to ‐0.19) for those consuming more than 800 mg of calcium per day, four studies (N = 1860) with low heterogeneity (P = 0.25; I² = 25%) (Analysis 1.14).
-
Effect considering only the studies reporting change in blood pressure
None of the studies showing basal calcium intake and reporting change in blood pressure had a group with calcium intake less than 600 mg/day.
For those studies showing change in systolic blood pressure, the effect was ‐0.89 mmHg (95% CI ‐1.90 to 0.12) for those who consumed between 600 and 800 mg of calcium per day, five studies (N = 758) with low heterogeneity (P = 0.45; I² = 0%) and ‐1.37 mmHg (95% CI ‐2.86 to 0.12) for those consuming more than 800 mg of calcium per day, three studies (N = 1822) with low heterogeneity (P = 0.64; I² = 0%) (Analysis 1.15). The effect on diastolic blood pressure was ‐1.86 mmHg (95% CI ‐3.68 to 0.03) for those who consumed between 600 and 800 mg of calcium per day, five studies (N = 758) with high heterogeneity (P = 0.05; I² = 73%) and ‐1.32 mmHg (95% CI ‐2.54 to ‐0.10) for those consuming more than 800 mg of calcium per day, three studies (N = 1822) with moderate heterogeneity (P = 0.15; I² = 44%) (Analysis 1.16).
-
Effect considering all the studies reporting final value of blood pressure
In those studies reporting final values, the effect on systolic blood pressure was ‐1.70 mmHg (95% CI ‐6.33 to 2.93) for those consuming less than 600 mg a day, one study (N = 58); ‐2.17 mmHg (95% CI ‐8.54 to 4.20) for those who consumed between 600 and 800 mg of calcium per day, three studies (N = 183) with high heterogeneity (P = 0.02; I² = 75%); and 0.00 mmHg (95% CI ‐8.93 to 8.93) for those consuming more than 800 mg of calcium per day, one study (N = 38) (Analysis 1.17). The effect on diastolic blood pressure was 1.40 mmHg (95% CI ‐1.90 to 4.70) for those consuming less than 600 mg a day, one study (N = 58); ‐2.18 mmHg (95% CI ‐4.60 to ‐0.25) for those who consumed between 600 and 800 mg of calcium per day, three studies (N = 183) with low heterogeneity (P = 0.26; I² = 25%); and ‐1.00 mmHg (95% CI ‐6.72 to 4.72) for those consuming more than 800 mg of calcium per day, one study (N = 38) (Analysis 1.18).
Analysis by dose
-
Effect considering all the studies reporting change or final value of blood pressure
The overall effect on systolic blood pressure was ‐0.02 mmHg (95% CI ‐2.23 to 2.20) for the group with doses less than 1000 mg, three studies (N = 302) with low heterogeneity (P = 0.88; I² = 0%); ‐1.05 mmHg (95% CI ‐1.91 to ‐0.19) with doses between 1000 and 1500 mg, nine studies (N = 2488) with low heterogeneity (P = 0.69; I² = 0%); and ‐2.79 mmHg (95% CI ‐4.71 to ‐0.86) with doses more than 1500 mg, seven studies (N = 350) with low heterogeneity (P = 0.45; I² = 0%) (Analysis 1.19).
The overall effect on diastolic blood pressure was ‐0.41 mmHg (95% CI ‐2.07 to 1.25) for the group with doses less than 1000 mg, two studies (N = 162) without heterogeneity (P = 0.39; I² = 0%); ‐2.03 mmHg (95% CI ‐3.44 to ‐0.62) with doses between 1000 and 1500 mg, eight studies (N = 964) with high heterogeneity (P = 0.006; I² = 63%); and ‐1.35 mmHg (95% CI ‐2.75 to ‐0.05) with doses more than 1500 mg, eight studies (N = 1821) with high heterogeneity (P = 0.04; I² = 51%) (Analysis 1.20).
-
Effect considering all the studies reporting change value of blood pressure
For those studies showing change in systolic blood pressure, the effect was ‐0.00 (95% CI ‐2.87 to 2.87) with less than 1000 mg of calcium intake, two studies (N = 162) without heterogeneity (P = 0.87; I² = 0%); ‐1.14 (95% CI ‐2.01 to ‐0.27) with 1000‐1500 of calcium intake, eight studies (N = 2365) without heterogeneity (P = 0.65; I² = 0%); and ‐5.70 (95% CI ‐10.58 to ‐0.82) with 1500 mg or more of calcium intake, one study (N = 32) (Analysis 1.21).
For those studies showing change in diastolic blood pressure, the effect was ‐0.41 (95% CI ‐2.07 to 1.25) with less than 1000 mg of calcium intake, two studies (N = 162) without heterogeneity (P = 0.39; I² = 0%); ‐2.11 (95% CI ‐3.67 to ‐0.56) with 1000‐1500 of calcium intake, six studies (N = 947) with high heterogeneity (P = 0.002; I² = 71%); and ‐2.15 (95% CI ‐4.59 to ‐0.29) with 1500 mg or more of calcium intake, two studies (N = 1503) (Analysis 1.22).
-
Effect considering all the studies reporting final value of blood pressure
For those studies reporting final values in systolic blood pressure, the effect was ‐0.11 (95% CI ‐3.44 to 3.21) with less than 1000 mg of calcium intake, two studies (N = 140) without heterogeneity (P = 0.62; I² = 0%); 1.05 (95% CI ‐3.06 to 5.16) with 1000‐1500 of calcium intake, three studies (N = 123) without heterogeneity (P = 0.82; I² = 0%); and ‐2.25 (95% CI ‐4.34 to ‐0.16) with 1500 mg or more of calcium intake, six studies (N = 318) (Analysis 1.23).
For those studies reporting final values in diastolic blood pressure, the effect was ‐3.50 (95% CI ‐7.28, 0.28) with less than 1000 mg of calcium intake, one study (N = 53); ‐1.65 (95% CI ‐5.37 to 2.07) with 1000‐1500 of calcium intake, three studies (N = 109) without heterogeneity (P = 0.87 ; I² = 0%); and ‐0.82 (95% CI ‐2.73 to 1.10) with 1500 mg or more of calcium intake, six studies (N = 318) (Analysis 1.24).
Analysis by intervention duration
The overall effect on systolic blood pressure was ‐1.63 mmHg (95% CI ‐2.72 to ‐0.53) where the intervention lasted less than six months, 13 studies (N = 766) with low heterogeneity (P = 0.47; I² = 0%); and ‐0.83 mmHg (95% CI ‐1.83 to 0.17) where the intervention lasted six months or more, five studies (N = 2374) with low heterogeneity (P = 0.76; I² = 0%) (Analysis 1.25). The overall effect on diastolic blood pressure was ‐2.16 mmHg (95% CI ‐3.34 to ‐0.98) where the intervention lasted less than six months, 12 studies (N = 665) with moderate heterogeneity (P = 0.06; I² = 40%); and ‐0.43 mmHg (95% CI ‐1.03 to 0.17) where the intervention lasted six months or more, five studies (N = 2374) with low heterogeneity (P = 0.54; I² = 0%) (Analysis 1.26) (test for subgroup differences: Chi² = 8.65, df = 1, P = 0.002, I² = 89.6%).
Analysis by intervention type (fortification and supplementation)
The overall effect on systolic blood pressure was ‐1.26 mmHg (95% CI ‐2.02 to ‐0.50) where the intervention was food supplementation, 16 studies (N = 3001) with low heterogeneity (P = 0.54; I² = 0%); and 0.09 mmHg (95% CI ‐3.11 to 3.29) where the intervention was food fortification, two studies (N = 139) with low heterogeneity (P = 0.98; I² = 0%) (Analysis 1.27). The overall effect on diastolic blood pressure was ‐1.45 mmHg (95% CI ‐2.27 to ‐0.43) where the intervention was food supplementation, 17 studies (N = 3039) with high heterogeneity (P = 0.008; I² = 49%); and ‐1.00 mmHg (95% CI ‐6.72 to 4.72) where the intervention was food fortification, one study (N = 38) (Analysis 1.28).
Analysis by ethnicity, fat intake, other minerals
It was not possible to do these analyses, as presented in the protocol, as the information was not available.
Planned sensitivity analysis results
1 Sensitivity analysis according to risk of bias
Figure 2 shows risk of bias classification of studies.
Mean effect on systolic blood pressure in 18 studies (N = 3140) (mean difference in all cases) was ‐1.37 mmHg (‐2.08 to ‐0.66). When we restricted the analyses to only those studies with low risk of bias, the results still showed a significant effect:
-
Random sequence: ‐1.26 mmHg (‐2.04 to ‐0.49) in 10 studies (N = 1730)
-
Allocation concealment: ‐1.20 mmHg (‐2.09 to ‐0.31) in 7 studies (N = 1193)
-
Blinding of participants: ‐1.36 mmHg (‐2.11 to ‐0.59) in 13 studies (N = 2827)
-
Blinding of outcome assessment: ‐1.26 mmHg (‐2.01 to ‐0.50) in 11 studies (N = 2800)
-
Incomplete outcome data: ‐1.68 mmHg (‐2.69 to ‐0.67) in 11 studies (N = 1250)
Mean effect on diastolic blood pressure in 17 studies (N = 3039) was ‐1.45 mmHg (‐2.23 to ‐0.67). When we restricted the analyses to only those studies with low risk of bias, the results still showed a significant effect:
-
Random sequence: ‐1.52 mmHg (‐2.49 to ‐0.55) in 9 studies (N = 1629)
-
Allocation concealment: ‐1.91 mmHg (‐3.38 to ‐0.45) in 6 studies (N = 1092)
-
Blinding of participants: ‐1.67 mmHg (‐2.63 to ‐0.62) in 12 studies (N = 2726)
-
Blinding of outcome assessment: ‐1.27 mmHg (‐2.13 to ‐0.41) in 10 studies (N = 2799)
-
Incomplete outcome data: ‐1.39 mmHg (‐2.55 to ‐0.24) in 10 studies (N = 1149)
2 Sensitivy analysis for industry‐funded studies
We performed a sensitivity analysis excluding five studies that we believed to be industry‐funded (Gillman 1995; Hilary Green 2000; Johnson 1985; Lijnen 1995; Reid 2010).
Mean difference of the effect on systolic blood pressure excluding industry‐funded studies was ‐1.31 [‐2.14, ‐0.49 13 studies (N = 2565), whereas for the industry‐funded studies, the mean difference was ‐1.54 mmHg (95% CI ‐2.94 to ‐0.15) 5 studies (N = 575).Analysis 1.1
Mean difference of the effect on diastolic blood pressure excluding industry‐funded studies was ‐1.45 mmHg (95% CI ‐2.42 to ‐0.49) 12 studies (N = 1257), whereas, for the industry‐funded studies, the mean difference was ‐1.52 mmHg (95% CI ‐2.88 to ‐0.17) 4 studies (N = 474).
3 Sensitivity analysis by position of the participant during blood pressure measurement
| Systolic blood pressure | |
| Sitting position (Belizan 1983; Gillman 1995; Johnson 1985) | ‐1.60 mmHg (95% CI ‐3.23 to 0.03), 3 studies (N = 299) |
| Standing (Lijnen 1995) | ‐5.70 mmHg (95% CI ‐10.58 to ‐0.82), 1 study (N = 32) |
| Supine (McCarron 1985; Thomsen 1987; Entezari 2015) | 1.09 mmHg (95% CI ‐3.23 to 5.42), 3 studies (N = 113) |
| Diastolic blood pressure | |
| Sitting (Belizan 1983; Johnson 1985) | ‐3.30 mmHg (95% CI ‐6.99 to ‐0.40), 2 studies (N = 138) |
| Standing (Lijnen 1995) | ‐3.50 mmHg (95% CI ‐5.29 to ‐1.71), 1 study (N = 32) |
| Supine (McCarron 1985; Thomsen 1987; Entezari 2015 | ‐3.04 mmHg (95% CI ‐6.00 to ‐0.07), 3 studies (N = 113) |
4 Sensitivity analysis for trials with imputed standard deviations
We did not impute any standard deviations for the data from these 16 trials.
Post hoc sensitivity analyses
Sensitivity analysis comparing mean difference and standardised mean difference results
We did a sensitivity analysis comparing mean difference (MD) and standardised mean difference (SMD) results for all 28 outcomes reported in data analysis. Even though the mean difference results were in the same direction, of the 28 analyses performed, eight presented confidence intervals with different statistical significance between MD and SMD results, suggesting that we should be more cautious in interpreting these results. The following list shows cases where the confidence interval crossed the line of no effect on one measurement method but not on the other:
1. The mean difference effect on systolic blood pressure for women was ‐1.25 mmHg (95% CI ‐2.53 to ‐0.03), whereas the standardised mean difference was ‐0.10 mmHg (95% CI ‐0.19 to 0.01) (Analysis 1.1).
2. The mean difference effect on change of systolic blood pressure for men was ‐2.01 mmHg (95% CI ‐3.95 to ‐0.08), whereas the standardised mean difference was ‐0.23 mmHg (95% CI ‐0.49 to 0.02) (Analysis 1.3).
3. The mean difference effect on change of diastolic blood pressure for women was ‐1.87 mmHg (95% CI ‐3.62 to ‐0.12), whereas the standardised mean difference was ‐0.25 mmHg (95% CI ‐0.53 to 0.03) (Analysis 1.4).
4. The mean difference effect on the final value of diastolic blood pressure for both genders was ‐2.33 mmHg (95% CI ‐4.50 to ‐0.17), whereas the standardised mean difference was ‐0.32 mmHg (95% CI ‐0.65 to 0.01) (Analysis 1.6).
5. The mean difference effect on change in systolic blood pressure in those less than 35 years was ‐2.34 (95% CI ‐4.55 to ‐0.13), whereas the standardised mean difference was (SMD ‐0.31, 95% CI ‐0.64 to 0.03) (Analysis 1.9).
6. The mean difference effect on systolic blood pressure in the group with intakes higher than 800 mg a day was ‐1.34 mmHg (95% CI ‐2.80 to 0.13), whereas the standardised mean difference was (SMD ‐0.09 (‐0.19, ‐0.00)(Analysis 1.13).
7. The mean difference effect on diastolic blood pressure in the group with intakes higher than 800 mg a day was ‐1.24 mmHg (95% CI ‐2.29 to 0.19), whereas the standardised mean difference was (SMD ‐0.14 (‐0.30, 0.01) (Analysis 1.14).
8. The mean difference effect on change of diastolic blood pressure in the group with intakes higher than 800 mg a day was ‐1.32 mmHg (95% CI ‐2.54 to 0.10), whereas the standardised mean difference was (SMD ‐0.17 (‐0.36, 0.03) (Analysis 1.16).
When we analysed the results in units of standard deviation (SMDs), each study weight was modified; if the weight increased in those studies showing more effect, the final result using this method showed a higher effect. Correspondingly, when the weights were increased in the studies with no effect, the final result tended to show a weaker global effect.
Sensitivity analysis excluding studies with less than 3.5 months of intervention
Of the 18 studies included in the meta‐analysis, eight (Belizan 1983; Cutler 1992; Johnson 1985; Lijnen 1995; Reid 2005; Reid 2010; Sacks 1998; Thomsen 1987) presented interventions lasting more than 3.5 months (N = 2619).
The mean effect in systolic blood pressure was ‐1.37 mmHg (‐2.08 to ‐0.66) (Analysis 1.1). When we performed a sensitivity analysis only including the studies with interventions lasting more than 3.5 months, the results were still significant: ‐1.03 mmHg (‐1.87 to ‐0.19).
The mean effect in diastolic blood pressure was ‐1.45 mmHg (‐2.23 to ‐0.67) (Analysis 1.2). When we performed a sensitivity analysis only including the studies with interventions lasting more than 3.5 months, the results were still significant: ‐1.38 mmHg (95% CI ‐2.435to ‐0.41).
Sensitivity analysis by blood pressure methodology
Blood pressure was measured using an auscultatory method in seven studies Belizan 1983; Cutler 1992; Johnson 1985; Lyle 1992; Lyle 1987; McCarron 1985; Thomsen 1987; (N = 786), and using an oscillometric method in six studies Davis 1996; Gillman 1995 (only systolic blood pressure (N = 101); Hilary Green 2000; Reid 2005; Reid 2010; Sacks 1998 (N = 2123).
| Systolic blood pressure | |
| Auscultatory | ‐1.12 mmHg (95% CI ‐2.19 to ‐0.04) |
| Oscillometric | ‐1.34 mmHg (95% CI ‐2.38 to ‐0.31) |
| Diastolic blood pressure | |
| Auscultatory | ‐2.19 mmHg (95% CI ‐4.12 to ‐0.25) |
| Oscillometric | ‐0.85 mmHg (95% CI ‐1.54 to ‐0.16) |
Sensitivity analysis by studies reporting clinic blood pressure measurements and automated ambulatory blood pressure
Blood pressure was measured at a clinic in eight studies (Belizan 1983; Cutler 1992; Entezari 2015; Gillman 1995; Johnson 1985; Lyle 1987; Lyle 1992; McCarron 1985; Thomsen 1987; Yosephin 2015 (N = 887)); and using automated ambulatory measurements in three studies (Davis 1996; Hilary Green 2000; Sacks 1998 (N = 228)).
We did not find any study using ambulatory measurements reported by the participant. Those studies reporting ambulatory measurement were conducted with automated devices.
| Systolic blood pleasure | |
| Clinic measurements | ‐1.15 mmHg (95% CI ‐2.09 to 0.20) |
| Automated ambulatory measurements | ‐0.92 mmHg (95% CI ‐2.63 to 0.78) |
|
Diastolic blood pressure | |
| Clinic | ‐2.24 mmHg (95% CI ‐3.496to 0.52) |
| Automated ambulatory measurements | ‐0.83 mmHg (95% CI ‐2.05 to 0.39) |
Assessment of potential reporting biases (such as publication bias)
Funnel plot visual analysis revealed no asymmetry (Figure 4; Figure 5).
Funnel plot of comparison: 1. Calcium supplementation/fortification vs control. Outcome 1.1: Mean difference in systolic blood pressure
Funnel plot of comparison: 1. Calcium supplementation/fortification vs control. Outcome 1.2: Mean difference in diastolic blood pressure
Secondary Outcomes
Cutler 1992 was the only article evaluating side effects, but reported none. A further two study reports (Lyle 1987; McCarron 1985) mentioned that the supplements were well tolerated and that no participants required withdrawal from the trial after randomisation.
No trials reported any incidence of kidney stone formation, iron deficiency anaemia, anaemia, cardiovascular events, myocardial infarction, stroke or mortality.
Discussion
The aim of this review was to evaluate the effectiveness of calcium supplementation, as a single nutrient, for the prevention of primary hypertension. We analysed the effect of calcium according to sex, intervention dose, intervention duration, age of participants and basal calcium intake.
Summary of main results
There was a small reduction in both systolic and diastolic blood pressure in the groups receiving calcium compared to those receiving placebo or control. We found a lower effect in those studies that did not discriminate between the results by sex and, in at least one of those studies (Lyle 1992), a sex imbalance at randomisation was reported as a possible explanation.
The effect was confirmed in multiple prespecified subgroups. We detected a dose‐response effect trend, both in systolic and in diastolic blood pressure, that could reinforce the efficacy of the intervention. Those studies with interventions of 1500 mg of calcium a day or higher showed a higher decrease in systolic and diastolic blood pressure than those studies with interventions less than 1000 mg a day. For those studies with interventions of less than 1000 mg, we found no effect, although in this last group there were very few studies from which to draw any conclusion.
When we evaluated the overall effect and change of blood pressure before and after the intervention with calcium, those studies that were performed in younger people tended to show higher reductions in systolic and diastolic blood pressure than those in older people.
There was no difference in the effect by baseline calcium intake, reported in ten of the 18 studies included in the meta‐analysis. This could be due to different methods used in assessing calcium intake among the studies. The information provided in this review, therefore, does not contradict the possibility of a higher effect in populations with low calcium intake, as has been suggested before (Belizan 1980; Belizan 1983; WHO 2009). Only two of the selected studies were performed in low‐ or middle‐income countries.
It is difficult to assess the effect of differences in the forms of calcium interventions, such as diet, fortification or supplements, since 14 of the 18 studies included in the meta‐analysis used supplementation as the intervention.
Our data show a greater effect in those studies lasting less than six months. There is some suggestion that the effect might be lost over time in populations with adequate calcium intake, as some studies showed no effect after 30 months (Reid 2005) and one year (Thomsen 1987).
None of the secondary outcomes were reported in the included studies, therefore, we found no evidence of adverse effects.
Overall completeness and applicability of evidence
We found a substantial number of studies to address the objectives of the review, with no evidence of publication bias, although some population groups such as children and teenagers might not be well represented. Only one study was performed in children (Gillman 1995), and one in teenagers (Davis 1996).
The effect was higher in four studies from low‐ and middle‐income countries (Belizan 1983; Entezari 2015; Shidfar 2010; Yosephin 2015) (MD ‐1.73 mmHG, 95% CI ‐3.76 to ‐0.29); however, we also found an effect on blood pressure reduction in high‐income countries, 14 studies (‐1.32 mmHg, 95% CI ‐2.08 to ‐0.57).
The effect on diastolic blood pressure was higher in men, in those younger than 35 years and in those receiving the intervention for less than six months (test for subgroup differences: P = 0.03, P = 0.004 and P = 0.001, respectively).
The other subgroup analyses look underpowered and, therefore, need to be interpreted cautiously. For example, we observed a trend to higher effect with increasing doses; however, the test for subgroup differences indicated P values that were not statistically significant (0.14 and 0.34 for systolic and diastolic blood pressure, respectively).
The findings of this review support the importance of an adequate calcium intake for the prevention of high blood pressure and the need to explore interventions to increase calcium intake in both men and women. For cardiovascular risk prevention, a small decrease in blood pressure outweighs a larger decrease only among hypertensive groups (Gillman 1995). Additionally, small reductions in blood pressure of the general population are predicted to have important health implications, as they are shown to produce rapid reductions in vascular disease risk even in individuals with normal blood pressure ranges (Lewington 2002). Population‐wide decreases in blood pressure of 2–3 mmHg could decrease the prevalence of hypertension by 17%, the risk of coronary artery disease by 6% and the risk of stroke by 15% (Cook 1995). A 2 mmHg lower systolic blood pressure is predicted to produce about 10% lower stroke mortality and about 7% lower mortality from ischaemic heart disease, and a 5 mmHg reduction in systolic blood pressure at the population level is predicted to result in a 14% reduction in stroke death, 9% reduction in coronary artery disease‐related death and a 7% reduction in total mortality (Whelton 2002). In the same way, a 2 mmHg reduction in systolic blood pressure in adults is estimated to have the potential to save about 12,000 lives a year in the United States (Stamler 1991) and to generate an increase in life expectancy of 1.8 months in men and 1.4 months in women (Selmer 2000).
Globally, around 3.5 billion people are at risk of calcium deficiency (Kumssa 2015). A fortification strategy may be the most appropriate strategy to target countries with general low calcium intake (Cormick 2019a; Cormick 2020).
Quality of the evidence
We included 20 trials, of which 18 were included in the meta‐analysis with 3140 participants, providing high‐quality evidence (Guyatt 2011) of the effect of calcium supplementation on systolic and diastolic blood pressure (summary of findings Table 1). The quality of some outcomes was rated as being at moderate certainty due to imprecision (small sample size).
Risks of bias for random sequence generation and incomplete outcome data were low for 55% of the studies; allocation concealment risk of bias was low for 40% of the studies and unclear for the remainder; blinding of participants and personnel was low for 65% of the studies and risk of detection bias and attrition bias was low for 60% of the studies. We rated 85% of the studies as being at low risk of reporting bias.
Potential biases in the review process
We restricted this review to clinical trials in which the intervention was calcium supplementation as a single ingredient, which limited the number of studies we could include. On the other hand, we used an exhaustive search strategy to avoid publication selection bias. Two review authors independently assessed the articles and double‐checked data extraction to minimise errors.
Many of the studies were old and, even though in these cases published information was not enough to assess risk of bias, we attempted to contact authors, although the response was limited. Nevertheless, there was generally a low risk of bias.
Agreements and disagreements with other studies or reviews
Our results are in line with the most recent review by Van Mierlo 2006 that included a meta‐analysis of 40 randomised controlled trials (RCTs) with normotensive and hypertensive people, showing that supplementation with around 1 gm of calcium per day significantly reduced systolic blood pressure by 1.9 mmHg and diastolic blood pressure by 1.0 mmHg. This review also found a higher effect in populations with low basal calcium intake. In a previous meta‐analysis involving 42 trials in normotensive and hypertensive people, the pooled analysis showed a reduction in systolic blood pressure of ‐1.44 mmHg (95% CI ‐2.20 to ‐0.68; P < 0.001) and in diastolic blood pressure of ‐0.84 mmHg (95% CI ‐1.44 to ‐0.24; P < 0.001) (Griffith 1999).
Our results are in the same direction as the Dickinson 2006 review in hypertensive people. Although this showed a statistically significantly larger reduction in blood pressure in the calcium group, the authors interpret this as more likely reflecting a bias due to poor‐quality trials than a real effect. We performed a sensitivity analysis excluding studies classified at high and moderate risk of bias. All studies were classified at low risk of selective reporting bias, so we could conduct no analysis for this domain. For the remaining five domains evaluated, the effect persisted after removing studies classified as being at high or moderate risk. The Evidence Analysis Library (EAL) guideline encourages adults with hypertension to consume adequate amounts of dietary calcium to meet the Dietary Reference Intakes (DRI). The authors stated that dietary calcium intake of 800 mg or more per day reduced systolic blood pressure up to 4 mm Hg and diastolic blood pressure up to 2 mm Hg in adults with hypertension. If an adult is unable to meet the DRI for calcium with diet alone, they consider calcium supplementation of 1,000 to 1,500 mg/day to aid in blood pressure control. A strong body of research indicated that calcium supplementation of 1,000 to 1,500 mg/d reduced systolic blood pressure up to 3.0 mm Hg and diastolic blood pressure up to 2.5 mm Hg in adults with hypertension (Lennon 2017).
Calcium intake also showed effects on different populations. A Cochrane review (Hofmeyr 2018) showed that a good calcium intake has benefits for pregnancy outcomes, effects which are thought to be mediated by blood pressure reduction. Preliminary observations showed that calcium supplementation during pregnancy could also have effects on reducing the blood pressure of the progeny (Belizan 1988, Hatton 2003). Consequently, calcium intake could play a role in the prevention of hypertension, particularly at a young age where small changes in blood pressure could have a higher effect. It has been shown that lowering blood pressure at younger ages is relevant, since the relative risk of cardiovascular diseases with blood pressure decreases with age and no significant deviations from linearity occurred in the associations of either systolic or diastolic blood pressure (Rapsomaniki 2014).
A recent systematic review and meta‐analysis investigated the effect of calcium and vitamin D co‐supplementation on blood pressure (Morvaridzadeh 2020). The meta‐analysis of the eight trials included showed a reduction in blood pressure in the intervention group compared with control (standardised mean difference (SMD) −0.23; 95% CI, −0.52 to 0.06; SMD −0.29; 95% CI, −0.55 to −0.02, respectively), with a greater diastolic blood pressure reduction in young adults than other age groups. Our findings go in line with this study, although with lower reduction in both systolic and diastolic blood pressure (SMD ‐0.10 (95% CI ‐0.19 to ‐0.01); SMD ‐0.24 (95% CI ‐0.43 to ‐0.04), respectively) and higher blood pressure reductions in young adults. Such findings could suggest a major effect of vitamin D co‐supplementation.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
Funnel plot of comparison: 1. Calcium supplementation/fortification vs control. Outcome 1.1: Mean difference in systolic blood pressure
Funnel plot of comparison: 1. Calcium supplementation/fortification vs control. Outcome 1.2: Mean difference in diastolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 1: Mean difference in systolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 2: Mean difference in diastolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 3: Change data: systolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 4: Change data: diastolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 5: Final value: systolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 6: Final value: diastolic blood pressure
Comparison 1: Calcium supplementation/fortification vs control, Outcome 7: Mean difference in systolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 8: Mean difference in diastolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 9: Change in systolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 10: Change in diastolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 11: Final value in systolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 12: Final value in diastolic blood pressure by age
Comparison 1: Calcium supplementation/fortification vs control, Outcome 13: Mean difference in systolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 14: Mean difference in diastolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 15: Change in systolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 16: Change in diastolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 17: Final value in systolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 18: Final value in diastolic blood pressure by basal calcium intake
Comparison 1: Calcium supplementation/fortification vs control, Outcome 19: Mean difference in systolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 20: Mean difference in diastolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 21: Change in systolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 22: Change in diastolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 23: Final value in systolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 24: Final value in diastolic blood pressure by dose
Comparison 1: Calcium supplementation/fortification vs control, Outcome 25: Mean difference in systolic blood pressure by duration
Comparison 1: Calcium supplementation/fortification vs control, Outcome 26: Mean difference in diastolic blood pressure by duration
Comparison 1: Calcium supplementation/fortification vs control, Outcome 27: Mean difference in systolic blood pressure by intervention type
Comparison 1: Calcium supplementation/fortification vs control, Outcome 28: Mean difference in diastolic blood pressure by intervention type
| Calcium supplementation/fortification compared to control for prevention of primary hypertension | |||||
| Patient or population: People who may be at risk for primary hypertension | |||||
| Outcomes | Illustrative blood pressure in control group b | Mean difference in mmHg (95% CIa) | No of participants | Quality of the evidence | Comments |
|---|---|---|---|---|---|
| Systolic blood pressure (range of follow‐up from 4 weeks to 4 years) | 115.62 | 1.37 lower (2.08 lower to 0.66 lower) | 3140 | ⊕⊕⊕⊕ | Women: ‐1.25 mmHg [95% CI: ‐2.53, 0.03; 8 studies] Men: ‐2.07 mmHg [95% CI: ‐3.56, ‐0.59; 5 studies] Both: ‐1.11 mmHg [95% CI: ‐2.15, ‐0.08; 6 studies] |
| Diastolic blood pressure (range of follow‐up from 4 weeks to 4 years) | 78.17 | 1.45 lower (2.23 lower to 0.67 lower)
| 3039 | ⊕⊕⊕⊕ | Women: ‐1.03 mmHg [95% CI: ‐1.80, ‐0.26; 8 studies] Men: ‐1.91 mmHg [95% CI: ‐2.80, ‐1.02; 5 studies] Both: ‐0.25 mmHg [95% CI: ‐1.08, 0.57; 5 studies] |
| Systolic blood pressure. Dose less than 1000 mg a day (range of follow‐up from 12 weeks to 2 years) | 103.74 | 0.02 lower (2.23 lower to 2.20 higher) | 302 | ⊕⊕⊕⊝ | Subgroup analysis by dose |
| Systolic blood pressure. Dose between 1000 mg a day and less than 1500 mg a day (range from 4 weeks to 2 years) | 116.29 | 1.05 lower (1.91 lower to 0.19 lower) | 2488 | ⊕⊕⊕⊕ | Subgroup analysis by dose |
| Systolic blood pressure. Dose 1500 mg a day or more (range of follow‐up from 4 weeks to 4 years) | 112.85 | 2.79 lower (4.71 lower to 0.86 lower) | 350 | ⊕⊕⊕⊝ | Subgroup analysis by dose |
| Systolic blood pressure. Less than 35 years of age (range of follow‐up from 4 weeks to 22 weeks) | 113.23 | 1.79 lower (3.20 lower to 0.38 lower) | 452 | ⊕⊕⊕⊝ | Subgroup analysis by age |
| Systolic blood pressure. 35 years or older (range of follow‐up from 4 weeks to 4 years) | 124.20 | 0.97 lower (1.83 lower to 0.10 lower) | 2688 | ⊕⊕⊕⊕ | Subgroup analysis by age |
| Adverse events (secondary outcome) |
|
|
|
| One study evaluated side effects, but none were reported. A further two studies mentioned that the supplements were well tolerated. No trials reported any incidence of kidney stone formation, iron deficiency anaemia, anaemia, cardiovascular events, myocardial infarction, stroke or mortality. |
| aCI: Confidence interval; bEstimated using Comprehensive Meta‐Analysis Software Software; cGRADE Working Group grades of evidence |
| ||||
|
High quality: Further research is very unlikely to change our confidence in the estimate of effect. |
| ||||
| 1. Downgraded one level for imprecision due to small number of participants. | |||||
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 1.1 Mean difference in systolic blood pressure Show forest plot | 18 | 3140 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.13 [‐0.20, ‐0.06] |
| 1.1.1 Women | 8 | 1915 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.10 [‐0.19, ‐0.01] |
| 1.1.2 Men | 5 | 507 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.24 [‐0.43, ‐0.04] |
| 1.1.3 Both genders | 6 | 718 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.17 [‐0.34, 0.00] |
| 1.2 Mean difference in diastolic blood pressure Show forest plot | 17 | 3039 | Mean Difference (IV, Random, 95% CI) | ‐1.45 [‐2.23, ‐0.67] |
| 1.2.1 Women | 8 | 1915 | Mean Difference (IV, Random, 95% CI) | ‐1.04 [‐1.86, ‐0.22] |
| 1.2.2 Men | 5 | 507 | Mean Difference (IV, Random, 95% CI) | ‐1.99 [‐3.25, ‐0.74] |
| 1.2.3 Both genders | 5 | 617 | Mean Difference (IV, Random, 95% CI) | ‐1.54 [‐3.83, 0.74] |
| 1.3 Change data: systolic blood pressure Show forest plot | 11 | 2786 | Mean Difference (IV, Random, 95% CI) | ‐1.27 [‐2.02, ‐0.52] |
| 1.3.1 Women | 5 | 1748 | Mean Difference (IV, Random, 95% CI) | ‐1.47 [‐2.87, ‐0.08] |
| 1.3.2 Men | 4 | 432 | Mean Difference (IV, Random, 95% CI) | ‐2.01 [‐3.95, ‐0.08] |
| 1.3.3 Both genders | 3 | 606 | Mean Difference (IV, Random, 95% CI) | ‐0.89 [‐1.96, 0.18] |
| 1.4 Change data: diastolic blood pressure Show forest plot | 10 | 2685 | Mean Difference (IV, Random, 95% CI) | ‐1.62 [‐2.61, ‐0.63] |
| 1.4.1 Women | 5 | 1748 | Mean Difference (IV, Random, 95% CI) | ‐1.87 [‐3.62, ‐0.12] |
| 1.4.2 Men | 4 | 432 | Mean Difference (IV, Random, 95% CI) | ‐2.24 [‐3.75, ‐0.73] |
| 1.4.3 Both genders | 2 | 505 | Mean Difference (IV, Random, 95% CI) | 0.14 [‐0.73, 1.01] |
| 1.5 Final value: systolic blood pressure Show forest plot | 12 | 630 | Mean Difference (IV, Random, 95% CI) | ‐1.93 [‐3.72, ‐0.14] |
| 1.5.1 Women | 5 | 259 | Mean Difference (IV, Random, 95% CI) | ‐0.20 [‐3.00, 2.60] |
| 1.5.2 Men | 2 | 124 | Mean Difference (IV, Random, 95% CI) | ‐5.36 [‐9.03, ‐1.70] |
| 1.5.3 Both genders | 5 | 247 | Mean Difference (IV, Random, 95% CI) | ‐1.33 [‐4.07, 1.41] |
| 1.6 Final value: diastolic blood pressure Show forest plot | 11 | 529 | Mean Difference (IV, Random, 95% CI) | ‐1.46 [‐2.82, ‐0.11] |
| 1.6.1 Women | 5 | 259 | Mean Difference (IV, Random, 95% CI) | ‐0.52 [‐2.38, 1.34] |
| 1.6.2 Men | 2 | 124 | Mean Difference (IV, Random, 95% CI) | ‐1.88 [‐4.26, 0.50] |
| 1.6.3 Both genders | 4 | 146 | Mean Difference (IV, Random, 95% CI) | ‐2.25 [‐5.49, 0.99] |
| 1.7 Mean difference in systolic blood pressure by age Show forest plot | 18 | 3140 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.11 [‐0.18, ‐0.04] |
| 1.7.1 Less than 35 years of age | 8 | 452 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.22 [‐0.43, ‐0.02] |
| 1.7.2 35 years and older | 10 | 2688 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.09 [‐0.17, ‐0.02] |
| 1.8 Mean difference in diastolic blood pressure by age Show forest plot | 17 | 3039 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.20 [‐0.33, ‐0.07] |
| 1.8.1 Less than 35 years of age | 7 | 351 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.46 [‐0.81, ‐0.10] |
| 1.8.2 35 years and older | 10 | 2688 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.09 [‐0.16, ‐0.01] |
| 1.9 Change in systolic blood pressure by age Show forest plot | 9 | 2651 | Mean Difference (IV, Random, 95% CI) | ‐1.17 [‐1.99, ‐0.35] |
| 1.9.1 Less than 35 years of age | 3 | 142 | Mean Difference (IV, Random, 95% CI) | ‐2.34 [‐4.55, ‐0.13] |
| 1.9.2 35 years and older | 6 | 2509 | Mean Difference (IV, Random, 95% CI) | ‐0.98 [‐1.87, ‐0.10] |
| 1.10 Change in diastolic blood pressure by age Show forest plot | 9 | 2651 | Mean Difference (IV, Random, 95% CI) | ‐1.73 [‐2.79, ‐0.67] |
| 1.10.1 Less than 35 years of age | 3 | 142 | Mean Difference (IV, Random, 95% CI) | ‐4.22 [‐5.68, ‐2.76] |
| 1.10.2 35 years and older | 6 | 2509 | Mean Difference (IV, Random, 95% CI) | ‐0.60 [‐1.19, ‐0.02] |
| 1.11 Final value in systolic blood pressure by age Show forest plot | 12 | 630 | Mean Difference (IV, Random, 95% CI) | ‐1.93 [‐3.72, ‐0.14] |
| 1.11.1 Less than 35 years of age | 6 | 363 | Mean Difference (IV, Random, 95% CI) | ‐1.48 [‐3.57, 0.62] |
| 1.11.2 35 years and older | 6 | 267 | Mean Difference (IV, Random, 95% CI) | ‐3.28 [‐6.77, 0.21] |
| 1.12 Final value in diastolic blood pressure by age Show forest plot | 11 | 529 | Mean Difference (IV, Random, 95% CI) | ‐1.46 [‐2.82, ‐0.11] |
| 1.12.1 Less than 35 years of age | 5 | 262 | Mean Difference (IV, Random, 95% CI) | ‐1.39 [‐3.67, 0.89] |
| 1.12.2 35 years and older | 6 | 267 | Mean Difference (IV, Random, 95% CI) | ‐1.52 [‐3.52, 0.48] |
| 1.13 Mean difference in systolic blood pressure by basal calcium intake Show forest plot | 10 | 2757 | Mean Difference (IV, Random, 95% CI) | ‐0.96 [‐1.77, ‐0.16] |
| 1.13.1 Calcium Intake below 600 mg a day | 1 | 58 | Mean Difference (IV, Random, 95% CI) | ‐1.70 [‐6.33, 2.93] |
| 1.13.2 Calcium Intake from 600 to less than 800 mg a day | 6 | 839 | Mean Difference (IV, Random, 95% CI) | ‐0.76 [‐1.75, 0.22] |
| 1.13.3 Calcium intake above 800 mg a day | 4 | 1860 | Mean Difference (IV, Random, 95% CI) | ‐1.34 [‐2.80, 0.13] |
| 1.14 Mean difference in diastolic blood pressure by basal calcium intake Show forest plot | 10 | 2757 | Mean Difference (IV, Random, 95% CI) | ‐1.04 [‐1.84, ‐0.23] |
| 1.14.1 Calcium Intake below 600 mg a day | 1 | 58 | Mean Difference (IV, Random, 95% CI) | 1.40 [‐1.90, 4.70] |
| 1.14.2 Calcium Intake from 600 to less than 800 mg a day | 6 | 839 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐2.49, 0.11] |
| 1.14.3 Calcium intake above 800 mg a day | 4 | 1860 | Mean Difference (IV, Random, 95% CI) | ‐1.24 [‐2.29, ‐0.19] |
| 1.15 Change in systolic blood pressure by basal calcium intake Show forest plot | 7 | 2580 | Mean Difference (IV, Random, 95% CI) | ‐1.04 [‐1.88, ‐0.21] |
| 1.15.1 Calcium Intake from 600 to less than 800 mg a day | 5 | 758 | Mean Difference (IV, Random, 95% CI) | ‐0.89 [‐1.90, 0.12] |
| 1.15.2 Calcium intake above 800 mg a day | 3 | 1822 | Mean Difference (IV, Random, 95% CI) | ‐1.37 [‐2.86, 0.12] |
| 1.16 Change in diastolic blood pressure by basal calcium intake Show forest plot | 7 | 2580 | Mean Difference (IV, Random, 95% CI) | ‐1.46 [‐2.49, ‐0.43] |
| 1.16.1 Calcium Intake from 600 to less than 800 mg a day | 5 | 758 | Mean Difference (IV, Random, 95% CI) | ‐1.86 [‐3.68, ‐0.03] |
| 1.16.2 Calcium intake above 800 mg a day | 3 | 1822 | Mean Difference (IV, Random, 95% CI) | ‐1.32 [‐2.54, ‐0.10] |
| 1.17 Final value in systolic blood pressure by basal calcium intake Show forest plot | 5 | 279 | Mean Difference (IV, Random, 95% CI) | ‐1.77 [‐5.48, 1.93] |
| 1.17.1 Calcium Intake below 600 mg a day | 1 | 58 | Mean Difference (IV, Random, 95% CI) | ‐1.70 [‐6.33, 2.93] |
| 1.17.2 Calcium Intake from 600 to less than 800 mg a day | 3 | 183 | Mean Difference (IV, Random, 95% CI) | ‐2.17 [‐8.54, 4.20] |
| 1.17.3 Calcium intake above 800 mg a day | 1 | 38 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐8.93, 8.93] |
| 1.18 Final value in diastolic blood pressure by basal calcium intake Show forest plot | 5 | 279 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐3.25, 0.87] |
| 1.18.1 Calcium Intake below 600 mg a day | 1 | 58 | Mean Difference (IV, Random, 95% CI) | 1.40 [‐1.90, 4.70] |
| 1.18.2 Calcium Intake from 600 to less than 800 mg a day | 3 | 183 | Mean Difference (IV, Random, 95% CI) | ‐2.18 [‐4.60, 0.25] |
| 1.18.3 Calcium intake above 800 mg a day | 1 | 38 | Mean Difference (IV, Random, 95% CI) | ‐1.00 [‐6.72, 4.72] |
| 1.19 Mean difference in systolic blood pressure by dose Show forest plot | 18 | 3140 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐1.93, ‐0.45] |
| 1.19.1 Less than 1000 mg of calcium intake | 3 | 302 | Mean Difference (IV, Random, 95% CI) | ‐0.02 [‐2.23, 2.20] |
| 1.19.2 1000 ‐ 1500 of calcium intake | 9 | 2488 | Mean Difference (IV, Random, 95% CI) | ‐1.05 [‐1.91, ‐0.19] |
| 1.19.3 1500 mg or more of calcium intake | 7 | 350 | Mean Difference (IV, Random, 95% CI) | ‐2.79 [‐4.71, ‐0.86] |
| 1.20 Mean difference in diastolic blood pressure by dose Show forest plot | 17 | 3039 | Mean Difference (IV, Random, 95% CI) | ‐1.49 [‐2.35, ‐0.63] |
| 1.20.1 Diary calcium intake less than 1000 mg | 2 | 201 | Mean Difference (IV, Random, 95% CI) | ‐0.41 [‐2.07, 1.25] |
| 1.20.2 Diary calcium intake 1000‐1250 mg | 8 | 1017 | Mean Difference (IV, Random, 95% CI) | ‐2.03 [‐3.44, ‐0.62] |
| 1.20.3 Diary calcium intake 1500 mg or more | 8 | 1821 | Mean Difference (IV, Random, 95% CI) | ‐1.35 [‐2.75, 0.05] |
| 1.21 Change in systolic blood pressure by dose Show forest plot | 9 | 2651 | Mean Difference (IV, Random, 95% CI) | ‐1.17 [‐1.99, ‐0.35] |
| 1.21.1 Less than 1000 mg of calcium intake | 2 | 201 | Mean Difference (IV, Random, 95% CI) | ‐0.00 [‐2.87, 2.87] |
| 1.21.2 1000‐1500 of calcium intake | 7 | 2418 | Mean Difference (IV, Random, 95% CI) | ‐1.14 [‐2.01, ‐0.27] |
| 1.21.3 1500 mg or more of calcium intake | 1 | 32 | Mean Difference (IV, Random, 95% CI) | ‐5.70 [‐10.58, ‐0.82] |
| 1.22 Change in diastolic blood pressure by dose Show forest plot | 9 | 2651 | Mean Difference (IV, Random, 95% CI) | ‐1.73 [‐2.79, ‐0.67] |
| 1.22.1 Diary calcium intake less than 1000 mg | 2 | 201 | Mean Difference (IV, Random, 95% CI) | ‐0.41 [‐2.07, 1.25] |
| 1.22.2 Diary calcium intake 1000‐1500 mg | 6 | 947 | Mean Difference (IV, Random, 95% CI) | ‐2.11 [‐3.67, ‐0.56] |
| 1.22.3 Diary calcium intake 1500 mg or more | 2 | 1503 | Mean Difference (IV, Random, 95% CI) | ‐2.15 [‐4.59, 0.29] |
| 1.23 Final value in systolic blood pressure by dose Show forest plot | 11 | 581 | Mean Difference (IV, Random, 95% CI) | ‐1.23 [‐2.85, 0.40] |
| 1.23.1 Less than 1000 mg of calcium intake | 2 | 140 | Mean Difference (IV, Random, 95% CI) | ‐0.11 [‐3.44, 3.21] |
| 1.23.2 1000‐1500 of calcium intake | 3 | 123 | Mean Difference (IV, Random, 95% CI) | 1.05 [‐3.06, 5.16] |
| 1.23.3 1500 mg or more of calcium intake | 6 | 318 | Mean Difference (IV, Random, 95% CI) | ‐2.25 [‐4.34, ‐0.16] |
| 1.24 Final value in diastolic blood pressure by dose Show forest plot | 10 | 480 | Mean Difference (IV, Random, 95% CI) | ‐1.23 [‐2.65, 0.19] |
| 1.24.1 Diary calcium intake less than 1000 mg | 1 | 53 | Mean Difference (IV, Random, 95% CI) | ‐3.50 [‐7.28, 0.28] |
| 1.24.2 Diary calcium intake 1000‐1500 mg | 3 | 109 | Mean Difference (IV, Random, 95% CI) | ‐1.65 [‐5.37, 2.07] |
| 1.24.3 Diary calcium intake 1500 mg or more | 6 | 318 | Mean Difference (IV, Random, 95% CI) | ‐0.82 [‐2.73, 1.10] |
| 1.25 Mean difference in systolic blood pressure by duration Show forest plot | 18 | 3140 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐1.93, ‐0.45] |
| 1.25.1 Less than 6 months | 13 | 766 | Mean Difference (IV, Random, 95% CI) | ‐1.63 [‐2.72, ‐0.53] |
| 1.25.2 6 months or more | 5 | 2374 | Mean Difference (IV, Random, 95% CI) | ‐0.83 [‐1.83, 0.17] |
| 1.26 Mean difference in diastolic blood pressure by duration Show forest plot | 17 | 3039 | Mean Difference (IV, Random, 95% CI) | ‐1.43 [‐2.23, ‐0.63] |
| 1.26.1 Less than 6 months | 12 | 665 | Mean Difference (IV, Random, 95% CI) | ‐2.16 [‐3.34, ‐0.98] |
| 1.26.2 6 months or more | 5 | 2374 | Mean Difference (IV, Random, 95% CI) | ‐0.43 [‐1.03, 0.17] |
| 1.27 Mean difference in systolic blood pressure by intervention type Show forest plot | 18 | 3140 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐1.93, ‐0.45] |
| 1.27.1 Supplementation | 16 | 3001 | Mean Difference (IV, Random, 95% CI) | ‐1.26 [‐2.02, ‐0.50] |
| 1.27.2 Fortification | 2 | 139 | Mean Difference (IV, Random, 95% CI) | 0.09 [‐3.11, 3.29] |
| 1.28 Mean difference in diastolic blood pressure by intervention type Show forest plot | 17 | 3039 | Mean Difference (IV, Random, 95% CI) | ‐1.43 [‐2.23, ‐0.63] |
| 1.28.1 Supplementation | 16 | 3001 | Mean Difference (IV, Random, 95% CI) | ‐1.45 [‐2.27, ‐0.63] |
| 1.28.2 Fortification | 1 | 38 | Mean Difference (IV, Random, 95% CI) | ‐1.00 [‐6.72, 4.72] |
